"ID","ISO","ISO3","Country","Covariate","PathToRaster","Description"
1,643,"RUS","Russia","ppp_2000","GIS/Population/Global_2000_2020/2000/RUS/rus_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2,360,"IDN","Indonesia","ppp_2000","GIS/Population/Global_2000_2020/2000/IDN/idn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3,840,"USA","United States","ppp_2000","GIS/Population/Global_2000_2020/2000/USA/usa_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4,850,"VIR","Virgin_Islands_U_S","ppp_2000","GIS/Population/Global_2000_2020/2000/VIR/vir_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5,304,"GRL","Greenland","ppp_2000","GIS/Population/Global_2000_2020/2000/GRL/grl_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6,156,"CHN","China","ppp_2000","GIS/Population/Global_2000_2020/2000/CHN/chn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7,36,"AUS","Australia","ppp_2000","GIS/Population/Global_2000_2020/2000/AUS/aus_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8,76,"BRA","Brazil","ppp_2000","GIS/Population/Global_2000_2020/2000/BRA/bra_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9,124,"CAN","Canada","ppp_2000","GIS/Population/Global_2000_2020/2000/CAN/can_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10,152,"CHL","Chile","ppp_2000","GIS/Population/Global_2000_2020/2000/CHL/chl_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
11,4,"AFG","Afghanistan","ppp_2000","GIS/Population/Global_2000_2020/2000/AFG/afg_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
12,8,"ALB","Albania","ppp_2000","GIS/Population/Global_2000_2020/2000/ALB/alb_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
13,10,"ATA","Antarctica","ppp_2000","GIS/Population/Global_2000_2020/2000/ATA/ata_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
14,12,"DZA","Algeria","ppp_2000","GIS/Population/Global_2000_2020/2000/DZA/dza_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
15,16,"ASM","American Samoa","ppp_2000","GIS/Population/Global_2000_2020/2000/ASM/asm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
16,20,"AND","Andorra","ppp_2000","GIS/Population/Global_2000_2020/2000/AND/and_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
17,24,"AGO","Angola","ppp_2000","GIS/Population/Global_2000_2020/2000/AGO/ago_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
18,28,"ATG","Antigua and Barbuda","ppp_2000","GIS/Population/Global_2000_2020/2000/ATG/atg_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
19,31,"AZE","Azerbaijan","ppp_2000","GIS/Population/Global_2000_2020/2000/AZE/aze_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
20,32,"ARG","Argentina","ppp_2000","GIS/Population/Global_2000_2020/2000/ARG/arg_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
21,40,"AUT","Austria","ppp_2000","GIS/Population/Global_2000_2020/2000/AUT/aut_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
22,44,"BHS","Bahamas","ppp_2000","GIS/Population/Global_2000_2020/2000/BHS/bhs_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
23,48,"BHR","Bahrain","ppp_2000","GIS/Population/Global_2000_2020/2000/BHR/bhr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
24,50,"BGD","Bangladesh","ppp_2000","GIS/Population/Global_2000_2020/2000/BGD/bgd_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
25,51,"ARM","Armenia","ppp_2000","GIS/Population/Global_2000_2020/2000/ARM/arm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
26,52,"BRB","Barbados","ppp_2000","GIS/Population/Global_2000_2020/2000/BRB/brb_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
27,56,"BEL","Belgium","ppp_2000","GIS/Population/Global_2000_2020/2000/BEL/bel_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
28,60,"BMU","Bermuda","ppp_2000","GIS/Population/Global_2000_2020/2000/BMU/bmu_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
29,64,"BTN","Bhutan","ppp_2000","GIS/Population/Global_2000_2020/2000/BTN/btn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
30,68,"BOL","Bolivia","ppp_2000","GIS/Population/Global_2000_2020/2000/BOL/bol_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
31,70,"BIH","Bosnia and Herzegovina","ppp_2000","GIS/Population/Global_2000_2020/2000/BIH/bih_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
32,72,"BWA","Botswana","ppp_2000","GIS/Population/Global_2000_2020/2000/BWA/bwa_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
33,74,"BVT","Bouvet Island","ppp_2000","GIS/Population/Global_2000_2020/2000/BVT/bvt_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
34,84,"BLZ","Belize","ppp_2000","GIS/Population/Global_2000_2020/2000/BLZ/blz_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
35,86,"IOT","British Indian Ocean Territory","ppp_2000","GIS/Population/Global_2000_2020/2000/IOT/iot_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
36,90,"SLB","Solomon Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/SLB/slb_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
37,92,"VGB","British Virgin Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/VGB/vgb_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
38,96,"BRN","Brunei","ppp_2000","GIS/Population/Global_2000_2020/2000/BRN/brn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
39,100,"BGR","Bulgaria","ppp_2000","GIS/Population/Global_2000_2020/2000/BGR/bgr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
40,104,"MMR","Myanmar","ppp_2000","GIS/Population/Global_2000_2020/2000/MMR/mmr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
41,108,"BDI","Burundi","ppp_2000","GIS/Population/Global_2000_2020/2000/BDI/bdi_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
42,112,"BLR","Belarus","ppp_2000","GIS/Population/Global_2000_2020/2000/BLR/blr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
43,116,"KHM","Cambodia","ppp_2000","GIS/Population/Global_2000_2020/2000/KHM/khm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
44,120,"CMR","Cameroon","ppp_2000","GIS/Population/Global_2000_2020/2000/CMR/cmr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
45,132,"CPV","Cape Verde","ppp_2000","GIS/Population/Global_2000_2020/2000/CPV/cpv_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
46,136,"CYM","Cayman Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/CYM/cym_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
47,140,"CAF","Central African Republic","ppp_2000","GIS/Population/Global_2000_2020/2000/CAF/caf_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
48,144,"LKA","Sri Lanka","ppp_2000","GIS/Population/Global_2000_2020/2000/LKA/lka_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
49,148,"TCD","Chad","ppp_2000","GIS/Population/Global_2000_2020/2000/TCD/tcd_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
50,158,"TWN","Taiwan","ppp_2000","GIS/Population/Global_2000_2020/2000/TWN/twn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
51,170,"COL","Colombia","ppp_2000","GIS/Population/Global_2000_2020/2000/COL/col_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
52,174,"COM","Comoros","ppp_2000","GIS/Population/Global_2000_2020/2000/COM/com_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
53,175,"MYT","Mayotte","ppp_2000","GIS/Population/Global_2000_2020/2000/MYT/myt_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
54,178,"COG","Republic of Congo","ppp_2000","GIS/Population/Global_2000_2020/2000/COG/cog_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
55,180,"COD","Democratic Republic of the Congo","ppp_2000","GIS/Population/Global_2000_2020/2000/COD/cod_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
56,184,"COK","Cook Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/COK/cok_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
57,188,"CRI","Costa Rica","ppp_2000","GIS/Population/Global_2000_2020/2000/CRI/cri_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
58,191,"HRV","Croatia","ppp_2000","GIS/Population/Global_2000_2020/2000/HRV/hrv_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
59,192,"CUB","Cuba","ppp_2000","GIS/Population/Global_2000_2020/2000/CUB/cub_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
60,196,"CYP","Cyprus","ppp_2000","GIS/Population/Global_2000_2020/2000/CYP/cyp_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
61,203,"CZE","Czech Republic","ppp_2000","GIS/Population/Global_2000_2020/2000/CZE/cze_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
62,204,"BEN","Benin","ppp_2000","GIS/Population/Global_2000_2020/2000/BEN/ben_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
63,208,"DNK","Denmark","ppp_2000","GIS/Population/Global_2000_2020/2000/DNK/dnk_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
64,212,"DMA","Dominica","ppp_2000","GIS/Population/Global_2000_2020/2000/DMA/dma_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
65,214,"DOM","Dominican Republic","ppp_2000","GIS/Population/Global_2000_2020/2000/DOM/dom_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
66,218,"ECU","Ecuador","ppp_2000","GIS/Population/Global_2000_2020/2000/ECU/ecu_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
67,222,"SLV","El Salvador","ppp_2000","GIS/Population/Global_2000_2020/2000/SLV/slv_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
68,226,"GNQ","Equatorial Guinea","ppp_2000","GIS/Population/Global_2000_2020/2000/GNQ/gnq_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
69,231,"ETH","Ethiopia","ppp_2000","GIS/Population/Global_2000_2020/2000/ETH/eth_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
70,232,"ERI","Eritrea","ppp_2000","GIS/Population/Global_2000_2020/2000/ERI/eri_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
71,233,"EST","Estonia","ppp_2000","GIS/Population/Global_2000_2020/2000/EST/est_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
72,234,"FRO","Faroe Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/FRO/fro_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
73,238,"FLK","Falkland Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/FLK/flk_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
74,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/SGS/sgs_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
75,242,"FJI","Fiji","ppp_2000","GIS/Population/Global_2000_2020/2000/FJI/fji_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
76,246,"FIN","Finland","ppp_2000","GIS/Population/Global_2000_2020/2000/FIN/fin_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
77,248,"ALA","Aland Islands ","ppp_2000","GIS/Population/Global_2000_2020/2000/ALA/ala_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
78,250,"FRA","France","ppp_2000","GIS/Population/Global_2000_2020/2000/FRA/fra_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
79,254,"GUF","French Guiana","ppp_2000","GIS/Population/Global_2000_2020/2000/GUF/guf_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
80,258,"PYF","French Polynesia","ppp_2000","GIS/Population/Global_2000_2020/2000/PYF/pyf_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
81,260,"ATF","French Southern Territories","ppp_2000","GIS/Population/Global_2000_2020/2000/ATF/atf_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
82,262,"DJI","Djibouti","ppp_2000","GIS/Population/Global_2000_2020/2000/DJI/dji_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
83,266,"GAB","Gabon","ppp_2000","GIS/Population/Global_2000_2020/2000/GAB/gab_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
84,268,"GEO","Georgia","ppp_2000","GIS/Population/Global_2000_2020/2000/GEO/geo_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
85,270,"GMB","Gambia","ppp_2000","GIS/Population/Global_2000_2020/2000/GMB/gmb_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
86,275,"PSE","Palestina","ppp_2000","GIS/Population/Global_2000_2020/2000/PSE/pse_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
87,276,"DEU","Germany","ppp_2000","GIS/Population/Global_2000_2020/2000/DEU/deu_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
88,288,"GHA","Ghana","ppp_2000","GIS/Population/Global_2000_2020/2000/GHA/gha_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
89,292,"GIB","Gibraltar","ppp_2000","GIS/Population/Global_2000_2020/2000/GIB/gib_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
90,296,"KIR","Kiribati","ppp_2000","GIS/Population/Global_2000_2020/2000/KIR/kir_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
91,300,"GRC","Greece","ppp_2000","GIS/Population/Global_2000_2020/2000/GRC/grc_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
92,308,"GRD","Grenada","ppp_2000","GIS/Population/Global_2000_2020/2000/GRD/grd_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
93,312,"GLP","Guadeloupe","ppp_2000","GIS/Population/Global_2000_2020/2000/GLP/glp_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
94,316,"GUM","Guam","ppp_2000","GIS/Population/Global_2000_2020/2000/GUM/gum_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
95,320,"GTM","Guatemala","ppp_2000","GIS/Population/Global_2000_2020/2000/GTM/gtm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
96,324,"GIN","Guinea","ppp_2000","GIS/Population/Global_2000_2020/2000/GIN/gin_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
97,328,"GUY","Guyana","ppp_2000","GIS/Population/Global_2000_2020/2000/GUY/guy_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
98,332,"HTI","Haiti","ppp_2000","GIS/Population/Global_2000_2020/2000/HTI/hti_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
99,334,"HMD","Heard Island and McDonald Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/HMD/hmd_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
100,336,"VAT","Vatican City","ppp_2000","GIS/Population/Global_2000_2020/2000/VAT/vat_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
101,340,"HND","Honduras","ppp_2000","GIS/Population/Global_2000_2020/2000/HND/hnd_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
102,344,"HKG","Hong Kong","ppp_2000","GIS/Population/Global_2000_2020/2000/HKG/hkg_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
103,348,"HUN","Hungary","ppp_2000","GIS/Population/Global_2000_2020/2000/HUN/hun_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
104,352,"ISL","Iceland","ppp_2000","GIS/Population/Global_2000_2020/2000/ISL/isl_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
105,356,"IND","India","ppp_2000","GIS/Population/Global_2000_2020/2000/IND/ind_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
106,364,"IRN","Iran","ppp_2000","GIS/Population/Global_2000_2020/2000/IRN/irn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
107,368,"IRQ","Iraq","ppp_2000","GIS/Population/Global_2000_2020/2000/IRQ/irq_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
108,372,"IRL","Ireland","ppp_2000","GIS/Population/Global_2000_2020/2000/IRL/irl_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
109,376,"ISR","Israel","ppp_2000","GIS/Population/Global_2000_2020/2000/ISR/isr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
110,380,"ITA","Italy","ppp_2000","GIS/Population/Global_2000_2020/2000/ITA/ita_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
111,384,"CIV","CIte dIvoire","ppp_2000","GIS/Population/Global_2000_2020/2000/CIV/civ_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
112,388,"JAM","Jamaica","ppp_2000","GIS/Population/Global_2000_2020/2000/JAM/jam_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
113,392,"JPN","Japan","ppp_2000","GIS/Population/Global_2000_2020/2000/JPN/jpn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
114,398,"KAZ","Kazakhstan","ppp_2000","GIS/Population/Global_2000_2020/2000/KAZ/kaz_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
115,400,"JOR","Jordan","ppp_2000","GIS/Population/Global_2000_2020/2000/JOR/jor_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
116,404,"KEN","Kenya","ppp_2000","GIS/Population/Global_2000_2020/2000/KEN/ken_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
117,408,"PRK","North Korea","ppp_2000","GIS/Population/Global_2000_2020/2000/PRK/prk_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
118,410,"KOR","South Korea","ppp_2000","GIS/Population/Global_2000_2020/2000/KOR/kor_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
119,414,"KWT","Kuwait","ppp_2000","GIS/Population/Global_2000_2020/2000/KWT/kwt_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
120,417,"KGZ","Kyrgyzstan","ppp_2000","GIS/Population/Global_2000_2020/2000/KGZ/kgz_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
121,418,"LAO","Laos","ppp_2000","GIS/Population/Global_2000_2020/2000/LAO/lao_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
122,422,"LBN","Lebanon","ppp_2000","GIS/Population/Global_2000_2020/2000/LBN/lbn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
123,426,"LSO","Lesotho","ppp_2000","GIS/Population/Global_2000_2020/2000/LSO/lso_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
124,428,"LVA","Latvia","ppp_2000","GIS/Population/Global_2000_2020/2000/LVA/lva_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
125,430,"LBR","Liberia","ppp_2000","GIS/Population/Global_2000_2020/2000/LBR/lbr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
126,434,"LBY","Libya","ppp_2000","GIS/Population/Global_2000_2020/2000/LBY/lby_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
127,438,"LIE","Liechtenstein","ppp_2000","GIS/Population/Global_2000_2020/2000/LIE/lie_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
128,440,"LTU","Lithuania","ppp_2000","GIS/Population/Global_2000_2020/2000/LTU/ltu_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
129,442,"LUX","Luxembourg","ppp_2000","GIS/Population/Global_2000_2020/2000/LUX/lux_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
130,446,"MAC","Macao","ppp_2000","GIS/Population/Global_2000_2020/2000/MAC/mac_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
131,450,"MDG","Madagascar","ppp_2000","GIS/Population/Global_2000_2020/2000/MDG/mdg_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
132,454,"MWI","Malawi","ppp_2000","GIS/Population/Global_2000_2020/2000/MWI/mwi_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
133,458,"MYS","Malaysia","ppp_2000","GIS/Population/Global_2000_2020/2000/MYS/mys_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
134,462,"MDV","Maldives","ppp_2000","GIS/Population/Global_2000_2020/2000/MDV/mdv_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
135,466,"MLI","Mali","ppp_2000","GIS/Population/Global_2000_2020/2000/MLI/mli_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
136,470,"MLT","Malta","ppp_2000","GIS/Population/Global_2000_2020/2000/MLT/mlt_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
137,474,"MTQ","Martinique","ppp_2000","GIS/Population/Global_2000_2020/2000/MTQ/mtq_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
138,478,"MRT","Mauritania","ppp_2000","GIS/Population/Global_2000_2020/2000/MRT/mrt_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
139,480,"MUS","Mauritius","ppp_2000","GIS/Population/Global_2000_2020/2000/MUS/mus_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
140,484,"MEX","Mexico","ppp_2000","GIS/Population/Global_2000_2020/2000/MEX/mex_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
141,492,"MCO","Monaco","ppp_2000","GIS/Population/Global_2000_2020/2000/MCO/mco_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
142,496,"MNG","Mongolia","ppp_2000","GIS/Population/Global_2000_2020/2000/MNG/mng_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
143,498,"MDA","Moldova","ppp_2000","GIS/Population/Global_2000_2020/2000/MDA/mda_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
144,499,"MNE","Montenegro","ppp_2000","GIS/Population/Global_2000_2020/2000/MNE/mne_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
145,500,"MSR","Montserrat","ppp_2000","GIS/Population/Global_2000_2020/2000/MSR/msr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
146,504,"MAR","Morocco","ppp_2000","GIS/Population/Global_2000_2020/2000/MAR/mar_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
147,508,"MOZ","Mozambique","ppp_2000","GIS/Population/Global_2000_2020/2000/MOZ/moz_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
148,512,"OMN","Oman","ppp_2000","GIS/Population/Global_2000_2020/2000/OMN/omn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
149,516,"NAM","Namibia","ppp_2000","GIS/Population/Global_2000_2020/2000/NAM/nam_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
150,520,"NRU","Nauru","ppp_2000","GIS/Population/Global_2000_2020/2000/NRU/nru_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
151,524,"NPL","Nepal","ppp_2000","GIS/Population/Global_2000_2020/2000/NPL/npl_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
152,528,"NLD","Netherlands","ppp_2000","GIS/Population/Global_2000_2020/2000/NLD/nld_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
153,531,"CUW","Curacao","ppp_2000","GIS/Population/Global_2000_2020/2000/CUW/cuw_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
154,533,"ABW","Aruba","ppp_2000","GIS/Population/Global_2000_2020/2000/ABW/abw_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
155,534,"SXM","Sint Maarten (Dutch part)","ppp_2000","GIS/Population/Global_2000_2020/2000/SXM/sxm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
156,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2000","GIS/Population/Global_2000_2020/2000/BES/bes_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
157,540,"NCL","New Caledonia","ppp_2000","GIS/Population/Global_2000_2020/2000/NCL/ncl_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
158,548,"VUT","Vanuatu","ppp_2000","GIS/Population/Global_2000_2020/2000/VUT/vut_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
159,554,"NZL","New Zealand","ppp_2000","GIS/Population/Global_2000_2020/2000/NZL/nzl_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
160,558,"NIC","Nicaragua","ppp_2000","GIS/Population/Global_2000_2020/2000/NIC/nic_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
161,562,"NER","Niger","ppp_2000","GIS/Population/Global_2000_2020/2000/NER/ner_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
162,566,"NGA","Nigeria","ppp_2000","GIS/Population/Global_2000_2020/2000/NGA/nga_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
163,570,"NIU","Niue","ppp_2000","GIS/Population/Global_2000_2020/2000/NIU/niu_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
164,574,"NFK","Norfolk Island","ppp_2000","GIS/Population/Global_2000_2020/2000/NFK/nfk_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
165,578,"NOR","Norway","ppp_2000","GIS/Population/Global_2000_2020/2000/NOR/nor_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
166,580,"MNP","Northern Mariana Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/MNP/mnp_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
167,581,"UMI","United States Minor Outlying Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/UMI/umi_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
168,583,"FSM","Micronesia","ppp_2000","GIS/Population/Global_2000_2020/2000/FSM/fsm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
169,584,"MHL","Marshall Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/MHL/mhl_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
170,585,"PLW","Palau","ppp_2000","GIS/Population/Global_2000_2020/2000/PLW/plw_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
171,586,"PAK","Pakistan","ppp_2000","GIS/Population/Global_2000_2020/2000/PAK/pak_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
172,591,"PAN","Panama","ppp_2000","GIS/Population/Global_2000_2020/2000/PAN/pan_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
173,598,"PNG","Papua New Guinea","ppp_2000","GIS/Population/Global_2000_2020/2000/PNG/png_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
174,600,"PRY","Paraguay","ppp_2000","GIS/Population/Global_2000_2020/2000/PRY/pry_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
175,604,"PER","Peru","ppp_2000","GIS/Population/Global_2000_2020/2000/PER/per_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
176,608,"PHL","Philippines","ppp_2000","GIS/Population/Global_2000_2020/2000/PHL/phl_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
177,612,"PCN","Pitcairn Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/PCN/pcn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
178,616,"POL","Poland","ppp_2000","GIS/Population/Global_2000_2020/2000/POL/pol_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
179,620,"PRT","Portugal","ppp_2000","GIS/Population/Global_2000_2020/2000/PRT/prt_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
180,624,"GNB","Guinea-Bissau","ppp_2000","GIS/Population/Global_2000_2020/2000/GNB/gnb_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
181,626,"TLS","East Timor","ppp_2000","GIS/Population/Global_2000_2020/2000/TLS/tls_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
182,630,"PRI","Puerto Rico","ppp_2000","GIS/Population/Global_2000_2020/2000/PRI/pri_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
183,634,"QAT","Qatar","ppp_2000","GIS/Population/Global_2000_2020/2000/QAT/qat_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
184,638,"REU","Reunion","ppp_2000","GIS/Population/Global_2000_2020/2000/REU/reu_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
185,642,"ROU","Romania","ppp_2000","GIS/Population/Global_2000_2020/2000/ROU/rou_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
186,646,"RWA","Rwanda","ppp_2000","GIS/Population/Global_2000_2020/2000/RWA/rwa_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
187,652,"BLM","Saint Barthelemy","ppp_2000","GIS/Population/Global_2000_2020/2000/BLM/blm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
188,654,"SHN","Saint Helena","ppp_2000","GIS/Population/Global_2000_2020/2000/SHN/shn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
189,659,"KNA","Saint Kitts and Nevis","ppp_2000","GIS/Population/Global_2000_2020/2000/KNA/kna_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
190,660,"AIA","Anguilla","ppp_2000","GIS/Population/Global_2000_2020/2000/AIA/aia_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
191,662,"LCA","Saint Lucia","ppp_2000","GIS/Population/Global_2000_2020/2000/LCA/lca_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
192,663,"MAF","Saint Martin (French part)","ppp_2000","GIS/Population/Global_2000_2020/2000/MAF/maf_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
193,666,"SPM","Saint Pierre and Miquelon","ppp_2000","GIS/Population/Global_2000_2020/2000/SPM/spm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
194,670,"VCT","Saint Vincent and the Grenadines","ppp_2000","GIS/Population/Global_2000_2020/2000/VCT/vct_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
195,674,"SMR","San Marino","ppp_2000","GIS/Population/Global_2000_2020/2000/SMR/smr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
196,678,"STP","Sao Tome and Principe","ppp_2000","GIS/Population/Global_2000_2020/2000/STP/stp_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
197,682,"SAU","Saudi Arabia","ppp_2000","GIS/Population/Global_2000_2020/2000/SAU/sau_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
198,686,"SEN","Senegal","ppp_2000","GIS/Population/Global_2000_2020/2000/SEN/sen_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
199,688,"SRB","Serbia","ppp_2000","GIS/Population/Global_2000_2020/2000/SRB/srb_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
200,690,"SYC","Seychelles","ppp_2000","GIS/Population/Global_2000_2020/2000/SYC/syc_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
201,694,"SLE","Sierra Leone","ppp_2000","GIS/Population/Global_2000_2020/2000/SLE/sle_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
202,702,"SGP","Singapore","ppp_2000","GIS/Population/Global_2000_2020/2000/SGP/sgp_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
203,703,"SVK","Slovakia","ppp_2000","GIS/Population/Global_2000_2020/2000/SVK/svk_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
204,704,"VNM","Vietnam","ppp_2000","GIS/Population/Global_2000_2020/2000/VNM/vnm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
205,705,"SVN","Slovenia","ppp_2000","GIS/Population/Global_2000_2020/2000/SVN/svn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
206,706,"SOM","Somalia","ppp_2000","GIS/Population/Global_2000_2020/2000/SOM/som_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
207,710,"ZAF","South Africa","ppp_2000","GIS/Population/Global_2000_2020/2000/ZAF/zaf_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
208,716,"ZWE","Zimbabwe","ppp_2000","GIS/Population/Global_2000_2020/2000/ZWE/zwe_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
209,724,"ESP","Spain","ppp_2000","GIS/Population/Global_2000_2020/2000/ESP/esp_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
210,728,"SSD","South Sudan","ppp_2000","GIS/Population/Global_2000_2020/2000/SSD/ssd_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
211,729,"SDN","Sudan","ppp_2000","GIS/Population/Global_2000_2020/2000/SDN/sdn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
212,732,"ESH","Western Sahara","ppp_2000","GIS/Population/Global_2000_2020/2000/ESH/esh_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
213,740,"SUR","Suriname","ppp_2000","GIS/Population/Global_2000_2020/2000/SUR/sur_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
214,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/SJM/sjm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
215,748,"SWZ","Swaziland","ppp_2000","GIS/Population/Global_2000_2020/2000/SWZ/swz_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
216,752,"SWE","Sweden","ppp_2000","GIS/Population/Global_2000_2020/2000/SWE/swe_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
217,756,"CHE","Switzerland","ppp_2000","GIS/Population/Global_2000_2020/2000/CHE/che_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
218,760,"SYR","Syria","ppp_2000","GIS/Population/Global_2000_2020/2000/SYR/syr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
219,762,"TJK","Tajikistan","ppp_2000","GIS/Population/Global_2000_2020/2000/TJK/tjk_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
220,764,"THA","Thailand","ppp_2000","GIS/Population/Global_2000_2020/2000/THA/tha_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
221,768,"TGO","Togo","ppp_2000","GIS/Population/Global_2000_2020/2000/TGO/tgo_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
222,772,"TKL","Tokelau","ppp_2000","GIS/Population/Global_2000_2020/2000/TKL/tkl_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
223,776,"TON","Tonga","ppp_2000","GIS/Population/Global_2000_2020/2000/TON/ton_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
224,780,"TTO","Trinidad and Tobago","ppp_2000","GIS/Population/Global_2000_2020/2000/TTO/tto_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
225,784,"ARE","United Arab Emirates","ppp_2000","GIS/Population/Global_2000_2020/2000/ARE/are_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
226,788,"TUN","Tunisia","ppp_2000","GIS/Population/Global_2000_2020/2000/TUN/tun_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
227,792,"TUR","Turkey","ppp_2000","GIS/Population/Global_2000_2020/2000/TUR/tur_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
228,795,"TKM","Turkmenistan","ppp_2000","GIS/Population/Global_2000_2020/2000/TKM/tkm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
229,796,"TCA","Turks and Caicos Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/TCA/tca_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
230,798,"TUV","Tuvalu","ppp_2000","GIS/Population/Global_2000_2020/2000/TUV/tuv_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
231,800,"UGA","Uganda","ppp_2000","GIS/Population/Global_2000_2020/2000/UGA/uga_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
232,804,"UKR","Ukraine","ppp_2000","GIS/Population/Global_2000_2020/2000/UKR/ukr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
233,807,"MKD","Macedonia","ppp_2000","GIS/Population/Global_2000_2020/2000/MKD/mkd_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
234,818,"EGY","Egypt","ppp_2000","GIS/Population/Global_2000_2020/2000/EGY/egy_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
235,826,"GBR","United Kingdom","ppp_2000","GIS/Population/Global_2000_2020/2000/GBR/gbr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
236,831,"GGY","Guernsey","ppp_2000","GIS/Population/Global_2000_2020/2000/GGY/ggy_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
237,832,"JEY","Jersey","ppp_2000","GIS/Population/Global_2000_2020/2000/JEY/jey_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
238,833,"IMN","Isle of Man","ppp_2000","GIS/Population/Global_2000_2020/2000/IMN/imn_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
239,834,"TZA","Tanzania","ppp_2000","GIS/Population/Global_2000_2020/2000/TZA/tza_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
240,854,"BFA","Burkina Faso","ppp_2000","GIS/Population/Global_2000_2020/2000/BFA/bfa_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
241,858,"URY","Uruguay","ppp_2000","GIS/Population/Global_2000_2020/2000/URY/ury_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
242,860,"UZB","Uzbekistan","ppp_2000","GIS/Population/Global_2000_2020/2000/UZB/uzb_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
243,862,"VEN","Venezuela","ppp_2000","GIS/Population/Global_2000_2020/2000/VEN/ven_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
244,876,"WLF","Wallis and Futuna","ppp_2000","GIS/Population/Global_2000_2020/2000/WLF/wlf_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
245,882,"WSM","Samoa","ppp_2000","GIS/Population/Global_2000_2020/2000/WSM/wsm_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
246,887,"YEM","Yemen","ppp_2000","GIS/Population/Global_2000_2020/2000/YEM/yem_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
247,894,"ZMB","Zambia","ppp_2000","GIS/Population/Global_2000_2020/2000/ZMB/zmb_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
248,900,"KOS","Kosovo","ppp_2000","GIS/Population/Global_2000_2020/2000/KOS/kos_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
249,901,"SPR","Spratly Islands","ppp_2000","GIS/Population/Global_2000_2020/2000/SPR/spr_ppp_2000.tif","Estimated total number of people per grid-cell 2000 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
250,643,"RUS","Russia","ppp_2001","GIS/Population/Global_2000_2020/2001/RUS/rus_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
251,360,"IDN","Indonesia","ppp_2001","GIS/Population/Global_2000_2020/2001/IDN/idn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
252,840,"USA","United States","ppp_2001","GIS/Population/Global_2000_2020/2001/USA/usa_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
253,850,"VIR","Virgin_Islands_U_S","ppp_2001","GIS/Population/Global_2000_2020/2001/VIR/vir_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
254,304,"GRL","Greenland","ppp_2001","GIS/Population/Global_2000_2020/2001/GRL/grl_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
255,156,"CHN","China","ppp_2001","GIS/Population/Global_2000_2020/2001/CHN/chn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
256,36,"AUS","Australia","ppp_2001","GIS/Population/Global_2000_2020/2001/AUS/aus_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
257,76,"BRA","Brazil","ppp_2001","GIS/Population/Global_2000_2020/2001/BRA/bra_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
258,124,"CAN","Canada","ppp_2001","GIS/Population/Global_2000_2020/2001/CAN/can_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
259,152,"CHL","Chile","ppp_2001","GIS/Population/Global_2000_2020/2001/CHL/chl_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
260,4,"AFG","Afghanistan","ppp_2001","GIS/Population/Global_2000_2020/2001/AFG/afg_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
261,8,"ALB","Albania","ppp_2001","GIS/Population/Global_2000_2020/2001/ALB/alb_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
262,10,"ATA","Antarctica","ppp_2001","GIS/Population/Global_2000_2020/2001/ATA/ata_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
263,12,"DZA","Algeria","ppp_2001","GIS/Population/Global_2000_2020/2001/DZA/dza_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
264,16,"ASM","American Samoa","ppp_2001","GIS/Population/Global_2000_2020/2001/ASM/asm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
265,20,"AND","Andorra","ppp_2001","GIS/Population/Global_2000_2020/2001/AND/and_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
266,24,"AGO","Angola","ppp_2001","GIS/Population/Global_2000_2020/2001/AGO/ago_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
267,28,"ATG","Antigua and Barbuda","ppp_2001","GIS/Population/Global_2000_2020/2001/ATG/atg_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
268,31,"AZE","Azerbaijan","ppp_2001","GIS/Population/Global_2000_2020/2001/AZE/aze_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
269,32,"ARG","Argentina","ppp_2001","GIS/Population/Global_2000_2020/2001/ARG/arg_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
270,40,"AUT","Austria","ppp_2001","GIS/Population/Global_2000_2020/2001/AUT/aut_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
271,44,"BHS","Bahamas","ppp_2001","GIS/Population/Global_2000_2020/2001/BHS/bhs_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
272,48,"BHR","Bahrain","ppp_2001","GIS/Population/Global_2000_2020/2001/BHR/bhr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
273,50,"BGD","Bangladesh","ppp_2001","GIS/Population/Global_2000_2020/2001/BGD/bgd_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
274,51,"ARM","Armenia","ppp_2001","GIS/Population/Global_2000_2020/2001/ARM/arm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
275,52,"BRB","Barbados","ppp_2001","GIS/Population/Global_2000_2020/2001/BRB/brb_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
276,56,"BEL","Belgium","ppp_2001","GIS/Population/Global_2000_2020/2001/BEL/bel_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
277,60,"BMU","Bermuda","ppp_2001","GIS/Population/Global_2000_2020/2001/BMU/bmu_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
278,64,"BTN","Bhutan","ppp_2001","GIS/Population/Global_2000_2020/2001/BTN/btn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
279,68,"BOL","Bolivia","ppp_2001","GIS/Population/Global_2000_2020/2001/BOL/bol_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
280,70,"BIH","Bosnia and Herzegovina","ppp_2001","GIS/Population/Global_2000_2020/2001/BIH/bih_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
281,72,"BWA","Botswana","ppp_2001","GIS/Population/Global_2000_2020/2001/BWA/bwa_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
282,74,"BVT","Bouvet Island","ppp_2001","GIS/Population/Global_2000_2020/2001/BVT/bvt_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
283,84,"BLZ","Belize","ppp_2001","GIS/Population/Global_2000_2020/2001/BLZ/blz_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
284,86,"IOT","British Indian Ocean Territory","ppp_2001","GIS/Population/Global_2000_2020/2001/IOT/iot_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
285,90,"SLB","Solomon Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/SLB/slb_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
286,92,"VGB","British Virgin Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/VGB/vgb_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
287,96,"BRN","Brunei","ppp_2001","GIS/Population/Global_2000_2020/2001/BRN/brn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
288,100,"BGR","Bulgaria","ppp_2001","GIS/Population/Global_2000_2020/2001/BGR/bgr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
289,104,"MMR","Myanmar","ppp_2001","GIS/Population/Global_2000_2020/2001/MMR/mmr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
290,108,"BDI","Burundi","ppp_2001","GIS/Population/Global_2000_2020/2001/BDI/bdi_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
291,112,"BLR","Belarus","ppp_2001","GIS/Population/Global_2000_2020/2001/BLR/blr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
292,116,"KHM","Cambodia","ppp_2001","GIS/Population/Global_2000_2020/2001/KHM/khm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
293,120,"CMR","Cameroon","ppp_2001","GIS/Population/Global_2000_2020/2001/CMR/cmr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
294,132,"CPV","Cape Verde","ppp_2001","GIS/Population/Global_2000_2020/2001/CPV/cpv_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
295,136,"CYM","Cayman Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/CYM/cym_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
296,140,"CAF","Central African Republic","ppp_2001","GIS/Population/Global_2000_2020/2001/CAF/caf_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
297,144,"LKA","Sri Lanka","ppp_2001","GIS/Population/Global_2000_2020/2001/LKA/lka_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
298,148,"TCD","Chad","ppp_2001","GIS/Population/Global_2000_2020/2001/TCD/tcd_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
299,158,"TWN","Taiwan","ppp_2001","GIS/Population/Global_2000_2020/2001/TWN/twn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
300,170,"COL","Colombia","ppp_2001","GIS/Population/Global_2000_2020/2001/COL/col_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
301,174,"COM","Comoros","ppp_2001","GIS/Population/Global_2000_2020/2001/COM/com_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
302,175,"MYT","Mayotte","ppp_2001","GIS/Population/Global_2000_2020/2001/MYT/myt_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
303,178,"COG","Republic of Congo","ppp_2001","GIS/Population/Global_2000_2020/2001/COG/cog_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
304,180,"COD","Democratic Republic of the Congo","ppp_2001","GIS/Population/Global_2000_2020/2001/COD/cod_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
305,184,"COK","Cook Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/COK/cok_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
306,188,"CRI","Costa Rica","ppp_2001","GIS/Population/Global_2000_2020/2001/CRI/cri_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
307,191,"HRV","Croatia","ppp_2001","GIS/Population/Global_2000_2020/2001/HRV/hrv_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
308,192,"CUB","Cuba","ppp_2001","GIS/Population/Global_2000_2020/2001/CUB/cub_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
309,196,"CYP","Cyprus","ppp_2001","GIS/Population/Global_2000_2020/2001/CYP/cyp_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
310,203,"CZE","Czech Republic","ppp_2001","GIS/Population/Global_2000_2020/2001/CZE/cze_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
311,204,"BEN","Benin","ppp_2001","GIS/Population/Global_2000_2020/2001/BEN/ben_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
312,208,"DNK","Denmark","ppp_2001","GIS/Population/Global_2000_2020/2001/DNK/dnk_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
313,212,"DMA","Dominica","ppp_2001","GIS/Population/Global_2000_2020/2001/DMA/dma_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
314,214,"DOM","Dominican Republic","ppp_2001","GIS/Population/Global_2000_2020/2001/DOM/dom_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
315,218,"ECU","Ecuador","ppp_2001","GIS/Population/Global_2000_2020/2001/ECU/ecu_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
316,222,"SLV","El Salvador","ppp_2001","GIS/Population/Global_2000_2020/2001/SLV/slv_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
317,226,"GNQ","Equatorial Guinea","ppp_2001","GIS/Population/Global_2000_2020/2001/GNQ/gnq_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
318,231,"ETH","Ethiopia","ppp_2001","GIS/Population/Global_2000_2020/2001/ETH/eth_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
319,232,"ERI","Eritrea","ppp_2001","GIS/Population/Global_2000_2020/2001/ERI/eri_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
320,233,"EST","Estonia","ppp_2001","GIS/Population/Global_2000_2020/2001/EST/est_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
321,234,"FRO","Faroe Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/FRO/fro_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
322,238,"FLK","Falkland Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/FLK/flk_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
323,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/SGS/sgs_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
324,242,"FJI","Fiji","ppp_2001","GIS/Population/Global_2000_2020/2001/FJI/fji_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
325,246,"FIN","Finland","ppp_2001","GIS/Population/Global_2000_2020/2001/FIN/fin_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
326,248,"ALA","Aland Islands ","ppp_2001","GIS/Population/Global_2000_2020/2001/ALA/ala_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
327,250,"FRA","France","ppp_2001","GIS/Population/Global_2000_2020/2001/FRA/fra_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
328,254,"GUF","French Guiana","ppp_2001","GIS/Population/Global_2000_2020/2001/GUF/guf_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
329,258,"PYF","French Polynesia","ppp_2001","GIS/Population/Global_2000_2020/2001/PYF/pyf_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
330,260,"ATF","French Southern Territories","ppp_2001","GIS/Population/Global_2000_2020/2001/ATF/atf_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
331,262,"DJI","Djibouti","ppp_2001","GIS/Population/Global_2000_2020/2001/DJI/dji_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
332,266,"GAB","Gabon","ppp_2001","GIS/Population/Global_2000_2020/2001/GAB/gab_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
333,268,"GEO","Georgia","ppp_2001","GIS/Population/Global_2000_2020/2001/GEO/geo_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
334,270,"GMB","Gambia","ppp_2001","GIS/Population/Global_2000_2020/2001/GMB/gmb_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
335,275,"PSE","Palestina","ppp_2001","GIS/Population/Global_2000_2020/2001/PSE/pse_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
336,276,"DEU","Germany","ppp_2001","GIS/Population/Global_2000_2020/2001/DEU/deu_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
337,288,"GHA","Ghana","ppp_2001","GIS/Population/Global_2000_2020/2001/GHA/gha_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
338,292,"GIB","Gibraltar","ppp_2001","GIS/Population/Global_2000_2020/2001/GIB/gib_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
339,296,"KIR","Kiribati","ppp_2001","GIS/Population/Global_2000_2020/2001/KIR/kir_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
340,300,"GRC","Greece","ppp_2001","GIS/Population/Global_2000_2020/2001/GRC/grc_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
341,308,"GRD","Grenada","ppp_2001","GIS/Population/Global_2000_2020/2001/GRD/grd_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
342,312,"GLP","Guadeloupe","ppp_2001","GIS/Population/Global_2000_2020/2001/GLP/glp_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
343,316,"GUM","Guam","ppp_2001","GIS/Population/Global_2000_2020/2001/GUM/gum_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
344,320,"GTM","Guatemala","ppp_2001","GIS/Population/Global_2000_2020/2001/GTM/gtm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
345,324,"GIN","Guinea","ppp_2001","GIS/Population/Global_2000_2020/2001/GIN/gin_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
346,328,"GUY","Guyana","ppp_2001","GIS/Population/Global_2000_2020/2001/GUY/guy_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
347,332,"HTI","Haiti","ppp_2001","GIS/Population/Global_2000_2020/2001/HTI/hti_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
348,334,"HMD","Heard Island and McDonald Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/HMD/hmd_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
349,336,"VAT","Vatican City","ppp_2001","GIS/Population/Global_2000_2020/2001/VAT/vat_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
350,340,"HND","Honduras","ppp_2001","GIS/Population/Global_2000_2020/2001/HND/hnd_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
351,344,"HKG","Hong Kong","ppp_2001","GIS/Population/Global_2000_2020/2001/HKG/hkg_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
352,348,"HUN","Hungary","ppp_2001","GIS/Population/Global_2000_2020/2001/HUN/hun_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
353,352,"ISL","Iceland","ppp_2001","GIS/Population/Global_2000_2020/2001/ISL/isl_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
354,356,"IND","India","ppp_2001","GIS/Population/Global_2000_2020/2001/IND/ind_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
355,364,"IRN","Iran","ppp_2001","GIS/Population/Global_2000_2020/2001/IRN/irn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
356,368,"IRQ","Iraq","ppp_2001","GIS/Population/Global_2000_2020/2001/IRQ/irq_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
357,372,"IRL","Ireland","ppp_2001","GIS/Population/Global_2000_2020/2001/IRL/irl_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
358,376,"ISR","Israel","ppp_2001","GIS/Population/Global_2000_2020/2001/ISR/isr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
359,380,"ITA","Italy","ppp_2001","GIS/Population/Global_2000_2020/2001/ITA/ita_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
360,384,"CIV","CIte dIvoire","ppp_2001","GIS/Population/Global_2000_2020/2001/CIV/civ_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
361,388,"JAM","Jamaica","ppp_2001","GIS/Population/Global_2000_2020/2001/JAM/jam_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
362,392,"JPN","Japan","ppp_2001","GIS/Population/Global_2000_2020/2001/JPN/jpn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
363,398,"KAZ","Kazakhstan","ppp_2001","GIS/Population/Global_2000_2020/2001/KAZ/kaz_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
364,400,"JOR","Jordan","ppp_2001","GIS/Population/Global_2000_2020/2001/JOR/jor_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
365,404,"KEN","Kenya","ppp_2001","GIS/Population/Global_2000_2020/2001/KEN/ken_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
366,408,"PRK","North Korea","ppp_2001","GIS/Population/Global_2000_2020/2001/PRK/prk_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
367,410,"KOR","South Korea","ppp_2001","GIS/Population/Global_2000_2020/2001/KOR/kor_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
368,414,"KWT","Kuwait","ppp_2001","GIS/Population/Global_2000_2020/2001/KWT/kwt_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
369,417,"KGZ","Kyrgyzstan","ppp_2001","GIS/Population/Global_2000_2020/2001/KGZ/kgz_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
370,418,"LAO","Laos","ppp_2001","GIS/Population/Global_2000_2020/2001/LAO/lao_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
371,422,"LBN","Lebanon","ppp_2001","GIS/Population/Global_2000_2020/2001/LBN/lbn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
372,426,"LSO","Lesotho","ppp_2001","GIS/Population/Global_2000_2020/2001/LSO/lso_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
373,428,"LVA","Latvia","ppp_2001","GIS/Population/Global_2000_2020/2001/LVA/lva_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
374,430,"LBR","Liberia","ppp_2001","GIS/Population/Global_2000_2020/2001/LBR/lbr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
375,434,"LBY","Libya","ppp_2001","GIS/Population/Global_2000_2020/2001/LBY/lby_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
376,438,"LIE","Liechtenstein","ppp_2001","GIS/Population/Global_2000_2020/2001/LIE/lie_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
377,440,"LTU","Lithuania","ppp_2001","GIS/Population/Global_2000_2020/2001/LTU/ltu_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
378,442,"LUX","Luxembourg","ppp_2001","GIS/Population/Global_2000_2020/2001/LUX/lux_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
379,446,"MAC","Macao","ppp_2001","GIS/Population/Global_2000_2020/2001/MAC/mac_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
380,450,"MDG","Madagascar","ppp_2001","GIS/Population/Global_2000_2020/2001/MDG/mdg_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
381,454,"MWI","Malawi","ppp_2001","GIS/Population/Global_2000_2020/2001/MWI/mwi_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
382,458,"MYS","Malaysia","ppp_2001","GIS/Population/Global_2000_2020/2001/MYS/mys_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
383,462,"MDV","Maldives","ppp_2001","GIS/Population/Global_2000_2020/2001/MDV/mdv_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
384,466,"MLI","Mali","ppp_2001","GIS/Population/Global_2000_2020/2001/MLI/mli_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
385,470,"MLT","Malta","ppp_2001","GIS/Population/Global_2000_2020/2001/MLT/mlt_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
386,474,"MTQ","Martinique","ppp_2001","GIS/Population/Global_2000_2020/2001/MTQ/mtq_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
387,478,"MRT","Mauritania","ppp_2001","GIS/Population/Global_2000_2020/2001/MRT/mrt_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
388,480,"MUS","Mauritius","ppp_2001","GIS/Population/Global_2000_2020/2001/MUS/mus_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
389,484,"MEX","Mexico","ppp_2001","GIS/Population/Global_2000_2020/2001/MEX/mex_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
390,492,"MCO","Monaco","ppp_2001","GIS/Population/Global_2000_2020/2001/MCO/mco_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
391,496,"MNG","Mongolia","ppp_2001","GIS/Population/Global_2000_2020/2001/MNG/mng_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
392,498,"MDA","Moldova","ppp_2001","GIS/Population/Global_2000_2020/2001/MDA/mda_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
393,499,"MNE","Montenegro","ppp_2001","GIS/Population/Global_2000_2020/2001/MNE/mne_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
394,500,"MSR","Montserrat","ppp_2001","GIS/Population/Global_2000_2020/2001/MSR/msr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
395,504,"MAR","Morocco","ppp_2001","GIS/Population/Global_2000_2020/2001/MAR/mar_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
396,508,"MOZ","Mozambique","ppp_2001","GIS/Population/Global_2000_2020/2001/MOZ/moz_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
397,512,"OMN","Oman","ppp_2001","GIS/Population/Global_2000_2020/2001/OMN/omn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
398,516,"NAM","Namibia","ppp_2001","GIS/Population/Global_2000_2020/2001/NAM/nam_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
399,520,"NRU","Nauru","ppp_2001","GIS/Population/Global_2000_2020/2001/NRU/nru_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
400,524,"NPL","Nepal","ppp_2001","GIS/Population/Global_2000_2020/2001/NPL/npl_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
401,528,"NLD","Netherlands","ppp_2001","GIS/Population/Global_2000_2020/2001/NLD/nld_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
402,531,"CUW","Curacao","ppp_2001","GIS/Population/Global_2000_2020/2001/CUW/cuw_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
403,533,"ABW","Aruba","ppp_2001","GIS/Population/Global_2000_2020/2001/ABW/abw_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
404,534,"SXM","Sint Maarten (Dutch part)","ppp_2001","GIS/Population/Global_2000_2020/2001/SXM/sxm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
405,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2001","GIS/Population/Global_2000_2020/2001/BES/bes_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
406,540,"NCL","New Caledonia","ppp_2001","GIS/Population/Global_2000_2020/2001/NCL/ncl_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
407,548,"VUT","Vanuatu","ppp_2001","GIS/Population/Global_2000_2020/2001/VUT/vut_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
408,554,"NZL","New Zealand","ppp_2001","GIS/Population/Global_2000_2020/2001/NZL/nzl_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
409,558,"NIC","Nicaragua","ppp_2001","GIS/Population/Global_2000_2020/2001/NIC/nic_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
410,562,"NER","Niger","ppp_2001","GIS/Population/Global_2000_2020/2001/NER/ner_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
411,566,"NGA","Nigeria","ppp_2001","GIS/Population/Global_2000_2020/2001/NGA/nga_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
412,570,"NIU","Niue","ppp_2001","GIS/Population/Global_2000_2020/2001/NIU/niu_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
413,574,"NFK","Norfolk Island","ppp_2001","GIS/Population/Global_2000_2020/2001/NFK/nfk_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
414,578,"NOR","Norway","ppp_2001","GIS/Population/Global_2000_2020/2001/NOR/nor_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
415,580,"MNP","Northern Mariana Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/MNP/mnp_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
416,581,"UMI","United States Minor Outlying Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/UMI/umi_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
417,583,"FSM","Micronesia","ppp_2001","GIS/Population/Global_2000_2020/2001/FSM/fsm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
418,584,"MHL","Marshall Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/MHL/mhl_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
419,585,"PLW","Palau","ppp_2001","GIS/Population/Global_2000_2020/2001/PLW/plw_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
420,586,"PAK","Pakistan","ppp_2001","GIS/Population/Global_2000_2020/2001/PAK/pak_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
421,591,"PAN","Panama","ppp_2001","GIS/Population/Global_2000_2020/2001/PAN/pan_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
422,598,"PNG","Papua New Guinea","ppp_2001","GIS/Population/Global_2000_2020/2001/PNG/png_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
423,600,"PRY","Paraguay","ppp_2001","GIS/Population/Global_2000_2020/2001/PRY/pry_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
424,604,"PER","Peru","ppp_2001","GIS/Population/Global_2000_2020/2001/PER/per_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
425,608,"PHL","Philippines","ppp_2001","GIS/Population/Global_2000_2020/2001/PHL/phl_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
426,612,"PCN","Pitcairn Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/PCN/pcn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
427,616,"POL","Poland","ppp_2001","GIS/Population/Global_2000_2020/2001/POL/pol_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
428,620,"PRT","Portugal","ppp_2001","GIS/Population/Global_2000_2020/2001/PRT/prt_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
429,624,"GNB","Guinea-Bissau","ppp_2001","GIS/Population/Global_2000_2020/2001/GNB/gnb_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
430,626,"TLS","East Timor","ppp_2001","GIS/Population/Global_2000_2020/2001/TLS/tls_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
431,630,"PRI","Puerto Rico","ppp_2001","GIS/Population/Global_2000_2020/2001/PRI/pri_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
432,634,"QAT","Qatar","ppp_2001","GIS/Population/Global_2000_2020/2001/QAT/qat_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
433,638,"REU","Reunion","ppp_2001","GIS/Population/Global_2000_2020/2001/REU/reu_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
434,642,"ROU","Romania","ppp_2001","GIS/Population/Global_2000_2020/2001/ROU/rou_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
435,646,"RWA","Rwanda","ppp_2001","GIS/Population/Global_2000_2020/2001/RWA/rwa_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
436,652,"BLM","Saint Barthelemy","ppp_2001","GIS/Population/Global_2000_2020/2001/BLM/blm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
437,654,"SHN","Saint Helena","ppp_2001","GIS/Population/Global_2000_2020/2001/SHN/shn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
438,659,"KNA","Saint Kitts and Nevis","ppp_2001","GIS/Population/Global_2000_2020/2001/KNA/kna_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
439,660,"AIA","Anguilla","ppp_2001","GIS/Population/Global_2000_2020/2001/AIA/aia_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
440,662,"LCA","Saint Lucia","ppp_2001","GIS/Population/Global_2000_2020/2001/LCA/lca_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
441,663,"MAF","Saint Martin (French part)","ppp_2001","GIS/Population/Global_2000_2020/2001/MAF/maf_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
442,666,"SPM","Saint Pierre and Miquelon","ppp_2001","GIS/Population/Global_2000_2020/2001/SPM/spm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
443,670,"VCT","Saint Vincent and the Grenadines","ppp_2001","GIS/Population/Global_2000_2020/2001/VCT/vct_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
444,674,"SMR","San Marino","ppp_2001","GIS/Population/Global_2000_2020/2001/SMR/smr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
445,678,"STP","Sao Tome and Principe","ppp_2001","GIS/Population/Global_2000_2020/2001/STP/stp_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
446,682,"SAU","Saudi Arabia","ppp_2001","GIS/Population/Global_2000_2020/2001/SAU/sau_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
447,686,"SEN","Senegal","ppp_2001","GIS/Population/Global_2000_2020/2001/SEN/sen_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
448,688,"SRB","Serbia","ppp_2001","GIS/Population/Global_2000_2020/2001/SRB/srb_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
449,690,"SYC","Seychelles","ppp_2001","GIS/Population/Global_2000_2020/2001/SYC/syc_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
450,694,"SLE","Sierra Leone","ppp_2001","GIS/Population/Global_2000_2020/2001/SLE/sle_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
451,702,"SGP","Singapore","ppp_2001","GIS/Population/Global_2000_2020/2001/SGP/sgp_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
452,703,"SVK","Slovakia","ppp_2001","GIS/Population/Global_2000_2020/2001/SVK/svk_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
453,704,"VNM","Vietnam","ppp_2001","GIS/Population/Global_2000_2020/2001/VNM/vnm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
454,705,"SVN","Slovenia","ppp_2001","GIS/Population/Global_2000_2020/2001/SVN/svn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
455,706,"SOM","Somalia","ppp_2001","GIS/Population/Global_2000_2020/2001/SOM/som_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
456,710,"ZAF","South Africa","ppp_2001","GIS/Population/Global_2000_2020/2001/ZAF/zaf_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
457,716,"ZWE","Zimbabwe","ppp_2001","GIS/Population/Global_2000_2020/2001/ZWE/zwe_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
458,724,"ESP","Spain","ppp_2001","GIS/Population/Global_2000_2020/2001/ESP/esp_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
459,728,"SSD","South Sudan","ppp_2001","GIS/Population/Global_2000_2020/2001/SSD/ssd_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
460,729,"SDN","Sudan","ppp_2001","GIS/Population/Global_2000_2020/2001/SDN/sdn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
461,732,"ESH","Western Sahara","ppp_2001","GIS/Population/Global_2000_2020/2001/ESH/esh_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
462,740,"SUR","Suriname","ppp_2001","GIS/Population/Global_2000_2020/2001/SUR/sur_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
463,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/SJM/sjm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
464,748,"SWZ","Swaziland","ppp_2001","GIS/Population/Global_2000_2020/2001/SWZ/swz_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
465,752,"SWE","Sweden","ppp_2001","GIS/Population/Global_2000_2020/2001/SWE/swe_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
466,756,"CHE","Switzerland","ppp_2001","GIS/Population/Global_2000_2020/2001/CHE/che_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
467,760,"SYR","Syria","ppp_2001","GIS/Population/Global_2000_2020/2001/SYR/syr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
468,762,"TJK","Tajikistan","ppp_2001","GIS/Population/Global_2000_2020/2001/TJK/tjk_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
469,764,"THA","Thailand","ppp_2001","GIS/Population/Global_2000_2020/2001/THA/tha_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
470,768,"TGO","Togo","ppp_2001","GIS/Population/Global_2000_2020/2001/TGO/tgo_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
471,772,"TKL","Tokelau","ppp_2001","GIS/Population/Global_2000_2020/2001/TKL/tkl_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
472,776,"TON","Tonga","ppp_2001","GIS/Population/Global_2000_2020/2001/TON/ton_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
473,780,"TTO","Trinidad and Tobago","ppp_2001","GIS/Population/Global_2000_2020/2001/TTO/tto_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
474,784,"ARE","United Arab Emirates","ppp_2001","GIS/Population/Global_2000_2020/2001/ARE/are_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
475,788,"TUN","Tunisia","ppp_2001","GIS/Population/Global_2000_2020/2001/TUN/tun_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
476,792,"TUR","Turkey","ppp_2001","GIS/Population/Global_2000_2020/2001/TUR/tur_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
477,795,"TKM","Turkmenistan","ppp_2001","GIS/Population/Global_2000_2020/2001/TKM/tkm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
478,796,"TCA","Turks and Caicos Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/TCA/tca_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
479,798,"TUV","Tuvalu","ppp_2001","GIS/Population/Global_2000_2020/2001/TUV/tuv_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
480,800,"UGA","Uganda","ppp_2001","GIS/Population/Global_2000_2020/2001/UGA/uga_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
481,804,"UKR","Ukraine","ppp_2001","GIS/Population/Global_2000_2020/2001/UKR/ukr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
482,807,"MKD","Macedonia","ppp_2001","GIS/Population/Global_2000_2020/2001/MKD/mkd_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
483,818,"EGY","Egypt","ppp_2001","GIS/Population/Global_2000_2020/2001/EGY/egy_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
484,826,"GBR","United Kingdom","ppp_2001","GIS/Population/Global_2000_2020/2001/GBR/gbr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
485,831,"GGY","Guernsey","ppp_2001","GIS/Population/Global_2000_2020/2001/GGY/ggy_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
486,832,"JEY","Jersey","ppp_2001","GIS/Population/Global_2000_2020/2001/JEY/jey_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
487,833,"IMN","Isle of Man","ppp_2001","GIS/Population/Global_2000_2020/2001/IMN/imn_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
488,834,"TZA","Tanzania","ppp_2001","GIS/Population/Global_2000_2020/2001/TZA/tza_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
489,854,"BFA","Burkina Faso","ppp_2001","GIS/Population/Global_2000_2020/2001/BFA/bfa_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
490,858,"URY","Uruguay","ppp_2001","GIS/Population/Global_2000_2020/2001/URY/ury_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
491,860,"UZB","Uzbekistan","ppp_2001","GIS/Population/Global_2000_2020/2001/UZB/uzb_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
492,862,"VEN","Venezuela","ppp_2001","GIS/Population/Global_2000_2020/2001/VEN/ven_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
493,876,"WLF","Wallis and Futuna","ppp_2001","GIS/Population/Global_2000_2020/2001/WLF/wlf_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
494,882,"WSM","Samoa","ppp_2001","GIS/Population/Global_2000_2020/2001/WSM/wsm_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
495,887,"YEM","Yemen","ppp_2001","GIS/Population/Global_2000_2020/2001/YEM/yem_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
496,894,"ZMB","Zambia","ppp_2001","GIS/Population/Global_2000_2020/2001/ZMB/zmb_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
497,900,"KOS","Kosovo","ppp_2001","GIS/Population/Global_2000_2020/2001/KOS/kos_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
498,901,"SPR","Spratly Islands","ppp_2001","GIS/Population/Global_2000_2020/2001/SPR/spr_ppp_2001.tif","Estimated total number of people per grid-cell 2001 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
499,643,"RUS","Russia","ppp_2002","GIS/Population/Global_2000_2020/2002/RUS/rus_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
500,360,"IDN","Indonesia","ppp_2002","GIS/Population/Global_2000_2020/2002/IDN/idn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
501,840,"USA","United States","ppp_2002","GIS/Population/Global_2000_2020/2002/USA/usa_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
502,850,"VIR","Virgin_Islands_U_S","ppp_2002","GIS/Population/Global_2000_2020/2002/VIR/vir_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
503,304,"GRL","Greenland","ppp_2002","GIS/Population/Global_2000_2020/2002/GRL/grl_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
504,156,"CHN","China","ppp_2002","GIS/Population/Global_2000_2020/2002/CHN/chn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
505,36,"AUS","Australia","ppp_2002","GIS/Population/Global_2000_2020/2002/AUS/aus_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
506,76,"BRA","Brazil","ppp_2002","GIS/Population/Global_2000_2020/2002/BRA/bra_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
507,124,"CAN","Canada","ppp_2002","GIS/Population/Global_2000_2020/2002/CAN/can_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
508,152,"CHL","Chile","ppp_2002","GIS/Population/Global_2000_2020/2002/CHL/chl_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
509,4,"AFG","Afghanistan","ppp_2002","GIS/Population/Global_2000_2020/2002/AFG/afg_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
510,8,"ALB","Albania","ppp_2002","GIS/Population/Global_2000_2020/2002/ALB/alb_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
511,10,"ATA","Antarctica","ppp_2002","GIS/Population/Global_2000_2020/2002/ATA/ata_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
512,12,"DZA","Algeria","ppp_2002","GIS/Population/Global_2000_2020/2002/DZA/dza_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
513,16,"ASM","American Samoa","ppp_2002","GIS/Population/Global_2000_2020/2002/ASM/asm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
514,20,"AND","Andorra","ppp_2002","GIS/Population/Global_2000_2020/2002/AND/and_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
515,24,"AGO","Angola","ppp_2002","GIS/Population/Global_2000_2020/2002/AGO/ago_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
516,28,"ATG","Antigua and Barbuda","ppp_2002","GIS/Population/Global_2000_2020/2002/ATG/atg_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
517,31,"AZE","Azerbaijan","ppp_2002","GIS/Population/Global_2000_2020/2002/AZE/aze_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
518,32,"ARG","Argentina","ppp_2002","GIS/Population/Global_2000_2020/2002/ARG/arg_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
519,40,"AUT","Austria","ppp_2002","GIS/Population/Global_2000_2020/2002/AUT/aut_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
520,44,"BHS","Bahamas","ppp_2002","GIS/Population/Global_2000_2020/2002/BHS/bhs_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
521,48,"BHR","Bahrain","ppp_2002","GIS/Population/Global_2000_2020/2002/BHR/bhr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
522,50,"BGD","Bangladesh","ppp_2002","GIS/Population/Global_2000_2020/2002/BGD/bgd_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
523,51,"ARM","Armenia","ppp_2002","GIS/Population/Global_2000_2020/2002/ARM/arm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
524,52,"BRB","Barbados","ppp_2002","GIS/Population/Global_2000_2020/2002/BRB/brb_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
525,56,"BEL","Belgium","ppp_2002","GIS/Population/Global_2000_2020/2002/BEL/bel_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
526,60,"BMU","Bermuda","ppp_2002","GIS/Population/Global_2000_2020/2002/BMU/bmu_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
527,64,"BTN","Bhutan","ppp_2002","GIS/Population/Global_2000_2020/2002/BTN/btn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
528,68,"BOL","Bolivia","ppp_2002","GIS/Population/Global_2000_2020/2002/BOL/bol_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
529,70,"BIH","Bosnia and Herzegovina","ppp_2002","GIS/Population/Global_2000_2020/2002/BIH/bih_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
530,72,"BWA","Botswana","ppp_2002","GIS/Population/Global_2000_2020/2002/BWA/bwa_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
531,74,"BVT","Bouvet Island","ppp_2002","GIS/Population/Global_2000_2020/2002/BVT/bvt_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
532,84,"BLZ","Belize","ppp_2002","GIS/Population/Global_2000_2020/2002/BLZ/blz_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
533,86,"IOT","British Indian Ocean Territory","ppp_2002","GIS/Population/Global_2000_2020/2002/IOT/iot_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
534,90,"SLB","Solomon Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/SLB/slb_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
535,92,"VGB","British Virgin Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/VGB/vgb_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
536,96,"BRN","Brunei","ppp_2002","GIS/Population/Global_2000_2020/2002/BRN/brn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
537,100,"BGR","Bulgaria","ppp_2002","GIS/Population/Global_2000_2020/2002/BGR/bgr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
538,104,"MMR","Myanmar","ppp_2002","GIS/Population/Global_2000_2020/2002/MMR/mmr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
539,108,"BDI","Burundi","ppp_2002","GIS/Population/Global_2000_2020/2002/BDI/bdi_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
540,112,"BLR","Belarus","ppp_2002","GIS/Population/Global_2000_2020/2002/BLR/blr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
541,116,"KHM","Cambodia","ppp_2002","GIS/Population/Global_2000_2020/2002/KHM/khm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
542,120,"CMR","Cameroon","ppp_2002","GIS/Population/Global_2000_2020/2002/CMR/cmr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
543,132,"CPV","Cape Verde","ppp_2002","GIS/Population/Global_2000_2020/2002/CPV/cpv_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
544,136,"CYM","Cayman Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/CYM/cym_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
545,140,"CAF","Central African Republic","ppp_2002","GIS/Population/Global_2000_2020/2002/CAF/caf_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
546,144,"LKA","Sri Lanka","ppp_2002","GIS/Population/Global_2000_2020/2002/LKA/lka_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
547,148,"TCD","Chad","ppp_2002","GIS/Population/Global_2000_2020/2002/TCD/tcd_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
548,158,"TWN","Taiwan","ppp_2002","GIS/Population/Global_2000_2020/2002/TWN/twn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
549,170,"COL","Colombia","ppp_2002","GIS/Population/Global_2000_2020/2002/COL/col_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
550,174,"COM","Comoros","ppp_2002","GIS/Population/Global_2000_2020/2002/COM/com_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
551,175,"MYT","Mayotte","ppp_2002","GIS/Population/Global_2000_2020/2002/MYT/myt_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
552,178,"COG","Republic of Congo","ppp_2002","GIS/Population/Global_2000_2020/2002/COG/cog_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
553,180,"COD","Democratic Republic of the Congo","ppp_2002","GIS/Population/Global_2000_2020/2002/COD/cod_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
554,184,"COK","Cook Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/COK/cok_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
555,188,"CRI","Costa Rica","ppp_2002","GIS/Population/Global_2000_2020/2002/CRI/cri_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
556,191,"HRV","Croatia","ppp_2002","GIS/Population/Global_2000_2020/2002/HRV/hrv_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
557,192,"CUB","Cuba","ppp_2002","GIS/Population/Global_2000_2020/2002/CUB/cub_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
558,196,"CYP","Cyprus","ppp_2002","GIS/Population/Global_2000_2020/2002/CYP/cyp_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
559,203,"CZE","Czech Republic","ppp_2002","GIS/Population/Global_2000_2020/2002/CZE/cze_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
560,204,"BEN","Benin","ppp_2002","GIS/Population/Global_2000_2020/2002/BEN/ben_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
561,208,"DNK","Denmark","ppp_2002","GIS/Population/Global_2000_2020/2002/DNK/dnk_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
562,212,"DMA","Dominica","ppp_2002","GIS/Population/Global_2000_2020/2002/DMA/dma_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
563,214,"DOM","Dominican Republic","ppp_2002","GIS/Population/Global_2000_2020/2002/DOM/dom_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
564,218,"ECU","Ecuador","ppp_2002","GIS/Population/Global_2000_2020/2002/ECU/ecu_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
565,222,"SLV","El Salvador","ppp_2002","GIS/Population/Global_2000_2020/2002/SLV/slv_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
566,226,"GNQ","Equatorial Guinea","ppp_2002","GIS/Population/Global_2000_2020/2002/GNQ/gnq_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
567,231,"ETH","Ethiopia","ppp_2002","GIS/Population/Global_2000_2020/2002/ETH/eth_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
568,232,"ERI","Eritrea","ppp_2002","GIS/Population/Global_2000_2020/2002/ERI/eri_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
569,233,"EST","Estonia","ppp_2002","GIS/Population/Global_2000_2020/2002/EST/est_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
570,234,"FRO","Faroe Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/FRO/fro_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
571,238,"FLK","Falkland Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/FLK/flk_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
572,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/SGS/sgs_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
573,242,"FJI","Fiji","ppp_2002","GIS/Population/Global_2000_2020/2002/FJI/fji_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
574,246,"FIN","Finland","ppp_2002","GIS/Population/Global_2000_2020/2002/FIN/fin_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
575,248,"ALA","Aland Islands ","ppp_2002","GIS/Population/Global_2000_2020/2002/ALA/ala_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
576,250,"FRA","France","ppp_2002","GIS/Population/Global_2000_2020/2002/FRA/fra_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
577,254,"GUF","French Guiana","ppp_2002","GIS/Population/Global_2000_2020/2002/GUF/guf_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
578,258,"PYF","French Polynesia","ppp_2002","GIS/Population/Global_2000_2020/2002/PYF/pyf_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
579,260,"ATF","French Southern Territories","ppp_2002","GIS/Population/Global_2000_2020/2002/ATF/atf_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
580,262,"DJI","Djibouti","ppp_2002","GIS/Population/Global_2000_2020/2002/DJI/dji_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
581,266,"GAB","Gabon","ppp_2002","GIS/Population/Global_2000_2020/2002/GAB/gab_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
582,268,"GEO","Georgia","ppp_2002","GIS/Population/Global_2000_2020/2002/GEO/geo_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
583,270,"GMB","Gambia","ppp_2002","GIS/Population/Global_2000_2020/2002/GMB/gmb_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
584,275,"PSE","Palestina","ppp_2002","GIS/Population/Global_2000_2020/2002/PSE/pse_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
585,276,"DEU","Germany","ppp_2002","GIS/Population/Global_2000_2020/2002/DEU/deu_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
586,288,"GHA","Ghana","ppp_2002","GIS/Population/Global_2000_2020/2002/GHA/gha_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
587,292,"GIB","Gibraltar","ppp_2002","GIS/Population/Global_2000_2020/2002/GIB/gib_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
588,296,"KIR","Kiribati","ppp_2002","GIS/Population/Global_2000_2020/2002/KIR/kir_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
589,300,"GRC","Greece","ppp_2002","GIS/Population/Global_2000_2020/2002/GRC/grc_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
590,308,"GRD","Grenada","ppp_2002","GIS/Population/Global_2000_2020/2002/GRD/grd_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
591,312,"GLP","Guadeloupe","ppp_2002","GIS/Population/Global_2000_2020/2002/GLP/glp_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
592,316,"GUM","Guam","ppp_2002","GIS/Population/Global_2000_2020/2002/GUM/gum_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
593,320,"GTM","Guatemala","ppp_2002","GIS/Population/Global_2000_2020/2002/GTM/gtm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
594,324,"GIN","Guinea","ppp_2002","GIS/Population/Global_2000_2020/2002/GIN/gin_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
595,328,"GUY","Guyana","ppp_2002","GIS/Population/Global_2000_2020/2002/GUY/guy_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
596,332,"HTI","Haiti","ppp_2002","GIS/Population/Global_2000_2020/2002/HTI/hti_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
597,334,"HMD","Heard Island and McDonald Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/HMD/hmd_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
598,336,"VAT","Vatican City","ppp_2002","GIS/Population/Global_2000_2020/2002/VAT/vat_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
599,340,"HND","Honduras","ppp_2002","GIS/Population/Global_2000_2020/2002/HND/hnd_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
600,344,"HKG","Hong Kong","ppp_2002","GIS/Population/Global_2000_2020/2002/HKG/hkg_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
601,348,"HUN","Hungary","ppp_2002","GIS/Population/Global_2000_2020/2002/HUN/hun_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
602,352,"ISL","Iceland","ppp_2002","GIS/Population/Global_2000_2020/2002/ISL/isl_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
603,356,"IND","India","ppp_2002","GIS/Population/Global_2000_2020/2002/IND/ind_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
604,364,"IRN","Iran","ppp_2002","GIS/Population/Global_2000_2020/2002/IRN/irn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
605,368,"IRQ","Iraq","ppp_2002","GIS/Population/Global_2000_2020/2002/IRQ/irq_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
606,372,"IRL","Ireland","ppp_2002","GIS/Population/Global_2000_2020/2002/IRL/irl_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
607,376,"ISR","Israel","ppp_2002","GIS/Population/Global_2000_2020/2002/ISR/isr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
608,380,"ITA","Italy","ppp_2002","GIS/Population/Global_2000_2020/2002/ITA/ita_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
609,384,"CIV","CIte dIvoire","ppp_2002","GIS/Population/Global_2000_2020/2002/CIV/civ_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
610,388,"JAM","Jamaica","ppp_2002","GIS/Population/Global_2000_2020/2002/JAM/jam_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
611,392,"JPN","Japan","ppp_2002","GIS/Population/Global_2000_2020/2002/JPN/jpn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
612,398,"KAZ","Kazakhstan","ppp_2002","GIS/Population/Global_2000_2020/2002/KAZ/kaz_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
613,400,"JOR","Jordan","ppp_2002","GIS/Population/Global_2000_2020/2002/JOR/jor_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
614,404,"KEN","Kenya","ppp_2002","GIS/Population/Global_2000_2020/2002/KEN/ken_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
615,408,"PRK","North Korea","ppp_2002","GIS/Population/Global_2000_2020/2002/PRK/prk_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
616,410,"KOR","South Korea","ppp_2002","GIS/Population/Global_2000_2020/2002/KOR/kor_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
617,414,"KWT","Kuwait","ppp_2002","GIS/Population/Global_2000_2020/2002/KWT/kwt_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
618,417,"KGZ","Kyrgyzstan","ppp_2002","GIS/Population/Global_2000_2020/2002/KGZ/kgz_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
619,418,"LAO","Laos","ppp_2002","GIS/Population/Global_2000_2020/2002/LAO/lao_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
620,422,"LBN","Lebanon","ppp_2002","GIS/Population/Global_2000_2020/2002/LBN/lbn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
621,426,"LSO","Lesotho","ppp_2002","GIS/Population/Global_2000_2020/2002/LSO/lso_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
622,428,"LVA","Latvia","ppp_2002","GIS/Population/Global_2000_2020/2002/LVA/lva_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
623,430,"LBR","Liberia","ppp_2002","GIS/Population/Global_2000_2020/2002/LBR/lbr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
624,434,"LBY","Libya","ppp_2002","GIS/Population/Global_2000_2020/2002/LBY/lby_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
625,438,"LIE","Liechtenstein","ppp_2002","GIS/Population/Global_2000_2020/2002/LIE/lie_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
626,440,"LTU","Lithuania","ppp_2002","GIS/Population/Global_2000_2020/2002/LTU/ltu_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
627,442,"LUX","Luxembourg","ppp_2002","GIS/Population/Global_2000_2020/2002/LUX/lux_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
628,446,"MAC","Macao","ppp_2002","GIS/Population/Global_2000_2020/2002/MAC/mac_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
629,450,"MDG","Madagascar","ppp_2002","GIS/Population/Global_2000_2020/2002/MDG/mdg_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
630,454,"MWI","Malawi","ppp_2002","GIS/Population/Global_2000_2020/2002/MWI/mwi_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
631,458,"MYS","Malaysia","ppp_2002","GIS/Population/Global_2000_2020/2002/MYS/mys_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
632,462,"MDV","Maldives","ppp_2002","GIS/Population/Global_2000_2020/2002/MDV/mdv_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
633,466,"MLI","Mali","ppp_2002","GIS/Population/Global_2000_2020/2002/MLI/mli_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
634,470,"MLT","Malta","ppp_2002","GIS/Population/Global_2000_2020/2002/MLT/mlt_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
635,474,"MTQ","Martinique","ppp_2002","GIS/Population/Global_2000_2020/2002/MTQ/mtq_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
636,478,"MRT","Mauritania","ppp_2002","GIS/Population/Global_2000_2020/2002/MRT/mrt_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
637,480,"MUS","Mauritius","ppp_2002","GIS/Population/Global_2000_2020/2002/MUS/mus_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
638,484,"MEX","Mexico","ppp_2002","GIS/Population/Global_2000_2020/2002/MEX/mex_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
639,492,"MCO","Monaco","ppp_2002","GIS/Population/Global_2000_2020/2002/MCO/mco_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
640,496,"MNG","Mongolia","ppp_2002","GIS/Population/Global_2000_2020/2002/MNG/mng_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
641,498,"MDA","Moldova","ppp_2002","GIS/Population/Global_2000_2020/2002/MDA/mda_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
642,499,"MNE","Montenegro","ppp_2002","GIS/Population/Global_2000_2020/2002/MNE/mne_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
643,500,"MSR","Montserrat","ppp_2002","GIS/Population/Global_2000_2020/2002/MSR/msr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
644,504,"MAR","Morocco","ppp_2002","GIS/Population/Global_2000_2020/2002/MAR/mar_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
645,508,"MOZ","Mozambique","ppp_2002","GIS/Population/Global_2000_2020/2002/MOZ/moz_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
646,512,"OMN","Oman","ppp_2002","GIS/Population/Global_2000_2020/2002/OMN/omn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
647,516,"NAM","Namibia","ppp_2002","GIS/Population/Global_2000_2020/2002/NAM/nam_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
648,520,"NRU","Nauru","ppp_2002","GIS/Population/Global_2000_2020/2002/NRU/nru_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
649,524,"NPL","Nepal","ppp_2002","GIS/Population/Global_2000_2020/2002/NPL/npl_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
650,528,"NLD","Netherlands","ppp_2002","GIS/Population/Global_2000_2020/2002/NLD/nld_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
651,531,"CUW","Curacao","ppp_2002","GIS/Population/Global_2000_2020/2002/CUW/cuw_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
652,533,"ABW","Aruba","ppp_2002","GIS/Population/Global_2000_2020/2002/ABW/abw_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
653,534,"SXM","Sint Maarten (Dutch part)","ppp_2002","GIS/Population/Global_2000_2020/2002/SXM/sxm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
654,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2002","GIS/Population/Global_2000_2020/2002/BES/bes_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
655,540,"NCL","New Caledonia","ppp_2002","GIS/Population/Global_2000_2020/2002/NCL/ncl_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
656,548,"VUT","Vanuatu","ppp_2002","GIS/Population/Global_2000_2020/2002/VUT/vut_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
657,554,"NZL","New Zealand","ppp_2002","GIS/Population/Global_2000_2020/2002/NZL/nzl_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
658,558,"NIC","Nicaragua","ppp_2002","GIS/Population/Global_2000_2020/2002/NIC/nic_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
659,562,"NER","Niger","ppp_2002","GIS/Population/Global_2000_2020/2002/NER/ner_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
660,566,"NGA","Nigeria","ppp_2002","GIS/Population/Global_2000_2020/2002/NGA/nga_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
661,570,"NIU","Niue","ppp_2002","GIS/Population/Global_2000_2020/2002/NIU/niu_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
662,574,"NFK","Norfolk Island","ppp_2002","GIS/Population/Global_2000_2020/2002/NFK/nfk_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
663,578,"NOR","Norway","ppp_2002","GIS/Population/Global_2000_2020/2002/NOR/nor_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
664,580,"MNP","Northern Mariana Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/MNP/mnp_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
665,581,"UMI","United States Minor Outlying Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/UMI/umi_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
666,583,"FSM","Micronesia","ppp_2002","GIS/Population/Global_2000_2020/2002/FSM/fsm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
667,584,"MHL","Marshall Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/MHL/mhl_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
668,585,"PLW","Palau","ppp_2002","GIS/Population/Global_2000_2020/2002/PLW/plw_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
669,586,"PAK","Pakistan","ppp_2002","GIS/Population/Global_2000_2020/2002/PAK/pak_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
670,591,"PAN","Panama","ppp_2002","GIS/Population/Global_2000_2020/2002/PAN/pan_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
671,598,"PNG","Papua New Guinea","ppp_2002","GIS/Population/Global_2000_2020/2002/PNG/png_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
672,600,"PRY","Paraguay","ppp_2002","GIS/Population/Global_2000_2020/2002/PRY/pry_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
673,604,"PER","Peru","ppp_2002","GIS/Population/Global_2000_2020/2002/PER/per_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
674,608,"PHL","Philippines","ppp_2002","GIS/Population/Global_2000_2020/2002/PHL/phl_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
675,612,"PCN","Pitcairn Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/PCN/pcn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
676,616,"POL","Poland","ppp_2002","GIS/Population/Global_2000_2020/2002/POL/pol_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
677,620,"PRT","Portugal","ppp_2002","GIS/Population/Global_2000_2020/2002/PRT/prt_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
678,624,"GNB","Guinea-Bissau","ppp_2002","GIS/Population/Global_2000_2020/2002/GNB/gnb_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
679,626,"TLS","East Timor","ppp_2002","GIS/Population/Global_2000_2020/2002/TLS/tls_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
680,630,"PRI","Puerto Rico","ppp_2002","GIS/Population/Global_2000_2020/2002/PRI/pri_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
681,634,"QAT","Qatar","ppp_2002","GIS/Population/Global_2000_2020/2002/QAT/qat_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
682,638,"REU","Reunion","ppp_2002","GIS/Population/Global_2000_2020/2002/REU/reu_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
683,642,"ROU","Romania","ppp_2002","GIS/Population/Global_2000_2020/2002/ROU/rou_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
684,646,"RWA","Rwanda","ppp_2002","GIS/Population/Global_2000_2020/2002/RWA/rwa_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
685,652,"BLM","Saint Barthelemy","ppp_2002","GIS/Population/Global_2000_2020/2002/BLM/blm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
686,654,"SHN","Saint Helena","ppp_2002","GIS/Population/Global_2000_2020/2002/SHN/shn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
687,659,"KNA","Saint Kitts and Nevis","ppp_2002","GIS/Population/Global_2000_2020/2002/KNA/kna_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
688,660,"AIA","Anguilla","ppp_2002","GIS/Population/Global_2000_2020/2002/AIA/aia_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
689,662,"LCA","Saint Lucia","ppp_2002","GIS/Population/Global_2000_2020/2002/LCA/lca_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
690,663,"MAF","Saint Martin (French part)","ppp_2002","GIS/Population/Global_2000_2020/2002/MAF/maf_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
691,666,"SPM","Saint Pierre and Miquelon","ppp_2002","GIS/Population/Global_2000_2020/2002/SPM/spm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
692,670,"VCT","Saint Vincent and the Grenadines","ppp_2002","GIS/Population/Global_2000_2020/2002/VCT/vct_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
693,674,"SMR","San Marino","ppp_2002","GIS/Population/Global_2000_2020/2002/SMR/smr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
694,678,"STP","Sao Tome and Principe","ppp_2002","GIS/Population/Global_2000_2020/2002/STP/stp_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
695,682,"SAU","Saudi Arabia","ppp_2002","GIS/Population/Global_2000_2020/2002/SAU/sau_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
696,686,"SEN","Senegal","ppp_2002","GIS/Population/Global_2000_2020/2002/SEN/sen_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
697,688,"SRB","Serbia","ppp_2002","GIS/Population/Global_2000_2020/2002/SRB/srb_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
698,690,"SYC","Seychelles","ppp_2002","GIS/Population/Global_2000_2020/2002/SYC/syc_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
699,694,"SLE","Sierra Leone","ppp_2002","GIS/Population/Global_2000_2020/2002/SLE/sle_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
700,702,"SGP","Singapore","ppp_2002","GIS/Population/Global_2000_2020/2002/SGP/sgp_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
701,703,"SVK","Slovakia","ppp_2002","GIS/Population/Global_2000_2020/2002/SVK/svk_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
702,704,"VNM","Vietnam","ppp_2002","GIS/Population/Global_2000_2020/2002/VNM/vnm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
703,705,"SVN","Slovenia","ppp_2002","GIS/Population/Global_2000_2020/2002/SVN/svn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
704,706,"SOM","Somalia","ppp_2002","GIS/Population/Global_2000_2020/2002/SOM/som_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
705,710,"ZAF","South Africa","ppp_2002","GIS/Population/Global_2000_2020/2002/ZAF/zaf_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
706,716,"ZWE","Zimbabwe","ppp_2002","GIS/Population/Global_2000_2020/2002/ZWE/zwe_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
707,724,"ESP","Spain","ppp_2002","GIS/Population/Global_2000_2020/2002/ESP/esp_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
708,728,"SSD","South Sudan","ppp_2002","GIS/Population/Global_2000_2020/2002/SSD/ssd_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
709,729,"SDN","Sudan","ppp_2002","GIS/Population/Global_2000_2020/2002/SDN/sdn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
710,732,"ESH","Western Sahara","ppp_2002","GIS/Population/Global_2000_2020/2002/ESH/esh_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
711,740,"SUR","Suriname","ppp_2002","GIS/Population/Global_2000_2020/2002/SUR/sur_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
712,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/SJM/sjm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
713,748,"SWZ","Swaziland","ppp_2002","GIS/Population/Global_2000_2020/2002/SWZ/swz_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
714,752,"SWE","Sweden","ppp_2002","GIS/Population/Global_2000_2020/2002/SWE/swe_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
715,756,"CHE","Switzerland","ppp_2002","GIS/Population/Global_2000_2020/2002/CHE/che_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
716,760,"SYR","Syria","ppp_2002","GIS/Population/Global_2000_2020/2002/SYR/syr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
717,762,"TJK","Tajikistan","ppp_2002","GIS/Population/Global_2000_2020/2002/TJK/tjk_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
718,764,"THA","Thailand","ppp_2002","GIS/Population/Global_2000_2020/2002/THA/tha_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
719,768,"TGO","Togo","ppp_2002","GIS/Population/Global_2000_2020/2002/TGO/tgo_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
720,772,"TKL","Tokelau","ppp_2002","GIS/Population/Global_2000_2020/2002/TKL/tkl_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
721,776,"TON","Tonga","ppp_2002","GIS/Population/Global_2000_2020/2002/TON/ton_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
722,780,"TTO","Trinidad and Tobago","ppp_2002","GIS/Population/Global_2000_2020/2002/TTO/tto_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
723,784,"ARE","United Arab Emirates","ppp_2002","GIS/Population/Global_2000_2020/2002/ARE/are_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
724,788,"TUN","Tunisia","ppp_2002","GIS/Population/Global_2000_2020/2002/TUN/tun_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
725,792,"TUR","Turkey","ppp_2002","GIS/Population/Global_2000_2020/2002/TUR/tur_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
726,795,"TKM","Turkmenistan","ppp_2002","GIS/Population/Global_2000_2020/2002/TKM/tkm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
727,796,"TCA","Turks and Caicos Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/TCA/tca_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
728,798,"TUV","Tuvalu","ppp_2002","GIS/Population/Global_2000_2020/2002/TUV/tuv_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
729,800,"UGA","Uganda","ppp_2002","GIS/Population/Global_2000_2020/2002/UGA/uga_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
730,804,"UKR","Ukraine","ppp_2002","GIS/Population/Global_2000_2020/2002/UKR/ukr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
731,807,"MKD","Macedonia","ppp_2002","GIS/Population/Global_2000_2020/2002/MKD/mkd_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
732,818,"EGY","Egypt","ppp_2002","GIS/Population/Global_2000_2020/2002/EGY/egy_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
733,826,"GBR","United Kingdom","ppp_2002","GIS/Population/Global_2000_2020/2002/GBR/gbr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
734,831,"GGY","Guernsey","ppp_2002","GIS/Population/Global_2000_2020/2002/GGY/ggy_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
735,832,"JEY","Jersey","ppp_2002","GIS/Population/Global_2000_2020/2002/JEY/jey_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
736,833,"IMN","Isle of Man","ppp_2002","GIS/Population/Global_2000_2020/2002/IMN/imn_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
737,834,"TZA","Tanzania","ppp_2002","GIS/Population/Global_2000_2020/2002/TZA/tza_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
738,854,"BFA","Burkina Faso","ppp_2002","GIS/Population/Global_2000_2020/2002/BFA/bfa_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
739,858,"URY","Uruguay","ppp_2002","GIS/Population/Global_2000_2020/2002/URY/ury_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
740,860,"UZB","Uzbekistan","ppp_2002","GIS/Population/Global_2000_2020/2002/UZB/uzb_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
741,862,"VEN","Venezuela","ppp_2002","GIS/Population/Global_2000_2020/2002/VEN/ven_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
742,876,"WLF","Wallis and Futuna","ppp_2002","GIS/Population/Global_2000_2020/2002/WLF/wlf_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
743,882,"WSM","Samoa","ppp_2002","GIS/Population/Global_2000_2020/2002/WSM/wsm_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
744,887,"YEM","Yemen","ppp_2002","GIS/Population/Global_2000_2020/2002/YEM/yem_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
745,894,"ZMB","Zambia","ppp_2002","GIS/Population/Global_2000_2020/2002/ZMB/zmb_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
746,900,"KOS","Kosovo","ppp_2002","GIS/Population/Global_2000_2020/2002/KOS/kos_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
747,901,"SPR","Spratly Islands","ppp_2002","GIS/Population/Global_2000_2020/2002/SPR/spr_ppp_2002.tif","Estimated total number of people per grid-cell 2002 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
748,643,"RUS","Russia","ppp_2003","GIS/Population/Global_2000_2020/2003/RUS/rus_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
749,360,"IDN","Indonesia","ppp_2003","GIS/Population/Global_2000_2020/2003/IDN/idn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
750,840,"USA","United States","ppp_2003","GIS/Population/Global_2000_2020/2003/USA/usa_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
751,850,"VIR","Virgin_Islands_U_S","ppp_2003","GIS/Population/Global_2000_2020/2003/VIR/vir_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
752,304,"GRL","Greenland","ppp_2003","GIS/Population/Global_2000_2020/2003/GRL/grl_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
753,156,"CHN","China","ppp_2003","GIS/Population/Global_2000_2020/2003/CHN/chn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
754,36,"AUS","Australia","ppp_2003","GIS/Population/Global_2000_2020/2003/AUS/aus_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
755,76,"BRA","Brazil","ppp_2003","GIS/Population/Global_2000_2020/2003/BRA/bra_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
756,124,"CAN","Canada","ppp_2003","GIS/Population/Global_2000_2020/2003/CAN/can_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
757,152,"CHL","Chile","ppp_2003","GIS/Population/Global_2000_2020/2003/CHL/chl_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
758,4,"AFG","Afghanistan","ppp_2003","GIS/Population/Global_2000_2020/2003/AFG/afg_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
759,8,"ALB","Albania","ppp_2003","GIS/Population/Global_2000_2020/2003/ALB/alb_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
760,10,"ATA","Antarctica","ppp_2003","GIS/Population/Global_2000_2020/2003/ATA/ata_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
761,12,"DZA","Algeria","ppp_2003","GIS/Population/Global_2000_2020/2003/DZA/dza_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
762,16,"ASM","American Samoa","ppp_2003","GIS/Population/Global_2000_2020/2003/ASM/asm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
763,20,"AND","Andorra","ppp_2003","GIS/Population/Global_2000_2020/2003/AND/and_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
764,24,"AGO","Angola","ppp_2003","GIS/Population/Global_2000_2020/2003/AGO/ago_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
765,28,"ATG","Antigua and Barbuda","ppp_2003","GIS/Population/Global_2000_2020/2003/ATG/atg_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
766,31,"AZE","Azerbaijan","ppp_2003","GIS/Population/Global_2000_2020/2003/AZE/aze_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
767,32,"ARG","Argentina","ppp_2003","GIS/Population/Global_2000_2020/2003/ARG/arg_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
768,40,"AUT","Austria","ppp_2003","GIS/Population/Global_2000_2020/2003/AUT/aut_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
769,44,"BHS","Bahamas","ppp_2003","GIS/Population/Global_2000_2020/2003/BHS/bhs_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
770,48,"BHR","Bahrain","ppp_2003","GIS/Population/Global_2000_2020/2003/BHR/bhr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
771,50,"BGD","Bangladesh","ppp_2003","GIS/Population/Global_2000_2020/2003/BGD/bgd_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
772,51,"ARM","Armenia","ppp_2003","GIS/Population/Global_2000_2020/2003/ARM/arm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
773,52,"BRB","Barbados","ppp_2003","GIS/Population/Global_2000_2020/2003/BRB/brb_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
774,56,"BEL","Belgium","ppp_2003","GIS/Population/Global_2000_2020/2003/BEL/bel_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
775,60,"BMU","Bermuda","ppp_2003","GIS/Population/Global_2000_2020/2003/BMU/bmu_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
776,64,"BTN","Bhutan","ppp_2003","GIS/Population/Global_2000_2020/2003/BTN/btn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
777,68,"BOL","Bolivia","ppp_2003","GIS/Population/Global_2000_2020/2003/BOL/bol_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
778,70,"BIH","Bosnia and Herzegovina","ppp_2003","GIS/Population/Global_2000_2020/2003/BIH/bih_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
779,72,"BWA","Botswana","ppp_2003","GIS/Population/Global_2000_2020/2003/BWA/bwa_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
780,74,"BVT","Bouvet Island","ppp_2003","GIS/Population/Global_2000_2020/2003/BVT/bvt_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
781,84,"BLZ","Belize","ppp_2003","GIS/Population/Global_2000_2020/2003/BLZ/blz_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
782,86,"IOT","British Indian Ocean Territory","ppp_2003","GIS/Population/Global_2000_2020/2003/IOT/iot_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
783,90,"SLB","Solomon Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/SLB/slb_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
784,92,"VGB","British Virgin Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/VGB/vgb_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
785,96,"BRN","Brunei","ppp_2003","GIS/Population/Global_2000_2020/2003/BRN/brn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
786,100,"BGR","Bulgaria","ppp_2003","GIS/Population/Global_2000_2020/2003/BGR/bgr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
787,104,"MMR","Myanmar","ppp_2003","GIS/Population/Global_2000_2020/2003/MMR/mmr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
788,108,"BDI","Burundi","ppp_2003","GIS/Population/Global_2000_2020/2003/BDI/bdi_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
789,112,"BLR","Belarus","ppp_2003","GIS/Population/Global_2000_2020/2003/BLR/blr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
790,116,"KHM","Cambodia","ppp_2003","GIS/Population/Global_2000_2020/2003/KHM/khm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
791,120,"CMR","Cameroon","ppp_2003","GIS/Population/Global_2000_2020/2003/CMR/cmr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
792,132,"CPV","Cape Verde","ppp_2003","GIS/Population/Global_2000_2020/2003/CPV/cpv_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
793,136,"CYM","Cayman Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/CYM/cym_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
794,140,"CAF","Central African Republic","ppp_2003","GIS/Population/Global_2000_2020/2003/CAF/caf_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
795,144,"LKA","Sri Lanka","ppp_2003","GIS/Population/Global_2000_2020/2003/LKA/lka_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
796,148,"TCD","Chad","ppp_2003","GIS/Population/Global_2000_2020/2003/TCD/tcd_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
797,158,"TWN","Taiwan","ppp_2003","GIS/Population/Global_2000_2020/2003/TWN/twn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
798,170,"COL","Colombia","ppp_2003","GIS/Population/Global_2000_2020/2003/COL/col_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
799,174,"COM","Comoros","ppp_2003","GIS/Population/Global_2000_2020/2003/COM/com_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
800,175,"MYT","Mayotte","ppp_2003","GIS/Population/Global_2000_2020/2003/MYT/myt_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
801,178,"COG","Republic of Congo","ppp_2003","GIS/Population/Global_2000_2020/2003/COG/cog_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
802,180,"COD","Democratic Republic of the Congo","ppp_2003","GIS/Population/Global_2000_2020/2003/COD/cod_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
803,184,"COK","Cook Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/COK/cok_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
804,188,"CRI","Costa Rica","ppp_2003","GIS/Population/Global_2000_2020/2003/CRI/cri_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
805,191,"HRV","Croatia","ppp_2003","GIS/Population/Global_2000_2020/2003/HRV/hrv_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
806,192,"CUB","Cuba","ppp_2003","GIS/Population/Global_2000_2020/2003/CUB/cub_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
807,196,"CYP","Cyprus","ppp_2003","GIS/Population/Global_2000_2020/2003/CYP/cyp_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
808,203,"CZE","Czech Republic","ppp_2003","GIS/Population/Global_2000_2020/2003/CZE/cze_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
809,204,"BEN","Benin","ppp_2003","GIS/Population/Global_2000_2020/2003/BEN/ben_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
810,208,"DNK","Denmark","ppp_2003","GIS/Population/Global_2000_2020/2003/DNK/dnk_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
811,212,"DMA","Dominica","ppp_2003","GIS/Population/Global_2000_2020/2003/DMA/dma_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
812,214,"DOM","Dominican Republic","ppp_2003","GIS/Population/Global_2000_2020/2003/DOM/dom_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
813,218,"ECU","Ecuador","ppp_2003","GIS/Population/Global_2000_2020/2003/ECU/ecu_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
814,222,"SLV","El Salvador","ppp_2003","GIS/Population/Global_2000_2020/2003/SLV/slv_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
815,226,"GNQ","Equatorial Guinea","ppp_2003","GIS/Population/Global_2000_2020/2003/GNQ/gnq_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
816,231,"ETH","Ethiopia","ppp_2003","GIS/Population/Global_2000_2020/2003/ETH/eth_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
817,232,"ERI","Eritrea","ppp_2003","GIS/Population/Global_2000_2020/2003/ERI/eri_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
818,233,"EST","Estonia","ppp_2003","GIS/Population/Global_2000_2020/2003/EST/est_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
819,234,"FRO","Faroe Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/FRO/fro_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
820,238,"FLK","Falkland Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/FLK/flk_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
821,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/SGS/sgs_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
822,242,"FJI","Fiji","ppp_2003","GIS/Population/Global_2000_2020/2003/FJI/fji_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
823,246,"FIN","Finland","ppp_2003","GIS/Population/Global_2000_2020/2003/FIN/fin_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
824,248,"ALA","Aland Islands ","ppp_2003","GIS/Population/Global_2000_2020/2003/ALA/ala_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
825,250,"FRA","France","ppp_2003","GIS/Population/Global_2000_2020/2003/FRA/fra_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
826,254,"GUF","French Guiana","ppp_2003","GIS/Population/Global_2000_2020/2003/GUF/guf_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
827,258,"PYF","French Polynesia","ppp_2003","GIS/Population/Global_2000_2020/2003/PYF/pyf_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
828,260,"ATF","French Southern Territories","ppp_2003","GIS/Population/Global_2000_2020/2003/ATF/atf_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
829,262,"DJI","Djibouti","ppp_2003","GIS/Population/Global_2000_2020/2003/DJI/dji_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
830,266,"GAB","Gabon","ppp_2003","GIS/Population/Global_2000_2020/2003/GAB/gab_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
831,268,"GEO","Georgia","ppp_2003","GIS/Population/Global_2000_2020/2003/GEO/geo_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
832,270,"GMB","Gambia","ppp_2003","GIS/Population/Global_2000_2020/2003/GMB/gmb_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
833,275,"PSE","Palestina","ppp_2003","GIS/Population/Global_2000_2020/2003/PSE/pse_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
834,276,"DEU","Germany","ppp_2003","GIS/Population/Global_2000_2020/2003/DEU/deu_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
835,288,"GHA","Ghana","ppp_2003","GIS/Population/Global_2000_2020/2003/GHA/gha_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
836,292,"GIB","Gibraltar","ppp_2003","GIS/Population/Global_2000_2020/2003/GIB/gib_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
837,296,"KIR","Kiribati","ppp_2003","GIS/Population/Global_2000_2020/2003/KIR/kir_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
838,300,"GRC","Greece","ppp_2003","GIS/Population/Global_2000_2020/2003/GRC/grc_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
839,308,"GRD","Grenada","ppp_2003","GIS/Population/Global_2000_2020/2003/GRD/grd_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
840,312,"GLP","Guadeloupe","ppp_2003","GIS/Population/Global_2000_2020/2003/GLP/glp_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
841,316,"GUM","Guam","ppp_2003","GIS/Population/Global_2000_2020/2003/GUM/gum_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
842,320,"GTM","Guatemala","ppp_2003","GIS/Population/Global_2000_2020/2003/GTM/gtm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
843,324,"GIN","Guinea","ppp_2003","GIS/Population/Global_2000_2020/2003/GIN/gin_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
844,328,"GUY","Guyana","ppp_2003","GIS/Population/Global_2000_2020/2003/GUY/guy_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
845,332,"HTI","Haiti","ppp_2003","GIS/Population/Global_2000_2020/2003/HTI/hti_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
846,334,"HMD","Heard Island and McDonald Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/HMD/hmd_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
847,336,"VAT","Vatican City","ppp_2003","GIS/Population/Global_2000_2020/2003/VAT/vat_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
848,340,"HND","Honduras","ppp_2003","GIS/Population/Global_2000_2020/2003/HND/hnd_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
849,344,"HKG","Hong Kong","ppp_2003","GIS/Population/Global_2000_2020/2003/HKG/hkg_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
850,348,"HUN","Hungary","ppp_2003","GIS/Population/Global_2000_2020/2003/HUN/hun_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
851,352,"ISL","Iceland","ppp_2003","GIS/Population/Global_2000_2020/2003/ISL/isl_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
852,356,"IND","India","ppp_2003","GIS/Population/Global_2000_2020/2003/IND/ind_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
853,364,"IRN","Iran","ppp_2003","GIS/Population/Global_2000_2020/2003/IRN/irn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
854,368,"IRQ","Iraq","ppp_2003","GIS/Population/Global_2000_2020/2003/IRQ/irq_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
855,372,"IRL","Ireland","ppp_2003","GIS/Population/Global_2000_2020/2003/IRL/irl_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
856,376,"ISR","Israel","ppp_2003","GIS/Population/Global_2000_2020/2003/ISR/isr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
857,380,"ITA","Italy","ppp_2003","GIS/Population/Global_2000_2020/2003/ITA/ita_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
858,384,"CIV","CIte dIvoire","ppp_2003","GIS/Population/Global_2000_2020/2003/CIV/civ_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
859,388,"JAM","Jamaica","ppp_2003","GIS/Population/Global_2000_2020/2003/JAM/jam_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
860,392,"JPN","Japan","ppp_2003","GIS/Population/Global_2000_2020/2003/JPN/jpn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
861,398,"KAZ","Kazakhstan","ppp_2003","GIS/Population/Global_2000_2020/2003/KAZ/kaz_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
862,400,"JOR","Jordan","ppp_2003","GIS/Population/Global_2000_2020/2003/JOR/jor_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
863,404,"KEN","Kenya","ppp_2003","GIS/Population/Global_2000_2020/2003/KEN/ken_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
864,408,"PRK","North Korea","ppp_2003","GIS/Population/Global_2000_2020/2003/PRK/prk_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
865,410,"KOR","South Korea","ppp_2003","GIS/Population/Global_2000_2020/2003/KOR/kor_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
866,414,"KWT","Kuwait","ppp_2003","GIS/Population/Global_2000_2020/2003/KWT/kwt_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
867,417,"KGZ","Kyrgyzstan","ppp_2003","GIS/Population/Global_2000_2020/2003/KGZ/kgz_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
868,418,"LAO","Laos","ppp_2003","GIS/Population/Global_2000_2020/2003/LAO/lao_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
869,422,"LBN","Lebanon","ppp_2003","GIS/Population/Global_2000_2020/2003/LBN/lbn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
870,426,"LSO","Lesotho","ppp_2003","GIS/Population/Global_2000_2020/2003/LSO/lso_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
871,428,"LVA","Latvia","ppp_2003","GIS/Population/Global_2000_2020/2003/LVA/lva_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
872,430,"LBR","Liberia","ppp_2003","GIS/Population/Global_2000_2020/2003/LBR/lbr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
873,434,"LBY","Libya","ppp_2003","GIS/Population/Global_2000_2020/2003/LBY/lby_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
874,438,"LIE","Liechtenstein","ppp_2003","GIS/Population/Global_2000_2020/2003/LIE/lie_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
875,440,"LTU","Lithuania","ppp_2003","GIS/Population/Global_2000_2020/2003/LTU/ltu_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
876,442,"LUX","Luxembourg","ppp_2003","GIS/Population/Global_2000_2020/2003/LUX/lux_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
877,446,"MAC","Macao","ppp_2003","GIS/Population/Global_2000_2020/2003/MAC/mac_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
878,450,"MDG","Madagascar","ppp_2003","GIS/Population/Global_2000_2020/2003/MDG/mdg_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
879,454,"MWI","Malawi","ppp_2003","GIS/Population/Global_2000_2020/2003/MWI/mwi_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
880,458,"MYS","Malaysia","ppp_2003","GIS/Population/Global_2000_2020/2003/MYS/mys_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
881,462,"MDV","Maldives","ppp_2003","GIS/Population/Global_2000_2020/2003/MDV/mdv_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
882,466,"MLI","Mali","ppp_2003","GIS/Population/Global_2000_2020/2003/MLI/mli_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
883,470,"MLT","Malta","ppp_2003","GIS/Population/Global_2000_2020/2003/MLT/mlt_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
884,474,"MTQ","Martinique","ppp_2003","GIS/Population/Global_2000_2020/2003/MTQ/mtq_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
885,478,"MRT","Mauritania","ppp_2003","GIS/Population/Global_2000_2020/2003/MRT/mrt_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
886,480,"MUS","Mauritius","ppp_2003","GIS/Population/Global_2000_2020/2003/MUS/mus_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
887,484,"MEX","Mexico","ppp_2003","GIS/Population/Global_2000_2020/2003/MEX/mex_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
888,492,"MCO","Monaco","ppp_2003","GIS/Population/Global_2000_2020/2003/MCO/mco_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
889,496,"MNG","Mongolia","ppp_2003","GIS/Population/Global_2000_2020/2003/MNG/mng_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
890,498,"MDA","Moldova","ppp_2003","GIS/Population/Global_2000_2020/2003/MDA/mda_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
891,499,"MNE","Montenegro","ppp_2003","GIS/Population/Global_2000_2020/2003/MNE/mne_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
892,500,"MSR","Montserrat","ppp_2003","GIS/Population/Global_2000_2020/2003/MSR/msr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
893,504,"MAR","Morocco","ppp_2003","GIS/Population/Global_2000_2020/2003/MAR/mar_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
894,508,"MOZ","Mozambique","ppp_2003","GIS/Population/Global_2000_2020/2003/MOZ/moz_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
895,512,"OMN","Oman","ppp_2003","GIS/Population/Global_2000_2020/2003/OMN/omn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
896,516,"NAM","Namibia","ppp_2003","GIS/Population/Global_2000_2020/2003/NAM/nam_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
897,520,"NRU","Nauru","ppp_2003","GIS/Population/Global_2000_2020/2003/NRU/nru_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
898,524,"NPL","Nepal","ppp_2003","GIS/Population/Global_2000_2020/2003/NPL/npl_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
899,528,"NLD","Netherlands","ppp_2003","GIS/Population/Global_2000_2020/2003/NLD/nld_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
900,531,"CUW","Curacao","ppp_2003","GIS/Population/Global_2000_2020/2003/CUW/cuw_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
901,533,"ABW","Aruba","ppp_2003","GIS/Population/Global_2000_2020/2003/ABW/abw_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
902,534,"SXM","Sint Maarten (Dutch part)","ppp_2003","GIS/Population/Global_2000_2020/2003/SXM/sxm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
903,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2003","GIS/Population/Global_2000_2020/2003/BES/bes_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
904,540,"NCL","New Caledonia","ppp_2003","GIS/Population/Global_2000_2020/2003/NCL/ncl_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
905,548,"VUT","Vanuatu","ppp_2003","GIS/Population/Global_2000_2020/2003/VUT/vut_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
906,554,"NZL","New Zealand","ppp_2003","GIS/Population/Global_2000_2020/2003/NZL/nzl_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
907,558,"NIC","Nicaragua","ppp_2003","GIS/Population/Global_2000_2020/2003/NIC/nic_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
908,562,"NER","Niger","ppp_2003","GIS/Population/Global_2000_2020/2003/NER/ner_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
909,566,"NGA","Nigeria","ppp_2003","GIS/Population/Global_2000_2020/2003/NGA/nga_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
910,570,"NIU","Niue","ppp_2003","GIS/Population/Global_2000_2020/2003/NIU/niu_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
911,574,"NFK","Norfolk Island","ppp_2003","GIS/Population/Global_2000_2020/2003/NFK/nfk_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
912,578,"NOR","Norway","ppp_2003","GIS/Population/Global_2000_2020/2003/NOR/nor_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
913,580,"MNP","Northern Mariana Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/MNP/mnp_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
914,581,"UMI","United States Minor Outlying Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/UMI/umi_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
915,583,"FSM","Micronesia","ppp_2003","GIS/Population/Global_2000_2020/2003/FSM/fsm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
916,584,"MHL","Marshall Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/MHL/mhl_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
917,585,"PLW","Palau","ppp_2003","GIS/Population/Global_2000_2020/2003/PLW/plw_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
918,586,"PAK","Pakistan","ppp_2003","GIS/Population/Global_2000_2020/2003/PAK/pak_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
919,591,"PAN","Panama","ppp_2003","GIS/Population/Global_2000_2020/2003/PAN/pan_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
920,598,"PNG","Papua New Guinea","ppp_2003","GIS/Population/Global_2000_2020/2003/PNG/png_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
921,600,"PRY","Paraguay","ppp_2003","GIS/Population/Global_2000_2020/2003/PRY/pry_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
922,604,"PER","Peru","ppp_2003","GIS/Population/Global_2000_2020/2003/PER/per_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
923,608,"PHL","Philippines","ppp_2003","GIS/Population/Global_2000_2020/2003/PHL/phl_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
924,612,"PCN","Pitcairn Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/PCN/pcn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
925,616,"POL","Poland","ppp_2003","GIS/Population/Global_2000_2020/2003/POL/pol_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
926,620,"PRT","Portugal","ppp_2003","GIS/Population/Global_2000_2020/2003/PRT/prt_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
927,624,"GNB","Guinea-Bissau","ppp_2003","GIS/Population/Global_2000_2020/2003/GNB/gnb_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
928,626,"TLS","East Timor","ppp_2003","GIS/Population/Global_2000_2020/2003/TLS/tls_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
929,630,"PRI","Puerto Rico","ppp_2003","GIS/Population/Global_2000_2020/2003/PRI/pri_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
930,634,"QAT","Qatar","ppp_2003","GIS/Population/Global_2000_2020/2003/QAT/qat_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
931,638,"REU","Reunion","ppp_2003","GIS/Population/Global_2000_2020/2003/REU/reu_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
932,642,"ROU","Romania","ppp_2003","GIS/Population/Global_2000_2020/2003/ROU/rou_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
933,646,"RWA","Rwanda","ppp_2003","GIS/Population/Global_2000_2020/2003/RWA/rwa_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
934,652,"BLM","Saint Barthelemy","ppp_2003","GIS/Population/Global_2000_2020/2003/BLM/blm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
935,654,"SHN","Saint Helena","ppp_2003","GIS/Population/Global_2000_2020/2003/SHN/shn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
936,659,"KNA","Saint Kitts and Nevis","ppp_2003","GIS/Population/Global_2000_2020/2003/KNA/kna_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
937,660,"AIA","Anguilla","ppp_2003","GIS/Population/Global_2000_2020/2003/AIA/aia_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
938,662,"LCA","Saint Lucia","ppp_2003","GIS/Population/Global_2000_2020/2003/LCA/lca_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
939,663,"MAF","Saint Martin (French part)","ppp_2003","GIS/Population/Global_2000_2020/2003/MAF/maf_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
940,666,"SPM","Saint Pierre and Miquelon","ppp_2003","GIS/Population/Global_2000_2020/2003/SPM/spm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
941,670,"VCT","Saint Vincent and the Grenadines","ppp_2003","GIS/Population/Global_2000_2020/2003/VCT/vct_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
942,674,"SMR","San Marino","ppp_2003","GIS/Population/Global_2000_2020/2003/SMR/smr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
943,678,"STP","Sao Tome and Principe","ppp_2003","GIS/Population/Global_2000_2020/2003/STP/stp_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
944,682,"SAU","Saudi Arabia","ppp_2003","GIS/Population/Global_2000_2020/2003/SAU/sau_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
945,686,"SEN","Senegal","ppp_2003","GIS/Population/Global_2000_2020/2003/SEN/sen_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
946,688,"SRB","Serbia","ppp_2003","GIS/Population/Global_2000_2020/2003/SRB/srb_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
947,690,"SYC","Seychelles","ppp_2003","GIS/Population/Global_2000_2020/2003/SYC/syc_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
948,694,"SLE","Sierra Leone","ppp_2003","GIS/Population/Global_2000_2020/2003/SLE/sle_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
949,702,"SGP","Singapore","ppp_2003","GIS/Population/Global_2000_2020/2003/SGP/sgp_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
950,703,"SVK","Slovakia","ppp_2003","GIS/Population/Global_2000_2020/2003/SVK/svk_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
951,704,"VNM","Vietnam","ppp_2003","GIS/Population/Global_2000_2020/2003/VNM/vnm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
952,705,"SVN","Slovenia","ppp_2003","GIS/Population/Global_2000_2020/2003/SVN/svn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
953,706,"SOM","Somalia","ppp_2003","GIS/Population/Global_2000_2020/2003/SOM/som_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
954,710,"ZAF","South Africa","ppp_2003","GIS/Population/Global_2000_2020/2003/ZAF/zaf_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
955,716,"ZWE","Zimbabwe","ppp_2003","GIS/Population/Global_2000_2020/2003/ZWE/zwe_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
956,724,"ESP","Spain","ppp_2003","GIS/Population/Global_2000_2020/2003/ESP/esp_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
957,728,"SSD","South Sudan","ppp_2003","GIS/Population/Global_2000_2020/2003/SSD/ssd_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
958,729,"SDN","Sudan","ppp_2003","GIS/Population/Global_2000_2020/2003/SDN/sdn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
959,732,"ESH","Western Sahara","ppp_2003","GIS/Population/Global_2000_2020/2003/ESH/esh_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
960,740,"SUR","Suriname","ppp_2003","GIS/Population/Global_2000_2020/2003/SUR/sur_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
961,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/SJM/sjm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
962,748,"SWZ","Swaziland","ppp_2003","GIS/Population/Global_2000_2020/2003/SWZ/swz_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
963,752,"SWE","Sweden","ppp_2003","GIS/Population/Global_2000_2020/2003/SWE/swe_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
964,756,"CHE","Switzerland","ppp_2003","GIS/Population/Global_2000_2020/2003/CHE/che_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
965,760,"SYR","Syria","ppp_2003","GIS/Population/Global_2000_2020/2003/SYR/syr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
966,762,"TJK","Tajikistan","ppp_2003","GIS/Population/Global_2000_2020/2003/TJK/tjk_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
967,764,"THA","Thailand","ppp_2003","GIS/Population/Global_2000_2020/2003/THA/tha_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
968,768,"TGO","Togo","ppp_2003","GIS/Population/Global_2000_2020/2003/TGO/tgo_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
969,772,"TKL","Tokelau","ppp_2003","GIS/Population/Global_2000_2020/2003/TKL/tkl_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
970,776,"TON","Tonga","ppp_2003","GIS/Population/Global_2000_2020/2003/TON/ton_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
971,780,"TTO","Trinidad and Tobago","ppp_2003","GIS/Population/Global_2000_2020/2003/TTO/tto_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
972,784,"ARE","United Arab Emirates","ppp_2003","GIS/Population/Global_2000_2020/2003/ARE/are_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
973,788,"TUN","Tunisia","ppp_2003","GIS/Population/Global_2000_2020/2003/TUN/tun_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
974,792,"TUR","Turkey","ppp_2003","GIS/Population/Global_2000_2020/2003/TUR/tur_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
975,795,"TKM","Turkmenistan","ppp_2003","GIS/Population/Global_2000_2020/2003/TKM/tkm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
976,796,"TCA","Turks and Caicos Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/TCA/tca_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
977,798,"TUV","Tuvalu","ppp_2003","GIS/Population/Global_2000_2020/2003/TUV/tuv_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
978,800,"UGA","Uganda","ppp_2003","GIS/Population/Global_2000_2020/2003/UGA/uga_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
979,804,"UKR","Ukraine","ppp_2003","GIS/Population/Global_2000_2020/2003/UKR/ukr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
980,807,"MKD","Macedonia","ppp_2003","GIS/Population/Global_2000_2020/2003/MKD/mkd_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
981,818,"EGY","Egypt","ppp_2003","GIS/Population/Global_2000_2020/2003/EGY/egy_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
982,826,"GBR","United Kingdom","ppp_2003","GIS/Population/Global_2000_2020/2003/GBR/gbr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
983,831,"GGY","Guernsey","ppp_2003","GIS/Population/Global_2000_2020/2003/GGY/ggy_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
984,832,"JEY","Jersey","ppp_2003","GIS/Population/Global_2000_2020/2003/JEY/jey_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
985,833,"IMN","Isle of Man","ppp_2003","GIS/Population/Global_2000_2020/2003/IMN/imn_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
986,834,"TZA","Tanzania","ppp_2003","GIS/Population/Global_2000_2020/2003/TZA/tza_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
987,854,"BFA","Burkina Faso","ppp_2003","GIS/Population/Global_2000_2020/2003/BFA/bfa_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
988,858,"URY","Uruguay","ppp_2003","GIS/Population/Global_2000_2020/2003/URY/ury_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
989,860,"UZB","Uzbekistan","ppp_2003","GIS/Population/Global_2000_2020/2003/UZB/uzb_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
990,862,"VEN","Venezuela","ppp_2003","GIS/Population/Global_2000_2020/2003/VEN/ven_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
991,876,"WLF","Wallis and Futuna","ppp_2003","GIS/Population/Global_2000_2020/2003/WLF/wlf_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
992,882,"WSM","Samoa","ppp_2003","GIS/Population/Global_2000_2020/2003/WSM/wsm_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
993,887,"YEM","Yemen","ppp_2003","GIS/Population/Global_2000_2020/2003/YEM/yem_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
994,894,"ZMB","Zambia","ppp_2003","GIS/Population/Global_2000_2020/2003/ZMB/zmb_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
995,900,"KOS","Kosovo","ppp_2003","GIS/Population/Global_2000_2020/2003/KOS/kos_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
996,901,"SPR","Spratly Islands","ppp_2003","GIS/Population/Global_2000_2020/2003/SPR/spr_ppp_2003.tif","Estimated total number of people per grid-cell 2003 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
997,643,"RUS","Russia","ppp_2004","GIS/Population/Global_2000_2020/2004/RUS/rus_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
998,360,"IDN","Indonesia","ppp_2004","GIS/Population/Global_2000_2020/2004/IDN/idn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
999,840,"USA","United States","ppp_2004","GIS/Population/Global_2000_2020/2004/USA/usa_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1000,850,"VIR","Virgin_Islands_U_S","ppp_2004","GIS/Population/Global_2000_2020/2004/VIR/vir_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1001,304,"GRL","Greenland","ppp_2004","GIS/Population/Global_2000_2020/2004/GRL/grl_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1002,156,"CHN","China","ppp_2004","GIS/Population/Global_2000_2020/2004/CHN/chn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1003,36,"AUS","Australia","ppp_2004","GIS/Population/Global_2000_2020/2004/AUS/aus_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1004,76,"BRA","Brazil","ppp_2004","GIS/Population/Global_2000_2020/2004/BRA/bra_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1005,124,"CAN","Canada","ppp_2004","GIS/Population/Global_2000_2020/2004/CAN/can_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1006,152,"CHL","Chile","ppp_2004","GIS/Population/Global_2000_2020/2004/CHL/chl_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1007,4,"AFG","Afghanistan","ppp_2004","GIS/Population/Global_2000_2020/2004/AFG/afg_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1008,8,"ALB","Albania","ppp_2004","GIS/Population/Global_2000_2020/2004/ALB/alb_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1009,10,"ATA","Antarctica","ppp_2004","GIS/Population/Global_2000_2020/2004/ATA/ata_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1010,12,"DZA","Algeria","ppp_2004","GIS/Population/Global_2000_2020/2004/DZA/dza_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1011,16,"ASM","American Samoa","ppp_2004","GIS/Population/Global_2000_2020/2004/ASM/asm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1012,20,"AND","Andorra","ppp_2004","GIS/Population/Global_2000_2020/2004/AND/and_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1013,24,"AGO","Angola","ppp_2004","GIS/Population/Global_2000_2020/2004/AGO/ago_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1014,28,"ATG","Antigua and Barbuda","ppp_2004","GIS/Population/Global_2000_2020/2004/ATG/atg_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1015,31,"AZE","Azerbaijan","ppp_2004","GIS/Population/Global_2000_2020/2004/AZE/aze_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1016,32,"ARG","Argentina","ppp_2004","GIS/Population/Global_2000_2020/2004/ARG/arg_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1017,40,"AUT","Austria","ppp_2004","GIS/Population/Global_2000_2020/2004/AUT/aut_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1018,44,"BHS","Bahamas","ppp_2004","GIS/Population/Global_2000_2020/2004/BHS/bhs_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1019,48,"BHR","Bahrain","ppp_2004","GIS/Population/Global_2000_2020/2004/BHR/bhr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1020,50,"BGD","Bangladesh","ppp_2004","GIS/Population/Global_2000_2020/2004/BGD/bgd_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1021,51,"ARM","Armenia","ppp_2004","GIS/Population/Global_2000_2020/2004/ARM/arm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1022,52,"BRB","Barbados","ppp_2004","GIS/Population/Global_2000_2020/2004/BRB/brb_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1023,56,"BEL","Belgium","ppp_2004","GIS/Population/Global_2000_2020/2004/BEL/bel_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1024,60,"BMU","Bermuda","ppp_2004","GIS/Population/Global_2000_2020/2004/BMU/bmu_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1025,64,"BTN","Bhutan","ppp_2004","GIS/Population/Global_2000_2020/2004/BTN/btn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1026,68,"BOL","Bolivia","ppp_2004","GIS/Population/Global_2000_2020/2004/BOL/bol_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1027,70,"BIH","Bosnia and Herzegovina","ppp_2004","GIS/Population/Global_2000_2020/2004/BIH/bih_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1028,72,"BWA","Botswana","ppp_2004","GIS/Population/Global_2000_2020/2004/BWA/bwa_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1029,74,"BVT","Bouvet Island","ppp_2004","GIS/Population/Global_2000_2020/2004/BVT/bvt_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1030,84,"BLZ","Belize","ppp_2004","GIS/Population/Global_2000_2020/2004/BLZ/blz_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1031,86,"IOT","British Indian Ocean Territory","ppp_2004","GIS/Population/Global_2000_2020/2004/IOT/iot_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1032,90,"SLB","Solomon Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/SLB/slb_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1033,92,"VGB","British Virgin Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/VGB/vgb_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1034,96,"BRN","Brunei","ppp_2004","GIS/Population/Global_2000_2020/2004/BRN/brn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1035,100,"BGR","Bulgaria","ppp_2004","GIS/Population/Global_2000_2020/2004/BGR/bgr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1036,104,"MMR","Myanmar","ppp_2004","GIS/Population/Global_2000_2020/2004/MMR/mmr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1037,108,"BDI","Burundi","ppp_2004","GIS/Population/Global_2000_2020/2004/BDI/bdi_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1038,112,"BLR","Belarus","ppp_2004","GIS/Population/Global_2000_2020/2004/BLR/blr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1039,116,"KHM","Cambodia","ppp_2004","GIS/Population/Global_2000_2020/2004/KHM/khm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1040,120,"CMR","Cameroon","ppp_2004","GIS/Population/Global_2000_2020/2004/CMR/cmr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1041,132,"CPV","Cape Verde","ppp_2004","GIS/Population/Global_2000_2020/2004/CPV/cpv_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1042,136,"CYM","Cayman Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/CYM/cym_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1043,140,"CAF","Central African Republic","ppp_2004","GIS/Population/Global_2000_2020/2004/CAF/caf_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1044,144,"LKA","Sri Lanka","ppp_2004","GIS/Population/Global_2000_2020/2004/LKA/lka_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1045,148,"TCD","Chad","ppp_2004","GIS/Population/Global_2000_2020/2004/TCD/tcd_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1046,158,"TWN","Taiwan","ppp_2004","GIS/Population/Global_2000_2020/2004/TWN/twn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1047,170,"COL","Colombia","ppp_2004","GIS/Population/Global_2000_2020/2004/COL/col_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1048,174,"COM","Comoros","ppp_2004","GIS/Population/Global_2000_2020/2004/COM/com_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1049,175,"MYT","Mayotte","ppp_2004","GIS/Population/Global_2000_2020/2004/MYT/myt_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1050,178,"COG","Republic of Congo","ppp_2004","GIS/Population/Global_2000_2020/2004/COG/cog_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1051,180,"COD","Democratic Republic of the Congo","ppp_2004","GIS/Population/Global_2000_2020/2004/COD/cod_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1052,184,"COK","Cook Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/COK/cok_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1053,188,"CRI","Costa Rica","ppp_2004","GIS/Population/Global_2000_2020/2004/CRI/cri_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1054,191,"HRV","Croatia","ppp_2004","GIS/Population/Global_2000_2020/2004/HRV/hrv_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1055,192,"CUB","Cuba","ppp_2004","GIS/Population/Global_2000_2020/2004/CUB/cub_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1056,196,"CYP","Cyprus","ppp_2004","GIS/Population/Global_2000_2020/2004/CYP/cyp_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1057,203,"CZE","Czech Republic","ppp_2004","GIS/Population/Global_2000_2020/2004/CZE/cze_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1058,204,"BEN","Benin","ppp_2004","GIS/Population/Global_2000_2020/2004/BEN/ben_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1059,208,"DNK","Denmark","ppp_2004","GIS/Population/Global_2000_2020/2004/DNK/dnk_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1060,212,"DMA","Dominica","ppp_2004","GIS/Population/Global_2000_2020/2004/DMA/dma_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1061,214,"DOM","Dominican Republic","ppp_2004","GIS/Population/Global_2000_2020/2004/DOM/dom_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1062,218,"ECU","Ecuador","ppp_2004","GIS/Population/Global_2000_2020/2004/ECU/ecu_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1063,222,"SLV","El Salvador","ppp_2004","GIS/Population/Global_2000_2020/2004/SLV/slv_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1064,226,"GNQ","Equatorial Guinea","ppp_2004","GIS/Population/Global_2000_2020/2004/GNQ/gnq_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1065,231,"ETH","Ethiopia","ppp_2004","GIS/Population/Global_2000_2020/2004/ETH/eth_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1066,232,"ERI","Eritrea","ppp_2004","GIS/Population/Global_2000_2020/2004/ERI/eri_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1067,233,"EST","Estonia","ppp_2004","GIS/Population/Global_2000_2020/2004/EST/est_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1068,234,"FRO","Faroe Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/FRO/fro_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1069,238,"FLK","Falkland Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/FLK/flk_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1070,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/SGS/sgs_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1071,242,"FJI","Fiji","ppp_2004","GIS/Population/Global_2000_2020/2004/FJI/fji_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1072,246,"FIN","Finland","ppp_2004","GIS/Population/Global_2000_2020/2004/FIN/fin_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1073,248,"ALA","Aland Islands ","ppp_2004","GIS/Population/Global_2000_2020/2004/ALA/ala_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1074,250,"FRA","France","ppp_2004","GIS/Population/Global_2000_2020/2004/FRA/fra_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1075,254,"GUF","French Guiana","ppp_2004","GIS/Population/Global_2000_2020/2004/GUF/guf_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1076,258,"PYF","French Polynesia","ppp_2004","GIS/Population/Global_2000_2020/2004/PYF/pyf_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1077,260,"ATF","French Southern Territories","ppp_2004","GIS/Population/Global_2000_2020/2004/ATF/atf_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1078,262,"DJI","Djibouti","ppp_2004","GIS/Population/Global_2000_2020/2004/DJI/dji_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1079,266,"GAB","Gabon","ppp_2004","GIS/Population/Global_2000_2020/2004/GAB/gab_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1080,268,"GEO","Georgia","ppp_2004","GIS/Population/Global_2000_2020/2004/GEO/geo_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1081,270,"GMB","Gambia","ppp_2004","GIS/Population/Global_2000_2020/2004/GMB/gmb_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1082,275,"PSE","Palestina","ppp_2004","GIS/Population/Global_2000_2020/2004/PSE/pse_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1083,276,"DEU","Germany","ppp_2004","GIS/Population/Global_2000_2020/2004/DEU/deu_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1084,288,"GHA","Ghana","ppp_2004","GIS/Population/Global_2000_2020/2004/GHA/gha_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1085,292,"GIB","Gibraltar","ppp_2004","GIS/Population/Global_2000_2020/2004/GIB/gib_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1086,296,"KIR","Kiribati","ppp_2004","GIS/Population/Global_2000_2020/2004/KIR/kir_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1087,300,"GRC","Greece","ppp_2004","GIS/Population/Global_2000_2020/2004/GRC/grc_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1088,308,"GRD","Grenada","ppp_2004","GIS/Population/Global_2000_2020/2004/GRD/grd_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1089,312,"GLP","Guadeloupe","ppp_2004","GIS/Population/Global_2000_2020/2004/GLP/glp_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1090,316,"GUM","Guam","ppp_2004","GIS/Population/Global_2000_2020/2004/GUM/gum_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1091,320,"GTM","Guatemala","ppp_2004","GIS/Population/Global_2000_2020/2004/GTM/gtm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1092,324,"GIN","Guinea","ppp_2004","GIS/Population/Global_2000_2020/2004/GIN/gin_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1093,328,"GUY","Guyana","ppp_2004","GIS/Population/Global_2000_2020/2004/GUY/guy_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1094,332,"HTI","Haiti","ppp_2004","GIS/Population/Global_2000_2020/2004/HTI/hti_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1095,334,"HMD","Heard Island and McDonald Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/HMD/hmd_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1096,336,"VAT","Vatican City","ppp_2004","GIS/Population/Global_2000_2020/2004/VAT/vat_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1097,340,"HND","Honduras","ppp_2004","GIS/Population/Global_2000_2020/2004/HND/hnd_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1098,344,"HKG","Hong Kong","ppp_2004","GIS/Population/Global_2000_2020/2004/HKG/hkg_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1099,348,"HUN","Hungary","ppp_2004","GIS/Population/Global_2000_2020/2004/HUN/hun_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1100,352,"ISL","Iceland","ppp_2004","GIS/Population/Global_2000_2020/2004/ISL/isl_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1101,356,"IND","India","ppp_2004","GIS/Population/Global_2000_2020/2004/IND/ind_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1102,364,"IRN","Iran","ppp_2004","GIS/Population/Global_2000_2020/2004/IRN/irn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1103,368,"IRQ","Iraq","ppp_2004","GIS/Population/Global_2000_2020/2004/IRQ/irq_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1104,372,"IRL","Ireland","ppp_2004","GIS/Population/Global_2000_2020/2004/IRL/irl_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1105,376,"ISR","Israel","ppp_2004","GIS/Population/Global_2000_2020/2004/ISR/isr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1106,380,"ITA","Italy","ppp_2004","GIS/Population/Global_2000_2020/2004/ITA/ita_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1107,384,"CIV","CIte dIvoire","ppp_2004","GIS/Population/Global_2000_2020/2004/CIV/civ_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1108,388,"JAM","Jamaica","ppp_2004","GIS/Population/Global_2000_2020/2004/JAM/jam_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1109,392,"JPN","Japan","ppp_2004","GIS/Population/Global_2000_2020/2004/JPN/jpn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1110,398,"KAZ","Kazakhstan","ppp_2004","GIS/Population/Global_2000_2020/2004/KAZ/kaz_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1111,400,"JOR","Jordan","ppp_2004","GIS/Population/Global_2000_2020/2004/JOR/jor_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1112,404,"KEN","Kenya","ppp_2004","GIS/Population/Global_2000_2020/2004/KEN/ken_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1113,408,"PRK","North Korea","ppp_2004","GIS/Population/Global_2000_2020/2004/PRK/prk_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1114,410,"KOR","South Korea","ppp_2004","GIS/Population/Global_2000_2020/2004/KOR/kor_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1115,414,"KWT","Kuwait","ppp_2004","GIS/Population/Global_2000_2020/2004/KWT/kwt_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1116,417,"KGZ","Kyrgyzstan","ppp_2004","GIS/Population/Global_2000_2020/2004/KGZ/kgz_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1117,418,"LAO","Laos","ppp_2004","GIS/Population/Global_2000_2020/2004/LAO/lao_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1118,422,"LBN","Lebanon","ppp_2004","GIS/Population/Global_2000_2020/2004/LBN/lbn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1119,426,"LSO","Lesotho","ppp_2004","GIS/Population/Global_2000_2020/2004/LSO/lso_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1120,428,"LVA","Latvia","ppp_2004","GIS/Population/Global_2000_2020/2004/LVA/lva_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1121,430,"LBR","Liberia","ppp_2004","GIS/Population/Global_2000_2020/2004/LBR/lbr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1122,434,"LBY","Libya","ppp_2004","GIS/Population/Global_2000_2020/2004/LBY/lby_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1123,438,"LIE","Liechtenstein","ppp_2004","GIS/Population/Global_2000_2020/2004/LIE/lie_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1124,440,"LTU","Lithuania","ppp_2004","GIS/Population/Global_2000_2020/2004/LTU/ltu_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1125,442,"LUX","Luxembourg","ppp_2004","GIS/Population/Global_2000_2020/2004/LUX/lux_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1126,446,"MAC","Macao","ppp_2004","GIS/Population/Global_2000_2020/2004/MAC/mac_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1127,450,"MDG","Madagascar","ppp_2004","GIS/Population/Global_2000_2020/2004/MDG/mdg_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1128,454,"MWI","Malawi","ppp_2004","GIS/Population/Global_2000_2020/2004/MWI/mwi_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1129,458,"MYS","Malaysia","ppp_2004","GIS/Population/Global_2000_2020/2004/MYS/mys_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1130,462,"MDV","Maldives","ppp_2004","GIS/Population/Global_2000_2020/2004/MDV/mdv_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1131,466,"MLI","Mali","ppp_2004","GIS/Population/Global_2000_2020/2004/MLI/mli_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1132,470,"MLT","Malta","ppp_2004","GIS/Population/Global_2000_2020/2004/MLT/mlt_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1133,474,"MTQ","Martinique","ppp_2004","GIS/Population/Global_2000_2020/2004/MTQ/mtq_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1134,478,"MRT","Mauritania","ppp_2004","GIS/Population/Global_2000_2020/2004/MRT/mrt_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1135,480,"MUS","Mauritius","ppp_2004","GIS/Population/Global_2000_2020/2004/MUS/mus_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1136,484,"MEX","Mexico","ppp_2004","GIS/Population/Global_2000_2020/2004/MEX/mex_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1137,492,"MCO","Monaco","ppp_2004","GIS/Population/Global_2000_2020/2004/MCO/mco_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1138,496,"MNG","Mongolia","ppp_2004","GIS/Population/Global_2000_2020/2004/MNG/mng_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1139,498,"MDA","Moldova","ppp_2004","GIS/Population/Global_2000_2020/2004/MDA/mda_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1140,499,"MNE","Montenegro","ppp_2004","GIS/Population/Global_2000_2020/2004/MNE/mne_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1141,500,"MSR","Montserrat","ppp_2004","GIS/Population/Global_2000_2020/2004/MSR/msr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1142,504,"MAR","Morocco","ppp_2004","GIS/Population/Global_2000_2020/2004/MAR/mar_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1143,508,"MOZ","Mozambique","ppp_2004","GIS/Population/Global_2000_2020/2004/MOZ/moz_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1144,512,"OMN","Oman","ppp_2004","GIS/Population/Global_2000_2020/2004/OMN/omn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1145,516,"NAM","Namibia","ppp_2004","GIS/Population/Global_2000_2020/2004/NAM/nam_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1146,520,"NRU","Nauru","ppp_2004","GIS/Population/Global_2000_2020/2004/NRU/nru_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1147,524,"NPL","Nepal","ppp_2004","GIS/Population/Global_2000_2020/2004/NPL/npl_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1148,528,"NLD","Netherlands","ppp_2004","GIS/Population/Global_2000_2020/2004/NLD/nld_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1149,531,"CUW","Curacao","ppp_2004","GIS/Population/Global_2000_2020/2004/CUW/cuw_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1150,533,"ABW","Aruba","ppp_2004","GIS/Population/Global_2000_2020/2004/ABW/abw_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1151,534,"SXM","Sint Maarten (Dutch part)","ppp_2004","GIS/Population/Global_2000_2020/2004/SXM/sxm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1152,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2004","GIS/Population/Global_2000_2020/2004/BES/bes_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1153,540,"NCL","New Caledonia","ppp_2004","GIS/Population/Global_2000_2020/2004/NCL/ncl_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1154,548,"VUT","Vanuatu","ppp_2004","GIS/Population/Global_2000_2020/2004/VUT/vut_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1155,554,"NZL","New Zealand","ppp_2004","GIS/Population/Global_2000_2020/2004/NZL/nzl_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1156,558,"NIC","Nicaragua","ppp_2004","GIS/Population/Global_2000_2020/2004/NIC/nic_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1157,562,"NER","Niger","ppp_2004","GIS/Population/Global_2000_2020/2004/NER/ner_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1158,566,"NGA","Nigeria","ppp_2004","GIS/Population/Global_2000_2020/2004/NGA/nga_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1159,570,"NIU","Niue","ppp_2004","GIS/Population/Global_2000_2020/2004/NIU/niu_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1160,574,"NFK","Norfolk Island","ppp_2004","GIS/Population/Global_2000_2020/2004/NFK/nfk_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1161,578,"NOR","Norway","ppp_2004","GIS/Population/Global_2000_2020/2004/NOR/nor_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1162,580,"MNP","Northern Mariana Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/MNP/mnp_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1163,581,"UMI","United States Minor Outlying Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/UMI/umi_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1164,583,"FSM","Micronesia","ppp_2004","GIS/Population/Global_2000_2020/2004/FSM/fsm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1165,584,"MHL","Marshall Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/MHL/mhl_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1166,585,"PLW","Palau","ppp_2004","GIS/Population/Global_2000_2020/2004/PLW/plw_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1167,586,"PAK","Pakistan","ppp_2004","GIS/Population/Global_2000_2020/2004/PAK/pak_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1168,591,"PAN","Panama","ppp_2004","GIS/Population/Global_2000_2020/2004/PAN/pan_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1169,598,"PNG","Papua New Guinea","ppp_2004","GIS/Population/Global_2000_2020/2004/PNG/png_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1170,600,"PRY","Paraguay","ppp_2004","GIS/Population/Global_2000_2020/2004/PRY/pry_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1171,604,"PER","Peru","ppp_2004","GIS/Population/Global_2000_2020/2004/PER/per_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1172,608,"PHL","Philippines","ppp_2004","GIS/Population/Global_2000_2020/2004/PHL/phl_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1173,612,"PCN","Pitcairn Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/PCN/pcn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1174,616,"POL","Poland","ppp_2004","GIS/Population/Global_2000_2020/2004/POL/pol_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1175,620,"PRT","Portugal","ppp_2004","GIS/Population/Global_2000_2020/2004/PRT/prt_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1176,624,"GNB","Guinea-Bissau","ppp_2004","GIS/Population/Global_2000_2020/2004/GNB/gnb_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1177,626,"TLS","East Timor","ppp_2004","GIS/Population/Global_2000_2020/2004/TLS/tls_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1178,630,"PRI","Puerto Rico","ppp_2004","GIS/Population/Global_2000_2020/2004/PRI/pri_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1179,634,"QAT","Qatar","ppp_2004","GIS/Population/Global_2000_2020/2004/QAT/qat_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1180,638,"REU","Reunion","ppp_2004","GIS/Population/Global_2000_2020/2004/REU/reu_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1181,642,"ROU","Romania","ppp_2004","GIS/Population/Global_2000_2020/2004/ROU/rou_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1182,646,"RWA","Rwanda","ppp_2004","GIS/Population/Global_2000_2020/2004/RWA/rwa_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1183,652,"BLM","Saint Barthelemy","ppp_2004","GIS/Population/Global_2000_2020/2004/BLM/blm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1184,654,"SHN","Saint Helena","ppp_2004","GIS/Population/Global_2000_2020/2004/SHN/shn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1185,659,"KNA","Saint Kitts and Nevis","ppp_2004","GIS/Population/Global_2000_2020/2004/KNA/kna_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1186,660,"AIA","Anguilla","ppp_2004","GIS/Population/Global_2000_2020/2004/AIA/aia_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1187,662,"LCA","Saint Lucia","ppp_2004","GIS/Population/Global_2000_2020/2004/LCA/lca_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1188,663,"MAF","Saint Martin (French part)","ppp_2004","GIS/Population/Global_2000_2020/2004/MAF/maf_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1189,666,"SPM","Saint Pierre and Miquelon","ppp_2004","GIS/Population/Global_2000_2020/2004/SPM/spm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1190,670,"VCT","Saint Vincent and the Grenadines","ppp_2004","GIS/Population/Global_2000_2020/2004/VCT/vct_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1191,674,"SMR","San Marino","ppp_2004","GIS/Population/Global_2000_2020/2004/SMR/smr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1192,678,"STP","Sao Tome and Principe","ppp_2004","GIS/Population/Global_2000_2020/2004/STP/stp_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1193,682,"SAU","Saudi Arabia","ppp_2004","GIS/Population/Global_2000_2020/2004/SAU/sau_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1194,686,"SEN","Senegal","ppp_2004","GIS/Population/Global_2000_2020/2004/SEN/sen_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1195,688,"SRB","Serbia","ppp_2004","GIS/Population/Global_2000_2020/2004/SRB/srb_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1196,690,"SYC","Seychelles","ppp_2004","GIS/Population/Global_2000_2020/2004/SYC/syc_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1197,694,"SLE","Sierra Leone","ppp_2004","GIS/Population/Global_2000_2020/2004/SLE/sle_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1198,702,"SGP","Singapore","ppp_2004","GIS/Population/Global_2000_2020/2004/SGP/sgp_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1199,703,"SVK","Slovakia","ppp_2004","GIS/Population/Global_2000_2020/2004/SVK/svk_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1200,704,"VNM","Vietnam","ppp_2004","GIS/Population/Global_2000_2020/2004/VNM/vnm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1201,705,"SVN","Slovenia","ppp_2004","GIS/Population/Global_2000_2020/2004/SVN/svn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1202,706,"SOM","Somalia","ppp_2004","GIS/Population/Global_2000_2020/2004/SOM/som_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1203,710,"ZAF","South Africa","ppp_2004","GIS/Population/Global_2000_2020/2004/ZAF/zaf_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1204,716,"ZWE","Zimbabwe","ppp_2004","GIS/Population/Global_2000_2020/2004/ZWE/zwe_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1205,724,"ESP","Spain","ppp_2004","GIS/Population/Global_2000_2020/2004/ESP/esp_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1206,728,"SSD","South Sudan","ppp_2004","GIS/Population/Global_2000_2020/2004/SSD/ssd_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1207,729,"SDN","Sudan","ppp_2004","GIS/Population/Global_2000_2020/2004/SDN/sdn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1208,732,"ESH","Western Sahara","ppp_2004","GIS/Population/Global_2000_2020/2004/ESH/esh_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1209,740,"SUR","Suriname","ppp_2004","GIS/Population/Global_2000_2020/2004/SUR/sur_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1210,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/SJM/sjm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1211,748,"SWZ","Swaziland","ppp_2004","GIS/Population/Global_2000_2020/2004/SWZ/swz_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1212,752,"SWE","Sweden","ppp_2004","GIS/Population/Global_2000_2020/2004/SWE/swe_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1213,756,"CHE","Switzerland","ppp_2004","GIS/Population/Global_2000_2020/2004/CHE/che_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1214,760,"SYR","Syria","ppp_2004","GIS/Population/Global_2000_2020/2004/SYR/syr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1215,762,"TJK","Tajikistan","ppp_2004","GIS/Population/Global_2000_2020/2004/TJK/tjk_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1216,764,"THA","Thailand","ppp_2004","GIS/Population/Global_2000_2020/2004/THA/tha_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1217,768,"TGO","Togo","ppp_2004","GIS/Population/Global_2000_2020/2004/TGO/tgo_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1218,772,"TKL","Tokelau","ppp_2004","GIS/Population/Global_2000_2020/2004/TKL/tkl_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1219,776,"TON","Tonga","ppp_2004","GIS/Population/Global_2000_2020/2004/TON/ton_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1220,780,"TTO","Trinidad and Tobago","ppp_2004","GIS/Population/Global_2000_2020/2004/TTO/tto_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1221,784,"ARE","United Arab Emirates","ppp_2004","GIS/Population/Global_2000_2020/2004/ARE/are_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1222,788,"TUN","Tunisia","ppp_2004","GIS/Population/Global_2000_2020/2004/TUN/tun_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1223,792,"TUR","Turkey","ppp_2004","GIS/Population/Global_2000_2020/2004/TUR/tur_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1224,795,"TKM","Turkmenistan","ppp_2004","GIS/Population/Global_2000_2020/2004/TKM/tkm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1225,796,"TCA","Turks and Caicos Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/TCA/tca_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1226,798,"TUV","Tuvalu","ppp_2004","GIS/Population/Global_2000_2020/2004/TUV/tuv_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1227,800,"UGA","Uganda","ppp_2004","GIS/Population/Global_2000_2020/2004/UGA/uga_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1228,804,"UKR","Ukraine","ppp_2004","GIS/Population/Global_2000_2020/2004/UKR/ukr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1229,807,"MKD","Macedonia","ppp_2004","GIS/Population/Global_2000_2020/2004/MKD/mkd_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1230,818,"EGY","Egypt","ppp_2004","GIS/Population/Global_2000_2020/2004/EGY/egy_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1231,826,"GBR","United Kingdom","ppp_2004","GIS/Population/Global_2000_2020/2004/GBR/gbr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1232,831,"GGY","Guernsey","ppp_2004","GIS/Population/Global_2000_2020/2004/GGY/ggy_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1233,832,"JEY","Jersey","ppp_2004","GIS/Population/Global_2000_2020/2004/JEY/jey_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1234,833,"IMN","Isle of Man","ppp_2004","GIS/Population/Global_2000_2020/2004/IMN/imn_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1235,834,"TZA","Tanzania","ppp_2004","GIS/Population/Global_2000_2020/2004/TZA/tza_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1236,854,"BFA","Burkina Faso","ppp_2004","GIS/Population/Global_2000_2020/2004/BFA/bfa_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1237,858,"URY","Uruguay","ppp_2004","GIS/Population/Global_2000_2020/2004/URY/ury_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1238,860,"UZB","Uzbekistan","ppp_2004","GIS/Population/Global_2000_2020/2004/UZB/uzb_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1239,862,"VEN","Venezuela","ppp_2004","GIS/Population/Global_2000_2020/2004/VEN/ven_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1240,876,"WLF","Wallis and Futuna","ppp_2004","GIS/Population/Global_2000_2020/2004/WLF/wlf_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1241,882,"WSM","Samoa","ppp_2004","GIS/Population/Global_2000_2020/2004/WSM/wsm_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1242,887,"YEM","Yemen","ppp_2004","GIS/Population/Global_2000_2020/2004/YEM/yem_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1243,894,"ZMB","Zambia","ppp_2004","GIS/Population/Global_2000_2020/2004/ZMB/zmb_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1244,900,"KOS","Kosovo","ppp_2004","GIS/Population/Global_2000_2020/2004/KOS/kos_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1245,901,"SPR","Spratly Islands","ppp_2004","GIS/Population/Global_2000_2020/2004/SPR/spr_ppp_2004.tif","Estimated total number of people per grid-cell 2004 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1246,643,"RUS","Russia","ppp_2005","GIS/Population/Global_2000_2020/2005/RUS/rus_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1247,360,"IDN","Indonesia","ppp_2005","GIS/Population/Global_2000_2020/2005/IDN/idn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1248,840,"USA","United States","ppp_2005","GIS/Population/Global_2000_2020/2005/USA/usa_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1249,850,"VIR","Virgin_Islands_U_S","ppp_2005","GIS/Population/Global_2000_2020/2005/VIR/vir_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1250,304,"GRL","Greenland","ppp_2005","GIS/Population/Global_2000_2020/2005/GRL/grl_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1251,156,"CHN","China","ppp_2005","GIS/Population/Global_2000_2020/2005/CHN/chn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1252,36,"AUS","Australia","ppp_2005","GIS/Population/Global_2000_2020/2005/AUS/aus_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1253,76,"BRA","Brazil","ppp_2005","GIS/Population/Global_2000_2020/2005/BRA/bra_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1254,124,"CAN","Canada","ppp_2005","GIS/Population/Global_2000_2020/2005/CAN/can_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1255,152,"CHL","Chile","ppp_2005","GIS/Population/Global_2000_2020/2005/CHL/chl_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1256,4,"AFG","Afghanistan","ppp_2005","GIS/Population/Global_2000_2020/2005/AFG/afg_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1257,8,"ALB","Albania","ppp_2005","GIS/Population/Global_2000_2020/2005/ALB/alb_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1258,10,"ATA","Antarctica","ppp_2005","GIS/Population/Global_2000_2020/2005/ATA/ata_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1259,12,"DZA","Algeria","ppp_2005","GIS/Population/Global_2000_2020/2005/DZA/dza_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1260,16,"ASM","American Samoa","ppp_2005","GIS/Population/Global_2000_2020/2005/ASM/asm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1261,20,"AND","Andorra","ppp_2005","GIS/Population/Global_2000_2020/2005/AND/and_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1262,24,"AGO","Angola","ppp_2005","GIS/Population/Global_2000_2020/2005/AGO/ago_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1263,28,"ATG","Antigua and Barbuda","ppp_2005","GIS/Population/Global_2000_2020/2005/ATG/atg_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1264,31,"AZE","Azerbaijan","ppp_2005","GIS/Population/Global_2000_2020/2005/AZE/aze_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1265,32,"ARG","Argentina","ppp_2005","GIS/Population/Global_2000_2020/2005/ARG/arg_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1266,40,"AUT","Austria","ppp_2005","GIS/Population/Global_2000_2020/2005/AUT/aut_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1267,44,"BHS","Bahamas","ppp_2005","GIS/Population/Global_2000_2020/2005/BHS/bhs_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1268,48,"BHR","Bahrain","ppp_2005","GIS/Population/Global_2000_2020/2005/BHR/bhr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1269,50,"BGD","Bangladesh","ppp_2005","GIS/Population/Global_2000_2020/2005/BGD/bgd_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1270,51,"ARM","Armenia","ppp_2005","GIS/Population/Global_2000_2020/2005/ARM/arm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1271,52,"BRB","Barbados","ppp_2005","GIS/Population/Global_2000_2020/2005/BRB/brb_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1272,56,"BEL","Belgium","ppp_2005","GIS/Population/Global_2000_2020/2005/BEL/bel_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1273,60,"BMU","Bermuda","ppp_2005","GIS/Population/Global_2000_2020/2005/BMU/bmu_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1274,64,"BTN","Bhutan","ppp_2005","GIS/Population/Global_2000_2020/2005/BTN/btn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1275,68,"BOL","Bolivia","ppp_2005","GIS/Population/Global_2000_2020/2005/BOL/bol_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1276,70,"BIH","Bosnia and Herzegovina","ppp_2005","GIS/Population/Global_2000_2020/2005/BIH/bih_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1277,72,"BWA","Botswana","ppp_2005","GIS/Population/Global_2000_2020/2005/BWA/bwa_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1278,74,"BVT","Bouvet Island","ppp_2005","GIS/Population/Global_2000_2020/2005/BVT/bvt_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1279,84,"BLZ","Belize","ppp_2005","GIS/Population/Global_2000_2020/2005/BLZ/blz_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1280,86,"IOT","British Indian Ocean Territory","ppp_2005","GIS/Population/Global_2000_2020/2005/IOT/iot_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1281,90,"SLB","Solomon Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/SLB/slb_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1282,92,"VGB","British Virgin Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/VGB/vgb_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1283,96,"BRN","Brunei","ppp_2005","GIS/Population/Global_2000_2020/2005/BRN/brn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1284,100,"BGR","Bulgaria","ppp_2005","GIS/Population/Global_2000_2020/2005/BGR/bgr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1285,104,"MMR","Myanmar","ppp_2005","GIS/Population/Global_2000_2020/2005/MMR/mmr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1286,108,"BDI","Burundi","ppp_2005","GIS/Population/Global_2000_2020/2005/BDI/bdi_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1287,112,"BLR","Belarus","ppp_2005","GIS/Population/Global_2000_2020/2005/BLR/blr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1288,116,"KHM","Cambodia","ppp_2005","GIS/Population/Global_2000_2020/2005/KHM/khm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1289,120,"CMR","Cameroon","ppp_2005","GIS/Population/Global_2000_2020/2005/CMR/cmr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1290,132,"CPV","Cape Verde","ppp_2005","GIS/Population/Global_2000_2020/2005/CPV/cpv_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1291,136,"CYM","Cayman Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/CYM/cym_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1292,140,"CAF","Central African Republic","ppp_2005","GIS/Population/Global_2000_2020/2005/CAF/caf_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1293,144,"LKA","Sri Lanka","ppp_2005","GIS/Population/Global_2000_2020/2005/LKA/lka_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1294,148,"TCD","Chad","ppp_2005","GIS/Population/Global_2000_2020/2005/TCD/tcd_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1295,158,"TWN","Taiwan","ppp_2005","GIS/Population/Global_2000_2020/2005/TWN/twn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1296,170,"COL","Colombia","ppp_2005","GIS/Population/Global_2000_2020/2005/COL/col_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1297,174,"COM","Comoros","ppp_2005","GIS/Population/Global_2000_2020/2005/COM/com_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1298,175,"MYT","Mayotte","ppp_2005","GIS/Population/Global_2000_2020/2005/MYT/myt_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1299,178,"COG","Republic of Congo","ppp_2005","GIS/Population/Global_2000_2020/2005/COG/cog_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1300,180,"COD","Democratic Republic of the Congo","ppp_2005","GIS/Population/Global_2000_2020/2005/COD/cod_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1301,184,"COK","Cook Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/COK/cok_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1302,188,"CRI","Costa Rica","ppp_2005","GIS/Population/Global_2000_2020/2005/CRI/cri_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1303,191,"HRV","Croatia","ppp_2005","GIS/Population/Global_2000_2020/2005/HRV/hrv_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1304,192,"CUB","Cuba","ppp_2005","GIS/Population/Global_2000_2020/2005/CUB/cub_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1305,196,"CYP","Cyprus","ppp_2005","GIS/Population/Global_2000_2020/2005/CYP/cyp_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1306,203,"CZE","Czech Republic","ppp_2005","GIS/Population/Global_2000_2020/2005/CZE/cze_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1307,204,"BEN","Benin","ppp_2005","GIS/Population/Global_2000_2020/2005/BEN/ben_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1308,208,"DNK","Denmark","ppp_2005","GIS/Population/Global_2000_2020/2005/DNK/dnk_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1309,212,"DMA","Dominica","ppp_2005","GIS/Population/Global_2000_2020/2005/DMA/dma_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1310,214,"DOM","Dominican Republic","ppp_2005","GIS/Population/Global_2000_2020/2005/DOM/dom_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1311,218,"ECU","Ecuador","ppp_2005","GIS/Population/Global_2000_2020/2005/ECU/ecu_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1312,222,"SLV","El Salvador","ppp_2005","GIS/Population/Global_2000_2020/2005/SLV/slv_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1313,226,"GNQ","Equatorial Guinea","ppp_2005","GIS/Population/Global_2000_2020/2005/GNQ/gnq_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1314,231,"ETH","Ethiopia","ppp_2005","GIS/Population/Global_2000_2020/2005/ETH/eth_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1315,232,"ERI","Eritrea","ppp_2005","GIS/Population/Global_2000_2020/2005/ERI/eri_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1316,233,"EST","Estonia","ppp_2005","GIS/Population/Global_2000_2020/2005/EST/est_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1317,234,"FRO","Faroe Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/FRO/fro_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1318,238,"FLK","Falkland Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/FLK/flk_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1319,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/SGS/sgs_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1320,242,"FJI","Fiji","ppp_2005","GIS/Population/Global_2000_2020/2005/FJI/fji_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1321,246,"FIN","Finland","ppp_2005","GIS/Population/Global_2000_2020/2005/FIN/fin_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1322,248,"ALA","Aland Islands ","ppp_2005","GIS/Population/Global_2000_2020/2005/ALA/ala_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1323,250,"FRA","France","ppp_2005","GIS/Population/Global_2000_2020/2005/FRA/fra_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1324,254,"GUF","French Guiana","ppp_2005","GIS/Population/Global_2000_2020/2005/GUF/guf_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1325,258,"PYF","French Polynesia","ppp_2005","GIS/Population/Global_2000_2020/2005/PYF/pyf_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1326,260,"ATF","French Southern Territories","ppp_2005","GIS/Population/Global_2000_2020/2005/ATF/atf_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1327,262,"DJI","Djibouti","ppp_2005","GIS/Population/Global_2000_2020/2005/DJI/dji_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1328,266,"GAB","Gabon","ppp_2005","GIS/Population/Global_2000_2020/2005/GAB/gab_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1329,268,"GEO","Georgia","ppp_2005","GIS/Population/Global_2000_2020/2005/GEO/geo_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1330,270,"GMB","Gambia","ppp_2005","GIS/Population/Global_2000_2020/2005/GMB/gmb_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1331,275,"PSE","Palestina","ppp_2005","GIS/Population/Global_2000_2020/2005/PSE/pse_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1332,276,"DEU","Germany","ppp_2005","GIS/Population/Global_2000_2020/2005/DEU/deu_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1333,288,"GHA","Ghana","ppp_2005","GIS/Population/Global_2000_2020/2005/GHA/gha_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1334,292,"GIB","Gibraltar","ppp_2005","GIS/Population/Global_2000_2020/2005/GIB/gib_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1335,296,"KIR","Kiribati","ppp_2005","GIS/Population/Global_2000_2020/2005/KIR/kir_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1336,300,"GRC","Greece","ppp_2005","GIS/Population/Global_2000_2020/2005/GRC/grc_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1337,308,"GRD","Grenada","ppp_2005","GIS/Population/Global_2000_2020/2005/GRD/grd_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1338,312,"GLP","Guadeloupe","ppp_2005","GIS/Population/Global_2000_2020/2005/GLP/glp_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1339,316,"GUM","Guam","ppp_2005","GIS/Population/Global_2000_2020/2005/GUM/gum_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1340,320,"GTM","Guatemala","ppp_2005","GIS/Population/Global_2000_2020/2005/GTM/gtm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1341,324,"GIN","Guinea","ppp_2005","GIS/Population/Global_2000_2020/2005/GIN/gin_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1342,328,"GUY","Guyana","ppp_2005","GIS/Population/Global_2000_2020/2005/GUY/guy_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1343,332,"HTI","Haiti","ppp_2005","GIS/Population/Global_2000_2020/2005/HTI/hti_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1344,334,"HMD","Heard Island and McDonald Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/HMD/hmd_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1345,336,"VAT","Vatican City","ppp_2005","GIS/Population/Global_2000_2020/2005/VAT/vat_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1346,340,"HND","Honduras","ppp_2005","GIS/Population/Global_2000_2020/2005/HND/hnd_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1347,344,"HKG","Hong Kong","ppp_2005","GIS/Population/Global_2000_2020/2005/HKG/hkg_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1348,348,"HUN","Hungary","ppp_2005","GIS/Population/Global_2000_2020/2005/HUN/hun_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1349,352,"ISL","Iceland","ppp_2005","GIS/Population/Global_2000_2020/2005/ISL/isl_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1350,356,"IND","India","ppp_2005","GIS/Population/Global_2000_2020/2005/IND/ind_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1351,364,"IRN","Iran","ppp_2005","GIS/Population/Global_2000_2020/2005/IRN/irn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1352,368,"IRQ","Iraq","ppp_2005","GIS/Population/Global_2000_2020/2005/IRQ/irq_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1353,372,"IRL","Ireland","ppp_2005","GIS/Population/Global_2000_2020/2005/IRL/irl_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1354,376,"ISR","Israel","ppp_2005","GIS/Population/Global_2000_2020/2005/ISR/isr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1355,380,"ITA","Italy","ppp_2005","GIS/Population/Global_2000_2020/2005/ITA/ita_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1356,384,"CIV","CIte dIvoire","ppp_2005","GIS/Population/Global_2000_2020/2005/CIV/civ_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1357,388,"JAM","Jamaica","ppp_2005","GIS/Population/Global_2000_2020/2005/JAM/jam_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1358,392,"JPN","Japan","ppp_2005","GIS/Population/Global_2000_2020/2005/JPN/jpn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1359,398,"KAZ","Kazakhstan","ppp_2005","GIS/Population/Global_2000_2020/2005/KAZ/kaz_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1360,400,"JOR","Jordan","ppp_2005","GIS/Population/Global_2000_2020/2005/JOR/jor_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1361,404,"KEN","Kenya","ppp_2005","GIS/Population/Global_2000_2020/2005/KEN/ken_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1362,408,"PRK","North Korea","ppp_2005","GIS/Population/Global_2000_2020/2005/PRK/prk_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1363,410,"KOR","South Korea","ppp_2005","GIS/Population/Global_2000_2020/2005/KOR/kor_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1364,414,"KWT","Kuwait","ppp_2005","GIS/Population/Global_2000_2020/2005/KWT/kwt_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1365,417,"KGZ","Kyrgyzstan","ppp_2005","GIS/Population/Global_2000_2020/2005/KGZ/kgz_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1366,418,"LAO","Laos","ppp_2005","GIS/Population/Global_2000_2020/2005/LAO/lao_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1367,422,"LBN","Lebanon","ppp_2005","GIS/Population/Global_2000_2020/2005/LBN/lbn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1368,426,"LSO","Lesotho","ppp_2005","GIS/Population/Global_2000_2020/2005/LSO/lso_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1369,428,"LVA","Latvia","ppp_2005","GIS/Population/Global_2000_2020/2005/LVA/lva_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1370,430,"LBR","Liberia","ppp_2005","GIS/Population/Global_2000_2020/2005/LBR/lbr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1371,434,"LBY","Libya","ppp_2005","GIS/Population/Global_2000_2020/2005/LBY/lby_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1372,438,"LIE","Liechtenstein","ppp_2005","GIS/Population/Global_2000_2020/2005/LIE/lie_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1373,440,"LTU","Lithuania","ppp_2005","GIS/Population/Global_2000_2020/2005/LTU/ltu_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1374,442,"LUX","Luxembourg","ppp_2005","GIS/Population/Global_2000_2020/2005/LUX/lux_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1375,446,"MAC","Macao","ppp_2005","GIS/Population/Global_2000_2020/2005/MAC/mac_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1376,450,"MDG","Madagascar","ppp_2005","GIS/Population/Global_2000_2020/2005/MDG/mdg_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1377,454,"MWI","Malawi","ppp_2005","GIS/Population/Global_2000_2020/2005/MWI/mwi_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1378,458,"MYS","Malaysia","ppp_2005","GIS/Population/Global_2000_2020/2005/MYS/mys_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1379,462,"MDV","Maldives","ppp_2005","GIS/Population/Global_2000_2020/2005/MDV/mdv_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1380,466,"MLI","Mali","ppp_2005","GIS/Population/Global_2000_2020/2005/MLI/mli_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1381,470,"MLT","Malta","ppp_2005","GIS/Population/Global_2000_2020/2005/MLT/mlt_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1382,474,"MTQ","Martinique","ppp_2005","GIS/Population/Global_2000_2020/2005/MTQ/mtq_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1383,478,"MRT","Mauritania","ppp_2005","GIS/Population/Global_2000_2020/2005/MRT/mrt_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1384,480,"MUS","Mauritius","ppp_2005","GIS/Population/Global_2000_2020/2005/MUS/mus_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1385,484,"MEX","Mexico","ppp_2005","GIS/Population/Global_2000_2020/2005/MEX/mex_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1386,492,"MCO","Monaco","ppp_2005","GIS/Population/Global_2000_2020/2005/MCO/mco_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1387,496,"MNG","Mongolia","ppp_2005","GIS/Population/Global_2000_2020/2005/MNG/mng_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1388,498,"MDA","Moldova","ppp_2005","GIS/Population/Global_2000_2020/2005/MDA/mda_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1389,499,"MNE","Montenegro","ppp_2005","GIS/Population/Global_2000_2020/2005/MNE/mne_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1390,500,"MSR","Montserrat","ppp_2005","GIS/Population/Global_2000_2020/2005/MSR/msr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1391,504,"MAR","Morocco","ppp_2005","GIS/Population/Global_2000_2020/2005/MAR/mar_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1392,508,"MOZ","Mozambique","ppp_2005","GIS/Population/Global_2000_2020/2005/MOZ/moz_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1393,512,"OMN","Oman","ppp_2005","GIS/Population/Global_2000_2020/2005/OMN/omn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1394,516,"NAM","Namibia","ppp_2005","GIS/Population/Global_2000_2020/2005/NAM/nam_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1395,520,"NRU","Nauru","ppp_2005","GIS/Population/Global_2000_2020/2005/NRU/nru_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1396,524,"NPL","Nepal","ppp_2005","GIS/Population/Global_2000_2020/2005/NPL/npl_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1397,528,"NLD","Netherlands","ppp_2005","GIS/Population/Global_2000_2020/2005/NLD/nld_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1398,531,"CUW","Curacao","ppp_2005","GIS/Population/Global_2000_2020/2005/CUW/cuw_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1399,533,"ABW","Aruba","ppp_2005","GIS/Population/Global_2000_2020/2005/ABW/abw_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1400,534,"SXM","Sint Maarten (Dutch part)","ppp_2005","GIS/Population/Global_2000_2020/2005/SXM/sxm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1401,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2005","GIS/Population/Global_2000_2020/2005/BES/bes_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1402,540,"NCL","New Caledonia","ppp_2005","GIS/Population/Global_2000_2020/2005/NCL/ncl_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1403,548,"VUT","Vanuatu","ppp_2005","GIS/Population/Global_2000_2020/2005/VUT/vut_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1404,554,"NZL","New Zealand","ppp_2005","GIS/Population/Global_2000_2020/2005/NZL/nzl_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1405,558,"NIC","Nicaragua","ppp_2005","GIS/Population/Global_2000_2020/2005/NIC/nic_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1406,562,"NER","Niger","ppp_2005","GIS/Population/Global_2000_2020/2005/NER/ner_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1407,566,"NGA","Nigeria","ppp_2005","GIS/Population/Global_2000_2020/2005/NGA/nga_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1408,570,"NIU","Niue","ppp_2005","GIS/Population/Global_2000_2020/2005/NIU/niu_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1409,574,"NFK","Norfolk Island","ppp_2005","GIS/Population/Global_2000_2020/2005/NFK/nfk_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1410,578,"NOR","Norway","ppp_2005","GIS/Population/Global_2000_2020/2005/NOR/nor_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1411,580,"MNP","Northern Mariana Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/MNP/mnp_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1412,581,"UMI","United States Minor Outlying Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/UMI/umi_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1413,583,"FSM","Micronesia","ppp_2005","GIS/Population/Global_2000_2020/2005/FSM/fsm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1414,584,"MHL","Marshall Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/MHL/mhl_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1415,585,"PLW","Palau","ppp_2005","GIS/Population/Global_2000_2020/2005/PLW/plw_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1416,586,"PAK","Pakistan","ppp_2005","GIS/Population/Global_2000_2020/2005/PAK/pak_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1417,591,"PAN","Panama","ppp_2005","GIS/Population/Global_2000_2020/2005/PAN/pan_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1418,598,"PNG","Papua New Guinea","ppp_2005","GIS/Population/Global_2000_2020/2005/PNG/png_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1419,600,"PRY","Paraguay","ppp_2005","GIS/Population/Global_2000_2020/2005/PRY/pry_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1420,604,"PER","Peru","ppp_2005","GIS/Population/Global_2000_2020/2005/PER/per_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1421,608,"PHL","Philippines","ppp_2005","GIS/Population/Global_2000_2020/2005/PHL/phl_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1422,612,"PCN","Pitcairn Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/PCN/pcn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1423,616,"POL","Poland","ppp_2005","GIS/Population/Global_2000_2020/2005/POL/pol_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1424,620,"PRT","Portugal","ppp_2005","GIS/Population/Global_2000_2020/2005/PRT/prt_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1425,624,"GNB","Guinea-Bissau","ppp_2005","GIS/Population/Global_2000_2020/2005/GNB/gnb_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1426,626,"TLS","East Timor","ppp_2005","GIS/Population/Global_2000_2020/2005/TLS/tls_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1427,630,"PRI","Puerto Rico","ppp_2005","GIS/Population/Global_2000_2020/2005/PRI/pri_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1428,634,"QAT","Qatar","ppp_2005","GIS/Population/Global_2000_2020/2005/QAT/qat_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1429,638,"REU","Reunion","ppp_2005","GIS/Population/Global_2000_2020/2005/REU/reu_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1430,642,"ROU","Romania","ppp_2005","GIS/Population/Global_2000_2020/2005/ROU/rou_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1431,646,"RWA","Rwanda","ppp_2005","GIS/Population/Global_2000_2020/2005/RWA/rwa_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1432,652,"BLM","Saint Barthelemy","ppp_2005","GIS/Population/Global_2000_2020/2005/BLM/blm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1433,654,"SHN","Saint Helena","ppp_2005","GIS/Population/Global_2000_2020/2005/SHN/shn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1434,659,"KNA","Saint Kitts and Nevis","ppp_2005","GIS/Population/Global_2000_2020/2005/KNA/kna_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1435,660,"AIA","Anguilla","ppp_2005","GIS/Population/Global_2000_2020/2005/AIA/aia_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1436,662,"LCA","Saint Lucia","ppp_2005","GIS/Population/Global_2000_2020/2005/LCA/lca_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1437,663,"MAF","Saint Martin (French part)","ppp_2005","GIS/Population/Global_2000_2020/2005/MAF/maf_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1438,666,"SPM","Saint Pierre and Miquelon","ppp_2005","GIS/Population/Global_2000_2020/2005/SPM/spm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1439,670,"VCT","Saint Vincent and the Grenadines","ppp_2005","GIS/Population/Global_2000_2020/2005/VCT/vct_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1440,674,"SMR","San Marino","ppp_2005","GIS/Population/Global_2000_2020/2005/SMR/smr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1441,678,"STP","Sao Tome and Principe","ppp_2005","GIS/Population/Global_2000_2020/2005/STP/stp_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1442,682,"SAU","Saudi Arabia","ppp_2005","GIS/Population/Global_2000_2020/2005/SAU/sau_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1443,686,"SEN","Senegal","ppp_2005","GIS/Population/Global_2000_2020/2005/SEN/sen_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1444,688,"SRB","Serbia","ppp_2005","GIS/Population/Global_2000_2020/2005/SRB/srb_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1445,690,"SYC","Seychelles","ppp_2005","GIS/Population/Global_2000_2020/2005/SYC/syc_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1446,694,"SLE","Sierra Leone","ppp_2005","GIS/Population/Global_2000_2020/2005/SLE/sle_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1447,702,"SGP","Singapore","ppp_2005","GIS/Population/Global_2000_2020/2005/SGP/sgp_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1448,703,"SVK","Slovakia","ppp_2005","GIS/Population/Global_2000_2020/2005/SVK/svk_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1449,704,"VNM","Vietnam","ppp_2005","GIS/Population/Global_2000_2020/2005/VNM/vnm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1450,705,"SVN","Slovenia","ppp_2005","GIS/Population/Global_2000_2020/2005/SVN/svn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1451,706,"SOM","Somalia","ppp_2005","GIS/Population/Global_2000_2020/2005/SOM/som_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1452,710,"ZAF","South Africa","ppp_2005","GIS/Population/Global_2000_2020/2005/ZAF/zaf_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1453,716,"ZWE","Zimbabwe","ppp_2005","GIS/Population/Global_2000_2020/2005/ZWE/zwe_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1454,724,"ESP","Spain","ppp_2005","GIS/Population/Global_2000_2020/2005/ESP/esp_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1455,728,"SSD","South Sudan","ppp_2005","GIS/Population/Global_2000_2020/2005/SSD/ssd_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1456,729,"SDN","Sudan","ppp_2005","GIS/Population/Global_2000_2020/2005/SDN/sdn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1457,732,"ESH","Western Sahara","ppp_2005","GIS/Population/Global_2000_2020/2005/ESH/esh_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1458,740,"SUR","Suriname","ppp_2005","GIS/Population/Global_2000_2020/2005/SUR/sur_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1459,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/SJM/sjm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1460,748,"SWZ","Swaziland","ppp_2005","GIS/Population/Global_2000_2020/2005/SWZ/swz_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1461,752,"SWE","Sweden","ppp_2005","GIS/Population/Global_2000_2020/2005/SWE/swe_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1462,756,"CHE","Switzerland","ppp_2005","GIS/Population/Global_2000_2020/2005/CHE/che_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1463,760,"SYR","Syria","ppp_2005","GIS/Population/Global_2000_2020/2005/SYR/syr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1464,762,"TJK","Tajikistan","ppp_2005","GIS/Population/Global_2000_2020/2005/TJK/tjk_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1465,764,"THA","Thailand","ppp_2005","GIS/Population/Global_2000_2020/2005/THA/tha_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1466,768,"TGO","Togo","ppp_2005","GIS/Population/Global_2000_2020/2005/TGO/tgo_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1467,772,"TKL","Tokelau","ppp_2005","GIS/Population/Global_2000_2020/2005/TKL/tkl_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1468,776,"TON","Tonga","ppp_2005","GIS/Population/Global_2000_2020/2005/TON/ton_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1469,780,"TTO","Trinidad and Tobago","ppp_2005","GIS/Population/Global_2000_2020/2005/TTO/tto_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1470,784,"ARE","United Arab Emirates","ppp_2005","GIS/Population/Global_2000_2020/2005/ARE/are_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1471,788,"TUN","Tunisia","ppp_2005","GIS/Population/Global_2000_2020/2005/TUN/tun_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1472,792,"TUR","Turkey","ppp_2005","GIS/Population/Global_2000_2020/2005/TUR/tur_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1473,795,"TKM","Turkmenistan","ppp_2005","GIS/Population/Global_2000_2020/2005/TKM/tkm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1474,796,"TCA","Turks and Caicos Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/TCA/tca_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1475,798,"TUV","Tuvalu","ppp_2005","GIS/Population/Global_2000_2020/2005/TUV/tuv_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1476,800,"UGA","Uganda","ppp_2005","GIS/Population/Global_2000_2020/2005/UGA/uga_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1477,804,"UKR","Ukraine","ppp_2005","GIS/Population/Global_2000_2020/2005/UKR/ukr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1478,807,"MKD","Macedonia","ppp_2005","GIS/Population/Global_2000_2020/2005/MKD/mkd_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1479,818,"EGY","Egypt","ppp_2005","GIS/Population/Global_2000_2020/2005/EGY/egy_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1480,826,"GBR","United Kingdom","ppp_2005","GIS/Population/Global_2000_2020/2005/GBR/gbr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1481,831,"GGY","Guernsey","ppp_2005","GIS/Population/Global_2000_2020/2005/GGY/ggy_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1482,832,"JEY","Jersey","ppp_2005","GIS/Population/Global_2000_2020/2005/JEY/jey_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1483,833,"IMN","Isle of Man","ppp_2005","GIS/Population/Global_2000_2020/2005/IMN/imn_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1484,834,"TZA","Tanzania","ppp_2005","GIS/Population/Global_2000_2020/2005/TZA/tza_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1485,854,"BFA","Burkina Faso","ppp_2005","GIS/Population/Global_2000_2020/2005/BFA/bfa_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1486,858,"URY","Uruguay","ppp_2005","GIS/Population/Global_2000_2020/2005/URY/ury_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1487,860,"UZB","Uzbekistan","ppp_2005","GIS/Population/Global_2000_2020/2005/UZB/uzb_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1488,862,"VEN","Venezuela","ppp_2005","GIS/Population/Global_2000_2020/2005/VEN/ven_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1489,876,"WLF","Wallis and Futuna","ppp_2005","GIS/Population/Global_2000_2020/2005/WLF/wlf_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1490,882,"WSM","Samoa","ppp_2005","GIS/Population/Global_2000_2020/2005/WSM/wsm_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1491,887,"YEM","Yemen","ppp_2005","GIS/Population/Global_2000_2020/2005/YEM/yem_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1492,894,"ZMB","Zambia","ppp_2005","GIS/Population/Global_2000_2020/2005/ZMB/zmb_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1493,900,"KOS","Kosovo","ppp_2005","GIS/Population/Global_2000_2020/2005/KOS/kos_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1494,901,"SPR","Spratly Islands","ppp_2005","GIS/Population/Global_2000_2020/2005/SPR/spr_ppp_2005.tif","Estimated total number of people per grid-cell 2005 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1495,643,"RUS","Russia","ppp_2006","GIS/Population/Global_2000_2020/2006/RUS/rus_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1496,360,"IDN","Indonesia","ppp_2006","GIS/Population/Global_2000_2020/2006/IDN/idn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1497,840,"USA","United States","ppp_2006","GIS/Population/Global_2000_2020/2006/USA/usa_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1498,850,"VIR","Virgin_Islands_U_S","ppp_2006","GIS/Population/Global_2000_2020/2006/VIR/vir_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1499,304,"GRL","Greenland","ppp_2006","GIS/Population/Global_2000_2020/2006/GRL/grl_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1500,156,"CHN","China","ppp_2006","GIS/Population/Global_2000_2020/2006/CHN/chn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1501,36,"AUS","Australia","ppp_2006","GIS/Population/Global_2000_2020/2006/AUS/aus_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1502,76,"BRA","Brazil","ppp_2006","GIS/Population/Global_2000_2020/2006/BRA/bra_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1503,124,"CAN","Canada","ppp_2006","GIS/Population/Global_2000_2020/2006/CAN/can_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1504,152,"CHL","Chile","ppp_2006","GIS/Population/Global_2000_2020/2006/CHL/chl_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1505,4,"AFG","Afghanistan","ppp_2006","GIS/Population/Global_2000_2020/2006/AFG/afg_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1506,8,"ALB","Albania","ppp_2006","GIS/Population/Global_2000_2020/2006/ALB/alb_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1507,10,"ATA","Antarctica","ppp_2006","GIS/Population/Global_2000_2020/2006/ATA/ata_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1508,12,"DZA","Algeria","ppp_2006","GIS/Population/Global_2000_2020/2006/DZA/dza_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1509,16,"ASM","American Samoa","ppp_2006","GIS/Population/Global_2000_2020/2006/ASM/asm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1510,20,"AND","Andorra","ppp_2006","GIS/Population/Global_2000_2020/2006/AND/and_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1511,24,"AGO","Angola","ppp_2006","GIS/Population/Global_2000_2020/2006/AGO/ago_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1512,28,"ATG","Antigua and Barbuda","ppp_2006","GIS/Population/Global_2000_2020/2006/ATG/atg_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1513,31,"AZE","Azerbaijan","ppp_2006","GIS/Population/Global_2000_2020/2006/AZE/aze_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1514,32,"ARG","Argentina","ppp_2006","GIS/Population/Global_2000_2020/2006/ARG/arg_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1515,40,"AUT","Austria","ppp_2006","GIS/Population/Global_2000_2020/2006/AUT/aut_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1516,44,"BHS","Bahamas","ppp_2006","GIS/Population/Global_2000_2020/2006/BHS/bhs_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1517,48,"BHR","Bahrain","ppp_2006","GIS/Population/Global_2000_2020/2006/BHR/bhr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1518,50,"BGD","Bangladesh","ppp_2006","GIS/Population/Global_2000_2020/2006/BGD/bgd_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1519,51,"ARM","Armenia","ppp_2006","GIS/Population/Global_2000_2020/2006/ARM/arm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1520,52,"BRB","Barbados","ppp_2006","GIS/Population/Global_2000_2020/2006/BRB/brb_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1521,56,"BEL","Belgium","ppp_2006","GIS/Population/Global_2000_2020/2006/BEL/bel_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1522,60,"BMU","Bermuda","ppp_2006","GIS/Population/Global_2000_2020/2006/BMU/bmu_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1523,64,"BTN","Bhutan","ppp_2006","GIS/Population/Global_2000_2020/2006/BTN/btn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1524,68,"BOL","Bolivia","ppp_2006","GIS/Population/Global_2000_2020/2006/BOL/bol_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1525,70,"BIH","Bosnia and Herzegovina","ppp_2006","GIS/Population/Global_2000_2020/2006/BIH/bih_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1526,72,"BWA","Botswana","ppp_2006","GIS/Population/Global_2000_2020/2006/BWA/bwa_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1527,74,"BVT","Bouvet Island","ppp_2006","GIS/Population/Global_2000_2020/2006/BVT/bvt_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1528,84,"BLZ","Belize","ppp_2006","GIS/Population/Global_2000_2020/2006/BLZ/blz_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1529,86,"IOT","British Indian Ocean Territory","ppp_2006","GIS/Population/Global_2000_2020/2006/IOT/iot_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1530,90,"SLB","Solomon Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/SLB/slb_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1531,92,"VGB","British Virgin Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/VGB/vgb_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1532,96,"BRN","Brunei","ppp_2006","GIS/Population/Global_2000_2020/2006/BRN/brn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1533,100,"BGR","Bulgaria","ppp_2006","GIS/Population/Global_2000_2020/2006/BGR/bgr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1534,104,"MMR","Myanmar","ppp_2006","GIS/Population/Global_2000_2020/2006/MMR/mmr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1535,108,"BDI","Burundi","ppp_2006","GIS/Population/Global_2000_2020/2006/BDI/bdi_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1536,112,"BLR","Belarus","ppp_2006","GIS/Population/Global_2000_2020/2006/BLR/blr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1537,116,"KHM","Cambodia","ppp_2006","GIS/Population/Global_2000_2020/2006/KHM/khm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1538,120,"CMR","Cameroon","ppp_2006","GIS/Population/Global_2000_2020/2006/CMR/cmr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1539,132,"CPV","Cape Verde","ppp_2006","GIS/Population/Global_2000_2020/2006/CPV/cpv_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1540,136,"CYM","Cayman Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/CYM/cym_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1541,140,"CAF","Central African Republic","ppp_2006","GIS/Population/Global_2000_2020/2006/CAF/caf_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1542,144,"LKA","Sri Lanka","ppp_2006","GIS/Population/Global_2000_2020/2006/LKA/lka_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1543,148,"TCD","Chad","ppp_2006","GIS/Population/Global_2000_2020/2006/TCD/tcd_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1544,158,"TWN","Taiwan","ppp_2006","GIS/Population/Global_2000_2020/2006/TWN/twn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1545,170,"COL","Colombia","ppp_2006","GIS/Population/Global_2000_2020/2006/COL/col_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1546,174,"COM","Comoros","ppp_2006","GIS/Population/Global_2000_2020/2006/COM/com_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1547,175,"MYT","Mayotte","ppp_2006","GIS/Population/Global_2000_2020/2006/MYT/myt_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1548,178,"COG","Republic of Congo","ppp_2006","GIS/Population/Global_2000_2020/2006/COG/cog_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1549,180,"COD","Democratic Republic of the Congo","ppp_2006","GIS/Population/Global_2000_2020/2006/COD/cod_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1550,184,"COK","Cook Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/COK/cok_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1551,188,"CRI","Costa Rica","ppp_2006","GIS/Population/Global_2000_2020/2006/CRI/cri_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1552,191,"HRV","Croatia","ppp_2006","GIS/Population/Global_2000_2020/2006/HRV/hrv_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1553,192,"CUB","Cuba","ppp_2006","GIS/Population/Global_2000_2020/2006/CUB/cub_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1554,196,"CYP","Cyprus","ppp_2006","GIS/Population/Global_2000_2020/2006/CYP/cyp_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1555,203,"CZE","Czech Republic","ppp_2006","GIS/Population/Global_2000_2020/2006/CZE/cze_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1556,204,"BEN","Benin","ppp_2006","GIS/Population/Global_2000_2020/2006/BEN/ben_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1557,208,"DNK","Denmark","ppp_2006","GIS/Population/Global_2000_2020/2006/DNK/dnk_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1558,212,"DMA","Dominica","ppp_2006","GIS/Population/Global_2000_2020/2006/DMA/dma_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1559,214,"DOM","Dominican Republic","ppp_2006","GIS/Population/Global_2000_2020/2006/DOM/dom_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1560,218,"ECU","Ecuador","ppp_2006","GIS/Population/Global_2000_2020/2006/ECU/ecu_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1561,222,"SLV","El Salvador","ppp_2006","GIS/Population/Global_2000_2020/2006/SLV/slv_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1562,226,"GNQ","Equatorial Guinea","ppp_2006","GIS/Population/Global_2000_2020/2006/GNQ/gnq_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1563,231,"ETH","Ethiopia","ppp_2006","GIS/Population/Global_2000_2020/2006/ETH/eth_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1564,232,"ERI","Eritrea","ppp_2006","GIS/Population/Global_2000_2020/2006/ERI/eri_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1565,233,"EST","Estonia","ppp_2006","GIS/Population/Global_2000_2020/2006/EST/est_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1566,234,"FRO","Faroe Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/FRO/fro_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1567,238,"FLK","Falkland Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/FLK/flk_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1568,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/SGS/sgs_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1569,242,"FJI","Fiji","ppp_2006","GIS/Population/Global_2000_2020/2006/FJI/fji_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1570,246,"FIN","Finland","ppp_2006","GIS/Population/Global_2000_2020/2006/FIN/fin_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1571,248,"ALA","Aland Islands ","ppp_2006","GIS/Population/Global_2000_2020/2006/ALA/ala_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1572,250,"FRA","France","ppp_2006","GIS/Population/Global_2000_2020/2006/FRA/fra_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1573,254,"GUF","French Guiana","ppp_2006","GIS/Population/Global_2000_2020/2006/GUF/guf_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1574,258,"PYF","French Polynesia","ppp_2006","GIS/Population/Global_2000_2020/2006/PYF/pyf_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1575,260,"ATF","French Southern Territories","ppp_2006","GIS/Population/Global_2000_2020/2006/ATF/atf_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1576,262,"DJI","Djibouti","ppp_2006","GIS/Population/Global_2000_2020/2006/DJI/dji_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1577,266,"GAB","Gabon","ppp_2006","GIS/Population/Global_2000_2020/2006/GAB/gab_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1578,268,"GEO","Georgia","ppp_2006","GIS/Population/Global_2000_2020/2006/GEO/geo_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1579,270,"GMB","Gambia","ppp_2006","GIS/Population/Global_2000_2020/2006/GMB/gmb_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1580,275,"PSE","Palestina","ppp_2006","GIS/Population/Global_2000_2020/2006/PSE/pse_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1581,276,"DEU","Germany","ppp_2006","GIS/Population/Global_2000_2020/2006/DEU/deu_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1582,288,"GHA","Ghana","ppp_2006","GIS/Population/Global_2000_2020/2006/GHA/gha_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1583,292,"GIB","Gibraltar","ppp_2006","GIS/Population/Global_2000_2020/2006/GIB/gib_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1584,296,"KIR","Kiribati","ppp_2006","GIS/Population/Global_2000_2020/2006/KIR/kir_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1585,300,"GRC","Greece","ppp_2006","GIS/Population/Global_2000_2020/2006/GRC/grc_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1586,308,"GRD","Grenada","ppp_2006","GIS/Population/Global_2000_2020/2006/GRD/grd_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1587,312,"GLP","Guadeloupe","ppp_2006","GIS/Population/Global_2000_2020/2006/GLP/glp_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1588,316,"GUM","Guam","ppp_2006","GIS/Population/Global_2000_2020/2006/GUM/gum_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1589,320,"GTM","Guatemala","ppp_2006","GIS/Population/Global_2000_2020/2006/GTM/gtm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1590,324,"GIN","Guinea","ppp_2006","GIS/Population/Global_2000_2020/2006/GIN/gin_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1591,328,"GUY","Guyana","ppp_2006","GIS/Population/Global_2000_2020/2006/GUY/guy_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1592,332,"HTI","Haiti","ppp_2006","GIS/Population/Global_2000_2020/2006/HTI/hti_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1593,334,"HMD","Heard Island and McDonald Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/HMD/hmd_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1594,336,"VAT","Vatican City","ppp_2006","GIS/Population/Global_2000_2020/2006/VAT/vat_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1595,340,"HND","Honduras","ppp_2006","GIS/Population/Global_2000_2020/2006/HND/hnd_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1596,344,"HKG","Hong Kong","ppp_2006","GIS/Population/Global_2000_2020/2006/HKG/hkg_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1597,348,"HUN","Hungary","ppp_2006","GIS/Population/Global_2000_2020/2006/HUN/hun_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1598,352,"ISL","Iceland","ppp_2006","GIS/Population/Global_2000_2020/2006/ISL/isl_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1599,356,"IND","India","ppp_2006","GIS/Population/Global_2000_2020/2006/IND/ind_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1600,364,"IRN","Iran","ppp_2006","GIS/Population/Global_2000_2020/2006/IRN/irn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1601,368,"IRQ","Iraq","ppp_2006","GIS/Population/Global_2000_2020/2006/IRQ/irq_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1602,372,"IRL","Ireland","ppp_2006","GIS/Population/Global_2000_2020/2006/IRL/irl_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1603,376,"ISR","Israel","ppp_2006","GIS/Population/Global_2000_2020/2006/ISR/isr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1604,380,"ITA","Italy","ppp_2006","GIS/Population/Global_2000_2020/2006/ITA/ita_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1605,384,"CIV","CIte dIvoire","ppp_2006","GIS/Population/Global_2000_2020/2006/CIV/civ_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1606,388,"JAM","Jamaica","ppp_2006","GIS/Population/Global_2000_2020/2006/JAM/jam_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1607,392,"JPN","Japan","ppp_2006","GIS/Population/Global_2000_2020/2006/JPN/jpn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1608,398,"KAZ","Kazakhstan","ppp_2006","GIS/Population/Global_2000_2020/2006/KAZ/kaz_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1609,400,"JOR","Jordan","ppp_2006","GIS/Population/Global_2000_2020/2006/JOR/jor_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1610,404,"KEN","Kenya","ppp_2006","GIS/Population/Global_2000_2020/2006/KEN/ken_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1611,408,"PRK","North Korea","ppp_2006","GIS/Population/Global_2000_2020/2006/PRK/prk_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1612,410,"KOR","South Korea","ppp_2006","GIS/Population/Global_2000_2020/2006/KOR/kor_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1613,414,"KWT","Kuwait","ppp_2006","GIS/Population/Global_2000_2020/2006/KWT/kwt_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1614,417,"KGZ","Kyrgyzstan","ppp_2006","GIS/Population/Global_2000_2020/2006/KGZ/kgz_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1615,418,"LAO","Laos","ppp_2006","GIS/Population/Global_2000_2020/2006/LAO/lao_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1616,422,"LBN","Lebanon","ppp_2006","GIS/Population/Global_2000_2020/2006/LBN/lbn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1617,426,"LSO","Lesotho","ppp_2006","GIS/Population/Global_2000_2020/2006/LSO/lso_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1618,428,"LVA","Latvia","ppp_2006","GIS/Population/Global_2000_2020/2006/LVA/lva_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1619,430,"LBR","Liberia","ppp_2006","GIS/Population/Global_2000_2020/2006/LBR/lbr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1620,434,"LBY","Libya","ppp_2006","GIS/Population/Global_2000_2020/2006/LBY/lby_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1621,438,"LIE","Liechtenstein","ppp_2006","GIS/Population/Global_2000_2020/2006/LIE/lie_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1622,440,"LTU","Lithuania","ppp_2006","GIS/Population/Global_2000_2020/2006/LTU/ltu_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1623,442,"LUX","Luxembourg","ppp_2006","GIS/Population/Global_2000_2020/2006/LUX/lux_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1624,446,"MAC","Macao","ppp_2006","GIS/Population/Global_2000_2020/2006/MAC/mac_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1625,450,"MDG","Madagascar","ppp_2006","GIS/Population/Global_2000_2020/2006/MDG/mdg_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1626,454,"MWI","Malawi","ppp_2006","GIS/Population/Global_2000_2020/2006/MWI/mwi_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1627,458,"MYS","Malaysia","ppp_2006","GIS/Population/Global_2000_2020/2006/MYS/mys_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1628,462,"MDV","Maldives","ppp_2006","GIS/Population/Global_2000_2020/2006/MDV/mdv_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1629,466,"MLI","Mali","ppp_2006","GIS/Population/Global_2000_2020/2006/MLI/mli_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1630,470,"MLT","Malta","ppp_2006","GIS/Population/Global_2000_2020/2006/MLT/mlt_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1631,474,"MTQ","Martinique","ppp_2006","GIS/Population/Global_2000_2020/2006/MTQ/mtq_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1632,478,"MRT","Mauritania","ppp_2006","GIS/Population/Global_2000_2020/2006/MRT/mrt_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1633,480,"MUS","Mauritius","ppp_2006","GIS/Population/Global_2000_2020/2006/MUS/mus_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1634,484,"MEX","Mexico","ppp_2006","GIS/Population/Global_2000_2020/2006/MEX/mex_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1635,492,"MCO","Monaco","ppp_2006","GIS/Population/Global_2000_2020/2006/MCO/mco_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1636,496,"MNG","Mongolia","ppp_2006","GIS/Population/Global_2000_2020/2006/MNG/mng_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1637,498,"MDA","Moldova","ppp_2006","GIS/Population/Global_2000_2020/2006/MDA/mda_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1638,499,"MNE","Montenegro","ppp_2006","GIS/Population/Global_2000_2020/2006/MNE/mne_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1639,500,"MSR","Montserrat","ppp_2006","GIS/Population/Global_2000_2020/2006/MSR/msr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1640,504,"MAR","Morocco","ppp_2006","GIS/Population/Global_2000_2020/2006/MAR/mar_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1641,508,"MOZ","Mozambique","ppp_2006","GIS/Population/Global_2000_2020/2006/MOZ/moz_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1642,512,"OMN","Oman","ppp_2006","GIS/Population/Global_2000_2020/2006/OMN/omn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1643,516,"NAM","Namibia","ppp_2006","GIS/Population/Global_2000_2020/2006/NAM/nam_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1644,520,"NRU","Nauru","ppp_2006","GIS/Population/Global_2000_2020/2006/NRU/nru_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1645,524,"NPL","Nepal","ppp_2006","GIS/Population/Global_2000_2020/2006/NPL/npl_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1646,528,"NLD","Netherlands","ppp_2006","GIS/Population/Global_2000_2020/2006/NLD/nld_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1647,531,"CUW","Curacao","ppp_2006","GIS/Population/Global_2000_2020/2006/CUW/cuw_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1648,533,"ABW","Aruba","ppp_2006","GIS/Population/Global_2000_2020/2006/ABW/abw_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1649,534,"SXM","Sint Maarten (Dutch part)","ppp_2006","GIS/Population/Global_2000_2020/2006/SXM/sxm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1650,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2006","GIS/Population/Global_2000_2020/2006/BES/bes_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1651,540,"NCL","New Caledonia","ppp_2006","GIS/Population/Global_2000_2020/2006/NCL/ncl_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1652,548,"VUT","Vanuatu","ppp_2006","GIS/Population/Global_2000_2020/2006/VUT/vut_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1653,554,"NZL","New Zealand","ppp_2006","GIS/Population/Global_2000_2020/2006/NZL/nzl_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1654,558,"NIC","Nicaragua","ppp_2006","GIS/Population/Global_2000_2020/2006/NIC/nic_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1655,562,"NER","Niger","ppp_2006","GIS/Population/Global_2000_2020/2006/NER/ner_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1656,566,"NGA","Nigeria","ppp_2006","GIS/Population/Global_2000_2020/2006/NGA/nga_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1657,570,"NIU","Niue","ppp_2006","GIS/Population/Global_2000_2020/2006/NIU/niu_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1658,574,"NFK","Norfolk Island","ppp_2006","GIS/Population/Global_2000_2020/2006/NFK/nfk_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1659,578,"NOR","Norway","ppp_2006","GIS/Population/Global_2000_2020/2006/NOR/nor_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1660,580,"MNP","Northern Mariana Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/MNP/mnp_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1661,581,"UMI","United States Minor Outlying Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/UMI/umi_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1662,583,"FSM","Micronesia","ppp_2006","GIS/Population/Global_2000_2020/2006/FSM/fsm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1663,584,"MHL","Marshall Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/MHL/mhl_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1664,585,"PLW","Palau","ppp_2006","GIS/Population/Global_2000_2020/2006/PLW/plw_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1665,586,"PAK","Pakistan","ppp_2006","GIS/Population/Global_2000_2020/2006/PAK/pak_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1666,591,"PAN","Panama","ppp_2006","GIS/Population/Global_2000_2020/2006/PAN/pan_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1667,598,"PNG","Papua New Guinea","ppp_2006","GIS/Population/Global_2000_2020/2006/PNG/png_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1668,600,"PRY","Paraguay","ppp_2006","GIS/Population/Global_2000_2020/2006/PRY/pry_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1669,604,"PER","Peru","ppp_2006","GIS/Population/Global_2000_2020/2006/PER/per_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1670,608,"PHL","Philippines","ppp_2006","GIS/Population/Global_2000_2020/2006/PHL/phl_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1671,612,"PCN","Pitcairn Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/PCN/pcn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1672,616,"POL","Poland","ppp_2006","GIS/Population/Global_2000_2020/2006/POL/pol_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1673,620,"PRT","Portugal","ppp_2006","GIS/Population/Global_2000_2020/2006/PRT/prt_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1674,624,"GNB","Guinea-Bissau","ppp_2006","GIS/Population/Global_2000_2020/2006/GNB/gnb_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1675,626,"TLS","East Timor","ppp_2006","GIS/Population/Global_2000_2020/2006/TLS/tls_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1676,630,"PRI","Puerto Rico","ppp_2006","GIS/Population/Global_2000_2020/2006/PRI/pri_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1677,634,"QAT","Qatar","ppp_2006","GIS/Population/Global_2000_2020/2006/QAT/qat_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1678,638,"REU","Reunion","ppp_2006","GIS/Population/Global_2000_2020/2006/REU/reu_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1679,642,"ROU","Romania","ppp_2006","GIS/Population/Global_2000_2020/2006/ROU/rou_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1680,646,"RWA","Rwanda","ppp_2006","GIS/Population/Global_2000_2020/2006/RWA/rwa_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1681,652,"BLM","Saint Barthelemy","ppp_2006","GIS/Population/Global_2000_2020/2006/BLM/blm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1682,654,"SHN","Saint Helena","ppp_2006","GIS/Population/Global_2000_2020/2006/SHN/shn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1683,659,"KNA","Saint Kitts and Nevis","ppp_2006","GIS/Population/Global_2000_2020/2006/KNA/kna_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1684,660,"AIA","Anguilla","ppp_2006","GIS/Population/Global_2000_2020/2006/AIA/aia_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1685,662,"LCA","Saint Lucia","ppp_2006","GIS/Population/Global_2000_2020/2006/LCA/lca_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1686,663,"MAF","Saint Martin (French part)","ppp_2006","GIS/Population/Global_2000_2020/2006/MAF/maf_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1687,666,"SPM","Saint Pierre and Miquelon","ppp_2006","GIS/Population/Global_2000_2020/2006/SPM/spm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1688,670,"VCT","Saint Vincent and the Grenadines","ppp_2006","GIS/Population/Global_2000_2020/2006/VCT/vct_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1689,674,"SMR","San Marino","ppp_2006","GIS/Population/Global_2000_2020/2006/SMR/smr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1690,678,"STP","Sao Tome and Principe","ppp_2006","GIS/Population/Global_2000_2020/2006/STP/stp_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1691,682,"SAU","Saudi Arabia","ppp_2006","GIS/Population/Global_2000_2020/2006/SAU/sau_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1692,686,"SEN","Senegal","ppp_2006","GIS/Population/Global_2000_2020/2006/SEN/sen_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1693,688,"SRB","Serbia","ppp_2006","GIS/Population/Global_2000_2020/2006/SRB/srb_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1694,690,"SYC","Seychelles","ppp_2006","GIS/Population/Global_2000_2020/2006/SYC/syc_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1695,694,"SLE","Sierra Leone","ppp_2006","GIS/Population/Global_2000_2020/2006/SLE/sle_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1696,702,"SGP","Singapore","ppp_2006","GIS/Population/Global_2000_2020/2006/SGP/sgp_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1697,703,"SVK","Slovakia","ppp_2006","GIS/Population/Global_2000_2020/2006/SVK/svk_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1698,704,"VNM","Vietnam","ppp_2006","GIS/Population/Global_2000_2020/2006/VNM/vnm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1699,705,"SVN","Slovenia","ppp_2006","GIS/Population/Global_2000_2020/2006/SVN/svn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1700,706,"SOM","Somalia","ppp_2006","GIS/Population/Global_2000_2020/2006/SOM/som_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1701,710,"ZAF","South Africa","ppp_2006","GIS/Population/Global_2000_2020/2006/ZAF/zaf_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1702,716,"ZWE","Zimbabwe","ppp_2006","GIS/Population/Global_2000_2020/2006/ZWE/zwe_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1703,724,"ESP","Spain","ppp_2006","GIS/Population/Global_2000_2020/2006/ESP/esp_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1704,728,"SSD","South Sudan","ppp_2006","GIS/Population/Global_2000_2020/2006/SSD/ssd_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1705,729,"SDN","Sudan","ppp_2006","GIS/Population/Global_2000_2020/2006/SDN/sdn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1706,732,"ESH","Western Sahara","ppp_2006","GIS/Population/Global_2000_2020/2006/ESH/esh_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1707,740,"SUR","Suriname","ppp_2006","GIS/Population/Global_2000_2020/2006/SUR/sur_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1708,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/SJM/sjm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1709,748,"SWZ","Swaziland","ppp_2006","GIS/Population/Global_2000_2020/2006/SWZ/swz_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1710,752,"SWE","Sweden","ppp_2006","GIS/Population/Global_2000_2020/2006/SWE/swe_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1711,756,"CHE","Switzerland","ppp_2006","GIS/Population/Global_2000_2020/2006/CHE/che_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1712,760,"SYR","Syria","ppp_2006","GIS/Population/Global_2000_2020/2006/SYR/syr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1713,762,"TJK","Tajikistan","ppp_2006","GIS/Population/Global_2000_2020/2006/TJK/tjk_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1714,764,"THA","Thailand","ppp_2006","GIS/Population/Global_2000_2020/2006/THA/tha_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1715,768,"TGO","Togo","ppp_2006","GIS/Population/Global_2000_2020/2006/TGO/tgo_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1716,772,"TKL","Tokelau","ppp_2006","GIS/Population/Global_2000_2020/2006/TKL/tkl_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1717,776,"TON","Tonga","ppp_2006","GIS/Population/Global_2000_2020/2006/TON/ton_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1718,780,"TTO","Trinidad and Tobago","ppp_2006","GIS/Population/Global_2000_2020/2006/TTO/tto_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1719,784,"ARE","United Arab Emirates","ppp_2006","GIS/Population/Global_2000_2020/2006/ARE/are_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1720,788,"TUN","Tunisia","ppp_2006","GIS/Population/Global_2000_2020/2006/TUN/tun_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1721,792,"TUR","Turkey","ppp_2006","GIS/Population/Global_2000_2020/2006/TUR/tur_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1722,795,"TKM","Turkmenistan","ppp_2006","GIS/Population/Global_2000_2020/2006/TKM/tkm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1723,796,"TCA","Turks and Caicos Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/TCA/tca_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1724,798,"TUV","Tuvalu","ppp_2006","GIS/Population/Global_2000_2020/2006/TUV/tuv_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1725,800,"UGA","Uganda","ppp_2006","GIS/Population/Global_2000_2020/2006/UGA/uga_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1726,804,"UKR","Ukraine","ppp_2006","GIS/Population/Global_2000_2020/2006/UKR/ukr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1727,807,"MKD","Macedonia","ppp_2006","GIS/Population/Global_2000_2020/2006/MKD/mkd_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1728,818,"EGY","Egypt","ppp_2006","GIS/Population/Global_2000_2020/2006/EGY/egy_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1729,826,"GBR","United Kingdom","ppp_2006","GIS/Population/Global_2000_2020/2006/GBR/gbr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1730,831,"GGY","Guernsey","ppp_2006","GIS/Population/Global_2000_2020/2006/GGY/ggy_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1731,832,"JEY","Jersey","ppp_2006","GIS/Population/Global_2000_2020/2006/JEY/jey_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1732,833,"IMN","Isle of Man","ppp_2006","GIS/Population/Global_2000_2020/2006/IMN/imn_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1733,834,"TZA","Tanzania","ppp_2006","GIS/Population/Global_2000_2020/2006/TZA/tza_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1734,854,"BFA","Burkina Faso","ppp_2006","GIS/Population/Global_2000_2020/2006/BFA/bfa_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1735,858,"URY","Uruguay","ppp_2006","GIS/Population/Global_2000_2020/2006/URY/ury_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1736,860,"UZB","Uzbekistan","ppp_2006","GIS/Population/Global_2000_2020/2006/UZB/uzb_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1737,862,"VEN","Venezuela","ppp_2006","GIS/Population/Global_2000_2020/2006/VEN/ven_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1738,876,"WLF","Wallis and Futuna","ppp_2006","GIS/Population/Global_2000_2020/2006/WLF/wlf_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1739,882,"WSM","Samoa","ppp_2006","GIS/Population/Global_2000_2020/2006/WSM/wsm_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1740,887,"YEM","Yemen","ppp_2006","GIS/Population/Global_2000_2020/2006/YEM/yem_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1741,894,"ZMB","Zambia","ppp_2006","GIS/Population/Global_2000_2020/2006/ZMB/zmb_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1742,900,"KOS","Kosovo","ppp_2006","GIS/Population/Global_2000_2020/2006/KOS/kos_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1743,901,"SPR","Spratly Islands","ppp_2006","GIS/Population/Global_2000_2020/2006/SPR/spr_ppp_2006.tif","Estimated total number of people per grid-cell 2006 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1744,643,"RUS","Russia","ppp_2007","GIS/Population/Global_2000_2020/2007/RUS/rus_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1745,360,"IDN","Indonesia","ppp_2007","GIS/Population/Global_2000_2020/2007/IDN/idn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1746,840,"USA","United States","ppp_2007","GIS/Population/Global_2000_2020/2007/USA/usa_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1747,850,"VIR","Virgin_Islands_U_S","ppp_2007","GIS/Population/Global_2000_2020/2007/VIR/vir_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1748,304,"GRL","Greenland","ppp_2007","GIS/Population/Global_2000_2020/2007/GRL/grl_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1749,156,"CHN","China","ppp_2007","GIS/Population/Global_2000_2020/2007/CHN/chn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1750,36,"AUS","Australia","ppp_2007","GIS/Population/Global_2000_2020/2007/AUS/aus_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1751,76,"BRA","Brazil","ppp_2007","GIS/Population/Global_2000_2020/2007/BRA/bra_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1752,124,"CAN","Canada","ppp_2007","GIS/Population/Global_2000_2020/2007/CAN/can_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1753,152,"CHL","Chile","ppp_2007","GIS/Population/Global_2000_2020/2007/CHL/chl_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1754,4,"AFG","Afghanistan","ppp_2007","GIS/Population/Global_2000_2020/2007/AFG/afg_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1755,8,"ALB","Albania","ppp_2007","GIS/Population/Global_2000_2020/2007/ALB/alb_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1756,10,"ATA","Antarctica","ppp_2007","GIS/Population/Global_2000_2020/2007/ATA/ata_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1757,12,"DZA","Algeria","ppp_2007","GIS/Population/Global_2000_2020/2007/DZA/dza_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1758,16,"ASM","American Samoa","ppp_2007","GIS/Population/Global_2000_2020/2007/ASM/asm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1759,20,"AND","Andorra","ppp_2007","GIS/Population/Global_2000_2020/2007/AND/and_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1760,24,"AGO","Angola","ppp_2007","GIS/Population/Global_2000_2020/2007/AGO/ago_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1761,28,"ATG","Antigua and Barbuda","ppp_2007","GIS/Population/Global_2000_2020/2007/ATG/atg_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1762,31,"AZE","Azerbaijan","ppp_2007","GIS/Population/Global_2000_2020/2007/AZE/aze_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1763,32,"ARG","Argentina","ppp_2007","GIS/Population/Global_2000_2020/2007/ARG/arg_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1764,40,"AUT","Austria","ppp_2007","GIS/Population/Global_2000_2020/2007/AUT/aut_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1765,44,"BHS","Bahamas","ppp_2007","GIS/Population/Global_2000_2020/2007/BHS/bhs_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1766,48,"BHR","Bahrain","ppp_2007","GIS/Population/Global_2000_2020/2007/BHR/bhr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1767,50,"BGD","Bangladesh","ppp_2007","GIS/Population/Global_2000_2020/2007/BGD/bgd_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1768,51,"ARM","Armenia","ppp_2007","GIS/Population/Global_2000_2020/2007/ARM/arm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1769,52,"BRB","Barbados","ppp_2007","GIS/Population/Global_2000_2020/2007/BRB/brb_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1770,56,"BEL","Belgium","ppp_2007","GIS/Population/Global_2000_2020/2007/BEL/bel_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1771,60,"BMU","Bermuda","ppp_2007","GIS/Population/Global_2000_2020/2007/BMU/bmu_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1772,64,"BTN","Bhutan","ppp_2007","GIS/Population/Global_2000_2020/2007/BTN/btn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1773,68,"BOL","Bolivia","ppp_2007","GIS/Population/Global_2000_2020/2007/BOL/bol_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1774,70,"BIH","Bosnia and Herzegovina","ppp_2007","GIS/Population/Global_2000_2020/2007/BIH/bih_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1775,72,"BWA","Botswana","ppp_2007","GIS/Population/Global_2000_2020/2007/BWA/bwa_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1776,74,"BVT","Bouvet Island","ppp_2007","GIS/Population/Global_2000_2020/2007/BVT/bvt_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1777,84,"BLZ","Belize","ppp_2007","GIS/Population/Global_2000_2020/2007/BLZ/blz_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1778,86,"IOT","British Indian Ocean Territory","ppp_2007","GIS/Population/Global_2000_2020/2007/IOT/iot_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1779,90,"SLB","Solomon Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/SLB/slb_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1780,92,"VGB","British Virgin Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/VGB/vgb_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1781,96,"BRN","Brunei","ppp_2007","GIS/Population/Global_2000_2020/2007/BRN/brn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1782,100,"BGR","Bulgaria","ppp_2007","GIS/Population/Global_2000_2020/2007/BGR/bgr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1783,104,"MMR","Myanmar","ppp_2007","GIS/Population/Global_2000_2020/2007/MMR/mmr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1784,108,"BDI","Burundi","ppp_2007","GIS/Population/Global_2000_2020/2007/BDI/bdi_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1785,112,"BLR","Belarus","ppp_2007","GIS/Population/Global_2000_2020/2007/BLR/blr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1786,116,"KHM","Cambodia","ppp_2007","GIS/Population/Global_2000_2020/2007/KHM/khm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1787,120,"CMR","Cameroon","ppp_2007","GIS/Population/Global_2000_2020/2007/CMR/cmr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1788,132,"CPV","Cape Verde","ppp_2007","GIS/Population/Global_2000_2020/2007/CPV/cpv_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1789,136,"CYM","Cayman Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/CYM/cym_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1790,140,"CAF","Central African Republic","ppp_2007","GIS/Population/Global_2000_2020/2007/CAF/caf_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1791,144,"LKA","Sri Lanka","ppp_2007","GIS/Population/Global_2000_2020/2007/LKA/lka_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1792,148,"TCD","Chad","ppp_2007","GIS/Population/Global_2000_2020/2007/TCD/tcd_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1793,158,"TWN","Taiwan","ppp_2007","GIS/Population/Global_2000_2020/2007/TWN/twn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1794,170,"COL","Colombia","ppp_2007","GIS/Population/Global_2000_2020/2007/COL/col_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1795,174,"COM","Comoros","ppp_2007","GIS/Population/Global_2000_2020/2007/COM/com_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1796,175,"MYT","Mayotte","ppp_2007","GIS/Population/Global_2000_2020/2007/MYT/myt_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1797,178,"COG","Republic of Congo","ppp_2007","GIS/Population/Global_2000_2020/2007/COG/cog_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1798,180,"COD","Democratic Republic of the Congo","ppp_2007","GIS/Population/Global_2000_2020/2007/COD/cod_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1799,184,"COK","Cook Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/COK/cok_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1800,188,"CRI","Costa Rica","ppp_2007","GIS/Population/Global_2000_2020/2007/CRI/cri_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1801,191,"HRV","Croatia","ppp_2007","GIS/Population/Global_2000_2020/2007/HRV/hrv_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1802,192,"CUB","Cuba","ppp_2007","GIS/Population/Global_2000_2020/2007/CUB/cub_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1803,196,"CYP","Cyprus","ppp_2007","GIS/Population/Global_2000_2020/2007/CYP/cyp_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1804,203,"CZE","Czech Republic","ppp_2007","GIS/Population/Global_2000_2020/2007/CZE/cze_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1805,204,"BEN","Benin","ppp_2007","GIS/Population/Global_2000_2020/2007/BEN/ben_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1806,208,"DNK","Denmark","ppp_2007","GIS/Population/Global_2000_2020/2007/DNK/dnk_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1807,212,"DMA","Dominica","ppp_2007","GIS/Population/Global_2000_2020/2007/DMA/dma_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1808,214,"DOM","Dominican Republic","ppp_2007","GIS/Population/Global_2000_2020/2007/DOM/dom_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1809,218,"ECU","Ecuador","ppp_2007","GIS/Population/Global_2000_2020/2007/ECU/ecu_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1810,222,"SLV","El Salvador","ppp_2007","GIS/Population/Global_2000_2020/2007/SLV/slv_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1811,226,"GNQ","Equatorial Guinea","ppp_2007","GIS/Population/Global_2000_2020/2007/GNQ/gnq_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1812,231,"ETH","Ethiopia","ppp_2007","GIS/Population/Global_2000_2020/2007/ETH/eth_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1813,232,"ERI","Eritrea","ppp_2007","GIS/Population/Global_2000_2020/2007/ERI/eri_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1814,233,"EST","Estonia","ppp_2007","GIS/Population/Global_2000_2020/2007/EST/est_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1815,234,"FRO","Faroe Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/FRO/fro_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1816,238,"FLK","Falkland Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/FLK/flk_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1817,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/SGS/sgs_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1818,242,"FJI","Fiji","ppp_2007","GIS/Population/Global_2000_2020/2007/FJI/fji_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1819,246,"FIN","Finland","ppp_2007","GIS/Population/Global_2000_2020/2007/FIN/fin_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1820,248,"ALA","Aland Islands ","ppp_2007","GIS/Population/Global_2000_2020/2007/ALA/ala_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1821,250,"FRA","France","ppp_2007","GIS/Population/Global_2000_2020/2007/FRA/fra_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1822,254,"GUF","French Guiana","ppp_2007","GIS/Population/Global_2000_2020/2007/GUF/guf_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1823,258,"PYF","French Polynesia","ppp_2007","GIS/Population/Global_2000_2020/2007/PYF/pyf_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1824,260,"ATF","French Southern Territories","ppp_2007","GIS/Population/Global_2000_2020/2007/ATF/atf_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1825,262,"DJI","Djibouti","ppp_2007","GIS/Population/Global_2000_2020/2007/DJI/dji_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1826,266,"GAB","Gabon","ppp_2007","GIS/Population/Global_2000_2020/2007/GAB/gab_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1827,268,"GEO","Georgia","ppp_2007","GIS/Population/Global_2000_2020/2007/GEO/geo_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1828,270,"GMB","Gambia","ppp_2007","GIS/Population/Global_2000_2020/2007/GMB/gmb_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1829,275,"PSE","Palestina","ppp_2007","GIS/Population/Global_2000_2020/2007/PSE/pse_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1830,276,"DEU","Germany","ppp_2007","GIS/Population/Global_2000_2020/2007/DEU/deu_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1831,288,"GHA","Ghana","ppp_2007","GIS/Population/Global_2000_2020/2007/GHA/gha_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1832,292,"GIB","Gibraltar","ppp_2007","GIS/Population/Global_2000_2020/2007/GIB/gib_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1833,296,"KIR","Kiribati","ppp_2007","GIS/Population/Global_2000_2020/2007/KIR/kir_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1834,300,"GRC","Greece","ppp_2007","GIS/Population/Global_2000_2020/2007/GRC/grc_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1835,308,"GRD","Grenada","ppp_2007","GIS/Population/Global_2000_2020/2007/GRD/grd_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1836,312,"GLP","Guadeloupe","ppp_2007","GIS/Population/Global_2000_2020/2007/GLP/glp_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1837,316,"GUM","Guam","ppp_2007","GIS/Population/Global_2000_2020/2007/GUM/gum_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1838,320,"GTM","Guatemala","ppp_2007","GIS/Population/Global_2000_2020/2007/GTM/gtm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1839,324,"GIN","Guinea","ppp_2007","GIS/Population/Global_2000_2020/2007/GIN/gin_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1840,328,"GUY","Guyana","ppp_2007","GIS/Population/Global_2000_2020/2007/GUY/guy_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1841,332,"HTI","Haiti","ppp_2007","GIS/Population/Global_2000_2020/2007/HTI/hti_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1842,334,"HMD","Heard Island and McDonald Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/HMD/hmd_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1843,336,"VAT","Vatican City","ppp_2007","GIS/Population/Global_2000_2020/2007/VAT/vat_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1844,340,"HND","Honduras","ppp_2007","GIS/Population/Global_2000_2020/2007/HND/hnd_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1845,344,"HKG","Hong Kong","ppp_2007","GIS/Population/Global_2000_2020/2007/HKG/hkg_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1846,348,"HUN","Hungary","ppp_2007","GIS/Population/Global_2000_2020/2007/HUN/hun_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1847,352,"ISL","Iceland","ppp_2007","GIS/Population/Global_2000_2020/2007/ISL/isl_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1848,356,"IND","India","ppp_2007","GIS/Population/Global_2000_2020/2007/IND/ind_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1849,364,"IRN","Iran","ppp_2007","GIS/Population/Global_2000_2020/2007/IRN/irn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1850,368,"IRQ","Iraq","ppp_2007","GIS/Population/Global_2000_2020/2007/IRQ/irq_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1851,372,"IRL","Ireland","ppp_2007","GIS/Population/Global_2000_2020/2007/IRL/irl_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1852,376,"ISR","Israel","ppp_2007","GIS/Population/Global_2000_2020/2007/ISR/isr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1853,380,"ITA","Italy","ppp_2007","GIS/Population/Global_2000_2020/2007/ITA/ita_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1854,384,"CIV","CIte dIvoire","ppp_2007","GIS/Population/Global_2000_2020/2007/CIV/civ_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1855,388,"JAM","Jamaica","ppp_2007","GIS/Population/Global_2000_2020/2007/JAM/jam_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1856,392,"JPN","Japan","ppp_2007","GIS/Population/Global_2000_2020/2007/JPN/jpn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1857,398,"KAZ","Kazakhstan","ppp_2007","GIS/Population/Global_2000_2020/2007/KAZ/kaz_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1858,400,"JOR","Jordan","ppp_2007","GIS/Population/Global_2000_2020/2007/JOR/jor_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1859,404,"KEN","Kenya","ppp_2007","GIS/Population/Global_2000_2020/2007/KEN/ken_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1860,408,"PRK","North Korea","ppp_2007","GIS/Population/Global_2000_2020/2007/PRK/prk_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1861,410,"KOR","South Korea","ppp_2007","GIS/Population/Global_2000_2020/2007/KOR/kor_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1862,414,"KWT","Kuwait","ppp_2007","GIS/Population/Global_2000_2020/2007/KWT/kwt_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1863,417,"KGZ","Kyrgyzstan","ppp_2007","GIS/Population/Global_2000_2020/2007/KGZ/kgz_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1864,418,"LAO","Laos","ppp_2007","GIS/Population/Global_2000_2020/2007/LAO/lao_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1865,422,"LBN","Lebanon","ppp_2007","GIS/Population/Global_2000_2020/2007/LBN/lbn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1866,426,"LSO","Lesotho","ppp_2007","GIS/Population/Global_2000_2020/2007/LSO/lso_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1867,428,"LVA","Latvia","ppp_2007","GIS/Population/Global_2000_2020/2007/LVA/lva_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1868,430,"LBR","Liberia","ppp_2007","GIS/Population/Global_2000_2020/2007/LBR/lbr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1869,434,"LBY","Libya","ppp_2007","GIS/Population/Global_2000_2020/2007/LBY/lby_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1870,438,"LIE","Liechtenstein","ppp_2007","GIS/Population/Global_2000_2020/2007/LIE/lie_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1871,440,"LTU","Lithuania","ppp_2007","GIS/Population/Global_2000_2020/2007/LTU/ltu_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1872,442,"LUX","Luxembourg","ppp_2007","GIS/Population/Global_2000_2020/2007/LUX/lux_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1873,446,"MAC","Macao","ppp_2007","GIS/Population/Global_2000_2020/2007/MAC/mac_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1874,450,"MDG","Madagascar","ppp_2007","GIS/Population/Global_2000_2020/2007/MDG/mdg_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1875,454,"MWI","Malawi","ppp_2007","GIS/Population/Global_2000_2020/2007/MWI/mwi_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1876,458,"MYS","Malaysia","ppp_2007","GIS/Population/Global_2000_2020/2007/MYS/mys_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1877,462,"MDV","Maldives","ppp_2007","GIS/Population/Global_2000_2020/2007/MDV/mdv_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1878,466,"MLI","Mali","ppp_2007","GIS/Population/Global_2000_2020/2007/MLI/mli_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1879,470,"MLT","Malta","ppp_2007","GIS/Population/Global_2000_2020/2007/MLT/mlt_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1880,474,"MTQ","Martinique","ppp_2007","GIS/Population/Global_2000_2020/2007/MTQ/mtq_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1881,478,"MRT","Mauritania","ppp_2007","GIS/Population/Global_2000_2020/2007/MRT/mrt_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1882,480,"MUS","Mauritius","ppp_2007","GIS/Population/Global_2000_2020/2007/MUS/mus_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1883,484,"MEX","Mexico","ppp_2007","GIS/Population/Global_2000_2020/2007/MEX/mex_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1884,492,"MCO","Monaco","ppp_2007","GIS/Population/Global_2000_2020/2007/MCO/mco_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1885,496,"MNG","Mongolia","ppp_2007","GIS/Population/Global_2000_2020/2007/MNG/mng_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1886,498,"MDA","Moldova","ppp_2007","GIS/Population/Global_2000_2020/2007/MDA/mda_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1887,499,"MNE","Montenegro","ppp_2007","GIS/Population/Global_2000_2020/2007/MNE/mne_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1888,500,"MSR","Montserrat","ppp_2007","GIS/Population/Global_2000_2020/2007/MSR/msr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1889,504,"MAR","Morocco","ppp_2007","GIS/Population/Global_2000_2020/2007/MAR/mar_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1890,508,"MOZ","Mozambique","ppp_2007","GIS/Population/Global_2000_2020/2007/MOZ/moz_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1891,512,"OMN","Oman","ppp_2007","GIS/Population/Global_2000_2020/2007/OMN/omn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1892,516,"NAM","Namibia","ppp_2007","GIS/Population/Global_2000_2020/2007/NAM/nam_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1893,520,"NRU","Nauru","ppp_2007","GIS/Population/Global_2000_2020/2007/NRU/nru_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1894,524,"NPL","Nepal","ppp_2007","GIS/Population/Global_2000_2020/2007/NPL/npl_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1895,528,"NLD","Netherlands","ppp_2007","GIS/Population/Global_2000_2020/2007/NLD/nld_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1896,531,"CUW","Curacao","ppp_2007","GIS/Population/Global_2000_2020/2007/CUW/cuw_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1897,533,"ABW","Aruba","ppp_2007","GIS/Population/Global_2000_2020/2007/ABW/abw_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1898,534,"SXM","Sint Maarten (Dutch part)","ppp_2007","GIS/Population/Global_2000_2020/2007/SXM/sxm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1899,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2007","GIS/Population/Global_2000_2020/2007/BES/bes_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1900,540,"NCL","New Caledonia","ppp_2007","GIS/Population/Global_2000_2020/2007/NCL/ncl_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1901,548,"VUT","Vanuatu","ppp_2007","GIS/Population/Global_2000_2020/2007/VUT/vut_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1902,554,"NZL","New Zealand","ppp_2007","GIS/Population/Global_2000_2020/2007/NZL/nzl_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1903,558,"NIC","Nicaragua","ppp_2007","GIS/Population/Global_2000_2020/2007/NIC/nic_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1904,562,"NER","Niger","ppp_2007","GIS/Population/Global_2000_2020/2007/NER/ner_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1905,566,"NGA","Nigeria","ppp_2007","GIS/Population/Global_2000_2020/2007/NGA/nga_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1906,570,"NIU","Niue","ppp_2007","GIS/Population/Global_2000_2020/2007/NIU/niu_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1907,574,"NFK","Norfolk Island","ppp_2007","GIS/Population/Global_2000_2020/2007/NFK/nfk_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1908,578,"NOR","Norway","ppp_2007","GIS/Population/Global_2000_2020/2007/NOR/nor_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1909,580,"MNP","Northern Mariana Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/MNP/mnp_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1910,581,"UMI","United States Minor Outlying Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/UMI/umi_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1911,583,"FSM","Micronesia","ppp_2007","GIS/Population/Global_2000_2020/2007/FSM/fsm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1912,584,"MHL","Marshall Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/MHL/mhl_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1913,585,"PLW","Palau","ppp_2007","GIS/Population/Global_2000_2020/2007/PLW/plw_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1914,586,"PAK","Pakistan","ppp_2007","GIS/Population/Global_2000_2020/2007/PAK/pak_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1915,591,"PAN","Panama","ppp_2007","GIS/Population/Global_2000_2020/2007/PAN/pan_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1916,598,"PNG","Papua New Guinea","ppp_2007","GIS/Population/Global_2000_2020/2007/PNG/png_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1917,600,"PRY","Paraguay","ppp_2007","GIS/Population/Global_2000_2020/2007/PRY/pry_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1918,604,"PER","Peru","ppp_2007","GIS/Population/Global_2000_2020/2007/PER/per_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1919,608,"PHL","Philippines","ppp_2007","GIS/Population/Global_2000_2020/2007/PHL/phl_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1920,612,"PCN","Pitcairn Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/PCN/pcn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1921,616,"POL","Poland","ppp_2007","GIS/Population/Global_2000_2020/2007/POL/pol_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1922,620,"PRT","Portugal","ppp_2007","GIS/Population/Global_2000_2020/2007/PRT/prt_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1923,624,"GNB","Guinea-Bissau","ppp_2007","GIS/Population/Global_2000_2020/2007/GNB/gnb_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1924,626,"TLS","East Timor","ppp_2007","GIS/Population/Global_2000_2020/2007/TLS/tls_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1925,630,"PRI","Puerto Rico","ppp_2007","GIS/Population/Global_2000_2020/2007/PRI/pri_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1926,634,"QAT","Qatar","ppp_2007","GIS/Population/Global_2000_2020/2007/QAT/qat_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1927,638,"REU","Reunion","ppp_2007","GIS/Population/Global_2000_2020/2007/REU/reu_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1928,642,"ROU","Romania","ppp_2007","GIS/Population/Global_2000_2020/2007/ROU/rou_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1929,646,"RWA","Rwanda","ppp_2007","GIS/Population/Global_2000_2020/2007/RWA/rwa_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1930,652,"BLM","Saint Barthelemy","ppp_2007","GIS/Population/Global_2000_2020/2007/BLM/blm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1931,654,"SHN","Saint Helena","ppp_2007","GIS/Population/Global_2000_2020/2007/SHN/shn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1932,659,"KNA","Saint Kitts and Nevis","ppp_2007","GIS/Population/Global_2000_2020/2007/KNA/kna_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1933,660,"AIA","Anguilla","ppp_2007","GIS/Population/Global_2000_2020/2007/AIA/aia_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1934,662,"LCA","Saint Lucia","ppp_2007","GIS/Population/Global_2000_2020/2007/LCA/lca_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1935,663,"MAF","Saint Martin (French part)","ppp_2007","GIS/Population/Global_2000_2020/2007/MAF/maf_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1936,666,"SPM","Saint Pierre and Miquelon","ppp_2007","GIS/Population/Global_2000_2020/2007/SPM/spm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1937,670,"VCT","Saint Vincent and the Grenadines","ppp_2007","GIS/Population/Global_2000_2020/2007/VCT/vct_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1938,674,"SMR","San Marino","ppp_2007","GIS/Population/Global_2000_2020/2007/SMR/smr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1939,678,"STP","Sao Tome and Principe","ppp_2007","GIS/Population/Global_2000_2020/2007/STP/stp_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1940,682,"SAU","Saudi Arabia","ppp_2007","GIS/Population/Global_2000_2020/2007/SAU/sau_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1941,686,"SEN","Senegal","ppp_2007","GIS/Population/Global_2000_2020/2007/SEN/sen_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1942,688,"SRB","Serbia","ppp_2007","GIS/Population/Global_2000_2020/2007/SRB/srb_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1943,690,"SYC","Seychelles","ppp_2007","GIS/Population/Global_2000_2020/2007/SYC/syc_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1944,694,"SLE","Sierra Leone","ppp_2007","GIS/Population/Global_2000_2020/2007/SLE/sle_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1945,702,"SGP","Singapore","ppp_2007","GIS/Population/Global_2000_2020/2007/SGP/sgp_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1946,703,"SVK","Slovakia","ppp_2007","GIS/Population/Global_2000_2020/2007/SVK/svk_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1947,704,"VNM","Vietnam","ppp_2007","GIS/Population/Global_2000_2020/2007/VNM/vnm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1948,705,"SVN","Slovenia","ppp_2007","GIS/Population/Global_2000_2020/2007/SVN/svn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1949,706,"SOM","Somalia","ppp_2007","GIS/Population/Global_2000_2020/2007/SOM/som_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1950,710,"ZAF","South Africa","ppp_2007","GIS/Population/Global_2000_2020/2007/ZAF/zaf_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1951,716,"ZWE","Zimbabwe","ppp_2007","GIS/Population/Global_2000_2020/2007/ZWE/zwe_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1952,724,"ESP","Spain","ppp_2007","GIS/Population/Global_2000_2020/2007/ESP/esp_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1953,728,"SSD","South Sudan","ppp_2007","GIS/Population/Global_2000_2020/2007/SSD/ssd_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1954,729,"SDN","Sudan","ppp_2007","GIS/Population/Global_2000_2020/2007/SDN/sdn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1955,732,"ESH","Western Sahara","ppp_2007","GIS/Population/Global_2000_2020/2007/ESH/esh_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1956,740,"SUR","Suriname","ppp_2007","GIS/Population/Global_2000_2020/2007/SUR/sur_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1957,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/SJM/sjm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1958,748,"SWZ","Swaziland","ppp_2007","GIS/Population/Global_2000_2020/2007/SWZ/swz_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1959,752,"SWE","Sweden","ppp_2007","GIS/Population/Global_2000_2020/2007/SWE/swe_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1960,756,"CHE","Switzerland","ppp_2007","GIS/Population/Global_2000_2020/2007/CHE/che_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1961,760,"SYR","Syria","ppp_2007","GIS/Population/Global_2000_2020/2007/SYR/syr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1962,762,"TJK","Tajikistan","ppp_2007","GIS/Population/Global_2000_2020/2007/TJK/tjk_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1963,764,"THA","Thailand","ppp_2007","GIS/Population/Global_2000_2020/2007/THA/tha_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1964,768,"TGO","Togo","ppp_2007","GIS/Population/Global_2000_2020/2007/TGO/tgo_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1965,772,"TKL","Tokelau","ppp_2007","GIS/Population/Global_2000_2020/2007/TKL/tkl_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1966,776,"TON","Tonga","ppp_2007","GIS/Population/Global_2000_2020/2007/TON/ton_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1967,780,"TTO","Trinidad and Tobago","ppp_2007","GIS/Population/Global_2000_2020/2007/TTO/tto_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1968,784,"ARE","United Arab Emirates","ppp_2007","GIS/Population/Global_2000_2020/2007/ARE/are_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1969,788,"TUN","Tunisia","ppp_2007","GIS/Population/Global_2000_2020/2007/TUN/tun_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1970,792,"TUR","Turkey","ppp_2007","GIS/Population/Global_2000_2020/2007/TUR/tur_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1971,795,"TKM","Turkmenistan","ppp_2007","GIS/Population/Global_2000_2020/2007/TKM/tkm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1972,796,"TCA","Turks and Caicos Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/TCA/tca_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1973,798,"TUV","Tuvalu","ppp_2007","GIS/Population/Global_2000_2020/2007/TUV/tuv_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1974,800,"UGA","Uganda","ppp_2007","GIS/Population/Global_2000_2020/2007/UGA/uga_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1975,804,"UKR","Ukraine","ppp_2007","GIS/Population/Global_2000_2020/2007/UKR/ukr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1976,807,"MKD","Macedonia","ppp_2007","GIS/Population/Global_2000_2020/2007/MKD/mkd_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1977,818,"EGY","Egypt","ppp_2007","GIS/Population/Global_2000_2020/2007/EGY/egy_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1978,826,"GBR","United Kingdom","ppp_2007","GIS/Population/Global_2000_2020/2007/GBR/gbr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1979,831,"GGY","Guernsey","ppp_2007","GIS/Population/Global_2000_2020/2007/GGY/ggy_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1980,832,"JEY","Jersey","ppp_2007","GIS/Population/Global_2000_2020/2007/JEY/jey_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1981,833,"IMN","Isle of Man","ppp_2007","GIS/Population/Global_2000_2020/2007/IMN/imn_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1982,834,"TZA","Tanzania","ppp_2007","GIS/Population/Global_2000_2020/2007/TZA/tza_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1983,854,"BFA","Burkina Faso","ppp_2007","GIS/Population/Global_2000_2020/2007/BFA/bfa_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1984,858,"URY","Uruguay","ppp_2007","GIS/Population/Global_2000_2020/2007/URY/ury_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1985,860,"UZB","Uzbekistan","ppp_2007","GIS/Population/Global_2000_2020/2007/UZB/uzb_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1986,862,"VEN","Venezuela","ppp_2007","GIS/Population/Global_2000_2020/2007/VEN/ven_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1987,876,"WLF","Wallis and Futuna","ppp_2007","GIS/Population/Global_2000_2020/2007/WLF/wlf_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1988,882,"WSM","Samoa","ppp_2007","GIS/Population/Global_2000_2020/2007/WSM/wsm_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1989,887,"YEM","Yemen","ppp_2007","GIS/Population/Global_2000_2020/2007/YEM/yem_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1990,894,"ZMB","Zambia","ppp_2007","GIS/Population/Global_2000_2020/2007/ZMB/zmb_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1991,900,"KOS","Kosovo","ppp_2007","GIS/Population/Global_2000_2020/2007/KOS/kos_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1992,901,"SPR","Spratly Islands","ppp_2007","GIS/Population/Global_2000_2020/2007/SPR/spr_ppp_2007.tif","Estimated total number of people per grid-cell 2007 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1993,643,"RUS","Russia","ppp_2008","GIS/Population/Global_2000_2020/2008/RUS/rus_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1994,360,"IDN","Indonesia","ppp_2008","GIS/Population/Global_2000_2020/2008/IDN/idn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1995,840,"USA","United States","ppp_2008","GIS/Population/Global_2000_2020/2008/USA/usa_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1996,850,"VIR","Virgin_Islands_U_S","ppp_2008","GIS/Population/Global_2000_2020/2008/VIR/vir_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1997,304,"GRL","Greenland","ppp_2008","GIS/Population/Global_2000_2020/2008/GRL/grl_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1998,156,"CHN","China","ppp_2008","GIS/Population/Global_2000_2020/2008/CHN/chn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
1999,36,"AUS","Australia","ppp_2008","GIS/Population/Global_2000_2020/2008/AUS/aus_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2000,76,"BRA","Brazil","ppp_2008","GIS/Population/Global_2000_2020/2008/BRA/bra_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2001,124,"CAN","Canada","ppp_2008","GIS/Population/Global_2000_2020/2008/CAN/can_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2002,152,"CHL","Chile","ppp_2008","GIS/Population/Global_2000_2020/2008/CHL/chl_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2003,4,"AFG","Afghanistan","ppp_2008","GIS/Population/Global_2000_2020/2008/AFG/afg_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2004,8,"ALB","Albania","ppp_2008","GIS/Population/Global_2000_2020/2008/ALB/alb_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2005,10,"ATA","Antarctica","ppp_2008","GIS/Population/Global_2000_2020/2008/ATA/ata_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2006,12,"DZA","Algeria","ppp_2008","GIS/Population/Global_2000_2020/2008/DZA/dza_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2007,16,"ASM","American Samoa","ppp_2008","GIS/Population/Global_2000_2020/2008/ASM/asm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2008,20,"AND","Andorra","ppp_2008","GIS/Population/Global_2000_2020/2008/AND/and_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2009,24,"AGO","Angola","ppp_2008","GIS/Population/Global_2000_2020/2008/AGO/ago_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2010,28,"ATG","Antigua and Barbuda","ppp_2008","GIS/Population/Global_2000_2020/2008/ATG/atg_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2011,31,"AZE","Azerbaijan","ppp_2008","GIS/Population/Global_2000_2020/2008/AZE/aze_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2012,32,"ARG","Argentina","ppp_2008","GIS/Population/Global_2000_2020/2008/ARG/arg_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2013,40,"AUT","Austria","ppp_2008","GIS/Population/Global_2000_2020/2008/AUT/aut_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2014,44,"BHS","Bahamas","ppp_2008","GIS/Population/Global_2000_2020/2008/BHS/bhs_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2015,48,"BHR","Bahrain","ppp_2008","GIS/Population/Global_2000_2020/2008/BHR/bhr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2016,50,"BGD","Bangladesh","ppp_2008","GIS/Population/Global_2000_2020/2008/BGD/bgd_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2017,51,"ARM","Armenia","ppp_2008","GIS/Population/Global_2000_2020/2008/ARM/arm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2018,52,"BRB","Barbados","ppp_2008","GIS/Population/Global_2000_2020/2008/BRB/brb_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2019,56,"BEL","Belgium","ppp_2008","GIS/Population/Global_2000_2020/2008/BEL/bel_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2020,60,"BMU","Bermuda","ppp_2008","GIS/Population/Global_2000_2020/2008/BMU/bmu_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2021,64,"BTN","Bhutan","ppp_2008","GIS/Population/Global_2000_2020/2008/BTN/btn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2022,68,"BOL","Bolivia","ppp_2008","GIS/Population/Global_2000_2020/2008/BOL/bol_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2023,70,"BIH","Bosnia and Herzegovina","ppp_2008","GIS/Population/Global_2000_2020/2008/BIH/bih_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2024,72,"BWA","Botswana","ppp_2008","GIS/Population/Global_2000_2020/2008/BWA/bwa_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2025,74,"BVT","Bouvet Island","ppp_2008","GIS/Population/Global_2000_2020/2008/BVT/bvt_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2026,84,"BLZ","Belize","ppp_2008","GIS/Population/Global_2000_2020/2008/BLZ/blz_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2027,86,"IOT","British Indian Ocean Territory","ppp_2008","GIS/Population/Global_2000_2020/2008/IOT/iot_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2028,90,"SLB","Solomon Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/SLB/slb_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2029,92,"VGB","British Virgin Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/VGB/vgb_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2030,96,"BRN","Brunei","ppp_2008","GIS/Population/Global_2000_2020/2008/BRN/brn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2031,100,"BGR","Bulgaria","ppp_2008","GIS/Population/Global_2000_2020/2008/BGR/bgr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2032,104,"MMR","Myanmar","ppp_2008","GIS/Population/Global_2000_2020/2008/MMR/mmr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2033,108,"BDI","Burundi","ppp_2008","GIS/Population/Global_2000_2020/2008/BDI/bdi_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2034,112,"BLR","Belarus","ppp_2008","GIS/Population/Global_2000_2020/2008/BLR/blr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2035,116,"KHM","Cambodia","ppp_2008","GIS/Population/Global_2000_2020/2008/KHM/khm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2036,120,"CMR","Cameroon","ppp_2008","GIS/Population/Global_2000_2020/2008/CMR/cmr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2037,132,"CPV","Cape Verde","ppp_2008","GIS/Population/Global_2000_2020/2008/CPV/cpv_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2038,136,"CYM","Cayman Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/CYM/cym_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2039,140,"CAF","Central African Republic","ppp_2008","GIS/Population/Global_2000_2020/2008/CAF/caf_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2040,144,"LKA","Sri Lanka","ppp_2008","GIS/Population/Global_2000_2020/2008/LKA/lka_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2041,148,"TCD","Chad","ppp_2008","GIS/Population/Global_2000_2020/2008/TCD/tcd_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2042,158,"TWN","Taiwan","ppp_2008","GIS/Population/Global_2000_2020/2008/TWN/twn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2043,170,"COL","Colombia","ppp_2008","GIS/Population/Global_2000_2020/2008/COL/col_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2044,174,"COM","Comoros","ppp_2008","GIS/Population/Global_2000_2020/2008/COM/com_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2045,175,"MYT","Mayotte","ppp_2008","GIS/Population/Global_2000_2020/2008/MYT/myt_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2046,178,"COG","Republic of Congo","ppp_2008","GIS/Population/Global_2000_2020/2008/COG/cog_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2047,180,"COD","Democratic Republic of the Congo","ppp_2008","GIS/Population/Global_2000_2020/2008/COD/cod_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2048,184,"COK","Cook Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/COK/cok_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2049,188,"CRI","Costa Rica","ppp_2008","GIS/Population/Global_2000_2020/2008/CRI/cri_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2050,191,"HRV","Croatia","ppp_2008","GIS/Population/Global_2000_2020/2008/HRV/hrv_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2051,192,"CUB","Cuba","ppp_2008","GIS/Population/Global_2000_2020/2008/CUB/cub_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2052,196,"CYP","Cyprus","ppp_2008","GIS/Population/Global_2000_2020/2008/CYP/cyp_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2053,203,"CZE","Czech Republic","ppp_2008","GIS/Population/Global_2000_2020/2008/CZE/cze_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2054,204,"BEN","Benin","ppp_2008","GIS/Population/Global_2000_2020/2008/BEN/ben_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2055,208,"DNK","Denmark","ppp_2008","GIS/Population/Global_2000_2020/2008/DNK/dnk_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2056,212,"DMA","Dominica","ppp_2008","GIS/Population/Global_2000_2020/2008/DMA/dma_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2057,214,"DOM","Dominican Republic","ppp_2008","GIS/Population/Global_2000_2020/2008/DOM/dom_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2058,218,"ECU","Ecuador","ppp_2008","GIS/Population/Global_2000_2020/2008/ECU/ecu_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2059,222,"SLV","El Salvador","ppp_2008","GIS/Population/Global_2000_2020/2008/SLV/slv_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2060,226,"GNQ","Equatorial Guinea","ppp_2008","GIS/Population/Global_2000_2020/2008/GNQ/gnq_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2061,231,"ETH","Ethiopia","ppp_2008","GIS/Population/Global_2000_2020/2008/ETH/eth_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2062,232,"ERI","Eritrea","ppp_2008","GIS/Population/Global_2000_2020/2008/ERI/eri_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2063,233,"EST","Estonia","ppp_2008","GIS/Population/Global_2000_2020/2008/EST/est_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2064,234,"FRO","Faroe Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/FRO/fro_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2065,238,"FLK","Falkland Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/FLK/flk_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2066,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/SGS/sgs_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2067,242,"FJI","Fiji","ppp_2008","GIS/Population/Global_2000_2020/2008/FJI/fji_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2068,246,"FIN","Finland","ppp_2008","GIS/Population/Global_2000_2020/2008/FIN/fin_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2069,248,"ALA","Aland Islands ","ppp_2008","GIS/Population/Global_2000_2020/2008/ALA/ala_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2070,250,"FRA","France","ppp_2008","GIS/Population/Global_2000_2020/2008/FRA/fra_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2071,254,"GUF","French Guiana","ppp_2008","GIS/Population/Global_2000_2020/2008/GUF/guf_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2072,258,"PYF","French Polynesia","ppp_2008","GIS/Population/Global_2000_2020/2008/PYF/pyf_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2073,260,"ATF","French Southern Territories","ppp_2008","GIS/Population/Global_2000_2020/2008/ATF/atf_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2074,262,"DJI","Djibouti","ppp_2008","GIS/Population/Global_2000_2020/2008/DJI/dji_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2075,266,"GAB","Gabon","ppp_2008","GIS/Population/Global_2000_2020/2008/GAB/gab_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2076,268,"GEO","Georgia","ppp_2008","GIS/Population/Global_2000_2020/2008/GEO/geo_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2077,270,"GMB","Gambia","ppp_2008","GIS/Population/Global_2000_2020/2008/GMB/gmb_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2078,275,"PSE","Palestina","ppp_2008","GIS/Population/Global_2000_2020/2008/PSE/pse_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2079,276,"DEU","Germany","ppp_2008","GIS/Population/Global_2000_2020/2008/DEU/deu_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2080,288,"GHA","Ghana","ppp_2008","GIS/Population/Global_2000_2020/2008/GHA/gha_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2081,292,"GIB","Gibraltar","ppp_2008","GIS/Population/Global_2000_2020/2008/GIB/gib_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2082,296,"KIR","Kiribati","ppp_2008","GIS/Population/Global_2000_2020/2008/KIR/kir_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2083,300,"GRC","Greece","ppp_2008","GIS/Population/Global_2000_2020/2008/GRC/grc_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2084,308,"GRD","Grenada","ppp_2008","GIS/Population/Global_2000_2020/2008/GRD/grd_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2085,312,"GLP","Guadeloupe","ppp_2008","GIS/Population/Global_2000_2020/2008/GLP/glp_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2086,316,"GUM","Guam","ppp_2008","GIS/Population/Global_2000_2020/2008/GUM/gum_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2087,320,"GTM","Guatemala","ppp_2008","GIS/Population/Global_2000_2020/2008/GTM/gtm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2088,324,"GIN","Guinea","ppp_2008","GIS/Population/Global_2000_2020/2008/GIN/gin_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2089,328,"GUY","Guyana","ppp_2008","GIS/Population/Global_2000_2020/2008/GUY/guy_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2090,332,"HTI","Haiti","ppp_2008","GIS/Population/Global_2000_2020/2008/HTI/hti_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2091,334,"HMD","Heard Island and McDonald Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/HMD/hmd_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2092,336,"VAT","Vatican City","ppp_2008","GIS/Population/Global_2000_2020/2008/VAT/vat_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2093,340,"HND","Honduras","ppp_2008","GIS/Population/Global_2000_2020/2008/HND/hnd_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2094,344,"HKG","Hong Kong","ppp_2008","GIS/Population/Global_2000_2020/2008/HKG/hkg_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2095,348,"HUN","Hungary","ppp_2008","GIS/Population/Global_2000_2020/2008/HUN/hun_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2096,352,"ISL","Iceland","ppp_2008","GIS/Population/Global_2000_2020/2008/ISL/isl_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2097,356,"IND","India","ppp_2008","GIS/Population/Global_2000_2020/2008/IND/ind_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2098,364,"IRN","Iran","ppp_2008","GIS/Population/Global_2000_2020/2008/IRN/irn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2099,368,"IRQ","Iraq","ppp_2008","GIS/Population/Global_2000_2020/2008/IRQ/irq_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2100,372,"IRL","Ireland","ppp_2008","GIS/Population/Global_2000_2020/2008/IRL/irl_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2101,376,"ISR","Israel","ppp_2008","GIS/Population/Global_2000_2020/2008/ISR/isr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2102,380,"ITA","Italy","ppp_2008","GIS/Population/Global_2000_2020/2008/ITA/ita_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2103,384,"CIV","CIte dIvoire","ppp_2008","GIS/Population/Global_2000_2020/2008/CIV/civ_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2104,388,"JAM","Jamaica","ppp_2008","GIS/Population/Global_2000_2020/2008/JAM/jam_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2105,392,"JPN","Japan","ppp_2008","GIS/Population/Global_2000_2020/2008/JPN/jpn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2106,398,"KAZ","Kazakhstan","ppp_2008","GIS/Population/Global_2000_2020/2008/KAZ/kaz_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2107,400,"JOR","Jordan","ppp_2008","GIS/Population/Global_2000_2020/2008/JOR/jor_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2108,404,"KEN","Kenya","ppp_2008","GIS/Population/Global_2000_2020/2008/KEN/ken_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2109,408,"PRK","North Korea","ppp_2008","GIS/Population/Global_2000_2020/2008/PRK/prk_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2110,410,"KOR","South Korea","ppp_2008","GIS/Population/Global_2000_2020/2008/KOR/kor_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2111,414,"KWT","Kuwait","ppp_2008","GIS/Population/Global_2000_2020/2008/KWT/kwt_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2112,417,"KGZ","Kyrgyzstan","ppp_2008","GIS/Population/Global_2000_2020/2008/KGZ/kgz_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2113,418,"LAO","Laos","ppp_2008","GIS/Population/Global_2000_2020/2008/LAO/lao_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2114,422,"LBN","Lebanon","ppp_2008","GIS/Population/Global_2000_2020/2008/LBN/lbn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2115,426,"LSO","Lesotho","ppp_2008","GIS/Population/Global_2000_2020/2008/LSO/lso_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2116,428,"LVA","Latvia","ppp_2008","GIS/Population/Global_2000_2020/2008/LVA/lva_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2117,430,"LBR","Liberia","ppp_2008","GIS/Population/Global_2000_2020/2008/LBR/lbr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2118,434,"LBY","Libya","ppp_2008","GIS/Population/Global_2000_2020/2008/LBY/lby_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2119,438,"LIE","Liechtenstein","ppp_2008","GIS/Population/Global_2000_2020/2008/LIE/lie_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2120,440,"LTU","Lithuania","ppp_2008","GIS/Population/Global_2000_2020/2008/LTU/ltu_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2121,442,"LUX","Luxembourg","ppp_2008","GIS/Population/Global_2000_2020/2008/LUX/lux_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2122,446,"MAC","Macao","ppp_2008","GIS/Population/Global_2000_2020/2008/MAC/mac_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2123,450,"MDG","Madagascar","ppp_2008","GIS/Population/Global_2000_2020/2008/MDG/mdg_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2124,454,"MWI","Malawi","ppp_2008","GIS/Population/Global_2000_2020/2008/MWI/mwi_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2125,458,"MYS","Malaysia","ppp_2008","GIS/Population/Global_2000_2020/2008/MYS/mys_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2126,462,"MDV","Maldives","ppp_2008","GIS/Population/Global_2000_2020/2008/MDV/mdv_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2127,466,"MLI","Mali","ppp_2008","GIS/Population/Global_2000_2020/2008/MLI/mli_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2128,470,"MLT","Malta","ppp_2008","GIS/Population/Global_2000_2020/2008/MLT/mlt_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2129,474,"MTQ","Martinique","ppp_2008","GIS/Population/Global_2000_2020/2008/MTQ/mtq_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2130,478,"MRT","Mauritania","ppp_2008","GIS/Population/Global_2000_2020/2008/MRT/mrt_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2131,480,"MUS","Mauritius","ppp_2008","GIS/Population/Global_2000_2020/2008/MUS/mus_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2132,484,"MEX","Mexico","ppp_2008","GIS/Population/Global_2000_2020/2008/MEX/mex_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2133,492,"MCO","Monaco","ppp_2008","GIS/Population/Global_2000_2020/2008/MCO/mco_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2134,496,"MNG","Mongolia","ppp_2008","GIS/Population/Global_2000_2020/2008/MNG/mng_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2135,498,"MDA","Moldova","ppp_2008","GIS/Population/Global_2000_2020/2008/MDA/mda_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2136,499,"MNE","Montenegro","ppp_2008","GIS/Population/Global_2000_2020/2008/MNE/mne_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2137,500,"MSR","Montserrat","ppp_2008","GIS/Population/Global_2000_2020/2008/MSR/msr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2138,504,"MAR","Morocco","ppp_2008","GIS/Population/Global_2000_2020/2008/MAR/mar_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2139,508,"MOZ","Mozambique","ppp_2008","GIS/Population/Global_2000_2020/2008/MOZ/moz_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2140,512,"OMN","Oman","ppp_2008","GIS/Population/Global_2000_2020/2008/OMN/omn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2141,516,"NAM","Namibia","ppp_2008","GIS/Population/Global_2000_2020/2008/NAM/nam_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2142,520,"NRU","Nauru","ppp_2008","GIS/Population/Global_2000_2020/2008/NRU/nru_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2143,524,"NPL","Nepal","ppp_2008","GIS/Population/Global_2000_2020/2008/NPL/npl_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2144,528,"NLD","Netherlands","ppp_2008","GIS/Population/Global_2000_2020/2008/NLD/nld_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2145,531,"CUW","Curacao","ppp_2008","GIS/Population/Global_2000_2020/2008/CUW/cuw_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2146,533,"ABW","Aruba","ppp_2008","GIS/Population/Global_2000_2020/2008/ABW/abw_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2147,534,"SXM","Sint Maarten (Dutch part)","ppp_2008","GIS/Population/Global_2000_2020/2008/SXM/sxm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2148,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2008","GIS/Population/Global_2000_2020/2008/BES/bes_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2149,540,"NCL","New Caledonia","ppp_2008","GIS/Population/Global_2000_2020/2008/NCL/ncl_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2150,548,"VUT","Vanuatu","ppp_2008","GIS/Population/Global_2000_2020/2008/VUT/vut_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2151,554,"NZL","New Zealand","ppp_2008","GIS/Population/Global_2000_2020/2008/NZL/nzl_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2152,558,"NIC","Nicaragua","ppp_2008","GIS/Population/Global_2000_2020/2008/NIC/nic_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2153,562,"NER","Niger","ppp_2008","GIS/Population/Global_2000_2020/2008/NER/ner_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2154,566,"NGA","Nigeria","ppp_2008","GIS/Population/Global_2000_2020/2008/NGA/nga_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2155,570,"NIU","Niue","ppp_2008","GIS/Population/Global_2000_2020/2008/NIU/niu_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2156,574,"NFK","Norfolk Island","ppp_2008","GIS/Population/Global_2000_2020/2008/NFK/nfk_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2157,578,"NOR","Norway","ppp_2008","GIS/Population/Global_2000_2020/2008/NOR/nor_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2158,580,"MNP","Northern Mariana Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/MNP/mnp_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2159,581,"UMI","United States Minor Outlying Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/UMI/umi_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2160,583,"FSM","Micronesia","ppp_2008","GIS/Population/Global_2000_2020/2008/FSM/fsm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2161,584,"MHL","Marshall Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/MHL/mhl_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2162,585,"PLW","Palau","ppp_2008","GIS/Population/Global_2000_2020/2008/PLW/plw_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2163,586,"PAK","Pakistan","ppp_2008","GIS/Population/Global_2000_2020/2008/PAK/pak_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2164,591,"PAN","Panama","ppp_2008","GIS/Population/Global_2000_2020/2008/PAN/pan_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2165,598,"PNG","Papua New Guinea","ppp_2008","GIS/Population/Global_2000_2020/2008/PNG/png_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2166,600,"PRY","Paraguay","ppp_2008","GIS/Population/Global_2000_2020/2008/PRY/pry_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2167,604,"PER","Peru","ppp_2008","GIS/Population/Global_2000_2020/2008/PER/per_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2168,608,"PHL","Philippines","ppp_2008","GIS/Population/Global_2000_2020/2008/PHL/phl_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2169,612,"PCN","Pitcairn Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/PCN/pcn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2170,616,"POL","Poland","ppp_2008","GIS/Population/Global_2000_2020/2008/POL/pol_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2171,620,"PRT","Portugal","ppp_2008","GIS/Population/Global_2000_2020/2008/PRT/prt_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2172,624,"GNB","Guinea-Bissau","ppp_2008","GIS/Population/Global_2000_2020/2008/GNB/gnb_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2173,626,"TLS","East Timor","ppp_2008","GIS/Population/Global_2000_2020/2008/TLS/tls_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2174,630,"PRI","Puerto Rico","ppp_2008","GIS/Population/Global_2000_2020/2008/PRI/pri_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2175,634,"QAT","Qatar","ppp_2008","GIS/Population/Global_2000_2020/2008/QAT/qat_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2176,638,"REU","Reunion","ppp_2008","GIS/Population/Global_2000_2020/2008/REU/reu_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2177,642,"ROU","Romania","ppp_2008","GIS/Population/Global_2000_2020/2008/ROU/rou_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2178,646,"RWA","Rwanda","ppp_2008","GIS/Population/Global_2000_2020/2008/RWA/rwa_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2179,652,"BLM","Saint Barthelemy","ppp_2008","GIS/Population/Global_2000_2020/2008/BLM/blm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2180,654,"SHN","Saint Helena","ppp_2008","GIS/Population/Global_2000_2020/2008/SHN/shn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2181,659,"KNA","Saint Kitts and Nevis","ppp_2008","GIS/Population/Global_2000_2020/2008/KNA/kna_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2182,660,"AIA","Anguilla","ppp_2008","GIS/Population/Global_2000_2020/2008/AIA/aia_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2183,662,"LCA","Saint Lucia","ppp_2008","GIS/Population/Global_2000_2020/2008/LCA/lca_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2184,663,"MAF","Saint Martin (French part)","ppp_2008","GIS/Population/Global_2000_2020/2008/MAF/maf_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2185,666,"SPM","Saint Pierre and Miquelon","ppp_2008","GIS/Population/Global_2000_2020/2008/SPM/spm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2186,670,"VCT","Saint Vincent and the Grenadines","ppp_2008","GIS/Population/Global_2000_2020/2008/VCT/vct_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2187,674,"SMR","San Marino","ppp_2008","GIS/Population/Global_2000_2020/2008/SMR/smr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2188,678,"STP","Sao Tome and Principe","ppp_2008","GIS/Population/Global_2000_2020/2008/STP/stp_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2189,682,"SAU","Saudi Arabia","ppp_2008","GIS/Population/Global_2000_2020/2008/SAU/sau_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2190,686,"SEN","Senegal","ppp_2008","GIS/Population/Global_2000_2020/2008/SEN/sen_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2191,688,"SRB","Serbia","ppp_2008","GIS/Population/Global_2000_2020/2008/SRB/srb_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2192,690,"SYC","Seychelles","ppp_2008","GIS/Population/Global_2000_2020/2008/SYC/syc_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2193,694,"SLE","Sierra Leone","ppp_2008","GIS/Population/Global_2000_2020/2008/SLE/sle_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2194,702,"SGP","Singapore","ppp_2008","GIS/Population/Global_2000_2020/2008/SGP/sgp_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2195,703,"SVK","Slovakia","ppp_2008","GIS/Population/Global_2000_2020/2008/SVK/svk_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2196,704,"VNM","Vietnam","ppp_2008","GIS/Population/Global_2000_2020/2008/VNM/vnm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2197,705,"SVN","Slovenia","ppp_2008","GIS/Population/Global_2000_2020/2008/SVN/svn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2198,706,"SOM","Somalia","ppp_2008","GIS/Population/Global_2000_2020/2008/SOM/som_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2199,710,"ZAF","South Africa","ppp_2008","GIS/Population/Global_2000_2020/2008/ZAF/zaf_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2200,716,"ZWE","Zimbabwe","ppp_2008","GIS/Population/Global_2000_2020/2008/ZWE/zwe_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2201,724,"ESP","Spain","ppp_2008","GIS/Population/Global_2000_2020/2008/ESP/esp_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2202,728,"SSD","South Sudan","ppp_2008","GIS/Population/Global_2000_2020/2008/SSD/ssd_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2203,729,"SDN","Sudan","ppp_2008","GIS/Population/Global_2000_2020/2008/SDN/sdn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2204,732,"ESH","Western Sahara","ppp_2008","GIS/Population/Global_2000_2020/2008/ESH/esh_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2205,740,"SUR","Suriname","ppp_2008","GIS/Population/Global_2000_2020/2008/SUR/sur_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2206,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/SJM/sjm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2207,748,"SWZ","Swaziland","ppp_2008","GIS/Population/Global_2000_2020/2008/SWZ/swz_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2208,752,"SWE","Sweden","ppp_2008","GIS/Population/Global_2000_2020/2008/SWE/swe_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2209,756,"CHE","Switzerland","ppp_2008","GIS/Population/Global_2000_2020/2008/CHE/che_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2210,760,"SYR","Syria","ppp_2008","GIS/Population/Global_2000_2020/2008/SYR/syr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2211,762,"TJK","Tajikistan","ppp_2008","GIS/Population/Global_2000_2020/2008/TJK/tjk_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2212,764,"THA","Thailand","ppp_2008","GIS/Population/Global_2000_2020/2008/THA/tha_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2213,768,"TGO","Togo","ppp_2008","GIS/Population/Global_2000_2020/2008/TGO/tgo_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2214,772,"TKL","Tokelau","ppp_2008","GIS/Population/Global_2000_2020/2008/TKL/tkl_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2215,776,"TON","Tonga","ppp_2008","GIS/Population/Global_2000_2020/2008/TON/ton_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2216,780,"TTO","Trinidad and Tobago","ppp_2008","GIS/Population/Global_2000_2020/2008/TTO/tto_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2217,784,"ARE","United Arab Emirates","ppp_2008","GIS/Population/Global_2000_2020/2008/ARE/are_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2218,788,"TUN","Tunisia","ppp_2008","GIS/Population/Global_2000_2020/2008/TUN/tun_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2219,792,"TUR","Turkey","ppp_2008","GIS/Population/Global_2000_2020/2008/TUR/tur_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2220,795,"TKM","Turkmenistan","ppp_2008","GIS/Population/Global_2000_2020/2008/TKM/tkm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2221,796,"TCA","Turks and Caicos Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/TCA/tca_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2222,798,"TUV","Tuvalu","ppp_2008","GIS/Population/Global_2000_2020/2008/TUV/tuv_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2223,800,"UGA","Uganda","ppp_2008","GIS/Population/Global_2000_2020/2008/UGA/uga_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2224,804,"UKR","Ukraine","ppp_2008","GIS/Population/Global_2000_2020/2008/UKR/ukr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2225,807,"MKD","Macedonia","ppp_2008","GIS/Population/Global_2000_2020/2008/MKD/mkd_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2226,818,"EGY","Egypt","ppp_2008","GIS/Population/Global_2000_2020/2008/EGY/egy_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2227,826,"GBR","United Kingdom","ppp_2008","GIS/Population/Global_2000_2020/2008/GBR/gbr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2228,831,"GGY","Guernsey","ppp_2008","GIS/Population/Global_2000_2020/2008/GGY/ggy_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2229,832,"JEY","Jersey","ppp_2008","GIS/Population/Global_2000_2020/2008/JEY/jey_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2230,833,"IMN","Isle of Man","ppp_2008","GIS/Population/Global_2000_2020/2008/IMN/imn_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2231,834,"TZA","Tanzania","ppp_2008","GIS/Population/Global_2000_2020/2008/TZA/tza_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2232,854,"BFA","Burkina Faso","ppp_2008","GIS/Population/Global_2000_2020/2008/BFA/bfa_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2233,858,"URY","Uruguay","ppp_2008","GIS/Population/Global_2000_2020/2008/URY/ury_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2234,860,"UZB","Uzbekistan","ppp_2008","GIS/Population/Global_2000_2020/2008/UZB/uzb_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2235,862,"VEN","Venezuela","ppp_2008","GIS/Population/Global_2000_2020/2008/VEN/ven_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2236,876,"WLF","Wallis and Futuna","ppp_2008","GIS/Population/Global_2000_2020/2008/WLF/wlf_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2237,882,"WSM","Samoa","ppp_2008","GIS/Population/Global_2000_2020/2008/WSM/wsm_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2238,887,"YEM","Yemen","ppp_2008","GIS/Population/Global_2000_2020/2008/YEM/yem_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2239,894,"ZMB","Zambia","ppp_2008","GIS/Population/Global_2000_2020/2008/ZMB/zmb_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2240,900,"KOS","Kosovo","ppp_2008","GIS/Population/Global_2000_2020/2008/KOS/kos_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2241,901,"SPR","Spratly Islands","ppp_2008","GIS/Population/Global_2000_2020/2008/SPR/spr_ppp_2008.tif","Estimated total number of people per grid-cell 2008 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2242,643,"RUS","Russia","ppp_2009","GIS/Population/Global_2000_2020/2009/RUS/rus_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2243,360,"IDN","Indonesia","ppp_2009","GIS/Population/Global_2000_2020/2009/IDN/idn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2244,840,"USA","United States","ppp_2009","GIS/Population/Global_2000_2020/2009/USA/usa_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2245,850,"VIR","Virgin_Islands_U_S","ppp_2009","GIS/Population/Global_2000_2020/2009/VIR/vir_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2246,304,"GRL","Greenland","ppp_2009","GIS/Population/Global_2000_2020/2009/GRL/grl_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2247,156,"CHN","China","ppp_2009","GIS/Population/Global_2000_2020/2009/CHN/chn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2248,36,"AUS","Australia","ppp_2009","GIS/Population/Global_2000_2020/2009/AUS/aus_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2249,76,"BRA","Brazil","ppp_2009","GIS/Population/Global_2000_2020/2009/BRA/bra_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2250,124,"CAN","Canada","ppp_2009","GIS/Population/Global_2000_2020/2009/CAN/can_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2251,152,"CHL","Chile","ppp_2009","GIS/Population/Global_2000_2020/2009/CHL/chl_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2252,4,"AFG","Afghanistan","ppp_2009","GIS/Population/Global_2000_2020/2009/AFG/afg_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2253,8,"ALB","Albania","ppp_2009","GIS/Population/Global_2000_2020/2009/ALB/alb_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2254,10,"ATA","Antarctica","ppp_2009","GIS/Population/Global_2000_2020/2009/ATA/ata_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2255,12,"DZA","Algeria","ppp_2009","GIS/Population/Global_2000_2020/2009/DZA/dza_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2256,16,"ASM","American Samoa","ppp_2009","GIS/Population/Global_2000_2020/2009/ASM/asm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2257,20,"AND","Andorra","ppp_2009","GIS/Population/Global_2000_2020/2009/AND/and_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2258,24,"AGO","Angola","ppp_2009","GIS/Population/Global_2000_2020/2009/AGO/ago_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2259,28,"ATG","Antigua and Barbuda","ppp_2009","GIS/Population/Global_2000_2020/2009/ATG/atg_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2260,31,"AZE","Azerbaijan","ppp_2009","GIS/Population/Global_2000_2020/2009/AZE/aze_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2261,32,"ARG","Argentina","ppp_2009","GIS/Population/Global_2000_2020/2009/ARG/arg_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2262,40,"AUT","Austria","ppp_2009","GIS/Population/Global_2000_2020/2009/AUT/aut_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2263,44,"BHS","Bahamas","ppp_2009","GIS/Population/Global_2000_2020/2009/BHS/bhs_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2264,48,"BHR","Bahrain","ppp_2009","GIS/Population/Global_2000_2020/2009/BHR/bhr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2265,50,"BGD","Bangladesh","ppp_2009","GIS/Population/Global_2000_2020/2009/BGD/bgd_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2266,51,"ARM","Armenia","ppp_2009","GIS/Population/Global_2000_2020/2009/ARM/arm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2267,52,"BRB","Barbados","ppp_2009","GIS/Population/Global_2000_2020/2009/BRB/brb_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2268,56,"BEL","Belgium","ppp_2009","GIS/Population/Global_2000_2020/2009/BEL/bel_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2269,60,"BMU","Bermuda","ppp_2009","GIS/Population/Global_2000_2020/2009/BMU/bmu_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2270,64,"BTN","Bhutan","ppp_2009","GIS/Population/Global_2000_2020/2009/BTN/btn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2271,68,"BOL","Bolivia","ppp_2009","GIS/Population/Global_2000_2020/2009/BOL/bol_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2272,70,"BIH","Bosnia and Herzegovina","ppp_2009","GIS/Population/Global_2000_2020/2009/BIH/bih_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2273,72,"BWA","Botswana","ppp_2009","GIS/Population/Global_2000_2020/2009/BWA/bwa_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2274,74,"BVT","Bouvet Island","ppp_2009","GIS/Population/Global_2000_2020/2009/BVT/bvt_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2275,84,"BLZ","Belize","ppp_2009","GIS/Population/Global_2000_2020/2009/BLZ/blz_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2276,86,"IOT","British Indian Ocean Territory","ppp_2009","GIS/Population/Global_2000_2020/2009/IOT/iot_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2277,90,"SLB","Solomon Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/SLB/slb_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2278,92,"VGB","British Virgin Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/VGB/vgb_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2279,96,"BRN","Brunei","ppp_2009","GIS/Population/Global_2000_2020/2009/BRN/brn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2280,100,"BGR","Bulgaria","ppp_2009","GIS/Population/Global_2000_2020/2009/BGR/bgr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2281,104,"MMR","Myanmar","ppp_2009","GIS/Population/Global_2000_2020/2009/MMR/mmr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2282,108,"BDI","Burundi","ppp_2009","GIS/Population/Global_2000_2020/2009/BDI/bdi_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2283,112,"BLR","Belarus","ppp_2009","GIS/Population/Global_2000_2020/2009/BLR/blr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2284,116,"KHM","Cambodia","ppp_2009","GIS/Population/Global_2000_2020/2009/KHM/khm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2285,120,"CMR","Cameroon","ppp_2009","GIS/Population/Global_2000_2020/2009/CMR/cmr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2286,132,"CPV","Cape Verde","ppp_2009","GIS/Population/Global_2000_2020/2009/CPV/cpv_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2287,136,"CYM","Cayman Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/CYM/cym_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2288,140,"CAF","Central African Republic","ppp_2009","GIS/Population/Global_2000_2020/2009/CAF/caf_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2289,144,"LKA","Sri Lanka","ppp_2009","GIS/Population/Global_2000_2020/2009/LKA/lka_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2290,148,"TCD","Chad","ppp_2009","GIS/Population/Global_2000_2020/2009/TCD/tcd_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2291,158,"TWN","Taiwan","ppp_2009","GIS/Population/Global_2000_2020/2009/TWN/twn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2292,170,"COL","Colombia","ppp_2009","GIS/Population/Global_2000_2020/2009/COL/col_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2293,174,"COM","Comoros","ppp_2009","GIS/Population/Global_2000_2020/2009/COM/com_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2294,175,"MYT","Mayotte","ppp_2009","GIS/Population/Global_2000_2020/2009/MYT/myt_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2295,178,"COG","Republic of Congo","ppp_2009","GIS/Population/Global_2000_2020/2009/COG/cog_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2296,180,"COD","Democratic Republic of the Congo","ppp_2009","GIS/Population/Global_2000_2020/2009/COD/cod_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2297,184,"COK","Cook Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/COK/cok_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2298,188,"CRI","Costa Rica","ppp_2009","GIS/Population/Global_2000_2020/2009/CRI/cri_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2299,191,"HRV","Croatia","ppp_2009","GIS/Population/Global_2000_2020/2009/HRV/hrv_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2300,192,"CUB","Cuba","ppp_2009","GIS/Population/Global_2000_2020/2009/CUB/cub_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2301,196,"CYP","Cyprus","ppp_2009","GIS/Population/Global_2000_2020/2009/CYP/cyp_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2302,203,"CZE","Czech Republic","ppp_2009","GIS/Population/Global_2000_2020/2009/CZE/cze_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2303,204,"BEN","Benin","ppp_2009","GIS/Population/Global_2000_2020/2009/BEN/ben_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2304,208,"DNK","Denmark","ppp_2009","GIS/Population/Global_2000_2020/2009/DNK/dnk_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2305,212,"DMA","Dominica","ppp_2009","GIS/Population/Global_2000_2020/2009/DMA/dma_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2306,214,"DOM","Dominican Republic","ppp_2009","GIS/Population/Global_2000_2020/2009/DOM/dom_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2307,218,"ECU","Ecuador","ppp_2009","GIS/Population/Global_2000_2020/2009/ECU/ecu_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2308,222,"SLV","El Salvador","ppp_2009","GIS/Population/Global_2000_2020/2009/SLV/slv_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2309,226,"GNQ","Equatorial Guinea","ppp_2009","GIS/Population/Global_2000_2020/2009/GNQ/gnq_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2310,231,"ETH","Ethiopia","ppp_2009","GIS/Population/Global_2000_2020/2009/ETH/eth_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2311,232,"ERI","Eritrea","ppp_2009","GIS/Population/Global_2000_2020/2009/ERI/eri_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2312,233,"EST","Estonia","ppp_2009","GIS/Population/Global_2000_2020/2009/EST/est_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2313,234,"FRO","Faroe Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/FRO/fro_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2314,238,"FLK","Falkland Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/FLK/flk_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2315,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/SGS/sgs_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2316,242,"FJI","Fiji","ppp_2009","GIS/Population/Global_2000_2020/2009/FJI/fji_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2317,246,"FIN","Finland","ppp_2009","GIS/Population/Global_2000_2020/2009/FIN/fin_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2318,248,"ALA","Aland Islands ","ppp_2009","GIS/Population/Global_2000_2020/2009/ALA/ala_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2319,250,"FRA","France","ppp_2009","GIS/Population/Global_2000_2020/2009/FRA/fra_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2320,254,"GUF","French Guiana","ppp_2009","GIS/Population/Global_2000_2020/2009/GUF/guf_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2321,258,"PYF","French Polynesia","ppp_2009","GIS/Population/Global_2000_2020/2009/PYF/pyf_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2322,260,"ATF","French Southern Territories","ppp_2009","GIS/Population/Global_2000_2020/2009/ATF/atf_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2323,262,"DJI","Djibouti","ppp_2009","GIS/Population/Global_2000_2020/2009/DJI/dji_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2324,266,"GAB","Gabon","ppp_2009","GIS/Population/Global_2000_2020/2009/GAB/gab_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2325,268,"GEO","Georgia","ppp_2009","GIS/Population/Global_2000_2020/2009/GEO/geo_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2326,270,"GMB","Gambia","ppp_2009","GIS/Population/Global_2000_2020/2009/GMB/gmb_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2327,275,"PSE","Palestina","ppp_2009","GIS/Population/Global_2000_2020/2009/PSE/pse_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2328,276,"DEU","Germany","ppp_2009","GIS/Population/Global_2000_2020/2009/DEU/deu_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2329,288,"GHA","Ghana","ppp_2009","GIS/Population/Global_2000_2020/2009/GHA/gha_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2330,292,"GIB","Gibraltar","ppp_2009","GIS/Population/Global_2000_2020/2009/GIB/gib_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2331,296,"KIR","Kiribati","ppp_2009","GIS/Population/Global_2000_2020/2009/KIR/kir_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2332,300,"GRC","Greece","ppp_2009","GIS/Population/Global_2000_2020/2009/GRC/grc_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2333,308,"GRD","Grenada","ppp_2009","GIS/Population/Global_2000_2020/2009/GRD/grd_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2334,312,"GLP","Guadeloupe","ppp_2009","GIS/Population/Global_2000_2020/2009/GLP/glp_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2335,316,"GUM","Guam","ppp_2009","GIS/Population/Global_2000_2020/2009/GUM/gum_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2336,320,"GTM","Guatemala","ppp_2009","GIS/Population/Global_2000_2020/2009/GTM/gtm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2337,324,"GIN","Guinea","ppp_2009","GIS/Population/Global_2000_2020/2009/GIN/gin_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2338,328,"GUY","Guyana","ppp_2009","GIS/Population/Global_2000_2020/2009/GUY/guy_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2339,332,"HTI","Haiti","ppp_2009","GIS/Population/Global_2000_2020/2009/HTI/hti_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2340,334,"HMD","Heard Island and McDonald Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/HMD/hmd_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2341,336,"VAT","Vatican City","ppp_2009","GIS/Population/Global_2000_2020/2009/VAT/vat_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2342,340,"HND","Honduras","ppp_2009","GIS/Population/Global_2000_2020/2009/HND/hnd_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2343,344,"HKG","Hong Kong","ppp_2009","GIS/Population/Global_2000_2020/2009/HKG/hkg_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2344,348,"HUN","Hungary","ppp_2009","GIS/Population/Global_2000_2020/2009/HUN/hun_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2345,352,"ISL","Iceland","ppp_2009","GIS/Population/Global_2000_2020/2009/ISL/isl_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2346,356,"IND","India","ppp_2009","GIS/Population/Global_2000_2020/2009/IND/ind_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2347,364,"IRN","Iran","ppp_2009","GIS/Population/Global_2000_2020/2009/IRN/irn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2348,368,"IRQ","Iraq","ppp_2009","GIS/Population/Global_2000_2020/2009/IRQ/irq_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2349,372,"IRL","Ireland","ppp_2009","GIS/Population/Global_2000_2020/2009/IRL/irl_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2350,376,"ISR","Israel","ppp_2009","GIS/Population/Global_2000_2020/2009/ISR/isr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2351,380,"ITA","Italy","ppp_2009","GIS/Population/Global_2000_2020/2009/ITA/ita_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2352,384,"CIV","CIte dIvoire","ppp_2009","GIS/Population/Global_2000_2020/2009/CIV/civ_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2353,388,"JAM","Jamaica","ppp_2009","GIS/Population/Global_2000_2020/2009/JAM/jam_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2354,392,"JPN","Japan","ppp_2009","GIS/Population/Global_2000_2020/2009/JPN/jpn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2355,398,"KAZ","Kazakhstan","ppp_2009","GIS/Population/Global_2000_2020/2009/KAZ/kaz_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2356,400,"JOR","Jordan","ppp_2009","GIS/Population/Global_2000_2020/2009/JOR/jor_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2357,404,"KEN","Kenya","ppp_2009","GIS/Population/Global_2000_2020/2009/KEN/ken_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2358,408,"PRK","North Korea","ppp_2009","GIS/Population/Global_2000_2020/2009/PRK/prk_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2359,410,"KOR","South Korea","ppp_2009","GIS/Population/Global_2000_2020/2009/KOR/kor_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2360,414,"KWT","Kuwait","ppp_2009","GIS/Population/Global_2000_2020/2009/KWT/kwt_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2361,417,"KGZ","Kyrgyzstan","ppp_2009","GIS/Population/Global_2000_2020/2009/KGZ/kgz_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2362,418,"LAO","Laos","ppp_2009","GIS/Population/Global_2000_2020/2009/LAO/lao_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2363,422,"LBN","Lebanon","ppp_2009","GIS/Population/Global_2000_2020/2009/LBN/lbn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2364,426,"LSO","Lesotho","ppp_2009","GIS/Population/Global_2000_2020/2009/LSO/lso_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2365,428,"LVA","Latvia","ppp_2009","GIS/Population/Global_2000_2020/2009/LVA/lva_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2366,430,"LBR","Liberia","ppp_2009","GIS/Population/Global_2000_2020/2009/LBR/lbr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2367,434,"LBY","Libya","ppp_2009","GIS/Population/Global_2000_2020/2009/LBY/lby_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2368,438,"LIE","Liechtenstein","ppp_2009","GIS/Population/Global_2000_2020/2009/LIE/lie_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2369,440,"LTU","Lithuania","ppp_2009","GIS/Population/Global_2000_2020/2009/LTU/ltu_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2370,442,"LUX","Luxembourg","ppp_2009","GIS/Population/Global_2000_2020/2009/LUX/lux_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2371,446,"MAC","Macao","ppp_2009","GIS/Population/Global_2000_2020/2009/MAC/mac_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2372,450,"MDG","Madagascar","ppp_2009","GIS/Population/Global_2000_2020/2009/MDG/mdg_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2373,454,"MWI","Malawi","ppp_2009","GIS/Population/Global_2000_2020/2009/MWI/mwi_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2374,458,"MYS","Malaysia","ppp_2009","GIS/Population/Global_2000_2020/2009/MYS/mys_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2375,462,"MDV","Maldives","ppp_2009","GIS/Population/Global_2000_2020/2009/MDV/mdv_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2376,466,"MLI","Mali","ppp_2009","GIS/Population/Global_2000_2020/2009/MLI/mli_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2377,470,"MLT","Malta","ppp_2009","GIS/Population/Global_2000_2020/2009/MLT/mlt_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2378,474,"MTQ","Martinique","ppp_2009","GIS/Population/Global_2000_2020/2009/MTQ/mtq_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2379,478,"MRT","Mauritania","ppp_2009","GIS/Population/Global_2000_2020/2009/MRT/mrt_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2380,480,"MUS","Mauritius","ppp_2009","GIS/Population/Global_2000_2020/2009/MUS/mus_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2381,484,"MEX","Mexico","ppp_2009","GIS/Population/Global_2000_2020/2009/MEX/mex_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2382,492,"MCO","Monaco","ppp_2009","GIS/Population/Global_2000_2020/2009/MCO/mco_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2383,496,"MNG","Mongolia","ppp_2009","GIS/Population/Global_2000_2020/2009/MNG/mng_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2384,498,"MDA","Moldova","ppp_2009","GIS/Population/Global_2000_2020/2009/MDA/mda_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2385,499,"MNE","Montenegro","ppp_2009","GIS/Population/Global_2000_2020/2009/MNE/mne_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2386,500,"MSR","Montserrat","ppp_2009","GIS/Population/Global_2000_2020/2009/MSR/msr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2387,504,"MAR","Morocco","ppp_2009","GIS/Population/Global_2000_2020/2009/MAR/mar_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2388,508,"MOZ","Mozambique","ppp_2009","GIS/Population/Global_2000_2020/2009/MOZ/moz_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2389,512,"OMN","Oman","ppp_2009","GIS/Population/Global_2000_2020/2009/OMN/omn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2390,516,"NAM","Namibia","ppp_2009","GIS/Population/Global_2000_2020/2009/NAM/nam_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2391,520,"NRU","Nauru","ppp_2009","GIS/Population/Global_2000_2020/2009/NRU/nru_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2392,524,"NPL","Nepal","ppp_2009","GIS/Population/Global_2000_2020/2009/NPL/npl_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2393,528,"NLD","Netherlands","ppp_2009","GIS/Population/Global_2000_2020/2009/NLD/nld_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2394,531,"CUW","Curacao","ppp_2009","GIS/Population/Global_2000_2020/2009/CUW/cuw_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2395,533,"ABW","Aruba","ppp_2009","GIS/Population/Global_2000_2020/2009/ABW/abw_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2396,534,"SXM","Sint Maarten (Dutch part)","ppp_2009","GIS/Population/Global_2000_2020/2009/SXM/sxm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2397,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2009","GIS/Population/Global_2000_2020/2009/BES/bes_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2398,540,"NCL","New Caledonia","ppp_2009","GIS/Population/Global_2000_2020/2009/NCL/ncl_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2399,548,"VUT","Vanuatu","ppp_2009","GIS/Population/Global_2000_2020/2009/VUT/vut_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2400,554,"NZL","New Zealand","ppp_2009","GIS/Population/Global_2000_2020/2009/NZL/nzl_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2401,558,"NIC","Nicaragua","ppp_2009","GIS/Population/Global_2000_2020/2009/NIC/nic_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2402,562,"NER","Niger","ppp_2009","GIS/Population/Global_2000_2020/2009/NER/ner_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2403,566,"NGA","Nigeria","ppp_2009","GIS/Population/Global_2000_2020/2009/NGA/nga_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2404,570,"NIU","Niue","ppp_2009","GIS/Population/Global_2000_2020/2009/NIU/niu_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2405,574,"NFK","Norfolk Island","ppp_2009","GIS/Population/Global_2000_2020/2009/NFK/nfk_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2406,578,"NOR","Norway","ppp_2009","GIS/Population/Global_2000_2020/2009/NOR/nor_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2407,580,"MNP","Northern Mariana Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/MNP/mnp_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2408,581,"UMI","United States Minor Outlying Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/UMI/umi_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2409,583,"FSM","Micronesia","ppp_2009","GIS/Population/Global_2000_2020/2009/FSM/fsm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2410,584,"MHL","Marshall Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/MHL/mhl_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2411,585,"PLW","Palau","ppp_2009","GIS/Population/Global_2000_2020/2009/PLW/plw_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2412,586,"PAK","Pakistan","ppp_2009","GIS/Population/Global_2000_2020/2009/PAK/pak_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2413,591,"PAN","Panama","ppp_2009","GIS/Population/Global_2000_2020/2009/PAN/pan_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2414,598,"PNG","Papua New Guinea","ppp_2009","GIS/Population/Global_2000_2020/2009/PNG/png_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2415,600,"PRY","Paraguay","ppp_2009","GIS/Population/Global_2000_2020/2009/PRY/pry_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2416,604,"PER","Peru","ppp_2009","GIS/Population/Global_2000_2020/2009/PER/per_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2417,608,"PHL","Philippines","ppp_2009","GIS/Population/Global_2000_2020/2009/PHL/phl_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2418,612,"PCN","Pitcairn Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/PCN/pcn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2419,616,"POL","Poland","ppp_2009","GIS/Population/Global_2000_2020/2009/POL/pol_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2420,620,"PRT","Portugal","ppp_2009","GIS/Population/Global_2000_2020/2009/PRT/prt_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2421,624,"GNB","Guinea-Bissau","ppp_2009","GIS/Population/Global_2000_2020/2009/GNB/gnb_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2422,626,"TLS","East Timor","ppp_2009","GIS/Population/Global_2000_2020/2009/TLS/tls_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2423,630,"PRI","Puerto Rico","ppp_2009","GIS/Population/Global_2000_2020/2009/PRI/pri_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2424,634,"QAT","Qatar","ppp_2009","GIS/Population/Global_2000_2020/2009/QAT/qat_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2425,638,"REU","Reunion","ppp_2009","GIS/Population/Global_2000_2020/2009/REU/reu_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2426,642,"ROU","Romania","ppp_2009","GIS/Population/Global_2000_2020/2009/ROU/rou_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2427,646,"RWA","Rwanda","ppp_2009","GIS/Population/Global_2000_2020/2009/RWA/rwa_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2428,652,"BLM","Saint Barthelemy","ppp_2009","GIS/Population/Global_2000_2020/2009/BLM/blm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2429,654,"SHN","Saint Helena","ppp_2009","GIS/Population/Global_2000_2020/2009/SHN/shn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2430,659,"KNA","Saint Kitts and Nevis","ppp_2009","GIS/Population/Global_2000_2020/2009/KNA/kna_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2431,660,"AIA","Anguilla","ppp_2009","GIS/Population/Global_2000_2020/2009/AIA/aia_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2432,662,"LCA","Saint Lucia","ppp_2009","GIS/Population/Global_2000_2020/2009/LCA/lca_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2433,663,"MAF","Saint Martin (French part)","ppp_2009","GIS/Population/Global_2000_2020/2009/MAF/maf_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2434,666,"SPM","Saint Pierre and Miquelon","ppp_2009","GIS/Population/Global_2000_2020/2009/SPM/spm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2435,670,"VCT","Saint Vincent and the Grenadines","ppp_2009","GIS/Population/Global_2000_2020/2009/VCT/vct_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2436,674,"SMR","San Marino","ppp_2009","GIS/Population/Global_2000_2020/2009/SMR/smr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2437,678,"STP","Sao Tome and Principe","ppp_2009","GIS/Population/Global_2000_2020/2009/STP/stp_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2438,682,"SAU","Saudi Arabia","ppp_2009","GIS/Population/Global_2000_2020/2009/SAU/sau_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2439,686,"SEN","Senegal","ppp_2009","GIS/Population/Global_2000_2020/2009/SEN/sen_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2440,688,"SRB","Serbia","ppp_2009","GIS/Population/Global_2000_2020/2009/SRB/srb_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2441,690,"SYC","Seychelles","ppp_2009","GIS/Population/Global_2000_2020/2009/SYC/syc_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2442,694,"SLE","Sierra Leone","ppp_2009","GIS/Population/Global_2000_2020/2009/SLE/sle_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2443,702,"SGP","Singapore","ppp_2009","GIS/Population/Global_2000_2020/2009/SGP/sgp_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2444,703,"SVK","Slovakia","ppp_2009","GIS/Population/Global_2000_2020/2009/SVK/svk_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2445,704,"VNM","Vietnam","ppp_2009","GIS/Population/Global_2000_2020/2009/VNM/vnm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2446,705,"SVN","Slovenia","ppp_2009","GIS/Population/Global_2000_2020/2009/SVN/svn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2447,706,"SOM","Somalia","ppp_2009","GIS/Population/Global_2000_2020/2009/SOM/som_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2448,710,"ZAF","South Africa","ppp_2009","GIS/Population/Global_2000_2020/2009/ZAF/zaf_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2449,716,"ZWE","Zimbabwe","ppp_2009","GIS/Population/Global_2000_2020/2009/ZWE/zwe_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2450,724,"ESP","Spain","ppp_2009","GIS/Population/Global_2000_2020/2009/ESP/esp_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2451,728,"SSD","South Sudan","ppp_2009","GIS/Population/Global_2000_2020/2009/SSD/ssd_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2452,729,"SDN","Sudan","ppp_2009","GIS/Population/Global_2000_2020/2009/SDN/sdn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2453,732,"ESH","Western Sahara","ppp_2009","GIS/Population/Global_2000_2020/2009/ESH/esh_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2454,740,"SUR","Suriname","ppp_2009","GIS/Population/Global_2000_2020/2009/SUR/sur_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2455,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/SJM/sjm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2456,748,"SWZ","Swaziland","ppp_2009","GIS/Population/Global_2000_2020/2009/SWZ/swz_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2457,752,"SWE","Sweden","ppp_2009","GIS/Population/Global_2000_2020/2009/SWE/swe_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2458,756,"CHE","Switzerland","ppp_2009","GIS/Population/Global_2000_2020/2009/CHE/che_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2459,760,"SYR","Syria","ppp_2009","GIS/Population/Global_2000_2020/2009/SYR/syr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2460,762,"TJK","Tajikistan","ppp_2009","GIS/Population/Global_2000_2020/2009/TJK/tjk_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2461,764,"THA","Thailand","ppp_2009","GIS/Population/Global_2000_2020/2009/THA/tha_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2462,768,"TGO","Togo","ppp_2009","GIS/Population/Global_2000_2020/2009/TGO/tgo_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2463,772,"TKL","Tokelau","ppp_2009","GIS/Population/Global_2000_2020/2009/TKL/tkl_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2464,776,"TON","Tonga","ppp_2009","GIS/Population/Global_2000_2020/2009/TON/ton_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2465,780,"TTO","Trinidad and Tobago","ppp_2009","GIS/Population/Global_2000_2020/2009/TTO/tto_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2466,784,"ARE","United Arab Emirates","ppp_2009","GIS/Population/Global_2000_2020/2009/ARE/are_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2467,788,"TUN","Tunisia","ppp_2009","GIS/Population/Global_2000_2020/2009/TUN/tun_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2468,792,"TUR","Turkey","ppp_2009","GIS/Population/Global_2000_2020/2009/TUR/tur_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2469,795,"TKM","Turkmenistan","ppp_2009","GIS/Population/Global_2000_2020/2009/TKM/tkm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2470,796,"TCA","Turks and Caicos Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/TCA/tca_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2471,798,"TUV","Tuvalu","ppp_2009","GIS/Population/Global_2000_2020/2009/TUV/tuv_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2472,800,"UGA","Uganda","ppp_2009","GIS/Population/Global_2000_2020/2009/UGA/uga_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2473,804,"UKR","Ukraine","ppp_2009","GIS/Population/Global_2000_2020/2009/UKR/ukr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2474,807,"MKD","Macedonia","ppp_2009","GIS/Population/Global_2000_2020/2009/MKD/mkd_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2475,818,"EGY","Egypt","ppp_2009","GIS/Population/Global_2000_2020/2009/EGY/egy_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2476,826,"GBR","United Kingdom","ppp_2009","GIS/Population/Global_2000_2020/2009/GBR/gbr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2477,831,"GGY","Guernsey","ppp_2009","GIS/Population/Global_2000_2020/2009/GGY/ggy_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2478,832,"JEY","Jersey","ppp_2009","GIS/Population/Global_2000_2020/2009/JEY/jey_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2479,833,"IMN","Isle of Man","ppp_2009","GIS/Population/Global_2000_2020/2009/IMN/imn_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2480,834,"TZA","Tanzania","ppp_2009","GIS/Population/Global_2000_2020/2009/TZA/tza_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2481,854,"BFA","Burkina Faso","ppp_2009","GIS/Population/Global_2000_2020/2009/BFA/bfa_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2482,858,"URY","Uruguay","ppp_2009","GIS/Population/Global_2000_2020/2009/URY/ury_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2483,860,"UZB","Uzbekistan","ppp_2009","GIS/Population/Global_2000_2020/2009/UZB/uzb_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2484,862,"VEN","Venezuela","ppp_2009","GIS/Population/Global_2000_2020/2009/VEN/ven_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2485,876,"WLF","Wallis and Futuna","ppp_2009","GIS/Population/Global_2000_2020/2009/WLF/wlf_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2486,882,"WSM","Samoa","ppp_2009","GIS/Population/Global_2000_2020/2009/WSM/wsm_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2487,887,"YEM","Yemen","ppp_2009","GIS/Population/Global_2000_2020/2009/YEM/yem_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2488,894,"ZMB","Zambia","ppp_2009","GIS/Population/Global_2000_2020/2009/ZMB/zmb_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2489,900,"KOS","Kosovo","ppp_2009","GIS/Population/Global_2000_2020/2009/KOS/kos_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2490,901,"SPR","Spratly Islands","ppp_2009","GIS/Population/Global_2000_2020/2009/SPR/spr_ppp_2009.tif","Estimated total number of people per grid-cell 2009 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2491,643,"RUS","Russia","ppp_2010","GIS/Population/Global_2000_2020/2010/RUS/rus_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2492,360,"IDN","Indonesia","ppp_2010","GIS/Population/Global_2000_2020/2010/IDN/idn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2493,840,"USA","United States","ppp_2010","GIS/Population/Global_2000_2020/2010/USA/usa_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2494,850,"VIR","Virgin_Islands_U_S","ppp_2010","GIS/Population/Global_2000_2020/2010/VIR/vir_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2495,304,"GRL","Greenland","ppp_2010","GIS/Population/Global_2000_2020/2010/GRL/grl_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2496,156,"CHN","China","ppp_2010","GIS/Population/Global_2000_2020/2010/CHN/chn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2497,36,"AUS","Australia","ppp_2010","GIS/Population/Global_2000_2020/2010/AUS/aus_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2498,76,"BRA","Brazil","ppp_2010","GIS/Population/Global_2000_2020/2010/BRA/bra_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2499,124,"CAN","Canada","ppp_2010","GIS/Population/Global_2000_2020/2010/CAN/can_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2500,152,"CHL","Chile","ppp_2010","GIS/Population/Global_2000_2020/2010/CHL/chl_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2501,4,"AFG","Afghanistan","ppp_2010","GIS/Population/Global_2000_2020/2010/AFG/afg_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2502,8,"ALB","Albania","ppp_2010","GIS/Population/Global_2000_2020/2010/ALB/alb_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2503,10,"ATA","Antarctica","ppp_2010","GIS/Population/Global_2000_2020/2010/ATA/ata_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2504,12,"DZA","Algeria","ppp_2010","GIS/Population/Global_2000_2020/2010/DZA/dza_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2505,16,"ASM","American Samoa","ppp_2010","GIS/Population/Global_2000_2020/2010/ASM/asm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2506,20,"AND","Andorra","ppp_2010","GIS/Population/Global_2000_2020/2010/AND/and_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2507,24,"AGO","Angola","ppp_2010","GIS/Population/Global_2000_2020/2010/AGO/ago_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2508,28,"ATG","Antigua and Barbuda","ppp_2010","GIS/Population/Global_2000_2020/2010/ATG/atg_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2509,31,"AZE","Azerbaijan","ppp_2010","GIS/Population/Global_2000_2020/2010/AZE/aze_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2510,32,"ARG","Argentina","ppp_2010","GIS/Population/Global_2000_2020/2010/ARG/arg_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2511,40,"AUT","Austria","ppp_2010","GIS/Population/Global_2000_2020/2010/AUT/aut_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2512,44,"BHS","Bahamas","ppp_2010","GIS/Population/Global_2000_2020/2010/BHS/bhs_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2513,48,"BHR","Bahrain","ppp_2010","GIS/Population/Global_2000_2020/2010/BHR/bhr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2514,50,"BGD","Bangladesh","ppp_2010","GIS/Population/Global_2000_2020/2010/BGD/bgd_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2515,51,"ARM","Armenia","ppp_2010","GIS/Population/Global_2000_2020/2010/ARM/arm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2516,52,"BRB","Barbados","ppp_2010","GIS/Population/Global_2000_2020/2010/BRB/brb_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2517,56,"BEL","Belgium","ppp_2010","GIS/Population/Global_2000_2020/2010/BEL/bel_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2518,60,"BMU","Bermuda","ppp_2010","GIS/Population/Global_2000_2020/2010/BMU/bmu_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2519,64,"BTN","Bhutan","ppp_2010","GIS/Population/Global_2000_2020/2010/BTN/btn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2520,68,"BOL","Bolivia","ppp_2010","GIS/Population/Global_2000_2020/2010/BOL/bol_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2521,70,"BIH","Bosnia and Herzegovina","ppp_2010","GIS/Population/Global_2000_2020/2010/BIH/bih_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2522,72,"BWA","Botswana","ppp_2010","GIS/Population/Global_2000_2020/2010/BWA/bwa_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2523,74,"BVT","Bouvet Island","ppp_2010","GIS/Population/Global_2000_2020/2010/BVT/bvt_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2524,84,"BLZ","Belize","ppp_2010","GIS/Population/Global_2000_2020/2010/BLZ/blz_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2525,86,"IOT","British Indian Ocean Territory","ppp_2010","GIS/Population/Global_2000_2020/2010/IOT/iot_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2526,90,"SLB","Solomon Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/SLB/slb_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2527,92,"VGB","British Virgin Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/VGB/vgb_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2528,96,"BRN","Brunei","ppp_2010","GIS/Population/Global_2000_2020/2010/BRN/brn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2529,100,"BGR","Bulgaria","ppp_2010","GIS/Population/Global_2000_2020/2010/BGR/bgr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2530,104,"MMR","Myanmar","ppp_2010","GIS/Population/Global_2000_2020/2010/MMR/mmr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2531,108,"BDI","Burundi","ppp_2010","GIS/Population/Global_2000_2020/2010/BDI/bdi_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2532,112,"BLR","Belarus","ppp_2010","GIS/Population/Global_2000_2020/2010/BLR/blr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2533,116,"KHM","Cambodia","ppp_2010","GIS/Population/Global_2000_2020/2010/KHM/khm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2534,120,"CMR","Cameroon","ppp_2010","GIS/Population/Global_2000_2020/2010/CMR/cmr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2535,132,"CPV","Cape Verde","ppp_2010","GIS/Population/Global_2000_2020/2010/CPV/cpv_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2536,136,"CYM","Cayman Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/CYM/cym_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2537,140,"CAF","Central African Republic","ppp_2010","GIS/Population/Global_2000_2020/2010/CAF/caf_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2538,144,"LKA","Sri Lanka","ppp_2010","GIS/Population/Global_2000_2020/2010/LKA/lka_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2539,148,"TCD","Chad","ppp_2010","GIS/Population/Global_2000_2020/2010/TCD/tcd_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2540,158,"TWN","Taiwan","ppp_2010","GIS/Population/Global_2000_2020/2010/TWN/twn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2541,170,"COL","Colombia","ppp_2010","GIS/Population/Global_2000_2020/2010/COL/col_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2542,174,"COM","Comoros","ppp_2010","GIS/Population/Global_2000_2020/2010/COM/com_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2543,175,"MYT","Mayotte","ppp_2010","GIS/Population/Global_2000_2020/2010/MYT/myt_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2544,178,"COG","Republic of Congo","ppp_2010","GIS/Population/Global_2000_2020/2010/COG/cog_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2545,180,"COD","Democratic Republic of the Congo","ppp_2010","GIS/Population/Global_2000_2020/2010/COD/cod_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2546,184,"COK","Cook Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/COK/cok_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2547,188,"CRI","Costa Rica","ppp_2010","GIS/Population/Global_2000_2020/2010/CRI/cri_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2548,191,"HRV","Croatia","ppp_2010","GIS/Population/Global_2000_2020/2010/HRV/hrv_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2549,192,"CUB","Cuba","ppp_2010","GIS/Population/Global_2000_2020/2010/CUB/cub_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2550,196,"CYP","Cyprus","ppp_2010","GIS/Population/Global_2000_2020/2010/CYP/cyp_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2551,203,"CZE","Czech Republic","ppp_2010","GIS/Population/Global_2000_2020/2010/CZE/cze_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2552,204,"BEN","Benin","ppp_2010","GIS/Population/Global_2000_2020/2010/BEN/ben_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2553,208,"DNK","Denmark","ppp_2010","GIS/Population/Global_2000_2020/2010/DNK/dnk_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2554,212,"DMA","Dominica","ppp_2010","GIS/Population/Global_2000_2020/2010/DMA/dma_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2555,214,"DOM","Dominican Republic","ppp_2010","GIS/Population/Global_2000_2020/2010/DOM/dom_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2556,218,"ECU","Ecuador","ppp_2010","GIS/Population/Global_2000_2020/2010/ECU/ecu_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2557,222,"SLV","El Salvador","ppp_2010","GIS/Population/Global_2000_2020/2010/SLV/slv_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2558,226,"GNQ","Equatorial Guinea","ppp_2010","GIS/Population/Global_2000_2020/2010/GNQ/gnq_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2559,231,"ETH","Ethiopia","ppp_2010","GIS/Population/Global_2000_2020/2010/ETH/eth_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2560,232,"ERI","Eritrea","ppp_2010","GIS/Population/Global_2000_2020/2010/ERI/eri_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2561,233,"EST","Estonia","ppp_2010","GIS/Population/Global_2000_2020/2010/EST/est_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2562,234,"FRO","Faroe Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/FRO/fro_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2563,238,"FLK","Falkland Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/FLK/flk_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2564,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/SGS/sgs_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2565,242,"FJI","Fiji","ppp_2010","GIS/Population/Global_2000_2020/2010/FJI/fji_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2566,246,"FIN","Finland","ppp_2010","GIS/Population/Global_2000_2020/2010/FIN/fin_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2567,248,"ALA","Aland Islands ","ppp_2010","GIS/Population/Global_2000_2020/2010/ALA/ala_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2568,250,"FRA","France","ppp_2010","GIS/Population/Global_2000_2020/2010/FRA/fra_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2569,254,"GUF","French Guiana","ppp_2010","GIS/Population/Global_2000_2020/2010/GUF/guf_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2570,258,"PYF","French Polynesia","ppp_2010","GIS/Population/Global_2000_2020/2010/PYF/pyf_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2571,260,"ATF","French Southern Territories","ppp_2010","GIS/Population/Global_2000_2020/2010/ATF/atf_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2572,262,"DJI","Djibouti","ppp_2010","GIS/Population/Global_2000_2020/2010/DJI/dji_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2573,266,"GAB","Gabon","ppp_2010","GIS/Population/Global_2000_2020/2010/GAB/gab_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2574,268,"GEO","Georgia","ppp_2010","GIS/Population/Global_2000_2020/2010/GEO/geo_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2575,270,"GMB","Gambia","ppp_2010","GIS/Population/Global_2000_2020/2010/GMB/gmb_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2576,275,"PSE","Palestina","ppp_2010","GIS/Population/Global_2000_2020/2010/PSE/pse_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2577,276,"DEU","Germany","ppp_2010","GIS/Population/Global_2000_2020/2010/DEU/deu_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2578,288,"GHA","Ghana","ppp_2010","GIS/Population/Global_2000_2020/2010/GHA/gha_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2579,292,"GIB","Gibraltar","ppp_2010","GIS/Population/Global_2000_2020/2010/GIB/gib_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2580,296,"KIR","Kiribati","ppp_2010","GIS/Population/Global_2000_2020/2010/KIR/kir_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2581,300,"GRC","Greece","ppp_2010","GIS/Population/Global_2000_2020/2010/GRC/grc_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2582,308,"GRD","Grenada","ppp_2010","GIS/Population/Global_2000_2020/2010/GRD/grd_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2583,312,"GLP","Guadeloupe","ppp_2010","GIS/Population/Global_2000_2020/2010/GLP/glp_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2584,316,"GUM","Guam","ppp_2010","GIS/Population/Global_2000_2020/2010/GUM/gum_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2585,320,"GTM","Guatemala","ppp_2010","GIS/Population/Global_2000_2020/2010/GTM/gtm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2586,324,"GIN","Guinea","ppp_2010","GIS/Population/Global_2000_2020/2010/GIN/gin_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2587,328,"GUY","Guyana","ppp_2010","GIS/Population/Global_2000_2020/2010/GUY/guy_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2588,332,"HTI","Haiti","ppp_2010","GIS/Population/Global_2000_2020/2010/HTI/hti_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2589,334,"HMD","Heard Island and McDonald Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/HMD/hmd_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2590,336,"VAT","Vatican City","ppp_2010","GIS/Population/Global_2000_2020/2010/VAT/vat_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2591,340,"HND","Honduras","ppp_2010","GIS/Population/Global_2000_2020/2010/HND/hnd_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2592,344,"HKG","Hong Kong","ppp_2010","GIS/Population/Global_2000_2020/2010/HKG/hkg_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2593,348,"HUN","Hungary","ppp_2010","GIS/Population/Global_2000_2020/2010/HUN/hun_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2594,352,"ISL","Iceland","ppp_2010","GIS/Population/Global_2000_2020/2010/ISL/isl_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2595,356,"IND","India","ppp_2010","GIS/Population/Global_2000_2020/2010/IND/ind_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2596,364,"IRN","Iran","ppp_2010","GIS/Population/Global_2000_2020/2010/IRN/irn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2597,368,"IRQ","Iraq","ppp_2010","GIS/Population/Global_2000_2020/2010/IRQ/irq_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2598,372,"IRL","Ireland","ppp_2010","GIS/Population/Global_2000_2020/2010/IRL/irl_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2599,376,"ISR","Israel","ppp_2010","GIS/Population/Global_2000_2020/2010/ISR/isr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2600,380,"ITA","Italy","ppp_2010","GIS/Population/Global_2000_2020/2010/ITA/ita_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2601,384,"CIV","CIte dIvoire","ppp_2010","GIS/Population/Global_2000_2020/2010/CIV/civ_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2602,388,"JAM","Jamaica","ppp_2010","GIS/Population/Global_2000_2020/2010/JAM/jam_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2603,392,"JPN","Japan","ppp_2010","GIS/Population/Global_2000_2020/2010/JPN/jpn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2604,398,"KAZ","Kazakhstan","ppp_2010","GIS/Population/Global_2000_2020/2010/KAZ/kaz_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2605,400,"JOR","Jordan","ppp_2010","GIS/Population/Global_2000_2020/2010/JOR/jor_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2606,404,"KEN","Kenya","ppp_2010","GIS/Population/Global_2000_2020/2010/KEN/ken_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2607,408,"PRK","North Korea","ppp_2010","GIS/Population/Global_2000_2020/2010/PRK/prk_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2608,410,"KOR","South Korea","ppp_2010","GIS/Population/Global_2000_2020/2010/KOR/kor_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2609,414,"KWT","Kuwait","ppp_2010","GIS/Population/Global_2000_2020/2010/KWT/kwt_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2610,417,"KGZ","Kyrgyzstan","ppp_2010","GIS/Population/Global_2000_2020/2010/KGZ/kgz_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2611,418,"LAO","Laos","ppp_2010","GIS/Population/Global_2000_2020/2010/LAO/lao_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2612,422,"LBN","Lebanon","ppp_2010","GIS/Population/Global_2000_2020/2010/LBN/lbn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2613,426,"LSO","Lesotho","ppp_2010","GIS/Population/Global_2000_2020/2010/LSO/lso_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2614,428,"LVA","Latvia","ppp_2010","GIS/Population/Global_2000_2020/2010/LVA/lva_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2615,430,"LBR","Liberia","ppp_2010","GIS/Population/Global_2000_2020/2010/LBR/lbr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2616,434,"LBY","Libya","ppp_2010","GIS/Population/Global_2000_2020/2010/LBY/lby_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2617,438,"LIE","Liechtenstein","ppp_2010","GIS/Population/Global_2000_2020/2010/LIE/lie_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2618,440,"LTU","Lithuania","ppp_2010","GIS/Population/Global_2000_2020/2010/LTU/ltu_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2619,442,"LUX","Luxembourg","ppp_2010","GIS/Population/Global_2000_2020/2010/LUX/lux_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2620,446,"MAC","Macao","ppp_2010","GIS/Population/Global_2000_2020/2010/MAC/mac_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2621,450,"MDG","Madagascar","ppp_2010","GIS/Population/Global_2000_2020/2010/MDG/mdg_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2622,454,"MWI","Malawi","ppp_2010","GIS/Population/Global_2000_2020/2010/MWI/mwi_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2623,458,"MYS","Malaysia","ppp_2010","GIS/Population/Global_2000_2020/2010/MYS/mys_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2624,462,"MDV","Maldives","ppp_2010","GIS/Population/Global_2000_2020/2010/MDV/mdv_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2625,466,"MLI","Mali","ppp_2010","GIS/Population/Global_2000_2020/2010/MLI/mli_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2626,470,"MLT","Malta","ppp_2010","GIS/Population/Global_2000_2020/2010/MLT/mlt_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2627,474,"MTQ","Martinique","ppp_2010","GIS/Population/Global_2000_2020/2010/MTQ/mtq_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2628,478,"MRT","Mauritania","ppp_2010","GIS/Population/Global_2000_2020/2010/MRT/mrt_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2629,480,"MUS","Mauritius","ppp_2010","GIS/Population/Global_2000_2020/2010/MUS/mus_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2630,484,"MEX","Mexico","ppp_2010","GIS/Population/Global_2000_2020/2010/MEX/mex_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2631,492,"MCO","Monaco","ppp_2010","GIS/Population/Global_2000_2020/2010/MCO/mco_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2632,496,"MNG","Mongolia","ppp_2010","GIS/Population/Global_2000_2020/2010/MNG/mng_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2633,498,"MDA","Moldova","ppp_2010","GIS/Population/Global_2000_2020/2010/MDA/mda_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2634,499,"MNE","Montenegro","ppp_2010","GIS/Population/Global_2000_2020/2010/MNE/mne_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2635,500,"MSR","Montserrat","ppp_2010","GIS/Population/Global_2000_2020/2010/MSR/msr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2636,504,"MAR","Morocco","ppp_2010","GIS/Population/Global_2000_2020/2010/MAR/mar_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2637,508,"MOZ","Mozambique","ppp_2010","GIS/Population/Global_2000_2020/2010/MOZ/moz_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2638,512,"OMN","Oman","ppp_2010","GIS/Population/Global_2000_2020/2010/OMN/omn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2639,516,"NAM","Namibia","ppp_2010","GIS/Population/Global_2000_2020/2010/NAM/nam_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2640,520,"NRU","Nauru","ppp_2010","GIS/Population/Global_2000_2020/2010/NRU/nru_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2641,524,"NPL","Nepal","ppp_2010","GIS/Population/Global_2000_2020/2010/NPL/npl_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2642,528,"NLD","Netherlands","ppp_2010","GIS/Population/Global_2000_2020/2010/NLD/nld_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2643,531,"CUW","Curacao","ppp_2010","GIS/Population/Global_2000_2020/2010/CUW/cuw_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2644,533,"ABW","Aruba","ppp_2010","GIS/Population/Global_2000_2020/2010/ABW/abw_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2645,534,"SXM","Sint Maarten (Dutch part)","ppp_2010","GIS/Population/Global_2000_2020/2010/SXM/sxm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2646,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2010","GIS/Population/Global_2000_2020/2010/BES/bes_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2647,540,"NCL","New Caledonia","ppp_2010","GIS/Population/Global_2000_2020/2010/NCL/ncl_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2648,548,"VUT","Vanuatu","ppp_2010","GIS/Population/Global_2000_2020/2010/VUT/vut_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2649,554,"NZL","New Zealand","ppp_2010","GIS/Population/Global_2000_2020/2010/NZL/nzl_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2650,558,"NIC","Nicaragua","ppp_2010","GIS/Population/Global_2000_2020/2010/NIC/nic_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2651,562,"NER","Niger","ppp_2010","GIS/Population/Global_2000_2020/2010/NER/ner_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2652,566,"NGA","Nigeria","ppp_2010","GIS/Population/Global_2000_2020/2010/NGA/nga_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2653,570,"NIU","Niue","ppp_2010","GIS/Population/Global_2000_2020/2010/NIU/niu_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2654,574,"NFK","Norfolk Island","ppp_2010","GIS/Population/Global_2000_2020/2010/NFK/nfk_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2655,578,"NOR","Norway","ppp_2010","GIS/Population/Global_2000_2020/2010/NOR/nor_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2656,580,"MNP","Northern Mariana Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/MNP/mnp_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2657,581,"UMI","United States Minor Outlying Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/UMI/umi_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2658,583,"FSM","Micronesia","ppp_2010","GIS/Population/Global_2000_2020/2010/FSM/fsm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2659,584,"MHL","Marshall Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/MHL/mhl_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2660,585,"PLW","Palau","ppp_2010","GIS/Population/Global_2000_2020/2010/PLW/plw_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2661,586,"PAK","Pakistan","ppp_2010","GIS/Population/Global_2000_2020/2010/PAK/pak_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2662,591,"PAN","Panama","ppp_2010","GIS/Population/Global_2000_2020/2010/PAN/pan_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2663,598,"PNG","Papua New Guinea","ppp_2010","GIS/Population/Global_2000_2020/2010/PNG/png_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2664,600,"PRY","Paraguay","ppp_2010","GIS/Population/Global_2000_2020/2010/PRY/pry_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2665,604,"PER","Peru","ppp_2010","GIS/Population/Global_2000_2020/2010/PER/per_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2666,608,"PHL","Philippines","ppp_2010","GIS/Population/Global_2000_2020/2010/PHL/phl_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2667,612,"PCN","Pitcairn Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/PCN/pcn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2668,616,"POL","Poland","ppp_2010","GIS/Population/Global_2000_2020/2010/POL/pol_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2669,620,"PRT","Portugal","ppp_2010","GIS/Population/Global_2000_2020/2010/PRT/prt_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2670,624,"GNB","Guinea-Bissau","ppp_2010","GIS/Population/Global_2000_2020/2010/GNB/gnb_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2671,626,"TLS","East Timor","ppp_2010","GIS/Population/Global_2000_2020/2010/TLS/tls_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2672,630,"PRI","Puerto Rico","ppp_2010","GIS/Population/Global_2000_2020/2010/PRI/pri_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2673,634,"QAT","Qatar","ppp_2010","GIS/Population/Global_2000_2020/2010/QAT/qat_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2674,638,"REU","Reunion","ppp_2010","GIS/Population/Global_2000_2020/2010/REU/reu_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2675,642,"ROU","Romania","ppp_2010","GIS/Population/Global_2000_2020/2010/ROU/rou_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2676,646,"RWA","Rwanda","ppp_2010","GIS/Population/Global_2000_2020/2010/RWA/rwa_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2677,652,"BLM","Saint Barthelemy","ppp_2010","GIS/Population/Global_2000_2020/2010/BLM/blm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2678,654,"SHN","Saint Helena","ppp_2010","GIS/Population/Global_2000_2020/2010/SHN/shn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2679,659,"KNA","Saint Kitts and Nevis","ppp_2010","GIS/Population/Global_2000_2020/2010/KNA/kna_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2680,660,"AIA","Anguilla","ppp_2010","GIS/Population/Global_2000_2020/2010/AIA/aia_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2681,662,"LCA","Saint Lucia","ppp_2010","GIS/Population/Global_2000_2020/2010/LCA/lca_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2682,663,"MAF","Saint Martin (French part)","ppp_2010","GIS/Population/Global_2000_2020/2010/MAF/maf_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2683,666,"SPM","Saint Pierre and Miquelon","ppp_2010","GIS/Population/Global_2000_2020/2010/SPM/spm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2684,670,"VCT","Saint Vincent and the Grenadines","ppp_2010","GIS/Population/Global_2000_2020/2010/VCT/vct_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2685,674,"SMR","San Marino","ppp_2010","GIS/Population/Global_2000_2020/2010/SMR/smr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2686,678,"STP","Sao Tome and Principe","ppp_2010","GIS/Population/Global_2000_2020/2010/STP/stp_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2687,682,"SAU","Saudi Arabia","ppp_2010","GIS/Population/Global_2000_2020/2010/SAU/sau_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2688,686,"SEN","Senegal","ppp_2010","GIS/Population/Global_2000_2020/2010/SEN/sen_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2689,688,"SRB","Serbia","ppp_2010","GIS/Population/Global_2000_2020/2010/SRB/srb_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2690,690,"SYC","Seychelles","ppp_2010","GIS/Population/Global_2000_2020/2010/SYC/syc_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2691,694,"SLE","Sierra Leone","ppp_2010","GIS/Population/Global_2000_2020/2010/SLE/sle_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2692,702,"SGP","Singapore","ppp_2010","GIS/Population/Global_2000_2020/2010/SGP/sgp_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2693,703,"SVK","Slovakia","ppp_2010","GIS/Population/Global_2000_2020/2010/SVK/svk_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2694,704,"VNM","Vietnam","ppp_2010","GIS/Population/Global_2000_2020/2010/VNM/vnm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2695,705,"SVN","Slovenia","ppp_2010","GIS/Population/Global_2000_2020/2010/SVN/svn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2696,706,"SOM","Somalia","ppp_2010","GIS/Population/Global_2000_2020/2010/SOM/som_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2697,710,"ZAF","South Africa","ppp_2010","GIS/Population/Global_2000_2020/2010/ZAF/zaf_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2698,716,"ZWE","Zimbabwe","ppp_2010","GIS/Population/Global_2000_2020/2010/ZWE/zwe_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2699,724,"ESP","Spain","ppp_2010","GIS/Population/Global_2000_2020/2010/ESP/esp_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2700,728,"SSD","South Sudan","ppp_2010","GIS/Population/Global_2000_2020/2010/SSD/ssd_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2701,729,"SDN","Sudan","ppp_2010","GIS/Population/Global_2000_2020/2010/SDN/sdn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2702,732,"ESH","Western Sahara","ppp_2010","GIS/Population/Global_2000_2020/2010/ESH/esh_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2703,740,"SUR","Suriname","ppp_2010","GIS/Population/Global_2000_2020/2010/SUR/sur_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2704,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/SJM/sjm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2705,748,"SWZ","Swaziland","ppp_2010","GIS/Population/Global_2000_2020/2010/SWZ/swz_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2706,752,"SWE","Sweden","ppp_2010","GIS/Population/Global_2000_2020/2010/SWE/swe_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2707,756,"CHE","Switzerland","ppp_2010","GIS/Population/Global_2000_2020/2010/CHE/che_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2708,760,"SYR","Syria","ppp_2010","GIS/Population/Global_2000_2020/2010/SYR/syr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2709,762,"TJK","Tajikistan","ppp_2010","GIS/Population/Global_2000_2020/2010/TJK/tjk_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2710,764,"THA","Thailand","ppp_2010","GIS/Population/Global_2000_2020/2010/THA/tha_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2711,768,"TGO","Togo","ppp_2010","GIS/Population/Global_2000_2020/2010/TGO/tgo_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2712,772,"TKL","Tokelau","ppp_2010","GIS/Population/Global_2000_2020/2010/TKL/tkl_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2713,776,"TON","Tonga","ppp_2010","GIS/Population/Global_2000_2020/2010/TON/ton_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2714,780,"TTO","Trinidad and Tobago","ppp_2010","GIS/Population/Global_2000_2020/2010/TTO/tto_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2715,784,"ARE","United Arab Emirates","ppp_2010","GIS/Population/Global_2000_2020/2010/ARE/are_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2716,788,"TUN","Tunisia","ppp_2010","GIS/Population/Global_2000_2020/2010/TUN/tun_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2717,792,"TUR","Turkey","ppp_2010","GIS/Population/Global_2000_2020/2010/TUR/tur_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2718,795,"TKM","Turkmenistan","ppp_2010","GIS/Population/Global_2000_2020/2010/TKM/tkm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2719,796,"TCA","Turks and Caicos Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/TCA/tca_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2720,798,"TUV","Tuvalu","ppp_2010","GIS/Population/Global_2000_2020/2010/TUV/tuv_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2721,800,"UGA","Uganda","ppp_2010","GIS/Population/Global_2000_2020/2010/UGA/uga_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2722,804,"UKR","Ukraine","ppp_2010","GIS/Population/Global_2000_2020/2010/UKR/ukr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2723,807,"MKD","Macedonia","ppp_2010","GIS/Population/Global_2000_2020/2010/MKD/mkd_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2724,818,"EGY","Egypt","ppp_2010","GIS/Population/Global_2000_2020/2010/EGY/egy_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2725,826,"GBR","United Kingdom","ppp_2010","GIS/Population/Global_2000_2020/2010/GBR/gbr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2726,831,"GGY","Guernsey","ppp_2010","GIS/Population/Global_2000_2020/2010/GGY/ggy_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2727,832,"JEY","Jersey","ppp_2010","GIS/Population/Global_2000_2020/2010/JEY/jey_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2728,833,"IMN","Isle of Man","ppp_2010","GIS/Population/Global_2000_2020/2010/IMN/imn_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2729,834,"TZA","Tanzania","ppp_2010","GIS/Population/Global_2000_2020/2010/TZA/tza_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2730,854,"BFA","Burkina Faso","ppp_2010","GIS/Population/Global_2000_2020/2010/BFA/bfa_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2731,858,"URY","Uruguay","ppp_2010","GIS/Population/Global_2000_2020/2010/URY/ury_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2732,860,"UZB","Uzbekistan","ppp_2010","GIS/Population/Global_2000_2020/2010/UZB/uzb_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2733,862,"VEN","Venezuela","ppp_2010","GIS/Population/Global_2000_2020/2010/VEN/ven_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2734,876,"WLF","Wallis and Futuna","ppp_2010","GIS/Population/Global_2000_2020/2010/WLF/wlf_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2735,882,"WSM","Samoa","ppp_2010","GIS/Population/Global_2000_2020/2010/WSM/wsm_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2736,887,"YEM","Yemen","ppp_2010","GIS/Population/Global_2000_2020/2010/YEM/yem_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2737,894,"ZMB","Zambia","ppp_2010","GIS/Population/Global_2000_2020/2010/ZMB/zmb_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2738,900,"KOS","Kosovo","ppp_2010","GIS/Population/Global_2000_2020/2010/KOS/kos_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2739,901,"SPR","Spratly Islands","ppp_2010","GIS/Population/Global_2000_2020/2010/SPR/spr_ppp_2010.tif","Estimated total number of people per grid-cell 2010 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2740,643,"RUS","Russia","ppp_2011","GIS/Population/Global_2000_2020/2011/RUS/rus_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2741,360,"IDN","Indonesia","ppp_2011","GIS/Population/Global_2000_2020/2011/IDN/idn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2742,840,"USA","United States","ppp_2011","GIS/Population/Global_2000_2020/2011/USA/usa_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2743,850,"VIR","Virgin_Islands_U_S","ppp_2011","GIS/Population/Global_2000_2020/2011/VIR/vir_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2744,304,"GRL","Greenland","ppp_2011","GIS/Population/Global_2000_2020/2011/GRL/grl_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2745,156,"CHN","China","ppp_2011","GIS/Population/Global_2000_2020/2011/CHN/chn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2746,36,"AUS","Australia","ppp_2011","GIS/Population/Global_2000_2020/2011/AUS/aus_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2747,76,"BRA","Brazil","ppp_2011","GIS/Population/Global_2000_2020/2011/BRA/bra_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2748,124,"CAN","Canada","ppp_2011","GIS/Population/Global_2000_2020/2011/CAN/can_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2749,152,"CHL","Chile","ppp_2011","GIS/Population/Global_2000_2020/2011/CHL/chl_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2750,4,"AFG","Afghanistan","ppp_2011","GIS/Population/Global_2000_2020/2011/AFG/afg_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2751,8,"ALB","Albania","ppp_2011","GIS/Population/Global_2000_2020/2011/ALB/alb_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2752,10,"ATA","Antarctica","ppp_2011","GIS/Population/Global_2000_2020/2011/ATA/ata_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2753,12,"DZA","Algeria","ppp_2011","GIS/Population/Global_2000_2020/2011/DZA/dza_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2754,16,"ASM","American Samoa","ppp_2011","GIS/Population/Global_2000_2020/2011/ASM/asm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2755,20,"AND","Andorra","ppp_2011","GIS/Population/Global_2000_2020/2011/AND/and_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2756,24,"AGO","Angola","ppp_2011","GIS/Population/Global_2000_2020/2011/AGO/ago_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2757,28,"ATG","Antigua and Barbuda","ppp_2011","GIS/Population/Global_2000_2020/2011/ATG/atg_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2758,31,"AZE","Azerbaijan","ppp_2011","GIS/Population/Global_2000_2020/2011/AZE/aze_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2759,32,"ARG","Argentina","ppp_2011","GIS/Population/Global_2000_2020/2011/ARG/arg_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2760,40,"AUT","Austria","ppp_2011","GIS/Population/Global_2000_2020/2011/AUT/aut_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2761,44,"BHS","Bahamas","ppp_2011","GIS/Population/Global_2000_2020/2011/BHS/bhs_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2762,48,"BHR","Bahrain","ppp_2011","GIS/Population/Global_2000_2020/2011/BHR/bhr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2763,50,"BGD","Bangladesh","ppp_2011","GIS/Population/Global_2000_2020/2011/BGD/bgd_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2764,51,"ARM","Armenia","ppp_2011","GIS/Population/Global_2000_2020/2011/ARM/arm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2765,52,"BRB","Barbados","ppp_2011","GIS/Population/Global_2000_2020/2011/BRB/brb_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2766,56,"BEL","Belgium","ppp_2011","GIS/Population/Global_2000_2020/2011/BEL/bel_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2767,60,"BMU","Bermuda","ppp_2011","GIS/Population/Global_2000_2020/2011/BMU/bmu_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2768,64,"BTN","Bhutan","ppp_2011","GIS/Population/Global_2000_2020/2011/BTN/btn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2769,68,"BOL","Bolivia","ppp_2011","GIS/Population/Global_2000_2020/2011/BOL/bol_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2770,70,"BIH","Bosnia and Herzegovina","ppp_2011","GIS/Population/Global_2000_2020/2011/BIH/bih_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2771,72,"BWA","Botswana","ppp_2011","GIS/Population/Global_2000_2020/2011/BWA/bwa_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2772,74,"BVT","Bouvet Island","ppp_2011","GIS/Population/Global_2000_2020/2011/BVT/bvt_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2773,84,"BLZ","Belize","ppp_2011","GIS/Population/Global_2000_2020/2011/BLZ/blz_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2774,86,"IOT","British Indian Ocean Territory","ppp_2011","GIS/Population/Global_2000_2020/2011/IOT/iot_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2775,90,"SLB","Solomon Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/SLB/slb_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2776,92,"VGB","British Virgin Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/VGB/vgb_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2777,96,"BRN","Brunei","ppp_2011","GIS/Population/Global_2000_2020/2011/BRN/brn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2778,100,"BGR","Bulgaria","ppp_2011","GIS/Population/Global_2000_2020/2011/BGR/bgr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2779,104,"MMR","Myanmar","ppp_2011","GIS/Population/Global_2000_2020/2011/MMR/mmr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2780,108,"BDI","Burundi","ppp_2011","GIS/Population/Global_2000_2020/2011/BDI/bdi_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2781,112,"BLR","Belarus","ppp_2011","GIS/Population/Global_2000_2020/2011/BLR/blr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2782,116,"KHM","Cambodia","ppp_2011","GIS/Population/Global_2000_2020/2011/KHM/khm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2783,120,"CMR","Cameroon","ppp_2011","GIS/Population/Global_2000_2020/2011/CMR/cmr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2784,132,"CPV","Cape Verde","ppp_2011","GIS/Population/Global_2000_2020/2011/CPV/cpv_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2785,136,"CYM","Cayman Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/CYM/cym_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2786,140,"CAF","Central African Republic","ppp_2011","GIS/Population/Global_2000_2020/2011/CAF/caf_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2787,144,"LKA","Sri Lanka","ppp_2011","GIS/Population/Global_2000_2020/2011/LKA/lka_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2788,148,"TCD","Chad","ppp_2011","GIS/Population/Global_2000_2020/2011/TCD/tcd_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2789,158,"TWN","Taiwan","ppp_2011","GIS/Population/Global_2000_2020/2011/TWN/twn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2790,170,"COL","Colombia","ppp_2011","GIS/Population/Global_2000_2020/2011/COL/col_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2791,174,"COM","Comoros","ppp_2011","GIS/Population/Global_2000_2020/2011/COM/com_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2792,175,"MYT","Mayotte","ppp_2011","GIS/Population/Global_2000_2020/2011/MYT/myt_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2793,178,"COG","Republic of Congo","ppp_2011","GIS/Population/Global_2000_2020/2011/COG/cog_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2794,180,"COD","Democratic Republic of the Congo","ppp_2011","GIS/Population/Global_2000_2020/2011/COD/cod_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2795,184,"COK","Cook Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/COK/cok_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2796,188,"CRI","Costa Rica","ppp_2011","GIS/Population/Global_2000_2020/2011/CRI/cri_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2797,191,"HRV","Croatia","ppp_2011","GIS/Population/Global_2000_2020/2011/HRV/hrv_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2798,192,"CUB","Cuba","ppp_2011","GIS/Population/Global_2000_2020/2011/CUB/cub_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2799,196,"CYP","Cyprus","ppp_2011","GIS/Population/Global_2000_2020/2011/CYP/cyp_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2800,203,"CZE","Czech Republic","ppp_2011","GIS/Population/Global_2000_2020/2011/CZE/cze_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2801,204,"BEN","Benin","ppp_2011","GIS/Population/Global_2000_2020/2011/BEN/ben_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2802,208,"DNK","Denmark","ppp_2011","GIS/Population/Global_2000_2020/2011/DNK/dnk_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2803,212,"DMA","Dominica","ppp_2011","GIS/Population/Global_2000_2020/2011/DMA/dma_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2804,214,"DOM","Dominican Republic","ppp_2011","GIS/Population/Global_2000_2020/2011/DOM/dom_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2805,218,"ECU","Ecuador","ppp_2011","GIS/Population/Global_2000_2020/2011/ECU/ecu_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2806,222,"SLV","El Salvador","ppp_2011","GIS/Population/Global_2000_2020/2011/SLV/slv_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2807,226,"GNQ","Equatorial Guinea","ppp_2011","GIS/Population/Global_2000_2020/2011/GNQ/gnq_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2808,231,"ETH","Ethiopia","ppp_2011","GIS/Population/Global_2000_2020/2011/ETH/eth_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2809,232,"ERI","Eritrea","ppp_2011","GIS/Population/Global_2000_2020/2011/ERI/eri_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2810,233,"EST","Estonia","ppp_2011","GIS/Population/Global_2000_2020/2011/EST/est_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2811,234,"FRO","Faroe Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/FRO/fro_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2812,238,"FLK","Falkland Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/FLK/flk_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2813,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/SGS/sgs_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2814,242,"FJI","Fiji","ppp_2011","GIS/Population/Global_2000_2020/2011/FJI/fji_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2815,246,"FIN","Finland","ppp_2011","GIS/Population/Global_2000_2020/2011/FIN/fin_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2816,248,"ALA","Aland Islands ","ppp_2011","GIS/Population/Global_2000_2020/2011/ALA/ala_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2817,250,"FRA","France","ppp_2011","GIS/Population/Global_2000_2020/2011/FRA/fra_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2818,254,"GUF","French Guiana","ppp_2011","GIS/Population/Global_2000_2020/2011/GUF/guf_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2819,258,"PYF","French Polynesia","ppp_2011","GIS/Population/Global_2000_2020/2011/PYF/pyf_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2820,260,"ATF","French Southern Territories","ppp_2011","GIS/Population/Global_2000_2020/2011/ATF/atf_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2821,262,"DJI","Djibouti","ppp_2011","GIS/Population/Global_2000_2020/2011/DJI/dji_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2822,266,"GAB","Gabon","ppp_2011","GIS/Population/Global_2000_2020/2011/GAB/gab_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2823,268,"GEO","Georgia","ppp_2011","GIS/Population/Global_2000_2020/2011/GEO/geo_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2824,270,"GMB","Gambia","ppp_2011","GIS/Population/Global_2000_2020/2011/GMB/gmb_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2825,275,"PSE","Palestina","ppp_2011","GIS/Population/Global_2000_2020/2011/PSE/pse_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2826,276,"DEU","Germany","ppp_2011","GIS/Population/Global_2000_2020/2011/DEU/deu_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2827,288,"GHA","Ghana","ppp_2011","GIS/Population/Global_2000_2020/2011/GHA/gha_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2828,292,"GIB","Gibraltar","ppp_2011","GIS/Population/Global_2000_2020/2011/GIB/gib_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2829,296,"KIR","Kiribati","ppp_2011","GIS/Population/Global_2000_2020/2011/KIR/kir_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2830,300,"GRC","Greece","ppp_2011","GIS/Population/Global_2000_2020/2011/GRC/grc_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2831,308,"GRD","Grenada","ppp_2011","GIS/Population/Global_2000_2020/2011/GRD/grd_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2832,312,"GLP","Guadeloupe","ppp_2011","GIS/Population/Global_2000_2020/2011/GLP/glp_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2833,316,"GUM","Guam","ppp_2011","GIS/Population/Global_2000_2020/2011/GUM/gum_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2834,320,"GTM","Guatemala","ppp_2011","GIS/Population/Global_2000_2020/2011/GTM/gtm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2835,324,"GIN","Guinea","ppp_2011","GIS/Population/Global_2000_2020/2011/GIN/gin_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2836,328,"GUY","Guyana","ppp_2011","GIS/Population/Global_2000_2020/2011/GUY/guy_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2837,332,"HTI","Haiti","ppp_2011","GIS/Population/Global_2000_2020/2011/HTI/hti_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2838,334,"HMD","Heard Island and McDonald Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/HMD/hmd_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2839,336,"VAT","Vatican City","ppp_2011","GIS/Population/Global_2000_2020/2011/VAT/vat_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2840,340,"HND","Honduras","ppp_2011","GIS/Population/Global_2000_2020/2011/HND/hnd_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2841,344,"HKG","Hong Kong","ppp_2011","GIS/Population/Global_2000_2020/2011/HKG/hkg_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2842,348,"HUN","Hungary","ppp_2011","GIS/Population/Global_2000_2020/2011/HUN/hun_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2843,352,"ISL","Iceland","ppp_2011","GIS/Population/Global_2000_2020/2011/ISL/isl_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2844,356,"IND","India","ppp_2011","GIS/Population/Global_2000_2020/2011/IND/ind_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2845,364,"IRN","Iran","ppp_2011","GIS/Population/Global_2000_2020/2011/IRN/irn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2846,368,"IRQ","Iraq","ppp_2011","GIS/Population/Global_2000_2020/2011/IRQ/irq_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2847,372,"IRL","Ireland","ppp_2011","GIS/Population/Global_2000_2020/2011/IRL/irl_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2848,376,"ISR","Israel","ppp_2011","GIS/Population/Global_2000_2020/2011/ISR/isr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2849,380,"ITA","Italy","ppp_2011","GIS/Population/Global_2000_2020/2011/ITA/ita_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2850,384,"CIV","CIte dIvoire","ppp_2011","GIS/Population/Global_2000_2020/2011/CIV/civ_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2851,388,"JAM","Jamaica","ppp_2011","GIS/Population/Global_2000_2020/2011/JAM/jam_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2852,392,"JPN","Japan","ppp_2011","GIS/Population/Global_2000_2020/2011/JPN/jpn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2853,398,"KAZ","Kazakhstan","ppp_2011","GIS/Population/Global_2000_2020/2011/KAZ/kaz_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2854,400,"JOR","Jordan","ppp_2011","GIS/Population/Global_2000_2020/2011/JOR/jor_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2855,404,"KEN","Kenya","ppp_2011","GIS/Population/Global_2000_2020/2011/KEN/ken_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2856,408,"PRK","North Korea","ppp_2011","GIS/Population/Global_2000_2020/2011/PRK/prk_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2857,410,"KOR","South Korea","ppp_2011","GIS/Population/Global_2000_2020/2011/KOR/kor_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2858,414,"KWT","Kuwait","ppp_2011","GIS/Population/Global_2000_2020/2011/KWT/kwt_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2859,417,"KGZ","Kyrgyzstan","ppp_2011","GIS/Population/Global_2000_2020/2011/KGZ/kgz_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2860,418,"LAO","Laos","ppp_2011","GIS/Population/Global_2000_2020/2011/LAO/lao_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2861,422,"LBN","Lebanon","ppp_2011","GIS/Population/Global_2000_2020/2011/LBN/lbn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2862,426,"LSO","Lesotho","ppp_2011","GIS/Population/Global_2000_2020/2011/LSO/lso_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2863,428,"LVA","Latvia","ppp_2011","GIS/Population/Global_2000_2020/2011/LVA/lva_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2864,430,"LBR","Liberia","ppp_2011","GIS/Population/Global_2000_2020/2011/LBR/lbr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2865,434,"LBY","Libya","ppp_2011","GIS/Population/Global_2000_2020/2011/LBY/lby_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2866,438,"LIE","Liechtenstein","ppp_2011","GIS/Population/Global_2000_2020/2011/LIE/lie_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2867,440,"LTU","Lithuania","ppp_2011","GIS/Population/Global_2000_2020/2011/LTU/ltu_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2868,442,"LUX","Luxembourg","ppp_2011","GIS/Population/Global_2000_2020/2011/LUX/lux_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2869,446,"MAC","Macao","ppp_2011","GIS/Population/Global_2000_2020/2011/MAC/mac_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2870,450,"MDG","Madagascar","ppp_2011","GIS/Population/Global_2000_2020/2011/MDG/mdg_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2871,454,"MWI","Malawi","ppp_2011","GIS/Population/Global_2000_2020/2011/MWI/mwi_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2872,458,"MYS","Malaysia","ppp_2011","GIS/Population/Global_2000_2020/2011/MYS/mys_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2873,462,"MDV","Maldives","ppp_2011","GIS/Population/Global_2000_2020/2011/MDV/mdv_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2874,466,"MLI","Mali","ppp_2011","GIS/Population/Global_2000_2020/2011/MLI/mli_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2875,470,"MLT","Malta","ppp_2011","GIS/Population/Global_2000_2020/2011/MLT/mlt_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2876,474,"MTQ","Martinique","ppp_2011","GIS/Population/Global_2000_2020/2011/MTQ/mtq_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2877,478,"MRT","Mauritania","ppp_2011","GIS/Population/Global_2000_2020/2011/MRT/mrt_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2878,480,"MUS","Mauritius","ppp_2011","GIS/Population/Global_2000_2020/2011/MUS/mus_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2879,484,"MEX","Mexico","ppp_2011","GIS/Population/Global_2000_2020/2011/MEX/mex_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2880,492,"MCO","Monaco","ppp_2011","GIS/Population/Global_2000_2020/2011/MCO/mco_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2881,496,"MNG","Mongolia","ppp_2011","GIS/Population/Global_2000_2020/2011/MNG/mng_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2882,498,"MDA","Moldova","ppp_2011","GIS/Population/Global_2000_2020/2011/MDA/mda_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2883,499,"MNE","Montenegro","ppp_2011","GIS/Population/Global_2000_2020/2011/MNE/mne_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2884,500,"MSR","Montserrat","ppp_2011","GIS/Population/Global_2000_2020/2011/MSR/msr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2885,504,"MAR","Morocco","ppp_2011","GIS/Population/Global_2000_2020/2011/MAR/mar_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2886,508,"MOZ","Mozambique","ppp_2011","GIS/Population/Global_2000_2020/2011/MOZ/moz_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2887,512,"OMN","Oman","ppp_2011","GIS/Population/Global_2000_2020/2011/OMN/omn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2888,516,"NAM","Namibia","ppp_2011","GIS/Population/Global_2000_2020/2011/NAM/nam_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2889,520,"NRU","Nauru","ppp_2011","GIS/Population/Global_2000_2020/2011/NRU/nru_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2890,524,"NPL","Nepal","ppp_2011","GIS/Population/Global_2000_2020/2011/NPL/npl_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2891,528,"NLD","Netherlands","ppp_2011","GIS/Population/Global_2000_2020/2011/NLD/nld_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2892,531,"CUW","Curacao","ppp_2011","GIS/Population/Global_2000_2020/2011/CUW/cuw_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2893,533,"ABW","Aruba","ppp_2011","GIS/Population/Global_2000_2020/2011/ABW/abw_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2894,534,"SXM","Sint Maarten (Dutch part)","ppp_2011","GIS/Population/Global_2000_2020/2011/SXM/sxm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2895,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2011","GIS/Population/Global_2000_2020/2011/BES/bes_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2896,540,"NCL","New Caledonia","ppp_2011","GIS/Population/Global_2000_2020/2011/NCL/ncl_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2897,548,"VUT","Vanuatu","ppp_2011","GIS/Population/Global_2000_2020/2011/VUT/vut_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2898,554,"NZL","New Zealand","ppp_2011","GIS/Population/Global_2000_2020/2011/NZL/nzl_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2899,558,"NIC","Nicaragua","ppp_2011","GIS/Population/Global_2000_2020/2011/NIC/nic_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2900,562,"NER","Niger","ppp_2011","GIS/Population/Global_2000_2020/2011/NER/ner_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2901,566,"NGA","Nigeria","ppp_2011","GIS/Population/Global_2000_2020/2011/NGA/nga_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2902,570,"NIU","Niue","ppp_2011","GIS/Population/Global_2000_2020/2011/NIU/niu_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2903,574,"NFK","Norfolk Island","ppp_2011","GIS/Population/Global_2000_2020/2011/NFK/nfk_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2904,578,"NOR","Norway","ppp_2011","GIS/Population/Global_2000_2020/2011/NOR/nor_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2905,580,"MNP","Northern Mariana Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/MNP/mnp_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2906,581,"UMI","United States Minor Outlying Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/UMI/umi_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2907,583,"FSM","Micronesia","ppp_2011","GIS/Population/Global_2000_2020/2011/FSM/fsm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2908,584,"MHL","Marshall Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/MHL/mhl_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2909,585,"PLW","Palau","ppp_2011","GIS/Population/Global_2000_2020/2011/PLW/plw_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2910,586,"PAK","Pakistan","ppp_2011","GIS/Population/Global_2000_2020/2011/PAK/pak_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2911,591,"PAN","Panama","ppp_2011","GIS/Population/Global_2000_2020/2011/PAN/pan_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2912,598,"PNG","Papua New Guinea","ppp_2011","GIS/Population/Global_2000_2020/2011/PNG/png_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2913,600,"PRY","Paraguay","ppp_2011","GIS/Population/Global_2000_2020/2011/PRY/pry_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2914,604,"PER","Peru","ppp_2011","GIS/Population/Global_2000_2020/2011/PER/per_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2915,608,"PHL","Philippines","ppp_2011","GIS/Population/Global_2000_2020/2011/PHL/phl_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2916,612,"PCN","Pitcairn Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/PCN/pcn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2917,616,"POL","Poland","ppp_2011","GIS/Population/Global_2000_2020/2011/POL/pol_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2918,620,"PRT","Portugal","ppp_2011","GIS/Population/Global_2000_2020/2011/PRT/prt_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2919,624,"GNB","Guinea-Bissau","ppp_2011","GIS/Population/Global_2000_2020/2011/GNB/gnb_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2920,626,"TLS","East Timor","ppp_2011","GIS/Population/Global_2000_2020/2011/TLS/tls_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2921,630,"PRI","Puerto Rico","ppp_2011","GIS/Population/Global_2000_2020/2011/PRI/pri_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2922,634,"QAT","Qatar","ppp_2011","GIS/Population/Global_2000_2020/2011/QAT/qat_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2923,638,"REU","Reunion","ppp_2011","GIS/Population/Global_2000_2020/2011/REU/reu_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2924,642,"ROU","Romania","ppp_2011","GIS/Population/Global_2000_2020/2011/ROU/rou_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2925,646,"RWA","Rwanda","ppp_2011","GIS/Population/Global_2000_2020/2011/RWA/rwa_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2926,652,"BLM","Saint Barthelemy","ppp_2011","GIS/Population/Global_2000_2020/2011/BLM/blm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2927,654,"SHN","Saint Helena","ppp_2011","GIS/Population/Global_2000_2020/2011/SHN/shn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2928,659,"KNA","Saint Kitts and Nevis","ppp_2011","GIS/Population/Global_2000_2020/2011/KNA/kna_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2929,660,"AIA","Anguilla","ppp_2011","GIS/Population/Global_2000_2020/2011/AIA/aia_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2930,662,"LCA","Saint Lucia","ppp_2011","GIS/Population/Global_2000_2020/2011/LCA/lca_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2931,663,"MAF","Saint Martin (French part)","ppp_2011","GIS/Population/Global_2000_2020/2011/MAF/maf_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2932,666,"SPM","Saint Pierre and Miquelon","ppp_2011","GIS/Population/Global_2000_2020/2011/SPM/spm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2933,670,"VCT","Saint Vincent and the Grenadines","ppp_2011","GIS/Population/Global_2000_2020/2011/VCT/vct_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2934,674,"SMR","San Marino","ppp_2011","GIS/Population/Global_2000_2020/2011/SMR/smr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2935,678,"STP","Sao Tome and Principe","ppp_2011","GIS/Population/Global_2000_2020/2011/STP/stp_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2936,682,"SAU","Saudi Arabia","ppp_2011","GIS/Population/Global_2000_2020/2011/SAU/sau_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2937,686,"SEN","Senegal","ppp_2011","GIS/Population/Global_2000_2020/2011/SEN/sen_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2938,688,"SRB","Serbia","ppp_2011","GIS/Population/Global_2000_2020/2011/SRB/srb_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2939,690,"SYC","Seychelles","ppp_2011","GIS/Population/Global_2000_2020/2011/SYC/syc_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2940,694,"SLE","Sierra Leone","ppp_2011","GIS/Population/Global_2000_2020/2011/SLE/sle_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2941,702,"SGP","Singapore","ppp_2011","GIS/Population/Global_2000_2020/2011/SGP/sgp_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2942,703,"SVK","Slovakia","ppp_2011","GIS/Population/Global_2000_2020/2011/SVK/svk_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2943,704,"VNM","Vietnam","ppp_2011","GIS/Population/Global_2000_2020/2011/VNM/vnm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2944,705,"SVN","Slovenia","ppp_2011","GIS/Population/Global_2000_2020/2011/SVN/svn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2945,706,"SOM","Somalia","ppp_2011","GIS/Population/Global_2000_2020/2011/SOM/som_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2946,710,"ZAF","South Africa","ppp_2011","GIS/Population/Global_2000_2020/2011/ZAF/zaf_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2947,716,"ZWE","Zimbabwe","ppp_2011","GIS/Population/Global_2000_2020/2011/ZWE/zwe_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2948,724,"ESP","Spain","ppp_2011","GIS/Population/Global_2000_2020/2011/ESP/esp_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2949,728,"SSD","South Sudan","ppp_2011","GIS/Population/Global_2000_2020/2011/SSD/ssd_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2950,729,"SDN","Sudan","ppp_2011","GIS/Population/Global_2000_2020/2011/SDN/sdn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2951,732,"ESH","Western Sahara","ppp_2011","GIS/Population/Global_2000_2020/2011/ESH/esh_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2952,740,"SUR","Suriname","ppp_2011","GIS/Population/Global_2000_2020/2011/SUR/sur_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2953,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/SJM/sjm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2954,748,"SWZ","Swaziland","ppp_2011","GIS/Population/Global_2000_2020/2011/SWZ/swz_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2955,752,"SWE","Sweden","ppp_2011","GIS/Population/Global_2000_2020/2011/SWE/swe_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2956,756,"CHE","Switzerland","ppp_2011","GIS/Population/Global_2000_2020/2011/CHE/che_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2957,760,"SYR","Syria","ppp_2011","GIS/Population/Global_2000_2020/2011/SYR/syr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2958,762,"TJK","Tajikistan","ppp_2011","GIS/Population/Global_2000_2020/2011/TJK/tjk_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2959,764,"THA","Thailand","ppp_2011","GIS/Population/Global_2000_2020/2011/THA/tha_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2960,768,"TGO","Togo","ppp_2011","GIS/Population/Global_2000_2020/2011/TGO/tgo_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2961,772,"TKL","Tokelau","ppp_2011","GIS/Population/Global_2000_2020/2011/TKL/tkl_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2962,776,"TON","Tonga","ppp_2011","GIS/Population/Global_2000_2020/2011/TON/ton_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2963,780,"TTO","Trinidad and Tobago","ppp_2011","GIS/Population/Global_2000_2020/2011/TTO/tto_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2964,784,"ARE","United Arab Emirates","ppp_2011","GIS/Population/Global_2000_2020/2011/ARE/are_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2965,788,"TUN","Tunisia","ppp_2011","GIS/Population/Global_2000_2020/2011/TUN/tun_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2966,792,"TUR","Turkey","ppp_2011","GIS/Population/Global_2000_2020/2011/TUR/tur_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2967,795,"TKM","Turkmenistan","ppp_2011","GIS/Population/Global_2000_2020/2011/TKM/tkm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2968,796,"TCA","Turks and Caicos Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/TCA/tca_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2969,798,"TUV","Tuvalu","ppp_2011","GIS/Population/Global_2000_2020/2011/TUV/tuv_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2970,800,"UGA","Uganda","ppp_2011","GIS/Population/Global_2000_2020/2011/UGA/uga_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2971,804,"UKR","Ukraine","ppp_2011","GIS/Population/Global_2000_2020/2011/UKR/ukr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2972,807,"MKD","Macedonia","ppp_2011","GIS/Population/Global_2000_2020/2011/MKD/mkd_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2973,818,"EGY","Egypt","ppp_2011","GIS/Population/Global_2000_2020/2011/EGY/egy_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2974,826,"GBR","United Kingdom","ppp_2011","GIS/Population/Global_2000_2020/2011/GBR/gbr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2975,831,"GGY","Guernsey","ppp_2011","GIS/Population/Global_2000_2020/2011/GGY/ggy_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2976,832,"JEY","Jersey","ppp_2011","GIS/Population/Global_2000_2020/2011/JEY/jey_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2977,833,"IMN","Isle of Man","ppp_2011","GIS/Population/Global_2000_2020/2011/IMN/imn_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2978,834,"TZA","Tanzania","ppp_2011","GIS/Population/Global_2000_2020/2011/TZA/tza_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2979,854,"BFA","Burkina Faso","ppp_2011","GIS/Population/Global_2000_2020/2011/BFA/bfa_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2980,858,"URY","Uruguay","ppp_2011","GIS/Population/Global_2000_2020/2011/URY/ury_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2981,860,"UZB","Uzbekistan","ppp_2011","GIS/Population/Global_2000_2020/2011/UZB/uzb_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2982,862,"VEN","Venezuela","ppp_2011","GIS/Population/Global_2000_2020/2011/VEN/ven_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2983,876,"WLF","Wallis and Futuna","ppp_2011","GIS/Population/Global_2000_2020/2011/WLF/wlf_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2984,882,"WSM","Samoa","ppp_2011","GIS/Population/Global_2000_2020/2011/WSM/wsm_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2985,887,"YEM","Yemen","ppp_2011","GIS/Population/Global_2000_2020/2011/YEM/yem_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2986,894,"ZMB","Zambia","ppp_2011","GIS/Population/Global_2000_2020/2011/ZMB/zmb_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2987,900,"KOS","Kosovo","ppp_2011","GIS/Population/Global_2000_2020/2011/KOS/kos_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2988,901,"SPR","Spratly Islands","ppp_2011","GIS/Population/Global_2000_2020/2011/SPR/spr_ppp_2011.tif","Estimated total number of people per grid-cell 2011 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2989,643,"RUS","Russia","ppp_2012","GIS/Population/Global_2000_2020/2012/RUS/rus_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2990,360,"IDN","Indonesia","ppp_2012","GIS/Population/Global_2000_2020/2012/IDN/idn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2991,840,"USA","United States","ppp_2012","GIS/Population/Global_2000_2020/2012/USA/usa_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2992,850,"VIR","Virgin_Islands_U_S","ppp_2012","GIS/Population/Global_2000_2020/2012/VIR/vir_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2993,304,"GRL","Greenland","ppp_2012","GIS/Population/Global_2000_2020/2012/GRL/grl_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2994,156,"CHN","China","ppp_2012","GIS/Population/Global_2000_2020/2012/CHN/chn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2995,36,"AUS","Australia","ppp_2012","GIS/Population/Global_2000_2020/2012/AUS/aus_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2996,76,"BRA","Brazil","ppp_2012","GIS/Population/Global_2000_2020/2012/BRA/bra_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2997,124,"CAN","Canada","ppp_2012","GIS/Population/Global_2000_2020/2012/CAN/can_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2998,152,"CHL","Chile","ppp_2012","GIS/Population/Global_2000_2020/2012/CHL/chl_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
2999,4,"AFG","Afghanistan","ppp_2012","GIS/Population/Global_2000_2020/2012/AFG/afg_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3000,8,"ALB","Albania","ppp_2012","GIS/Population/Global_2000_2020/2012/ALB/alb_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3001,10,"ATA","Antarctica","ppp_2012","GIS/Population/Global_2000_2020/2012/ATA/ata_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3002,12,"DZA","Algeria","ppp_2012","GIS/Population/Global_2000_2020/2012/DZA/dza_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3003,16,"ASM","American Samoa","ppp_2012","GIS/Population/Global_2000_2020/2012/ASM/asm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3004,20,"AND","Andorra","ppp_2012","GIS/Population/Global_2000_2020/2012/AND/and_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3005,24,"AGO","Angola","ppp_2012","GIS/Population/Global_2000_2020/2012/AGO/ago_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3006,28,"ATG","Antigua and Barbuda","ppp_2012","GIS/Population/Global_2000_2020/2012/ATG/atg_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3007,31,"AZE","Azerbaijan","ppp_2012","GIS/Population/Global_2000_2020/2012/AZE/aze_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3008,32,"ARG","Argentina","ppp_2012","GIS/Population/Global_2000_2020/2012/ARG/arg_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3009,40,"AUT","Austria","ppp_2012","GIS/Population/Global_2000_2020/2012/AUT/aut_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3010,44,"BHS","Bahamas","ppp_2012","GIS/Population/Global_2000_2020/2012/BHS/bhs_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3011,48,"BHR","Bahrain","ppp_2012","GIS/Population/Global_2000_2020/2012/BHR/bhr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3012,50,"BGD","Bangladesh","ppp_2012","GIS/Population/Global_2000_2020/2012/BGD/bgd_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3013,51,"ARM","Armenia","ppp_2012","GIS/Population/Global_2000_2020/2012/ARM/arm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3014,52,"BRB","Barbados","ppp_2012","GIS/Population/Global_2000_2020/2012/BRB/brb_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3015,56,"BEL","Belgium","ppp_2012","GIS/Population/Global_2000_2020/2012/BEL/bel_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3016,60,"BMU","Bermuda","ppp_2012","GIS/Population/Global_2000_2020/2012/BMU/bmu_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3017,64,"BTN","Bhutan","ppp_2012","GIS/Population/Global_2000_2020/2012/BTN/btn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3018,68,"BOL","Bolivia","ppp_2012","GIS/Population/Global_2000_2020/2012/BOL/bol_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3019,70,"BIH","Bosnia and Herzegovina","ppp_2012","GIS/Population/Global_2000_2020/2012/BIH/bih_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3020,72,"BWA","Botswana","ppp_2012","GIS/Population/Global_2000_2020/2012/BWA/bwa_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3021,74,"BVT","Bouvet Island","ppp_2012","GIS/Population/Global_2000_2020/2012/BVT/bvt_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3022,84,"BLZ","Belize","ppp_2012","GIS/Population/Global_2000_2020/2012/BLZ/blz_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3023,86,"IOT","British Indian Ocean Territory","ppp_2012","GIS/Population/Global_2000_2020/2012/IOT/iot_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3024,90,"SLB","Solomon Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/SLB/slb_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3025,92,"VGB","British Virgin Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/VGB/vgb_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3026,96,"BRN","Brunei","ppp_2012","GIS/Population/Global_2000_2020/2012/BRN/brn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3027,100,"BGR","Bulgaria","ppp_2012","GIS/Population/Global_2000_2020/2012/BGR/bgr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3028,104,"MMR","Myanmar","ppp_2012","GIS/Population/Global_2000_2020/2012/MMR/mmr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3029,108,"BDI","Burundi","ppp_2012","GIS/Population/Global_2000_2020/2012/BDI/bdi_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3030,112,"BLR","Belarus","ppp_2012","GIS/Population/Global_2000_2020/2012/BLR/blr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3031,116,"KHM","Cambodia","ppp_2012","GIS/Population/Global_2000_2020/2012/KHM/khm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3032,120,"CMR","Cameroon","ppp_2012","GIS/Population/Global_2000_2020/2012/CMR/cmr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3033,132,"CPV","Cape Verde","ppp_2012","GIS/Population/Global_2000_2020/2012/CPV/cpv_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3034,136,"CYM","Cayman Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/CYM/cym_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3035,140,"CAF","Central African Republic","ppp_2012","GIS/Population/Global_2000_2020/2012/CAF/caf_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3036,144,"LKA","Sri Lanka","ppp_2012","GIS/Population/Global_2000_2020/2012/LKA/lka_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3037,148,"TCD","Chad","ppp_2012","GIS/Population/Global_2000_2020/2012/TCD/tcd_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3038,158,"TWN","Taiwan","ppp_2012","GIS/Population/Global_2000_2020/2012/TWN/twn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3039,170,"COL","Colombia","ppp_2012","GIS/Population/Global_2000_2020/2012/COL/col_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3040,174,"COM","Comoros","ppp_2012","GIS/Population/Global_2000_2020/2012/COM/com_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3041,175,"MYT","Mayotte","ppp_2012","GIS/Population/Global_2000_2020/2012/MYT/myt_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3042,178,"COG","Republic of Congo","ppp_2012","GIS/Population/Global_2000_2020/2012/COG/cog_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3043,180,"COD","Democratic Republic of the Congo","ppp_2012","GIS/Population/Global_2000_2020/2012/COD/cod_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3044,184,"COK","Cook Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/COK/cok_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3045,188,"CRI","Costa Rica","ppp_2012","GIS/Population/Global_2000_2020/2012/CRI/cri_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3046,191,"HRV","Croatia","ppp_2012","GIS/Population/Global_2000_2020/2012/HRV/hrv_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3047,192,"CUB","Cuba","ppp_2012","GIS/Population/Global_2000_2020/2012/CUB/cub_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3048,196,"CYP","Cyprus","ppp_2012","GIS/Population/Global_2000_2020/2012/CYP/cyp_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3049,203,"CZE","Czech Republic","ppp_2012","GIS/Population/Global_2000_2020/2012/CZE/cze_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3050,204,"BEN","Benin","ppp_2012","GIS/Population/Global_2000_2020/2012/BEN/ben_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3051,208,"DNK","Denmark","ppp_2012","GIS/Population/Global_2000_2020/2012/DNK/dnk_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3052,212,"DMA","Dominica","ppp_2012","GIS/Population/Global_2000_2020/2012/DMA/dma_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3053,214,"DOM","Dominican Republic","ppp_2012","GIS/Population/Global_2000_2020/2012/DOM/dom_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3054,218,"ECU","Ecuador","ppp_2012","GIS/Population/Global_2000_2020/2012/ECU/ecu_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3055,222,"SLV","El Salvador","ppp_2012","GIS/Population/Global_2000_2020/2012/SLV/slv_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3056,226,"GNQ","Equatorial Guinea","ppp_2012","GIS/Population/Global_2000_2020/2012/GNQ/gnq_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3057,231,"ETH","Ethiopia","ppp_2012","GIS/Population/Global_2000_2020/2012/ETH/eth_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3058,232,"ERI","Eritrea","ppp_2012","GIS/Population/Global_2000_2020/2012/ERI/eri_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3059,233,"EST","Estonia","ppp_2012","GIS/Population/Global_2000_2020/2012/EST/est_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3060,234,"FRO","Faroe Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/FRO/fro_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3061,238,"FLK","Falkland Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/FLK/flk_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3062,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/SGS/sgs_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3063,242,"FJI","Fiji","ppp_2012","GIS/Population/Global_2000_2020/2012/FJI/fji_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3064,246,"FIN","Finland","ppp_2012","GIS/Population/Global_2000_2020/2012/FIN/fin_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3065,248,"ALA","Aland Islands ","ppp_2012","GIS/Population/Global_2000_2020/2012/ALA/ala_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3066,250,"FRA","France","ppp_2012","GIS/Population/Global_2000_2020/2012/FRA/fra_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3067,254,"GUF","French Guiana","ppp_2012","GIS/Population/Global_2000_2020/2012/GUF/guf_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3068,258,"PYF","French Polynesia","ppp_2012","GIS/Population/Global_2000_2020/2012/PYF/pyf_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3069,260,"ATF","French Southern Territories","ppp_2012","GIS/Population/Global_2000_2020/2012/ATF/atf_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3070,262,"DJI","Djibouti","ppp_2012","GIS/Population/Global_2000_2020/2012/DJI/dji_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3071,266,"GAB","Gabon","ppp_2012","GIS/Population/Global_2000_2020/2012/GAB/gab_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3072,268,"GEO","Georgia","ppp_2012","GIS/Population/Global_2000_2020/2012/GEO/geo_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3073,270,"GMB","Gambia","ppp_2012","GIS/Population/Global_2000_2020/2012/GMB/gmb_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3074,275,"PSE","Palestina","ppp_2012","GIS/Population/Global_2000_2020/2012/PSE/pse_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3075,276,"DEU","Germany","ppp_2012","GIS/Population/Global_2000_2020/2012/DEU/deu_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3076,288,"GHA","Ghana","ppp_2012","GIS/Population/Global_2000_2020/2012/GHA/gha_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3077,292,"GIB","Gibraltar","ppp_2012","GIS/Population/Global_2000_2020/2012/GIB/gib_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3078,296,"KIR","Kiribati","ppp_2012","GIS/Population/Global_2000_2020/2012/KIR/kir_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3079,300,"GRC","Greece","ppp_2012","GIS/Population/Global_2000_2020/2012/GRC/grc_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3080,308,"GRD","Grenada","ppp_2012","GIS/Population/Global_2000_2020/2012/GRD/grd_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3081,312,"GLP","Guadeloupe","ppp_2012","GIS/Population/Global_2000_2020/2012/GLP/glp_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3082,316,"GUM","Guam","ppp_2012","GIS/Population/Global_2000_2020/2012/GUM/gum_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3083,320,"GTM","Guatemala","ppp_2012","GIS/Population/Global_2000_2020/2012/GTM/gtm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3084,324,"GIN","Guinea","ppp_2012","GIS/Population/Global_2000_2020/2012/GIN/gin_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3085,328,"GUY","Guyana","ppp_2012","GIS/Population/Global_2000_2020/2012/GUY/guy_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3086,332,"HTI","Haiti","ppp_2012","GIS/Population/Global_2000_2020/2012/HTI/hti_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3087,334,"HMD","Heard Island and McDonald Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/HMD/hmd_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3088,336,"VAT","Vatican City","ppp_2012","GIS/Population/Global_2000_2020/2012/VAT/vat_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3089,340,"HND","Honduras","ppp_2012","GIS/Population/Global_2000_2020/2012/HND/hnd_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3090,344,"HKG","Hong Kong","ppp_2012","GIS/Population/Global_2000_2020/2012/HKG/hkg_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3091,348,"HUN","Hungary","ppp_2012","GIS/Population/Global_2000_2020/2012/HUN/hun_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3092,352,"ISL","Iceland","ppp_2012","GIS/Population/Global_2000_2020/2012/ISL/isl_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3093,356,"IND","India","ppp_2012","GIS/Population/Global_2000_2020/2012/IND/ind_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3094,364,"IRN","Iran","ppp_2012","GIS/Population/Global_2000_2020/2012/IRN/irn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3095,368,"IRQ","Iraq","ppp_2012","GIS/Population/Global_2000_2020/2012/IRQ/irq_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3096,372,"IRL","Ireland","ppp_2012","GIS/Population/Global_2000_2020/2012/IRL/irl_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3097,376,"ISR","Israel","ppp_2012","GIS/Population/Global_2000_2020/2012/ISR/isr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3098,380,"ITA","Italy","ppp_2012","GIS/Population/Global_2000_2020/2012/ITA/ita_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3099,384,"CIV","CIte dIvoire","ppp_2012","GIS/Population/Global_2000_2020/2012/CIV/civ_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3100,388,"JAM","Jamaica","ppp_2012","GIS/Population/Global_2000_2020/2012/JAM/jam_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3101,392,"JPN","Japan","ppp_2012","GIS/Population/Global_2000_2020/2012/JPN/jpn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3102,398,"KAZ","Kazakhstan","ppp_2012","GIS/Population/Global_2000_2020/2012/KAZ/kaz_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3103,400,"JOR","Jordan","ppp_2012","GIS/Population/Global_2000_2020/2012/JOR/jor_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3104,404,"KEN","Kenya","ppp_2012","GIS/Population/Global_2000_2020/2012/KEN/ken_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3105,408,"PRK","North Korea","ppp_2012","GIS/Population/Global_2000_2020/2012/PRK/prk_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3106,410,"KOR","South Korea","ppp_2012","GIS/Population/Global_2000_2020/2012/KOR/kor_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3107,414,"KWT","Kuwait","ppp_2012","GIS/Population/Global_2000_2020/2012/KWT/kwt_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3108,417,"KGZ","Kyrgyzstan","ppp_2012","GIS/Population/Global_2000_2020/2012/KGZ/kgz_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3109,418,"LAO","Laos","ppp_2012","GIS/Population/Global_2000_2020/2012/LAO/lao_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3110,422,"LBN","Lebanon","ppp_2012","GIS/Population/Global_2000_2020/2012/LBN/lbn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3111,426,"LSO","Lesotho","ppp_2012","GIS/Population/Global_2000_2020/2012/LSO/lso_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3112,428,"LVA","Latvia","ppp_2012","GIS/Population/Global_2000_2020/2012/LVA/lva_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3113,430,"LBR","Liberia","ppp_2012","GIS/Population/Global_2000_2020/2012/LBR/lbr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3114,434,"LBY","Libya","ppp_2012","GIS/Population/Global_2000_2020/2012/LBY/lby_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3115,438,"LIE","Liechtenstein","ppp_2012","GIS/Population/Global_2000_2020/2012/LIE/lie_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3116,440,"LTU","Lithuania","ppp_2012","GIS/Population/Global_2000_2020/2012/LTU/ltu_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3117,442,"LUX","Luxembourg","ppp_2012","GIS/Population/Global_2000_2020/2012/LUX/lux_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3118,446,"MAC","Macao","ppp_2012","GIS/Population/Global_2000_2020/2012/MAC/mac_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3119,450,"MDG","Madagascar","ppp_2012","GIS/Population/Global_2000_2020/2012/MDG/mdg_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3120,454,"MWI","Malawi","ppp_2012","GIS/Population/Global_2000_2020/2012/MWI/mwi_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3121,458,"MYS","Malaysia","ppp_2012","GIS/Population/Global_2000_2020/2012/MYS/mys_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3122,462,"MDV","Maldives","ppp_2012","GIS/Population/Global_2000_2020/2012/MDV/mdv_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3123,466,"MLI","Mali","ppp_2012","GIS/Population/Global_2000_2020/2012/MLI/mli_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3124,470,"MLT","Malta","ppp_2012","GIS/Population/Global_2000_2020/2012/MLT/mlt_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3125,474,"MTQ","Martinique","ppp_2012","GIS/Population/Global_2000_2020/2012/MTQ/mtq_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3126,478,"MRT","Mauritania","ppp_2012","GIS/Population/Global_2000_2020/2012/MRT/mrt_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3127,480,"MUS","Mauritius","ppp_2012","GIS/Population/Global_2000_2020/2012/MUS/mus_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3128,484,"MEX","Mexico","ppp_2012","GIS/Population/Global_2000_2020/2012/MEX/mex_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3129,492,"MCO","Monaco","ppp_2012","GIS/Population/Global_2000_2020/2012/MCO/mco_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3130,496,"MNG","Mongolia","ppp_2012","GIS/Population/Global_2000_2020/2012/MNG/mng_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3131,498,"MDA","Moldova","ppp_2012","GIS/Population/Global_2000_2020/2012/MDA/mda_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3132,499,"MNE","Montenegro","ppp_2012","GIS/Population/Global_2000_2020/2012/MNE/mne_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3133,500,"MSR","Montserrat","ppp_2012","GIS/Population/Global_2000_2020/2012/MSR/msr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3134,504,"MAR","Morocco","ppp_2012","GIS/Population/Global_2000_2020/2012/MAR/mar_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3135,508,"MOZ","Mozambique","ppp_2012","GIS/Population/Global_2000_2020/2012/MOZ/moz_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3136,512,"OMN","Oman","ppp_2012","GIS/Population/Global_2000_2020/2012/OMN/omn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3137,516,"NAM","Namibia","ppp_2012","GIS/Population/Global_2000_2020/2012/NAM/nam_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3138,520,"NRU","Nauru","ppp_2012","GIS/Population/Global_2000_2020/2012/NRU/nru_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3139,524,"NPL","Nepal","ppp_2012","GIS/Population/Global_2000_2020/2012/NPL/npl_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3140,528,"NLD","Netherlands","ppp_2012","GIS/Population/Global_2000_2020/2012/NLD/nld_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3141,531,"CUW","Curacao","ppp_2012","GIS/Population/Global_2000_2020/2012/CUW/cuw_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3142,533,"ABW","Aruba","ppp_2012","GIS/Population/Global_2000_2020/2012/ABW/abw_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3143,534,"SXM","Sint Maarten (Dutch part)","ppp_2012","GIS/Population/Global_2000_2020/2012/SXM/sxm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3144,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2012","GIS/Population/Global_2000_2020/2012/BES/bes_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3145,540,"NCL","New Caledonia","ppp_2012","GIS/Population/Global_2000_2020/2012/NCL/ncl_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3146,548,"VUT","Vanuatu","ppp_2012","GIS/Population/Global_2000_2020/2012/VUT/vut_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3147,554,"NZL","New Zealand","ppp_2012","GIS/Population/Global_2000_2020/2012/NZL/nzl_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3148,558,"NIC","Nicaragua","ppp_2012","GIS/Population/Global_2000_2020/2012/NIC/nic_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3149,562,"NER","Niger","ppp_2012","GIS/Population/Global_2000_2020/2012/NER/ner_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3150,566,"NGA","Nigeria","ppp_2012","GIS/Population/Global_2000_2020/2012/NGA/nga_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3151,570,"NIU","Niue","ppp_2012","GIS/Population/Global_2000_2020/2012/NIU/niu_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3152,574,"NFK","Norfolk Island","ppp_2012","GIS/Population/Global_2000_2020/2012/NFK/nfk_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3153,578,"NOR","Norway","ppp_2012","GIS/Population/Global_2000_2020/2012/NOR/nor_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3154,580,"MNP","Northern Mariana Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/MNP/mnp_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3155,581,"UMI","United States Minor Outlying Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/UMI/umi_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3156,583,"FSM","Micronesia","ppp_2012","GIS/Population/Global_2000_2020/2012/FSM/fsm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3157,584,"MHL","Marshall Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/MHL/mhl_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3158,585,"PLW","Palau","ppp_2012","GIS/Population/Global_2000_2020/2012/PLW/plw_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3159,586,"PAK","Pakistan","ppp_2012","GIS/Population/Global_2000_2020/2012/PAK/pak_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3160,591,"PAN","Panama","ppp_2012","GIS/Population/Global_2000_2020/2012/PAN/pan_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3161,598,"PNG","Papua New Guinea","ppp_2012","GIS/Population/Global_2000_2020/2012/PNG/png_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3162,600,"PRY","Paraguay","ppp_2012","GIS/Population/Global_2000_2020/2012/PRY/pry_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3163,604,"PER","Peru","ppp_2012","GIS/Population/Global_2000_2020/2012/PER/per_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3164,608,"PHL","Philippines","ppp_2012","GIS/Population/Global_2000_2020/2012/PHL/phl_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3165,612,"PCN","Pitcairn Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/PCN/pcn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3166,616,"POL","Poland","ppp_2012","GIS/Population/Global_2000_2020/2012/POL/pol_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3167,620,"PRT","Portugal","ppp_2012","GIS/Population/Global_2000_2020/2012/PRT/prt_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3168,624,"GNB","Guinea-Bissau","ppp_2012","GIS/Population/Global_2000_2020/2012/GNB/gnb_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3169,626,"TLS","East Timor","ppp_2012","GIS/Population/Global_2000_2020/2012/TLS/tls_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3170,630,"PRI","Puerto Rico","ppp_2012","GIS/Population/Global_2000_2020/2012/PRI/pri_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3171,634,"QAT","Qatar","ppp_2012","GIS/Population/Global_2000_2020/2012/QAT/qat_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3172,638,"REU","Reunion","ppp_2012","GIS/Population/Global_2000_2020/2012/REU/reu_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3173,642,"ROU","Romania","ppp_2012","GIS/Population/Global_2000_2020/2012/ROU/rou_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3174,646,"RWA","Rwanda","ppp_2012","GIS/Population/Global_2000_2020/2012/RWA/rwa_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3175,652,"BLM","Saint Barthelemy","ppp_2012","GIS/Population/Global_2000_2020/2012/BLM/blm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3176,654,"SHN","Saint Helena","ppp_2012","GIS/Population/Global_2000_2020/2012/SHN/shn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3177,659,"KNA","Saint Kitts and Nevis","ppp_2012","GIS/Population/Global_2000_2020/2012/KNA/kna_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3178,660,"AIA","Anguilla","ppp_2012","GIS/Population/Global_2000_2020/2012/AIA/aia_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3179,662,"LCA","Saint Lucia","ppp_2012","GIS/Population/Global_2000_2020/2012/LCA/lca_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3180,663,"MAF","Saint Martin (French part)","ppp_2012","GIS/Population/Global_2000_2020/2012/MAF/maf_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3181,666,"SPM","Saint Pierre and Miquelon","ppp_2012","GIS/Population/Global_2000_2020/2012/SPM/spm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3182,670,"VCT","Saint Vincent and the Grenadines","ppp_2012","GIS/Population/Global_2000_2020/2012/VCT/vct_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3183,674,"SMR","San Marino","ppp_2012","GIS/Population/Global_2000_2020/2012/SMR/smr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3184,678,"STP","Sao Tome and Principe","ppp_2012","GIS/Population/Global_2000_2020/2012/STP/stp_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3185,682,"SAU","Saudi Arabia","ppp_2012","GIS/Population/Global_2000_2020/2012/SAU/sau_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3186,686,"SEN","Senegal","ppp_2012","GIS/Population/Global_2000_2020/2012/SEN/sen_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3187,688,"SRB","Serbia","ppp_2012","GIS/Population/Global_2000_2020/2012/SRB/srb_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3188,690,"SYC","Seychelles","ppp_2012","GIS/Population/Global_2000_2020/2012/SYC/syc_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3189,694,"SLE","Sierra Leone","ppp_2012","GIS/Population/Global_2000_2020/2012/SLE/sle_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3190,702,"SGP","Singapore","ppp_2012","GIS/Population/Global_2000_2020/2012/SGP/sgp_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3191,703,"SVK","Slovakia","ppp_2012","GIS/Population/Global_2000_2020/2012/SVK/svk_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3192,704,"VNM","Vietnam","ppp_2012","GIS/Population/Global_2000_2020/2012/VNM/vnm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3193,705,"SVN","Slovenia","ppp_2012","GIS/Population/Global_2000_2020/2012/SVN/svn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3194,706,"SOM","Somalia","ppp_2012","GIS/Population/Global_2000_2020/2012/SOM/som_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3195,710,"ZAF","South Africa","ppp_2012","GIS/Population/Global_2000_2020/2012/ZAF/zaf_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3196,716,"ZWE","Zimbabwe","ppp_2012","GIS/Population/Global_2000_2020/2012/ZWE/zwe_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3197,724,"ESP","Spain","ppp_2012","GIS/Population/Global_2000_2020/2012/ESP/esp_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3198,728,"SSD","South Sudan","ppp_2012","GIS/Population/Global_2000_2020/2012/SSD/ssd_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3199,729,"SDN","Sudan","ppp_2012","GIS/Population/Global_2000_2020/2012/SDN/sdn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3200,732,"ESH","Western Sahara","ppp_2012","GIS/Population/Global_2000_2020/2012/ESH/esh_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3201,740,"SUR","Suriname","ppp_2012","GIS/Population/Global_2000_2020/2012/SUR/sur_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3202,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/SJM/sjm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3203,748,"SWZ","Swaziland","ppp_2012","GIS/Population/Global_2000_2020/2012/SWZ/swz_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3204,752,"SWE","Sweden","ppp_2012","GIS/Population/Global_2000_2020/2012/SWE/swe_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3205,756,"CHE","Switzerland","ppp_2012","GIS/Population/Global_2000_2020/2012/CHE/che_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3206,760,"SYR","Syria","ppp_2012","GIS/Population/Global_2000_2020/2012/SYR/syr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3207,762,"TJK","Tajikistan","ppp_2012","GIS/Population/Global_2000_2020/2012/TJK/tjk_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3208,764,"THA","Thailand","ppp_2012","GIS/Population/Global_2000_2020/2012/THA/tha_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3209,768,"TGO","Togo","ppp_2012","GIS/Population/Global_2000_2020/2012/TGO/tgo_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3210,772,"TKL","Tokelau","ppp_2012","GIS/Population/Global_2000_2020/2012/TKL/tkl_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3211,776,"TON","Tonga","ppp_2012","GIS/Population/Global_2000_2020/2012/TON/ton_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3212,780,"TTO","Trinidad and Tobago","ppp_2012","GIS/Population/Global_2000_2020/2012/TTO/tto_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3213,784,"ARE","United Arab Emirates","ppp_2012","GIS/Population/Global_2000_2020/2012/ARE/are_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3214,788,"TUN","Tunisia","ppp_2012","GIS/Population/Global_2000_2020/2012/TUN/tun_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3215,792,"TUR","Turkey","ppp_2012","GIS/Population/Global_2000_2020/2012/TUR/tur_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3216,795,"TKM","Turkmenistan","ppp_2012","GIS/Population/Global_2000_2020/2012/TKM/tkm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3217,796,"TCA","Turks and Caicos Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/TCA/tca_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3218,798,"TUV","Tuvalu","ppp_2012","GIS/Population/Global_2000_2020/2012/TUV/tuv_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3219,800,"UGA","Uganda","ppp_2012","GIS/Population/Global_2000_2020/2012/UGA/uga_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3220,804,"UKR","Ukraine","ppp_2012","GIS/Population/Global_2000_2020/2012/UKR/ukr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3221,807,"MKD","Macedonia","ppp_2012","GIS/Population/Global_2000_2020/2012/MKD/mkd_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3222,818,"EGY","Egypt","ppp_2012","GIS/Population/Global_2000_2020/2012/EGY/egy_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3223,826,"GBR","United Kingdom","ppp_2012","GIS/Population/Global_2000_2020/2012/GBR/gbr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3224,831,"GGY","Guernsey","ppp_2012","GIS/Population/Global_2000_2020/2012/GGY/ggy_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3225,832,"JEY","Jersey","ppp_2012","GIS/Population/Global_2000_2020/2012/JEY/jey_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3226,833,"IMN","Isle of Man","ppp_2012","GIS/Population/Global_2000_2020/2012/IMN/imn_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3227,834,"TZA","Tanzania","ppp_2012","GIS/Population/Global_2000_2020/2012/TZA/tza_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3228,854,"BFA","Burkina Faso","ppp_2012","GIS/Population/Global_2000_2020/2012/BFA/bfa_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3229,858,"URY","Uruguay","ppp_2012","GIS/Population/Global_2000_2020/2012/URY/ury_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3230,860,"UZB","Uzbekistan","ppp_2012","GIS/Population/Global_2000_2020/2012/UZB/uzb_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3231,862,"VEN","Venezuela","ppp_2012","GIS/Population/Global_2000_2020/2012/VEN/ven_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3232,876,"WLF","Wallis and Futuna","ppp_2012","GIS/Population/Global_2000_2020/2012/WLF/wlf_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3233,882,"WSM","Samoa","ppp_2012","GIS/Population/Global_2000_2020/2012/WSM/wsm_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3234,887,"YEM","Yemen","ppp_2012","GIS/Population/Global_2000_2020/2012/YEM/yem_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3235,894,"ZMB","Zambia","ppp_2012","GIS/Population/Global_2000_2020/2012/ZMB/zmb_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3236,900,"KOS","Kosovo","ppp_2012","GIS/Population/Global_2000_2020/2012/KOS/kos_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3237,901,"SPR","Spratly Islands","ppp_2012","GIS/Population/Global_2000_2020/2012/SPR/spr_ppp_2012.tif","Estimated total number of people per grid-cell 2012 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3238,643,"RUS","Russia","ppp_2013","GIS/Population/Global_2000_2020/2013/RUS/rus_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3239,360,"IDN","Indonesia","ppp_2013","GIS/Population/Global_2000_2020/2013/IDN/idn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3240,840,"USA","United States","ppp_2013","GIS/Population/Global_2000_2020/2013/USA/usa_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3241,850,"VIR","Virgin_Islands_U_S","ppp_2013","GIS/Population/Global_2000_2020/2013/VIR/vir_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3242,304,"GRL","Greenland","ppp_2013","GIS/Population/Global_2000_2020/2013/GRL/grl_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3243,156,"CHN","China","ppp_2013","GIS/Population/Global_2000_2020/2013/CHN/chn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3244,36,"AUS","Australia","ppp_2013","GIS/Population/Global_2000_2020/2013/AUS/aus_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3245,76,"BRA","Brazil","ppp_2013","GIS/Population/Global_2000_2020/2013/BRA/bra_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3246,124,"CAN","Canada","ppp_2013","GIS/Population/Global_2000_2020/2013/CAN/can_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3247,152,"CHL","Chile","ppp_2013","GIS/Population/Global_2000_2020/2013/CHL/chl_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3248,4,"AFG","Afghanistan","ppp_2013","GIS/Population/Global_2000_2020/2013/AFG/afg_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3249,8,"ALB","Albania","ppp_2013","GIS/Population/Global_2000_2020/2013/ALB/alb_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3250,10,"ATA","Antarctica","ppp_2013","GIS/Population/Global_2000_2020/2013/ATA/ata_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3251,12,"DZA","Algeria","ppp_2013","GIS/Population/Global_2000_2020/2013/DZA/dza_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3252,16,"ASM","American Samoa","ppp_2013","GIS/Population/Global_2000_2020/2013/ASM/asm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3253,20,"AND","Andorra","ppp_2013","GIS/Population/Global_2000_2020/2013/AND/and_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3254,24,"AGO","Angola","ppp_2013","GIS/Population/Global_2000_2020/2013/AGO/ago_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3255,28,"ATG","Antigua and Barbuda","ppp_2013","GIS/Population/Global_2000_2020/2013/ATG/atg_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3256,31,"AZE","Azerbaijan","ppp_2013","GIS/Population/Global_2000_2020/2013/AZE/aze_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3257,32,"ARG","Argentina","ppp_2013","GIS/Population/Global_2000_2020/2013/ARG/arg_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3258,40,"AUT","Austria","ppp_2013","GIS/Population/Global_2000_2020/2013/AUT/aut_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3259,44,"BHS","Bahamas","ppp_2013","GIS/Population/Global_2000_2020/2013/BHS/bhs_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3260,48,"BHR","Bahrain","ppp_2013","GIS/Population/Global_2000_2020/2013/BHR/bhr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3261,50,"BGD","Bangladesh","ppp_2013","GIS/Population/Global_2000_2020/2013/BGD/bgd_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3262,51,"ARM","Armenia","ppp_2013","GIS/Population/Global_2000_2020/2013/ARM/arm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3263,52,"BRB","Barbados","ppp_2013","GIS/Population/Global_2000_2020/2013/BRB/brb_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3264,56,"BEL","Belgium","ppp_2013","GIS/Population/Global_2000_2020/2013/BEL/bel_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3265,60,"BMU","Bermuda","ppp_2013","GIS/Population/Global_2000_2020/2013/BMU/bmu_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3266,64,"BTN","Bhutan","ppp_2013","GIS/Population/Global_2000_2020/2013/BTN/btn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3267,68,"BOL","Bolivia","ppp_2013","GIS/Population/Global_2000_2020/2013/BOL/bol_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3268,70,"BIH","Bosnia and Herzegovina","ppp_2013","GIS/Population/Global_2000_2020/2013/BIH/bih_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3269,72,"BWA","Botswana","ppp_2013","GIS/Population/Global_2000_2020/2013/BWA/bwa_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3270,74,"BVT","Bouvet Island","ppp_2013","GIS/Population/Global_2000_2020/2013/BVT/bvt_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3271,84,"BLZ","Belize","ppp_2013","GIS/Population/Global_2000_2020/2013/BLZ/blz_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3272,86,"IOT","British Indian Ocean Territory","ppp_2013","GIS/Population/Global_2000_2020/2013/IOT/iot_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3273,90,"SLB","Solomon Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/SLB/slb_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3274,92,"VGB","British Virgin Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/VGB/vgb_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3275,96,"BRN","Brunei","ppp_2013","GIS/Population/Global_2000_2020/2013/BRN/brn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3276,100,"BGR","Bulgaria","ppp_2013","GIS/Population/Global_2000_2020/2013/BGR/bgr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3277,104,"MMR","Myanmar","ppp_2013","GIS/Population/Global_2000_2020/2013/MMR/mmr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3278,108,"BDI","Burundi","ppp_2013","GIS/Population/Global_2000_2020/2013/BDI/bdi_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3279,112,"BLR","Belarus","ppp_2013","GIS/Population/Global_2000_2020/2013/BLR/blr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3280,116,"KHM","Cambodia","ppp_2013","GIS/Population/Global_2000_2020/2013/KHM/khm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3281,120,"CMR","Cameroon","ppp_2013","GIS/Population/Global_2000_2020/2013/CMR/cmr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3282,132,"CPV","Cape Verde","ppp_2013","GIS/Population/Global_2000_2020/2013/CPV/cpv_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3283,136,"CYM","Cayman Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/CYM/cym_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3284,140,"CAF","Central African Republic","ppp_2013","GIS/Population/Global_2000_2020/2013/CAF/caf_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3285,144,"LKA","Sri Lanka","ppp_2013","GIS/Population/Global_2000_2020/2013/LKA/lka_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3286,148,"TCD","Chad","ppp_2013","GIS/Population/Global_2000_2020/2013/TCD/tcd_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3287,158,"TWN","Taiwan","ppp_2013","GIS/Population/Global_2000_2020/2013/TWN/twn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3288,170,"COL","Colombia","ppp_2013","GIS/Population/Global_2000_2020/2013/COL/col_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3289,174,"COM","Comoros","ppp_2013","GIS/Population/Global_2000_2020/2013/COM/com_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3290,175,"MYT","Mayotte","ppp_2013","GIS/Population/Global_2000_2020/2013/MYT/myt_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3291,178,"COG","Republic of Congo","ppp_2013","GIS/Population/Global_2000_2020/2013/COG/cog_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3292,180,"COD","Democratic Republic of the Congo","ppp_2013","GIS/Population/Global_2000_2020/2013/COD/cod_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3293,184,"COK","Cook Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/COK/cok_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3294,188,"CRI","Costa Rica","ppp_2013","GIS/Population/Global_2000_2020/2013/CRI/cri_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3295,191,"HRV","Croatia","ppp_2013","GIS/Population/Global_2000_2020/2013/HRV/hrv_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3296,192,"CUB","Cuba","ppp_2013","GIS/Population/Global_2000_2020/2013/CUB/cub_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3297,196,"CYP","Cyprus","ppp_2013","GIS/Population/Global_2000_2020/2013/CYP/cyp_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3298,203,"CZE","Czech Republic","ppp_2013","GIS/Population/Global_2000_2020/2013/CZE/cze_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3299,204,"BEN","Benin","ppp_2013","GIS/Population/Global_2000_2020/2013/BEN/ben_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3300,208,"DNK","Denmark","ppp_2013","GIS/Population/Global_2000_2020/2013/DNK/dnk_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3301,212,"DMA","Dominica","ppp_2013","GIS/Population/Global_2000_2020/2013/DMA/dma_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3302,214,"DOM","Dominican Republic","ppp_2013","GIS/Population/Global_2000_2020/2013/DOM/dom_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3303,218,"ECU","Ecuador","ppp_2013","GIS/Population/Global_2000_2020/2013/ECU/ecu_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3304,222,"SLV","El Salvador","ppp_2013","GIS/Population/Global_2000_2020/2013/SLV/slv_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3305,226,"GNQ","Equatorial Guinea","ppp_2013","GIS/Population/Global_2000_2020/2013/GNQ/gnq_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3306,231,"ETH","Ethiopia","ppp_2013","GIS/Population/Global_2000_2020/2013/ETH/eth_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3307,232,"ERI","Eritrea","ppp_2013","GIS/Population/Global_2000_2020/2013/ERI/eri_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3308,233,"EST","Estonia","ppp_2013","GIS/Population/Global_2000_2020/2013/EST/est_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3309,234,"FRO","Faroe Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/FRO/fro_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3310,238,"FLK","Falkland Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/FLK/flk_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3311,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/SGS/sgs_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3312,242,"FJI","Fiji","ppp_2013","GIS/Population/Global_2000_2020/2013/FJI/fji_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3313,246,"FIN","Finland","ppp_2013","GIS/Population/Global_2000_2020/2013/FIN/fin_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3314,248,"ALA","Aland Islands ","ppp_2013","GIS/Population/Global_2000_2020/2013/ALA/ala_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3315,250,"FRA","France","ppp_2013","GIS/Population/Global_2000_2020/2013/FRA/fra_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3316,254,"GUF","French Guiana","ppp_2013","GIS/Population/Global_2000_2020/2013/GUF/guf_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3317,258,"PYF","French Polynesia","ppp_2013","GIS/Population/Global_2000_2020/2013/PYF/pyf_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3318,260,"ATF","French Southern Territories","ppp_2013","GIS/Population/Global_2000_2020/2013/ATF/atf_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3319,262,"DJI","Djibouti","ppp_2013","GIS/Population/Global_2000_2020/2013/DJI/dji_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3320,266,"GAB","Gabon","ppp_2013","GIS/Population/Global_2000_2020/2013/GAB/gab_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3321,268,"GEO","Georgia","ppp_2013","GIS/Population/Global_2000_2020/2013/GEO/geo_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3322,270,"GMB","Gambia","ppp_2013","GIS/Population/Global_2000_2020/2013/GMB/gmb_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3323,275,"PSE","Palestina","ppp_2013","GIS/Population/Global_2000_2020/2013/PSE/pse_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3324,276,"DEU","Germany","ppp_2013","GIS/Population/Global_2000_2020/2013/DEU/deu_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3325,288,"GHA","Ghana","ppp_2013","GIS/Population/Global_2000_2020/2013/GHA/gha_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3326,292,"GIB","Gibraltar","ppp_2013","GIS/Population/Global_2000_2020/2013/GIB/gib_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3327,296,"KIR","Kiribati","ppp_2013","GIS/Population/Global_2000_2020/2013/KIR/kir_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3328,300,"GRC","Greece","ppp_2013","GIS/Population/Global_2000_2020/2013/GRC/grc_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3329,308,"GRD","Grenada","ppp_2013","GIS/Population/Global_2000_2020/2013/GRD/grd_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3330,312,"GLP","Guadeloupe","ppp_2013","GIS/Population/Global_2000_2020/2013/GLP/glp_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3331,316,"GUM","Guam","ppp_2013","GIS/Population/Global_2000_2020/2013/GUM/gum_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3332,320,"GTM","Guatemala","ppp_2013","GIS/Population/Global_2000_2020/2013/GTM/gtm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3333,324,"GIN","Guinea","ppp_2013","GIS/Population/Global_2000_2020/2013/GIN/gin_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3334,328,"GUY","Guyana","ppp_2013","GIS/Population/Global_2000_2020/2013/GUY/guy_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3335,332,"HTI","Haiti","ppp_2013","GIS/Population/Global_2000_2020/2013/HTI/hti_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3336,334,"HMD","Heard Island and McDonald Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/HMD/hmd_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3337,336,"VAT","Vatican City","ppp_2013","GIS/Population/Global_2000_2020/2013/VAT/vat_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3338,340,"HND","Honduras","ppp_2013","GIS/Population/Global_2000_2020/2013/HND/hnd_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3339,344,"HKG","Hong Kong","ppp_2013","GIS/Population/Global_2000_2020/2013/HKG/hkg_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3340,348,"HUN","Hungary","ppp_2013","GIS/Population/Global_2000_2020/2013/HUN/hun_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3341,352,"ISL","Iceland","ppp_2013","GIS/Population/Global_2000_2020/2013/ISL/isl_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3342,356,"IND","India","ppp_2013","GIS/Population/Global_2000_2020/2013/IND/ind_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3343,364,"IRN","Iran","ppp_2013","GIS/Population/Global_2000_2020/2013/IRN/irn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3344,368,"IRQ","Iraq","ppp_2013","GIS/Population/Global_2000_2020/2013/IRQ/irq_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3345,372,"IRL","Ireland","ppp_2013","GIS/Population/Global_2000_2020/2013/IRL/irl_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3346,376,"ISR","Israel","ppp_2013","GIS/Population/Global_2000_2020/2013/ISR/isr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3347,380,"ITA","Italy","ppp_2013","GIS/Population/Global_2000_2020/2013/ITA/ita_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3348,384,"CIV","CIte dIvoire","ppp_2013","GIS/Population/Global_2000_2020/2013/CIV/civ_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3349,388,"JAM","Jamaica","ppp_2013","GIS/Population/Global_2000_2020/2013/JAM/jam_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3350,392,"JPN","Japan","ppp_2013","GIS/Population/Global_2000_2020/2013/JPN/jpn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3351,398,"KAZ","Kazakhstan","ppp_2013","GIS/Population/Global_2000_2020/2013/KAZ/kaz_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3352,400,"JOR","Jordan","ppp_2013","GIS/Population/Global_2000_2020/2013/JOR/jor_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3353,404,"KEN","Kenya","ppp_2013","GIS/Population/Global_2000_2020/2013/KEN/ken_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3354,408,"PRK","North Korea","ppp_2013","GIS/Population/Global_2000_2020/2013/PRK/prk_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3355,410,"KOR","South Korea","ppp_2013","GIS/Population/Global_2000_2020/2013/KOR/kor_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3356,414,"KWT","Kuwait","ppp_2013","GIS/Population/Global_2000_2020/2013/KWT/kwt_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3357,417,"KGZ","Kyrgyzstan","ppp_2013","GIS/Population/Global_2000_2020/2013/KGZ/kgz_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3358,418,"LAO","Laos","ppp_2013","GIS/Population/Global_2000_2020/2013/LAO/lao_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3359,422,"LBN","Lebanon","ppp_2013","GIS/Population/Global_2000_2020/2013/LBN/lbn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3360,426,"LSO","Lesotho","ppp_2013","GIS/Population/Global_2000_2020/2013/LSO/lso_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3361,428,"LVA","Latvia","ppp_2013","GIS/Population/Global_2000_2020/2013/LVA/lva_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3362,430,"LBR","Liberia","ppp_2013","GIS/Population/Global_2000_2020/2013/LBR/lbr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3363,434,"LBY","Libya","ppp_2013","GIS/Population/Global_2000_2020/2013/LBY/lby_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3364,438,"LIE","Liechtenstein","ppp_2013","GIS/Population/Global_2000_2020/2013/LIE/lie_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3365,440,"LTU","Lithuania","ppp_2013","GIS/Population/Global_2000_2020/2013/LTU/ltu_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3366,442,"LUX","Luxembourg","ppp_2013","GIS/Population/Global_2000_2020/2013/LUX/lux_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3367,446,"MAC","Macao","ppp_2013","GIS/Population/Global_2000_2020/2013/MAC/mac_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3368,450,"MDG","Madagascar","ppp_2013","GIS/Population/Global_2000_2020/2013/MDG/mdg_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3369,454,"MWI","Malawi","ppp_2013","GIS/Population/Global_2000_2020/2013/MWI/mwi_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3370,458,"MYS","Malaysia","ppp_2013","GIS/Population/Global_2000_2020/2013/MYS/mys_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3371,462,"MDV","Maldives","ppp_2013","GIS/Population/Global_2000_2020/2013/MDV/mdv_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3372,466,"MLI","Mali","ppp_2013","GIS/Population/Global_2000_2020/2013/MLI/mli_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3373,470,"MLT","Malta","ppp_2013","GIS/Population/Global_2000_2020/2013/MLT/mlt_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3374,474,"MTQ","Martinique","ppp_2013","GIS/Population/Global_2000_2020/2013/MTQ/mtq_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3375,478,"MRT","Mauritania","ppp_2013","GIS/Population/Global_2000_2020/2013/MRT/mrt_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3376,480,"MUS","Mauritius","ppp_2013","GIS/Population/Global_2000_2020/2013/MUS/mus_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3377,484,"MEX","Mexico","ppp_2013","GIS/Population/Global_2000_2020/2013/MEX/mex_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3378,492,"MCO","Monaco","ppp_2013","GIS/Population/Global_2000_2020/2013/MCO/mco_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3379,496,"MNG","Mongolia","ppp_2013","GIS/Population/Global_2000_2020/2013/MNG/mng_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3380,498,"MDA","Moldova","ppp_2013","GIS/Population/Global_2000_2020/2013/MDA/mda_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3381,499,"MNE","Montenegro","ppp_2013","GIS/Population/Global_2000_2020/2013/MNE/mne_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3382,500,"MSR","Montserrat","ppp_2013","GIS/Population/Global_2000_2020/2013/MSR/msr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3383,504,"MAR","Morocco","ppp_2013","GIS/Population/Global_2000_2020/2013/MAR/mar_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3384,508,"MOZ","Mozambique","ppp_2013","GIS/Population/Global_2000_2020/2013/MOZ/moz_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3385,512,"OMN","Oman","ppp_2013","GIS/Population/Global_2000_2020/2013/OMN/omn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3386,516,"NAM","Namibia","ppp_2013","GIS/Population/Global_2000_2020/2013/NAM/nam_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3387,520,"NRU","Nauru","ppp_2013","GIS/Population/Global_2000_2020/2013/NRU/nru_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3388,524,"NPL","Nepal","ppp_2013","GIS/Population/Global_2000_2020/2013/NPL/npl_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3389,528,"NLD","Netherlands","ppp_2013","GIS/Population/Global_2000_2020/2013/NLD/nld_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3390,531,"CUW","Curacao","ppp_2013","GIS/Population/Global_2000_2020/2013/CUW/cuw_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3391,533,"ABW","Aruba","ppp_2013","GIS/Population/Global_2000_2020/2013/ABW/abw_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3392,534,"SXM","Sint Maarten (Dutch part)","ppp_2013","GIS/Population/Global_2000_2020/2013/SXM/sxm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3393,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2013","GIS/Population/Global_2000_2020/2013/BES/bes_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3394,540,"NCL","New Caledonia","ppp_2013","GIS/Population/Global_2000_2020/2013/NCL/ncl_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3395,548,"VUT","Vanuatu","ppp_2013","GIS/Population/Global_2000_2020/2013/VUT/vut_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3396,554,"NZL","New Zealand","ppp_2013","GIS/Population/Global_2000_2020/2013/NZL/nzl_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3397,558,"NIC","Nicaragua","ppp_2013","GIS/Population/Global_2000_2020/2013/NIC/nic_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3398,562,"NER","Niger","ppp_2013","GIS/Population/Global_2000_2020/2013/NER/ner_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3399,566,"NGA","Nigeria","ppp_2013","GIS/Population/Global_2000_2020/2013/NGA/nga_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3400,570,"NIU","Niue","ppp_2013","GIS/Population/Global_2000_2020/2013/NIU/niu_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3401,574,"NFK","Norfolk Island","ppp_2013","GIS/Population/Global_2000_2020/2013/NFK/nfk_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3402,578,"NOR","Norway","ppp_2013","GIS/Population/Global_2000_2020/2013/NOR/nor_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3403,580,"MNP","Northern Mariana Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/MNP/mnp_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3404,581,"UMI","United States Minor Outlying Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/UMI/umi_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3405,583,"FSM","Micronesia","ppp_2013","GIS/Population/Global_2000_2020/2013/FSM/fsm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3406,584,"MHL","Marshall Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/MHL/mhl_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3407,585,"PLW","Palau","ppp_2013","GIS/Population/Global_2000_2020/2013/PLW/plw_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3408,586,"PAK","Pakistan","ppp_2013","GIS/Population/Global_2000_2020/2013/PAK/pak_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3409,591,"PAN","Panama","ppp_2013","GIS/Population/Global_2000_2020/2013/PAN/pan_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3410,598,"PNG","Papua New Guinea","ppp_2013","GIS/Population/Global_2000_2020/2013/PNG/png_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3411,600,"PRY","Paraguay","ppp_2013","GIS/Population/Global_2000_2020/2013/PRY/pry_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3412,604,"PER","Peru","ppp_2013","GIS/Population/Global_2000_2020/2013/PER/per_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3413,608,"PHL","Philippines","ppp_2013","GIS/Population/Global_2000_2020/2013/PHL/phl_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3414,612,"PCN","Pitcairn Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/PCN/pcn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3415,616,"POL","Poland","ppp_2013","GIS/Population/Global_2000_2020/2013/POL/pol_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3416,620,"PRT","Portugal","ppp_2013","GIS/Population/Global_2000_2020/2013/PRT/prt_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3417,624,"GNB","Guinea-Bissau","ppp_2013","GIS/Population/Global_2000_2020/2013/GNB/gnb_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3418,626,"TLS","East Timor","ppp_2013","GIS/Population/Global_2000_2020/2013/TLS/tls_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3419,630,"PRI","Puerto Rico","ppp_2013","GIS/Population/Global_2000_2020/2013/PRI/pri_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3420,634,"QAT","Qatar","ppp_2013","GIS/Population/Global_2000_2020/2013/QAT/qat_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3421,638,"REU","Reunion","ppp_2013","GIS/Population/Global_2000_2020/2013/REU/reu_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3422,642,"ROU","Romania","ppp_2013","GIS/Population/Global_2000_2020/2013/ROU/rou_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3423,646,"RWA","Rwanda","ppp_2013","GIS/Population/Global_2000_2020/2013/RWA/rwa_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3424,652,"BLM","Saint Barthelemy","ppp_2013","GIS/Population/Global_2000_2020/2013/BLM/blm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3425,654,"SHN","Saint Helena","ppp_2013","GIS/Population/Global_2000_2020/2013/SHN/shn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3426,659,"KNA","Saint Kitts and Nevis","ppp_2013","GIS/Population/Global_2000_2020/2013/KNA/kna_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3427,660,"AIA","Anguilla","ppp_2013","GIS/Population/Global_2000_2020/2013/AIA/aia_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3428,662,"LCA","Saint Lucia","ppp_2013","GIS/Population/Global_2000_2020/2013/LCA/lca_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3429,663,"MAF","Saint Martin (French part)","ppp_2013","GIS/Population/Global_2000_2020/2013/MAF/maf_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3430,666,"SPM","Saint Pierre and Miquelon","ppp_2013","GIS/Population/Global_2000_2020/2013/SPM/spm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3431,670,"VCT","Saint Vincent and the Grenadines","ppp_2013","GIS/Population/Global_2000_2020/2013/VCT/vct_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3432,674,"SMR","San Marino","ppp_2013","GIS/Population/Global_2000_2020/2013/SMR/smr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3433,678,"STP","Sao Tome and Principe","ppp_2013","GIS/Population/Global_2000_2020/2013/STP/stp_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3434,682,"SAU","Saudi Arabia","ppp_2013","GIS/Population/Global_2000_2020/2013/SAU/sau_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3435,686,"SEN","Senegal","ppp_2013","GIS/Population/Global_2000_2020/2013/SEN/sen_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3436,688,"SRB","Serbia","ppp_2013","GIS/Population/Global_2000_2020/2013/SRB/srb_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3437,690,"SYC","Seychelles","ppp_2013","GIS/Population/Global_2000_2020/2013/SYC/syc_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3438,694,"SLE","Sierra Leone","ppp_2013","GIS/Population/Global_2000_2020/2013/SLE/sle_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3439,702,"SGP","Singapore","ppp_2013","GIS/Population/Global_2000_2020/2013/SGP/sgp_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3440,703,"SVK","Slovakia","ppp_2013","GIS/Population/Global_2000_2020/2013/SVK/svk_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3441,704,"VNM","Vietnam","ppp_2013","GIS/Population/Global_2000_2020/2013/VNM/vnm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3442,705,"SVN","Slovenia","ppp_2013","GIS/Population/Global_2000_2020/2013/SVN/svn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3443,706,"SOM","Somalia","ppp_2013","GIS/Population/Global_2000_2020/2013/SOM/som_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3444,710,"ZAF","South Africa","ppp_2013","GIS/Population/Global_2000_2020/2013/ZAF/zaf_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3445,716,"ZWE","Zimbabwe","ppp_2013","GIS/Population/Global_2000_2020/2013/ZWE/zwe_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3446,724,"ESP","Spain","ppp_2013","GIS/Population/Global_2000_2020/2013/ESP/esp_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3447,728,"SSD","South Sudan","ppp_2013","GIS/Population/Global_2000_2020/2013/SSD/ssd_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3448,729,"SDN","Sudan","ppp_2013","GIS/Population/Global_2000_2020/2013/SDN/sdn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3449,732,"ESH","Western Sahara","ppp_2013","GIS/Population/Global_2000_2020/2013/ESH/esh_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3450,740,"SUR","Suriname","ppp_2013","GIS/Population/Global_2000_2020/2013/SUR/sur_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3451,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/SJM/sjm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3452,748,"SWZ","Swaziland","ppp_2013","GIS/Population/Global_2000_2020/2013/SWZ/swz_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3453,752,"SWE","Sweden","ppp_2013","GIS/Population/Global_2000_2020/2013/SWE/swe_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3454,756,"CHE","Switzerland","ppp_2013","GIS/Population/Global_2000_2020/2013/CHE/che_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3455,760,"SYR","Syria","ppp_2013","GIS/Population/Global_2000_2020/2013/SYR/syr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3456,762,"TJK","Tajikistan","ppp_2013","GIS/Population/Global_2000_2020/2013/TJK/tjk_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3457,764,"THA","Thailand","ppp_2013","GIS/Population/Global_2000_2020/2013/THA/tha_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3458,768,"TGO","Togo","ppp_2013","GIS/Population/Global_2000_2020/2013/TGO/tgo_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3459,772,"TKL","Tokelau","ppp_2013","GIS/Population/Global_2000_2020/2013/TKL/tkl_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3460,776,"TON","Tonga","ppp_2013","GIS/Population/Global_2000_2020/2013/TON/ton_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3461,780,"TTO","Trinidad and Tobago","ppp_2013","GIS/Population/Global_2000_2020/2013/TTO/tto_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3462,784,"ARE","United Arab Emirates","ppp_2013","GIS/Population/Global_2000_2020/2013/ARE/are_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3463,788,"TUN","Tunisia","ppp_2013","GIS/Population/Global_2000_2020/2013/TUN/tun_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3464,792,"TUR","Turkey","ppp_2013","GIS/Population/Global_2000_2020/2013/TUR/tur_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3465,795,"TKM","Turkmenistan","ppp_2013","GIS/Population/Global_2000_2020/2013/TKM/tkm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3466,796,"TCA","Turks and Caicos Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/TCA/tca_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3467,798,"TUV","Tuvalu","ppp_2013","GIS/Population/Global_2000_2020/2013/TUV/tuv_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3468,800,"UGA","Uganda","ppp_2013","GIS/Population/Global_2000_2020/2013/UGA/uga_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3469,804,"UKR","Ukraine","ppp_2013","GIS/Population/Global_2000_2020/2013/UKR/ukr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3470,807,"MKD","Macedonia","ppp_2013","GIS/Population/Global_2000_2020/2013/MKD/mkd_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3471,818,"EGY","Egypt","ppp_2013","GIS/Population/Global_2000_2020/2013/EGY/egy_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3472,826,"GBR","United Kingdom","ppp_2013","GIS/Population/Global_2000_2020/2013/GBR/gbr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3473,831,"GGY","Guernsey","ppp_2013","GIS/Population/Global_2000_2020/2013/GGY/ggy_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3474,832,"JEY","Jersey","ppp_2013","GIS/Population/Global_2000_2020/2013/JEY/jey_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3475,833,"IMN","Isle of Man","ppp_2013","GIS/Population/Global_2000_2020/2013/IMN/imn_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3476,834,"TZA","Tanzania","ppp_2013","GIS/Population/Global_2000_2020/2013/TZA/tza_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3477,854,"BFA","Burkina Faso","ppp_2013","GIS/Population/Global_2000_2020/2013/BFA/bfa_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3478,858,"URY","Uruguay","ppp_2013","GIS/Population/Global_2000_2020/2013/URY/ury_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3479,860,"UZB","Uzbekistan","ppp_2013","GIS/Population/Global_2000_2020/2013/UZB/uzb_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3480,862,"VEN","Venezuela","ppp_2013","GIS/Population/Global_2000_2020/2013/VEN/ven_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3481,876,"WLF","Wallis and Futuna","ppp_2013","GIS/Population/Global_2000_2020/2013/WLF/wlf_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3482,882,"WSM","Samoa","ppp_2013","GIS/Population/Global_2000_2020/2013/WSM/wsm_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3483,887,"YEM","Yemen","ppp_2013","GIS/Population/Global_2000_2020/2013/YEM/yem_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3484,894,"ZMB","Zambia","ppp_2013","GIS/Population/Global_2000_2020/2013/ZMB/zmb_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3485,900,"KOS","Kosovo","ppp_2013","GIS/Population/Global_2000_2020/2013/KOS/kos_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3486,901,"SPR","Spratly Islands","ppp_2013","GIS/Population/Global_2000_2020/2013/SPR/spr_ppp_2013.tif","Estimated total number of people per grid-cell 2013 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3487,643,"RUS","Russia","ppp_2014","GIS/Population/Global_2000_2020/2014/RUS/rus_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3488,360,"IDN","Indonesia","ppp_2014","GIS/Population/Global_2000_2020/2014/IDN/idn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3489,840,"USA","United States","ppp_2014","GIS/Population/Global_2000_2020/2014/USA/usa_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3490,850,"VIR","Virgin_Islands_U_S","ppp_2014","GIS/Population/Global_2000_2020/2014/VIR/vir_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3491,304,"GRL","Greenland","ppp_2014","GIS/Population/Global_2000_2020/2014/GRL/grl_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3492,156,"CHN","China","ppp_2014","GIS/Population/Global_2000_2020/2014/CHN/chn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3493,36,"AUS","Australia","ppp_2014","GIS/Population/Global_2000_2020/2014/AUS/aus_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3494,76,"BRA","Brazil","ppp_2014","GIS/Population/Global_2000_2020/2014/BRA/bra_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3495,124,"CAN","Canada","ppp_2014","GIS/Population/Global_2000_2020/2014/CAN/can_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3496,152,"CHL","Chile","ppp_2014","GIS/Population/Global_2000_2020/2014/CHL/chl_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3497,4,"AFG","Afghanistan","ppp_2014","GIS/Population/Global_2000_2020/2014/AFG/afg_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3498,8,"ALB","Albania","ppp_2014","GIS/Population/Global_2000_2020/2014/ALB/alb_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3499,10,"ATA","Antarctica","ppp_2014","GIS/Population/Global_2000_2020/2014/ATA/ata_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3500,12,"DZA","Algeria","ppp_2014","GIS/Population/Global_2000_2020/2014/DZA/dza_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3501,16,"ASM","American Samoa","ppp_2014","GIS/Population/Global_2000_2020/2014/ASM/asm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3502,20,"AND","Andorra","ppp_2014","GIS/Population/Global_2000_2020/2014/AND/and_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3503,24,"AGO","Angola","ppp_2014","GIS/Population/Global_2000_2020/2014/AGO/ago_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3504,28,"ATG","Antigua and Barbuda","ppp_2014","GIS/Population/Global_2000_2020/2014/ATG/atg_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3505,31,"AZE","Azerbaijan","ppp_2014","GIS/Population/Global_2000_2020/2014/AZE/aze_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3506,32,"ARG","Argentina","ppp_2014","GIS/Population/Global_2000_2020/2014/ARG/arg_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3507,40,"AUT","Austria","ppp_2014","GIS/Population/Global_2000_2020/2014/AUT/aut_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3508,44,"BHS","Bahamas","ppp_2014","GIS/Population/Global_2000_2020/2014/BHS/bhs_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3509,48,"BHR","Bahrain","ppp_2014","GIS/Population/Global_2000_2020/2014/BHR/bhr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3510,50,"BGD","Bangladesh","ppp_2014","GIS/Population/Global_2000_2020/2014/BGD/bgd_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3511,51,"ARM","Armenia","ppp_2014","GIS/Population/Global_2000_2020/2014/ARM/arm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3512,52,"BRB","Barbados","ppp_2014","GIS/Population/Global_2000_2020/2014/BRB/brb_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3513,56,"BEL","Belgium","ppp_2014","GIS/Population/Global_2000_2020/2014/BEL/bel_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3514,60,"BMU","Bermuda","ppp_2014","GIS/Population/Global_2000_2020/2014/BMU/bmu_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3515,64,"BTN","Bhutan","ppp_2014","GIS/Population/Global_2000_2020/2014/BTN/btn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3516,68,"BOL","Bolivia","ppp_2014","GIS/Population/Global_2000_2020/2014/BOL/bol_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3517,70,"BIH","Bosnia and Herzegovina","ppp_2014","GIS/Population/Global_2000_2020/2014/BIH/bih_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3518,72,"BWA","Botswana","ppp_2014","GIS/Population/Global_2000_2020/2014/BWA/bwa_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3519,74,"BVT","Bouvet Island","ppp_2014","GIS/Population/Global_2000_2020/2014/BVT/bvt_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3520,84,"BLZ","Belize","ppp_2014","GIS/Population/Global_2000_2020/2014/BLZ/blz_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3521,86,"IOT","British Indian Ocean Territory","ppp_2014","GIS/Population/Global_2000_2020/2014/IOT/iot_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3522,90,"SLB","Solomon Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/SLB/slb_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3523,92,"VGB","British Virgin Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/VGB/vgb_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3524,96,"BRN","Brunei","ppp_2014","GIS/Population/Global_2000_2020/2014/BRN/brn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3525,100,"BGR","Bulgaria","ppp_2014","GIS/Population/Global_2000_2020/2014/BGR/bgr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3526,104,"MMR","Myanmar","ppp_2014","GIS/Population/Global_2000_2020/2014/MMR/mmr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3527,108,"BDI","Burundi","ppp_2014","GIS/Population/Global_2000_2020/2014/BDI/bdi_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3528,112,"BLR","Belarus","ppp_2014","GIS/Population/Global_2000_2020/2014/BLR/blr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3529,116,"KHM","Cambodia","ppp_2014","GIS/Population/Global_2000_2020/2014/KHM/khm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3530,120,"CMR","Cameroon","ppp_2014","GIS/Population/Global_2000_2020/2014/CMR/cmr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3531,132,"CPV","Cape Verde","ppp_2014","GIS/Population/Global_2000_2020/2014/CPV/cpv_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3532,136,"CYM","Cayman Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/CYM/cym_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3533,140,"CAF","Central African Republic","ppp_2014","GIS/Population/Global_2000_2020/2014/CAF/caf_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3534,144,"LKA","Sri Lanka","ppp_2014","GIS/Population/Global_2000_2020/2014/LKA/lka_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3535,148,"TCD","Chad","ppp_2014","GIS/Population/Global_2000_2020/2014/TCD/tcd_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3536,158,"TWN","Taiwan","ppp_2014","GIS/Population/Global_2000_2020/2014/TWN/twn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3537,170,"COL","Colombia","ppp_2014","GIS/Population/Global_2000_2020/2014/COL/col_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3538,174,"COM","Comoros","ppp_2014","GIS/Population/Global_2000_2020/2014/COM/com_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3539,175,"MYT","Mayotte","ppp_2014","GIS/Population/Global_2000_2020/2014/MYT/myt_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3540,178,"COG","Republic of Congo","ppp_2014","GIS/Population/Global_2000_2020/2014/COG/cog_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3541,180,"COD","Democratic Republic of the Congo","ppp_2014","GIS/Population/Global_2000_2020/2014/COD/cod_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3542,184,"COK","Cook Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/COK/cok_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3543,188,"CRI","Costa Rica","ppp_2014","GIS/Population/Global_2000_2020/2014/CRI/cri_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3544,191,"HRV","Croatia","ppp_2014","GIS/Population/Global_2000_2020/2014/HRV/hrv_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3545,192,"CUB","Cuba","ppp_2014","GIS/Population/Global_2000_2020/2014/CUB/cub_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3546,196,"CYP","Cyprus","ppp_2014","GIS/Population/Global_2000_2020/2014/CYP/cyp_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3547,203,"CZE","Czech Republic","ppp_2014","GIS/Population/Global_2000_2020/2014/CZE/cze_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3548,204,"BEN","Benin","ppp_2014","GIS/Population/Global_2000_2020/2014/BEN/ben_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3549,208,"DNK","Denmark","ppp_2014","GIS/Population/Global_2000_2020/2014/DNK/dnk_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3550,212,"DMA","Dominica","ppp_2014","GIS/Population/Global_2000_2020/2014/DMA/dma_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3551,214,"DOM","Dominican Republic","ppp_2014","GIS/Population/Global_2000_2020/2014/DOM/dom_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3552,218,"ECU","Ecuador","ppp_2014","GIS/Population/Global_2000_2020/2014/ECU/ecu_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3553,222,"SLV","El Salvador","ppp_2014","GIS/Population/Global_2000_2020/2014/SLV/slv_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3554,226,"GNQ","Equatorial Guinea","ppp_2014","GIS/Population/Global_2000_2020/2014/GNQ/gnq_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3555,231,"ETH","Ethiopia","ppp_2014","GIS/Population/Global_2000_2020/2014/ETH/eth_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3556,232,"ERI","Eritrea","ppp_2014","GIS/Population/Global_2000_2020/2014/ERI/eri_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3557,233,"EST","Estonia","ppp_2014","GIS/Population/Global_2000_2020/2014/EST/est_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3558,234,"FRO","Faroe Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/FRO/fro_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3559,238,"FLK","Falkland Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/FLK/flk_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3560,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/SGS/sgs_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3561,242,"FJI","Fiji","ppp_2014","GIS/Population/Global_2000_2020/2014/FJI/fji_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3562,246,"FIN","Finland","ppp_2014","GIS/Population/Global_2000_2020/2014/FIN/fin_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3563,248,"ALA","Aland Islands ","ppp_2014","GIS/Population/Global_2000_2020/2014/ALA/ala_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3564,250,"FRA","France","ppp_2014","GIS/Population/Global_2000_2020/2014/FRA/fra_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3565,254,"GUF","French Guiana","ppp_2014","GIS/Population/Global_2000_2020/2014/GUF/guf_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3566,258,"PYF","French Polynesia","ppp_2014","GIS/Population/Global_2000_2020/2014/PYF/pyf_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3567,260,"ATF","French Southern Territories","ppp_2014","GIS/Population/Global_2000_2020/2014/ATF/atf_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3568,262,"DJI","Djibouti","ppp_2014","GIS/Population/Global_2000_2020/2014/DJI/dji_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3569,266,"GAB","Gabon","ppp_2014","GIS/Population/Global_2000_2020/2014/GAB/gab_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3570,268,"GEO","Georgia","ppp_2014","GIS/Population/Global_2000_2020/2014/GEO/geo_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3571,270,"GMB","Gambia","ppp_2014","GIS/Population/Global_2000_2020/2014/GMB/gmb_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3572,275,"PSE","Palestina","ppp_2014","GIS/Population/Global_2000_2020/2014/PSE/pse_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3573,276,"DEU","Germany","ppp_2014","GIS/Population/Global_2000_2020/2014/DEU/deu_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3574,288,"GHA","Ghana","ppp_2014","GIS/Population/Global_2000_2020/2014/GHA/gha_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3575,292,"GIB","Gibraltar","ppp_2014","GIS/Population/Global_2000_2020/2014/GIB/gib_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3576,296,"KIR","Kiribati","ppp_2014","GIS/Population/Global_2000_2020/2014/KIR/kir_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3577,300,"GRC","Greece","ppp_2014","GIS/Population/Global_2000_2020/2014/GRC/grc_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3578,308,"GRD","Grenada","ppp_2014","GIS/Population/Global_2000_2020/2014/GRD/grd_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3579,312,"GLP","Guadeloupe","ppp_2014","GIS/Population/Global_2000_2020/2014/GLP/glp_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3580,316,"GUM","Guam","ppp_2014","GIS/Population/Global_2000_2020/2014/GUM/gum_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3581,320,"GTM","Guatemala","ppp_2014","GIS/Population/Global_2000_2020/2014/GTM/gtm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3582,324,"GIN","Guinea","ppp_2014","GIS/Population/Global_2000_2020/2014/GIN/gin_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3583,328,"GUY","Guyana","ppp_2014","GIS/Population/Global_2000_2020/2014/GUY/guy_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3584,332,"HTI","Haiti","ppp_2014","GIS/Population/Global_2000_2020/2014/HTI/hti_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3585,334,"HMD","Heard Island and McDonald Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/HMD/hmd_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3586,336,"VAT","Vatican City","ppp_2014","GIS/Population/Global_2000_2020/2014/VAT/vat_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3587,340,"HND","Honduras","ppp_2014","GIS/Population/Global_2000_2020/2014/HND/hnd_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3588,344,"HKG","Hong Kong","ppp_2014","GIS/Population/Global_2000_2020/2014/HKG/hkg_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3589,348,"HUN","Hungary","ppp_2014","GIS/Population/Global_2000_2020/2014/HUN/hun_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3590,352,"ISL","Iceland","ppp_2014","GIS/Population/Global_2000_2020/2014/ISL/isl_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3591,356,"IND","India","ppp_2014","GIS/Population/Global_2000_2020/2014/IND/ind_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3592,364,"IRN","Iran","ppp_2014","GIS/Population/Global_2000_2020/2014/IRN/irn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3593,368,"IRQ","Iraq","ppp_2014","GIS/Population/Global_2000_2020/2014/IRQ/irq_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3594,372,"IRL","Ireland","ppp_2014","GIS/Population/Global_2000_2020/2014/IRL/irl_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3595,376,"ISR","Israel","ppp_2014","GIS/Population/Global_2000_2020/2014/ISR/isr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3596,380,"ITA","Italy","ppp_2014","GIS/Population/Global_2000_2020/2014/ITA/ita_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3597,384,"CIV","CIte dIvoire","ppp_2014","GIS/Population/Global_2000_2020/2014/CIV/civ_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3598,388,"JAM","Jamaica","ppp_2014","GIS/Population/Global_2000_2020/2014/JAM/jam_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3599,392,"JPN","Japan","ppp_2014","GIS/Population/Global_2000_2020/2014/JPN/jpn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3600,398,"KAZ","Kazakhstan","ppp_2014","GIS/Population/Global_2000_2020/2014/KAZ/kaz_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3601,400,"JOR","Jordan","ppp_2014","GIS/Population/Global_2000_2020/2014/JOR/jor_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3602,404,"KEN","Kenya","ppp_2014","GIS/Population/Global_2000_2020/2014/KEN/ken_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3603,408,"PRK","North Korea","ppp_2014","GIS/Population/Global_2000_2020/2014/PRK/prk_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3604,410,"KOR","South Korea","ppp_2014","GIS/Population/Global_2000_2020/2014/KOR/kor_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3605,414,"KWT","Kuwait","ppp_2014","GIS/Population/Global_2000_2020/2014/KWT/kwt_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3606,417,"KGZ","Kyrgyzstan","ppp_2014","GIS/Population/Global_2000_2020/2014/KGZ/kgz_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3607,418,"LAO","Laos","ppp_2014","GIS/Population/Global_2000_2020/2014/LAO/lao_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3608,422,"LBN","Lebanon","ppp_2014","GIS/Population/Global_2000_2020/2014/LBN/lbn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3609,426,"LSO","Lesotho","ppp_2014","GIS/Population/Global_2000_2020/2014/LSO/lso_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3610,428,"LVA","Latvia","ppp_2014","GIS/Population/Global_2000_2020/2014/LVA/lva_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3611,430,"LBR","Liberia","ppp_2014","GIS/Population/Global_2000_2020/2014/LBR/lbr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3612,434,"LBY","Libya","ppp_2014","GIS/Population/Global_2000_2020/2014/LBY/lby_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3613,438,"LIE","Liechtenstein","ppp_2014","GIS/Population/Global_2000_2020/2014/LIE/lie_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3614,440,"LTU","Lithuania","ppp_2014","GIS/Population/Global_2000_2020/2014/LTU/ltu_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3615,442,"LUX","Luxembourg","ppp_2014","GIS/Population/Global_2000_2020/2014/LUX/lux_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3616,446,"MAC","Macao","ppp_2014","GIS/Population/Global_2000_2020/2014/MAC/mac_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3617,450,"MDG","Madagascar","ppp_2014","GIS/Population/Global_2000_2020/2014/MDG/mdg_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3618,454,"MWI","Malawi","ppp_2014","GIS/Population/Global_2000_2020/2014/MWI/mwi_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3619,458,"MYS","Malaysia","ppp_2014","GIS/Population/Global_2000_2020/2014/MYS/mys_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3620,462,"MDV","Maldives","ppp_2014","GIS/Population/Global_2000_2020/2014/MDV/mdv_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3621,466,"MLI","Mali","ppp_2014","GIS/Population/Global_2000_2020/2014/MLI/mli_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3622,470,"MLT","Malta","ppp_2014","GIS/Population/Global_2000_2020/2014/MLT/mlt_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3623,474,"MTQ","Martinique","ppp_2014","GIS/Population/Global_2000_2020/2014/MTQ/mtq_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3624,478,"MRT","Mauritania","ppp_2014","GIS/Population/Global_2000_2020/2014/MRT/mrt_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3625,480,"MUS","Mauritius","ppp_2014","GIS/Population/Global_2000_2020/2014/MUS/mus_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3626,484,"MEX","Mexico","ppp_2014","GIS/Population/Global_2000_2020/2014/MEX/mex_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3627,492,"MCO","Monaco","ppp_2014","GIS/Population/Global_2000_2020/2014/MCO/mco_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3628,496,"MNG","Mongolia","ppp_2014","GIS/Population/Global_2000_2020/2014/MNG/mng_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3629,498,"MDA","Moldova","ppp_2014","GIS/Population/Global_2000_2020/2014/MDA/mda_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3630,499,"MNE","Montenegro","ppp_2014","GIS/Population/Global_2000_2020/2014/MNE/mne_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3631,500,"MSR","Montserrat","ppp_2014","GIS/Population/Global_2000_2020/2014/MSR/msr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3632,504,"MAR","Morocco","ppp_2014","GIS/Population/Global_2000_2020/2014/MAR/mar_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3633,508,"MOZ","Mozambique","ppp_2014","GIS/Population/Global_2000_2020/2014/MOZ/moz_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3634,512,"OMN","Oman","ppp_2014","GIS/Population/Global_2000_2020/2014/OMN/omn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3635,516,"NAM","Namibia","ppp_2014","GIS/Population/Global_2000_2020/2014/NAM/nam_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3636,520,"NRU","Nauru","ppp_2014","GIS/Population/Global_2000_2020/2014/NRU/nru_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3637,524,"NPL","Nepal","ppp_2014","GIS/Population/Global_2000_2020/2014/NPL/npl_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3638,528,"NLD","Netherlands","ppp_2014","GIS/Population/Global_2000_2020/2014/NLD/nld_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3639,531,"CUW","Curacao","ppp_2014","GIS/Population/Global_2000_2020/2014/CUW/cuw_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3640,533,"ABW","Aruba","ppp_2014","GIS/Population/Global_2000_2020/2014/ABW/abw_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3641,534,"SXM","Sint Maarten (Dutch part)","ppp_2014","GIS/Population/Global_2000_2020/2014/SXM/sxm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3642,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2014","GIS/Population/Global_2000_2020/2014/BES/bes_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3643,540,"NCL","New Caledonia","ppp_2014","GIS/Population/Global_2000_2020/2014/NCL/ncl_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3644,548,"VUT","Vanuatu","ppp_2014","GIS/Population/Global_2000_2020/2014/VUT/vut_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3645,554,"NZL","New Zealand","ppp_2014","GIS/Population/Global_2000_2020/2014/NZL/nzl_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3646,558,"NIC","Nicaragua","ppp_2014","GIS/Population/Global_2000_2020/2014/NIC/nic_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3647,562,"NER","Niger","ppp_2014","GIS/Population/Global_2000_2020/2014/NER/ner_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3648,566,"NGA","Nigeria","ppp_2014","GIS/Population/Global_2000_2020/2014/NGA/nga_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3649,570,"NIU","Niue","ppp_2014","GIS/Population/Global_2000_2020/2014/NIU/niu_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3650,574,"NFK","Norfolk Island","ppp_2014","GIS/Population/Global_2000_2020/2014/NFK/nfk_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3651,578,"NOR","Norway","ppp_2014","GIS/Population/Global_2000_2020/2014/NOR/nor_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3652,580,"MNP","Northern Mariana Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/MNP/mnp_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3653,581,"UMI","United States Minor Outlying Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/UMI/umi_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3654,583,"FSM","Micronesia","ppp_2014","GIS/Population/Global_2000_2020/2014/FSM/fsm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3655,584,"MHL","Marshall Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/MHL/mhl_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3656,585,"PLW","Palau","ppp_2014","GIS/Population/Global_2000_2020/2014/PLW/plw_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3657,586,"PAK","Pakistan","ppp_2014","GIS/Population/Global_2000_2020/2014/PAK/pak_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3658,591,"PAN","Panama","ppp_2014","GIS/Population/Global_2000_2020/2014/PAN/pan_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3659,598,"PNG","Papua New Guinea","ppp_2014","GIS/Population/Global_2000_2020/2014/PNG/png_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3660,600,"PRY","Paraguay","ppp_2014","GIS/Population/Global_2000_2020/2014/PRY/pry_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3661,604,"PER","Peru","ppp_2014","GIS/Population/Global_2000_2020/2014/PER/per_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3662,608,"PHL","Philippines","ppp_2014","GIS/Population/Global_2000_2020/2014/PHL/phl_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3663,612,"PCN","Pitcairn Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/PCN/pcn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3664,616,"POL","Poland","ppp_2014","GIS/Population/Global_2000_2020/2014/POL/pol_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3665,620,"PRT","Portugal","ppp_2014","GIS/Population/Global_2000_2020/2014/PRT/prt_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3666,624,"GNB","Guinea-Bissau","ppp_2014","GIS/Population/Global_2000_2020/2014/GNB/gnb_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3667,626,"TLS","East Timor","ppp_2014","GIS/Population/Global_2000_2020/2014/TLS/tls_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3668,630,"PRI","Puerto Rico","ppp_2014","GIS/Population/Global_2000_2020/2014/PRI/pri_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3669,634,"QAT","Qatar","ppp_2014","GIS/Population/Global_2000_2020/2014/QAT/qat_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3670,638,"REU","Reunion","ppp_2014","GIS/Population/Global_2000_2020/2014/REU/reu_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3671,642,"ROU","Romania","ppp_2014","GIS/Population/Global_2000_2020/2014/ROU/rou_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3672,646,"RWA","Rwanda","ppp_2014","GIS/Population/Global_2000_2020/2014/RWA/rwa_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3673,652,"BLM","Saint Barthelemy","ppp_2014","GIS/Population/Global_2000_2020/2014/BLM/blm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3674,654,"SHN","Saint Helena","ppp_2014","GIS/Population/Global_2000_2020/2014/SHN/shn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3675,659,"KNA","Saint Kitts and Nevis","ppp_2014","GIS/Population/Global_2000_2020/2014/KNA/kna_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3676,660,"AIA","Anguilla","ppp_2014","GIS/Population/Global_2000_2020/2014/AIA/aia_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3677,662,"LCA","Saint Lucia","ppp_2014","GIS/Population/Global_2000_2020/2014/LCA/lca_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3678,663,"MAF","Saint Martin (French part)","ppp_2014","GIS/Population/Global_2000_2020/2014/MAF/maf_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3679,666,"SPM","Saint Pierre and Miquelon","ppp_2014","GIS/Population/Global_2000_2020/2014/SPM/spm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3680,670,"VCT","Saint Vincent and the Grenadines","ppp_2014","GIS/Population/Global_2000_2020/2014/VCT/vct_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3681,674,"SMR","San Marino","ppp_2014","GIS/Population/Global_2000_2020/2014/SMR/smr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3682,678,"STP","Sao Tome and Principe","ppp_2014","GIS/Population/Global_2000_2020/2014/STP/stp_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3683,682,"SAU","Saudi Arabia","ppp_2014","GIS/Population/Global_2000_2020/2014/SAU/sau_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3684,686,"SEN","Senegal","ppp_2014","GIS/Population/Global_2000_2020/2014/SEN/sen_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3685,688,"SRB","Serbia","ppp_2014","GIS/Population/Global_2000_2020/2014/SRB/srb_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3686,690,"SYC","Seychelles","ppp_2014","GIS/Population/Global_2000_2020/2014/SYC/syc_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3687,694,"SLE","Sierra Leone","ppp_2014","GIS/Population/Global_2000_2020/2014/SLE/sle_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3688,702,"SGP","Singapore","ppp_2014","GIS/Population/Global_2000_2020/2014/SGP/sgp_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3689,703,"SVK","Slovakia","ppp_2014","GIS/Population/Global_2000_2020/2014/SVK/svk_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3690,704,"VNM","Vietnam","ppp_2014","GIS/Population/Global_2000_2020/2014/VNM/vnm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3691,705,"SVN","Slovenia","ppp_2014","GIS/Population/Global_2000_2020/2014/SVN/svn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3692,706,"SOM","Somalia","ppp_2014","GIS/Population/Global_2000_2020/2014/SOM/som_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3693,710,"ZAF","South Africa","ppp_2014","GIS/Population/Global_2000_2020/2014/ZAF/zaf_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3694,716,"ZWE","Zimbabwe","ppp_2014","GIS/Population/Global_2000_2020/2014/ZWE/zwe_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3695,724,"ESP","Spain","ppp_2014","GIS/Population/Global_2000_2020/2014/ESP/esp_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3696,728,"SSD","South Sudan","ppp_2014","GIS/Population/Global_2000_2020/2014/SSD/ssd_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3697,729,"SDN","Sudan","ppp_2014","GIS/Population/Global_2000_2020/2014/SDN/sdn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3698,732,"ESH","Western Sahara","ppp_2014","GIS/Population/Global_2000_2020/2014/ESH/esh_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3699,740,"SUR","Suriname","ppp_2014","GIS/Population/Global_2000_2020/2014/SUR/sur_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3700,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/SJM/sjm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3701,748,"SWZ","Swaziland","ppp_2014","GIS/Population/Global_2000_2020/2014/SWZ/swz_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3702,752,"SWE","Sweden","ppp_2014","GIS/Population/Global_2000_2020/2014/SWE/swe_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3703,756,"CHE","Switzerland","ppp_2014","GIS/Population/Global_2000_2020/2014/CHE/che_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3704,760,"SYR","Syria","ppp_2014","GIS/Population/Global_2000_2020/2014/SYR/syr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3705,762,"TJK","Tajikistan","ppp_2014","GIS/Population/Global_2000_2020/2014/TJK/tjk_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3706,764,"THA","Thailand","ppp_2014","GIS/Population/Global_2000_2020/2014/THA/tha_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3707,768,"TGO","Togo","ppp_2014","GIS/Population/Global_2000_2020/2014/TGO/tgo_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3708,772,"TKL","Tokelau","ppp_2014","GIS/Population/Global_2000_2020/2014/TKL/tkl_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3709,776,"TON","Tonga","ppp_2014","GIS/Population/Global_2000_2020/2014/TON/ton_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3710,780,"TTO","Trinidad and Tobago","ppp_2014","GIS/Population/Global_2000_2020/2014/TTO/tto_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3711,784,"ARE","United Arab Emirates","ppp_2014","GIS/Population/Global_2000_2020/2014/ARE/are_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3712,788,"TUN","Tunisia","ppp_2014","GIS/Population/Global_2000_2020/2014/TUN/tun_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3713,792,"TUR","Turkey","ppp_2014","GIS/Population/Global_2000_2020/2014/TUR/tur_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3714,795,"TKM","Turkmenistan","ppp_2014","GIS/Population/Global_2000_2020/2014/TKM/tkm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3715,796,"TCA","Turks and Caicos Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/TCA/tca_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3716,798,"TUV","Tuvalu","ppp_2014","GIS/Population/Global_2000_2020/2014/TUV/tuv_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3717,800,"UGA","Uganda","ppp_2014","GIS/Population/Global_2000_2020/2014/UGA/uga_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3718,804,"UKR","Ukraine","ppp_2014","GIS/Population/Global_2000_2020/2014/UKR/ukr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3719,807,"MKD","Macedonia","ppp_2014","GIS/Population/Global_2000_2020/2014/MKD/mkd_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3720,818,"EGY","Egypt","ppp_2014","GIS/Population/Global_2000_2020/2014/EGY/egy_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3721,826,"GBR","United Kingdom","ppp_2014","GIS/Population/Global_2000_2020/2014/GBR/gbr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3722,831,"GGY","Guernsey","ppp_2014","GIS/Population/Global_2000_2020/2014/GGY/ggy_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3723,832,"JEY","Jersey","ppp_2014","GIS/Population/Global_2000_2020/2014/JEY/jey_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3724,833,"IMN","Isle of Man","ppp_2014","GIS/Population/Global_2000_2020/2014/IMN/imn_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3725,834,"TZA","Tanzania","ppp_2014","GIS/Population/Global_2000_2020/2014/TZA/tza_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3726,854,"BFA","Burkina Faso","ppp_2014","GIS/Population/Global_2000_2020/2014/BFA/bfa_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3727,858,"URY","Uruguay","ppp_2014","GIS/Population/Global_2000_2020/2014/URY/ury_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3728,860,"UZB","Uzbekistan","ppp_2014","GIS/Population/Global_2000_2020/2014/UZB/uzb_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3729,862,"VEN","Venezuela","ppp_2014","GIS/Population/Global_2000_2020/2014/VEN/ven_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3730,876,"WLF","Wallis and Futuna","ppp_2014","GIS/Population/Global_2000_2020/2014/WLF/wlf_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3731,882,"WSM","Samoa","ppp_2014","GIS/Population/Global_2000_2020/2014/WSM/wsm_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3732,887,"YEM","Yemen","ppp_2014","GIS/Population/Global_2000_2020/2014/YEM/yem_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3733,894,"ZMB","Zambia","ppp_2014","GIS/Population/Global_2000_2020/2014/ZMB/zmb_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3734,900,"KOS","Kosovo","ppp_2014","GIS/Population/Global_2000_2020/2014/KOS/kos_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3735,901,"SPR","Spratly Islands","ppp_2014","GIS/Population/Global_2000_2020/2014/SPR/spr_ppp_2014.tif","Estimated total number of people per grid-cell 2014 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3736,643,"RUS","Russia","ppp_2015","GIS/Population/Global_2000_2020/2015/RUS/rus_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3737,360,"IDN","Indonesia","ppp_2015","GIS/Population/Global_2000_2020/2015/IDN/idn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3738,840,"USA","United States","ppp_2015","GIS/Population/Global_2000_2020/2015/USA/usa_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3739,850,"VIR","Virgin_Islands_U_S","ppp_2015","GIS/Population/Global_2000_2020/2015/VIR/vir_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3740,304,"GRL","Greenland","ppp_2015","GIS/Population/Global_2000_2020/2015/GRL/grl_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3741,156,"CHN","China","ppp_2015","GIS/Population/Global_2000_2020/2015/CHN/chn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3742,36,"AUS","Australia","ppp_2015","GIS/Population/Global_2000_2020/2015/AUS/aus_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3743,76,"BRA","Brazil","ppp_2015","GIS/Population/Global_2000_2020/2015/BRA/bra_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3744,124,"CAN","Canada","ppp_2015","GIS/Population/Global_2000_2020/2015/CAN/can_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3745,152,"CHL","Chile","ppp_2015","GIS/Population/Global_2000_2020/2015/CHL/chl_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3746,4,"AFG","Afghanistan","ppp_2015","GIS/Population/Global_2000_2020/2015/AFG/afg_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3747,8,"ALB","Albania","ppp_2015","GIS/Population/Global_2000_2020/2015/ALB/alb_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3748,10,"ATA","Antarctica","ppp_2015","GIS/Population/Global_2000_2020/2015/ATA/ata_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3749,12,"DZA","Algeria","ppp_2015","GIS/Population/Global_2000_2020/2015/DZA/dza_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3750,16,"ASM","American Samoa","ppp_2015","GIS/Population/Global_2000_2020/2015/ASM/asm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3751,20,"AND","Andorra","ppp_2015","GIS/Population/Global_2000_2020/2015/AND/and_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3752,24,"AGO","Angola","ppp_2015","GIS/Population/Global_2000_2020/2015/AGO/ago_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3753,28,"ATG","Antigua and Barbuda","ppp_2015","GIS/Population/Global_2000_2020/2015/ATG/atg_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3754,31,"AZE","Azerbaijan","ppp_2015","GIS/Population/Global_2000_2020/2015/AZE/aze_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3755,32,"ARG","Argentina","ppp_2015","GIS/Population/Global_2000_2020/2015/ARG/arg_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3756,40,"AUT","Austria","ppp_2015","GIS/Population/Global_2000_2020/2015/AUT/aut_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3757,44,"BHS","Bahamas","ppp_2015","GIS/Population/Global_2000_2020/2015/BHS/bhs_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3758,48,"BHR","Bahrain","ppp_2015","GIS/Population/Global_2000_2020/2015/BHR/bhr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3759,50,"BGD","Bangladesh","ppp_2015","GIS/Population/Global_2000_2020/2015/BGD/bgd_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3760,51,"ARM","Armenia","ppp_2015","GIS/Population/Global_2000_2020/2015/ARM/arm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3761,52,"BRB","Barbados","ppp_2015","GIS/Population/Global_2000_2020/2015/BRB/brb_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3762,56,"BEL","Belgium","ppp_2015","GIS/Population/Global_2000_2020/2015/BEL/bel_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3763,60,"BMU","Bermuda","ppp_2015","GIS/Population/Global_2000_2020/2015/BMU/bmu_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3764,64,"BTN","Bhutan","ppp_2015","GIS/Population/Global_2000_2020/2015/BTN/btn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3765,68,"BOL","Bolivia","ppp_2015","GIS/Population/Global_2000_2020/2015/BOL/bol_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3766,70,"BIH","Bosnia and Herzegovina","ppp_2015","GIS/Population/Global_2000_2020/2015/BIH/bih_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3767,72,"BWA","Botswana","ppp_2015","GIS/Population/Global_2000_2020/2015/BWA/bwa_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3768,74,"BVT","Bouvet Island","ppp_2015","GIS/Population/Global_2000_2020/2015/BVT/bvt_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3769,84,"BLZ","Belize","ppp_2015","GIS/Population/Global_2000_2020/2015/BLZ/blz_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3770,86,"IOT","British Indian Ocean Territory","ppp_2015","GIS/Population/Global_2000_2020/2015/IOT/iot_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3771,90,"SLB","Solomon Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/SLB/slb_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3772,92,"VGB","British Virgin Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/VGB/vgb_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3773,96,"BRN","Brunei","ppp_2015","GIS/Population/Global_2000_2020/2015/BRN/brn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3774,100,"BGR","Bulgaria","ppp_2015","GIS/Population/Global_2000_2020/2015/BGR/bgr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3775,104,"MMR","Myanmar","ppp_2015","GIS/Population/Global_2000_2020/2015/MMR/mmr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3776,108,"BDI","Burundi","ppp_2015","GIS/Population/Global_2000_2020/2015/BDI/bdi_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3777,112,"BLR","Belarus","ppp_2015","GIS/Population/Global_2000_2020/2015/BLR/blr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3778,116,"KHM","Cambodia","ppp_2015","GIS/Population/Global_2000_2020/2015/KHM/khm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3779,120,"CMR","Cameroon","ppp_2015","GIS/Population/Global_2000_2020/2015/CMR/cmr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3780,132,"CPV","Cape Verde","ppp_2015","GIS/Population/Global_2000_2020/2015/CPV/cpv_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3781,136,"CYM","Cayman Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/CYM/cym_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3782,140,"CAF","Central African Republic","ppp_2015","GIS/Population/Global_2000_2020/2015/CAF/caf_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3783,144,"LKA","Sri Lanka","ppp_2015","GIS/Population/Global_2000_2020/2015/LKA/lka_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3784,148,"TCD","Chad","ppp_2015","GIS/Population/Global_2000_2020/2015/TCD/tcd_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3785,158,"TWN","Taiwan","ppp_2015","GIS/Population/Global_2000_2020/2015/TWN/twn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3786,170,"COL","Colombia","ppp_2015","GIS/Population/Global_2000_2020/2015/COL/col_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3787,174,"COM","Comoros","ppp_2015","GIS/Population/Global_2000_2020/2015/COM/com_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3788,175,"MYT","Mayotte","ppp_2015","GIS/Population/Global_2000_2020/2015/MYT/myt_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3789,178,"COG","Republic of Congo","ppp_2015","GIS/Population/Global_2000_2020/2015/COG/cog_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3790,180,"COD","Democratic Republic of the Congo","ppp_2015","GIS/Population/Global_2000_2020/2015/COD/cod_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3791,184,"COK","Cook Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/COK/cok_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3792,188,"CRI","Costa Rica","ppp_2015","GIS/Population/Global_2000_2020/2015/CRI/cri_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3793,191,"HRV","Croatia","ppp_2015","GIS/Population/Global_2000_2020/2015/HRV/hrv_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3794,192,"CUB","Cuba","ppp_2015","GIS/Population/Global_2000_2020/2015/CUB/cub_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3795,196,"CYP","Cyprus","ppp_2015","GIS/Population/Global_2000_2020/2015/CYP/cyp_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3796,203,"CZE","Czech Republic","ppp_2015","GIS/Population/Global_2000_2020/2015/CZE/cze_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3797,204,"BEN","Benin","ppp_2015","GIS/Population/Global_2000_2020/2015/BEN/ben_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3798,208,"DNK","Denmark","ppp_2015","GIS/Population/Global_2000_2020/2015/DNK/dnk_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3799,212,"DMA","Dominica","ppp_2015","GIS/Population/Global_2000_2020/2015/DMA/dma_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3800,214,"DOM","Dominican Republic","ppp_2015","GIS/Population/Global_2000_2020/2015/DOM/dom_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3801,218,"ECU","Ecuador","ppp_2015","GIS/Population/Global_2000_2020/2015/ECU/ecu_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3802,222,"SLV","El Salvador","ppp_2015","GIS/Population/Global_2000_2020/2015/SLV/slv_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3803,226,"GNQ","Equatorial Guinea","ppp_2015","GIS/Population/Global_2000_2020/2015/GNQ/gnq_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3804,231,"ETH","Ethiopia","ppp_2015","GIS/Population/Global_2000_2020/2015/ETH/eth_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3805,232,"ERI","Eritrea","ppp_2015","GIS/Population/Global_2000_2020/2015/ERI/eri_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3806,233,"EST","Estonia","ppp_2015","GIS/Population/Global_2000_2020/2015/EST/est_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3807,234,"FRO","Faroe Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/FRO/fro_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3808,238,"FLK","Falkland Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/FLK/flk_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3809,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/SGS/sgs_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3810,242,"FJI","Fiji","ppp_2015","GIS/Population/Global_2000_2020/2015/FJI/fji_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3811,246,"FIN","Finland","ppp_2015","GIS/Population/Global_2000_2020/2015/FIN/fin_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3812,248,"ALA","Aland Islands ","ppp_2015","GIS/Population/Global_2000_2020/2015/ALA/ala_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3813,250,"FRA","France","ppp_2015","GIS/Population/Global_2000_2020/2015/FRA/fra_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3814,254,"GUF","French Guiana","ppp_2015","GIS/Population/Global_2000_2020/2015/GUF/guf_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3815,258,"PYF","French Polynesia","ppp_2015","GIS/Population/Global_2000_2020/2015/PYF/pyf_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3816,260,"ATF","French Southern Territories","ppp_2015","GIS/Population/Global_2000_2020/2015/ATF/atf_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3817,262,"DJI","Djibouti","ppp_2015","GIS/Population/Global_2000_2020/2015/DJI/dji_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3818,266,"GAB","Gabon","ppp_2015","GIS/Population/Global_2000_2020/2015/GAB/gab_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3819,268,"GEO","Georgia","ppp_2015","GIS/Population/Global_2000_2020/2015/GEO/geo_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3820,270,"GMB","Gambia","ppp_2015","GIS/Population/Global_2000_2020/2015/GMB/gmb_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3821,275,"PSE","Palestina","ppp_2015","GIS/Population/Global_2000_2020/2015/PSE/pse_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3822,276,"DEU","Germany","ppp_2015","GIS/Population/Global_2000_2020/2015/DEU/deu_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3823,288,"GHA","Ghana","ppp_2015","GIS/Population/Global_2000_2020/2015/GHA/gha_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3824,292,"GIB","Gibraltar","ppp_2015","GIS/Population/Global_2000_2020/2015/GIB/gib_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3825,296,"KIR","Kiribati","ppp_2015","GIS/Population/Global_2000_2020/2015/KIR/kir_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3826,300,"GRC","Greece","ppp_2015","GIS/Population/Global_2000_2020/2015/GRC/grc_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3827,308,"GRD","Grenada","ppp_2015","GIS/Population/Global_2000_2020/2015/GRD/grd_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3828,312,"GLP","Guadeloupe","ppp_2015","GIS/Population/Global_2000_2020/2015/GLP/glp_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3829,316,"GUM","Guam","ppp_2015","GIS/Population/Global_2000_2020/2015/GUM/gum_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3830,320,"GTM","Guatemala","ppp_2015","GIS/Population/Global_2000_2020/2015/GTM/gtm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3831,324,"GIN","Guinea","ppp_2015","GIS/Population/Global_2000_2020/2015/GIN/gin_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3832,328,"GUY","Guyana","ppp_2015","GIS/Population/Global_2000_2020/2015/GUY/guy_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3833,332,"HTI","Haiti","ppp_2015","GIS/Population/Global_2000_2020/2015/HTI/hti_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3834,334,"HMD","Heard Island and McDonald Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/HMD/hmd_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3835,336,"VAT","Vatican City","ppp_2015","GIS/Population/Global_2000_2020/2015/VAT/vat_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3836,340,"HND","Honduras","ppp_2015","GIS/Population/Global_2000_2020/2015/HND/hnd_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3837,344,"HKG","Hong Kong","ppp_2015","GIS/Population/Global_2000_2020/2015/HKG/hkg_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3838,348,"HUN","Hungary","ppp_2015","GIS/Population/Global_2000_2020/2015/HUN/hun_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3839,352,"ISL","Iceland","ppp_2015","GIS/Population/Global_2000_2020/2015/ISL/isl_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3840,356,"IND","India","ppp_2015","GIS/Population/Global_2000_2020/2015/IND/ind_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3841,364,"IRN","Iran","ppp_2015","GIS/Population/Global_2000_2020/2015/IRN/irn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3842,368,"IRQ","Iraq","ppp_2015","GIS/Population/Global_2000_2020/2015/IRQ/irq_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3843,372,"IRL","Ireland","ppp_2015","GIS/Population/Global_2000_2020/2015/IRL/irl_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3844,376,"ISR","Israel","ppp_2015","GIS/Population/Global_2000_2020/2015/ISR/isr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3845,380,"ITA","Italy","ppp_2015","GIS/Population/Global_2000_2020/2015/ITA/ita_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3846,384,"CIV","CIte dIvoire","ppp_2015","GIS/Population/Global_2000_2020/2015/CIV/civ_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3847,388,"JAM","Jamaica","ppp_2015","GIS/Population/Global_2000_2020/2015/JAM/jam_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3848,392,"JPN","Japan","ppp_2015","GIS/Population/Global_2000_2020/2015/JPN/jpn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3849,398,"KAZ","Kazakhstan","ppp_2015","GIS/Population/Global_2000_2020/2015/KAZ/kaz_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3850,400,"JOR","Jordan","ppp_2015","GIS/Population/Global_2000_2020/2015/JOR/jor_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3851,404,"KEN","Kenya","ppp_2015","GIS/Population/Global_2000_2020/2015/KEN/ken_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3852,408,"PRK","North Korea","ppp_2015","GIS/Population/Global_2000_2020/2015/PRK/prk_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3853,410,"KOR","South Korea","ppp_2015","GIS/Population/Global_2000_2020/2015/KOR/kor_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3854,414,"KWT","Kuwait","ppp_2015","GIS/Population/Global_2000_2020/2015/KWT/kwt_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3855,417,"KGZ","Kyrgyzstan","ppp_2015","GIS/Population/Global_2000_2020/2015/KGZ/kgz_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3856,418,"LAO","Laos","ppp_2015","GIS/Population/Global_2000_2020/2015/LAO/lao_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3857,422,"LBN","Lebanon","ppp_2015","GIS/Population/Global_2000_2020/2015/LBN/lbn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3858,426,"LSO","Lesotho","ppp_2015","GIS/Population/Global_2000_2020/2015/LSO/lso_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3859,428,"LVA","Latvia","ppp_2015","GIS/Population/Global_2000_2020/2015/LVA/lva_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3860,430,"LBR","Liberia","ppp_2015","GIS/Population/Global_2000_2020/2015/LBR/lbr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3861,434,"LBY","Libya","ppp_2015","GIS/Population/Global_2000_2020/2015/LBY/lby_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3862,438,"LIE","Liechtenstein","ppp_2015","GIS/Population/Global_2000_2020/2015/LIE/lie_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3863,440,"LTU","Lithuania","ppp_2015","GIS/Population/Global_2000_2020/2015/LTU/ltu_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3864,442,"LUX","Luxembourg","ppp_2015","GIS/Population/Global_2000_2020/2015/LUX/lux_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3865,446,"MAC","Macao","ppp_2015","GIS/Population/Global_2000_2020/2015/MAC/mac_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3866,450,"MDG","Madagascar","ppp_2015","GIS/Population/Global_2000_2020/2015/MDG/mdg_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3867,454,"MWI","Malawi","ppp_2015","GIS/Population/Global_2000_2020/2015/MWI/mwi_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3868,458,"MYS","Malaysia","ppp_2015","GIS/Population/Global_2000_2020/2015/MYS/mys_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3869,462,"MDV","Maldives","ppp_2015","GIS/Population/Global_2000_2020/2015/MDV/mdv_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3870,466,"MLI","Mali","ppp_2015","GIS/Population/Global_2000_2020/2015/MLI/mli_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3871,470,"MLT","Malta","ppp_2015","GIS/Population/Global_2000_2020/2015/MLT/mlt_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3872,474,"MTQ","Martinique","ppp_2015","GIS/Population/Global_2000_2020/2015/MTQ/mtq_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3873,478,"MRT","Mauritania","ppp_2015","GIS/Population/Global_2000_2020/2015/MRT/mrt_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3874,480,"MUS","Mauritius","ppp_2015","GIS/Population/Global_2000_2020/2015/MUS/mus_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3875,484,"MEX","Mexico","ppp_2015","GIS/Population/Global_2000_2020/2015/MEX/mex_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3876,492,"MCO","Monaco","ppp_2015","GIS/Population/Global_2000_2020/2015/MCO/mco_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3877,496,"MNG","Mongolia","ppp_2015","GIS/Population/Global_2000_2020/2015/MNG/mng_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3878,498,"MDA","Moldova","ppp_2015","GIS/Population/Global_2000_2020/2015/MDA/mda_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3879,499,"MNE","Montenegro","ppp_2015","GIS/Population/Global_2000_2020/2015/MNE/mne_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3880,500,"MSR","Montserrat","ppp_2015","GIS/Population/Global_2000_2020/2015/MSR/msr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3881,504,"MAR","Morocco","ppp_2015","GIS/Population/Global_2000_2020/2015/MAR/mar_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3882,508,"MOZ","Mozambique","ppp_2015","GIS/Population/Global_2000_2020/2015/MOZ/moz_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3883,512,"OMN","Oman","ppp_2015","GIS/Population/Global_2000_2020/2015/OMN/omn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3884,516,"NAM","Namibia","ppp_2015","GIS/Population/Global_2000_2020/2015/NAM/nam_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3885,520,"NRU","Nauru","ppp_2015","GIS/Population/Global_2000_2020/2015/NRU/nru_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3886,524,"NPL","Nepal","ppp_2015","GIS/Population/Global_2000_2020/2015/NPL/npl_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3887,528,"NLD","Netherlands","ppp_2015","GIS/Population/Global_2000_2020/2015/NLD/nld_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3888,531,"CUW","Curacao","ppp_2015","GIS/Population/Global_2000_2020/2015/CUW/cuw_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3889,533,"ABW","Aruba","ppp_2015","GIS/Population/Global_2000_2020/2015/ABW/abw_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3890,534,"SXM","Sint Maarten (Dutch part)","ppp_2015","GIS/Population/Global_2000_2020/2015/SXM/sxm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3891,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2015","GIS/Population/Global_2000_2020/2015/BES/bes_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3892,540,"NCL","New Caledonia","ppp_2015","GIS/Population/Global_2000_2020/2015/NCL/ncl_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3893,548,"VUT","Vanuatu","ppp_2015","GIS/Population/Global_2000_2020/2015/VUT/vut_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3894,554,"NZL","New Zealand","ppp_2015","GIS/Population/Global_2000_2020/2015/NZL/nzl_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3895,558,"NIC","Nicaragua","ppp_2015","GIS/Population/Global_2000_2020/2015/NIC/nic_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3896,562,"NER","Niger","ppp_2015","GIS/Population/Global_2000_2020/2015/NER/ner_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3897,566,"NGA","Nigeria","ppp_2015","GIS/Population/Global_2000_2020/2015/NGA/nga_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3898,570,"NIU","Niue","ppp_2015","GIS/Population/Global_2000_2020/2015/NIU/niu_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3899,574,"NFK","Norfolk Island","ppp_2015","GIS/Population/Global_2000_2020/2015/NFK/nfk_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3900,578,"NOR","Norway","ppp_2015","GIS/Population/Global_2000_2020/2015/NOR/nor_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3901,580,"MNP","Northern Mariana Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/MNP/mnp_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3902,581,"UMI","United States Minor Outlying Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/UMI/umi_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3903,583,"FSM","Micronesia","ppp_2015","GIS/Population/Global_2000_2020/2015/FSM/fsm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3904,584,"MHL","Marshall Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/MHL/mhl_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3905,585,"PLW","Palau","ppp_2015","GIS/Population/Global_2000_2020/2015/PLW/plw_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3906,586,"PAK","Pakistan","ppp_2015","GIS/Population/Global_2000_2020/2015/PAK/pak_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3907,591,"PAN","Panama","ppp_2015","GIS/Population/Global_2000_2020/2015/PAN/pan_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3908,598,"PNG","Papua New Guinea","ppp_2015","GIS/Population/Global_2000_2020/2015/PNG/png_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3909,600,"PRY","Paraguay","ppp_2015","GIS/Population/Global_2000_2020/2015/PRY/pry_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3910,604,"PER","Peru","ppp_2015","GIS/Population/Global_2000_2020/2015/PER/per_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3911,608,"PHL","Philippines","ppp_2015","GIS/Population/Global_2000_2020/2015/PHL/phl_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3912,612,"PCN","Pitcairn Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/PCN/pcn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3913,616,"POL","Poland","ppp_2015","GIS/Population/Global_2000_2020/2015/POL/pol_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3914,620,"PRT","Portugal","ppp_2015","GIS/Population/Global_2000_2020/2015/PRT/prt_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3915,624,"GNB","Guinea-Bissau","ppp_2015","GIS/Population/Global_2000_2020/2015/GNB/gnb_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3916,626,"TLS","East Timor","ppp_2015","GIS/Population/Global_2000_2020/2015/TLS/tls_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3917,630,"PRI","Puerto Rico","ppp_2015","GIS/Population/Global_2000_2020/2015/PRI/pri_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3918,634,"QAT","Qatar","ppp_2015","GIS/Population/Global_2000_2020/2015/QAT/qat_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3919,638,"REU","Reunion","ppp_2015","GIS/Population/Global_2000_2020/2015/REU/reu_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3920,642,"ROU","Romania","ppp_2015","GIS/Population/Global_2000_2020/2015/ROU/rou_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3921,646,"RWA","Rwanda","ppp_2015","GIS/Population/Global_2000_2020/2015/RWA/rwa_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3922,652,"BLM","Saint Barthelemy","ppp_2015","GIS/Population/Global_2000_2020/2015/BLM/blm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3923,654,"SHN","Saint Helena","ppp_2015","GIS/Population/Global_2000_2020/2015/SHN/shn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3924,659,"KNA","Saint Kitts and Nevis","ppp_2015","GIS/Population/Global_2000_2020/2015/KNA/kna_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3925,660,"AIA","Anguilla","ppp_2015","GIS/Population/Global_2000_2020/2015/AIA/aia_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3926,662,"LCA","Saint Lucia","ppp_2015","GIS/Population/Global_2000_2020/2015/LCA/lca_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3927,663,"MAF","Saint Martin (French part)","ppp_2015","GIS/Population/Global_2000_2020/2015/MAF/maf_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3928,666,"SPM","Saint Pierre and Miquelon","ppp_2015","GIS/Population/Global_2000_2020/2015/SPM/spm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3929,670,"VCT","Saint Vincent and the Grenadines","ppp_2015","GIS/Population/Global_2000_2020/2015/VCT/vct_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3930,674,"SMR","San Marino","ppp_2015","GIS/Population/Global_2000_2020/2015/SMR/smr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3931,678,"STP","Sao Tome and Principe","ppp_2015","GIS/Population/Global_2000_2020/2015/STP/stp_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3932,682,"SAU","Saudi Arabia","ppp_2015","GIS/Population/Global_2000_2020/2015/SAU/sau_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3933,686,"SEN","Senegal","ppp_2015","GIS/Population/Global_2000_2020/2015/SEN/sen_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3934,688,"SRB","Serbia","ppp_2015","GIS/Population/Global_2000_2020/2015/SRB/srb_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3935,690,"SYC","Seychelles","ppp_2015","GIS/Population/Global_2000_2020/2015/SYC/syc_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3936,694,"SLE","Sierra Leone","ppp_2015","GIS/Population/Global_2000_2020/2015/SLE/sle_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3937,702,"SGP","Singapore","ppp_2015","GIS/Population/Global_2000_2020/2015/SGP/sgp_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3938,703,"SVK","Slovakia","ppp_2015","GIS/Population/Global_2000_2020/2015/SVK/svk_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3939,704,"VNM","Vietnam","ppp_2015","GIS/Population/Global_2000_2020/2015/VNM/vnm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3940,705,"SVN","Slovenia","ppp_2015","GIS/Population/Global_2000_2020/2015/SVN/svn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3941,706,"SOM","Somalia","ppp_2015","GIS/Population/Global_2000_2020/2015/SOM/som_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3942,710,"ZAF","South Africa","ppp_2015","GIS/Population/Global_2000_2020/2015/ZAF/zaf_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3943,716,"ZWE","Zimbabwe","ppp_2015","GIS/Population/Global_2000_2020/2015/ZWE/zwe_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3944,724,"ESP","Spain","ppp_2015","GIS/Population/Global_2000_2020/2015/ESP/esp_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3945,728,"SSD","South Sudan","ppp_2015","GIS/Population/Global_2000_2020/2015/SSD/ssd_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3946,729,"SDN","Sudan","ppp_2015","GIS/Population/Global_2000_2020/2015/SDN/sdn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3947,732,"ESH","Western Sahara","ppp_2015","GIS/Population/Global_2000_2020/2015/ESH/esh_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3948,740,"SUR","Suriname","ppp_2015","GIS/Population/Global_2000_2020/2015/SUR/sur_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3949,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/SJM/sjm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3950,748,"SWZ","Swaziland","ppp_2015","GIS/Population/Global_2000_2020/2015/SWZ/swz_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3951,752,"SWE","Sweden","ppp_2015","GIS/Population/Global_2000_2020/2015/SWE/swe_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3952,756,"CHE","Switzerland","ppp_2015","GIS/Population/Global_2000_2020/2015/CHE/che_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3953,760,"SYR","Syria","ppp_2015","GIS/Population/Global_2000_2020/2015/SYR/syr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3954,762,"TJK","Tajikistan","ppp_2015","GIS/Population/Global_2000_2020/2015/TJK/tjk_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3955,764,"THA","Thailand","ppp_2015","GIS/Population/Global_2000_2020/2015/THA/tha_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3956,768,"TGO","Togo","ppp_2015","GIS/Population/Global_2000_2020/2015/TGO/tgo_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3957,772,"TKL","Tokelau","ppp_2015","GIS/Population/Global_2000_2020/2015/TKL/tkl_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3958,776,"TON","Tonga","ppp_2015","GIS/Population/Global_2000_2020/2015/TON/ton_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3959,780,"TTO","Trinidad and Tobago","ppp_2015","GIS/Population/Global_2000_2020/2015/TTO/tto_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3960,784,"ARE","United Arab Emirates","ppp_2015","GIS/Population/Global_2000_2020/2015/ARE/are_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3961,788,"TUN","Tunisia","ppp_2015","GIS/Population/Global_2000_2020/2015/TUN/tun_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3962,792,"TUR","Turkey","ppp_2015","GIS/Population/Global_2000_2020/2015/TUR/tur_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3963,795,"TKM","Turkmenistan","ppp_2015","GIS/Population/Global_2000_2020/2015/TKM/tkm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3964,796,"TCA","Turks and Caicos Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/TCA/tca_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3965,798,"TUV","Tuvalu","ppp_2015","GIS/Population/Global_2000_2020/2015/TUV/tuv_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3966,800,"UGA","Uganda","ppp_2015","GIS/Population/Global_2000_2020/2015/UGA/uga_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3967,804,"UKR","Ukraine","ppp_2015","GIS/Population/Global_2000_2020/2015/UKR/ukr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3968,807,"MKD","Macedonia","ppp_2015","GIS/Population/Global_2000_2020/2015/MKD/mkd_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3969,818,"EGY","Egypt","ppp_2015","GIS/Population/Global_2000_2020/2015/EGY/egy_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3970,826,"GBR","United Kingdom","ppp_2015","GIS/Population/Global_2000_2020/2015/GBR/gbr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3971,831,"GGY","Guernsey","ppp_2015","GIS/Population/Global_2000_2020/2015/GGY/ggy_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3972,832,"JEY","Jersey","ppp_2015","GIS/Population/Global_2000_2020/2015/JEY/jey_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3973,833,"IMN","Isle of Man","ppp_2015","GIS/Population/Global_2000_2020/2015/IMN/imn_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3974,834,"TZA","Tanzania","ppp_2015","GIS/Population/Global_2000_2020/2015/TZA/tza_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3975,854,"BFA","Burkina Faso","ppp_2015","GIS/Population/Global_2000_2020/2015/BFA/bfa_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3976,858,"URY","Uruguay","ppp_2015","GIS/Population/Global_2000_2020/2015/URY/ury_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3977,860,"UZB","Uzbekistan","ppp_2015","GIS/Population/Global_2000_2020/2015/UZB/uzb_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3978,862,"VEN","Venezuela","ppp_2015","GIS/Population/Global_2000_2020/2015/VEN/ven_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3979,876,"WLF","Wallis and Futuna","ppp_2015","GIS/Population/Global_2000_2020/2015/WLF/wlf_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3980,882,"WSM","Samoa","ppp_2015","GIS/Population/Global_2000_2020/2015/WSM/wsm_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3981,887,"YEM","Yemen","ppp_2015","GIS/Population/Global_2000_2020/2015/YEM/yem_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3982,894,"ZMB","Zambia","ppp_2015","GIS/Population/Global_2000_2020/2015/ZMB/zmb_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3983,900,"KOS","Kosovo","ppp_2015","GIS/Population/Global_2000_2020/2015/KOS/kos_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3984,901,"SPR","Spratly Islands","ppp_2015","GIS/Population/Global_2000_2020/2015/SPR/spr_ppp_2015.tif","Estimated total number of people per grid-cell 2015 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3985,643,"RUS","Russia","ppp_2016","GIS/Population/Global_2000_2020/2016/RUS/rus_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3986,360,"IDN","Indonesia","ppp_2016","GIS/Population/Global_2000_2020/2016/IDN/idn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3987,840,"USA","United States","ppp_2016","GIS/Population/Global_2000_2020/2016/USA/usa_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3988,850,"VIR","Virgin_Islands_U_S","ppp_2016","GIS/Population/Global_2000_2020/2016/VIR/vir_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3989,304,"GRL","Greenland","ppp_2016","GIS/Population/Global_2000_2020/2016/GRL/grl_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3990,156,"CHN","China","ppp_2016","GIS/Population/Global_2000_2020/2016/CHN/chn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3991,36,"AUS","Australia","ppp_2016","GIS/Population/Global_2000_2020/2016/AUS/aus_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3992,76,"BRA","Brazil","ppp_2016","GIS/Population/Global_2000_2020/2016/BRA/bra_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3993,124,"CAN","Canada","ppp_2016","GIS/Population/Global_2000_2020/2016/CAN/can_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3994,152,"CHL","Chile","ppp_2016","GIS/Population/Global_2000_2020/2016/CHL/chl_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3995,4,"AFG","Afghanistan","ppp_2016","GIS/Population/Global_2000_2020/2016/AFG/afg_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3996,8,"ALB","Albania","ppp_2016","GIS/Population/Global_2000_2020/2016/ALB/alb_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3997,10,"ATA","Antarctica","ppp_2016","GIS/Population/Global_2000_2020/2016/ATA/ata_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3998,12,"DZA","Algeria","ppp_2016","GIS/Population/Global_2000_2020/2016/DZA/dza_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
3999,16,"ASM","American Samoa","ppp_2016","GIS/Population/Global_2000_2020/2016/ASM/asm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4000,20,"AND","Andorra","ppp_2016","GIS/Population/Global_2000_2020/2016/AND/and_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4001,24,"AGO","Angola","ppp_2016","GIS/Population/Global_2000_2020/2016/AGO/ago_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4002,28,"ATG","Antigua and Barbuda","ppp_2016","GIS/Population/Global_2000_2020/2016/ATG/atg_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4003,31,"AZE","Azerbaijan","ppp_2016","GIS/Population/Global_2000_2020/2016/AZE/aze_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4004,32,"ARG","Argentina","ppp_2016","GIS/Population/Global_2000_2020/2016/ARG/arg_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4005,40,"AUT","Austria","ppp_2016","GIS/Population/Global_2000_2020/2016/AUT/aut_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4006,44,"BHS","Bahamas","ppp_2016","GIS/Population/Global_2000_2020/2016/BHS/bhs_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4007,48,"BHR","Bahrain","ppp_2016","GIS/Population/Global_2000_2020/2016/BHR/bhr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4008,50,"BGD","Bangladesh","ppp_2016","GIS/Population/Global_2000_2020/2016/BGD/bgd_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4009,51,"ARM","Armenia","ppp_2016","GIS/Population/Global_2000_2020/2016/ARM/arm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4010,52,"BRB","Barbados","ppp_2016","GIS/Population/Global_2000_2020/2016/BRB/brb_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4011,56,"BEL","Belgium","ppp_2016","GIS/Population/Global_2000_2020/2016/BEL/bel_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4012,60,"BMU","Bermuda","ppp_2016","GIS/Population/Global_2000_2020/2016/BMU/bmu_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4013,64,"BTN","Bhutan","ppp_2016","GIS/Population/Global_2000_2020/2016/BTN/btn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4014,68,"BOL","Bolivia","ppp_2016","GIS/Population/Global_2000_2020/2016/BOL/bol_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4015,70,"BIH","Bosnia and Herzegovina","ppp_2016","GIS/Population/Global_2000_2020/2016/BIH/bih_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4016,72,"BWA","Botswana","ppp_2016","GIS/Population/Global_2000_2020/2016/BWA/bwa_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4017,74,"BVT","Bouvet Island","ppp_2016","GIS/Population/Global_2000_2020/2016/BVT/bvt_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4018,84,"BLZ","Belize","ppp_2016","GIS/Population/Global_2000_2020/2016/BLZ/blz_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4019,86,"IOT","British Indian Ocean Territory","ppp_2016","GIS/Population/Global_2000_2020/2016/IOT/iot_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4020,90,"SLB","Solomon Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/SLB/slb_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4021,92,"VGB","British Virgin Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/VGB/vgb_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4022,96,"BRN","Brunei","ppp_2016","GIS/Population/Global_2000_2020/2016/BRN/brn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4023,100,"BGR","Bulgaria","ppp_2016","GIS/Population/Global_2000_2020/2016/BGR/bgr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4024,104,"MMR","Myanmar","ppp_2016","GIS/Population/Global_2000_2020/2016/MMR/mmr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4025,108,"BDI","Burundi","ppp_2016","GIS/Population/Global_2000_2020/2016/BDI/bdi_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4026,112,"BLR","Belarus","ppp_2016","GIS/Population/Global_2000_2020/2016/BLR/blr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4027,116,"KHM","Cambodia","ppp_2016","GIS/Population/Global_2000_2020/2016/KHM/khm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4028,120,"CMR","Cameroon","ppp_2016","GIS/Population/Global_2000_2020/2016/CMR/cmr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4029,132,"CPV","Cape Verde","ppp_2016","GIS/Population/Global_2000_2020/2016/CPV/cpv_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4030,136,"CYM","Cayman Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/CYM/cym_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4031,140,"CAF","Central African Republic","ppp_2016","GIS/Population/Global_2000_2020/2016/CAF/caf_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4032,144,"LKA","Sri Lanka","ppp_2016","GIS/Population/Global_2000_2020/2016/LKA/lka_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4033,148,"TCD","Chad","ppp_2016","GIS/Population/Global_2000_2020/2016/TCD/tcd_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4034,158,"TWN","Taiwan","ppp_2016","GIS/Population/Global_2000_2020/2016/TWN/twn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4035,170,"COL","Colombia","ppp_2016","GIS/Population/Global_2000_2020/2016/COL/col_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4036,174,"COM","Comoros","ppp_2016","GIS/Population/Global_2000_2020/2016/COM/com_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4037,175,"MYT","Mayotte","ppp_2016","GIS/Population/Global_2000_2020/2016/MYT/myt_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4038,178,"COG","Republic of Congo","ppp_2016","GIS/Population/Global_2000_2020/2016/COG/cog_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4039,180,"COD","Democratic Republic of the Congo","ppp_2016","GIS/Population/Global_2000_2020/2016/COD/cod_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4040,184,"COK","Cook Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/COK/cok_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4041,188,"CRI","Costa Rica","ppp_2016","GIS/Population/Global_2000_2020/2016/CRI/cri_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4042,191,"HRV","Croatia","ppp_2016","GIS/Population/Global_2000_2020/2016/HRV/hrv_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4043,192,"CUB","Cuba","ppp_2016","GIS/Population/Global_2000_2020/2016/CUB/cub_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4044,196,"CYP","Cyprus","ppp_2016","GIS/Population/Global_2000_2020/2016/CYP/cyp_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4045,203,"CZE","Czech Republic","ppp_2016","GIS/Population/Global_2000_2020/2016/CZE/cze_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4046,204,"BEN","Benin","ppp_2016","GIS/Population/Global_2000_2020/2016/BEN/ben_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4047,208,"DNK","Denmark","ppp_2016","GIS/Population/Global_2000_2020/2016/DNK/dnk_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4048,212,"DMA","Dominica","ppp_2016","GIS/Population/Global_2000_2020/2016/DMA/dma_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4049,214,"DOM","Dominican Republic","ppp_2016","GIS/Population/Global_2000_2020/2016/DOM/dom_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4050,218,"ECU","Ecuador","ppp_2016","GIS/Population/Global_2000_2020/2016/ECU/ecu_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4051,222,"SLV","El Salvador","ppp_2016","GIS/Population/Global_2000_2020/2016/SLV/slv_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4052,226,"GNQ","Equatorial Guinea","ppp_2016","GIS/Population/Global_2000_2020/2016/GNQ/gnq_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4053,231,"ETH","Ethiopia","ppp_2016","GIS/Population/Global_2000_2020/2016/ETH/eth_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4054,232,"ERI","Eritrea","ppp_2016","GIS/Population/Global_2000_2020/2016/ERI/eri_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4055,233,"EST","Estonia","ppp_2016","GIS/Population/Global_2000_2020/2016/EST/est_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4056,234,"FRO","Faroe Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/FRO/fro_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4057,238,"FLK","Falkland Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/FLK/flk_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4058,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/SGS/sgs_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4059,242,"FJI","Fiji","ppp_2016","GIS/Population/Global_2000_2020/2016/FJI/fji_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4060,246,"FIN","Finland","ppp_2016","GIS/Population/Global_2000_2020/2016/FIN/fin_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4061,248,"ALA","Aland Islands ","ppp_2016","GIS/Population/Global_2000_2020/2016/ALA/ala_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4062,250,"FRA","France","ppp_2016","GIS/Population/Global_2000_2020/2016/FRA/fra_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4063,254,"GUF","French Guiana","ppp_2016","GIS/Population/Global_2000_2020/2016/GUF/guf_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4064,258,"PYF","French Polynesia","ppp_2016","GIS/Population/Global_2000_2020/2016/PYF/pyf_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4065,260,"ATF","French Southern Territories","ppp_2016","GIS/Population/Global_2000_2020/2016/ATF/atf_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4066,262,"DJI","Djibouti","ppp_2016","GIS/Population/Global_2000_2020/2016/DJI/dji_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4067,266,"GAB","Gabon","ppp_2016","GIS/Population/Global_2000_2020/2016/GAB/gab_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4068,268,"GEO","Georgia","ppp_2016","GIS/Population/Global_2000_2020/2016/GEO/geo_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4069,270,"GMB","Gambia","ppp_2016","GIS/Population/Global_2000_2020/2016/GMB/gmb_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4070,275,"PSE","Palestina","ppp_2016","GIS/Population/Global_2000_2020/2016/PSE/pse_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4071,276,"DEU","Germany","ppp_2016","GIS/Population/Global_2000_2020/2016/DEU/deu_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4072,288,"GHA","Ghana","ppp_2016","GIS/Population/Global_2000_2020/2016/GHA/gha_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4073,292,"GIB","Gibraltar","ppp_2016","GIS/Population/Global_2000_2020/2016/GIB/gib_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4074,296,"KIR","Kiribati","ppp_2016","GIS/Population/Global_2000_2020/2016/KIR/kir_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4075,300,"GRC","Greece","ppp_2016","GIS/Population/Global_2000_2020/2016/GRC/grc_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4076,308,"GRD","Grenada","ppp_2016","GIS/Population/Global_2000_2020/2016/GRD/grd_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4077,312,"GLP","Guadeloupe","ppp_2016","GIS/Population/Global_2000_2020/2016/GLP/glp_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4078,316,"GUM","Guam","ppp_2016","GIS/Population/Global_2000_2020/2016/GUM/gum_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4079,320,"GTM","Guatemala","ppp_2016","GIS/Population/Global_2000_2020/2016/GTM/gtm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4080,324,"GIN","Guinea","ppp_2016","GIS/Population/Global_2000_2020/2016/GIN/gin_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4081,328,"GUY","Guyana","ppp_2016","GIS/Population/Global_2000_2020/2016/GUY/guy_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4082,332,"HTI","Haiti","ppp_2016","GIS/Population/Global_2000_2020/2016/HTI/hti_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4083,334,"HMD","Heard Island and McDonald Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/HMD/hmd_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4084,336,"VAT","Vatican City","ppp_2016","GIS/Population/Global_2000_2020/2016/VAT/vat_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4085,340,"HND","Honduras","ppp_2016","GIS/Population/Global_2000_2020/2016/HND/hnd_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4086,344,"HKG","Hong Kong","ppp_2016","GIS/Population/Global_2000_2020/2016/HKG/hkg_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4087,348,"HUN","Hungary","ppp_2016","GIS/Population/Global_2000_2020/2016/HUN/hun_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4088,352,"ISL","Iceland","ppp_2016","GIS/Population/Global_2000_2020/2016/ISL/isl_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4089,356,"IND","India","ppp_2016","GIS/Population/Global_2000_2020/2016/IND/ind_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4090,364,"IRN","Iran","ppp_2016","GIS/Population/Global_2000_2020/2016/IRN/irn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4091,368,"IRQ","Iraq","ppp_2016","GIS/Population/Global_2000_2020/2016/IRQ/irq_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4092,372,"IRL","Ireland","ppp_2016","GIS/Population/Global_2000_2020/2016/IRL/irl_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4093,376,"ISR","Israel","ppp_2016","GIS/Population/Global_2000_2020/2016/ISR/isr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4094,380,"ITA","Italy","ppp_2016","GIS/Population/Global_2000_2020/2016/ITA/ita_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4095,384,"CIV","CIte dIvoire","ppp_2016","GIS/Population/Global_2000_2020/2016/CIV/civ_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4096,388,"JAM","Jamaica","ppp_2016","GIS/Population/Global_2000_2020/2016/JAM/jam_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4097,392,"JPN","Japan","ppp_2016","GIS/Population/Global_2000_2020/2016/JPN/jpn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4098,398,"KAZ","Kazakhstan","ppp_2016","GIS/Population/Global_2000_2020/2016/KAZ/kaz_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4099,400,"JOR","Jordan","ppp_2016","GIS/Population/Global_2000_2020/2016/JOR/jor_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4100,404,"KEN","Kenya","ppp_2016","GIS/Population/Global_2000_2020/2016/KEN/ken_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4101,408,"PRK","North Korea","ppp_2016","GIS/Population/Global_2000_2020/2016/PRK/prk_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4102,410,"KOR","South Korea","ppp_2016","GIS/Population/Global_2000_2020/2016/KOR/kor_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4103,414,"KWT","Kuwait","ppp_2016","GIS/Population/Global_2000_2020/2016/KWT/kwt_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4104,417,"KGZ","Kyrgyzstan","ppp_2016","GIS/Population/Global_2000_2020/2016/KGZ/kgz_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4105,418,"LAO","Laos","ppp_2016","GIS/Population/Global_2000_2020/2016/LAO/lao_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4106,422,"LBN","Lebanon","ppp_2016","GIS/Population/Global_2000_2020/2016/LBN/lbn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4107,426,"LSO","Lesotho","ppp_2016","GIS/Population/Global_2000_2020/2016/LSO/lso_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4108,428,"LVA","Latvia","ppp_2016","GIS/Population/Global_2000_2020/2016/LVA/lva_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4109,430,"LBR","Liberia","ppp_2016","GIS/Population/Global_2000_2020/2016/LBR/lbr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4110,434,"LBY","Libya","ppp_2016","GIS/Population/Global_2000_2020/2016/LBY/lby_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4111,438,"LIE","Liechtenstein","ppp_2016","GIS/Population/Global_2000_2020/2016/LIE/lie_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4112,440,"LTU","Lithuania","ppp_2016","GIS/Population/Global_2000_2020/2016/LTU/ltu_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4113,442,"LUX","Luxembourg","ppp_2016","GIS/Population/Global_2000_2020/2016/LUX/lux_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4114,446,"MAC","Macao","ppp_2016","GIS/Population/Global_2000_2020/2016/MAC/mac_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4115,450,"MDG","Madagascar","ppp_2016","GIS/Population/Global_2000_2020/2016/MDG/mdg_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4116,454,"MWI","Malawi","ppp_2016","GIS/Population/Global_2000_2020/2016/MWI/mwi_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4117,458,"MYS","Malaysia","ppp_2016","GIS/Population/Global_2000_2020/2016/MYS/mys_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4118,462,"MDV","Maldives","ppp_2016","GIS/Population/Global_2000_2020/2016/MDV/mdv_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4119,466,"MLI","Mali","ppp_2016","GIS/Population/Global_2000_2020/2016/MLI/mli_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4120,470,"MLT","Malta","ppp_2016","GIS/Population/Global_2000_2020/2016/MLT/mlt_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4121,474,"MTQ","Martinique","ppp_2016","GIS/Population/Global_2000_2020/2016/MTQ/mtq_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4122,478,"MRT","Mauritania","ppp_2016","GIS/Population/Global_2000_2020/2016/MRT/mrt_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4123,480,"MUS","Mauritius","ppp_2016","GIS/Population/Global_2000_2020/2016/MUS/mus_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4124,484,"MEX","Mexico","ppp_2016","GIS/Population/Global_2000_2020/2016/MEX/mex_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4125,492,"MCO","Monaco","ppp_2016","GIS/Population/Global_2000_2020/2016/MCO/mco_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4126,496,"MNG","Mongolia","ppp_2016","GIS/Population/Global_2000_2020/2016/MNG/mng_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4127,498,"MDA","Moldova","ppp_2016","GIS/Population/Global_2000_2020/2016/MDA/mda_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4128,499,"MNE","Montenegro","ppp_2016","GIS/Population/Global_2000_2020/2016/MNE/mne_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4129,500,"MSR","Montserrat","ppp_2016","GIS/Population/Global_2000_2020/2016/MSR/msr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4130,504,"MAR","Morocco","ppp_2016","GIS/Population/Global_2000_2020/2016/MAR/mar_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4131,508,"MOZ","Mozambique","ppp_2016","GIS/Population/Global_2000_2020/2016/MOZ/moz_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4132,512,"OMN","Oman","ppp_2016","GIS/Population/Global_2000_2020/2016/OMN/omn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4133,516,"NAM","Namibia","ppp_2016","GIS/Population/Global_2000_2020/2016/NAM/nam_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4134,520,"NRU","Nauru","ppp_2016","GIS/Population/Global_2000_2020/2016/NRU/nru_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4135,524,"NPL","Nepal","ppp_2016","GIS/Population/Global_2000_2020/2016/NPL/npl_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4136,528,"NLD","Netherlands","ppp_2016","GIS/Population/Global_2000_2020/2016/NLD/nld_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4137,531,"CUW","Curacao","ppp_2016","GIS/Population/Global_2000_2020/2016/CUW/cuw_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4138,533,"ABW","Aruba","ppp_2016","GIS/Population/Global_2000_2020/2016/ABW/abw_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4139,534,"SXM","Sint Maarten (Dutch part)","ppp_2016","GIS/Population/Global_2000_2020/2016/SXM/sxm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4140,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2016","GIS/Population/Global_2000_2020/2016/BES/bes_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4141,540,"NCL","New Caledonia","ppp_2016","GIS/Population/Global_2000_2020/2016/NCL/ncl_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4142,548,"VUT","Vanuatu","ppp_2016","GIS/Population/Global_2000_2020/2016/VUT/vut_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4143,554,"NZL","New Zealand","ppp_2016","GIS/Population/Global_2000_2020/2016/NZL/nzl_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4144,558,"NIC","Nicaragua","ppp_2016","GIS/Population/Global_2000_2020/2016/NIC/nic_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4145,562,"NER","Niger","ppp_2016","GIS/Population/Global_2000_2020/2016/NER/ner_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4146,566,"NGA","Nigeria","ppp_2016","GIS/Population/Global_2000_2020/2016/NGA/nga_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4147,570,"NIU","Niue","ppp_2016","GIS/Population/Global_2000_2020/2016/NIU/niu_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4148,574,"NFK","Norfolk Island","ppp_2016","GIS/Population/Global_2000_2020/2016/NFK/nfk_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4149,578,"NOR","Norway","ppp_2016","GIS/Population/Global_2000_2020/2016/NOR/nor_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4150,580,"MNP","Northern Mariana Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/MNP/mnp_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4151,581,"UMI","United States Minor Outlying Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/UMI/umi_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4152,583,"FSM","Micronesia","ppp_2016","GIS/Population/Global_2000_2020/2016/FSM/fsm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4153,584,"MHL","Marshall Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/MHL/mhl_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4154,585,"PLW","Palau","ppp_2016","GIS/Population/Global_2000_2020/2016/PLW/plw_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4155,586,"PAK","Pakistan","ppp_2016","GIS/Population/Global_2000_2020/2016/PAK/pak_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4156,591,"PAN","Panama","ppp_2016","GIS/Population/Global_2000_2020/2016/PAN/pan_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4157,598,"PNG","Papua New Guinea","ppp_2016","GIS/Population/Global_2000_2020/2016/PNG/png_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4158,600,"PRY","Paraguay","ppp_2016","GIS/Population/Global_2000_2020/2016/PRY/pry_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4159,604,"PER","Peru","ppp_2016","GIS/Population/Global_2000_2020/2016/PER/per_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4160,608,"PHL","Philippines","ppp_2016","GIS/Population/Global_2000_2020/2016/PHL/phl_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4161,612,"PCN","Pitcairn Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/PCN/pcn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4162,616,"POL","Poland","ppp_2016","GIS/Population/Global_2000_2020/2016/POL/pol_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4163,620,"PRT","Portugal","ppp_2016","GIS/Population/Global_2000_2020/2016/PRT/prt_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4164,624,"GNB","Guinea-Bissau","ppp_2016","GIS/Population/Global_2000_2020/2016/GNB/gnb_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4165,626,"TLS","East Timor","ppp_2016","GIS/Population/Global_2000_2020/2016/TLS/tls_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4166,630,"PRI","Puerto Rico","ppp_2016","GIS/Population/Global_2000_2020/2016/PRI/pri_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4167,634,"QAT","Qatar","ppp_2016","GIS/Population/Global_2000_2020/2016/QAT/qat_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4168,638,"REU","Reunion","ppp_2016","GIS/Population/Global_2000_2020/2016/REU/reu_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4169,642,"ROU","Romania","ppp_2016","GIS/Population/Global_2000_2020/2016/ROU/rou_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4170,646,"RWA","Rwanda","ppp_2016","GIS/Population/Global_2000_2020/2016/RWA/rwa_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4171,652,"BLM","Saint Barthelemy","ppp_2016","GIS/Population/Global_2000_2020/2016/BLM/blm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4172,654,"SHN","Saint Helena","ppp_2016","GIS/Population/Global_2000_2020/2016/SHN/shn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4173,659,"KNA","Saint Kitts and Nevis","ppp_2016","GIS/Population/Global_2000_2020/2016/KNA/kna_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4174,660,"AIA","Anguilla","ppp_2016","GIS/Population/Global_2000_2020/2016/AIA/aia_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4175,662,"LCA","Saint Lucia","ppp_2016","GIS/Population/Global_2000_2020/2016/LCA/lca_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4176,663,"MAF","Saint Martin (French part)","ppp_2016","GIS/Population/Global_2000_2020/2016/MAF/maf_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4177,666,"SPM","Saint Pierre and Miquelon","ppp_2016","GIS/Population/Global_2000_2020/2016/SPM/spm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4178,670,"VCT","Saint Vincent and the Grenadines","ppp_2016","GIS/Population/Global_2000_2020/2016/VCT/vct_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4179,674,"SMR","San Marino","ppp_2016","GIS/Population/Global_2000_2020/2016/SMR/smr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4180,678,"STP","Sao Tome and Principe","ppp_2016","GIS/Population/Global_2000_2020/2016/STP/stp_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4181,682,"SAU","Saudi Arabia","ppp_2016","GIS/Population/Global_2000_2020/2016/SAU/sau_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4182,686,"SEN","Senegal","ppp_2016","GIS/Population/Global_2000_2020/2016/SEN/sen_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4183,688,"SRB","Serbia","ppp_2016","GIS/Population/Global_2000_2020/2016/SRB/srb_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4184,690,"SYC","Seychelles","ppp_2016","GIS/Population/Global_2000_2020/2016/SYC/syc_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4185,694,"SLE","Sierra Leone","ppp_2016","GIS/Population/Global_2000_2020/2016/SLE/sle_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4186,702,"SGP","Singapore","ppp_2016","GIS/Population/Global_2000_2020/2016/SGP/sgp_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4187,703,"SVK","Slovakia","ppp_2016","GIS/Population/Global_2000_2020/2016/SVK/svk_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4188,704,"VNM","Vietnam","ppp_2016","GIS/Population/Global_2000_2020/2016/VNM/vnm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4189,705,"SVN","Slovenia","ppp_2016","GIS/Population/Global_2000_2020/2016/SVN/svn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4190,706,"SOM","Somalia","ppp_2016","GIS/Population/Global_2000_2020/2016/SOM/som_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4191,710,"ZAF","South Africa","ppp_2016","GIS/Population/Global_2000_2020/2016/ZAF/zaf_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4192,716,"ZWE","Zimbabwe","ppp_2016","GIS/Population/Global_2000_2020/2016/ZWE/zwe_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4193,724,"ESP","Spain","ppp_2016","GIS/Population/Global_2000_2020/2016/ESP/esp_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4194,728,"SSD","South Sudan","ppp_2016","GIS/Population/Global_2000_2020/2016/SSD/ssd_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4195,729,"SDN","Sudan","ppp_2016","GIS/Population/Global_2000_2020/2016/SDN/sdn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4196,732,"ESH","Western Sahara","ppp_2016","GIS/Population/Global_2000_2020/2016/ESH/esh_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4197,740,"SUR","Suriname","ppp_2016","GIS/Population/Global_2000_2020/2016/SUR/sur_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4198,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/SJM/sjm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4199,748,"SWZ","Swaziland","ppp_2016","GIS/Population/Global_2000_2020/2016/SWZ/swz_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4200,752,"SWE","Sweden","ppp_2016","GIS/Population/Global_2000_2020/2016/SWE/swe_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4201,756,"CHE","Switzerland","ppp_2016","GIS/Population/Global_2000_2020/2016/CHE/che_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4202,760,"SYR","Syria","ppp_2016","GIS/Population/Global_2000_2020/2016/SYR/syr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4203,762,"TJK","Tajikistan","ppp_2016","GIS/Population/Global_2000_2020/2016/TJK/tjk_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4204,764,"THA","Thailand","ppp_2016","GIS/Population/Global_2000_2020/2016/THA/tha_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4205,768,"TGO","Togo","ppp_2016","GIS/Population/Global_2000_2020/2016/TGO/tgo_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4206,772,"TKL","Tokelau","ppp_2016","GIS/Population/Global_2000_2020/2016/TKL/tkl_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4207,776,"TON","Tonga","ppp_2016","GIS/Population/Global_2000_2020/2016/TON/ton_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4208,780,"TTO","Trinidad and Tobago","ppp_2016","GIS/Population/Global_2000_2020/2016/TTO/tto_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4209,784,"ARE","United Arab Emirates","ppp_2016","GIS/Population/Global_2000_2020/2016/ARE/are_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4210,788,"TUN","Tunisia","ppp_2016","GIS/Population/Global_2000_2020/2016/TUN/tun_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4211,792,"TUR","Turkey","ppp_2016","GIS/Population/Global_2000_2020/2016/TUR/tur_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4212,795,"TKM","Turkmenistan","ppp_2016","GIS/Population/Global_2000_2020/2016/TKM/tkm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4213,796,"TCA","Turks and Caicos Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/TCA/tca_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4214,798,"TUV","Tuvalu","ppp_2016","GIS/Population/Global_2000_2020/2016/TUV/tuv_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4215,800,"UGA","Uganda","ppp_2016","GIS/Population/Global_2000_2020/2016/UGA/uga_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4216,804,"UKR","Ukraine","ppp_2016","GIS/Population/Global_2000_2020/2016/UKR/ukr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4217,807,"MKD","Macedonia","ppp_2016","GIS/Population/Global_2000_2020/2016/MKD/mkd_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4218,818,"EGY","Egypt","ppp_2016","GIS/Population/Global_2000_2020/2016/EGY/egy_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4219,826,"GBR","United Kingdom","ppp_2016","GIS/Population/Global_2000_2020/2016/GBR/gbr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4220,831,"GGY","Guernsey","ppp_2016","GIS/Population/Global_2000_2020/2016/GGY/ggy_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4221,832,"JEY","Jersey","ppp_2016","GIS/Population/Global_2000_2020/2016/JEY/jey_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4222,833,"IMN","Isle of Man","ppp_2016","GIS/Population/Global_2000_2020/2016/IMN/imn_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4223,834,"TZA","Tanzania","ppp_2016","GIS/Population/Global_2000_2020/2016/TZA/tza_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4224,854,"BFA","Burkina Faso","ppp_2016","GIS/Population/Global_2000_2020/2016/BFA/bfa_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4225,858,"URY","Uruguay","ppp_2016","GIS/Population/Global_2000_2020/2016/URY/ury_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4226,860,"UZB","Uzbekistan","ppp_2016","GIS/Population/Global_2000_2020/2016/UZB/uzb_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4227,862,"VEN","Venezuela","ppp_2016","GIS/Population/Global_2000_2020/2016/VEN/ven_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4228,876,"WLF","Wallis and Futuna","ppp_2016","GIS/Population/Global_2000_2020/2016/WLF/wlf_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4229,882,"WSM","Samoa","ppp_2016","GIS/Population/Global_2000_2020/2016/WSM/wsm_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4230,887,"YEM","Yemen","ppp_2016","GIS/Population/Global_2000_2020/2016/YEM/yem_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4231,894,"ZMB","Zambia","ppp_2016","GIS/Population/Global_2000_2020/2016/ZMB/zmb_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4232,900,"KOS","Kosovo","ppp_2016","GIS/Population/Global_2000_2020/2016/KOS/kos_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4233,901,"SPR","Spratly Islands","ppp_2016","GIS/Population/Global_2000_2020/2016/SPR/spr_ppp_2016.tif","Estimated total number of people per grid-cell 2016 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4234,643,"RUS","Russia","ppp_2017","GIS/Population/Global_2000_2020/2017/RUS/rus_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4235,360,"IDN","Indonesia","ppp_2017","GIS/Population/Global_2000_2020/2017/IDN/idn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4236,840,"USA","United States","ppp_2017","GIS/Population/Global_2000_2020/2017/USA/usa_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4237,850,"VIR","Virgin_Islands_U_S","ppp_2017","GIS/Population/Global_2000_2020/2017/VIR/vir_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4238,304,"GRL","Greenland","ppp_2017","GIS/Population/Global_2000_2020/2017/GRL/grl_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4239,156,"CHN","China","ppp_2017","GIS/Population/Global_2000_2020/2017/CHN/chn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4240,36,"AUS","Australia","ppp_2017","GIS/Population/Global_2000_2020/2017/AUS/aus_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4241,76,"BRA","Brazil","ppp_2017","GIS/Population/Global_2000_2020/2017/BRA/bra_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4242,124,"CAN","Canada","ppp_2017","GIS/Population/Global_2000_2020/2017/CAN/can_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4243,152,"CHL","Chile","ppp_2017","GIS/Population/Global_2000_2020/2017/CHL/chl_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4244,4,"AFG","Afghanistan","ppp_2017","GIS/Population/Global_2000_2020/2017/AFG/afg_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4245,8,"ALB","Albania","ppp_2017","GIS/Population/Global_2000_2020/2017/ALB/alb_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4246,10,"ATA","Antarctica","ppp_2017","GIS/Population/Global_2000_2020/2017/ATA/ata_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4247,12,"DZA","Algeria","ppp_2017","GIS/Population/Global_2000_2020/2017/DZA/dza_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4248,16,"ASM","American Samoa","ppp_2017","GIS/Population/Global_2000_2020/2017/ASM/asm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4249,20,"AND","Andorra","ppp_2017","GIS/Population/Global_2000_2020/2017/AND/and_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4250,24,"AGO","Angola","ppp_2017","GIS/Population/Global_2000_2020/2017/AGO/ago_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4251,28,"ATG","Antigua and Barbuda","ppp_2017","GIS/Population/Global_2000_2020/2017/ATG/atg_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4252,31,"AZE","Azerbaijan","ppp_2017","GIS/Population/Global_2000_2020/2017/AZE/aze_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4253,32,"ARG","Argentina","ppp_2017","GIS/Population/Global_2000_2020/2017/ARG/arg_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4254,40,"AUT","Austria","ppp_2017","GIS/Population/Global_2000_2020/2017/AUT/aut_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4255,44,"BHS","Bahamas","ppp_2017","GIS/Population/Global_2000_2020/2017/BHS/bhs_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4256,48,"BHR","Bahrain","ppp_2017","GIS/Population/Global_2000_2020/2017/BHR/bhr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4257,50,"BGD","Bangladesh","ppp_2017","GIS/Population/Global_2000_2020/2017/BGD/bgd_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4258,51,"ARM","Armenia","ppp_2017","GIS/Population/Global_2000_2020/2017/ARM/arm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4259,52,"BRB","Barbados","ppp_2017","GIS/Population/Global_2000_2020/2017/BRB/brb_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4260,56,"BEL","Belgium","ppp_2017","GIS/Population/Global_2000_2020/2017/BEL/bel_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4261,60,"BMU","Bermuda","ppp_2017","GIS/Population/Global_2000_2020/2017/BMU/bmu_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4262,64,"BTN","Bhutan","ppp_2017","GIS/Population/Global_2000_2020/2017/BTN/btn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4263,68,"BOL","Bolivia","ppp_2017","GIS/Population/Global_2000_2020/2017/BOL/bol_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4264,70,"BIH","Bosnia and Herzegovina","ppp_2017","GIS/Population/Global_2000_2020/2017/BIH/bih_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4265,72,"BWA","Botswana","ppp_2017","GIS/Population/Global_2000_2020/2017/BWA/bwa_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4266,74,"BVT","Bouvet Island","ppp_2017","GIS/Population/Global_2000_2020/2017/BVT/bvt_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4267,84,"BLZ","Belize","ppp_2017","GIS/Population/Global_2000_2020/2017/BLZ/blz_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4268,86,"IOT","British Indian Ocean Territory","ppp_2017","GIS/Population/Global_2000_2020/2017/IOT/iot_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4269,90,"SLB","Solomon Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/SLB/slb_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4270,92,"VGB","British Virgin Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/VGB/vgb_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4271,96,"BRN","Brunei","ppp_2017","GIS/Population/Global_2000_2020/2017/BRN/brn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4272,100,"BGR","Bulgaria","ppp_2017","GIS/Population/Global_2000_2020/2017/BGR/bgr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4273,104,"MMR","Myanmar","ppp_2017","GIS/Population/Global_2000_2020/2017/MMR/mmr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4274,108,"BDI","Burundi","ppp_2017","GIS/Population/Global_2000_2020/2017/BDI/bdi_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4275,112,"BLR","Belarus","ppp_2017","GIS/Population/Global_2000_2020/2017/BLR/blr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4276,116,"KHM","Cambodia","ppp_2017","GIS/Population/Global_2000_2020/2017/KHM/khm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4277,120,"CMR","Cameroon","ppp_2017","GIS/Population/Global_2000_2020/2017/CMR/cmr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4278,132,"CPV","Cape Verde","ppp_2017","GIS/Population/Global_2000_2020/2017/CPV/cpv_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4279,136,"CYM","Cayman Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/CYM/cym_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4280,140,"CAF","Central African Republic","ppp_2017","GIS/Population/Global_2000_2020/2017/CAF/caf_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4281,144,"LKA","Sri Lanka","ppp_2017","GIS/Population/Global_2000_2020/2017/LKA/lka_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4282,148,"TCD","Chad","ppp_2017","GIS/Population/Global_2000_2020/2017/TCD/tcd_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4283,158,"TWN","Taiwan","ppp_2017","GIS/Population/Global_2000_2020/2017/TWN/twn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4284,170,"COL","Colombia","ppp_2017","GIS/Population/Global_2000_2020/2017/COL/col_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4285,174,"COM","Comoros","ppp_2017","GIS/Population/Global_2000_2020/2017/COM/com_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4286,175,"MYT","Mayotte","ppp_2017","GIS/Population/Global_2000_2020/2017/MYT/myt_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4287,178,"COG","Republic of Congo","ppp_2017","GIS/Population/Global_2000_2020/2017/COG/cog_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4288,180,"COD","Democratic Republic of the Congo","ppp_2017","GIS/Population/Global_2000_2020/2017/COD/cod_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4289,184,"COK","Cook Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/COK/cok_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4290,188,"CRI","Costa Rica","ppp_2017","GIS/Population/Global_2000_2020/2017/CRI/cri_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4291,191,"HRV","Croatia","ppp_2017","GIS/Population/Global_2000_2020/2017/HRV/hrv_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4292,192,"CUB","Cuba","ppp_2017","GIS/Population/Global_2000_2020/2017/CUB/cub_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4293,196,"CYP","Cyprus","ppp_2017","GIS/Population/Global_2000_2020/2017/CYP/cyp_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4294,203,"CZE","Czech Republic","ppp_2017","GIS/Population/Global_2000_2020/2017/CZE/cze_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4295,204,"BEN","Benin","ppp_2017","GIS/Population/Global_2000_2020/2017/BEN/ben_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4296,208,"DNK","Denmark","ppp_2017","GIS/Population/Global_2000_2020/2017/DNK/dnk_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4297,212,"DMA","Dominica","ppp_2017","GIS/Population/Global_2000_2020/2017/DMA/dma_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4298,214,"DOM","Dominican Republic","ppp_2017","GIS/Population/Global_2000_2020/2017/DOM/dom_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4299,218,"ECU","Ecuador","ppp_2017","GIS/Population/Global_2000_2020/2017/ECU/ecu_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4300,222,"SLV","El Salvador","ppp_2017","GIS/Population/Global_2000_2020/2017/SLV/slv_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4301,226,"GNQ","Equatorial Guinea","ppp_2017","GIS/Population/Global_2000_2020/2017/GNQ/gnq_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4302,231,"ETH","Ethiopia","ppp_2017","GIS/Population/Global_2000_2020/2017/ETH/eth_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4303,232,"ERI","Eritrea","ppp_2017","GIS/Population/Global_2000_2020/2017/ERI/eri_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4304,233,"EST","Estonia","ppp_2017","GIS/Population/Global_2000_2020/2017/EST/est_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4305,234,"FRO","Faroe Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/FRO/fro_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4306,238,"FLK","Falkland Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/FLK/flk_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4307,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/SGS/sgs_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4308,242,"FJI","Fiji","ppp_2017","GIS/Population/Global_2000_2020/2017/FJI/fji_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4309,246,"FIN","Finland","ppp_2017","GIS/Population/Global_2000_2020/2017/FIN/fin_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4310,248,"ALA","Aland Islands ","ppp_2017","GIS/Population/Global_2000_2020/2017/ALA/ala_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4311,250,"FRA","France","ppp_2017","GIS/Population/Global_2000_2020/2017/FRA/fra_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4312,254,"GUF","French Guiana","ppp_2017","GIS/Population/Global_2000_2020/2017/GUF/guf_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4313,258,"PYF","French Polynesia","ppp_2017","GIS/Population/Global_2000_2020/2017/PYF/pyf_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4314,260,"ATF","French Southern Territories","ppp_2017","GIS/Population/Global_2000_2020/2017/ATF/atf_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4315,262,"DJI","Djibouti","ppp_2017","GIS/Population/Global_2000_2020/2017/DJI/dji_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4316,266,"GAB","Gabon","ppp_2017","GIS/Population/Global_2000_2020/2017/GAB/gab_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4317,268,"GEO","Georgia","ppp_2017","GIS/Population/Global_2000_2020/2017/GEO/geo_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4318,270,"GMB","Gambia","ppp_2017","GIS/Population/Global_2000_2020/2017/GMB/gmb_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4319,275,"PSE","Palestina","ppp_2017","GIS/Population/Global_2000_2020/2017/PSE/pse_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4320,276,"DEU","Germany","ppp_2017","GIS/Population/Global_2000_2020/2017/DEU/deu_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4321,288,"GHA","Ghana","ppp_2017","GIS/Population/Global_2000_2020/2017/GHA/gha_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4322,292,"GIB","Gibraltar","ppp_2017","GIS/Population/Global_2000_2020/2017/GIB/gib_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4323,296,"KIR","Kiribati","ppp_2017","GIS/Population/Global_2000_2020/2017/KIR/kir_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4324,300,"GRC","Greece","ppp_2017","GIS/Population/Global_2000_2020/2017/GRC/grc_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4325,308,"GRD","Grenada","ppp_2017","GIS/Population/Global_2000_2020/2017/GRD/grd_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4326,312,"GLP","Guadeloupe","ppp_2017","GIS/Population/Global_2000_2020/2017/GLP/glp_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4327,316,"GUM","Guam","ppp_2017","GIS/Population/Global_2000_2020/2017/GUM/gum_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4328,320,"GTM","Guatemala","ppp_2017","GIS/Population/Global_2000_2020/2017/GTM/gtm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4329,324,"GIN","Guinea","ppp_2017","GIS/Population/Global_2000_2020/2017/GIN/gin_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4330,328,"GUY","Guyana","ppp_2017","GIS/Population/Global_2000_2020/2017/GUY/guy_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4331,332,"HTI","Haiti","ppp_2017","GIS/Population/Global_2000_2020/2017/HTI/hti_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4332,334,"HMD","Heard Island and McDonald Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/HMD/hmd_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4333,336,"VAT","Vatican City","ppp_2017","GIS/Population/Global_2000_2020/2017/VAT/vat_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4334,340,"HND","Honduras","ppp_2017","GIS/Population/Global_2000_2020/2017/HND/hnd_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4335,344,"HKG","Hong Kong","ppp_2017","GIS/Population/Global_2000_2020/2017/HKG/hkg_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4336,348,"HUN","Hungary","ppp_2017","GIS/Population/Global_2000_2020/2017/HUN/hun_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4337,352,"ISL","Iceland","ppp_2017","GIS/Population/Global_2000_2020/2017/ISL/isl_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4338,356,"IND","India","ppp_2017","GIS/Population/Global_2000_2020/2017/IND/ind_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4339,364,"IRN","Iran","ppp_2017","GIS/Population/Global_2000_2020/2017/IRN/irn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4340,368,"IRQ","Iraq","ppp_2017","GIS/Population/Global_2000_2020/2017/IRQ/irq_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4341,372,"IRL","Ireland","ppp_2017","GIS/Population/Global_2000_2020/2017/IRL/irl_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4342,376,"ISR","Israel","ppp_2017","GIS/Population/Global_2000_2020/2017/ISR/isr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4343,380,"ITA","Italy","ppp_2017","GIS/Population/Global_2000_2020/2017/ITA/ita_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4344,384,"CIV","CIte dIvoire","ppp_2017","GIS/Population/Global_2000_2020/2017/CIV/civ_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4345,388,"JAM","Jamaica","ppp_2017","GIS/Population/Global_2000_2020/2017/JAM/jam_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4346,392,"JPN","Japan","ppp_2017","GIS/Population/Global_2000_2020/2017/JPN/jpn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4347,398,"KAZ","Kazakhstan","ppp_2017","GIS/Population/Global_2000_2020/2017/KAZ/kaz_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4348,400,"JOR","Jordan","ppp_2017","GIS/Population/Global_2000_2020/2017/JOR/jor_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4349,404,"KEN","Kenya","ppp_2017","GIS/Population/Global_2000_2020/2017/KEN/ken_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4350,408,"PRK","North Korea","ppp_2017","GIS/Population/Global_2000_2020/2017/PRK/prk_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4351,410,"KOR","South Korea","ppp_2017","GIS/Population/Global_2000_2020/2017/KOR/kor_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4352,414,"KWT","Kuwait","ppp_2017","GIS/Population/Global_2000_2020/2017/KWT/kwt_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4353,417,"KGZ","Kyrgyzstan","ppp_2017","GIS/Population/Global_2000_2020/2017/KGZ/kgz_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4354,418,"LAO","Laos","ppp_2017","GIS/Population/Global_2000_2020/2017/LAO/lao_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4355,422,"LBN","Lebanon","ppp_2017","GIS/Population/Global_2000_2020/2017/LBN/lbn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4356,426,"LSO","Lesotho","ppp_2017","GIS/Population/Global_2000_2020/2017/LSO/lso_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4357,428,"LVA","Latvia","ppp_2017","GIS/Population/Global_2000_2020/2017/LVA/lva_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4358,430,"LBR","Liberia","ppp_2017","GIS/Population/Global_2000_2020/2017/LBR/lbr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4359,434,"LBY","Libya","ppp_2017","GIS/Population/Global_2000_2020/2017/LBY/lby_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4360,438,"LIE","Liechtenstein","ppp_2017","GIS/Population/Global_2000_2020/2017/LIE/lie_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4361,440,"LTU","Lithuania","ppp_2017","GIS/Population/Global_2000_2020/2017/LTU/ltu_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4362,442,"LUX","Luxembourg","ppp_2017","GIS/Population/Global_2000_2020/2017/LUX/lux_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4363,446,"MAC","Macao","ppp_2017","GIS/Population/Global_2000_2020/2017/MAC/mac_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4364,450,"MDG","Madagascar","ppp_2017","GIS/Population/Global_2000_2020/2017/MDG/mdg_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4365,454,"MWI","Malawi","ppp_2017","GIS/Population/Global_2000_2020/2017/MWI/mwi_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4366,458,"MYS","Malaysia","ppp_2017","GIS/Population/Global_2000_2020/2017/MYS/mys_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4367,462,"MDV","Maldives","ppp_2017","GIS/Population/Global_2000_2020/2017/MDV/mdv_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4368,466,"MLI","Mali","ppp_2017","GIS/Population/Global_2000_2020/2017/MLI/mli_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4369,470,"MLT","Malta","ppp_2017","GIS/Population/Global_2000_2020/2017/MLT/mlt_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4370,474,"MTQ","Martinique","ppp_2017","GIS/Population/Global_2000_2020/2017/MTQ/mtq_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4371,478,"MRT","Mauritania","ppp_2017","GIS/Population/Global_2000_2020/2017/MRT/mrt_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4372,480,"MUS","Mauritius","ppp_2017","GIS/Population/Global_2000_2020/2017/MUS/mus_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4373,484,"MEX","Mexico","ppp_2017","GIS/Population/Global_2000_2020/2017/MEX/mex_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4374,492,"MCO","Monaco","ppp_2017","GIS/Population/Global_2000_2020/2017/MCO/mco_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4375,496,"MNG","Mongolia","ppp_2017","GIS/Population/Global_2000_2020/2017/MNG/mng_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4376,498,"MDA","Moldova","ppp_2017","GIS/Population/Global_2000_2020/2017/MDA/mda_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4377,499,"MNE","Montenegro","ppp_2017","GIS/Population/Global_2000_2020/2017/MNE/mne_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4378,500,"MSR","Montserrat","ppp_2017","GIS/Population/Global_2000_2020/2017/MSR/msr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4379,504,"MAR","Morocco","ppp_2017","GIS/Population/Global_2000_2020/2017/MAR/mar_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4380,508,"MOZ","Mozambique","ppp_2017","GIS/Population/Global_2000_2020/2017/MOZ/moz_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4381,512,"OMN","Oman","ppp_2017","GIS/Population/Global_2000_2020/2017/OMN/omn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4382,516,"NAM","Namibia","ppp_2017","GIS/Population/Global_2000_2020/2017/NAM/nam_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4383,520,"NRU","Nauru","ppp_2017","GIS/Population/Global_2000_2020/2017/NRU/nru_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4384,524,"NPL","Nepal","ppp_2017","GIS/Population/Global_2000_2020/2017/NPL/npl_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4385,528,"NLD","Netherlands","ppp_2017","GIS/Population/Global_2000_2020/2017/NLD/nld_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4386,531,"CUW","Curacao","ppp_2017","GIS/Population/Global_2000_2020/2017/CUW/cuw_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4387,533,"ABW","Aruba","ppp_2017","GIS/Population/Global_2000_2020/2017/ABW/abw_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4388,534,"SXM","Sint Maarten (Dutch part)","ppp_2017","GIS/Population/Global_2000_2020/2017/SXM/sxm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4389,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2017","GIS/Population/Global_2000_2020/2017/BES/bes_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4390,540,"NCL","New Caledonia","ppp_2017","GIS/Population/Global_2000_2020/2017/NCL/ncl_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4391,548,"VUT","Vanuatu","ppp_2017","GIS/Population/Global_2000_2020/2017/VUT/vut_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4392,554,"NZL","New Zealand","ppp_2017","GIS/Population/Global_2000_2020/2017/NZL/nzl_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4393,558,"NIC","Nicaragua","ppp_2017","GIS/Population/Global_2000_2020/2017/NIC/nic_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4394,562,"NER","Niger","ppp_2017","GIS/Population/Global_2000_2020/2017/NER/ner_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4395,566,"NGA","Nigeria","ppp_2017","GIS/Population/Global_2000_2020/2017/NGA/nga_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4396,570,"NIU","Niue","ppp_2017","GIS/Population/Global_2000_2020/2017/NIU/niu_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4397,574,"NFK","Norfolk Island","ppp_2017","GIS/Population/Global_2000_2020/2017/NFK/nfk_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4398,578,"NOR","Norway","ppp_2017","GIS/Population/Global_2000_2020/2017/NOR/nor_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4399,580,"MNP","Northern Mariana Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/MNP/mnp_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4400,581,"UMI","United States Minor Outlying Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/UMI/umi_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4401,583,"FSM","Micronesia","ppp_2017","GIS/Population/Global_2000_2020/2017/FSM/fsm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4402,584,"MHL","Marshall Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/MHL/mhl_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4403,585,"PLW","Palau","ppp_2017","GIS/Population/Global_2000_2020/2017/PLW/plw_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4404,586,"PAK","Pakistan","ppp_2017","GIS/Population/Global_2000_2020/2017/PAK/pak_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4405,591,"PAN","Panama","ppp_2017","GIS/Population/Global_2000_2020/2017/PAN/pan_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4406,598,"PNG","Papua New Guinea","ppp_2017","GIS/Population/Global_2000_2020/2017/PNG/png_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4407,600,"PRY","Paraguay","ppp_2017","GIS/Population/Global_2000_2020/2017/PRY/pry_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4408,604,"PER","Peru","ppp_2017","GIS/Population/Global_2000_2020/2017/PER/per_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4409,608,"PHL","Philippines","ppp_2017","GIS/Population/Global_2000_2020/2017/PHL/phl_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4410,612,"PCN","Pitcairn Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/PCN/pcn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4411,616,"POL","Poland","ppp_2017","GIS/Population/Global_2000_2020/2017/POL/pol_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4412,620,"PRT","Portugal","ppp_2017","GIS/Population/Global_2000_2020/2017/PRT/prt_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4413,624,"GNB","Guinea-Bissau","ppp_2017","GIS/Population/Global_2000_2020/2017/GNB/gnb_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4414,626,"TLS","East Timor","ppp_2017","GIS/Population/Global_2000_2020/2017/TLS/tls_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4415,630,"PRI","Puerto Rico","ppp_2017","GIS/Population/Global_2000_2020/2017/PRI/pri_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4416,634,"QAT","Qatar","ppp_2017","GIS/Population/Global_2000_2020/2017/QAT/qat_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4417,638,"REU","Reunion","ppp_2017","GIS/Population/Global_2000_2020/2017/REU/reu_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4418,642,"ROU","Romania","ppp_2017","GIS/Population/Global_2000_2020/2017/ROU/rou_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4419,646,"RWA","Rwanda","ppp_2017","GIS/Population/Global_2000_2020/2017/RWA/rwa_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4420,652,"BLM","Saint Barthelemy","ppp_2017","GIS/Population/Global_2000_2020/2017/BLM/blm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4421,654,"SHN","Saint Helena","ppp_2017","GIS/Population/Global_2000_2020/2017/SHN/shn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4422,659,"KNA","Saint Kitts and Nevis","ppp_2017","GIS/Population/Global_2000_2020/2017/KNA/kna_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4423,660,"AIA","Anguilla","ppp_2017","GIS/Population/Global_2000_2020/2017/AIA/aia_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4424,662,"LCA","Saint Lucia","ppp_2017","GIS/Population/Global_2000_2020/2017/LCA/lca_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4425,663,"MAF","Saint Martin (French part)","ppp_2017","GIS/Population/Global_2000_2020/2017/MAF/maf_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4426,666,"SPM","Saint Pierre and Miquelon","ppp_2017","GIS/Population/Global_2000_2020/2017/SPM/spm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4427,670,"VCT","Saint Vincent and the Grenadines","ppp_2017","GIS/Population/Global_2000_2020/2017/VCT/vct_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4428,674,"SMR","San Marino","ppp_2017","GIS/Population/Global_2000_2020/2017/SMR/smr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4429,678,"STP","Sao Tome and Principe","ppp_2017","GIS/Population/Global_2000_2020/2017/STP/stp_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4430,682,"SAU","Saudi Arabia","ppp_2017","GIS/Population/Global_2000_2020/2017/SAU/sau_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4431,686,"SEN","Senegal","ppp_2017","GIS/Population/Global_2000_2020/2017/SEN/sen_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4432,688,"SRB","Serbia","ppp_2017","GIS/Population/Global_2000_2020/2017/SRB/srb_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4433,690,"SYC","Seychelles","ppp_2017","GIS/Population/Global_2000_2020/2017/SYC/syc_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4434,694,"SLE","Sierra Leone","ppp_2017","GIS/Population/Global_2000_2020/2017/SLE/sle_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4435,702,"SGP","Singapore","ppp_2017","GIS/Population/Global_2000_2020/2017/SGP/sgp_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4436,703,"SVK","Slovakia","ppp_2017","GIS/Population/Global_2000_2020/2017/SVK/svk_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4437,704,"VNM","Vietnam","ppp_2017","GIS/Population/Global_2000_2020/2017/VNM/vnm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4438,705,"SVN","Slovenia","ppp_2017","GIS/Population/Global_2000_2020/2017/SVN/svn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4439,706,"SOM","Somalia","ppp_2017","GIS/Population/Global_2000_2020/2017/SOM/som_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4440,710,"ZAF","South Africa","ppp_2017","GIS/Population/Global_2000_2020/2017/ZAF/zaf_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4441,716,"ZWE","Zimbabwe","ppp_2017","GIS/Population/Global_2000_2020/2017/ZWE/zwe_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4442,724,"ESP","Spain","ppp_2017","GIS/Population/Global_2000_2020/2017/ESP/esp_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4443,728,"SSD","South Sudan","ppp_2017","GIS/Population/Global_2000_2020/2017/SSD/ssd_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4444,729,"SDN","Sudan","ppp_2017","GIS/Population/Global_2000_2020/2017/SDN/sdn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4445,732,"ESH","Western Sahara","ppp_2017","GIS/Population/Global_2000_2020/2017/ESH/esh_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4446,740,"SUR","Suriname","ppp_2017","GIS/Population/Global_2000_2020/2017/SUR/sur_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4447,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/SJM/sjm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4448,748,"SWZ","Swaziland","ppp_2017","GIS/Population/Global_2000_2020/2017/SWZ/swz_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4449,752,"SWE","Sweden","ppp_2017","GIS/Population/Global_2000_2020/2017/SWE/swe_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4450,756,"CHE","Switzerland","ppp_2017","GIS/Population/Global_2000_2020/2017/CHE/che_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4451,760,"SYR","Syria","ppp_2017","GIS/Population/Global_2000_2020/2017/SYR/syr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4452,762,"TJK","Tajikistan","ppp_2017","GIS/Population/Global_2000_2020/2017/TJK/tjk_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4453,764,"THA","Thailand","ppp_2017","GIS/Population/Global_2000_2020/2017/THA/tha_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4454,768,"TGO","Togo","ppp_2017","GIS/Population/Global_2000_2020/2017/TGO/tgo_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4455,772,"TKL","Tokelau","ppp_2017","GIS/Population/Global_2000_2020/2017/TKL/tkl_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4456,776,"TON","Tonga","ppp_2017","GIS/Population/Global_2000_2020/2017/TON/ton_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4457,780,"TTO","Trinidad and Tobago","ppp_2017","GIS/Population/Global_2000_2020/2017/TTO/tto_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4458,784,"ARE","United Arab Emirates","ppp_2017","GIS/Population/Global_2000_2020/2017/ARE/are_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4459,788,"TUN","Tunisia","ppp_2017","GIS/Population/Global_2000_2020/2017/TUN/tun_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4460,792,"TUR","Turkey","ppp_2017","GIS/Population/Global_2000_2020/2017/TUR/tur_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4461,795,"TKM","Turkmenistan","ppp_2017","GIS/Population/Global_2000_2020/2017/TKM/tkm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4462,796,"TCA","Turks and Caicos Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/TCA/tca_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4463,798,"TUV","Tuvalu","ppp_2017","GIS/Population/Global_2000_2020/2017/TUV/tuv_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4464,800,"UGA","Uganda","ppp_2017","GIS/Population/Global_2000_2020/2017/UGA/uga_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4465,804,"UKR","Ukraine","ppp_2017","GIS/Population/Global_2000_2020/2017/UKR/ukr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4466,807,"MKD","Macedonia","ppp_2017","GIS/Population/Global_2000_2020/2017/MKD/mkd_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4467,818,"EGY","Egypt","ppp_2017","GIS/Population/Global_2000_2020/2017/EGY/egy_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4468,826,"GBR","United Kingdom","ppp_2017","GIS/Population/Global_2000_2020/2017/GBR/gbr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4469,831,"GGY","Guernsey","ppp_2017","GIS/Population/Global_2000_2020/2017/GGY/ggy_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4470,832,"JEY","Jersey","ppp_2017","GIS/Population/Global_2000_2020/2017/JEY/jey_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4471,833,"IMN","Isle of Man","ppp_2017","GIS/Population/Global_2000_2020/2017/IMN/imn_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4472,834,"TZA","Tanzania","ppp_2017","GIS/Population/Global_2000_2020/2017/TZA/tza_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4473,854,"BFA","Burkina Faso","ppp_2017","GIS/Population/Global_2000_2020/2017/BFA/bfa_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4474,858,"URY","Uruguay","ppp_2017","GIS/Population/Global_2000_2020/2017/URY/ury_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4475,860,"UZB","Uzbekistan","ppp_2017","GIS/Population/Global_2000_2020/2017/UZB/uzb_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4476,862,"VEN","Venezuela","ppp_2017","GIS/Population/Global_2000_2020/2017/VEN/ven_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4477,876,"WLF","Wallis and Futuna","ppp_2017","GIS/Population/Global_2000_2020/2017/WLF/wlf_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4478,882,"WSM","Samoa","ppp_2017","GIS/Population/Global_2000_2020/2017/WSM/wsm_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4479,887,"YEM","Yemen","ppp_2017","GIS/Population/Global_2000_2020/2017/YEM/yem_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4480,894,"ZMB","Zambia","ppp_2017","GIS/Population/Global_2000_2020/2017/ZMB/zmb_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4481,900,"KOS","Kosovo","ppp_2017","GIS/Population/Global_2000_2020/2017/KOS/kos_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4482,901,"SPR","Spratly Islands","ppp_2017","GIS/Population/Global_2000_2020/2017/SPR/spr_ppp_2017.tif","Estimated total number of people per grid-cell 2017 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4483,643,"RUS","Russia","ppp_2018","GIS/Population/Global_2000_2020/2018/RUS/rus_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4484,360,"IDN","Indonesia","ppp_2018","GIS/Population/Global_2000_2020/2018/IDN/idn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4485,840,"USA","United States","ppp_2018","GIS/Population/Global_2000_2020/2018/USA/usa_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4486,850,"VIR","Virgin_Islands_U_S","ppp_2018","GIS/Population/Global_2000_2020/2018/VIR/vir_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4487,304,"GRL","Greenland","ppp_2018","GIS/Population/Global_2000_2020/2018/GRL/grl_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4488,156,"CHN","China","ppp_2018","GIS/Population/Global_2000_2020/2018/CHN/chn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4489,36,"AUS","Australia","ppp_2018","GIS/Population/Global_2000_2020/2018/AUS/aus_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4490,76,"BRA","Brazil","ppp_2018","GIS/Population/Global_2000_2020/2018/BRA/bra_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4491,124,"CAN","Canada","ppp_2018","GIS/Population/Global_2000_2020/2018/CAN/can_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4492,152,"CHL","Chile","ppp_2018","GIS/Population/Global_2000_2020/2018/CHL/chl_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4493,4,"AFG","Afghanistan","ppp_2018","GIS/Population/Global_2000_2020/2018/AFG/afg_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4494,8,"ALB","Albania","ppp_2018","GIS/Population/Global_2000_2020/2018/ALB/alb_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4495,10,"ATA","Antarctica","ppp_2018","GIS/Population/Global_2000_2020/2018/ATA/ata_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4496,12,"DZA","Algeria","ppp_2018","GIS/Population/Global_2000_2020/2018/DZA/dza_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4497,16,"ASM","American Samoa","ppp_2018","GIS/Population/Global_2000_2020/2018/ASM/asm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4498,20,"AND","Andorra","ppp_2018","GIS/Population/Global_2000_2020/2018/AND/and_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4499,24,"AGO","Angola","ppp_2018","GIS/Population/Global_2000_2020/2018/AGO/ago_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4500,28,"ATG","Antigua and Barbuda","ppp_2018","GIS/Population/Global_2000_2020/2018/ATG/atg_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4501,31,"AZE","Azerbaijan","ppp_2018","GIS/Population/Global_2000_2020/2018/AZE/aze_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4502,32,"ARG","Argentina","ppp_2018","GIS/Population/Global_2000_2020/2018/ARG/arg_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4503,40,"AUT","Austria","ppp_2018","GIS/Population/Global_2000_2020/2018/AUT/aut_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4504,44,"BHS","Bahamas","ppp_2018","GIS/Population/Global_2000_2020/2018/BHS/bhs_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4505,48,"BHR","Bahrain","ppp_2018","GIS/Population/Global_2000_2020/2018/BHR/bhr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4506,50,"BGD","Bangladesh","ppp_2018","GIS/Population/Global_2000_2020/2018/BGD/bgd_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4507,51,"ARM","Armenia","ppp_2018","GIS/Population/Global_2000_2020/2018/ARM/arm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4508,52,"BRB","Barbados","ppp_2018","GIS/Population/Global_2000_2020/2018/BRB/brb_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4509,56,"BEL","Belgium","ppp_2018","GIS/Population/Global_2000_2020/2018/BEL/bel_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4510,60,"BMU","Bermuda","ppp_2018","GIS/Population/Global_2000_2020/2018/BMU/bmu_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4511,64,"BTN","Bhutan","ppp_2018","GIS/Population/Global_2000_2020/2018/BTN/btn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4512,68,"BOL","Bolivia","ppp_2018","GIS/Population/Global_2000_2020/2018/BOL/bol_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4513,70,"BIH","Bosnia and Herzegovina","ppp_2018","GIS/Population/Global_2000_2020/2018/BIH/bih_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4514,72,"BWA","Botswana","ppp_2018","GIS/Population/Global_2000_2020/2018/BWA/bwa_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4515,74,"BVT","Bouvet Island","ppp_2018","GIS/Population/Global_2000_2020/2018/BVT/bvt_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4516,84,"BLZ","Belize","ppp_2018","GIS/Population/Global_2000_2020/2018/BLZ/blz_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4517,86,"IOT","British Indian Ocean Territory","ppp_2018","GIS/Population/Global_2000_2020/2018/IOT/iot_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4518,90,"SLB","Solomon Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/SLB/slb_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4519,92,"VGB","British Virgin Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/VGB/vgb_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4520,96,"BRN","Brunei","ppp_2018","GIS/Population/Global_2000_2020/2018/BRN/brn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4521,100,"BGR","Bulgaria","ppp_2018","GIS/Population/Global_2000_2020/2018/BGR/bgr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4522,104,"MMR","Myanmar","ppp_2018","GIS/Population/Global_2000_2020/2018/MMR/mmr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4523,108,"BDI","Burundi","ppp_2018","GIS/Population/Global_2000_2020/2018/BDI/bdi_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4524,112,"BLR","Belarus","ppp_2018","GIS/Population/Global_2000_2020/2018/BLR/blr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4525,116,"KHM","Cambodia","ppp_2018","GIS/Population/Global_2000_2020/2018/KHM/khm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4526,120,"CMR","Cameroon","ppp_2018","GIS/Population/Global_2000_2020/2018/CMR/cmr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4527,132,"CPV","Cape Verde","ppp_2018","GIS/Population/Global_2000_2020/2018/CPV/cpv_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4528,136,"CYM","Cayman Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/CYM/cym_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4529,140,"CAF","Central African Republic","ppp_2018","GIS/Population/Global_2000_2020/2018/CAF/caf_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4530,144,"LKA","Sri Lanka","ppp_2018","GIS/Population/Global_2000_2020/2018/LKA/lka_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4531,148,"TCD","Chad","ppp_2018","GIS/Population/Global_2000_2020/2018/TCD/tcd_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4532,158,"TWN","Taiwan","ppp_2018","GIS/Population/Global_2000_2020/2018/TWN/twn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4533,170,"COL","Colombia","ppp_2018","GIS/Population/Global_2000_2020/2018/COL/col_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4534,174,"COM","Comoros","ppp_2018","GIS/Population/Global_2000_2020/2018/COM/com_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4535,175,"MYT","Mayotte","ppp_2018","GIS/Population/Global_2000_2020/2018/MYT/myt_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4536,178,"COG","Republic of Congo","ppp_2018","GIS/Population/Global_2000_2020/2018/COG/cog_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4537,180,"COD","Democratic Republic of the Congo","ppp_2018","GIS/Population/Global_2000_2020/2018/COD/cod_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4538,184,"COK","Cook Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/COK/cok_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4539,188,"CRI","Costa Rica","ppp_2018","GIS/Population/Global_2000_2020/2018/CRI/cri_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4540,191,"HRV","Croatia","ppp_2018","GIS/Population/Global_2000_2020/2018/HRV/hrv_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4541,192,"CUB","Cuba","ppp_2018","GIS/Population/Global_2000_2020/2018/CUB/cub_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4542,196,"CYP","Cyprus","ppp_2018","GIS/Population/Global_2000_2020/2018/CYP/cyp_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4543,203,"CZE","Czech Republic","ppp_2018","GIS/Population/Global_2000_2020/2018/CZE/cze_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4544,204,"BEN","Benin","ppp_2018","GIS/Population/Global_2000_2020/2018/BEN/ben_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4545,208,"DNK","Denmark","ppp_2018","GIS/Population/Global_2000_2020/2018/DNK/dnk_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4546,212,"DMA","Dominica","ppp_2018","GIS/Population/Global_2000_2020/2018/DMA/dma_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4547,214,"DOM","Dominican Republic","ppp_2018","GIS/Population/Global_2000_2020/2018/DOM/dom_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4548,218,"ECU","Ecuador","ppp_2018","GIS/Population/Global_2000_2020/2018/ECU/ecu_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4549,222,"SLV","El Salvador","ppp_2018","GIS/Population/Global_2000_2020/2018/SLV/slv_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4550,226,"GNQ","Equatorial Guinea","ppp_2018","GIS/Population/Global_2000_2020/2018/GNQ/gnq_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4551,231,"ETH","Ethiopia","ppp_2018","GIS/Population/Global_2000_2020/2018/ETH/eth_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4552,232,"ERI","Eritrea","ppp_2018","GIS/Population/Global_2000_2020/2018/ERI/eri_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4553,233,"EST","Estonia","ppp_2018","GIS/Population/Global_2000_2020/2018/EST/est_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4554,234,"FRO","Faroe Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/FRO/fro_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4555,238,"FLK","Falkland Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/FLK/flk_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4556,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/SGS/sgs_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4557,242,"FJI","Fiji","ppp_2018","GIS/Population/Global_2000_2020/2018/FJI/fji_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4558,246,"FIN","Finland","ppp_2018","GIS/Population/Global_2000_2020/2018/FIN/fin_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4559,248,"ALA","Aland Islands ","ppp_2018","GIS/Population/Global_2000_2020/2018/ALA/ala_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4560,250,"FRA","France","ppp_2018","GIS/Population/Global_2000_2020/2018/FRA/fra_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4561,254,"GUF","French Guiana","ppp_2018","GIS/Population/Global_2000_2020/2018/GUF/guf_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4562,258,"PYF","French Polynesia","ppp_2018","GIS/Population/Global_2000_2020/2018/PYF/pyf_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4563,260,"ATF","French Southern Territories","ppp_2018","GIS/Population/Global_2000_2020/2018/ATF/atf_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4564,262,"DJI","Djibouti","ppp_2018","GIS/Population/Global_2000_2020/2018/DJI/dji_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4565,266,"GAB","Gabon","ppp_2018","GIS/Population/Global_2000_2020/2018/GAB/gab_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4566,268,"GEO","Georgia","ppp_2018","GIS/Population/Global_2000_2020/2018/GEO/geo_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4567,270,"GMB","Gambia","ppp_2018","GIS/Population/Global_2000_2020/2018/GMB/gmb_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4568,275,"PSE","Palestina","ppp_2018","GIS/Population/Global_2000_2020/2018/PSE/pse_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4569,276,"DEU","Germany","ppp_2018","GIS/Population/Global_2000_2020/2018/DEU/deu_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4570,288,"GHA","Ghana","ppp_2018","GIS/Population/Global_2000_2020/2018/GHA/gha_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4571,292,"GIB","Gibraltar","ppp_2018","GIS/Population/Global_2000_2020/2018/GIB/gib_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4572,296,"KIR","Kiribati","ppp_2018","GIS/Population/Global_2000_2020/2018/KIR/kir_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4573,300,"GRC","Greece","ppp_2018","GIS/Population/Global_2000_2020/2018/GRC/grc_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4574,308,"GRD","Grenada","ppp_2018","GIS/Population/Global_2000_2020/2018/GRD/grd_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4575,312,"GLP","Guadeloupe","ppp_2018","GIS/Population/Global_2000_2020/2018/GLP/glp_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4576,316,"GUM","Guam","ppp_2018","GIS/Population/Global_2000_2020/2018/GUM/gum_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4577,320,"GTM","Guatemala","ppp_2018","GIS/Population/Global_2000_2020/2018/GTM/gtm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4578,324,"GIN","Guinea","ppp_2018","GIS/Population/Global_2000_2020/2018/GIN/gin_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4579,328,"GUY","Guyana","ppp_2018","GIS/Population/Global_2000_2020/2018/GUY/guy_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4580,332,"HTI","Haiti","ppp_2018","GIS/Population/Global_2000_2020/2018/HTI/hti_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4581,334,"HMD","Heard Island and McDonald Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/HMD/hmd_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4582,336,"VAT","Vatican City","ppp_2018","GIS/Population/Global_2000_2020/2018/VAT/vat_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4583,340,"HND","Honduras","ppp_2018","GIS/Population/Global_2000_2020/2018/HND/hnd_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4584,344,"HKG","Hong Kong","ppp_2018","GIS/Population/Global_2000_2020/2018/HKG/hkg_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4585,348,"HUN","Hungary","ppp_2018","GIS/Population/Global_2000_2020/2018/HUN/hun_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4586,352,"ISL","Iceland","ppp_2018","GIS/Population/Global_2000_2020/2018/ISL/isl_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4587,356,"IND","India","ppp_2018","GIS/Population/Global_2000_2020/2018/IND/ind_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4588,364,"IRN","Iran","ppp_2018","GIS/Population/Global_2000_2020/2018/IRN/irn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4589,368,"IRQ","Iraq","ppp_2018","GIS/Population/Global_2000_2020/2018/IRQ/irq_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4590,372,"IRL","Ireland","ppp_2018","GIS/Population/Global_2000_2020/2018/IRL/irl_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4591,376,"ISR","Israel","ppp_2018","GIS/Population/Global_2000_2020/2018/ISR/isr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4592,380,"ITA","Italy","ppp_2018","GIS/Population/Global_2000_2020/2018/ITA/ita_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4593,384,"CIV","CIte dIvoire","ppp_2018","GIS/Population/Global_2000_2020/2018/CIV/civ_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4594,388,"JAM","Jamaica","ppp_2018","GIS/Population/Global_2000_2020/2018/JAM/jam_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4595,392,"JPN","Japan","ppp_2018","GIS/Population/Global_2000_2020/2018/JPN/jpn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4596,398,"KAZ","Kazakhstan","ppp_2018","GIS/Population/Global_2000_2020/2018/KAZ/kaz_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4597,400,"JOR","Jordan","ppp_2018","GIS/Population/Global_2000_2020/2018/JOR/jor_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4598,404,"KEN","Kenya","ppp_2018","GIS/Population/Global_2000_2020/2018/KEN/ken_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4599,408,"PRK","North Korea","ppp_2018","GIS/Population/Global_2000_2020/2018/PRK/prk_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4600,410,"KOR","South Korea","ppp_2018","GIS/Population/Global_2000_2020/2018/KOR/kor_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4601,414,"KWT","Kuwait","ppp_2018","GIS/Population/Global_2000_2020/2018/KWT/kwt_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4602,417,"KGZ","Kyrgyzstan","ppp_2018","GIS/Population/Global_2000_2020/2018/KGZ/kgz_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4603,418,"LAO","Laos","ppp_2018","GIS/Population/Global_2000_2020/2018/LAO/lao_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4604,422,"LBN","Lebanon","ppp_2018","GIS/Population/Global_2000_2020/2018/LBN/lbn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4605,426,"LSO","Lesotho","ppp_2018","GIS/Population/Global_2000_2020/2018/LSO/lso_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4606,428,"LVA","Latvia","ppp_2018","GIS/Population/Global_2000_2020/2018/LVA/lva_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4607,430,"LBR","Liberia","ppp_2018","GIS/Population/Global_2000_2020/2018/LBR/lbr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4608,434,"LBY","Libya","ppp_2018","GIS/Population/Global_2000_2020/2018/LBY/lby_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4609,438,"LIE","Liechtenstein","ppp_2018","GIS/Population/Global_2000_2020/2018/LIE/lie_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4610,440,"LTU","Lithuania","ppp_2018","GIS/Population/Global_2000_2020/2018/LTU/ltu_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4611,442,"LUX","Luxembourg","ppp_2018","GIS/Population/Global_2000_2020/2018/LUX/lux_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4612,446,"MAC","Macao","ppp_2018","GIS/Population/Global_2000_2020/2018/MAC/mac_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4613,450,"MDG","Madagascar","ppp_2018","GIS/Population/Global_2000_2020/2018/MDG/mdg_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4614,454,"MWI","Malawi","ppp_2018","GIS/Population/Global_2000_2020/2018/MWI/mwi_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4615,458,"MYS","Malaysia","ppp_2018","GIS/Population/Global_2000_2020/2018/MYS/mys_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4616,462,"MDV","Maldives","ppp_2018","GIS/Population/Global_2000_2020/2018/MDV/mdv_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4617,466,"MLI","Mali","ppp_2018","GIS/Population/Global_2000_2020/2018/MLI/mli_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4618,470,"MLT","Malta","ppp_2018","GIS/Population/Global_2000_2020/2018/MLT/mlt_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4619,474,"MTQ","Martinique","ppp_2018","GIS/Population/Global_2000_2020/2018/MTQ/mtq_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4620,478,"MRT","Mauritania","ppp_2018","GIS/Population/Global_2000_2020/2018/MRT/mrt_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4621,480,"MUS","Mauritius","ppp_2018","GIS/Population/Global_2000_2020/2018/MUS/mus_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4622,484,"MEX","Mexico","ppp_2018","GIS/Population/Global_2000_2020/2018/MEX/mex_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4623,492,"MCO","Monaco","ppp_2018","GIS/Population/Global_2000_2020/2018/MCO/mco_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4624,496,"MNG","Mongolia","ppp_2018","GIS/Population/Global_2000_2020/2018/MNG/mng_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4625,498,"MDA","Moldova","ppp_2018","GIS/Population/Global_2000_2020/2018/MDA/mda_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4626,499,"MNE","Montenegro","ppp_2018","GIS/Population/Global_2000_2020/2018/MNE/mne_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4627,500,"MSR","Montserrat","ppp_2018","GIS/Population/Global_2000_2020/2018/MSR/msr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4628,504,"MAR","Morocco","ppp_2018","GIS/Population/Global_2000_2020/2018/MAR/mar_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4629,508,"MOZ","Mozambique","ppp_2018","GIS/Population/Global_2000_2020/2018/MOZ/moz_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4630,512,"OMN","Oman","ppp_2018","GIS/Population/Global_2000_2020/2018/OMN/omn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4631,516,"NAM","Namibia","ppp_2018","GIS/Population/Global_2000_2020/2018/NAM/nam_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4632,520,"NRU","Nauru","ppp_2018","GIS/Population/Global_2000_2020/2018/NRU/nru_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4633,524,"NPL","Nepal","ppp_2018","GIS/Population/Global_2000_2020/2018/NPL/npl_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4634,528,"NLD","Netherlands","ppp_2018","GIS/Population/Global_2000_2020/2018/NLD/nld_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4635,531,"CUW","Curacao","ppp_2018","GIS/Population/Global_2000_2020/2018/CUW/cuw_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4636,533,"ABW","Aruba","ppp_2018","GIS/Population/Global_2000_2020/2018/ABW/abw_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4637,534,"SXM","Sint Maarten (Dutch part)","ppp_2018","GIS/Population/Global_2000_2020/2018/SXM/sxm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4638,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2018","GIS/Population/Global_2000_2020/2018/BES/bes_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4639,540,"NCL","New Caledonia","ppp_2018","GIS/Population/Global_2000_2020/2018/NCL/ncl_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4640,548,"VUT","Vanuatu","ppp_2018","GIS/Population/Global_2000_2020/2018/VUT/vut_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4641,554,"NZL","New Zealand","ppp_2018","GIS/Population/Global_2000_2020/2018/NZL/nzl_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4642,558,"NIC","Nicaragua","ppp_2018","GIS/Population/Global_2000_2020/2018/NIC/nic_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4643,562,"NER","Niger","ppp_2018","GIS/Population/Global_2000_2020/2018/NER/ner_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4644,566,"NGA","Nigeria","ppp_2018","GIS/Population/Global_2000_2020/2018/NGA/nga_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4645,570,"NIU","Niue","ppp_2018","GIS/Population/Global_2000_2020/2018/NIU/niu_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4646,574,"NFK","Norfolk Island","ppp_2018","GIS/Population/Global_2000_2020/2018/NFK/nfk_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4647,578,"NOR","Norway","ppp_2018","GIS/Population/Global_2000_2020/2018/NOR/nor_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4648,580,"MNP","Northern Mariana Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/MNP/mnp_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4649,581,"UMI","United States Minor Outlying Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/UMI/umi_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4650,583,"FSM","Micronesia","ppp_2018","GIS/Population/Global_2000_2020/2018/FSM/fsm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4651,584,"MHL","Marshall Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/MHL/mhl_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4652,585,"PLW","Palau","ppp_2018","GIS/Population/Global_2000_2020/2018/PLW/plw_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4653,586,"PAK","Pakistan","ppp_2018","GIS/Population/Global_2000_2020/2018/PAK/pak_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4654,591,"PAN","Panama","ppp_2018","GIS/Population/Global_2000_2020/2018/PAN/pan_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4655,598,"PNG","Papua New Guinea","ppp_2018","GIS/Population/Global_2000_2020/2018/PNG/png_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4656,600,"PRY","Paraguay","ppp_2018","GIS/Population/Global_2000_2020/2018/PRY/pry_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4657,604,"PER","Peru","ppp_2018","GIS/Population/Global_2000_2020/2018/PER/per_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4658,608,"PHL","Philippines","ppp_2018","GIS/Population/Global_2000_2020/2018/PHL/phl_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4659,612,"PCN","Pitcairn Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/PCN/pcn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4660,616,"POL","Poland","ppp_2018","GIS/Population/Global_2000_2020/2018/POL/pol_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4661,620,"PRT","Portugal","ppp_2018","GIS/Population/Global_2000_2020/2018/PRT/prt_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4662,624,"GNB","Guinea-Bissau","ppp_2018","GIS/Population/Global_2000_2020/2018/GNB/gnb_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4663,626,"TLS","East Timor","ppp_2018","GIS/Population/Global_2000_2020/2018/TLS/tls_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4664,630,"PRI","Puerto Rico","ppp_2018","GIS/Population/Global_2000_2020/2018/PRI/pri_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4665,634,"QAT","Qatar","ppp_2018","GIS/Population/Global_2000_2020/2018/QAT/qat_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4666,638,"REU","Reunion","ppp_2018","GIS/Population/Global_2000_2020/2018/REU/reu_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4667,642,"ROU","Romania","ppp_2018","GIS/Population/Global_2000_2020/2018/ROU/rou_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4668,646,"RWA","Rwanda","ppp_2018","GIS/Population/Global_2000_2020/2018/RWA/rwa_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4669,652,"BLM","Saint Barthelemy","ppp_2018","GIS/Population/Global_2000_2020/2018/BLM/blm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4670,654,"SHN","Saint Helena","ppp_2018","GIS/Population/Global_2000_2020/2018/SHN/shn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4671,659,"KNA","Saint Kitts and Nevis","ppp_2018","GIS/Population/Global_2000_2020/2018/KNA/kna_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4672,660,"AIA","Anguilla","ppp_2018","GIS/Population/Global_2000_2020/2018/AIA/aia_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4673,662,"LCA","Saint Lucia","ppp_2018","GIS/Population/Global_2000_2020/2018/LCA/lca_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4674,663,"MAF","Saint Martin (French part)","ppp_2018","GIS/Population/Global_2000_2020/2018/MAF/maf_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4675,666,"SPM","Saint Pierre and Miquelon","ppp_2018","GIS/Population/Global_2000_2020/2018/SPM/spm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4676,670,"VCT","Saint Vincent and the Grenadines","ppp_2018","GIS/Population/Global_2000_2020/2018/VCT/vct_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4677,674,"SMR","San Marino","ppp_2018","GIS/Population/Global_2000_2020/2018/SMR/smr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4678,678,"STP","Sao Tome and Principe","ppp_2018","GIS/Population/Global_2000_2020/2018/STP/stp_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4679,682,"SAU","Saudi Arabia","ppp_2018","GIS/Population/Global_2000_2020/2018/SAU/sau_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4680,686,"SEN","Senegal","ppp_2018","GIS/Population/Global_2000_2020/2018/SEN/sen_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4681,688,"SRB","Serbia","ppp_2018","GIS/Population/Global_2000_2020/2018/SRB/srb_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4682,690,"SYC","Seychelles","ppp_2018","GIS/Population/Global_2000_2020/2018/SYC/syc_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4683,694,"SLE","Sierra Leone","ppp_2018","GIS/Population/Global_2000_2020/2018/SLE/sle_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4684,702,"SGP","Singapore","ppp_2018","GIS/Population/Global_2000_2020/2018/SGP/sgp_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4685,703,"SVK","Slovakia","ppp_2018","GIS/Population/Global_2000_2020/2018/SVK/svk_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4686,704,"VNM","Vietnam","ppp_2018","GIS/Population/Global_2000_2020/2018/VNM/vnm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4687,705,"SVN","Slovenia","ppp_2018","GIS/Population/Global_2000_2020/2018/SVN/svn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4688,706,"SOM","Somalia","ppp_2018","GIS/Population/Global_2000_2020/2018/SOM/som_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4689,710,"ZAF","South Africa","ppp_2018","GIS/Population/Global_2000_2020/2018/ZAF/zaf_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4690,716,"ZWE","Zimbabwe","ppp_2018","GIS/Population/Global_2000_2020/2018/ZWE/zwe_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4691,724,"ESP","Spain","ppp_2018","GIS/Population/Global_2000_2020/2018/ESP/esp_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4692,728,"SSD","South Sudan","ppp_2018","GIS/Population/Global_2000_2020/2018/SSD/ssd_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4693,729,"SDN","Sudan","ppp_2018","GIS/Population/Global_2000_2020/2018/SDN/sdn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4694,732,"ESH","Western Sahara","ppp_2018","GIS/Population/Global_2000_2020/2018/ESH/esh_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4695,740,"SUR","Suriname","ppp_2018","GIS/Population/Global_2000_2020/2018/SUR/sur_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4696,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/SJM/sjm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4697,748,"SWZ","Swaziland","ppp_2018","GIS/Population/Global_2000_2020/2018/SWZ/swz_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4698,752,"SWE","Sweden","ppp_2018","GIS/Population/Global_2000_2020/2018/SWE/swe_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4699,756,"CHE","Switzerland","ppp_2018","GIS/Population/Global_2000_2020/2018/CHE/che_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4700,760,"SYR","Syria","ppp_2018","GIS/Population/Global_2000_2020/2018/SYR/syr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4701,762,"TJK","Tajikistan","ppp_2018","GIS/Population/Global_2000_2020/2018/TJK/tjk_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4702,764,"THA","Thailand","ppp_2018","GIS/Population/Global_2000_2020/2018/THA/tha_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4703,768,"TGO","Togo","ppp_2018","GIS/Population/Global_2000_2020/2018/TGO/tgo_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4704,772,"TKL","Tokelau","ppp_2018","GIS/Population/Global_2000_2020/2018/TKL/tkl_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4705,776,"TON","Tonga","ppp_2018","GIS/Population/Global_2000_2020/2018/TON/ton_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4706,780,"TTO","Trinidad and Tobago","ppp_2018","GIS/Population/Global_2000_2020/2018/TTO/tto_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4707,784,"ARE","United Arab Emirates","ppp_2018","GIS/Population/Global_2000_2020/2018/ARE/are_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4708,788,"TUN","Tunisia","ppp_2018","GIS/Population/Global_2000_2020/2018/TUN/tun_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4709,792,"TUR","Turkey","ppp_2018","GIS/Population/Global_2000_2020/2018/TUR/tur_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4710,795,"TKM","Turkmenistan","ppp_2018","GIS/Population/Global_2000_2020/2018/TKM/tkm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4711,796,"TCA","Turks and Caicos Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/TCA/tca_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4712,798,"TUV","Tuvalu","ppp_2018","GIS/Population/Global_2000_2020/2018/TUV/tuv_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4713,800,"UGA","Uganda","ppp_2018","GIS/Population/Global_2000_2020/2018/UGA/uga_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4714,804,"UKR","Ukraine","ppp_2018","GIS/Population/Global_2000_2020/2018/UKR/ukr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4715,807,"MKD","Macedonia","ppp_2018","GIS/Population/Global_2000_2020/2018/MKD/mkd_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4716,818,"EGY","Egypt","ppp_2018","GIS/Population/Global_2000_2020/2018/EGY/egy_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4717,826,"GBR","United Kingdom","ppp_2018","GIS/Population/Global_2000_2020/2018/GBR/gbr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4718,831,"GGY","Guernsey","ppp_2018","GIS/Population/Global_2000_2020/2018/GGY/ggy_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4719,832,"JEY","Jersey","ppp_2018","GIS/Population/Global_2000_2020/2018/JEY/jey_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4720,833,"IMN","Isle of Man","ppp_2018","GIS/Population/Global_2000_2020/2018/IMN/imn_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4721,834,"TZA","Tanzania","ppp_2018","GIS/Population/Global_2000_2020/2018/TZA/tza_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4722,854,"BFA","Burkina Faso","ppp_2018","GIS/Population/Global_2000_2020/2018/BFA/bfa_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4723,858,"URY","Uruguay","ppp_2018","GIS/Population/Global_2000_2020/2018/URY/ury_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4724,860,"UZB","Uzbekistan","ppp_2018","GIS/Population/Global_2000_2020/2018/UZB/uzb_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4725,862,"VEN","Venezuela","ppp_2018","GIS/Population/Global_2000_2020/2018/VEN/ven_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4726,876,"WLF","Wallis and Futuna","ppp_2018","GIS/Population/Global_2000_2020/2018/WLF/wlf_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4727,882,"WSM","Samoa","ppp_2018","GIS/Population/Global_2000_2020/2018/WSM/wsm_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4728,887,"YEM","Yemen","ppp_2018","GIS/Population/Global_2000_2020/2018/YEM/yem_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4729,894,"ZMB","Zambia","ppp_2018","GIS/Population/Global_2000_2020/2018/ZMB/zmb_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4730,900,"KOS","Kosovo","ppp_2018","GIS/Population/Global_2000_2020/2018/KOS/kos_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4731,901,"SPR","Spratly Islands","ppp_2018","GIS/Population/Global_2000_2020/2018/SPR/spr_ppp_2018.tif","Estimated total number of people per grid-cell 2018 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4732,643,"RUS","Russia","ppp_2019","GIS/Population/Global_2000_2020/2019/RUS/rus_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4733,360,"IDN","Indonesia","ppp_2019","GIS/Population/Global_2000_2020/2019/IDN/idn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4734,840,"USA","United States","ppp_2019","GIS/Population/Global_2000_2020/2019/USA/usa_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4735,850,"VIR","Virgin_Islands_U_S","ppp_2019","GIS/Population/Global_2000_2020/2019/VIR/vir_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4736,304,"GRL","Greenland","ppp_2019","GIS/Population/Global_2000_2020/2019/GRL/grl_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4737,156,"CHN","China","ppp_2019","GIS/Population/Global_2000_2020/2019/CHN/chn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4738,36,"AUS","Australia","ppp_2019","GIS/Population/Global_2000_2020/2019/AUS/aus_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4739,76,"BRA","Brazil","ppp_2019","GIS/Population/Global_2000_2020/2019/BRA/bra_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4740,124,"CAN","Canada","ppp_2019","GIS/Population/Global_2000_2020/2019/CAN/can_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4741,152,"CHL","Chile","ppp_2019","GIS/Population/Global_2000_2020/2019/CHL/chl_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4742,4,"AFG","Afghanistan","ppp_2019","GIS/Population/Global_2000_2020/2019/AFG/afg_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4743,8,"ALB","Albania","ppp_2019","GIS/Population/Global_2000_2020/2019/ALB/alb_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4744,10,"ATA","Antarctica","ppp_2019","GIS/Population/Global_2000_2020/2019/ATA/ata_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4745,12,"DZA","Algeria","ppp_2019","GIS/Population/Global_2000_2020/2019/DZA/dza_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4746,16,"ASM","American Samoa","ppp_2019","GIS/Population/Global_2000_2020/2019/ASM/asm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4747,20,"AND","Andorra","ppp_2019","GIS/Population/Global_2000_2020/2019/AND/and_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4748,24,"AGO","Angola","ppp_2019","GIS/Population/Global_2000_2020/2019/AGO/ago_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4749,28,"ATG","Antigua and Barbuda","ppp_2019","GIS/Population/Global_2000_2020/2019/ATG/atg_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4750,31,"AZE","Azerbaijan","ppp_2019","GIS/Population/Global_2000_2020/2019/AZE/aze_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4751,32,"ARG","Argentina","ppp_2019","GIS/Population/Global_2000_2020/2019/ARG/arg_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4752,40,"AUT","Austria","ppp_2019","GIS/Population/Global_2000_2020/2019/AUT/aut_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4753,44,"BHS","Bahamas","ppp_2019","GIS/Population/Global_2000_2020/2019/BHS/bhs_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4754,48,"BHR","Bahrain","ppp_2019","GIS/Population/Global_2000_2020/2019/BHR/bhr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4755,50,"BGD","Bangladesh","ppp_2019","GIS/Population/Global_2000_2020/2019/BGD/bgd_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4756,51,"ARM","Armenia","ppp_2019","GIS/Population/Global_2000_2020/2019/ARM/arm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4757,52,"BRB","Barbados","ppp_2019","GIS/Population/Global_2000_2020/2019/BRB/brb_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4758,56,"BEL","Belgium","ppp_2019","GIS/Population/Global_2000_2020/2019/BEL/bel_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4759,60,"BMU","Bermuda","ppp_2019","GIS/Population/Global_2000_2020/2019/BMU/bmu_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4760,64,"BTN","Bhutan","ppp_2019","GIS/Population/Global_2000_2020/2019/BTN/btn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4761,68,"BOL","Bolivia","ppp_2019","GIS/Population/Global_2000_2020/2019/BOL/bol_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4762,70,"BIH","Bosnia and Herzegovina","ppp_2019","GIS/Population/Global_2000_2020/2019/BIH/bih_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4763,72,"BWA","Botswana","ppp_2019","GIS/Population/Global_2000_2020/2019/BWA/bwa_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4764,74,"BVT","Bouvet Island","ppp_2019","GIS/Population/Global_2000_2020/2019/BVT/bvt_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4765,84,"BLZ","Belize","ppp_2019","GIS/Population/Global_2000_2020/2019/BLZ/blz_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4766,86,"IOT","British Indian Ocean Territory","ppp_2019","GIS/Population/Global_2000_2020/2019/IOT/iot_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4767,90,"SLB","Solomon Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/SLB/slb_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4768,92,"VGB","British Virgin Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/VGB/vgb_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4769,96,"BRN","Brunei","ppp_2019","GIS/Population/Global_2000_2020/2019/BRN/brn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4770,100,"BGR","Bulgaria","ppp_2019","GIS/Population/Global_2000_2020/2019/BGR/bgr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4771,104,"MMR","Myanmar","ppp_2019","GIS/Population/Global_2000_2020/2019/MMR/mmr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4772,108,"BDI","Burundi","ppp_2019","GIS/Population/Global_2000_2020/2019/BDI/bdi_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4773,112,"BLR","Belarus","ppp_2019","GIS/Population/Global_2000_2020/2019/BLR/blr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4774,116,"KHM","Cambodia","ppp_2019","GIS/Population/Global_2000_2020/2019/KHM/khm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4775,120,"CMR","Cameroon","ppp_2019","GIS/Population/Global_2000_2020/2019/CMR/cmr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4776,132,"CPV","Cape Verde","ppp_2019","GIS/Population/Global_2000_2020/2019/CPV/cpv_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4777,136,"CYM","Cayman Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/CYM/cym_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4778,140,"CAF","Central African Republic","ppp_2019","GIS/Population/Global_2000_2020/2019/CAF/caf_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4779,144,"LKA","Sri Lanka","ppp_2019","GIS/Population/Global_2000_2020/2019/LKA/lka_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4780,148,"TCD","Chad","ppp_2019","GIS/Population/Global_2000_2020/2019/TCD/tcd_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4781,158,"TWN","Taiwan","ppp_2019","GIS/Population/Global_2000_2020/2019/TWN/twn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4782,170,"COL","Colombia","ppp_2019","GIS/Population/Global_2000_2020/2019/COL/col_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4783,174,"COM","Comoros","ppp_2019","GIS/Population/Global_2000_2020/2019/COM/com_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4784,175,"MYT","Mayotte","ppp_2019","GIS/Population/Global_2000_2020/2019/MYT/myt_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4785,178,"COG","Republic of Congo","ppp_2019","GIS/Population/Global_2000_2020/2019/COG/cog_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4786,180,"COD","Democratic Republic of the Congo","ppp_2019","GIS/Population/Global_2000_2020/2019/COD/cod_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4787,184,"COK","Cook Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/COK/cok_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4788,188,"CRI","Costa Rica","ppp_2019","GIS/Population/Global_2000_2020/2019/CRI/cri_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4789,191,"HRV","Croatia","ppp_2019","GIS/Population/Global_2000_2020/2019/HRV/hrv_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4790,192,"CUB","Cuba","ppp_2019","GIS/Population/Global_2000_2020/2019/CUB/cub_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4791,196,"CYP","Cyprus","ppp_2019","GIS/Population/Global_2000_2020/2019/CYP/cyp_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4792,203,"CZE","Czech Republic","ppp_2019","GIS/Population/Global_2000_2020/2019/CZE/cze_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4793,204,"BEN","Benin","ppp_2019","GIS/Population/Global_2000_2020/2019/BEN/ben_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4794,208,"DNK","Denmark","ppp_2019","GIS/Population/Global_2000_2020/2019/DNK/dnk_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4795,212,"DMA","Dominica","ppp_2019","GIS/Population/Global_2000_2020/2019/DMA/dma_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4796,214,"DOM","Dominican Republic","ppp_2019","GIS/Population/Global_2000_2020/2019/DOM/dom_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4797,218,"ECU","Ecuador","ppp_2019","GIS/Population/Global_2000_2020/2019/ECU/ecu_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4798,222,"SLV","El Salvador","ppp_2019","GIS/Population/Global_2000_2020/2019/SLV/slv_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4799,226,"GNQ","Equatorial Guinea","ppp_2019","GIS/Population/Global_2000_2020/2019/GNQ/gnq_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4800,231,"ETH","Ethiopia","ppp_2019","GIS/Population/Global_2000_2020/2019/ETH/eth_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4801,232,"ERI","Eritrea","ppp_2019","GIS/Population/Global_2000_2020/2019/ERI/eri_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4802,233,"EST","Estonia","ppp_2019","GIS/Population/Global_2000_2020/2019/EST/est_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4803,234,"FRO","Faroe Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/FRO/fro_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4804,238,"FLK","Falkland Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/FLK/flk_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4805,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/SGS/sgs_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4806,242,"FJI","Fiji","ppp_2019","GIS/Population/Global_2000_2020/2019/FJI/fji_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4807,246,"FIN","Finland","ppp_2019","GIS/Population/Global_2000_2020/2019/FIN/fin_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4808,248,"ALA","Aland Islands ","ppp_2019","GIS/Population/Global_2000_2020/2019/ALA/ala_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4809,250,"FRA","France","ppp_2019","GIS/Population/Global_2000_2020/2019/FRA/fra_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4810,254,"GUF","French Guiana","ppp_2019","GIS/Population/Global_2000_2020/2019/GUF/guf_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4811,258,"PYF","French Polynesia","ppp_2019","GIS/Population/Global_2000_2020/2019/PYF/pyf_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4812,260,"ATF","French Southern Territories","ppp_2019","GIS/Population/Global_2000_2020/2019/ATF/atf_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4813,262,"DJI","Djibouti","ppp_2019","GIS/Population/Global_2000_2020/2019/DJI/dji_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4814,266,"GAB","Gabon","ppp_2019","GIS/Population/Global_2000_2020/2019/GAB/gab_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4815,268,"GEO","Georgia","ppp_2019","GIS/Population/Global_2000_2020/2019/GEO/geo_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4816,270,"GMB","Gambia","ppp_2019","GIS/Population/Global_2000_2020/2019/GMB/gmb_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4817,275,"PSE","Palestina","ppp_2019","GIS/Population/Global_2000_2020/2019/PSE/pse_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4818,276,"DEU","Germany","ppp_2019","GIS/Population/Global_2000_2020/2019/DEU/deu_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4819,288,"GHA","Ghana","ppp_2019","GIS/Population/Global_2000_2020/2019/GHA/gha_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4820,292,"GIB","Gibraltar","ppp_2019","GIS/Population/Global_2000_2020/2019/GIB/gib_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4821,296,"KIR","Kiribati","ppp_2019","GIS/Population/Global_2000_2020/2019/KIR/kir_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4822,300,"GRC","Greece","ppp_2019","GIS/Population/Global_2000_2020/2019/GRC/grc_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4823,308,"GRD","Grenada","ppp_2019","GIS/Population/Global_2000_2020/2019/GRD/grd_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4824,312,"GLP","Guadeloupe","ppp_2019","GIS/Population/Global_2000_2020/2019/GLP/glp_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4825,316,"GUM","Guam","ppp_2019","GIS/Population/Global_2000_2020/2019/GUM/gum_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4826,320,"GTM","Guatemala","ppp_2019","GIS/Population/Global_2000_2020/2019/GTM/gtm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4827,324,"GIN","Guinea","ppp_2019","GIS/Population/Global_2000_2020/2019/GIN/gin_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4828,328,"GUY","Guyana","ppp_2019","GIS/Population/Global_2000_2020/2019/GUY/guy_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4829,332,"HTI","Haiti","ppp_2019","GIS/Population/Global_2000_2020/2019/HTI/hti_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4830,334,"HMD","Heard Island and McDonald Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/HMD/hmd_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4831,336,"VAT","Vatican City","ppp_2019","GIS/Population/Global_2000_2020/2019/VAT/vat_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4832,340,"HND","Honduras","ppp_2019","GIS/Population/Global_2000_2020/2019/HND/hnd_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4833,344,"HKG","Hong Kong","ppp_2019","GIS/Population/Global_2000_2020/2019/HKG/hkg_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4834,348,"HUN","Hungary","ppp_2019","GIS/Population/Global_2000_2020/2019/HUN/hun_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4835,352,"ISL","Iceland","ppp_2019","GIS/Population/Global_2000_2020/2019/ISL/isl_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4836,356,"IND","India","ppp_2019","GIS/Population/Global_2000_2020/2019/IND/ind_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4837,364,"IRN","Iran","ppp_2019","GIS/Population/Global_2000_2020/2019/IRN/irn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4838,368,"IRQ","Iraq","ppp_2019","GIS/Population/Global_2000_2020/2019/IRQ/irq_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4839,372,"IRL","Ireland","ppp_2019","GIS/Population/Global_2000_2020/2019/IRL/irl_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4840,376,"ISR","Israel","ppp_2019","GIS/Population/Global_2000_2020/2019/ISR/isr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4841,380,"ITA","Italy","ppp_2019","GIS/Population/Global_2000_2020/2019/ITA/ita_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4842,384,"CIV","CIte dIvoire","ppp_2019","GIS/Population/Global_2000_2020/2019/CIV/civ_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4843,388,"JAM","Jamaica","ppp_2019","GIS/Population/Global_2000_2020/2019/JAM/jam_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4844,392,"JPN","Japan","ppp_2019","GIS/Population/Global_2000_2020/2019/JPN/jpn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4845,398,"KAZ","Kazakhstan","ppp_2019","GIS/Population/Global_2000_2020/2019/KAZ/kaz_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4846,400,"JOR","Jordan","ppp_2019","GIS/Population/Global_2000_2020/2019/JOR/jor_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4847,404,"KEN","Kenya","ppp_2019","GIS/Population/Global_2000_2020/2019/KEN/ken_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4848,408,"PRK","North Korea","ppp_2019","GIS/Population/Global_2000_2020/2019/PRK/prk_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4849,410,"KOR","South Korea","ppp_2019","GIS/Population/Global_2000_2020/2019/KOR/kor_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4850,414,"KWT","Kuwait","ppp_2019","GIS/Population/Global_2000_2020/2019/KWT/kwt_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4851,417,"KGZ","Kyrgyzstan","ppp_2019","GIS/Population/Global_2000_2020/2019/KGZ/kgz_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4852,418,"LAO","Laos","ppp_2019","GIS/Population/Global_2000_2020/2019/LAO/lao_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4853,422,"LBN","Lebanon","ppp_2019","GIS/Population/Global_2000_2020/2019/LBN/lbn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4854,426,"LSO","Lesotho","ppp_2019","GIS/Population/Global_2000_2020/2019/LSO/lso_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4855,428,"LVA","Latvia","ppp_2019","GIS/Population/Global_2000_2020/2019/LVA/lva_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4856,430,"LBR","Liberia","ppp_2019","GIS/Population/Global_2000_2020/2019/LBR/lbr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4857,434,"LBY","Libya","ppp_2019","GIS/Population/Global_2000_2020/2019/LBY/lby_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4858,438,"LIE","Liechtenstein","ppp_2019","GIS/Population/Global_2000_2020/2019/LIE/lie_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4859,440,"LTU","Lithuania","ppp_2019","GIS/Population/Global_2000_2020/2019/LTU/ltu_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4860,442,"LUX","Luxembourg","ppp_2019","GIS/Population/Global_2000_2020/2019/LUX/lux_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4861,446,"MAC","Macao","ppp_2019","GIS/Population/Global_2000_2020/2019/MAC/mac_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4862,450,"MDG","Madagascar","ppp_2019","GIS/Population/Global_2000_2020/2019/MDG/mdg_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4863,454,"MWI","Malawi","ppp_2019","GIS/Population/Global_2000_2020/2019/MWI/mwi_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4864,458,"MYS","Malaysia","ppp_2019","GIS/Population/Global_2000_2020/2019/MYS/mys_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4865,462,"MDV","Maldives","ppp_2019","GIS/Population/Global_2000_2020/2019/MDV/mdv_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4866,466,"MLI","Mali","ppp_2019","GIS/Population/Global_2000_2020/2019/MLI/mli_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4867,470,"MLT","Malta","ppp_2019","GIS/Population/Global_2000_2020/2019/MLT/mlt_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4868,474,"MTQ","Martinique","ppp_2019","GIS/Population/Global_2000_2020/2019/MTQ/mtq_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4869,478,"MRT","Mauritania","ppp_2019","GIS/Population/Global_2000_2020/2019/MRT/mrt_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4870,480,"MUS","Mauritius","ppp_2019","GIS/Population/Global_2000_2020/2019/MUS/mus_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4871,484,"MEX","Mexico","ppp_2019","GIS/Population/Global_2000_2020/2019/MEX/mex_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4872,492,"MCO","Monaco","ppp_2019","GIS/Population/Global_2000_2020/2019/MCO/mco_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4873,496,"MNG","Mongolia","ppp_2019","GIS/Population/Global_2000_2020/2019/MNG/mng_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4874,498,"MDA","Moldova","ppp_2019","GIS/Population/Global_2000_2020/2019/MDA/mda_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4875,499,"MNE","Montenegro","ppp_2019","GIS/Population/Global_2000_2020/2019/MNE/mne_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4876,500,"MSR","Montserrat","ppp_2019","GIS/Population/Global_2000_2020/2019/MSR/msr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4877,504,"MAR","Morocco","ppp_2019","GIS/Population/Global_2000_2020/2019/MAR/mar_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4878,508,"MOZ","Mozambique","ppp_2019","GIS/Population/Global_2000_2020/2019/MOZ/moz_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4879,512,"OMN","Oman","ppp_2019","GIS/Population/Global_2000_2020/2019/OMN/omn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4880,516,"NAM","Namibia","ppp_2019","GIS/Population/Global_2000_2020/2019/NAM/nam_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4881,520,"NRU","Nauru","ppp_2019","GIS/Population/Global_2000_2020/2019/NRU/nru_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4882,524,"NPL","Nepal","ppp_2019","GIS/Population/Global_2000_2020/2019/NPL/npl_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4883,528,"NLD","Netherlands","ppp_2019","GIS/Population/Global_2000_2020/2019/NLD/nld_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4884,531,"CUW","Curacao","ppp_2019","GIS/Population/Global_2000_2020/2019/CUW/cuw_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4885,533,"ABW","Aruba","ppp_2019","GIS/Population/Global_2000_2020/2019/ABW/abw_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4886,534,"SXM","Sint Maarten (Dutch part)","ppp_2019","GIS/Population/Global_2000_2020/2019/SXM/sxm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4887,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2019","GIS/Population/Global_2000_2020/2019/BES/bes_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4888,540,"NCL","New Caledonia","ppp_2019","GIS/Population/Global_2000_2020/2019/NCL/ncl_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4889,548,"VUT","Vanuatu","ppp_2019","GIS/Population/Global_2000_2020/2019/VUT/vut_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4890,554,"NZL","New Zealand","ppp_2019","GIS/Population/Global_2000_2020/2019/NZL/nzl_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4891,558,"NIC","Nicaragua","ppp_2019","GIS/Population/Global_2000_2020/2019/NIC/nic_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4892,562,"NER","Niger","ppp_2019","GIS/Population/Global_2000_2020/2019/NER/ner_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4893,566,"NGA","Nigeria","ppp_2019","GIS/Population/Global_2000_2020/2019/NGA/nga_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4894,570,"NIU","Niue","ppp_2019","GIS/Population/Global_2000_2020/2019/NIU/niu_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4895,574,"NFK","Norfolk Island","ppp_2019","GIS/Population/Global_2000_2020/2019/NFK/nfk_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4896,578,"NOR","Norway","ppp_2019","GIS/Population/Global_2000_2020/2019/NOR/nor_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4897,580,"MNP","Northern Mariana Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/MNP/mnp_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4898,581,"UMI","United States Minor Outlying Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/UMI/umi_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4899,583,"FSM","Micronesia","ppp_2019","GIS/Population/Global_2000_2020/2019/FSM/fsm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4900,584,"MHL","Marshall Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/MHL/mhl_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4901,585,"PLW","Palau","ppp_2019","GIS/Population/Global_2000_2020/2019/PLW/plw_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4902,586,"PAK","Pakistan","ppp_2019","GIS/Population/Global_2000_2020/2019/PAK/pak_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4903,591,"PAN","Panama","ppp_2019","GIS/Population/Global_2000_2020/2019/PAN/pan_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4904,598,"PNG","Papua New Guinea","ppp_2019","GIS/Population/Global_2000_2020/2019/PNG/png_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4905,600,"PRY","Paraguay","ppp_2019","GIS/Population/Global_2000_2020/2019/PRY/pry_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4906,604,"PER","Peru","ppp_2019","GIS/Population/Global_2000_2020/2019/PER/per_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4907,608,"PHL","Philippines","ppp_2019","GIS/Population/Global_2000_2020/2019/PHL/phl_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4908,612,"PCN","Pitcairn Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/PCN/pcn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4909,616,"POL","Poland","ppp_2019","GIS/Population/Global_2000_2020/2019/POL/pol_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4910,620,"PRT","Portugal","ppp_2019","GIS/Population/Global_2000_2020/2019/PRT/prt_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4911,624,"GNB","Guinea-Bissau","ppp_2019","GIS/Population/Global_2000_2020/2019/GNB/gnb_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4912,626,"TLS","East Timor","ppp_2019","GIS/Population/Global_2000_2020/2019/TLS/tls_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4913,630,"PRI","Puerto Rico","ppp_2019","GIS/Population/Global_2000_2020/2019/PRI/pri_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4914,634,"QAT","Qatar","ppp_2019","GIS/Population/Global_2000_2020/2019/QAT/qat_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4915,638,"REU","Reunion","ppp_2019","GIS/Population/Global_2000_2020/2019/REU/reu_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4916,642,"ROU","Romania","ppp_2019","GIS/Population/Global_2000_2020/2019/ROU/rou_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4917,646,"RWA","Rwanda","ppp_2019","GIS/Population/Global_2000_2020/2019/RWA/rwa_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4918,652,"BLM","Saint Barthelemy","ppp_2019","GIS/Population/Global_2000_2020/2019/BLM/blm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4919,654,"SHN","Saint Helena","ppp_2019","GIS/Population/Global_2000_2020/2019/SHN/shn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4920,659,"KNA","Saint Kitts and Nevis","ppp_2019","GIS/Population/Global_2000_2020/2019/KNA/kna_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4921,660,"AIA","Anguilla","ppp_2019","GIS/Population/Global_2000_2020/2019/AIA/aia_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4922,662,"LCA","Saint Lucia","ppp_2019","GIS/Population/Global_2000_2020/2019/LCA/lca_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4923,663,"MAF","Saint Martin (French part)","ppp_2019","GIS/Population/Global_2000_2020/2019/MAF/maf_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4924,666,"SPM","Saint Pierre and Miquelon","ppp_2019","GIS/Population/Global_2000_2020/2019/SPM/spm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4925,670,"VCT","Saint Vincent and the Grenadines","ppp_2019","GIS/Population/Global_2000_2020/2019/VCT/vct_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4926,674,"SMR","San Marino","ppp_2019","GIS/Population/Global_2000_2020/2019/SMR/smr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4927,678,"STP","Sao Tome and Principe","ppp_2019","GIS/Population/Global_2000_2020/2019/STP/stp_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4928,682,"SAU","Saudi Arabia","ppp_2019","GIS/Population/Global_2000_2020/2019/SAU/sau_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4929,686,"SEN","Senegal","ppp_2019","GIS/Population/Global_2000_2020/2019/SEN/sen_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4930,688,"SRB","Serbia","ppp_2019","GIS/Population/Global_2000_2020/2019/SRB/srb_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4931,690,"SYC","Seychelles","ppp_2019","GIS/Population/Global_2000_2020/2019/SYC/syc_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4932,694,"SLE","Sierra Leone","ppp_2019","GIS/Population/Global_2000_2020/2019/SLE/sle_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4933,702,"SGP","Singapore","ppp_2019","GIS/Population/Global_2000_2020/2019/SGP/sgp_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4934,703,"SVK","Slovakia","ppp_2019","GIS/Population/Global_2000_2020/2019/SVK/svk_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4935,704,"VNM","Vietnam","ppp_2019","GIS/Population/Global_2000_2020/2019/VNM/vnm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4936,705,"SVN","Slovenia","ppp_2019","GIS/Population/Global_2000_2020/2019/SVN/svn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4937,706,"SOM","Somalia","ppp_2019","GIS/Population/Global_2000_2020/2019/SOM/som_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4938,710,"ZAF","South Africa","ppp_2019","GIS/Population/Global_2000_2020/2019/ZAF/zaf_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4939,716,"ZWE","Zimbabwe","ppp_2019","GIS/Population/Global_2000_2020/2019/ZWE/zwe_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4940,724,"ESP","Spain","ppp_2019","GIS/Population/Global_2000_2020/2019/ESP/esp_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4941,728,"SSD","South Sudan","ppp_2019","GIS/Population/Global_2000_2020/2019/SSD/ssd_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4942,729,"SDN","Sudan","ppp_2019","GIS/Population/Global_2000_2020/2019/SDN/sdn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4943,732,"ESH","Western Sahara","ppp_2019","GIS/Population/Global_2000_2020/2019/ESH/esh_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4944,740,"SUR","Suriname","ppp_2019","GIS/Population/Global_2000_2020/2019/SUR/sur_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4945,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/SJM/sjm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4946,748,"SWZ","Swaziland","ppp_2019","GIS/Population/Global_2000_2020/2019/SWZ/swz_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4947,752,"SWE","Sweden","ppp_2019","GIS/Population/Global_2000_2020/2019/SWE/swe_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4948,756,"CHE","Switzerland","ppp_2019","GIS/Population/Global_2000_2020/2019/CHE/che_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4949,760,"SYR","Syria","ppp_2019","GIS/Population/Global_2000_2020/2019/SYR/syr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4950,762,"TJK","Tajikistan","ppp_2019","GIS/Population/Global_2000_2020/2019/TJK/tjk_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4951,764,"THA","Thailand","ppp_2019","GIS/Population/Global_2000_2020/2019/THA/tha_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4952,768,"TGO","Togo","ppp_2019","GIS/Population/Global_2000_2020/2019/TGO/tgo_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4953,772,"TKL","Tokelau","ppp_2019","GIS/Population/Global_2000_2020/2019/TKL/tkl_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4954,776,"TON","Tonga","ppp_2019","GIS/Population/Global_2000_2020/2019/TON/ton_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4955,780,"TTO","Trinidad and Tobago","ppp_2019","GIS/Population/Global_2000_2020/2019/TTO/tto_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4956,784,"ARE","United Arab Emirates","ppp_2019","GIS/Population/Global_2000_2020/2019/ARE/are_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4957,788,"TUN","Tunisia","ppp_2019","GIS/Population/Global_2000_2020/2019/TUN/tun_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4958,792,"TUR","Turkey","ppp_2019","GIS/Population/Global_2000_2020/2019/TUR/tur_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4959,795,"TKM","Turkmenistan","ppp_2019","GIS/Population/Global_2000_2020/2019/TKM/tkm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4960,796,"TCA","Turks and Caicos Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/TCA/tca_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4961,798,"TUV","Tuvalu","ppp_2019","GIS/Population/Global_2000_2020/2019/TUV/tuv_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4962,800,"UGA","Uganda","ppp_2019","GIS/Population/Global_2000_2020/2019/UGA/uga_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4963,804,"UKR","Ukraine","ppp_2019","GIS/Population/Global_2000_2020/2019/UKR/ukr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4964,807,"MKD","Macedonia","ppp_2019","GIS/Population/Global_2000_2020/2019/MKD/mkd_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4965,818,"EGY","Egypt","ppp_2019","GIS/Population/Global_2000_2020/2019/EGY/egy_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4966,826,"GBR","United Kingdom","ppp_2019","GIS/Population/Global_2000_2020/2019/GBR/gbr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4967,831,"GGY","Guernsey","ppp_2019","GIS/Population/Global_2000_2020/2019/GGY/ggy_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4968,832,"JEY","Jersey","ppp_2019","GIS/Population/Global_2000_2020/2019/JEY/jey_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4969,833,"IMN","Isle of Man","ppp_2019","GIS/Population/Global_2000_2020/2019/IMN/imn_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4970,834,"TZA","Tanzania","ppp_2019","GIS/Population/Global_2000_2020/2019/TZA/tza_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4971,854,"BFA","Burkina Faso","ppp_2019","GIS/Population/Global_2000_2020/2019/BFA/bfa_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4972,858,"URY","Uruguay","ppp_2019","GIS/Population/Global_2000_2020/2019/URY/ury_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4973,860,"UZB","Uzbekistan","ppp_2019","GIS/Population/Global_2000_2020/2019/UZB/uzb_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4974,862,"VEN","Venezuela","ppp_2019","GIS/Population/Global_2000_2020/2019/VEN/ven_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4975,876,"WLF","Wallis and Futuna","ppp_2019","GIS/Population/Global_2000_2020/2019/WLF/wlf_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4976,882,"WSM","Samoa","ppp_2019","GIS/Population/Global_2000_2020/2019/WSM/wsm_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4977,887,"YEM","Yemen","ppp_2019","GIS/Population/Global_2000_2020/2019/YEM/yem_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4978,894,"ZMB","Zambia","ppp_2019","GIS/Population/Global_2000_2020/2019/ZMB/zmb_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4979,900,"KOS","Kosovo","ppp_2019","GIS/Population/Global_2000_2020/2019/KOS/kos_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4980,901,"SPR","Spratly Islands","ppp_2019","GIS/Population/Global_2000_2020/2019/SPR/spr_ppp_2019.tif","Estimated total number of people per grid-cell 2019 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4981,643,"RUS","Russia","ppp_2020","GIS/Population/Global_2000_2020/2020/RUS/rus_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4982,360,"IDN","Indonesia","ppp_2020","GIS/Population/Global_2000_2020/2020/IDN/idn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4983,840,"USA","United States","ppp_2020","GIS/Population/Global_2000_2020/2020/USA/usa_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4984,850,"VIR","Virgin_Islands_U_S","ppp_2020","GIS/Population/Global_2000_2020/2020/VIR/vir_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4985,304,"GRL","Greenland","ppp_2020","GIS/Population/Global_2000_2020/2020/GRL/grl_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4986,156,"CHN","China","ppp_2020","GIS/Population/Global_2000_2020/2020/CHN/chn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4987,36,"AUS","Australia","ppp_2020","GIS/Population/Global_2000_2020/2020/AUS/aus_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4988,76,"BRA","Brazil","ppp_2020","GIS/Population/Global_2000_2020/2020/BRA/bra_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4989,124,"CAN","Canada","ppp_2020","GIS/Population/Global_2000_2020/2020/CAN/can_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4990,152,"CHL","Chile","ppp_2020","GIS/Population/Global_2000_2020/2020/CHL/chl_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4991,4,"AFG","Afghanistan","ppp_2020","GIS/Population/Global_2000_2020/2020/AFG/afg_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4992,8,"ALB","Albania","ppp_2020","GIS/Population/Global_2000_2020/2020/ALB/alb_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4993,10,"ATA","Antarctica","ppp_2020","GIS/Population/Global_2000_2020/2020/ATA/ata_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4994,12,"DZA","Algeria","ppp_2020","GIS/Population/Global_2000_2020/2020/DZA/dza_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4995,16,"ASM","American Samoa","ppp_2020","GIS/Population/Global_2000_2020/2020/ASM/asm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4996,20,"AND","Andorra","ppp_2020","GIS/Population/Global_2000_2020/2020/AND/and_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4997,24,"AGO","Angola","ppp_2020","GIS/Population/Global_2000_2020/2020/AGO/ago_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4998,28,"ATG","Antigua and Barbuda","ppp_2020","GIS/Population/Global_2000_2020/2020/ATG/atg_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
4999,31,"AZE","Azerbaijan","ppp_2020","GIS/Population/Global_2000_2020/2020/AZE/aze_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5000,32,"ARG","Argentina","ppp_2020","GIS/Population/Global_2000_2020/2020/ARG/arg_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5001,40,"AUT","Austria","ppp_2020","GIS/Population/Global_2000_2020/2020/AUT/aut_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5002,44,"BHS","Bahamas","ppp_2020","GIS/Population/Global_2000_2020/2020/BHS/bhs_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5003,48,"BHR","Bahrain","ppp_2020","GIS/Population/Global_2000_2020/2020/BHR/bhr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5004,50,"BGD","Bangladesh","ppp_2020","GIS/Population/Global_2000_2020/2020/BGD/bgd_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5005,51,"ARM","Armenia","ppp_2020","GIS/Population/Global_2000_2020/2020/ARM/arm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5006,52,"BRB","Barbados","ppp_2020","GIS/Population/Global_2000_2020/2020/BRB/brb_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5007,56,"BEL","Belgium","ppp_2020","GIS/Population/Global_2000_2020/2020/BEL/bel_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5008,60,"BMU","Bermuda","ppp_2020","GIS/Population/Global_2000_2020/2020/BMU/bmu_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5009,64,"BTN","Bhutan","ppp_2020","GIS/Population/Global_2000_2020/2020/BTN/btn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5010,68,"BOL","Bolivia","ppp_2020","GIS/Population/Global_2000_2020/2020/BOL/bol_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5011,70,"BIH","Bosnia and Herzegovina","ppp_2020","GIS/Population/Global_2000_2020/2020/BIH/bih_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5012,72,"BWA","Botswana","ppp_2020","GIS/Population/Global_2000_2020/2020/BWA/bwa_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5013,74,"BVT","Bouvet Island","ppp_2020","GIS/Population/Global_2000_2020/2020/BVT/bvt_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5014,84,"BLZ","Belize","ppp_2020","GIS/Population/Global_2000_2020/2020/BLZ/blz_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5015,86,"IOT","British Indian Ocean Territory","ppp_2020","GIS/Population/Global_2000_2020/2020/IOT/iot_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5016,90,"SLB","Solomon Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/SLB/slb_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5017,92,"VGB","British Virgin Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/VGB/vgb_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5018,96,"BRN","Brunei","ppp_2020","GIS/Population/Global_2000_2020/2020/BRN/brn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5019,100,"BGR","Bulgaria","ppp_2020","GIS/Population/Global_2000_2020/2020/BGR/bgr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5020,104,"MMR","Myanmar","ppp_2020","GIS/Population/Global_2000_2020/2020/MMR/mmr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5021,108,"BDI","Burundi","ppp_2020","GIS/Population/Global_2000_2020/2020/BDI/bdi_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5022,112,"BLR","Belarus","ppp_2020","GIS/Population/Global_2000_2020/2020/BLR/blr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5023,116,"KHM","Cambodia","ppp_2020","GIS/Population/Global_2000_2020/2020/KHM/khm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5024,120,"CMR","Cameroon","ppp_2020","GIS/Population/Global_2000_2020/2020/CMR/cmr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5025,132,"CPV","Cape Verde","ppp_2020","GIS/Population/Global_2000_2020/2020/CPV/cpv_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5026,136,"CYM","Cayman Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/CYM/cym_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5027,140,"CAF","Central African Republic","ppp_2020","GIS/Population/Global_2000_2020/2020/CAF/caf_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5028,144,"LKA","Sri Lanka","ppp_2020","GIS/Population/Global_2000_2020/2020/LKA/lka_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5029,148,"TCD","Chad","ppp_2020","GIS/Population/Global_2000_2020/2020/TCD/tcd_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5030,158,"TWN","Taiwan","ppp_2020","GIS/Population/Global_2000_2020/2020/TWN/twn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5031,170,"COL","Colombia","ppp_2020","GIS/Population/Global_2000_2020/2020/COL/col_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5032,174,"COM","Comoros","ppp_2020","GIS/Population/Global_2000_2020/2020/COM/com_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5033,175,"MYT","Mayotte","ppp_2020","GIS/Population/Global_2000_2020/2020/MYT/myt_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5034,178,"COG","Republic of Congo","ppp_2020","GIS/Population/Global_2000_2020/2020/COG/cog_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5035,180,"COD","Democratic Republic of the Congo","ppp_2020","GIS/Population/Global_2000_2020/2020/COD/cod_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5036,184,"COK","Cook Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/COK/cok_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5037,188,"CRI","Costa Rica","ppp_2020","GIS/Population/Global_2000_2020/2020/CRI/cri_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5038,191,"HRV","Croatia","ppp_2020","GIS/Population/Global_2000_2020/2020/HRV/hrv_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5039,192,"CUB","Cuba","ppp_2020","GIS/Population/Global_2000_2020/2020/CUB/cub_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5040,196,"CYP","Cyprus","ppp_2020","GIS/Population/Global_2000_2020/2020/CYP/cyp_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5041,203,"CZE","Czech Republic","ppp_2020","GIS/Population/Global_2000_2020/2020/CZE/cze_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5042,204,"BEN","Benin","ppp_2020","GIS/Population/Global_2000_2020/2020/BEN/ben_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5043,208,"DNK","Denmark","ppp_2020","GIS/Population/Global_2000_2020/2020/DNK/dnk_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5044,212,"DMA","Dominica","ppp_2020","GIS/Population/Global_2000_2020/2020/DMA/dma_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5045,214,"DOM","Dominican Republic","ppp_2020","GIS/Population/Global_2000_2020/2020/DOM/dom_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5046,218,"ECU","Ecuador","ppp_2020","GIS/Population/Global_2000_2020/2020/ECU/ecu_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5047,222,"SLV","El Salvador","ppp_2020","GIS/Population/Global_2000_2020/2020/SLV/slv_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5048,226,"GNQ","Equatorial Guinea","ppp_2020","GIS/Population/Global_2000_2020/2020/GNQ/gnq_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5049,231,"ETH","Ethiopia","ppp_2020","GIS/Population/Global_2000_2020/2020/ETH/eth_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5050,232,"ERI","Eritrea","ppp_2020","GIS/Population/Global_2000_2020/2020/ERI/eri_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5051,233,"EST","Estonia","ppp_2020","GIS/Population/Global_2000_2020/2020/EST/est_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5052,234,"FRO","Faroe Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/FRO/fro_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5053,238,"FLK","Falkland Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/FLK/flk_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5054,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/SGS/sgs_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5055,242,"FJI","Fiji","ppp_2020","GIS/Population/Global_2000_2020/2020/FJI/fji_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5056,246,"FIN","Finland","ppp_2020","GIS/Population/Global_2000_2020/2020/FIN/fin_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5057,248,"ALA","Aland Islands ","ppp_2020","GIS/Population/Global_2000_2020/2020/ALA/ala_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5058,250,"FRA","France","ppp_2020","GIS/Population/Global_2000_2020/2020/FRA/fra_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5059,254,"GUF","French Guiana","ppp_2020","GIS/Population/Global_2000_2020/2020/GUF/guf_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5060,258,"PYF","French Polynesia","ppp_2020","GIS/Population/Global_2000_2020/2020/PYF/pyf_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5061,260,"ATF","French Southern Territories","ppp_2020","GIS/Population/Global_2000_2020/2020/ATF/atf_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5062,262,"DJI","Djibouti","ppp_2020","GIS/Population/Global_2000_2020/2020/DJI/dji_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5063,266,"GAB","Gabon","ppp_2020","GIS/Population/Global_2000_2020/2020/GAB/gab_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5064,268,"GEO","Georgia","ppp_2020","GIS/Population/Global_2000_2020/2020/GEO/geo_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5065,270,"GMB","Gambia","ppp_2020","GIS/Population/Global_2000_2020/2020/GMB/gmb_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5066,275,"PSE","Palestina","ppp_2020","GIS/Population/Global_2000_2020/2020/PSE/pse_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5067,276,"DEU","Germany","ppp_2020","GIS/Population/Global_2000_2020/2020/DEU/deu_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5068,288,"GHA","Ghana","ppp_2020","GIS/Population/Global_2000_2020/2020/GHA/gha_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5069,292,"GIB","Gibraltar","ppp_2020","GIS/Population/Global_2000_2020/2020/GIB/gib_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5070,296,"KIR","Kiribati","ppp_2020","GIS/Population/Global_2000_2020/2020/KIR/kir_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5071,300,"GRC","Greece","ppp_2020","GIS/Population/Global_2000_2020/2020/GRC/grc_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5072,308,"GRD","Grenada","ppp_2020","GIS/Population/Global_2000_2020/2020/GRD/grd_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5073,312,"GLP","Guadeloupe","ppp_2020","GIS/Population/Global_2000_2020/2020/GLP/glp_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5074,316,"GUM","Guam","ppp_2020","GIS/Population/Global_2000_2020/2020/GUM/gum_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5075,320,"GTM","Guatemala","ppp_2020","GIS/Population/Global_2000_2020/2020/GTM/gtm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5076,324,"GIN","Guinea","ppp_2020","GIS/Population/Global_2000_2020/2020/GIN/gin_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5077,328,"GUY","Guyana","ppp_2020","GIS/Population/Global_2000_2020/2020/GUY/guy_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5078,332,"HTI","Haiti","ppp_2020","GIS/Population/Global_2000_2020/2020/HTI/hti_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5079,334,"HMD","Heard Island and McDonald Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/HMD/hmd_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5080,336,"VAT","Vatican City","ppp_2020","GIS/Population/Global_2000_2020/2020/VAT/vat_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5081,340,"HND","Honduras","ppp_2020","GIS/Population/Global_2000_2020/2020/HND/hnd_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5082,344,"HKG","Hong Kong","ppp_2020","GIS/Population/Global_2000_2020/2020/HKG/hkg_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5083,348,"HUN","Hungary","ppp_2020","GIS/Population/Global_2000_2020/2020/HUN/hun_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5084,352,"ISL","Iceland","ppp_2020","GIS/Population/Global_2000_2020/2020/ISL/isl_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5085,356,"IND","India","ppp_2020","GIS/Population/Global_2000_2020/2020/IND/ind_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5086,364,"IRN","Iran","ppp_2020","GIS/Population/Global_2000_2020/2020/IRN/irn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5087,368,"IRQ","Iraq","ppp_2020","GIS/Population/Global_2000_2020/2020/IRQ/irq_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5088,372,"IRL","Ireland","ppp_2020","GIS/Population/Global_2000_2020/2020/IRL/irl_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5089,376,"ISR","Israel","ppp_2020","GIS/Population/Global_2000_2020/2020/ISR/isr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5090,380,"ITA","Italy","ppp_2020","GIS/Population/Global_2000_2020/2020/ITA/ita_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5091,384,"CIV","CIte dIvoire","ppp_2020","GIS/Population/Global_2000_2020/2020/CIV/civ_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5092,388,"JAM","Jamaica","ppp_2020","GIS/Population/Global_2000_2020/2020/JAM/jam_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5093,392,"JPN","Japan","ppp_2020","GIS/Population/Global_2000_2020/2020/JPN/jpn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5094,398,"KAZ","Kazakhstan","ppp_2020","GIS/Population/Global_2000_2020/2020/KAZ/kaz_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5095,400,"JOR","Jordan","ppp_2020","GIS/Population/Global_2000_2020/2020/JOR/jor_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5096,404,"KEN","Kenya","ppp_2020","GIS/Population/Global_2000_2020/2020/KEN/ken_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5097,408,"PRK","North Korea","ppp_2020","GIS/Population/Global_2000_2020/2020/PRK/prk_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5098,410,"KOR","South Korea","ppp_2020","GIS/Population/Global_2000_2020/2020/KOR/kor_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5099,414,"KWT","Kuwait","ppp_2020","GIS/Population/Global_2000_2020/2020/KWT/kwt_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5100,417,"KGZ","Kyrgyzstan","ppp_2020","GIS/Population/Global_2000_2020/2020/KGZ/kgz_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5101,418,"LAO","Laos","ppp_2020","GIS/Population/Global_2000_2020/2020/LAO/lao_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5102,422,"LBN","Lebanon","ppp_2020","GIS/Population/Global_2000_2020/2020/LBN/lbn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5103,426,"LSO","Lesotho","ppp_2020","GIS/Population/Global_2000_2020/2020/LSO/lso_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5104,428,"LVA","Latvia","ppp_2020","GIS/Population/Global_2000_2020/2020/LVA/lva_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5105,430,"LBR","Liberia","ppp_2020","GIS/Population/Global_2000_2020/2020/LBR/lbr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5106,434,"LBY","Libya","ppp_2020","GIS/Population/Global_2000_2020/2020/LBY/lby_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5107,438,"LIE","Liechtenstein","ppp_2020","GIS/Population/Global_2000_2020/2020/LIE/lie_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5108,440,"LTU","Lithuania","ppp_2020","GIS/Population/Global_2000_2020/2020/LTU/ltu_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5109,442,"LUX","Luxembourg","ppp_2020","GIS/Population/Global_2000_2020/2020/LUX/lux_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5110,446,"MAC","Macao","ppp_2020","GIS/Population/Global_2000_2020/2020/MAC/mac_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5111,450,"MDG","Madagascar","ppp_2020","GIS/Population/Global_2000_2020/2020/MDG/mdg_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5112,454,"MWI","Malawi","ppp_2020","GIS/Population/Global_2000_2020/2020/MWI/mwi_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5113,458,"MYS","Malaysia","ppp_2020","GIS/Population/Global_2000_2020/2020/MYS/mys_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5114,462,"MDV","Maldives","ppp_2020","GIS/Population/Global_2000_2020/2020/MDV/mdv_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5115,466,"MLI","Mali","ppp_2020","GIS/Population/Global_2000_2020/2020/MLI/mli_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5116,470,"MLT","Malta","ppp_2020","GIS/Population/Global_2000_2020/2020/MLT/mlt_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5117,474,"MTQ","Martinique","ppp_2020","GIS/Population/Global_2000_2020/2020/MTQ/mtq_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5118,478,"MRT","Mauritania","ppp_2020","GIS/Population/Global_2000_2020/2020/MRT/mrt_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5119,480,"MUS","Mauritius","ppp_2020","GIS/Population/Global_2000_2020/2020/MUS/mus_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5120,484,"MEX","Mexico","ppp_2020","GIS/Population/Global_2000_2020/2020/MEX/mex_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5121,492,"MCO","Monaco","ppp_2020","GIS/Population/Global_2000_2020/2020/MCO/mco_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5122,496,"MNG","Mongolia","ppp_2020","GIS/Population/Global_2000_2020/2020/MNG/mng_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5123,498,"MDA","Moldova","ppp_2020","GIS/Population/Global_2000_2020/2020/MDA/mda_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5124,499,"MNE","Montenegro","ppp_2020","GIS/Population/Global_2000_2020/2020/MNE/mne_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5125,500,"MSR","Montserrat","ppp_2020","GIS/Population/Global_2000_2020/2020/MSR/msr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5126,504,"MAR","Morocco","ppp_2020","GIS/Population/Global_2000_2020/2020/MAR/mar_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5127,508,"MOZ","Mozambique","ppp_2020","GIS/Population/Global_2000_2020/2020/MOZ/moz_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5128,512,"OMN","Oman","ppp_2020","GIS/Population/Global_2000_2020/2020/OMN/omn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5129,516,"NAM","Namibia","ppp_2020","GIS/Population/Global_2000_2020/2020/NAM/nam_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5130,520,"NRU","Nauru","ppp_2020","GIS/Population/Global_2000_2020/2020/NRU/nru_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5131,524,"NPL","Nepal","ppp_2020","GIS/Population/Global_2000_2020/2020/NPL/npl_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5132,528,"NLD","Netherlands","ppp_2020","GIS/Population/Global_2000_2020/2020/NLD/nld_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5133,531,"CUW","Curacao","ppp_2020","GIS/Population/Global_2000_2020/2020/CUW/cuw_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5134,533,"ABW","Aruba","ppp_2020","GIS/Population/Global_2000_2020/2020/ABW/abw_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5135,534,"SXM","Sint Maarten (Dutch part)","ppp_2020","GIS/Population/Global_2000_2020/2020/SXM/sxm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5136,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2020","GIS/Population/Global_2000_2020/2020/BES/bes_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5137,540,"NCL","New Caledonia","ppp_2020","GIS/Population/Global_2000_2020/2020/NCL/ncl_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5138,548,"VUT","Vanuatu","ppp_2020","GIS/Population/Global_2000_2020/2020/VUT/vut_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5139,554,"NZL","New Zealand","ppp_2020","GIS/Population/Global_2000_2020/2020/NZL/nzl_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5140,558,"NIC","Nicaragua","ppp_2020","GIS/Population/Global_2000_2020/2020/NIC/nic_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5141,562,"NER","Niger","ppp_2020","GIS/Population/Global_2000_2020/2020/NER/ner_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5142,566,"NGA","Nigeria","ppp_2020","GIS/Population/Global_2000_2020/2020/NGA/nga_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5143,570,"NIU","Niue","ppp_2020","GIS/Population/Global_2000_2020/2020/NIU/niu_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5144,574,"NFK","Norfolk Island","ppp_2020","GIS/Population/Global_2000_2020/2020/NFK/nfk_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5145,578,"NOR","Norway","ppp_2020","GIS/Population/Global_2000_2020/2020/NOR/nor_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5146,580,"MNP","Northern Mariana Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/MNP/mnp_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5147,581,"UMI","United States Minor Outlying Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/UMI/umi_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5148,583,"FSM","Micronesia","ppp_2020","GIS/Population/Global_2000_2020/2020/FSM/fsm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5149,584,"MHL","Marshall Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/MHL/mhl_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5150,585,"PLW","Palau","ppp_2020","GIS/Population/Global_2000_2020/2020/PLW/plw_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5151,586,"PAK","Pakistan","ppp_2020","GIS/Population/Global_2000_2020/2020/PAK/pak_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5152,591,"PAN","Panama","ppp_2020","GIS/Population/Global_2000_2020/2020/PAN/pan_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5153,598,"PNG","Papua New Guinea","ppp_2020","GIS/Population/Global_2000_2020/2020/PNG/png_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5154,600,"PRY","Paraguay","ppp_2020","GIS/Population/Global_2000_2020/2020/PRY/pry_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5155,604,"PER","Peru","ppp_2020","GIS/Population/Global_2000_2020/2020/PER/per_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5156,608,"PHL","Philippines","ppp_2020","GIS/Population/Global_2000_2020/2020/PHL/phl_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5157,612,"PCN","Pitcairn Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/PCN/pcn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5158,616,"POL","Poland","ppp_2020","GIS/Population/Global_2000_2020/2020/POL/pol_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5159,620,"PRT","Portugal","ppp_2020","GIS/Population/Global_2000_2020/2020/PRT/prt_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5160,624,"GNB","Guinea-Bissau","ppp_2020","GIS/Population/Global_2000_2020/2020/GNB/gnb_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5161,626,"TLS","East Timor","ppp_2020","GIS/Population/Global_2000_2020/2020/TLS/tls_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5162,630,"PRI","Puerto Rico","ppp_2020","GIS/Population/Global_2000_2020/2020/PRI/pri_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5163,634,"QAT","Qatar","ppp_2020","GIS/Population/Global_2000_2020/2020/QAT/qat_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5164,638,"REU","Reunion","ppp_2020","GIS/Population/Global_2000_2020/2020/REU/reu_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5165,642,"ROU","Romania","ppp_2020","GIS/Population/Global_2000_2020/2020/ROU/rou_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5166,646,"RWA","Rwanda","ppp_2020","GIS/Population/Global_2000_2020/2020/RWA/rwa_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5167,652,"BLM","Saint Barthelemy","ppp_2020","GIS/Population/Global_2000_2020/2020/BLM/blm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5168,654,"SHN","Saint Helena","ppp_2020","GIS/Population/Global_2000_2020/2020/SHN/shn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5169,659,"KNA","Saint Kitts and Nevis","ppp_2020","GIS/Population/Global_2000_2020/2020/KNA/kna_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5170,660,"AIA","Anguilla","ppp_2020","GIS/Population/Global_2000_2020/2020/AIA/aia_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5171,662,"LCA","Saint Lucia","ppp_2020","GIS/Population/Global_2000_2020/2020/LCA/lca_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5172,663,"MAF","Saint Martin (French part)","ppp_2020","GIS/Population/Global_2000_2020/2020/MAF/maf_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5173,666,"SPM","Saint Pierre and Miquelon","ppp_2020","GIS/Population/Global_2000_2020/2020/SPM/spm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5174,670,"VCT","Saint Vincent and the Grenadines","ppp_2020","GIS/Population/Global_2000_2020/2020/VCT/vct_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5175,674,"SMR","San Marino","ppp_2020","GIS/Population/Global_2000_2020/2020/SMR/smr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5176,678,"STP","Sao Tome and Principe","ppp_2020","GIS/Population/Global_2000_2020/2020/STP/stp_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5177,682,"SAU","Saudi Arabia","ppp_2020","GIS/Population/Global_2000_2020/2020/SAU/sau_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5178,686,"SEN","Senegal","ppp_2020","GIS/Population/Global_2000_2020/2020/SEN/sen_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5179,688,"SRB","Serbia","ppp_2020","GIS/Population/Global_2000_2020/2020/SRB/srb_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5180,690,"SYC","Seychelles","ppp_2020","GIS/Population/Global_2000_2020/2020/SYC/syc_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5181,694,"SLE","Sierra Leone","ppp_2020","GIS/Population/Global_2000_2020/2020/SLE/sle_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5182,702,"SGP","Singapore","ppp_2020","GIS/Population/Global_2000_2020/2020/SGP/sgp_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5183,703,"SVK","Slovakia","ppp_2020","GIS/Population/Global_2000_2020/2020/SVK/svk_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5184,704,"VNM","Vietnam","ppp_2020","GIS/Population/Global_2000_2020/2020/VNM/vnm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5185,705,"SVN","Slovenia","ppp_2020","GIS/Population/Global_2000_2020/2020/SVN/svn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5186,706,"SOM","Somalia","ppp_2020","GIS/Population/Global_2000_2020/2020/SOM/som_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5187,710,"ZAF","South Africa","ppp_2020","GIS/Population/Global_2000_2020/2020/ZAF/zaf_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5188,716,"ZWE","Zimbabwe","ppp_2020","GIS/Population/Global_2000_2020/2020/ZWE/zwe_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5189,724,"ESP","Spain","ppp_2020","GIS/Population/Global_2000_2020/2020/ESP/esp_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5190,728,"SSD","South Sudan","ppp_2020","GIS/Population/Global_2000_2020/2020/SSD/ssd_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5191,729,"SDN","Sudan","ppp_2020","GIS/Population/Global_2000_2020/2020/SDN/sdn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5192,732,"ESH","Western Sahara","ppp_2020","GIS/Population/Global_2000_2020/2020/ESH/esh_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5193,740,"SUR","Suriname","ppp_2020","GIS/Population/Global_2000_2020/2020/SUR/sur_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5194,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/SJM/sjm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5195,748,"SWZ","Swaziland","ppp_2020","GIS/Population/Global_2000_2020/2020/SWZ/swz_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5196,752,"SWE","Sweden","ppp_2020","GIS/Population/Global_2000_2020/2020/SWE/swe_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5197,756,"CHE","Switzerland","ppp_2020","GIS/Population/Global_2000_2020/2020/CHE/che_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5198,760,"SYR","Syria","ppp_2020","GIS/Population/Global_2000_2020/2020/SYR/syr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5199,762,"TJK","Tajikistan","ppp_2020","GIS/Population/Global_2000_2020/2020/TJK/tjk_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5200,764,"THA","Thailand","ppp_2020","GIS/Population/Global_2000_2020/2020/THA/tha_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5201,768,"TGO","Togo","ppp_2020","GIS/Population/Global_2000_2020/2020/TGO/tgo_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5202,772,"TKL","Tokelau","ppp_2020","GIS/Population/Global_2000_2020/2020/TKL/tkl_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5203,776,"TON","Tonga","ppp_2020","GIS/Population/Global_2000_2020/2020/TON/ton_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5204,780,"TTO","Trinidad and Tobago","ppp_2020","GIS/Population/Global_2000_2020/2020/TTO/tto_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5205,784,"ARE","United Arab Emirates","ppp_2020","GIS/Population/Global_2000_2020/2020/ARE/are_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5206,788,"TUN","Tunisia","ppp_2020","GIS/Population/Global_2000_2020/2020/TUN/tun_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5207,792,"TUR","Turkey","ppp_2020","GIS/Population/Global_2000_2020/2020/TUR/tur_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5208,795,"TKM","Turkmenistan","ppp_2020","GIS/Population/Global_2000_2020/2020/TKM/tkm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5209,796,"TCA","Turks and Caicos Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/TCA/tca_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5210,798,"TUV","Tuvalu","ppp_2020","GIS/Population/Global_2000_2020/2020/TUV/tuv_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5211,800,"UGA","Uganda","ppp_2020","GIS/Population/Global_2000_2020/2020/UGA/uga_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5212,804,"UKR","Ukraine","ppp_2020","GIS/Population/Global_2000_2020/2020/UKR/ukr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5213,807,"MKD","Macedonia","ppp_2020","GIS/Population/Global_2000_2020/2020/MKD/mkd_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5214,818,"EGY","Egypt","ppp_2020","GIS/Population/Global_2000_2020/2020/EGY/egy_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5215,826,"GBR","United Kingdom","ppp_2020","GIS/Population/Global_2000_2020/2020/GBR/gbr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5216,831,"GGY","Guernsey","ppp_2020","GIS/Population/Global_2000_2020/2020/GGY/ggy_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5217,832,"JEY","Jersey","ppp_2020","GIS/Population/Global_2000_2020/2020/JEY/jey_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5218,833,"IMN","Isle of Man","ppp_2020","GIS/Population/Global_2000_2020/2020/IMN/imn_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5219,834,"TZA","Tanzania","ppp_2020","GIS/Population/Global_2000_2020/2020/TZA/tza_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5220,854,"BFA","Burkina Faso","ppp_2020","GIS/Population/Global_2000_2020/2020/BFA/bfa_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5221,858,"URY","Uruguay","ppp_2020","GIS/Population/Global_2000_2020/2020/URY/ury_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5222,860,"UZB","Uzbekistan","ppp_2020","GIS/Population/Global_2000_2020/2020/UZB/uzb_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5223,862,"VEN","Venezuela","ppp_2020","GIS/Population/Global_2000_2020/2020/VEN/ven_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5224,876,"WLF","Wallis and Futuna","ppp_2020","GIS/Population/Global_2000_2020/2020/WLF/wlf_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5225,882,"WSM","Samoa","ppp_2020","GIS/Population/Global_2000_2020/2020/WSM/wsm_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5226,887,"YEM","Yemen","ppp_2020","GIS/Population/Global_2000_2020/2020/YEM/yem_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5227,894,"ZMB","Zambia","ppp_2020","GIS/Population/Global_2000_2020/2020/ZMB/zmb_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5228,900,"KOS","Kosovo","ppp_2020","GIS/Population/Global_2000_2020/2020/KOS/kos_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5229,901,"SPR","Spratly Islands","ppp_2020","GIS/Population/Global_2000_2020/2020/SPR/spr_ppp_2020.tif","Estimated total number of people per grid-cell 2020 The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5230,643,"RUS","Russia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/RUS/rus_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5231,360,"IDN","Indonesia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/IDN/idn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5232,840,"USA","United States","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/USA/usa_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5233,850,"VIR","Virgin_Islands_U_S","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/VIR/vir_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5234,304,"GRL","Greenland","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GRL/grl_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5235,156,"CHN","China","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CHN/chn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5236,36,"AUS","Australia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/AUS/aus_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5237,76,"BRA","Brazil","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BRA/bra_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5238,124,"CAN","Canada","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CAN/can_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5239,152,"CHL","Chile","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CHL/chl_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5240,4,"AFG","Afghanistan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/AFG/afg_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5241,8,"ALB","Albania","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ALB/alb_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5242,10,"ATA","Antarctica","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ATA/ata_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5243,12,"DZA","Algeria","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/DZA/dza_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5244,16,"ASM","American Samoa","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ASM/asm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5245,20,"AND","Andorra","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/AND/and_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5246,24,"AGO","Angola","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/AGO/ago_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5247,28,"ATG","Antigua and Barbuda","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ATG/atg_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5248,31,"AZE","Azerbaijan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/AZE/aze_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5249,32,"ARG","Argentina","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ARG/arg_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5250,40,"AUT","Austria","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/AUT/aut_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5251,44,"BHS","Bahamas","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BHS/bhs_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5252,48,"BHR","Bahrain","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BHR/bhr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5253,50,"BGD","Bangladesh","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BGD/bgd_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5254,51,"ARM","Armenia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ARM/arm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5255,52,"BRB","Barbados","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BRB/brb_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5256,56,"BEL","Belgium","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BEL/bel_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5257,60,"BMU","Bermuda","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BMU/bmu_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5258,64,"BTN","Bhutan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BTN/btn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5259,68,"BOL","Bolivia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BOL/bol_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5260,70,"BIH","Bosnia and Herzegovina","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BIH/bih_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5261,72,"BWA","Botswana","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BWA/bwa_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5262,74,"BVT","Bouvet Island","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BVT/bvt_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5263,84,"BLZ","Belize","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BLZ/blz_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5264,86,"IOT","British Indian Ocean Territory","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/IOT/iot_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5265,90,"SLB","Solomon Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SLB/slb_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5266,92,"VGB","British Virgin Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/VGB/vgb_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5267,96,"BRN","Brunei","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BRN/brn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5268,100,"BGR","Bulgaria","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BGR/bgr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5269,104,"MMR","Myanmar","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MMR/mmr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5270,108,"BDI","Burundi","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BDI/bdi_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5271,112,"BLR","Belarus","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BLR/blr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5272,116,"KHM","Cambodia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/KHM/khm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5273,120,"CMR","Cameroon","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CMR/cmr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5274,132,"CPV","Cape Verde","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CPV/cpv_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5275,136,"CYM","Cayman Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CYM/cym_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5276,140,"CAF","Central African Republic","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CAF/caf_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5277,144,"LKA","Sri Lanka","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LKA/lka_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5278,148,"TCD","Chad","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TCD/tcd_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5279,158,"TWN","Taiwan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TWN/twn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5280,170,"COL","Colombia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/COL/col_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5281,174,"COM","Comoros","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/COM/com_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5282,175,"MYT","Mayotte","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MYT/myt_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5283,178,"COG","Republic of Congo","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/COG/cog_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5284,180,"COD","Democratic Republic of the Congo","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/COD/cod_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5285,184,"COK","Cook Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/COK/cok_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5286,188,"CRI","Costa Rica","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CRI/cri_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5287,191,"HRV","Croatia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/HRV/hrv_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5288,192,"CUB","Cuba","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CUB/cub_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5289,196,"CYP","Cyprus","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CYP/cyp_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5290,203,"CZE","Czech Republic","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CZE/cze_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5291,204,"BEN","Benin","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BEN/ben_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5292,208,"DNK","Denmark","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/DNK/dnk_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5293,212,"DMA","Dominica","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/DMA/dma_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5294,214,"DOM","Dominican Republic","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/DOM/dom_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5295,218,"ECU","Ecuador","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ECU/ecu_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5296,222,"SLV","El Salvador","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SLV/slv_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5297,226,"GNQ","Equatorial Guinea","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GNQ/gnq_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5298,231,"ETH","Ethiopia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ETH/eth_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5299,232,"ERI","Eritrea","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ERI/eri_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5300,233,"EST","Estonia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/EST/est_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5301,234,"FRO","Faroe Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/FRO/fro_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5302,238,"FLK","Falkland Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/FLK/flk_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5303,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SGS/sgs_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5304,242,"FJI","Fiji","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/FJI/fji_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5305,246,"FIN","Finland","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/FIN/fin_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5306,248,"ALA","Aland Islands ","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ALA/ala_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5307,250,"FRA","France","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/FRA/fra_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5308,254,"GUF","French Guiana","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GUF/guf_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5309,258,"PYF","French Polynesia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PYF/pyf_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5310,260,"ATF","French Southern Territories","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ATF/atf_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5311,262,"DJI","Djibouti","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/DJI/dji_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5312,266,"GAB","Gabon","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GAB/gab_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5313,268,"GEO","Georgia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GEO/geo_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5314,270,"GMB","Gambia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GMB/gmb_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5315,275,"PSE","Palestina","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PSE/pse_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5316,276,"DEU","Germany","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/DEU/deu_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5317,288,"GHA","Ghana","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GHA/gha_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5318,292,"GIB","Gibraltar","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GIB/gib_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5319,296,"KIR","Kiribati","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/KIR/kir_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5320,300,"GRC","Greece","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GRC/grc_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5321,308,"GRD","Grenada","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GRD/grd_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5322,312,"GLP","Guadeloupe","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GLP/glp_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5323,316,"GUM","Guam","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GUM/gum_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5324,320,"GTM","Guatemala","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GTM/gtm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5325,324,"GIN","Guinea","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GIN/gin_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5326,328,"GUY","Guyana","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GUY/guy_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5327,332,"HTI","Haiti","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/HTI/hti_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5328,334,"HMD","Heard Island and McDonald Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/HMD/hmd_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5329,336,"VAT","Vatican City","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/VAT/vat_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5330,340,"HND","Honduras","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/HND/hnd_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5331,344,"HKG","Hong Kong","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/HKG/hkg_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5332,348,"HUN","Hungary","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/HUN/hun_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5333,352,"ISL","Iceland","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ISL/isl_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5334,356,"IND","India","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/IND/ind_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5335,364,"IRN","Iran","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/IRN/irn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5336,368,"IRQ","Iraq","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/IRQ/irq_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5337,372,"IRL","Ireland","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/IRL/irl_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5338,376,"ISR","Israel","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ISR/isr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5339,380,"ITA","Italy","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ITA/ita_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5340,384,"CIV","CIte dIvoire","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CIV/civ_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5341,388,"JAM","Jamaica","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/JAM/jam_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5342,392,"JPN","Japan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/JPN/jpn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5343,398,"KAZ","Kazakhstan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/KAZ/kaz_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5344,400,"JOR","Jordan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/JOR/jor_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5345,404,"KEN","Kenya","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/KEN/ken_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5346,408,"PRK","North Korea","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PRK/prk_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5347,410,"KOR","South Korea","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/KOR/kor_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5348,414,"KWT","Kuwait","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/KWT/kwt_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5349,417,"KGZ","Kyrgyzstan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/KGZ/kgz_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5350,418,"LAO","Laos","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LAO/lao_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5351,422,"LBN","Lebanon","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LBN/lbn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5352,426,"LSO","Lesotho","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LSO/lso_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5353,428,"LVA","Latvia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LVA/lva_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5354,430,"LBR","Liberia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LBR/lbr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5355,434,"LBY","Libya","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LBY/lby_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5356,438,"LIE","Liechtenstein","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LIE/lie_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5357,440,"LTU","Lithuania","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LTU/ltu_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5358,442,"LUX","Luxembourg","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LUX/lux_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5359,446,"MAC","Macao","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MAC/mac_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5360,450,"MDG","Madagascar","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MDG/mdg_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5361,454,"MWI","Malawi","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MWI/mwi_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5362,458,"MYS","Malaysia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MYS/mys_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5363,462,"MDV","Maldives","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MDV/mdv_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5364,466,"MLI","Mali","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MLI/mli_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5365,470,"MLT","Malta","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MLT/mlt_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5366,474,"MTQ","Martinique","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MTQ/mtq_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5367,478,"MRT","Mauritania","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MRT/mrt_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5368,480,"MUS","Mauritius","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MUS/mus_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5369,484,"MEX","Mexico","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MEX/mex_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5370,492,"MCO","Monaco","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MCO/mco_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5371,496,"MNG","Mongolia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MNG/mng_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5372,498,"MDA","Moldova","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MDA/mda_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5373,499,"MNE","Montenegro","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MNE/mne_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5374,500,"MSR","Montserrat","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MSR/msr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5375,504,"MAR","Morocco","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MAR/mar_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5376,508,"MOZ","Mozambique","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MOZ/moz_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5377,512,"OMN","Oman","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/OMN/omn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5378,516,"NAM","Namibia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NAM/nam_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5379,520,"NRU","Nauru","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NRU/nru_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5380,524,"NPL","Nepal","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NPL/npl_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5381,528,"NLD","Netherlands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NLD/nld_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5382,531,"CUW","Curacao","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CUW/cuw_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5383,533,"ABW","Aruba","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ABW/abw_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5384,534,"SXM","Sint Maarten (Dutch part)","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SXM/sxm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5385,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BES/bes_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5386,540,"NCL","New Caledonia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NCL/ncl_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5387,548,"VUT","Vanuatu","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/VUT/vut_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5388,554,"NZL","New Zealand","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NZL/nzl_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5389,558,"NIC","Nicaragua","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NIC/nic_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5390,562,"NER","Niger","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NER/ner_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5391,566,"NGA","Nigeria","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NGA/nga_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5392,570,"NIU","Niue","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NIU/niu_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5393,574,"NFK","Norfolk Island","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NFK/nfk_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5394,578,"NOR","Norway","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/NOR/nor_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5395,580,"MNP","Northern Mariana Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MNP/mnp_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5396,581,"UMI","United States Minor Outlying Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/UMI/umi_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5397,583,"FSM","Micronesia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/FSM/fsm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5398,584,"MHL","Marshall Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MHL/mhl_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5399,585,"PLW","Palau","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PLW/plw_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5400,586,"PAK","Pakistan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PAK/pak_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5401,591,"PAN","Panama","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PAN/pan_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5402,598,"PNG","Papua New Guinea","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PNG/png_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5403,600,"PRY","Paraguay","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PRY/pry_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5404,604,"PER","Peru","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PER/per_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5405,608,"PHL","Philippines","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PHL/phl_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5406,612,"PCN","Pitcairn Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PCN/pcn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5407,616,"POL","Poland","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/POL/pol_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5408,620,"PRT","Portugal","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PRT/prt_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5409,624,"GNB","Guinea-Bissau","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GNB/gnb_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5410,626,"TLS","East Timor","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TLS/tls_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5411,630,"PRI","Puerto Rico","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/PRI/pri_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5412,634,"QAT","Qatar","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/QAT/qat_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5413,638,"REU","Reunion","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/REU/reu_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5414,642,"ROU","Romania","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ROU/rou_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5415,646,"RWA","Rwanda","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/RWA/rwa_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5416,652,"BLM","Saint Barthelemy","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BLM/blm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5417,654,"SHN","Saint Helena","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SHN/shn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5418,659,"KNA","Saint Kitts and Nevis","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/KNA/kna_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5419,660,"AIA","Anguilla","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/AIA/aia_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5420,662,"LCA","Saint Lucia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/LCA/lca_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5421,663,"MAF","Saint Martin (French part)","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MAF/maf_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5422,666,"SPM","Saint Pierre and Miquelon","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SPM/spm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5423,670,"VCT","Saint Vincent and the Grenadines","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/VCT/vct_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5424,674,"SMR","San Marino","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SMR/smr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5425,678,"STP","Sao Tome and Principe","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/STP/stp_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5426,682,"SAU","Saudi Arabia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SAU/sau_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5427,686,"SEN","Senegal","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SEN/sen_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5428,688,"SRB","Serbia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SRB/srb_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5429,690,"SYC","Seychelles","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SYC/syc_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5430,694,"SLE","Sierra Leone","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SLE/sle_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5431,702,"SGP","Singapore","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SGP/sgp_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5432,703,"SVK","Slovakia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SVK/svk_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5433,704,"VNM","Vietnam","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/VNM/vnm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5434,705,"SVN","Slovenia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SVN/svn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5435,706,"SOM","Somalia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SOM/som_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5436,710,"ZAF","South Africa","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ZAF/zaf_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5437,716,"ZWE","Zimbabwe","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ZWE/zwe_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5438,724,"ESP","Spain","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ESP/esp_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5439,728,"SSD","South Sudan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SSD/ssd_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5440,729,"SDN","Sudan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SDN/sdn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5441,732,"ESH","Western Sahara","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ESH/esh_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5442,740,"SUR","Suriname","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SUR/sur_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5443,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SJM/sjm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5444,748,"SWZ","Swaziland","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SWZ/swz_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5445,752,"SWE","Sweden","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SWE/swe_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5446,756,"CHE","Switzerland","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/CHE/che_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5447,760,"SYR","Syria","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SYR/syr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5448,762,"TJK","Tajikistan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TJK/tjk_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5449,764,"THA","Thailand","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/THA/tha_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5450,768,"TGO","Togo","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TGO/tgo_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5451,772,"TKL","Tokelau","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TKL/tkl_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5452,776,"TON","Tonga","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TON/ton_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5453,780,"TTO","Trinidad and Tobago","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TTO/tto_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5454,784,"ARE","United Arab Emirates","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ARE/are_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5455,788,"TUN","Tunisia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TUN/tun_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5456,792,"TUR","Turkey","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TUR/tur_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5457,795,"TKM","Turkmenistan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TKM/tkm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5458,796,"TCA","Turks and Caicos Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TCA/tca_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5459,798,"TUV","Tuvalu","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TUV/tuv_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5460,800,"UGA","Uganda","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/UGA/uga_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5461,804,"UKR","Ukraine","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/UKR/ukr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5462,807,"MKD","Macedonia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/MKD/mkd_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5463,818,"EGY","Egypt","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/EGY/egy_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5464,826,"GBR","United Kingdom","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GBR/gbr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5465,831,"GGY","Guernsey","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/GGY/ggy_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5466,832,"JEY","Jersey","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/JEY/jey_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5467,833,"IMN","Isle of Man","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/IMN/imn_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5468,834,"TZA","Tanzania","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/TZA/tza_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5469,854,"BFA","Burkina Faso","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/BFA/bfa_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5470,858,"URY","Uruguay","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/URY/ury_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5471,860,"UZB","Uzbekistan","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/UZB/uzb_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5472,862,"VEN","Venezuela","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/VEN/ven_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5473,876,"WLF","Wallis and Futuna","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/WLF/wlf_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5474,882,"WSM","Samoa","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/WSM/wsm_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5475,887,"YEM","Yemen","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/YEM/yem_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5476,894,"ZMB","Zambia","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/ZMB/zmb_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5477,900,"KOS","Kosovo","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/KOS/kos_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5478,901,"SPR","Spratly Islands","ppp_2000_UNadj","GIS/Population/Global_2000_2020/2000/SPR/spr_ppp_2000_UNadj.tif","Estimated total number of people per grid-cell 2000 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5479,643,"RUS","Russia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/RUS/rus_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5480,360,"IDN","Indonesia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/IDN/idn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5481,840,"USA","United States","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/USA/usa_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5482,850,"VIR","Virgin_Islands_U_S","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/VIR/vir_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5483,304,"GRL","Greenland","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GRL/grl_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5484,156,"CHN","China","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CHN/chn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5485,36,"AUS","Australia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/AUS/aus_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5486,76,"BRA","Brazil","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BRA/bra_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5487,124,"CAN","Canada","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CAN/can_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5488,152,"CHL","Chile","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CHL/chl_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5489,4,"AFG","Afghanistan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/AFG/afg_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5490,8,"ALB","Albania","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ALB/alb_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5491,10,"ATA","Antarctica","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ATA/ata_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5492,12,"DZA","Algeria","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/DZA/dza_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5493,16,"ASM","American Samoa","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ASM/asm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5494,20,"AND","Andorra","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/AND/and_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5495,24,"AGO","Angola","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/AGO/ago_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5496,28,"ATG","Antigua and Barbuda","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ATG/atg_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5497,31,"AZE","Azerbaijan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/AZE/aze_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5498,32,"ARG","Argentina","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ARG/arg_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5499,40,"AUT","Austria","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/AUT/aut_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5500,44,"BHS","Bahamas","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BHS/bhs_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5501,48,"BHR","Bahrain","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BHR/bhr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5502,50,"BGD","Bangladesh","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BGD/bgd_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5503,51,"ARM","Armenia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ARM/arm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5504,52,"BRB","Barbados","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BRB/brb_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5505,56,"BEL","Belgium","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BEL/bel_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5506,60,"BMU","Bermuda","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BMU/bmu_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5507,64,"BTN","Bhutan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BTN/btn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5508,68,"BOL","Bolivia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BOL/bol_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5509,70,"BIH","Bosnia and Herzegovina","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BIH/bih_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5510,72,"BWA","Botswana","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BWA/bwa_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5511,74,"BVT","Bouvet Island","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BVT/bvt_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5512,84,"BLZ","Belize","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BLZ/blz_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5513,86,"IOT","British Indian Ocean Territory","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/IOT/iot_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5514,90,"SLB","Solomon Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SLB/slb_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5515,92,"VGB","British Virgin Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/VGB/vgb_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5516,96,"BRN","Brunei","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BRN/brn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5517,100,"BGR","Bulgaria","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BGR/bgr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5518,104,"MMR","Myanmar","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MMR/mmr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5519,108,"BDI","Burundi","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BDI/bdi_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5520,112,"BLR","Belarus","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BLR/blr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5521,116,"KHM","Cambodia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/KHM/khm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5522,120,"CMR","Cameroon","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CMR/cmr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5523,132,"CPV","Cape Verde","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CPV/cpv_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5524,136,"CYM","Cayman Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CYM/cym_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5525,140,"CAF","Central African Republic","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CAF/caf_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5526,144,"LKA","Sri Lanka","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LKA/lka_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5527,148,"TCD","Chad","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TCD/tcd_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5528,158,"TWN","Taiwan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TWN/twn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5529,170,"COL","Colombia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/COL/col_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5530,174,"COM","Comoros","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/COM/com_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5531,175,"MYT","Mayotte","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MYT/myt_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5532,178,"COG","Republic of Congo","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/COG/cog_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5533,180,"COD","Democratic Republic of the Congo","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/COD/cod_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5534,184,"COK","Cook Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/COK/cok_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5535,188,"CRI","Costa Rica","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CRI/cri_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5536,191,"HRV","Croatia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/HRV/hrv_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5537,192,"CUB","Cuba","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CUB/cub_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5538,196,"CYP","Cyprus","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CYP/cyp_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5539,203,"CZE","Czech Republic","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CZE/cze_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5540,204,"BEN","Benin","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BEN/ben_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5541,208,"DNK","Denmark","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/DNK/dnk_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5542,212,"DMA","Dominica","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/DMA/dma_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5543,214,"DOM","Dominican Republic","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/DOM/dom_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5544,218,"ECU","Ecuador","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ECU/ecu_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5545,222,"SLV","El Salvador","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SLV/slv_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5546,226,"GNQ","Equatorial Guinea","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GNQ/gnq_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5547,231,"ETH","Ethiopia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ETH/eth_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5548,232,"ERI","Eritrea","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ERI/eri_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5549,233,"EST","Estonia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/EST/est_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5550,234,"FRO","Faroe Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/FRO/fro_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5551,238,"FLK","Falkland Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/FLK/flk_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5552,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SGS/sgs_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5553,242,"FJI","Fiji","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/FJI/fji_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5554,246,"FIN","Finland","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/FIN/fin_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5555,248,"ALA","Aland Islands ","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ALA/ala_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5556,250,"FRA","France","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/FRA/fra_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5557,254,"GUF","French Guiana","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GUF/guf_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5558,258,"PYF","French Polynesia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PYF/pyf_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5559,260,"ATF","French Southern Territories","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ATF/atf_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5560,262,"DJI","Djibouti","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/DJI/dji_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5561,266,"GAB","Gabon","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GAB/gab_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5562,268,"GEO","Georgia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GEO/geo_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5563,270,"GMB","Gambia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GMB/gmb_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5564,275,"PSE","Palestina","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PSE/pse_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5565,276,"DEU","Germany","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/DEU/deu_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5566,288,"GHA","Ghana","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GHA/gha_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5567,292,"GIB","Gibraltar","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GIB/gib_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5568,296,"KIR","Kiribati","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/KIR/kir_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5569,300,"GRC","Greece","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GRC/grc_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5570,308,"GRD","Grenada","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GRD/grd_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5571,312,"GLP","Guadeloupe","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GLP/glp_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5572,316,"GUM","Guam","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GUM/gum_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5573,320,"GTM","Guatemala","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GTM/gtm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5574,324,"GIN","Guinea","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GIN/gin_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5575,328,"GUY","Guyana","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GUY/guy_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5576,332,"HTI","Haiti","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/HTI/hti_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5577,334,"HMD","Heard Island and McDonald Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/HMD/hmd_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5578,336,"VAT","Vatican City","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/VAT/vat_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5579,340,"HND","Honduras","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/HND/hnd_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5580,344,"HKG","Hong Kong","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/HKG/hkg_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5581,348,"HUN","Hungary","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/HUN/hun_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5582,352,"ISL","Iceland","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ISL/isl_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5583,356,"IND","India","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/IND/ind_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5584,364,"IRN","Iran","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/IRN/irn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5585,368,"IRQ","Iraq","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/IRQ/irq_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5586,372,"IRL","Ireland","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/IRL/irl_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5587,376,"ISR","Israel","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ISR/isr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5588,380,"ITA","Italy","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ITA/ita_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5589,384,"CIV","CIte dIvoire","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CIV/civ_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5590,388,"JAM","Jamaica","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/JAM/jam_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5591,392,"JPN","Japan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/JPN/jpn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5592,398,"KAZ","Kazakhstan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/KAZ/kaz_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5593,400,"JOR","Jordan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/JOR/jor_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5594,404,"KEN","Kenya","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/KEN/ken_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5595,408,"PRK","North Korea","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PRK/prk_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5596,410,"KOR","South Korea","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/KOR/kor_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5597,414,"KWT","Kuwait","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/KWT/kwt_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5598,417,"KGZ","Kyrgyzstan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/KGZ/kgz_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5599,418,"LAO","Laos","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LAO/lao_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5600,422,"LBN","Lebanon","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LBN/lbn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5601,426,"LSO","Lesotho","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LSO/lso_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5602,428,"LVA","Latvia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LVA/lva_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5603,430,"LBR","Liberia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LBR/lbr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5604,434,"LBY","Libya","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LBY/lby_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5605,438,"LIE","Liechtenstein","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LIE/lie_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5606,440,"LTU","Lithuania","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LTU/ltu_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5607,442,"LUX","Luxembourg","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LUX/lux_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5608,446,"MAC","Macao","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MAC/mac_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5609,450,"MDG","Madagascar","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MDG/mdg_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5610,454,"MWI","Malawi","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MWI/mwi_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5611,458,"MYS","Malaysia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MYS/mys_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5612,462,"MDV","Maldives","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MDV/mdv_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5613,466,"MLI","Mali","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MLI/mli_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5614,470,"MLT","Malta","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MLT/mlt_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5615,474,"MTQ","Martinique","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MTQ/mtq_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5616,478,"MRT","Mauritania","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MRT/mrt_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5617,480,"MUS","Mauritius","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MUS/mus_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5618,484,"MEX","Mexico","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MEX/mex_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5619,492,"MCO","Monaco","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MCO/mco_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5620,496,"MNG","Mongolia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MNG/mng_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5621,498,"MDA","Moldova","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MDA/mda_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5622,499,"MNE","Montenegro","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MNE/mne_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5623,500,"MSR","Montserrat","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MSR/msr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5624,504,"MAR","Morocco","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MAR/mar_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5625,508,"MOZ","Mozambique","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MOZ/moz_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5626,512,"OMN","Oman","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/OMN/omn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5627,516,"NAM","Namibia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NAM/nam_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5628,520,"NRU","Nauru","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NRU/nru_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5629,524,"NPL","Nepal","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NPL/npl_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5630,528,"NLD","Netherlands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NLD/nld_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5631,531,"CUW","Curacao","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CUW/cuw_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5632,533,"ABW","Aruba","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ABW/abw_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5633,534,"SXM","Sint Maarten (Dutch part)","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SXM/sxm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5634,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BES/bes_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5635,540,"NCL","New Caledonia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NCL/ncl_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5636,548,"VUT","Vanuatu","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/VUT/vut_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5637,554,"NZL","New Zealand","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NZL/nzl_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5638,558,"NIC","Nicaragua","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NIC/nic_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5639,562,"NER","Niger","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NER/ner_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5640,566,"NGA","Nigeria","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NGA/nga_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5641,570,"NIU","Niue","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NIU/niu_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5642,574,"NFK","Norfolk Island","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NFK/nfk_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5643,578,"NOR","Norway","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/NOR/nor_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5644,580,"MNP","Northern Mariana Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MNP/mnp_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5645,581,"UMI","United States Minor Outlying Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/UMI/umi_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5646,583,"FSM","Micronesia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/FSM/fsm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5647,584,"MHL","Marshall Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MHL/mhl_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5648,585,"PLW","Palau","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PLW/plw_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5649,586,"PAK","Pakistan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PAK/pak_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5650,591,"PAN","Panama","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PAN/pan_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5651,598,"PNG","Papua New Guinea","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PNG/png_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5652,600,"PRY","Paraguay","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PRY/pry_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5653,604,"PER","Peru","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PER/per_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5654,608,"PHL","Philippines","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PHL/phl_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5655,612,"PCN","Pitcairn Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PCN/pcn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5656,616,"POL","Poland","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/POL/pol_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5657,620,"PRT","Portugal","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PRT/prt_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5658,624,"GNB","Guinea-Bissau","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GNB/gnb_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5659,626,"TLS","East Timor","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TLS/tls_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5660,630,"PRI","Puerto Rico","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/PRI/pri_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5661,634,"QAT","Qatar","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/QAT/qat_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5662,638,"REU","Reunion","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/REU/reu_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5663,642,"ROU","Romania","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ROU/rou_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5664,646,"RWA","Rwanda","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/RWA/rwa_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5665,652,"BLM","Saint Barthelemy","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BLM/blm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5666,654,"SHN","Saint Helena","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SHN/shn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5667,659,"KNA","Saint Kitts and Nevis","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/KNA/kna_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5668,660,"AIA","Anguilla","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/AIA/aia_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5669,662,"LCA","Saint Lucia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/LCA/lca_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5670,663,"MAF","Saint Martin (French part)","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MAF/maf_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5671,666,"SPM","Saint Pierre and Miquelon","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SPM/spm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5672,670,"VCT","Saint Vincent and the Grenadines","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/VCT/vct_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5673,674,"SMR","San Marino","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SMR/smr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5674,678,"STP","Sao Tome and Principe","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/STP/stp_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5675,682,"SAU","Saudi Arabia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SAU/sau_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5676,686,"SEN","Senegal","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SEN/sen_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5677,688,"SRB","Serbia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SRB/srb_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5678,690,"SYC","Seychelles","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SYC/syc_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5679,694,"SLE","Sierra Leone","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SLE/sle_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5680,702,"SGP","Singapore","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SGP/sgp_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5681,703,"SVK","Slovakia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SVK/svk_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5682,704,"VNM","Vietnam","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/VNM/vnm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5683,705,"SVN","Slovenia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SVN/svn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5684,706,"SOM","Somalia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SOM/som_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5685,710,"ZAF","South Africa","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ZAF/zaf_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5686,716,"ZWE","Zimbabwe","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ZWE/zwe_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5687,724,"ESP","Spain","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ESP/esp_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5688,728,"SSD","South Sudan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SSD/ssd_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5689,729,"SDN","Sudan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SDN/sdn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5690,732,"ESH","Western Sahara","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ESH/esh_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5691,740,"SUR","Suriname","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SUR/sur_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5692,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SJM/sjm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5693,748,"SWZ","Swaziland","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SWZ/swz_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5694,752,"SWE","Sweden","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SWE/swe_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5695,756,"CHE","Switzerland","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/CHE/che_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5696,760,"SYR","Syria","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SYR/syr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5697,762,"TJK","Tajikistan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TJK/tjk_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5698,764,"THA","Thailand","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/THA/tha_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5699,768,"TGO","Togo","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TGO/tgo_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5700,772,"TKL","Tokelau","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TKL/tkl_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5701,776,"TON","Tonga","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TON/ton_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5702,780,"TTO","Trinidad and Tobago","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TTO/tto_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5703,784,"ARE","United Arab Emirates","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ARE/are_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5704,788,"TUN","Tunisia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TUN/tun_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5705,792,"TUR","Turkey","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TUR/tur_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5706,795,"TKM","Turkmenistan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TKM/tkm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5707,796,"TCA","Turks and Caicos Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TCA/tca_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5708,798,"TUV","Tuvalu","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TUV/tuv_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5709,800,"UGA","Uganda","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/UGA/uga_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5710,804,"UKR","Ukraine","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/UKR/ukr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5711,807,"MKD","Macedonia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/MKD/mkd_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5712,818,"EGY","Egypt","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/EGY/egy_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5713,826,"GBR","United Kingdom","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GBR/gbr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5714,831,"GGY","Guernsey","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/GGY/ggy_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5715,832,"JEY","Jersey","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/JEY/jey_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5716,833,"IMN","Isle of Man","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/IMN/imn_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5717,834,"TZA","Tanzania","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/TZA/tza_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5718,854,"BFA","Burkina Faso","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/BFA/bfa_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5719,858,"URY","Uruguay","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/URY/ury_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5720,860,"UZB","Uzbekistan","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/UZB/uzb_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5721,862,"VEN","Venezuela","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/VEN/ven_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5722,876,"WLF","Wallis and Futuna","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/WLF/wlf_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5723,882,"WSM","Samoa","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/WSM/wsm_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5724,887,"YEM","Yemen","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/YEM/yem_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5725,894,"ZMB","Zambia","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/ZMB/zmb_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5726,900,"KOS","Kosovo","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/KOS/kos_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5727,901,"SPR","Spratly Islands","ppp_2001_UNadj","GIS/Population/Global_2000_2020/2001/SPR/spr_ppp_2001_UNadj.tif","Estimated total number of people per grid-cell 2001 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5728,643,"RUS","Russia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/RUS/rus_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5729,360,"IDN","Indonesia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/IDN/idn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5730,840,"USA","United States","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/USA/usa_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5731,850,"VIR","Virgin_Islands_U_S","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/VIR/vir_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5732,304,"GRL","Greenland","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GRL/grl_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5733,156,"CHN","China","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CHN/chn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5734,36,"AUS","Australia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/AUS/aus_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5735,76,"BRA","Brazil","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BRA/bra_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5736,124,"CAN","Canada","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CAN/can_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5737,152,"CHL","Chile","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CHL/chl_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5738,4,"AFG","Afghanistan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/AFG/afg_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5739,8,"ALB","Albania","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ALB/alb_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5740,10,"ATA","Antarctica","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ATA/ata_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5741,12,"DZA","Algeria","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/DZA/dza_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5742,16,"ASM","American Samoa","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ASM/asm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5743,20,"AND","Andorra","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/AND/and_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5744,24,"AGO","Angola","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/AGO/ago_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5745,28,"ATG","Antigua and Barbuda","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ATG/atg_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5746,31,"AZE","Azerbaijan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/AZE/aze_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5747,32,"ARG","Argentina","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ARG/arg_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5748,40,"AUT","Austria","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/AUT/aut_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5749,44,"BHS","Bahamas","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BHS/bhs_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5750,48,"BHR","Bahrain","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BHR/bhr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5751,50,"BGD","Bangladesh","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BGD/bgd_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5752,51,"ARM","Armenia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ARM/arm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5753,52,"BRB","Barbados","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BRB/brb_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5754,56,"BEL","Belgium","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BEL/bel_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5755,60,"BMU","Bermuda","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BMU/bmu_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5756,64,"BTN","Bhutan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BTN/btn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5757,68,"BOL","Bolivia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BOL/bol_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5758,70,"BIH","Bosnia and Herzegovina","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BIH/bih_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5759,72,"BWA","Botswana","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BWA/bwa_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5760,74,"BVT","Bouvet Island","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BVT/bvt_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5761,84,"BLZ","Belize","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BLZ/blz_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5762,86,"IOT","British Indian Ocean Territory","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/IOT/iot_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5763,90,"SLB","Solomon Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SLB/slb_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5764,92,"VGB","British Virgin Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/VGB/vgb_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5765,96,"BRN","Brunei","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BRN/brn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5766,100,"BGR","Bulgaria","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BGR/bgr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5767,104,"MMR","Myanmar","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MMR/mmr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5768,108,"BDI","Burundi","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BDI/bdi_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5769,112,"BLR","Belarus","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BLR/blr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5770,116,"KHM","Cambodia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/KHM/khm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5771,120,"CMR","Cameroon","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CMR/cmr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5772,132,"CPV","Cape Verde","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CPV/cpv_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5773,136,"CYM","Cayman Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CYM/cym_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5774,140,"CAF","Central African Republic","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CAF/caf_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5775,144,"LKA","Sri Lanka","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LKA/lka_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5776,148,"TCD","Chad","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TCD/tcd_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5777,158,"TWN","Taiwan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TWN/twn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5778,170,"COL","Colombia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/COL/col_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5779,174,"COM","Comoros","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/COM/com_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5780,175,"MYT","Mayotte","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MYT/myt_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5781,178,"COG","Republic of Congo","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/COG/cog_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5782,180,"COD","Democratic Republic of the Congo","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/COD/cod_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5783,184,"COK","Cook Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/COK/cok_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5784,188,"CRI","Costa Rica","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CRI/cri_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5785,191,"HRV","Croatia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/HRV/hrv_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5786,192,"CUB","Cuba","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CUB/cub_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5787,196,"CYP","Cyprus","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CYP/cyp_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5788,203,"CZE","Czech Republic","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CZE/cze_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5789,204,"BEN","Benin","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BEN/ben_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5790,208,"DNK","Denmark","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/DNK/dnk_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5791,212,"DMA","Dominica","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/DMA/dma_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5792,214,"DOM","Dominican Republic","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/DOM/dom_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5793,218,"ECU","Ecuador","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ECU/ecu_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5794,222,"SLV","El Salvador","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SLV/slv_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5795,226,"GNQ","Equatorial Guinea","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GNQ/gnq_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5796,231,"ETH","Ethiopia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ETH/eth_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5797,232,"ERI","Eritrea","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ERI/eri_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5798,233,"EST","Estonia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/EST/est_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5799,234,"FRO","Faroe Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/FRO/fro_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5800,238,"FLK","Falkland Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/FLK/flk_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5801,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SGS/sgs_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5802,242,"FJI","Fiji","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/FJI/fji_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5803,246,"FIN","Finland","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/FIN/fin_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5804,248,"ALA","Aland Islands ","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ALA/ala_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5805,250,"FRA","France","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/FRA/fra_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5806,254,"GUF","French Guiana","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GUF/guf_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5807,258,"PYF","French Polynesia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PYF/pyf_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5808,260,"ATF","French Southern Territories","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ATF/atf_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5809,262,"DJI","Djibouti","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/DJI/dji_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5810,266,"GAB","Gabon","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GAB/gab_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5811,268,"GEO","Georgia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GEO/geo_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5812,270,"GMB","Gambia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GMB/gmb_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5813,275,"PSE","Palestina","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PSE/pse_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5814,276,"DEU","Germany","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/DEU/deu_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5815,288,"GHA","Ghana","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GHA/gha_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5816,292,"GIB","Gibraltar","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GIB/gib_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5817,296,"KIR","Kiribati","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/KIR/kir_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5818,300,"GRC","Greece","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GRC/grc_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5819,308,"GRD","Grenada","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GRD/grd_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5820,312,"GLP","Guadeloupe","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GLP/glp_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5821,316,"GUM","Guam","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GUM/gum_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5822,320,"GTM","Guatemala","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GTM/gtm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5823,324,"GIN","Guinea","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GIN/gin_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5824,328,"GUY","Guyana","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GUY/guy_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5825,332,"HTI","Haiti","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/HTI/hti_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5826,334,"HMD","Heard Island and McDonald Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/HMD/hmd_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5827,336,"VAT","Vatican City","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/VAT/vat_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5828,340,"HND","Honduras","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/HND/hnd_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5829,344,"HKG","Hong Kong","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/HKG/hkg_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5830,348,"HUN","Hungary","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/HUN/hun_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5831,352,"ISL","Iceland","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ISL/isl_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5832,356,"IND","India","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/IND/ind_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5833,364,"IRN","Iran","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/IRN/irn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5834,368,"IRQ","Iraq","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/IRQ/irq_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5835,372,"IRL","Ireland","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/IRL/irl_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5836,376,"ISR","Israel","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ISR/isr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5837,380,"ITA","Italy","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ITA/ita_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5838,384,"CIV","CIte dIvoire","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CIV/civ_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5839,388,"JAM","Jamaica","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/JAM/jam_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5840,392,"JPN","Japan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/JPN/jpn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5841,398,"KAZ","Kazakhstan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/KAZ/kaz_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5842,400,"JOR","Jordan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/JOR/jor_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5843,404,"KEN","Kenya","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/KEN/ken_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5844,408,"PRK","North Korea","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PRK/prk_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5845,410,"KOR","South Korea","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/KOR/kor_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5846,414,"KWT","Kuwait","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/KWT/kwt_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5847,417,"KGZ","Kyrgyzstan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/KGZ/kgz_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5848,418,"LAO","Laos","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LAO/lao_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5849,422,"LBN","Lebanon","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LBN/lbn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5850,426,"LSO","Lesotho","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LSO/lso_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5851,428,"LVA","Latvia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LVA/lva_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5852,430,"LBR","Liberia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LBR/lbr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5853,434,"LBY","Libya","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LBY/lby_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5854,438,"LIE","Liechtenstein","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LIE/lie_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5855,440,"LTU","Lithuania","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LTU/ltu_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5856,442,"LUX","Luxembourg","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LUX/lux_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5857,446,"MAC","Macao","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MAC/mac_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5858,450,"MDG","Madagascar","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MDG/mdg_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5859,454,"MWI","Malawi","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MWI/mwi_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5860,458,"MYS","Malaysia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MYS/mys_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5861,462,"MDV","Maldives","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MDV/mdv_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5862,466,"MLI","Mali","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MLI/mli_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5863,470,"MLT","Malta","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MLT/mlt_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5864,474,"MTQ","Martinique","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MTQ/mtq_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5865,478,"MRT","Mauritania","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MRT/mrt_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5866,480,"MUS","Mauritius","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MUS/mus_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5867,484,"MEX","Mexico","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MEX/mex_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5868,492,"MCO","Monaco","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MCO/mco_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5869,496,"MNG","Mongolia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MNG/mng_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5870,498,"MDA","Moldova","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MDA/mda_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5871,499,"MNE","Montenegro","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MNE/mne_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5872,500,"MSR","Montserrat","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MSR/msr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5873,504,"MAR","Morocco","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MAR/mar_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5874,508,"MOZ","Mozambique","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MOZ/moz_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5875,512,"OMN","Oman","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/OMN/omn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5876,516,"NAM","Namibia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NAM/nam_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5877,520,"NRU","Nauru","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NRU/nru_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5878,524,"NPL","Nepal","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NPL/npl_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5879,528,"NLD","Netherlands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NLD/nld_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5880,531,"CUW","Curacao","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CUW/cuw_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5881,533,"ABW","Aruba","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ABW/abw_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5882,534,"SXM","Sint Maarten (Dutch part)","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SXM/sxm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5883,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BES/bes_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5884,540,"NCL","New Caledonia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NCL/ncl_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5885,548,"VUT","Vanuatu","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/VUT/vut_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5886,554,"NZL","New Zealand","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NZL/nzl_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5887,558,"NIC","Nicaragua","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NIC/nic_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5888,562,"NER","Niger","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NER/ner_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5889,566,"NGA","Nigeria","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NGA/nga_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5890,570,"NIU","Niue","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NIU/niu_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5891,574,"NFK","Norfolk Island","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NFK/nfk_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5892,578,"NOR","Norway","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/NOR/nor_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5893,580,"MNP","Northern Mariana Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MNP/mnp_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5894,581,"UMI","United States Minor Outlying Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/UMI/umi_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5895,583,"FSM","Micronesia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/FSM/fsm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5896,584,"MHL","Marshall Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MHL/mhl_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5897,585,"PLW","Palau","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PLW/plw_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5898,586,"PAK","Pakistan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PAK/pak_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5899,591,"PAN","Panama","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PAN/pan_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5900,598,"PNG","Papua New Guinea","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PNG/png_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5901,600,"PRY","Paraguay","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PRY/pry_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5902,604,"PER","Peru","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PER/per_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5903,608,"PHL","Philippines","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PHL/phl_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5904,612,"PCN","Pitcairn Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PCN/pcn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5905,616,"POL","Poland","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/POL/pol_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5906,620,"PRT","Portugal","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PRT/prt_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5907,624,"GNB","Guinea-Bissau","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GNB/gnb_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5908,626,"TLS","East Timor","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TLS/tls_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5909,630,"PRI","Puerto Rico","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/PRI/pri_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5910,634,"QAT","Qatar","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/QAT/qat_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5911,638,"REU","Reunion","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/REU/reu_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5912,642,"ROU","Romania","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ROU/rou_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5913,646,"RWA","Rwanda","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/RWA/rwa_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5914,652,"BLM","Saint Barthelemy","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BLM/blm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5915,654,"SHN","Saint Helena","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SHN/shn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5916,659,"KNA","Saint Kitts and Nevis","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/KNA/kna_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5917,660,"AIA","Anguilla","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/AIA/aia_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5918,662,"LCA","Saint Lucia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/LCA/lca_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5919,663,"MAF","Saint Martin (French part)","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MAF/maf_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5920,666,"SPM","Saint Pierre and Miquelon","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SPM/spm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5921,670,"VCT","Saint Vincent and the Grenadines","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/VCT/vct_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5922,674,"SMR","San Marino","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SMR/smr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5923,678,"STP","Sao Tome and Principe","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/STP/stp_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5924,682,"SAU","Saudi Arabia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SAU/sau_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5925,686,"SEN","Senegal","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SEN/sen_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5926,688,"SRB","Serbia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SRB/srb_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5927,690,"SYC","Seychelles","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SYC/syc_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5928,694,"SLE","Sierra Leone","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SLE/sle_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5929,702,"SGP","Singapore","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SGP/sgp_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5930,703,"SVK","Slovakia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SVK/svk_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5931,704,"VNM","Vietnam","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/VNM/vnm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5932,705,"SVN","Slovenia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SVN/svn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5933,706,"SOM","Somalia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SOM/som_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5934,710,"ZAF","South Africa","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ZAF/zaf_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5935,716,"ZWE","Zimbabwe","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ZWE/zwe_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5936,724,"ESP","Spain","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ESP/esp_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5937,728,"SSD","South Sudan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SSD/ssd_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5938,729,"SDN","Sudan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SDN/sdn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5939,732,"ESH","Western Sahara","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ESH/esh_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5940,740,"SUR","Suriname","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SUR/sur_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5941,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SJM/sjm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5942,748,"SWZ","Swaziland","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SWZ/swz_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5943,752,"SWE","Sweden","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SWE/swe_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5944,756,"CHE","Switzerland","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/CHE/che_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5945,760,"SYR","Syria","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SYR/syr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5946,762,"TJK","Tajikistan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TJK/tjk_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5947,764,"THA","Thailand","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/THA/tha_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5948,768,"TGO","Togo","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TGO/tgo_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5949,772,"TKL","Tokelau","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TKL/tkl_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5950,776,"TON","Tonga","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TON/ton_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5951,780,"TTO","Trinidad and Tobago","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TTO/tto_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5952,784,"ARE","United Arab Emirates","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ARE/are_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5953,788,"TUN","Tunisia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TUN/tun_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5954,792,"TUR","Turkey","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TUR/tur_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5955,795,"TKM","Turkmenistan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TKM/tkm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5956,796,"TCA","Turks and Caicos Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TCA/tca_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5957,798,"TUV","Tuvalu","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TUV/tuv_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5958,800,"UGA","Uganda","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/UGA/uga_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5959,804,"UKR","Ukraine","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/UKR/ukr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5960,807,"MKD","Macedonia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/MKD/mkd_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5961,818,"EGY","Egypt","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/EGY/egy_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5962,826,"GBR","United Kingdom","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GBR/gbr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5963,831,"GGY","Guernsey","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/GGY/ggy_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5964,832,"JEY","Jersey","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/JEY/jey_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5965,833,"IMN","Isle of Man","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/IMN/imn_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5966,834,"TZA","Tanzania","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/TZA/tza_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5967,854,"BFA","Burkina Faso","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/BFA/bfa_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5968,858,"URY","Uruguay","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/URY/ury_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5969,860,"UZB","Uzbekistan","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/UZB/uzb_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5970,862,"VEN","Venezuela","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/VEN/ven_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5971,876,"WLF","Wallis and Futuna","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/WLF/wlf_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5972,882,"WSM","Samoa","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/WSM/wsm_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5973,887,"YEM","Yemen","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/YEM/yem_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5974,894,"ZMB","Zambia","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/ZMB/zmb_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5975,900,"KOS","Kosovo","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/KOS/kos_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5976,901,"SPR","Spratly Islands","ppp_2002_UNadj","GIS/Population/Global_2000_2020/2002/SPR/spr_ppp_2002_UNadj.tif","Estimated total number of people per grid-cell 2002 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5977,643,"RUS","Russia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/RUS/rus_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5978,360,"IDN","Indonesia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/IDN/idn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5979,840,"USA","United States","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/USA/usa_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5980,850,"VIR","Virgin_Islands_U_S","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/VIR/vir_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5981,304,"GRL","Greenland","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GRL/grl_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5982,156,"CHN","China","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CHN/chn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5983,36,"AUS","Australia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/AUS/aus_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5984,76,"BRA","Brazil","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BRA/bra_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5985,124,"CAN","Canada","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CAN/can_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5986,152,"CHL","Chile","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CHL/chl_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5987,4,"AFG","Afghanistan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/AFG/afg_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5988,8,"ALB","Albania","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ALB/alb_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5989,10,"ATA","Antarctica","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ATA/ata_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5990,12,"DZA","Algeria","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/DZA/dza_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5991,16,"ASM","American Samoa","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ASM/asm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5992,20,"AND","Andorra","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/AND/and_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5993,24,"AGO","Angola","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/AGO/ago_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5994,28,"ATG","Antigua and Barbuda","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ATG/atg_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5995,31,"AZE","Azerbaijan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/AZE/aze_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5996,32,"ARG","Argentina","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ARG/arg_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5997,40,"AUT","Austria","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/AUT/aut_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5998,44,"BHS","Bahamas","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BHS/bhs_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
5999,48,"BHR","Bahrain","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BHR/bhr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6000,50,"BGD","Bangladesh","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BGD/bgd_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6001,51,"ARM","Armenia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ARM/arm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6002,52,"BRB","Barbados","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BRB/brb_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6003,56,"BEL","Belgium","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BEL/bel_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6004,60,"BMU","Bermuda","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BMU/bmu_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6005,64,"BTN","Bhutan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BTN/btn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6006,68,"BOL","Bolivia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BOL/bol_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6007,70,"BIH","Bosnia and Herzegovina","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BIH/bih_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6008,72,"BWA","Botswana","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BWA/bwa_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6009,74,"BVT","Bouvet Island","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BVT/bvt_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6010,84,"BLZ","Belize","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BLZ/blz_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6011,86,"IOT","British Indian Ocean Territory","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/IOT/iot_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6012,90,"SLB","Solomon Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SLB/slb_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6013,92,"VGB","British Virgin Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/VGB/vgb_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6014,96,"BRN","Brunei","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BRN/brn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6015,100,"BGR","Bulgaria","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BGR/bgr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6016,104,"MMR","Myanmar","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MMR/mmr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6017,108,"BDI","Burundi","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BDI/bdi_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6018,112,"BLR","Belarus","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BLR/blr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6019,116,"KHM","Cambodia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/KHM/khm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6020,120,"CMR","Cameroon","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CMR/cmr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6021,132,"CPV","Cape Verde","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CPV/cpv_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6022,136,"CYM","Cayman Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CYM/cym_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6023,140,"CAF","Central African Republic","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CAF/caf_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6024,144,"LKA","Sri Lanka","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LKA/lka_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6025,148,"TCD","Chad","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TCD/tcd_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6026,158,"TWN","Taiwan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TWN/twn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6027,170,"COL","Colombia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/COL/col_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6028,174,"COM","Comoros","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/COM/com_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6029,175,"MYT","Mayotte","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MYT/myt_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6030,178,"COG","Republic of Congo","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/COG/cog_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6031,180,"COD","Democratic Republic of the Congo","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/COD/cod_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6032,184,"COK","Cook Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/COK/cok_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6033,188,"CRI","Costa Rica","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CRI/cri_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6034,191,"HRV","Croatia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/HRV/hrv_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6035,192,"CUB","Cuba","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CUB/cub_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6036,196,"CYP","Cyprus","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CYP/cyp_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6037,203,"CZE","Czech Republic","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CZE/cze_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6038,204,"BEN","Benin","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BEN/ben_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6039,208,"DNK","Denmark","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/DNK/dnk_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6040,212,"DMA","Dominica","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/DMA/dma_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6041,214,"DOM","Dominican Republic","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/DOM/dom_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6042,218,"ECU","Ecuador","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ECU/ecu_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6043,222,"SLV","El Salvador","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SLV/slv_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6044,226,"GNQ","Equatorial Guinea","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GNQ/gnq_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6045,231,"ETH","Ethiopia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ETH/eth_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6046,232,"ERI","Eritrea","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ERI/eri_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6047,233,"EST","Estonia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/EST/est_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6048,234,"FRO","Faroe Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/FRO/fro_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6049,238,"FLK","Falkland Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/FLK/flk_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6050,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SGS/sgs_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6051,242,"FJI","Fiji","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/FJI/fji_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6052,246,"FIN","Finland","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/FIN/fin_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6053,248,"ALA","Aland Islands ","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ALA/ala_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6054,250,"FRA","France","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/FRA/fra_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6055,254,"GUF","French Guiana","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GUF/guf_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6056,258,"PYF","French Polynesia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PYF/pyf_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6057,260,"ATF","French Southern Territories","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ATF/atf_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6058,262,"DJI","Djibouti","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/DJI/dji_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6059,266,"GAB","Gabon","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GAB/gab_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6060,268,"GEO","Georgia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GEO/geo_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6061,270,"GMB","Gambia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GMB/gmb_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6062,275,"PSE","Palestina","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PSE/pse_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6063,276,"DEU","Germany","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/DEU/deu_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6064,288,"GHA","Ghana","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GHA/gha_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6065,292,"GIB","Gibraltar","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GIB/gib_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6066,296,"KIR","Kiribati","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/KIR/kir_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6067,300,"GRC","Greece","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GRC/grc_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6068,308,"GRD","Grenada","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GRD/grd_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6069,312,"GLP","Guadeloupe","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GLP/glp_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6070,316,"GUM","Guam","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GUM/gum_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6071,320,"GTM","Guatemala","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GTM/gtm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6072,324,"GIN","Guinea","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GIN/gin_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6073,328,"GUY","Guyana","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GUY/guy_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6074,332,"HTI","Haiti","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/HTI/hti_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6075,334,"HMD","Heard Island and McDonald Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/HMD/hmd_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6076,336,"VAT","Vatican City","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/VAT/vat_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6077,340,"HND","Honduras","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/HND/hnd_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6078,344,"HKG","Hong Kong","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/HKG/hkg_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6079,348,"HUN","Hungary","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/HUN/hun_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6080,352,"ISL","Iceland","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ISL/isl_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6081,356,"IND","India","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/IND/ind_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6082,364,"IRN","Iran","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/IRN/irn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6083,368,"IRQ","Iraq","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/IRQ/irq_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6084,372,"IRL","Ireland","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/IRL/irl_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6085,376,"ISR","Israel","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ISR/isr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6086,380,"ITA","Italy","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ITA/ita_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6087,384,"CIV","CIte dIvoire","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CIV/civ_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6088,388,"JAM","Jamaica","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/JAM/jam_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6089,392,"JPN","Japan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/JPN/jpn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6090,398,"KAZ","Kazakhstan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/KAZ/kaz_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6091,400,"JOR","Jordan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/JOR/jor_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6092,404,"KEN","Kenya","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/KEN/ken_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6093,408,"PRK","North Korea","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PRK/prk_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6094,410,"KOR","South Korea","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/KOR/kor_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6095,414,"KWT","Kuwait","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/KWT/kwt_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6096,417,"KGZ","Kyrgyzstan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/KGZ/kgz_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6097,418,"LAO","Laos","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LAO/lao_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6098,422,"LBN","Lebanon","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LBN/lbn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6099,426,"LSO","Lesotho","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LSO/lso_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6100,428,"LVA","Latvia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LVA/lva_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6101,430,"LBR","Liberia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LBR/lbr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6102,434,"LBY","Libya","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LBY/lby_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6103,438,"LIE","Liechtenstein","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LIE/lie_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6104,440,"LTU","Lithuania","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LTU/ltu_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6105,442,"LUX","Luxembourg","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LUX/lux_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6106,446,"MAC","Macao","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MAC/mac_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6107,450,"MDG","Madagascar","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MDG/mdg_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6108,454,"MWI","Malawi","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MWI/mwi_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6109,458,"MYS","Malaysia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MYS/mys_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6110,462,"MDV","Maldives","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MDV/mdv_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6111,466,"MLI","Mali","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MLI/mli_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6112,470,"MLT","Malta","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MLT/mlt_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6113,474,"MTQ","Martinique","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MTQ/mtq_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6114,478,"MRT","Mauritania","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MRT/mrt_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6115,480,"MUS","Mauritius","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MUS/mus_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6116,484,"MEX","Mexico","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MEX/mex_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6117,492,"MCO","Monaco","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MCO/mco_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6118,496,"MNG","Mongolia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MNG/mng_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6119,498,"MDA","Moldova","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MDA/mda_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6120,499,"MNE","Montenegro","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MNE/mne_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6121,500,"MSR","Montserrat","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MSR/msr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6122,504,"MAR","Morocco","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MAR/mar_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6123,508,"MOZ","Mozambique","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MOZ/moz_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6124,512,"OMN","Oman","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/OMN/omn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6125,516,"NAM","Namibia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NAM/nam_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6126,520,"NRU","Nauru","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NRU/nru_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6127,524,"NPL","Nepal","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NPL/npl_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6128,528,"NLD","Netherlands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NLD/nld_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6129,531,"CUW","Curacao","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CUW/cuw_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6130,533,"ABW","Aruba","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ABW/abw_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6131,534,"SXM","Sint Maarten (Dutch part)","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SXM/sxm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6132,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BES/bes_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6133,540,"NCL","New Caledonia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NCL/ncl_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6134,548,"VUT","Vanuatu","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/VUT/vut_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6135,554,"NZL","New Zealand","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NZL/nzl_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6136,558,"NIC","Nicaragua","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NIC/nic_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6137,562,"NER","Niger","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NER/ner_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6138,566,"NGA","Nigeria","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NGA/nga_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6139,570,"NIU","Niue","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NIU/niu_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6140,574,"NFK","Norfolk Island","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NFK/nfk_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6141,578,"NOR","Norway","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/NOR/nor_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6142,580,"MNP","Northern Mariana Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MNP/mnp_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6143,581,"UMI","United States Minor Outlying Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/UMI/umi_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6144,583,"FSM","Micronesia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/FSM/fsm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6145,584,"MHL","Marshall Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MHL/mhl_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6146,585,"PLW","Palau","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PLW/plw_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6147,586,"PAK","Pakistan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PAK/pak_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6148,591,"PAN","Panama","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PAN/pan_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6149,598,"PNG","Papua New Guinea","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PNG/png_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6150,600,"PRY","Paraguay","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PRY/pry_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6151,604,"PER","Peru","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PER/per_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6152,608,"PHL","Philippines","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PHL/phl_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6153,612,"PCN","Pitcairn Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PCN/pcn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6154,616,"POL","Poland","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/POL/pol_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6155,620,"PRT","Portugal","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PRT/prt_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6156,624,"GNB","Guinea-Bissau","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GNB/gnb_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6157,626,"TLS","East Timor","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TLS/tls_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6158,630,"PRI","Puerto Rico","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/PRI/pri_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6159,634,"QAT","Qatar","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/QAT/qat_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6160,638,"REU","Reunion","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/REU/reu_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6161,642,"ROU","Romania","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ROU/rou_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6162,646,"RWA","Rwanda","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/RWA/rwa_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6163,652,"BLM","Saint Barthelemy","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BLM/blm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6164,654,"SHN","Saint Helena","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SHN/shn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6165,659,"KNA","Saint Kitts and Nevis","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/KNA/kna_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6166,660,"AIA","Anguilla","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/AIA/aia_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6167,662,"LCA","Saint Lucia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/LCA/lca_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6168,663,"MAF","Saint Martin (French part)","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MAF/maf_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6169,666,"SPM","Saint Pierre and Miquelon","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SPM/spm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6170,670,"VCT","Saint Vincent and the Grenadines","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/VCT/vct_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6171,674,"SMR","San Marino","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SMR/smr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6172,678,"STP","Sao Tome and Principe","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/STP/stp_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6173,682,"SAU","Saudi Arabia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SAU/sau_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6174,686,"SEN","Senegal","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SEN/sen_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6175,688,"SRB","Serbia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SRB/srb_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6176,690,"SYC","Seychelles","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SYC/syc_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6177,694,"SLE","Sierra Leone","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SLE/sle_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6178,702,"SGP","Singapore","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SGP/sgp_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6179,703,"SVK","Slovakia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SVK/svk_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6180,704,"VNM","Vietnam","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/VNM/vnm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6181,705,"SVN","Slovenia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SVN/svn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6182,706,"SOM","Somalia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SOM/som_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6183,710,"ZAF","South Africa","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ZAF/zaf_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6184,716,"ZWE","Zimbabwe","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ZWE/zwe_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6185,724,"ESP","Spain","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ESP/esp_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6186,728,"SSD","South Sudan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SSD/ssd_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6187,729,"SDN","Sudan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SDN/sdn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6188,732,"ESH","Western Sahara","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ESH/esh_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6189,740,"SUR","Suriname","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SUR/sur_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6190,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SJM/sjm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6191,748,"SWZ","Swaziland","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SWZ/swz_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6192,752,"SWE","Sweden","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SWE/swe_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6193,756,"CHE","Switzerland","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/CHE/che_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6194,760,"SYR","Syria","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SYR/syr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6195,762,"TJK","Tajikistan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TJK/tjk_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6196,764,"THA","Thailand","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/THA/tha_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6197,768,"TGO","Togo","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TGO/tgo_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6198,772,"TKL","Tokelau","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TKL/tkl_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6199,776,"TON","Tonga","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TON/ton_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6200,780,"TTO","Trinidad and Tobago","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TTO/tto_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6201,784,"ARE","United Arab Emirates","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ARE/are_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6202,788,"TUN","Tunisia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TUN/tun_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6203,792,"TUR","Turkey","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TUR/tur_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6204,795,"TKM","Turkmenistan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TKM/tkm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6205,796,"TCA","Turks and Caicos Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TCA/tca_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6206,798,"TUV","Tuvalu","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TUV/tuv_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6207,800,"UGA","Uganda","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/UGA/uga_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6208,804,"UKR","Ukraine","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/UKR/ukr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6209,807,"MKD","Macedonia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/MKD/mkd_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6210,818,"EGY","Egypt","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/EGY/egy_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6211,826,"GBR","United Kingdom","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GBR/gbr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6212,831,"GGY","Guernsey","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/GGY/ggy_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6213,832,"JEY","Jersey","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/JEY/jey_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6214,833,"IMN","Isle of Man","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/IMN/imn_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6215,834,"TZA","Tanzania","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/TZA/tza_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6216,854,"BFA","Burkina Faso","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/BFA/bfa_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6217,858,"URY","Uruguay","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/URY/ury_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6218,860,"UZB","Uzbekistan","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/UZB/uzb_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6219,862,"VEN","Venezuela","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/VEN/ven_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6220,876,"WLF","Wallis and Futuna","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/WLF/wlf_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6221,882,"WSM","Samoa","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/WSM/wsm_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6222,887,"YEM","Yemen","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/YEM/yem_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6223,894,"ZMB","Zambia","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/ZMB/zmb_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6224,900,"KOS","Kosovo","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/KOS/kos_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6225,901,"SPR","Spratly Islands","ppp_2003_UNadj","GIS/Population/Global_2000_2020/2003/SPR/spr_ppp_2003_UNadj.tif","Estimated total number of people per grid-cell 2003 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6226,643,"RUS","Russia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/RUS/rus_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6227,360,"IDN","Indonesia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/IDN/idn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6228,840,"USA","United States","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/USA/usa_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6229,850,"VIR","Virgin_Islands_U_S","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/VIR/vir_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6230,304,"GRL","Greenland","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GRL/grl_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6231,156,"CHN","China","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CHN/chn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6232,36,"AUS","Australia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/AUS/aus_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6233,76,"BRA","Brazil","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BRA/bra_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6234,124,"CAN","Canada","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CAN/can_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6235,152,"CHL","Chile","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CHL/chl_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6236,4,"AFG","Afghanistan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/AFG/afg_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6237,8,"ALB","Albania","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ALB/alb_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6238,10,"ATA","Antarctica","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ATA/ata_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6239,12,"DZA","Algeria","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/DZA/dza_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6240,16,"ASM","American Samoa","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ASM/asm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6241,20,"AND","Andorra","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/AND/and_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6242,24,"AGO","Angola","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/AGO/ago_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6243,28,"ATG","Antigua and Barbuda","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ATG/atg_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6244,31,"AZE","Azerbaijan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/AZE/aze_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6245,32,"ARG","Argentina","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ARG/arg_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6246,40,"AUT","Austria","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/AUT/aut_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6247,44,"BHS","Bahamas","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BHS/bhs_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6248,48,"BHR","Bahrain","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BHR/bhr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6249,50,"BGD","Bangladesh","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BGD/bgd_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6250,51,"ARM","Armenia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ARM/arm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6251,52,"BRB","Barbados","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BRB/brb_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6252,56,"BEL","Belgium","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BEL/bel_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6253,60,"BMU","Bermuda","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BMU/bmu_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6254,64,"BTN","Bhutan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BTN/btn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6255,68,"BOL","Bolivia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BOL/bol_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6256,70,"BIH","Bosnia and Herzegovina","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BIH/bih_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6257,72,"BWA","Botswana","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BWA/bwa_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6258,74,"BVT","Bouvet Island","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BVT/bvt_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6259,84,"BLZ","Belize","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BLZ/blz_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6260,86,"IOT","British Indian Ocean Territory","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/IOT/iot_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6261,90,"SLB","Solomon Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SLB/slb_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6262,92,"VGB","British Virgin Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/VGB/vgb_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6263,96,"BRN","Brunei","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BRN/brn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6264,100,"BGR","Bulgaria","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BGR/bgr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6265,104,"MMR","Myanmar","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MMR/mmr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6266,108,"BDI","Burundi","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BDI/bdi_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6267,112,"BLR","Belarus","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BLR/blr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6268,116,"KHM","Cambodia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/KHM/khm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6269,120,"CMR","Cameroon","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CMR/cmr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6270,132,"CPV","Cape Verde","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CPV/cpv_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6271,136,"CYM","Cayman Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CYM/cym_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6272,140,"CAF","Central African Republic","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CAF/caf_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6273,144,"LKA","Sri Lanka","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LKA/lka_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6274,148,"TCD","Chad","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TCD/tcd_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6275,158,"TWN","Taiwan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TWN/twn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6276,170,"COL","Colombia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/COL/col_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6277,174,"COM","Comoros","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/COM/com_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6278,175,"MYT","Mayotte","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MYT/myt_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6279,178,"COG","Republic of Congo","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/COG/cog_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6280,180,"COD","Democratic Republic of the Congo","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/COD/cod_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6281,184,"COK","Cook Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/COK/cok_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6282,188,"CRI","Costa Rica","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CRI/cri_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6283,191,"HRV","Croatia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/HRV/hrv_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6284,192,"CUB","Cuba","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CUB/cub_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6285,196,"CYP","Cyprus","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CYP/cyp_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6286,203,"CZE","Czech Republic","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CZE/cze_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6287,204,"BEN","Benin","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BEN/ben_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6288,208,"DNK","Denmark","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/DNK/dnk_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6289,212,"DMA","Dominica","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/DMA/dma_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6290,214,"DOM","Dominican Republic","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/DOM/dom_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6291,218,"ECU","Ecuador","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ECU/ecu_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6292,222,"SLV","El Salvador","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SLV/slv_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6293,226,"GNQ","Equatorial Guinea","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GNQ/gnq_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6294,231,"ETH","Ethiopia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ETH/eth_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6295,232,"ERI","Eritrea","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ERI/eri_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6296,233,"EST","Estonia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/EST/est_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6297,234,"FRO","Faroe Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/FRO/fro_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6298,238,"FLK","Falkland Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/FLK/flk_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6299,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SGS/sgs_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6300,242,"FJI","Fiji","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/FJI/fji_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6301,246,"FIN","Finland","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/FIN/fin_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6302,248,"ALA","Aland Islands ","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ALA/ala_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6303,250,"FRA","France","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/FRA/fra_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6304,254,"GUF","French Guiana","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GUF/guf_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6305,258,"PYF","French Polynesia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PYF/pyf_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6306,260,"ATF","French Southern Territories","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ATF/atf_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6307,262,"DJI","Djibouti","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/DJI/dji_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6308,266,"GAB","Gabon","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GAB/gab_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6309,268,"GEO","Georgia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GEO/geo_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6310,270,"GMB","Gambia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GMB/gmb_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6311,275,"PSE","Palestina","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PSE/pse_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6312,276,"DEU","Germany","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/DEU/deu_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6313,288,"GHA","Ghana","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GHA/gha_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6314,292,"GIB","Gibraltar","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GIB/gib_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6315,296,"KIR","Kiribati","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/KIR/kir_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6316,300,"GRC","Greece","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GRC/grc_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6317,308,"GRD","Grenada","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GRD/grd_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6318,312,"GLP","Guadeloupe","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GLP/glp_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6319,316,"GUM","Guam","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GUM/gum_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6320,320,"GTM","Guatemala","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GTM/gtm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6321,324,"GIN","Guinea","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GIN/gin_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6322,328,"GUY","Guyana","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GUY/guy_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6323,332,"HTI","Haiti","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/HTI/hti_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6324,334,"HMD","Heard Island and McDonald Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/HMD/hmd_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6325,336,"VAT","Vatican City","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/VAT/vat_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6326,340,"HND","Honduras","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/HND/hnd_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6327,344,"HKG","Hong Kong","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/HKG/hkg_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6328,348,"HUN","Hungary","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/HUN/hun_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6329,352,"ISL","Iceland","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ISL/isl_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6330,356,"IND","India","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/IND/ind_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6331,364,"IRN","Iran","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/IRN/irn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6332,368,"IRQ","Iraq","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/IRQ/irq_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6333,372,"IRL","Ireland","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/IRL/irl_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6334,376,"ISR","Israel","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ISR/isr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6335,380,"ITA","Italy","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ITA/ita_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6336,384,"CIV","CIte dIvoire","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CIV/civ_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6337,388,"JAM","Jamaica","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/JAM/jam_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6338,392,"JPN","Japan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/JPN/jpn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6339,398,"KAZ","Kazakhstan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/KAZ/kaz_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6340,400,"JOR","Jordan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/JOR/jor_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6341,404,"KEN","Kenya","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/KEN/ken_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6342,408,"PRK","North Korea","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PRK/prk_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6343,410,"KOR","South Korea","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/KOR/kor_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6344,414,"KWT","Kuwait","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/KWT/kwt_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6345,417,"KGZ","Kyrgyzstan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/KGZ/kgz_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6346,418,"LAO","Laos","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LAO/lao_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6347,422,"LBN","Lebanon","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LBN/lbn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6348,426,"LSO","Lesotho","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LSO/lso_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6349,428,"LVA","Latvia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LVA/lva_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6350,430,"LBR","Liberia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LBR/lbr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6351,434,"LBY","Libya","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LBY/lby_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6352,438,"LIE","Liechtenstein","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LIE/lie_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6353,440,"LTU","Lithuania","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LTU/ltu_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6354,442,"LUX","Luxembourg","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LUX/lux_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6355,446,"MAC","Macao","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MAC/mac_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6356,450,"MDG","Madagascar","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MDG/mdg_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6357,454,"MWI","Malawi","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MWI/mwi_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6358,458,"MYS","Malaysia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MYS/mys_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6359,462,"MDV","Maldives","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MDV/mdv_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6360,466,"MLI","Mali","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MLI/mli_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6361,470,"MLT","Malta","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MLT/mlt_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6362,474,"MTQ","Martinique","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MTQ/mtq_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6363,478,"MRT","Mauritania","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MRT/mrt_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6364,480,"MUS","Mauritius","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MUS/mus_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6365,484,"MEX","Mexico","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MEX/mex_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6366,492,"MCO","Monaco","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MCO/mco_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6367,496,"MNG","Mongolia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MNG/mng_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6368,498,"MDA","Moldova","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MDA/mda_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6369,499,"MNE","Montenegro","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MNE/mne_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6370,500,"MSR","Montserrat","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MSR/msr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6371,504,"MAR","Morocco","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MAR/mar_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6372,508,"MOZ","Mozambique","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MOZ/moz_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6373,512,"OMN","Oman","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/OMN/omn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6374,516,"NAM","Namibia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NAM/nam_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6375,520,"NRU","Nauru","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NRU/nru_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6376,524,"NPL","Nepal","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NPL/npl_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6377,528,"NLD","Netherlands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NLD/nld_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6378,531,"CUW","Curacao","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CUW/cuw_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6379,533,"ABW","Aruba","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ABW/abw_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6380,534,"SXM","Sint Maarten (Dutch part)","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SXM/sxm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6381,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BES/bes_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6382,540,"NCL","New Caledonia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NCL/ncl_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6383,548,"VUT","Vanuatu","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/VUT/vut_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6384,554,"NZL","New Zealand","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NZL/nzl_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6385,558,"NIC","Nicaragua","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NIC/nic_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6386,562,"NER","Niger","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NER/ner_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6387,566,"NGA","Nigeria","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NGA/nga_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6388,570,"NIU","Niue","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NIU/niu_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6389,574,"NFK","Norfolk Island","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NFK/nfk_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6390,578,"NOR","Norway","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/NOR/nor_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6391,580,"MNP","Northern Mariana Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MNP/mnp_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6392,581,"UMI","United States Minor Outlying Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/UMI/umi_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6393,583,"FSM","Micronesia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/FSM/fsm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6394,584,"MHL","Marshall Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MHL/mhl_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6395,585,"PLW","Palau","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PLW/plw_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6396,586,"PAK","Pakistan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PAK/pak_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6397,591,"PAN","Panama","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PAN/pan_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6398,598,"PNG","Papua New Guinea","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PNG/png_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6399,600,"PRY","Paraguay","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PRY/pry_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6400,604,"PER","Peru","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PER/per_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6401,608,"PHL","Philippines","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PHL/phl_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6402,612,"PCN","Pitcairn Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PCN/pcn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6403,616,"POL","Poland","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/POL/pol_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6404,620,"PRT","Portugal","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PRT/prt_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6405,624,"GNB","Guinea-Bissau","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GNB/gnb_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6406,626,"TLS","East Timor","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TLS/tls_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6407,630,"PRI","Puerto Rico","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/PRI/pri_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6408,634,"QAT","Qatar","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/QAT/qat_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6409,638,"REU","Reunion","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/REU/reu_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6410,642,"ROU","Romania","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ROU/rou_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6411,646,"RWA","Rwanda","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/RWA/rwa_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6412,652,"BLM","Saint Barthelemy","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BLM/blm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6413,654,"SHN","Saint Helena","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SHN/shn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6414,659,"KNA","Saint Kitts and Nevis","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/KNA/kna_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6415,660,"AIA","Anguilla","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/AIA/aia_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6416,662,"LCA","Saint Lucia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/LCA/lca_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6417,663,"MAF","Saint Martin (French part)","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MAF/maf_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6418,666,"SPM","Saint Pierre and Miquelon","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SPM/spm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6419,670,"VCT","Saint Vincent and the Grenadines","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/VCT/vct_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6420,674,"SMR","San Marino","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SMR/smr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6421,678,"STP","Sao Tome and Principe","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/STP/stp_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6422,682,"SAU","Saudi Arabia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SAU/sau_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6423,686,"SEN","Senegal","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SEN/sen_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6424,688,"SRB","Serbia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SRB/srb_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6425,690,"SYC","Seychelles","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SYC/syc_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6426,694,"SLE","Sierra Leone","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SLE/sle_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6427,702,"SGP","Singapore","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SGP/sgp_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6428,703,"SVK","Slovakia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SVK/svk_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6429,704,"VNM","Vietnam","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/VNM/vnm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6430,705,"SVN","Slovenia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SVN/svn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6431,706,"SOM","Somalia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SOM/som_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6432,710,"ZAF","South Africa","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ZAF/zaf_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6433,716,"ZWE","Zimbabwe","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ZWE/zwe_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6434,724,"ESP","Spain","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ESP/esp_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6435,728,"SSD","South Sudan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SSD/ssd_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6436,729,"SDN","Sudan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SDN/sdn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6437,732,"ESH","Western Sahara","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ESH/esh_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6438,740,"SUR","Suriname","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SUR/sur_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6439,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SJM/sjm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6440,748,"SWZ","Swaziland","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SWZ/swz_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6441,752,"SWE","Sweden","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SWE/swe_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6442,756,"CHE","Switzerland","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/CHE/che_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6443,760,"SYR","Syria","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SYR/syr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6444,762,"TJK","Tajikistan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TJK/tjk_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6445,764,"THA","Thailand","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/THA/tha_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6446,768,"TGO","Togo","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TGO/tgo_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6447,772,"TKL","Tokelau","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TKL/tkl_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6448,776,"TON","Tonga","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TON/ton_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6449,780,"TTO","Trinidad and Tobago","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TTO/tto_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6450,784,"ARE","United Arab Emirates","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ARE/are_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6451,788,"TUN","Tunisia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TUN/tun_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6452,792,"TUR","Turkey","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TUR/tur_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6453,795,"TKM","Turkmenistan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TKM/tkm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6454,796,"TCA","Turks and Caicos Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TCA/tca_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6455,798,"TUV","Tuvalu","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TUV/tuv_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6456,800,"UGA","Uganda","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/UGA/uga_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6457,804,"UKR","Ukraine","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/UKR/ukr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6458,807,"MKD","Macedonia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/MKD/mkd_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6459,818,"EGY","Egypt","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/EGY/egy_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6460,826,"GBR","United Kingdom","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GBR/gbr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6461,831,"GGY","Guernsey","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/GGY/ggy_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6462,832,"JEY","Jersey","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/JEY/jey_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6463,833,"IMN","Isle of Man","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/IMN/imn_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6464,834,"TZA","Tanzania","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/TZA/tza_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6465,854,"BFA","Burkina Faso","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/BFA/bfa_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6466,858,"URY","Uruguay","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/URY/ury_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6467,860,"UZB","Uzbekistan","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/UZB/uzb_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6468,862,"VEN","Venezuela","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/VEN/ven_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6469,876,"WLF","Wallis and Futuna","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/WLF/wlf_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6470,882,"WSM","Samoa","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/WSM/wsm_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6471,887,"YEM","Yemen","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/YEM/yem_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6472,894,"ZMB","Zambia","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/ZMB/zmb_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6473,900,"KOS","Kosovo","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/KOS/kos_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6474,901,"SPR","Spratly Islands","ppp_2004_UNadj","GIS/Population/Global_2000_2020/2004/SPR/spr_ppp_2004_UNadj.tif","Estimated total number of people per grid-cell 2004 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6475,643,"RUS","Russia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/RUS/rus_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6476,360,"IDN","Indonesia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/IDN/idn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6477,840,"USA","United States","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/USA/usa_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6478,850,"VIR","Virgin_Islands_U_S","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/VIR/vir_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6479,304,"GRL","Greenland","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GRL/grl_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6480,156,"CHN","China","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CHN/chn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6481,36,"AUS","Australia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/AUS/aus_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6482,76,"BRA","Brazil","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BRA/bra_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6483,124,"CAN","Canada","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CAN/can_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6484,152,"CHL","Chile","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CHL/chl_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6485,4,"AFG","Afghanistan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/AFG/afg_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6486,8,"ALB","Albania","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ALB/alb_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6487,10,"ATA","Antarctica","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ATA/ata_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6488,12,"DZA","Algeria","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/DZA/dza_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6489,16,"ASM","American Samoa","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ASM/asm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6490,20,"AND","Andorra","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/AND/and_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6491,24,"AGO","Angola","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/AGO/ago_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6492,28,"ATG","Antigua and Barbuda","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ATG/atg_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6493,31,"AZE","Azerbaijan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/AZE/aze_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6494,32,"ARG","Argentina","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ARG/arg_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6495,40,"AUT","Austria","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/AUT/aut_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6496,44,"BHS","Bahamas","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BHS/bhs_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6497,48,"BHR","Bahrain","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BHR/bhr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6498,50,"BGD","Bangladesh","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BGD/bgd_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6499,51,"ARM","Armenia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ARM/arm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6500,52,"BRB","Barbados","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BRB/brb_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6501,56,"BEL","Belgium","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BEL/bel_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6502,60,"BMU","Bermuda","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BMU/bmu_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6503,64,"BTN","Bhutan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BTN/btn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6504,68,"BOL","Bolivia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BOL/bol_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6505,70,"BIH","Bosnia and Herzegovina","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BIH/bih_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6506,72,"BWA","Botswana","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BWA/bwa_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6507,74,"BVT","Bouvet Island","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BVT/bvt_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6508,84,"BLZ","Belize","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BLZ/blz_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6509,86,"IOT","British Indian Ocean Territory","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/IOT/iot_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6510,90,"SLB","Solomon Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SLB/slb_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6511,92,"VGB","British Virgin Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/VGB/vgb_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6512,96,"BRN","Brunei","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BRN/brn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6513,100,"BGR","Bulgaria","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BGR/bgr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6514,104,"MMR","Myanmar","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MMR/mmr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6515,108,"BDI","Burundi","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BDI/bdi_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6516,112,"BLR","Belarus","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BLR/blr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6517,116,"KHM","Cambodia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/KHM/khm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6518,120,"CMR","Cameroon","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CMR/cmr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6519,132,"CPV","Cape Verde","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CPV/cpv_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6520,136,"CYM","Cayman Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CYM/cym_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6521,140,"CAF","Central African Republic","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CAF/caf_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6522,144,"LKA","Sri Lanka","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LKA/lka_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6523,148,"TCD","Chad","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TCD/tcd_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6524,158,"TWN","Taiwan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TWN/twn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6525,170,"COL","Colombia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/COL/col_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6526,174,"COM","Comoros","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/COM/com_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6527,175,"MYT","Mayotte","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MYT/myt_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6528,178,"COG","Republic of Congo","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/COG/cog_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6529,180,"COD","Democratic Republic of the Congo","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/COD/cod_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6530,184,"COK","Cook Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/COK/cok_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6531,188,"CRI","Costa Rica","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CRI/cri_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6532,191,"HRV","Croatia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/HRV/hrv_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6533,192,"CUB","Cuba","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CUB/cub_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6534,196,"CYP","Cyprus","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CYP/cyp_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6535,203,"CZE","Czech Republic","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CZE/cze_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6536,204,"BEN","Benin","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BEN/ben_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6537,208,"DNK","Denmark","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/DNK/dnk_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6538,212,"DMA","Dominica","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/DMA/dma_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6539,214,"DOM","Dominican Republic","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/DOM/dom_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6540,218,"ECU","Ecuador","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ECU/ecu_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6541,222,"SLV","El Salvador","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SLV/slv_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6542,226,"GNQ","Equatorial Guinea","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GNQ/gnq_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6543,231,"ETH","Ethiopia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ETH/eth_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6544,232,"ERI","Eritrea","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ERI/eri_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6545,233,"EST","Estonia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/EST/est_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6546,234,"FRO","Faroe Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/FRO/fro_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6547,238,"FLK","Falkland Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/FLK/flk_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6548,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SGS/sgs_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6549,242,"FJI","Fiji","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/FJI/fji_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6550,246,"FIN","Finland","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/FIN/fin_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6551,248,"ALA","Aland Islands ","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ALA/ala_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6552,250,"FRA","France","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/FRA/fra_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6553,254,"GUF","French Guiana","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GUF/guf_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6554,258,"PYF","French Polynesia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PYF/pyf_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6555,260,"ATF","French Southern Territories","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ATF/atf_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6556,262,"DJI","Djibouti","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/DJI/dji_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6557,266,"GAB","Gabon","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GAB/gab_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6558,268,"GEO","Georgia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GEO/geo_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6559,270,"GMB","Gambia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GMB/gmb_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6560,275,"PSE","Palestina","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PSE/pse_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6561,276,"DEU","Germany","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/DEU/deu_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6562,288,"GHA","Ghana","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GHA/gha_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6563,292,"GIB","Gibraltar","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GIB/gib_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6564,296,"KIR","Kiribati","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/KIR/kir_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6565,300,"GRC","Greece","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GRC/grc_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6566,308,"GRD","Grenada","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GRD/grd_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6567,312,"GLP","Guadeloupe","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GLP/glp_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6568,316,"GUM","Guam","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GUM/gum_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6569,320,"GTM","Guatemala","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GTM/gtm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6570,324,"GIN","Guinea","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GIN/gin_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6571,328,"GUY","Guyana","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GUY/guy_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6572,332,"HTI","Haiti","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/HTI/hti_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6573,334,"HMD","Heard Island and McDonald Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/HMD/hmd_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6574,336,"VAT","Vatican City","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/VAT/vat_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6575,340,"HND","Honduras","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/HND/hnd_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6576,344,"HKG","Hong Kong","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/HKG/hkg_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6577,348,"HUN","Hungary","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/HUN/hun_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6578,352,"ISL","Iceland","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ISL/isl_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6579,356,"IND","India","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/IND/ind_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6580,364,"IRN","Iran","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/IRN/irn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6581,368,"IRQ","Iraq","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/IRQ/irq_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6582,372,"IRL","Ireland","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/IRL/irl_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6583,376,"ISR","Israel","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ISR/isr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6584,380,"ITA","Italy","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ITA/ita_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6585,384,"CIV","CIte dIvoire","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CIV/civ_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6586,388,"JAM","Jamaica","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/JAM/jam_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6587,392,"JPN","Japan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/JPN/jpn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6588,398,"KAZ","Kazakhstan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/KAZ/kaz_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6589,400,"JOR","Jordan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/JOR/jor_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6590,404,"KEN","Kenya","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/KEN/ken_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6591,408,"PRK","North Korea","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PRK/prk_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6592,410,"KOR","South Korea","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/KOR/kor_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6593,414,"KWT","Kuwait","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/KWT/kwt_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6594,417,"KGZ","Kyrgyzstan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/KGZ/kgz_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6595,418,"LAO","Laos","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LAO/lao_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6596,422,"LBN","Lebanon","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LBN/lbn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6597,426,"LSO","Lesotho","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LSO/lso_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6598,428,"LVA","Latvia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LVA/lva_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6599,430,"LBR","Liberia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LBR/lbr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6600,434,"LBY","Libya","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LBY/lby_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6601,438,"LIE","Liechtenstein","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LIE/lie_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6602,440,"LTU","Lithuania","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LTU/ltu_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6603,442,"LUX","Luxembourg","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LUX/lux_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6604,446,"MAC","Macao","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MAC/mac_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6605,450,"MDG","Madagascar","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MDG/mdg_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6606,454,"MWI","Malawi","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MWI/mwi_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6607,458,"MYS","Malaysia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MYS/mys_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6608,462,"MDV","Maldives","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MDV/mdv_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6609,466,"MLI","Mali","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MLI/mli_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6610,470,"MLT","Malta","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MLT/mlt_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6611,474,"MTQ","Martinique","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MTQ/mtq_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6612,478,"MRT","Mauritania","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MRT/mrt_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6613,480,"MUS","Mauritius","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MUS/mus_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6614,484,"MEX","Mexico","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MEX/mex_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6615,492,"MCO","Monaco","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MCO/mco_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6616,496,"MNG","Mongolia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MNG/mng_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6617,498,"MDA","Moldova","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MDA/mda_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6618,499,"MNE","Montenegro","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MNE/mne_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6619,500,"MSR","Montserrat","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MSR/msr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6620,504,"MAR","Morocco","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MAR/mar_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6621,508,"MOZ","Mozambique","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MOZ/moz_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6622,512,"OMN","Oman","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/OMN/omn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6623,516,"NAM","Namibia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NAM/nam_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6624,520,"NRU","Nauru","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NRU/nru_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6625,524,"NPL","Nepal","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NPL/npl_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6626,528,"NLD","Netherlands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NLD/nld_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6627,531,"CUW","Curacao","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CUW/cuw_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6628,533,"ABW","Aruba","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ABW/abw_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6629,534,"SXM","Sint Maarten (Dutch part)","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SXM/sxm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6630,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BES/bes_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6631,540,"NCL","New Caledonia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NCL/ncl_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6632,548,"VUT","Vanuatu","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/VUT/vut_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6633,554,"NZL","New Zealand","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NZL/nzl_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6634,558,"NIC","Nicaragua","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NIC/nic_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6635,562,"NER","Niger","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NER/ner_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6636,566,"NGA","Nigeria","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NGA/nga_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6637,570,"NIU","Niue","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NIU/niu_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6638,574,"NFK","Norfolk Island","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NFK/nfk_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6639,578,"NOR","Norway","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/NOR/nor_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6640,580,"MNP","Northern Mariana Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MNP/mnp_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6641,581,"UMI","United States Minor Outlying Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/UMI/umi_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6642,583,"FSM","Micronesia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/FSM/fsm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6643,584,"MHL","Marshall Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MHL/mhl_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6644,585,"PLW","Palau","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PLW/plw_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6645,586,"PAK","Pakistan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PAK/pak_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6646,591,"PAN","Panama","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PAN/pan_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6647,598,"PNG","Papua New Guinea","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PNG/png_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6648,600,"PRY","Paraguay","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PRY/pry_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6649,604,"PER","Peru","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PER/per_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6650,608,"PHL","Philippines","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PHL/phl_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6651,612,"PCN","Pitcairn Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PCN/pcn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6652,616,"POL","Poland","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/POL/pol_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6653,620,"PRT","Portugal","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PRT/prt_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6654,624,"GNB","Guinea-Bissau","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GNB/gnb_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6655,626,"TLS","East Timor","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TLS/tls_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6656,630,"PRI","Puerto Rico","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/PRI/pri_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6657,634,"QAT","Qatar","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/QAT/qat_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6658,638,"REU","Reunion","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/REU/reu_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6659,642,"ROU","Romania","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ROU/rou_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6660,646,"RWA","Rwanda","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/RWA/rwa_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6661,652,"BLM","Saint Barthelemy","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BLM/blm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6662,654,"SHN","Saint Helena","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SHN/shn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6663,659,"KNA","Saint Kitts and Nevis","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/KNA/kna_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6664,660,"AIA","Anguilla","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/AIA/aia_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6665,662,"LCA","Saint Lucia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/LCA/lca_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6666,663,"MAF","Saint Martin (French part)","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MAF/maf_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6667,666,"SPM","Saint Pierre and Miquelon","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SPM/spm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6668,670,"VCT","Saint Vincent and the Grenadines","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/VCT/vct_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6669,674,"SMR","San Marino","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SMR/smr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6670,678,"STP","Sao Tome and Principe","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/STP/stp_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6671,682,"SAU","Saudi Arabia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SAU/sau_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6672,686,"SEN","Senegal","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SEN/sen_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6673,688,"SRB","Serbia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SRB/srb_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6674,690,"SYC","Seychelles","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SYC/syc_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6675,694,"SLE","Sierra Leone","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SLE/sle_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6676,702,"SGP","Singapore","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SGP/sgp_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6677,703,"SVK","Slovakia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SVK/svk_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6678,704,"VNM","Vietnam","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/VNM/vnm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6679,705,"SVN","Slovenia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SVN/svn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6680,706,"SOM","Somalia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SOM/som_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6681,710,"ZAF","South Africa","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ZAF/zaf_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6682,716,"ZWE","Zimbabwe","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ZWE/zwe_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6683,724,"ESP","Spain","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ESP/esp_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6684,728,"SSD","South Sudan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SSD/ssd_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6685,729,"SDN","Sudan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SDN/sdn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6686,732,"ESH","Western Sahara","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ESH/esh_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6687,740,"SUR","Suriname","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SUR/sur_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6688,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SJM/sjm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6689,748,"SWZ","Swaziland","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SWZ/swz_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6690,752,"SWE","Sweden","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SWE/swe_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6691,756,"CHE","Switzerland","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/CHE/che_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6692,760,"SYR","Syria","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SYR/syr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6693,762,"TJK","Tajikistan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TJK/tjk_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6694,764,"THA","Thailand","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/THA/tha_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6695,768,"TGO","Togo","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TGO/tgo_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6696,772,"TKL","Tokelau","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TKL/tkl_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6697,776,"TON","Tonga","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TON/ton_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6698,780,"TTO","Trinidad and Tobago","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TTO/tto_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6699,784,"ARE","United Arab Emirates","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ARE/are_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6700,788,"TUN","Tunisia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TUN/tun_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6701,792,"TUR","Turkey","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TUR/tur_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6702,795,"TKM","Turkmenistan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TKM/tkm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6703,796,"TCA","Turks and Caicos Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TCA/tca_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6704,798,"TUV","Tuvalu","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TUV/tuv_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6705,800,"UGA","Uganda","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/UGA/uga_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6706,804,"UKR","Ukraine","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/UKR/ukr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6707,807,"MKD","Macedonia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/MKD/mkd_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6708,818,"EGY","Egypt","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/EGY/egy_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6709,826,"GBR","United Kingdom","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GBR/gbr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6710,831,"GGY","Guernsey","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/GGY/ggy_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6711,832,"JEY","Jersey","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/JEY/jey_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6712,833,"IMN","Isle of Man","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/IMN/imn_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6713,834,"TZA","Tanzania","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/TZA/tza_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6714,854,"BFA","Burkina Faso","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/BFA/bfa_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6715,858,"URY","Uruguay","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/URY/ury_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6716,860,"UZB","Uzbekistan","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/UZB/uzb_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6717,862,"VEN","Venezuela","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/VEN/ven_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6718,876,"WLF","Wallis and Futuna","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/WLF/wlf_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6719,882,"WSM","Samoa","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/WSM/wsm_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6720,887,"YEM","Yemen","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/YEM/yem_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6721,894,"ZMB","Zambia","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/ZMB/zmb_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6722,900,"KOS","Kosovo","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/KOS/kos_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6723,901,"SPR","Spratly Islands","ppp_2005_UNadj","GIS/Population/Global_2000_2020/2005/SPR/spr_ppp_2005_UNadj.tif","Estimated total number of people per grid-cell 2005 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6724,643,"RUS","Russia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/RUS/rus_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6725,360,"IDN","Indonesia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/IDN/idn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6726,840,"USA","United States","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/USA/usa_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6727,850,"VIR","Virgin_Islands_U_S","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/VIR/vir_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6728,304,"GRL","Greenland","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GRL/grl_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6729,156,"CHN","China","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CHN/chn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6730,36,"AUS","Australia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/AUS/aus_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6731,76,"BRA","Brazil","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BRA/bra_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6732,124,"CAN","Canada","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CAN/can_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6733,152,"CHL","Chile","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CHL/chl_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6734,4,"AFG","Afghanistan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/AFG/afg_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6735,8,"ALB","Albania","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ALB/alb_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6736,10,"ATA","Antarctica","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ATA/ata_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6737,12,"DZA","Algeria","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/DZA/dza_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6738,16,"ASM","American Samoa","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ASM/asm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6739,20,"AND","Andorra","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/AND/and_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6740,24,"AGO","Angola","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/AGO/ago_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6741,28,"ATG","Antigua and Barbuda","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ATG/atg_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6742,31,"AZE","Azerbaijan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/AZE/aze_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6743,32,"ARG","Argentina","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ARG/arg_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6744,40,"AUT","Austria","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/AUT/aut_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6745,44,"BHS","Bahamas","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BHS/bhs_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6746,48,"BHR","Bahrain","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BHR/bhr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6747,50,"BGD","Bangladesh","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BGD/bgd_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6748,51,"ARM","Armenia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ARM/arm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6749,52,"BRB","Barbados","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BRB/brb_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6750,56,"BEL","Belgium","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BEL/bel_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6751,60,"BMU","Bermuda","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BMU/bmu_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6752,64,"BTN","Bhutan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BTN/btn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6753,68,"BOL","Bolivia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BOL/bol_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6754,70,"BIH","Bosnia and Herzegovina","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BIH/bih_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6755,72,"BWA","Botswana","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BWA/bwa_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6756,74,"BVT","Bouvet Island","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BVT/bvt_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6757,84,"BLZ","Belize","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BLZ/blz_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6758,86,"IOT","British Indian Ocean Territory","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/IOT/iot_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6759,90,"SLB","Solomon Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SLB/slb_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6760,92,"VGB","British Virgin Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/VGB/vgb_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6761,96,"BRN","Brunei","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BRN/brn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6762,100,"BGR","Bulgaria","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BGR/bgr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6763,104,"MMR","Myanmar","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MMR/mmr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6764,108,"BDI","Burundi","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BDI/bdi_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6765,112,"BLR","Belarus","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BLR/blr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6766,116,"KHM","Cambodia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/KHM/khm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6767,120,"CMR","Cameroon","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CMR/cmr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6768,132,"CPV","Cape Verde","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CPV/cpv_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6769,136,"CYM","Cayman Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CYM/cym_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6770,140,"CAF","Central African Republic","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CAF/caf_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6771,144,"LKA","Sri Lanka","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LKA/lka_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6772,148,"TCD","Chad","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TCD/tcd_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6773,158,"TWN","Taiwan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TWN/twn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6774,170,"COL","Colombia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/COL/col_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6775,174,"COM","Comoros","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/COM/com_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6776,175,"MYT","Mayotte","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MYT/myt_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6777,178,"COG","Republic of Congo","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/COG/cog_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6778,180,"COD","Democratic Republic of the Congo","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/COD/cod_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6779,184,"COK","Cook Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/COK/cok_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6780,188,"CRI","Costa Rica","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CRI/cri_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6781,191,"HRV","Croatia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/HRV/hrv_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6782,192,"CUB","Cuba","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CUB/cub_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6783,196,"CYP","Cyprus","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CYP/cyp_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6784,203,"CZE","Czech Republic","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CZE/cze_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6785,204,"BEN","Benin","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BEN/ben_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6786,208,"DNK","Denmark","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/DNK/dnk_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6787,212,"DMA","Dominica","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/DMA/dma_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6788,214,"DOM","Dominican Republic","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/DOM/dom_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6789,218,"ECU","Ecuador","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ECU/ecu_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6790,222,"SLV","El Salvador","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SLV/slv_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6791,226,"GNQ","Equatorial Guinea","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GNQ/gnq_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6792,231,"ETH","Ethiopia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ETH/eth_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6793,232,"ERI","Eritrea","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ERI/eri_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6794,233,"EST","Estonia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/EST/est_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6795,234,"FRO","Faroe Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/FRO/fro_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6796,238,"FLK","Falkland Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/FLK/flk_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6797,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SGS/sgs_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6798,242,"FJI","Fiji","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/FJI/fji_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6799,246,"FIN","Finland","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/FIN/fin_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6800,248,"ALA","Aland Islands ","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ALA/ala_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6801,250,"FRA","France","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/FRA/fra_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6802,254,"GUF","French Guiana","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GUF/guf_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6803,258,"PYF","French Polynesia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PYF/pyf_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6804,260,"ATF","French Southern Territories","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ATF/atf_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6805,262,"DJI","Djibouti","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/DJI/dji_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6806,266,"GAB","Gabon","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GAB/gab_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6807,268,"GEO","Georgia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GEO/geo_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6808,270,"GMB","Gambia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GMB/gmb_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6809,275,"PSE","Palestina","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PSE/pse_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6810,276,"DEU","Germany","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/DEU/deu_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6811,288,"GHA","Ghana","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GHA/gha_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6812,292,"GIB","Gibraltar","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GIB/gib_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6813,296,"KIR","Kiribati","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/KIR/kir_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6814,300,"GRC","Greece","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GRC/grc_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6815,308,"GRD","Grenada","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GRD/grd_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6816,312,"GLP","Guadeloupe","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GLP/glp_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6817,316,"GUM","Guam","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GUM/gum_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6818,320,"GTM","Guatemala","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GTM/gtm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6819,324,"GIN","Guinea","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GIN/gin_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6820,328,"GUY","Guyana","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GUY/guy_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6821,332,"HTI","Haiti","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/HTI/hti_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6822,334,"HMD","Heard Island and McDonald Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/HMD/hmd_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6823,336,"VAT","Vatican City","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/VAT/vat_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6824,340,"HND","Honduras","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/HND/hnd_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6825,344,"HKG","Hong Kong","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/HKG/hkg_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6826,348,"HUN","Hungary","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/HUN/hun_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6827,352,"ISL","Iceland","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ISL/isl_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6828,356,"IND","India","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/IND/ind_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6829,364,"IRN","Iran","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/IRN/irn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6830,368,"IRQ","Iraq","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/IRQ/irq_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6831,372,"IRL","Ireland","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/IRL/irl_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6832,376,"ISR","Israel","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ISR/isr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6833,380,"ITA","Italy","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ITA/ita_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6834,384,"CIV","CIte dIvoire","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CIV/civ_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6835,388,"JAM","Jamaica","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/JAM/jam_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6836,392,"JPN","Japan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/JPN/jpn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6837,398,"KAZ","Kazakhstan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/KAZ/kaz_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6838,400,"JOR","Jordan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/JOR/jor_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6839,404,"KEN","Kenya","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/KEN/ken_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6840,408,"PRK","North Korea","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PRK/prk_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6841,410,"KOR","South Korea","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/KOR/kor_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6842,414,"KWT","Kuwait","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/KWT/kwt_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6843,417,"KGZ","Kyrgyzstan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/KGZ/kgz_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6844,418,"LAO","Laos","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LAO/lao_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6845,422,"LBN","Lebanon","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LBN/lbn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6846,426,"LSO","Lesotho","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LSO/lso_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6847,428,"LVA","Latvia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LVA/lva_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6848,430,"LBR","Liberia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LBR/lbr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6849,434,"LBY","Libya","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LBY/lby_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6850,438,"LIE","Liechtenstein","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LIE/lie_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6851,440,"LTU","Lithuania","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LTU/ltu_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6852,442,"LUX","Luxembourg","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LUX/lux_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6853,446,"MAC","Macao","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MAC/mac_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6854,450,"MDG","Madagascar","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MDG/mdg_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6855,454,"MWI","Malawi","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MWI/mwi_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6856,458,"MYS","Malaysia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MYS/mys_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6857,462,"MDV","Maldives","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MDV/mdv_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6858,466,"MLI","Mali","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MLI/mli_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6859,470,"MLT","Malta","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MLT/mlt_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6860,474,"MTQ","Martinique","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MTQ/mtq_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6861,478,"MRT","Mauritania","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MRT/mrt_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6862,480,"MUS","Mauritius","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MUS/mus_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6863,484,"MEX","Mexico","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MEX/mex_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6864,492,"MCO","Monaco","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MCO/mco_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6865,496,"MNG","Mongolia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MNG/mng_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6866,498,"MDA","Moldova","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MDA/mda_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6867,499,"MNE","Montenegro","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MNE/mne_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6868,500,"MSR","Montserrat","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MSR/msr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6869,504,"MAR","Morocco","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MAR/mar_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6870,508,"MOZ","Mozambique","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MOZ/moz_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6871,512,"OMN","Oman","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/OMN/omn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6872,516,"NAM","Namibia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NAM/nam_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6873,520,"NRU","Nauru","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NRU/nru_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6874,524,"NPL","Nepal","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NPL/npl_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6875,528,"NLD","Netherlands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NLD/nld_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6876,531,"CUW","Curacao","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CUW/cuw_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6877,533,"ABW","Aruba","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ABW/abw_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6878,534,"SXM","Sint Maarten (Dutch part)","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SXM/sxm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6879,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BES/bes_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6880,540,"NCL","New Caledonia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NCL/ncl_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6881,548,"VUT","Vanuatu","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/VUT/vut_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6882,554,"NZL","New Zealand","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NZL/nzl_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6883,558,"NIC","Nicaragua","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NIC/nic_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6884,562,"NER","Niger","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NER/ner_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6885,566,"NGA","Nigeria","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NGA/nga_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6886,570,"NIU","Niue","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NIU/niu_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6887,574,"NFK","Norfolk Island","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NFK/nfk_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6888,578,"NOR","Norway","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/NOR/nor_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6889,580,"MNP","Northern Mariana Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MNP/mnp_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6890,581,"UMI","United States Minor Outlying Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/UMI/umi_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6891,583,"FSM","Micronesia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/FSM/fsm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6892,584,"MHL","Marshall Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MHL/mhl_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6893,585,"PLW","Palau","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PLW/plw_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6894,586,"PAK","Pakistan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PAK/pak_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6895,591,"PAN","Panama","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PAN/pan_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6896,598,"PNG","Papua New Guinea","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PNG/png_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6897,600,"PRY","Paraguay","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PRY/pry_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6898,604,"PER","Peru","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PER/per_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6899,608,"PHL","Philippines","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PHL/phl_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6900,612,"PCN","Pitcairn Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PCN/pcn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6901,616,"POL","Poland","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/POL/pol_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6902,620,"PRT","Portugal","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PRT/prt_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6903,624,"GNB","Guinea-Bissau","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GNB/gnb_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6904,626,"TLS","East Timor","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TLS/tls_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6905,630,"PRI","Puerto Rico","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/PRI/pri_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6906,634,"QAT","Qatar","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/QAT/qat_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6907,638,"REU","Reunion","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/REU/reu_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6908,642,"ROU","Romania","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ROU/rou_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6909,646,"RWA","Rwanda","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/RWA/rwa_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6910,652,"BLM","Saint Barthelemy","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BLM/blm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6911,654,"SHN","Saint Helena","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SHN/shn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6912,659,"KNA","Saint Kitts and Nevis","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/KNA/kna_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6913,660,"AIA","Anguilla","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/AIA/aia_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6914,662,"LCA","Saint Lucia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/LCA/lca_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6915,663,"MAF","Saint Martin (French part)","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MAF/maf_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6916,666,"SPM","Saint Pierre and Miquelon","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SPM/spm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6917,670,"VCT","Saint Vincent and the Grenadines","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/VCT/vct_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6918,674,"SMR","San Marino","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SMR/smr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6919,678,"STP","Sao Tome and Principe","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/STP/stp_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6920,682,"SAU","Saudi Arabia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SAU/sau_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6921,686,"SEN","Senegal","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SEN/sen_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6922,688,"SRB","Serbia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SRB/srb_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6923,690,"SYC","Seychelles","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SYC/syc_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6924,694,"SLE","Sierra Leone","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SLE/sle_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6925,702,"SGP","Singapore","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SGP/sgp_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6926,703,"SVK","Slovakia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SVK/svk_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6927,704,"VNM","Vietnam","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/VNM/vnm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6928,705,"SVN","Slovenia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SVN/svn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6929,706,"SOM","Somalia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SOM/som_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6930,710,"ZAF","South Africa","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ZAF/zaf_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6931,716,"ZWE","Zimbabwe","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ZWE/zwe_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6932,724,"ESP","Spain","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ESP/esp_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6933,728,"SSD","South Sudan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SSD/ssd_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6934,729,"SDN","Sudan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SDN/sdn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6935,732,"ESH","Western Sahara","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ESH/esh_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6936,740,"SUR","Suriname","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SUR/sur_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6937,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SJM/sjm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6938,748,"SWZ","Swaziland","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SWZ/swz_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6939,752,"SWE","Sweden","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SWE/swe_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6940,756,"CHE","Switzerland","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/CHE/che_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6941,760,"SYR","Syria","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SYR/syr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6942,762,"TJK","Tajikistan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TJK/tjk_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6943,764,"THA","Thailand","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/THA/tha_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6944,768,"TGO","Togo","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TGO/tgo_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6945,772,"TKL","Tokelau","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TKL/tkl_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6946,776,"TON","Tonga","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TON/ton_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6947,780,"TTO","Trinidad and Tobago","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TTO/tto_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6948,784,"ARE","United Arab Emirates","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ARE/are_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6949,788,"TUN","Tunisia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TUN/tun_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6950,792,"TUR","Turkey","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TUR/tur_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6951,795,"TKM","Turkmenistan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TKM/tkm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6952,796,"TCA","Turks and Caicos Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TCA/tca_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6953,798,"TUV","Tuvalu","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TUV/tuv_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6954,800,"UGA","Uganda","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/UGA/uga_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6955,804,"UKR","Ukraine","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/UKR/ukr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6956,807,"MKD","Macedonia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/MKD/mkd_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6957,818,"EGY","Egypt","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/EGY/egy_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6958,826,"GBR","United Kingdom","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GBR/gbr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6959,831,"GGY","Guernsey","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/GGY/ggy_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6960,832,"JEY","Jersey","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/JEY/jey_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6961,833,"IMN","Isle of Man","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/IMN/imn_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6962,834,"TZA","Tanzania","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/TZA/tza_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6963,854,"BFA","Burkina Faso","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/BFA/bfa_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6964,858,"URY","Uruguay","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/URY/ury_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6965,860,"UZB","Uzbekistan","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/UZB/uzb_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6966,862,"VEN","Venezuela","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/VEN/ven_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6967,876,"WLF","Wallis and Futuna","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/WLF/wlf_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6968,882,"WSM","Samoa","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/WSM/wsm_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6969,887,"YEM","Yemen","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/YEM/yem_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6970,894,"ZMB","Zambia","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/ZMB/zmb_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6971,900,"KOS","Kosovo","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/KOS/kos_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6972,901,"SPR","Spratly Islands","ppp_2006_UNadj","GIS/Population/Global_2000_2020/2006/SPR/spr_ppp_2006_UNadj.tif","Estimated total number of people per grid-cell 2006 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6973,643,"RUS","Russia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/RUS/rus_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6974,360,"IDN","Indonesia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/IDN/idn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6975,840,"USA","United States","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/USA/usa_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6976,850,"VIR","Virgin_Islands_U_S","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/VIR/vir_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6977,304,"GRL","Greenland","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GRL/grl_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6978,156,"CHN","China","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CHN/chn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6979,36,"AUS","Australia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/AUS/aus_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6980,76,"BRA","Brazil","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BRA/bra_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6981,124,"CAN","Canada","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CAN/can_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6982,152,"CHL","Chile","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CHL/chl_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6983,4,"AFG","Afghanistan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/AFG/afg_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6984,8,"ALB","Albania","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ALB/alb_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6985,10,"ATA","Antarctica","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ATA/ata_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6986,12,"DZA","Algeria","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/DZA/dza_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6987,16,"ASM","American Samoa","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ASM/asm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6988,20,"AND","Andorra","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/AND/and_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6989,24,"AGO","Angola","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/AGO/ago_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6990,28,"ATG","Antigua and Barbuda","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ATG/atg_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6991,31,"AZE","Azerbaijan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/AZE/aze_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6992,32,"ARG","Argentina","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ARG/arg_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6993,40,"AUT","Austria","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/AUT/aut_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6994,44,"BHS","Bahamas","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BHS/bhs_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6995,48,"BHR","Bahrain","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BHR/bhr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6996,50,"BGD","Bangladesh","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BGD/bgd_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6997,51,"ARM","Armenia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ARM/arm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6998,52,"BRB","Barbados","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BRB/brb_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
6999,56,"BEL","Belgium","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BEL/bel_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7000,60,"BMU","Bermuda","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BMU/bmu_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7001,64,"BTN","Bhutan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BTN/btn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7002,68,"BOL","Bolivia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BOL/bol_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7003,70,"BIH","Bosnia and Herzegovina","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BIH/bih_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7004,72,"BWA","Botswana","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BWA/bwa_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7005,74,"BVT","Bouvet Island","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BVT/bvt_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7006,84,"BLZ","Belize","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BLZ/blz_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7007,86,"IOT","British Indian Ocean Territory","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/IOT/iot_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7008,90,"SLB","Solomon Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SLB/slb_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7009,92,"VGB","British Virgin Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/VGB/vgb_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7010,96,"BRN","Brunei","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BRN/brn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7011,100,"BGR","Bulgaria","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BGR/bgr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7012,104,"MMR","Myanmar","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MMR/mmr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7013,108,"BDI","Burundi","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BDI/bdi_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7014,112,"BLR","Belarus","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BLR/blr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7015,116,"KHM","Cambodia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/KHM/khm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7016,120,"CMR","Cameroon","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CMR/cmr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7017,132,"CPV","Cape Verde","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CPV/cpv_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7018,136,"CYM","Cayman Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CYM/cym_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7019,140,"CAF","Central African Republic","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CAF/caf_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7020,144,"LKA","Sri Lanka","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LKA/lka_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7021,148,"TCD","Chad","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TCD/tcd_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7022,158,"TWN","Taiwan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TWN/twn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7023,170,"COL","Colombia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/COL/col_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7024,174,"COM","Comoros","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/COM/com_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7025,175,"MYT","Mayotte","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MYT/myt_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7026,178,"COG","Republic of Congo","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/COG/cog_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7027,180,"COD","Democratic Republic of the Congo","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/COD/cod_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7028,184,"COK","Cook Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/COK/cok_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7029,188,"CRI","Costa Rica","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CRI/cri_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7030,191,"HRV","Croatia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/HRV/hrv_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7031,192,"CUB","Cuba","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CUB/cub_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7032,196,"CYP","Cyprus","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CYP/cyp_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7033,203,"CZE","Czech Republic","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CZE/cze_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7034,204,"BEN","Benin","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BEN/ben_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7035,208,"DNK","Denmark","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/DNK/dnk_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7036,212,"DMA","Dominica","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/DMA/dma_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7037,214,"DOM","Dominican Republic","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/DOM/dom_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7038,218,"ECU","Ecuador","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ECU/ecu_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7039,222,"SLV","El Salvador","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SLV/slv_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7040,226,"GNQ","Equatorial Guinea","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GNQ/gnq_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7041,231,"ETH","Ethiopia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ETH/eth_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7042,232,"ERI","Eritrea","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ERI/eri_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7043,233,"EST","Estonia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/EST/est_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7044,234,"FRO","Faroe Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/FRO/fro_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7045,238,"FLK","Falkland Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/FLK/flk_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7046,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SGS/sgs_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7047,242,"FJI","Fiji","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/FJI/fji_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7048,246,"FIN","Finland","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/FIN/fin_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7049,248,"ALA","Aland Islands ","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ALA/ala_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7050,250,"FRA","France","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/FRA/fra_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7051,254,"GUF","French Guiana","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GUF/guf_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7052,258,"PYF","French Polynesia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PYF/pyf_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7053,260,"ATF","French Southern Territories","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ATF/atf_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7054,262,"DJI","Djibouti","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/DJI/dji_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7055,266,"GAB","Gabon","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GAB/gab_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7056,268,"GEO","Georgia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GEO/geo_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7057,270,"GMB","Gambia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GMB/gmb_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7058,275,"PSE","Palestina","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PSE/pse_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7059,276,"DEU","Germany","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/DEU/deu_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7060,288,"GHA","Ghana","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GHA/gha_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7061,292,"GIB","Gibraltar","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GIB/gib_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7062,296,"KIR","Kiribati","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/KIR/kir_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7063,300,"GRC","Greece","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GRC/grc_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7064,308,"GRD","Grenada","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GRD/grd_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7065,312,"GLP","Guadeloupe","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GLP/glp_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7066,316,"GUM","Guam","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GUM/gum_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7067,320,"GTM","Guatemala","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GTM/gtm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7068,324,"GIN","Guinea","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GIN/gin_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7069,328,"GUY","Guyana","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GUY/guy_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7070,332,"HTI","Haiti","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/HTI/hti_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7071,334,"HMD","Heard Island and McDonald Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/HMD/hmd_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7072,336,"VAT","Vatican City","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/VAT/vat_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7073,340,"HND","Honduras","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/HND/hnd_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7074,344,"HKG","Hong Kong","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/HKG/hkg_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7075,348,"HUN","Hungary","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/HUN/hun_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7076,352,"ISL","Iceland","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ISL/isl_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7077,356,"IND","India","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/IND/ind_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7078,364,"IRN","Iran","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/IRN/irn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7079,368,"IRQ","Iraq","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/IRQ/irq_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7080,372,"IRL","Ireland","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/IRL/irl_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7081,376,"ISR","Israel","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ISR/isr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7082,380,"ITA","Italy","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ITA/ita_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7083,384,"CIV","CIte dIvoire","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CIV/civ_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7084,388,"JAM","Jamaica","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/JAM/jam_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7085,392,"JPN","Japan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/JPN/jpn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7086,398,"KAZ","Kazakhstan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/KAZ/kaz_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7087,400,"JOR","Jordan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/JOR/jor_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7088,404,"KEN","Kenya","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/KEN/ken_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7089,408,"PRK","North Korea","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PRK/prk_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7090,410,"KOR","South Korea","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/KOR/kor_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7091,414,"KWT","Kuwait","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/KWT/kwt_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7092,417,"KGZ","Kyrgyzstan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/KGZ/kgz_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7093,418,"LAO","Laos","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LAO/lao_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7094,422,"LBN","Lebanon","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LBN/lbn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7095,426,"LSO","Lesotho","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LSO/lso_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7096,428,"LVA","Latvia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LVA/lva_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7097,430,"LBR","Liberia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LBR/lbr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7098,434,"LBY","Libya","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LBY/lby_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7099,438,"LIE","Liechtenstein","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LIE/lie_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7100,440,"LTU","Lithuania","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LTU/ltu_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7101,442,"LUX","Luxembourg","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LUX/lux_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7102,446,"MAC","Macao","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MAC/mac_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7103,450,"MDG","Madagascar","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MDG/mdg_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7104,454,"MWI","Malawi","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MWI/mwi_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7105,458,"MYS","Malaysia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MYS/mys_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7106,462,"MDV","Maldives","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MDV/mdv_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7107,466,"MLI","Mali","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MLI/mli_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7108,470,"MLT","Malta","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MLT/mlt_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7109,474,"MTQ","Martinique","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MTQ/mtq_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7110,478,"MRT","Mauritania","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MRT/mrt_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7111,480,"MUS","Mauritius","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MUS/mus_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7112,484,"MEX","Mexico","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MEX/mex_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7113,492,"MCO","Monaco","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MCO/mco_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7114,496,"MNG","Mongolia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MNG/mng_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7115,498,"MDA","Moldova","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MDA/mda_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7116,499,"MNE","Montenegro","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MNE/mne_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7117,500,"MSR","Montserrat","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MSR/msr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7118,504,"MAR","Morocco","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MAR/mar_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7119,508,"MOZ","Mozambique","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MOZ/moz_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7120,512,"OMN","Oman","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/OMN/omn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7121,516,"NAM","Namibia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NAM/nam_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7122,520,"NRU","Nauru","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NRU/nru_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7123,524,"NPL","Nepal","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NPL/npl_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7124,528,"NLD","Netherlands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NLD/nld_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7125,531,"CUW","Curacao","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CUW/cuw_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7126,533,"ABW","Aruba","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ABW/abw_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7127,534,"SXM","Sint Maarten (Dutch part)","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SXM/sxm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7128,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BES/bes_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7129,540,"NCL","New Caledonia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NCL/ncl_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7130,548,"VUT","Vanuatu","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/VUT/vut_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7131,554,"NZL","New Zealand","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NZL/nzl_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7132,558,"NIC","Nicaragua","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NIC/nic_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7133,562,"NER","Niger","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NER/ner_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7134,566,"NGA","Nigeria","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NGA/nga_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7135,570,"NIU","Niue","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NIU/niu_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7136,574,"NFK","Norfolk Island","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NFK/nfk_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7137,578,"NOR","Norway","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/NOR/nor_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7138,580,"MNP","Northern Mariana Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MNP/mnp_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7139,581,"UMI","United States Minor Outlying Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/UMI/umi_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7140,583,"FSM","Micronesia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/FSM/fsm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7141,584,"MHL","Marshall Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MHL/mhl_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7142,585,"PLW","Palau","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PLW/plw_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7143,586,"PAK","Pakistan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PAK/pak_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7144,591,"PAN","Panama","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PAN/pan_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7145,598,"PNG","Papua New Guinea","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PNG/png_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7146,600,"PRY","Paraguay","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PRY/pry_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7147,604,"PER","Peru","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PER/per_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7148,608,"PHL","Philippines","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PHL/phl_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7149,612,"PCN","Pitcairn Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PCN/pcn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7150,616,"POL","Poland","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/POL/pol_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7151,620,"PRT","Portugal","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PRT/prt_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7152,624,"GNB","Guinea-Bissau","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GNB/gnb_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7153,626,"TLS","East Timor","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TLS/tls_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7154,630,"PRI","Puerto Rico","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/PRI/pri_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7155,634,"QAT","Qatar","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/QAT/qat_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7156,638,"REU","Reunion","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/REU/reu_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7157,642,"ROU","Romania","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ROU/rou_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7158,646,"RWA","Rwanda","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/RWA/rwa_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7159,652,"BLM","Saint Barthelemy","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BLM/blm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7160,654,"SHN","Saint Helena","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SHN/shn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7161,659,"KNA","Saint Kitts and Nevis","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/KNA/kna_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7162,660,"AIA","Anguilla","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/AIA/aia_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7163,662,"LCA","Saint Lucia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/LCA/lca_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7164,663,"MAF","Saint Martin (French part)","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MAF/maf_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7165,666,"SPM","Saint Pierre and Miquelon","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SPM/spm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7166,670,"VCT","Saint Vincent and the Grenadines","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/VCT/vct_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7167,674,"SMR","San Marino","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SMR/smr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7168,678,"STP","Sao Tome and Principe","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/STP/stp_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7169,682,"SAU","Saudi Arabia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SAU/sau_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7170,686,"SEN","Senegal","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SEN/sen_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7171,688,"SRB","Serbia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SRB/srb_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7172,690,"SYC","Seychelles","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SYC/syc_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7173,694,"SLE","Sierra Leone","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SLE/sle_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7174,702,"SGP","Singapore","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SGP/sgp_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7175,703,"SVK","Slovakia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SVK/svk_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7176,704,"VNM","Vietnam","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/VNM/vnm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7177,705,"SVN","Slovenia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SVN/svn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7178,706,"SOM","Somalia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SOM/som_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7179,710,"ZAF","South Africa","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ZAF/zaf_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7180,716,"ZWE","Zimbabwe","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ZWE/zwe_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7181,724,"ESP","Spain","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ESP/esp_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7182,728,"SSD","South Sudan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SSD/ssd_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7183,729,"SDN","Sudan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SDN/sdn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7184,732,"ESH","Western Sahara","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ESH/esh_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7185,740,"SUR","Suriname","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SUR/sur_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7186,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SJM/sjm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7187,748,"SWZ","Swaziland","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SWZ/swz_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7188,752,"SWE","Sweden","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SWE/swe_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7189,756,"CHE","Switzerland","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/CHE/che_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7190,760,"SYR","Syria","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SYR/syr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7191,762,"TJK","Tajikistan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TJK/tjk_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7192,764,"THA","Thailand","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/THA/tha_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7193,768,"TGO","Togo","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TGO/tgo_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7194,772,"TKL","Tokelau","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TKL/tkl_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7195,776,"TON","Tonga","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TON/ton_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7196,780,"TTO","Trinidad and Tobago","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TTO/tto_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7197,784,"ARE","United Arab Emirates","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ARE/are_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7198,788,"TUN","Tunisia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TUN/tun_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7199,792,"TUR","Turkey","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TUR/tur_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7200,795,"TKM","Turkmenistan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TKM/tkm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7201,796,"TCA","Turks and Caicos Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TCA/tca_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7202,798,"TUV","Tuvalu","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TUV/tuv_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7203,800,"UGA","Uganda","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/UGA/uga_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7204,804,"UKR","Ukraine","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/UKR/ukr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7205,807,"MKD","Macedonia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/MKD/mkd_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7206,818,"EGY","Egypt","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/EGY/egy_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7207,826,"GBR","United Kingdom","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GBR/gbr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7208,831,"GGY","Guernsey","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/GGY/ggy_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7209,832,"JEY","Jersey","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/JEY/jey_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7210,833,"IMN","Isle of Man","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/IMN/imn_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7211,834,"TZA","Tanzania","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/TZA/tza_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7212,854,"BFA","Burkina Faso","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/BFA/bfa_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7213,858,"URY","Uruguay","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/URY/ury_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7214,860,"UZB","Uzbekistan","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/UZB/uzb_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7215,862,"VEN","Venezuela","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/VEN/ven_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7216,876,"WLF","Wallis and Futuna","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/WLF/wlf_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7217,882,"WSM","Samoa","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/WSM/wsm_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7218,887,"YEM","Yemen","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/YEM/yem_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7219,894,"ZMB","Zambia","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/ZMB/zmb_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7220,900,"KOS","Kosovo","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/KOS/kos_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7221,901,"SPR","Spratly Islands","ppp_2007_UNadj","GIS/Population/Global_2000_2020/2007/SPR/spr_ppp_2007_UNadj.tif","Estimated total number of people per grid-cell 2007 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7222,643,"RUS","Russia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/RUS/rus_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7223,360,"IDN","Indonesia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/IDN/idn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7224,840,"USA","United States","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/USA/usa_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7225,850,"VIR","Virgin_Islands_U_S","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/VIR/vir_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7226,304,"GRL","Greenland","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GRL/grl_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7227,156,"CHN","China","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CHN/chn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7228,36,"AUS","Australia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/AUS/aus_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7229,76,"BRA","Brazil","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BRA/bra_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7230,124,"CAN","Canada","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CAN/can_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7231,152,"CHL","Chile","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CHL/chl_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7232,4,"AFG","Afghanistan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/AFG/afg_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7233,8,"ALB","Albania","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ALB/alb_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7234,10,"ATA","Antarctica","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ATA/ata_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7235,12,"DZA","Algeria","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/DZA/dza_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7236,16,"ASM","American Samoa","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ASM/asm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7237,20,"AND","Andorra","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/AND/and_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7238,24,"AGO","Angola","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/AGO/ago_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7239,28,"ATG","Antigua and Barbuda","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ATG/atg_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7240,31,"AZE","Azerbaijan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/AZE/aze_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7241,32,"ARG","Argentina","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ARG/arg_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7242,40,"AUT","Austria","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/AUT/aut_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7243,44,"BHS","Bahamas","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BHS/bhs_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7244,48,"BHR","Bahrain","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BHR/bhr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7245,50,"BGD","Bangladesh","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BGD/bgd_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7246,51,"ARM","Armenia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ARM/arm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7247,52,"BRB","Barbados","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BRB/brb_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7248,56,"BEL","Belgium","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BEL/bel_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7249,60,"BMU","Bermuda","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BMU/bmu_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7250,64,"BTN","Bhutan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BTN/btn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7251,68,"BOL","Bolivia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BOL/bol_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7252,70,"BIH","Bosnia and Herzegovina","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BIH/bih_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7253,72,"BWA","Botswana","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BWA/bwa_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7254,74,"BVT","Bouvet Island","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BVT/bvt_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7255,84,"BLZ","Belize","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BLZ/blz_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7256,86,"IOT","British Indian Ocean Territory","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/IOT/iot_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7257,90,"SLB","Solomon Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SLB/slb_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7258,92,"VGB","British Virgin Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/VGB/vgb_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7259,96,"BRN","Brunei","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BRN/brn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7260,100,"BGR","Bulgaria","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BGR/bgr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7261,104,"MMR","Myanmar","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MMR/mmr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7262,108,"BDI","Burundi","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BDI/bdi_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7263,112,"BLR","Belarus","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BLR/blr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7264,116,"KHM","Cambodia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/KHM/khm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7265,120,"CMR","Cameroon","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CMR/cmr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7266,132,"CPV","Cape Verde","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CPV/cpv_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7267,136,"CYM","Cayman Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CYM/cym_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7268,140,"CAF","Central African Republic","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CAF/caf_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7269,144,"LKA","Sri Lanka","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LKA/lka_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7270,148,"TCD","Chad","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TCD/tcd_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7271,158,"TWN","Taiwan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TWN/twn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7272,170,"COL","Colombia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/COL/col_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7273,174,"COM","Comoros","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/COM/com_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7274,175,"MYT","Mayotte","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MYT/myt_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7275,178,"COG","Republic of Congo","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/COG/cog_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7276,180,"COD","Democratic Republic of the Congo","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/COD/cod_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7277,184,"COK","Cook Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/COK/cok_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7278,188,"CRI","Costa Rica","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CRI/cri_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7279,191,"HRV","Croatia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/HRV/hrv_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7280,192,"CUB","Cuba","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CUB/cub_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7281,196,"CYP","Cyprus","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CYP/cyp_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7282,203,"CZE","Czech Republic","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CZE/cze_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7283,204,"BEN","Benin","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BEN/ben_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7284,208,"DNK","Denmark","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/DNK/dnk_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7285,212,"DMA","Dominica","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/DMA/dma_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7286,214,"DOM","Dominican Republic","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/DOM/dom_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7287,218,"ECU","Ecuador","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ECU/ecu_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7288,222,"SLV","El Salvador","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SLV/slv_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7289,226,"GNQ","Equatorial Guinea","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GNQ/gnq_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7290,231,"ETH","Ethiopia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ETH/eth_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7291,232,"ERI","Eritrea","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ERI/eri_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7292,233,"EST","Estonia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/EST/est_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7293,234,"FRO","Faroe Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/FRO/fro_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7294,238,"FLK","Falkland Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/FLK/flk_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7295,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SGS/sgs_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7296,242,"FJI","Fiji","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/FJI/fji_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7297,246,"FIN","Finland","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/FIN/fin_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7298,248,"ALA","Aland Islands ","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ALA/ala_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7299,250,"FRA","France","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/FRA/fra_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7300,254,"GUF","French Guiana","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GUF/guf_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7301,258,"PYF","French Polynesia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PYF/pyf_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7302,260,"ATF","French Southern Territories","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ATF/atf_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7303,262,"DJI","Djibouti","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/DJI/dji_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7304,266,"GAB","Gabon","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GAB/gab_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7305,268,"GEO","Georgia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GEO/geo_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7306,270,"GMB","Gambia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GMB/gmb_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7307,275,"PSE","Palestina","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PSE/pse_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7308,276,"DEU","Germany","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/DEU/deu_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7309,288,"GHA","Ghana","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GHA/gha_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7310,292,"GIB","Gibraltar","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GIB/gib_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7311,296,"KIR","Kiribati","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/KIR/kir_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7312,300,"GRC","Greece","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GRC/grc_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7313,308,"GRD","Grenada","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GRD/grd_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7314,312,"GLP","Guadeloupe","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GLP/glp_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7315,316,"GUM","Guam","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GUM/gum_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7316,320,"GTM","Guatemala","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GTM/gtm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7317,324,"GIN","Guinea","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GIN/gin_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7318,328,"GUY","Guyana","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GUY/guy_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7319,332,"HTI","Haiti","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/HTI/hti_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7320,334,"HMD","Heard Island and McDonald Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/HMD/hmd_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7321,336,"VAT","Vatican City","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/VAT/vat_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7322,340,"HND","Honduras","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/HND/hnd_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7323,344,"HKG","Hong Kong","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/HKG/hkg_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7324,348,"HUN","Hungary","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/HUN/hun_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7325,352,"ISL","Iceland","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ISL/isl_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7326,356,"IND","India","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/IND/ind_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7327,364,"IRN","Iran","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/IRN/irn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7328,368,"IRQ","Iraq","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/IRQ/irq_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7329,372,"IRL","Ireland","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/IRL/irl_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7330,376,"ISR","Israel","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ISR/isr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7331,380,"ITA","Italy","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ITA/ita_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7332,384,"CIV","CIte dIvoire","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CIV/civ_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7333,388,"JAM","Jamaica","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/JAM/jam_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7334,392,"JPN","Japan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/JPN/jpn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7335,398,"KAZ","Kazakhstan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/KAZ/kaz_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7336,400,"JOR","Jordan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/JOR/jor_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7337,404,"KEN","Kenya","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/KEN/ken_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7338,408,"PRK","North Korea","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PRK/prk_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7339,410,"KOR","South Korea","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/KOR/kor_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7340,414,"KWT","Kuwait","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/KWT/kwt_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7341,417,"KGZ","Kyrgyzstan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/KGZ/kgz_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7342,418,"LAO","Laos","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LAO/lao_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7343,422,"LBN","Lebanon","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LBN/lbn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7344,426,"LSO","Lesotho","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LSO/lso_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7345,428,"LVA","Latvia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LVA/lva_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7346,430,"LBR","Liberia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LBR/lbr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7347,434,"LBY","Libya","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LBY/lby_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7348,438,"LIE","Liechtenstein","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LIE/lie_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7349,440,"LTU","Lithuania","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LTU/ltu_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7350,442,"LUX","Luxembourg","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LUX/lux_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7351,446,"MAC","Macao","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MAC/mac_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7352,450,"MDG","Madagascar","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MDG/mdg_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7353,454,"MWI","Malawi","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MWI/mwi_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7354,458,"MYS","Malaysia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MYS/mys_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7355,462,"MDV","Maldives","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MDV/mdv_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7356,466,"MLI","Mali","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MLI/mli_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7357,470,"MLT","Malta","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MLT/mlt_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7358,474,"MTQ","Martinique","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MTQ/mtq_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7359,478,"MRT","Mauritania","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MRT/mrt_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7360,480,"MUS","Mauritius","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MUS/mus_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7361,484,"MEX","Mexico","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MEX/mex_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7362,492,"MCO","Monaco","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MCO/mco_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7363,496,"MNG","Mongolia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MNG/mng_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7364,498,"MDA","Moldova","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MDA/mda_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7365,499,"MNE","Montenegro","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MNE/mne_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7366,500,"MSR","Montserrat","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MSR/msr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7367,504,"MAR","Morocco","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MAR/mar_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7368,508,"MOZ","Mozambique","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MOZ/moz_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7369,512,"OMN","Oman","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/OMN/omn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7370,516,"NAM","Namibia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NAM/nam_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7371,520,"NRU","Nauru","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NRU/nru_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7372,524,"NPL","Nepal","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NPL/npl_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7373,528,"NLD","Netherlands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NLD/nld_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7374,531,"CUW","Curacao","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CUW/cuw_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7375,533,"ABW","Aruba","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ABW/abw_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7376,534,"SXM","Sint Maarten (Dutch part)","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SXM/sxm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7377,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BES/bes_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7378,540,"NCL","New Caledonia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NCL/ncl_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7379,548,"VUT","Vanuatu","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/VUT/vut_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7380,554,"NZL","New Zealand","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NZL/nzl_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7381,558,"NIC","Nicaragua","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NIC/nic_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7382,562,"NER","Niger","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NER/ner_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7383,566,"NGA","Nigeria","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NGA/nga_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7384,570,"NIU","Niue","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NIU/niu_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7385,574,"NFK","Norfolk Island","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NFK/nfk_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7386,578,"NOR","Norway","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/NOR/nor_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7387,580,"MNP","Northern Mariana Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MNP/mnp_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7388,581,"UMI","United States Minor Outlying Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/UMI/umi_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7389,583,"FSM","Micronesia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/FSM/fsm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7390,584,"MHL","Marshall Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MHL/mhl_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7391,585,"PLW","Palau","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PLW/plw_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7392,586,"PAK","Pakistan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PAK/pak_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7393,591,"PAN","Panama","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PAN/pan_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7394,598,"PNG","Papua New Guinea","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PNG/png_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7395,600,"PRY","Paraguay","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PRY/pry_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7396,604,"PER","Peru","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PER/per_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7397,608,"PHL","Philippines","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PHL/phl_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7398,612,"PCN","Pitcairn Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PCN/pcn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7399,616,"POL","Poland","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/POL/pol_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7400,620,"PRT","Portugal","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PRT/prt_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7401,624,"GNB","Guinea-Bissau","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GNB/gnb_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7402,626,"TLS","East Timor","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TLS/tls_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7403,630,"PRI","Puerto Rico","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/PRI/pri_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7404,634,"QAT","Qatar","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/QAT/qat_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7405,638,"REU","Reunion","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/REU/reu_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7406,642,"ROU","Romania","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ROU/rou_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7407,646,"RWA","Rwanda","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/RWA/rwa_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7408,652,"BLM","Saint Barthelemy","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BLM/blm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7409,654,"SHN","Saint Helena","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SHN/shn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7410,659,"KNA","Saint Kitts and Nevis","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/KNA/kna_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7411,660,"AIA","Anguilla","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/AIA/aia_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7412,662,"LCA","Saint Lucia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/LCA/lca_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7413,663,"MAF","Saint Martin (French part)","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MAF/maf_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7414,666,"SPM","Saint Pierre and Miquelon","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SPM/spm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7415,670,"VCT","Saint Vincent and the Grenadines","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/VCT/vct_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7416,674,"SMR","San Marino","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SMR/smr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7417,678,"STP","Sao Tome and Principe","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/STP/stp_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7418,682,"SAU","Saudi Arabia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SAU/sau_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7419,686,"SEN","Senegal","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SEN/sen_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7420,688,"SRB","Serbia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SRB/srb_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7421,690,"SYC","Seychelles","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SYC/syc_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7422,694,"SLE","Sierra Leone","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SLE/sle_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7423,702,"SGP","Singapore","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SGP/sgp_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7424,703,"SVK","Slovakia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SVK/svk_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7425,704,"VNM","Vietnam","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/VNM/vnm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7426,705,"SVN","Slovenia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SVN/svn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7427,706,"SOM","Somalia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SOM/som_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7428,710,"ZAF","South Africa","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ZAF/zaf_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7429,716,"ZWE","Zimbabwe","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ZWE/zwe_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7430,724,"ESP","Spain","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ESP/esp_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7431,728,"SSD","South Sudan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SSD/ssd_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7432,729,"SDN","Sudan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SDN/sdn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7433,732,"ESH","Western Sahara","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ESH/esh_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7434,740,"SUR","Suriname","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SUR/sur_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7435,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SJM/sjm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7436,748,"SWZ","Swaziland","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SWZ/swz_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7437,752,"SWE","Sweden","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SWE/swe_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7438,756,"CHE","Switzerland","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/CHE/che_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7439,760,"SYR","Syria","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SYR/syr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7440,762,"TJK","Tajikistan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TJK/tjk_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7441,764,"THA","Thailand","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/THA/tha_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7442,768,"TGO","Togo","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TGO/tgo_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7443,772,"TKL","Tokelau","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TKL/tkl_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7444,776,"TON","Tonga","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TON/ton_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7445,780,"TTO","Trinidad and Tobago","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TTO/tto_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7446,784,"ARE","United Arab Emirates","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ARE/are_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7447,788,"TUN","Tunisia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TUN/tun_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7448,792,"TUR","Turkey","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TUR/tur_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7449,795,"TKM","Turkmenistan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TKM/tkm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7450,796,"TCA","Turks and Caicos Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TCA/tca_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7451,798,"TUV","Tuvalu","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TUV/tuv_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7452,800,"UGA","Uganda","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/UGA/uga_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7453,804,"UKR","Ukraine","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/UKR/ukr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7454,807,"MKD","Macedonia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/MKD/mkd_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7455,818,"EGY","Egypt","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/EGY/egy_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7456,826,"GBR","United Kingdom","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GBR/gbr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7457,831,"GGY","Guernsey","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/GGY/ggy_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7458,832,"JEY","Jersey","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/JEY/jey_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7459,833,"IMN","Isle of Man","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/IMN/imn_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7460,834,"TZA","Tanzania","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/TZA/tza_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7461,854,"BFA","Burkina Faso","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/BFA/bfa_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7462,858,"URY","Uruguay","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/URY/ury_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7463,860,"UZB","Uzbekistan","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/UZB/uzb_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7464,862,"VEN","Venezuela","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/VEN/ven_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7465,876,"WLF","Wallis and Futuna","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/WLF/wlf_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7466,882,"WSM","Samoa","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/WSM/wsm_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7467,887,"YEM","Yemen","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/YEM/yem_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7468,894,"ZMB","Zambia","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/ZMB/zmb_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7469,900,"KOS","Kosovo","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/KOS/kos_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7470,901,"SPR","Spratly Islands","ppp_2008_UNadj","GIS/Population/Global_2000_2020/2008/SPR/spr_ppp_2008_UNadj.tif","Estimated total number of people per grid-cell 2008 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7471,643,"RUS","Russia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/RUS/rus_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7472,360,"IDN","Indonesia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/IDN/idn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7473,840,"USA","United States","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/USA/usa_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7474,850,"VIR","Virgin_Islands_U_S","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/VIR/vir_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7475,304,"GRL","Greenland","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GRL/grl_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7476,156,"CHN","China","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CHN/chn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7477,36,"AUS","Australia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/AUS/aus_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7478,76,"BRA","Brazil","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BRA/bra_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7479,124,"CAN","Canada","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CAN/can_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7480,152,"CHL","Chile","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CHL/chl_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7481,4,"AFG","Afghanistan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/AFG/afg_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7482,8,"ALB","Albania","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ALB/alb_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7483,10,"ATA","Antarctica","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ATA/ata_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7484,12,"DZA","Algeria","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/DZA/dza_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7485,16,"ASM","American Samoa","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ASM/asm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7486,20,"AND","Andorra","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/AND/and_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7487,24,"AGO","Angola","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/AGO/ago_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7488,28,"ATG","Antigua and Barbuda","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ATG/atg_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7489,31,"AZE","Azerbaijan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/AZE/aze_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7490,32,"ARG","Argentina","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ARG/arg_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7491,40,"AUT","Austria","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/AUT/aut_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7492,44,"BHS","Bahamas","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BHS/bhs_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7493,48,"BHR","Bahrain","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BHR/bhr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7494,50,"BGD","Bangladesh","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BGD/bgd_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7495,51,"ARM","Armenia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ARM/arm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7496,52,"BRB","Barbados","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BRB/brb_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7497,56,"BEL","Belgium","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BEL/bel_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7498,60,"BMU","Bermuda","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BMU/bmu_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7499,64,"BTN","Bhutan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BTN/btn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7500,68,"BOL","Bolivia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BOL/bol_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7501,70,"BIH","Bosnia and Herzegovina","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BIH/bih_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7502,72,"BWA","Botswana","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BWA/bwa_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7503,74,"BVT","Bouvet Island","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BVT/bvt_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7504,84,"BLZ","Belize","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BLZ/blz_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7505,86,"IOT","British Indian Ocean Territory","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/IOT/iot_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7506,90,"SLB","Solomon Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SLB/slb_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7507,92,"VGB","British Virgin Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/VGB/vgb_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7508,96,"BRN","Brunei","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BRN/brn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7509,100,"BGR","Bulgaria","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BGR/bgr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7510,104,"MMR","Myanmar","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MMR/mmr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7511,108,"BDI","Burundi","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BDI/bdi_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7512,112,"BLR","Belarus","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BLR/blr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7513,116,"KHM","Cambodia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/KHM/khm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7514,120,"CMR","Cameroon","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CMR/cmr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7515,132,"CPV","Cape Verde","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CPV/cpv_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7516,136,"CYM","Cayman Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CYM/cym_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7517,140,"CAF","Central African Republic","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CAF/caf_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7518,144,"LKA","Sri Lanka","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LKA/lka_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7519,148,"TCD","Chad","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TCD/tcd_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7520,158,"TWN","Taiwan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TWN/twn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7521,170,"COL","Colombia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/COL/col_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7522,174,"COM","Comoros","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/COM/com_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7523,175,"MYT","Mayotte","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MYT/myt_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7524,178,"COG","Republic of Congo","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/COG/cog_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7525,180,"COD","Democratic Republic of the Congo","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/COD/cod_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7526,184,"COK","Cook Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/COK/cok_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7527,188,"CRI","Costa Rica","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CRI/cri_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7528,191,"HRV","Croatia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/HRV/hrv_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7529,192,"CUB","Cuba","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CUB/cub_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7530,196,"CYP","Cyprus","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CYP/cyp_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7531,203,"CZE","Czech Republic","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CZE/cze_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7532,204,"BEN","Benin","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BEN/ben_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7533,208,"DNK","Denmark","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/DNK/dnk_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7534,212,"DMA","Dominica","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/DMA/dma_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7535,214,"DOM","Dominican Republic","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/DOM/dom_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7536,218,"ECU","Ecuador","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ECU/ecu_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7537,222,"SLV","El Salvador","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SLV/slv_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7538,226,"GNQ","Equatorial Guinea","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GNQ/gnq_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7539,231,"ETH","Ethiopia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ETH/eth_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7540,232,"ERI","Eritrea","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ERI/eri_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7541,233,"EST","Estonia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/EST/est_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7542,234,"FRO","Faroe Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/FRO/fro_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7543,238,"FLK","Falkland Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/FLK/flk_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7544,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SGS/sgs_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7545,242,"FJI","Fiji","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/FJI/fji_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7546,246,"FIN","Finland","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/FIN/fin_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7547,248,"ALA","Aland Islands ","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ALA/ala_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7548,250,"FRA","France","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/FRA/fra_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7549,254,"GUF","French Guiana","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GUF/guf_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7550,258,"PYF","French Polynesia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PYF/pyf_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7551,260,"ATF","French Southern Territories","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ATF/atf_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7552,262,"DJI","Djibouti","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/DJI/dji_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7553,266,"GAB","Gabon","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GAB/gab_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7554,268,"GEO","Georgia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GEO/geo_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7555,270,"GMB","Gambia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GMB/gmb_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7556,275,"PSE","Palestina","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PSE/pse_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7557,276,"DEU","Germany","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/DEU/deu_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7558,288,"GHA","Ghana","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GHA/gha_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7559,292,"GIB","Gibraltar","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GIB/gib_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7560,296,"KIR","Kiribati","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/KIR/kir_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7561,300,"GRC","Greece","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GRC/grc_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7562,308,"GRD","Grenada","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GRD/grd_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7563,312,"GLP","Guadeloupe","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GLP/glp_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7564,316,"GUM","Guam","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GUM/gum_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7565,320,"GTM","Guatemala","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GTM/gtm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7566,324,"GIN","Guinea","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GIN/gin_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7567,328,"GUY","Guyana","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GUY/guy_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7568,332,"HTI","Haiti","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/HTI/hti_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7569,334,"HMD","Heard Island and McDonald Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/HMD/hmd_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7570,336,"VAT","Vatican City","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/VAT/vat_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7571,340,"HND","Honduras","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/HND/hnd_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7572,344,"HKG","Hong Kong","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/HKG/hkg_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7573,348,"HUN","Hungary","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/HUN/hun_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7574,352,"ISL","Iceland","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ISL/isl_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7575,356,"IND","India","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/IND/ind_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7576,364,"IRN","Iran","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/IRN/irn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7577,368,"IRQ","Iraq","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/IRQ/irq_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7578,372,"IRL","Ireland","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/IRL/irl_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7579,376,"ISR","Israel","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ISR/isr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7580,380,"ITA","Italy","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ITA/ita_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7581,384,"CIV","CIte dIvoire","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CIV/civ_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7582,388,"JAM","Jamaica","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/JAM/jam_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7583,392,"JPN","Japan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/JPN/jpn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7584,398,"KAZ","Kazakhstan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/KAZ/kaz_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7585,400,"JOR","Jordan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/JOR/jor_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7586,404,"KEN","Kenya","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/KEN/ken_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7587,408,"PRK","North Korea","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PRK/prk_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7588,410,"KOR","South Korea","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/KOR/kor_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7589,414,"KWT","Kuwait","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/KWT/kwt_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7590,417,"KGZ","Kyrgyzstan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/KGZ/kgz_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7591,418,"LAO","Laos","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LAO/lao_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7592,422,"LBN","Lebanon","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LBN/lbn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7593,426,"LSO","Lesotho","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LSO/lso_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7594,428,"LVA","Latvia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LVA/lva_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7595,430,"LBR","Liberia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LBR/lbr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7596,434,"LBY","Libya","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LBY/lby_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7597,438,"LIE","Liechtenstein","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LIE/lie_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7598,440,"LTU","Lithuania","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LTU/ltu_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7599,442,"LUX","Luxembourg","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LUX/lux_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7600,446,"MAC","Macao","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MAC/mac_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7601,450,"MDG","Madagascar","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MDG/mdg_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7602,454,"MWI","Malawi","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MWI/mwi_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7603,458,"MYS","Malaysia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MYS/mys_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7604,462,"MDV","Maldives","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MDV/mdv_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7605,466,"MLI","Mali","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MLI/mli_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7606,470,"MLT","Malta","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MLT/mlt_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7607,474,"MTQ","Martinique","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MTQ/mtq_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7608,478,"MRT","Mauritania","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MRT/mrt_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7609,480,"MUS","Mauritius","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MUS/mus_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7610,484,"MEX","Mexico","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MEX/mex_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7611,492,"MCO","Monaco","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MCO/mco_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7612,496,"MNG","Mongolia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MNG/mng_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7613,498,"MDA","Moldova","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MDA/mda_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7614,499,"MNE","Montenegro","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MNE/mne_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7615,500,"MSR","Montserrat","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MSR/msr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7616,504,"MAR","Morocco","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MAR/mar_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7617,508,"MOZ","Mozambique","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MOZ/moz_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7618,512,"OMN","Oman","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/OMN/omn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7619,516,"NAM","Namibia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NAM/nam_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7620,520,"NRU","Nauru","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NRU/nru_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7621,524,"NPL","Nepal","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NPL/npl_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7622,528,"NLD","Netherlands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NLD/nld_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7623,531,"CUW","Curacao","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CUW/cuw_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7624,533,"ABW","Aruba","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ABW/abw_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7625,534,"SXM","Sint Maarten (Dutch part)","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SXM/sxm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7626,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BES/bes_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7627,540,"NCL","New Caledonia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NCL/ncl_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7628,548,"VUT","Vanuatu","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/VUT/vut_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7629,554,"NZL","New Zealand","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NZL/nzl_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7630,558,"NIC","Nicaragua","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NIC/nic_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7631,562,"NER","Niger","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NER/ner_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7632,566,"NGA","Nigeria","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NGA/nga_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7633,570,"NIU","Niue","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NIU/niu_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7634,574,"NFK","Norfolk Island","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NFK/nfk_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7635,578,"NOR","Norway","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/NOR/nor_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7636,580,"MNP","Northern Mariana Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MNP/mnp_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7637,581,"UMI","United States Minor Outlying Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/UMI/umi_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7638,583,"FSM","Micronesia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/FSM/fsm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7639,584,"MHL","Marshall Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MHL/mhl_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7640,585,"PLW","Palau","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PLW/plw_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7641,586,"PAK","Pakistan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PAK/pak_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7642,591,"PAN","Panama","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PAN/pan_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7643,598,"PNG","Papua New Guinea","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PNG/png_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7644,600,"PRY","Paraguay","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PRY/pry_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7645,604,"PER","Peru","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PER/per_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7646,608,"PHL","Philippines","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PHL/phl_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7647,612,"PCN","Pitcairn Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PCN/pcn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7648,616,"POL","Poland","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/POL/pol_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7649,620,"PRT","Portugal","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PRT/prt_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7650,624,"GNB","Guinea-Bissau","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GNB/gnb_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7651,626,"TLS","East Timor","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TLS/tls_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7652,630,"PRI","Puerto Rico","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/PRI/pri_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7653,634,"QAT","Qatar","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/QAT/qat_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7654,638,"REU","Reunion","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/REU/reu_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7655,642,"ROU","Romania","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ROU/rou_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7656,646,"RWA","Rwanda","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/RWA/rwa_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7657,652,"BLM","Saint Barthelemy","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BLM/blm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7658,654,"SHN","Saint Helena","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SHN/shn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7659,659,"KNA","Saint Kitts and Nevis","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/KNA/kna_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7660,660,"AIA","Anguilla","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/AIA/aia_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7661,662,"LCA","Saint Lucia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/LCA/lca_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7662,663,"MAF","Saint Martin (French part)","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MAF/maf_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7663,666,"SPM","Saint Pierre and Miquelon","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SPM/spm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7664,670,"VCT","Saint Vincent and the Grenadines","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/VCT/vct_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7665,674,"SMR","San Marino","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SMR/smr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7666,678,"STP","Sao Tome and Principe","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/STP/stp_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7667,682,"SAU","Saudi Arabia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SAU/sau_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7668,686,"SEN","Senegal","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SEN/sen_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7669,688,"SRB","Serbia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SRB/srb_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7670,690,"SYC","Seychelles","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SYC/syc_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7671,694,"SLE","Sierra Leone","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SLE/sle_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7672,702,"SGP","Singapore","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SGP/sgp_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7673,703,"SVK","Slovakia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SVK/svk_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7674,704,"VNM","Vietnam","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/VNM/vnm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7675,705,"SVN","Slovenia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SVN/svn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7676,706,"SOM","Somalia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SOM/som_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7677,710,"ZAF","South Africa","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ZAF/zaf_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7678,716,"ZWE","Zimbabwe","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ZWE/zwe_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7679,724,"ESP","Spain","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ESP/esp_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7680,728,"SSD","South Sudan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SSD/ssd_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7681,729,"SDN","Sudan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SDN/sdn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7682,732,"ESH","Western Sahara","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ESH/esh_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7683,740,"SUR","Suriname","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SUR/sur_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7684,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SJM/sjm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7685,748,"SWZ","Swaziland","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SWZ/swz_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7686,752,"SWE","Sweden","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SWE/swe_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7687,756,"CHE","Switzerland","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/CHE/che_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7688,760,"SYR","Syria","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SYR/syr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7689,762,"TJK","Tajikistan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TJK/tjk_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7690,764,"THA","Thailand","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/THA/tha_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7691,768,"TGO","Togo","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TGO/tgo_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7692,772,"TKL","Tokelau","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TKL/tkl_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7693,776,"TON","Tonga","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TON/ton_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7694,780,"TTO","Trinidad and Tobago","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TTO/tto_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7695,784,"ARE","United Arab Emirates","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ARE/are_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7696,788,"TUN","Tunisia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TUN/tun_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7697,792,"TUR","Turkey","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TUR/tur_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7698,795,"TKM","Turkmenistan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TKM/tkm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7699,796,"TCA","Turks and Caicos Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TCA/tca_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7700,798,"TUV","Tuvalu","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TUV/tuv_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7701,800,"UGA","Uganda","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/UGA/uga_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7702,804,"UKR","Ukraine","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/UKR/ukr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7703,807,"MKD","Macedonia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/MKD/mkd_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7704,818,"EGY","Egypt","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/EGY/egy_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7705,826,"GBR","United Kingdom","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GBR/gbr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7706,831,"GGY","Guernsey","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/GGY/ggy_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7707,832,"JEY","Jersey","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/JEY/jey_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7708,833,"IMN","Isle of Man","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/IMN/imn_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7709,834,"TZA","Tanzania","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/TZA/tza_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7710,854,"BFA","Burkina Faso","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/BFA/bfa_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7711,858,"URY","Uruguay","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/URY/ury_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7712,860,"UZB","Uzbekistan","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/UZB/uzb_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7713,862,"VEN","Venezuela","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/VEN/ven_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7714,876,"WLF","Wallis and Futuna","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/WLF/wlf_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7715,882,"WSM","Samoa","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/WSM/wsm_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7716,887,"YEM","Yemen","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/YEM/yem_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7717,894,"ZMB","Zambia","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/ZMB/zmb_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7718,900,"KOS","Kosovo","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/KOS/kos_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7719,901,"SPR","Spratly Islands","ppp_2009_UNadj","GIS/Population/Global_2000_2020/2009/SPR/spr_ppp_2009_UNadj.tif","Estimated total number of people per grid-cell 2009 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7720,643,"RUS","Russia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/RUS/rus_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7721,360,"IDN","Indonesia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/IDN/idn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7722,840,"USA","United States","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/USA/usa_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7723,850,"VIR","Virgin_Islands_U_S","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/VIR/vir_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7724,304,"GRL","Greenland","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GRL/grl_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7725,156,"CHN","China","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CHN/chn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7726,36,"AUS","Australia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/AUS/aus_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7727,76,"BRA","Brazil","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BRA/bra_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7728,124,"CAN","Canada","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CAN/can_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7729,152,"CHL","Chile","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CHL/chl_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7730,4,"AFG","Afghanistan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/AFG/afg_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7731,8,"ALB","Albania","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ALB/alb_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7732,10,"ATA","Antarctica","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ATA/ata_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7733,12,"DZA","Algeria","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/DZA/dza_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7734,16,"ASM","American Samoa","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ASM/asm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7735,20,"AND","Andorra","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/AND/and_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7736,24,"AGO","Angola","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/AGO/ago_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7737,28,"ATG","Antigua and Barbuda","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ATG/atg_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7738,31,"AZE","Azerbaijan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/AZE/aze_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7739,32,"ARG","Argentina","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ARG/arg_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7740,40,"AUT","Austria","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/AUT/aut_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7741,44,"BHS","Bahamas","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BHS/bhs_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7742,48,"BHR","Bahrain","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BHR/bhr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7743,50,"BGD","Bangladesh","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BGD/bgd_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7744,51,"ARM","Armenia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ARM/arm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7745,52,"BRB","Barbados","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BRB/brb_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7746,56,"BEL","Belgium","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BEL/bel_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7747,60,"BMU","Bermuda","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BMU/bmu_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7748,64,"BTN","Bhutan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BTN/btn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7749,68,"BOL","Bolivia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BOL/bol_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7750,70,"BIH","Bosnia and Herzegovina","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BIH/bih_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7751,72,"BWA","Botswana","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BWA/bwa_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7752,74,"BVT","Bouvet Island","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BVT/bvt_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7753,84,"BLZ","Belize","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BLZ/blz_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7754,86,"IOT","British Indian Ocean Territory","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/IOT/iot_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7755,90,"SLB","Solomon Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SLB/slb_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7756,92,"VGB","British Virgin Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/VGB/vgb_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7757,96,"BRN","Brunei","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BRN/brn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7758,100,"BGR","Bulgaria","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BGR/bgr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7759,104,"MMR","Myanmar","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MMR/mmr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7760,108,"BDI","Burundi","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BDI/bdi_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7761,112,"BLR","Belarus","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BLR/blr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7762,116,"KHM","Cambodia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/KHM/khm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7763,120,"CMR","Cameroon","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CMR/cmr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7764,132,"CPV","Cape Verde","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CPV/cpv_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7765,136,"CYM","Cayman Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CYM/cym_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7766,140,"CAF","Central African Republic","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CAF/caf_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7767,144,"LKA","Sri Lanka","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LKA/lka_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7768,148,"TCD","Chad","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TCD/tcd_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7769,158,"TWN","Taiwan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TWN/twn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7770,170,"COL","Colombia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/COL/col_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7771,174,"COM","Comoros","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/COM/com_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7772,175,"MYT","Mayotte","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MYT/myt_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7773,178,"COG","Republic of Congo","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/COG/cog_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7774,180,"COD","Democratic Republic of the Congo","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/COD/cod_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7775,184,"COK","Cook Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/COK/cok_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7776,188,"CRI","Costa Rica","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CRI/cri_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7777,191,"HRV","Croatia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/HRV/hrv_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7778,192,"CUB","Cuba","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CUB/cub_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7779,196,"CYP","Cyprus","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CYP/cyp_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7780,203,"CZE","Czech Republic","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CZE/cze_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7781,204,"BEN","Benin","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BEN/ben_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7782,208,"DNK","Denmark","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/DNK/dnk_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7783,212,"DMA","Dominica","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/DMA/dma_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7784,214,"DOM","Dominican Republic","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/DOM/dom_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7785,218,"ECU","Ecuador","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ECU/ecu_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7786,222,"SLV","El Salvador","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SLV/slv_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7787,226,"GNQ","Equatorial Guinea","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GNQ/gnq_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7788,231,"ETH","Ethiopia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ETH/eth_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7789,232,"ERI","Eritrea","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ERI/eri_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7790,233,"EST","Estonia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/EST/est_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7791,234,"FRO","Faroe Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/FRO/fro_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7792,238,"FLK","Falkland Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/FLK/flk_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7793,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SGS/sgs_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7794,242,"FJI","Fiji","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/FJI/fji_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7795,246,"FIN","Finland","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/FIN/fin_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7796,248,"ALA","Aland Islands ","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ALA/ala_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7797,250,"FRA","France","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/FRA/fra_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7798,254,"GUF","French Guiana","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GUF/guf_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7799,258,"PYF","French Polynesia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PYF/pyf_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7800,260,"ATF","French Southern Territories","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ATF/atf_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7801,262,"DJI","Djibouti","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/DJI/dji_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7802,266,"GAB","Gabon","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GAB/gab_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7803,268,"GEO","Georgia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GEO/geo_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7804,270,"GMB","Gambia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GMB/gmb_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7805,275,"PSE","Palestina","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PSE/pse_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7806,276,"DEU","Germany","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/DEU/deu_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7807,288,"GHA","Ghana","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GHA/gha_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7808,292,"GIB","Gibraltar","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GIB/gib_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7809,296,"KIR","Kiribati","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/KIR/kir_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7810,300,"GRC","Greece","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GRC/grc_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7811,308,"GRD","Grenada","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GRD/grd_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7812,312,"GLP","Guadeloupe","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GLP/glp_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7813,316,"GUM","Guam","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GUM/gum_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7814,320,"GTM","Guatemala","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GTM/gtm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7815,324,"GIN","Guinea","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GIN/gin_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7816,328,"GUY","Guyana","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GUY/guy_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7817,332,"HTI","Haiti","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/HTI/hti_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7818,334,"HMD","Heard Island and McDonald Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/HMD/hmd_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7819,336,"VAT","Vatican City","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/VAT/vat_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7820,340,"HND","Honduras","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/HND/hnd_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7821,344,"HKG","Hong Kong","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/HKG/hkg_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7822,348,"HUN","Hungary","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/HUN/hun_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7823,352,"ISL","Iceland","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ISL/isl_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7824,356,"IND","India","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/IND/ind_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7825,364,"IRN","Iran","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/IRN/irn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7826,368,"IRQ","Iraq","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/IRQ/irq_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7827,372,"IRL","Ireland","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/IRL/irl_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7828,376,"ISR","Israel","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ISR/isr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7829,380,"ITA","Italy","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ITA/ita_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7830,384,"CIV","CIte dIvoire","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CIV/civ_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7831,388,"JAM","Jamaica","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/JAM/jam_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7832,392,"JPN","Japan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/JPN/jpn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7833,398,"KAZ","Kazakhstan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/KAZ/kaz_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7834,400,"JOR","Jordan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/JOR/jor_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7835,404,"KEN","Kenya","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/KEN/ken_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7836,408,"PRK","North Korea","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PRK/prk_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7837,410,"KOR","South Korea","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/KOR/kor_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7838,414,"KWT","Kuwait","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/KWT/kwt_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7839,417,"KGZ","Kyrgyzstan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/KGZ/kgz_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7840,418,"LAO","Laos","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LAO/lao_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7841,422,"LBN","Lebanon","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LBN/lbn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7842,426,"LSO","Lesotho","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LSO/lso_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7843,428,"LVA","Latvia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LVA/lva_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7844,430,"LBR","Liberia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LBR/lbr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7845,434,"LBY","Libya","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LBY/lby_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7846,438,"LIE","Liechtenstein","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LIE/lie_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7847,440,"LTU","Lithuania","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LTU/ltu_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7848,442,"LUX","Luxembourg","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LUX/lux_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7849,446,"MAC","Macao","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MAC/mac_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7850,450,"MDG","Madagascar","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MDG/mdg_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7851,454,"MWI","Malawi","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MWI/mwi_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7852,458,"MYS","Malaysia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MYS/mys_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7853,462,"MDV","Maldives","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MDV/mdv_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7854,466,"MLI","Mali","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MLI/mli_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7855,470,"MLT","Malta","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MLT/mlt_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7856,474,"MTQ","Martinique","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MTQ/mtq_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7857,478,"MRT","Mauritania","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MRT/mrt_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7858,480,"MUS","Mauritius","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MUS/mus_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7859,484,"MEX","Mexico","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MEX/mex_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7860,492,"MCO","Monaco","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MCO/mco_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7861,496,"MNG","Mongolia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MNG/mng_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7862,498,"MDA","Moldova","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MDA/mda_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7863,499,"MNE","Montenegro","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MNE/mne_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7864,500,"MSR","Montserrat","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MSR/msr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7865,504,"MAR","Morocco","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MAR/mar_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7866,508,"MOZ","Mozambique","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MOZ/moz_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7867,512,"OMN","Oman","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/OMN/omn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7868,516,"NAM","Namibia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NAM/nam_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7869,520,"NRU","Nauru","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NRU/nru_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7870,524,"NPL","Nepal","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NPL/npl_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7871,528,"NLD","Netherlands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NLD/nld_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7872,531,"CUW","Curacao","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CUW/cuw_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7873,533,"ABW","Aruba","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ABW/abw_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7874,534,"SXM","Sint Maarten (Dutch part)","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SXM/sxm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7875,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BES/bes_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7876,540,"NCL","New Caledonia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NCL/ncl_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7877,548,"VUT","Vanuatu","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/VUT/vut_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7878,554,"NZL","New Zealand","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NZL/nzl_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7879,558,"NIC","Nicaragua","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NIC/nic_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7880,562,"NER","Niger","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NER/ner_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7881,566,"NGA","Nigeria","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NGA/nga_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7882,570,"NIU","Niue","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NIU/niu_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7883,574,"NFK","Norfolk Island","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NFK/nfk_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7884,578,"NOR","Norway","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/NOR/nor_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7885,580,"MNP","Northern Mariana Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MNP/mnp_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7886,581,"UMI","United States Minor Outlying Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/UMI/umi_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7887,583,"FSM","Micronesia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/FSM/fsm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7888,584,"MHL","Marshall Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MHL/mhl_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7889,585,"PLW","Palau","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PLW/plw_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7890,586,"PAK","Pakistan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PAK/pak_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7891,591,"PAN","Panama","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PAN/pan_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7892,598,"PNG","Papua New Guinea","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PNG/png_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7893,600,"PRY","Paraguay","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PRY/pry_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7894,604,"PER","Peru","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PER/per_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7895,608,"PHL","Philippines","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PHL/phl_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7896,612,"PCN","Pitcairn Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PCN/pcn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7897,616,"POL","Poland","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/POL/pol_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7898,620,"PRT","Portugal","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PRT/prt_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7899,624,"GNB","Guinea-Bissau","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GNB/gnb_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7900,626,"TLS","East Timor","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TLS/tls_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7901,630,"PRI","Puerto Rico","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/PRI/pri_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7902,634,"QAT","Qatar","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/QAT/qat_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7903,638,"REU","Reunion","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/REU/reu_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7904,642,"ROU","Romania","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ROU/rou_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7905,646,"RWA","Rwanda","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/RWA/rwa_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7906,652,"BLM","Saint Barthelemy","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BLM/blm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7907,654,"SHN","Saint Helena","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SHN/shn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7908,659,"KNA","Saint Kitts and Nevis","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/KNA/kna_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7909,660,"AIA","Anguilla","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/AIA/aia_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7910,662,"LCA","Saint Lucia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/LCA/lca_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7911,663,"MAF","Saint Martin (French part)","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MAF/maf_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7912,666,"SPM","Saint Pierre and Miquelon","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SPM/spm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7913,670,"VCT","Saint Vincent and the Grenadines","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/VCT/vct_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7914,674,"SMR","San Marino","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SMR/smr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7915,678,"STP","Sao Tome and Principe","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/STP/stp_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7916,682,"SAU","Saudi Arabia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SAU/sau_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7917,686,"SEN","Senegal","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SEN/sen_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7918,688,"SRB","Serbia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SRB/srb_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7919,690,"SYC","Seychelles","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SYC/syc_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7920,694,"SLE","Sierra Leone","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SLE/sle_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7921,702,"SGP","Singapore","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SGP/sgp_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7922,703,"SVK","Slovakia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SVK/svk_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7923,704,"VNM","Vietnam","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/VNM/vnm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7924,705,"SVN","Slovenia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SVN/svn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7925,706,"SOM","Somalia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SOM/som_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7926,710,"ZAF","South Africa","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ZAF/zaf_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7927,716,"ZWE","Zimbabwe","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ZWE/zwe_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7928,724,"ESP","Spain","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ESP/esp_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7929,728,"SSD","South Sudan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SSD/ssd_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7930,729,"SDN","Sudan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SDN/sdn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7931,732,"ESH","Western Sahara","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ESH/esh_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7932,740,"SUR","Suriname","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SUR/sur_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7933,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SJM/sjm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7934,748,"SWZ","Swaziland","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SWZ/swz_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7935,752,"SWE","Sweden","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SWE/swe_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7936,756,"CHE","Switzerland","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/CHE/che_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7937,760,"SYR","Syria","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SYR/syr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7938,762,"TJK","Tajikistan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TJK/tjk_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7939,764,"THA","Thailand","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/THA/tha_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7940,768,"TGO","Togo","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TGO/tgo_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7941,772,"TKL","Tokelau","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TKL/tkl_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7942,776,"TON","Tonga","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TON/ton_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7943,780,"TTO","Trinidad and Tobago","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TTO/tto_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7944,784,"ARE","United Arab Emirates","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ARE/are_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7945,788,"TUN","Tunisia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TUN/tun_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7946,792,"TUR","Turkey","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TUR/tur_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7947,795,"TKM","Turkmenistan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TKM/tkm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7948,796,"TCA","Turks and Caicos Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TCA/tca_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7949,798,"TUV","Tuvalu","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TUV/tuv_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7950,800,"UGA","Uganda","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/UGA/uga_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7951,804,"UKR","Ukraine","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/UKR/ukr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7952,807,"MKD","Macedonia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/MKD/mkd_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7953,818,"EGY","Egypt","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/EGY/egy_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7954,826,"GBR","United Kingdom","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GBR/gbr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7955,831,"GGY","Guernsey","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/GGY/ggy_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7956,832,"JEY","Jersey","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/JEY/jey_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7957,833,"IMN","Isle of Man","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/IMN/imn_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7958,834,"TZA","Tanzania","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/TZA/tza_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7959,854,"BFA","Burkina Faso","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/BFA/bfa_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7960,858,"URY","Uruguay","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/URY/ury_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7961,860,"UZB","Uzbekistan","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/UZB/uzb_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7962,862,"VEN","Venezuela","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/VEN/ven_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7963,876,"WLF","Wallis and Futuna","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/WLF/wlf_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7964,882,"WSM","Samoa","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/WSM/wsm_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7965,887,"YEM","Yemen","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/YEM/yem_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7966,894,"ZMB","Zambia","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/ZMB/zmb_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7967,900,"KOS","Kosovo","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/KOS/kos_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7968,901,"SPR","Spratly Islands","ppp_2010_UNadj","GIS/Population/Global_2000_2020/2010/SPR/spr_ppp_2010_UNadj.tif","Estimated total number of people per grid-cell 2010 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7969,643,"RUS","Russia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/RUS/rus_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7970,360,"IDN","Indonesia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/IDN/idn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7971,840,"USA","United States","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/USA/usa_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7972,850,"VIR","Virgin_Islands_U_S","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/VIR/vir_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7973,304,"GRL","Greenland","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GRL/grl_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7974,156,"CHN","China","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CHN/chn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7975,36,"AUS","Australia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/AUS/aus_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7976,76,"BRA","Brazil","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BRA/bra_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7977,124,"CAN","Canada","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CAN/can_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7978,152,"CHL","Chile","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CHL/chl_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7979,4,"AFG","Afghanistan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/AFG/afg_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7980,8,"ALB","Albania","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ALB/alb_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7981,10,"ATA","Antarctica","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ATA/ata_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7982,12,"DZA","Algeria","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/DZA/dza_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7983,16,"ASM","American Samoa","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ASM/asm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7984,20,"AND","Andorra","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/AND/and_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7985,24,"AGO","Angola","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/AGO/ago_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7986,28,"ATG","Antigua and Barbuda","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ATG/atg_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7987,31,"AZE","Azerbaijan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/AZE/aze_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7988,32,"ARG","Argentina","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ARG/arg_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7989,40,"AUT","Austria","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/AUT/aut_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7990,44,"BHS","Bahamas","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BHS/bhs_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7991,48,"BHR","Bahrain","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BHR/bhr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7992,50,"BGD","Bangladesh","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BGD/bgd_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7993,51,"ARM","Armenia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ARM/arm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7994,52,"BRB","Barbados","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BRB/brb_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7995,56,"BEL","Belgium","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BEL/bel_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7996,60,"BMU","Bermuda","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BMU/bmu_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7997,64,"BTN","Bhutan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BTN/btn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7998,68,"BOL","Bolivia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BOL/bol_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
7999,70,"BIH","Bosnia and Herzegovina","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BIH/bih_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8000,72,"BWA","Botswana","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BWA/bwa_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8001,74,"BVT","Bouvet Island","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BVT/bvt_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8002,84,"BLZ","Belize","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BLZ/blz_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8003,86,"IOT","British Indian Ocean Territory","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/IOT/iot_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8004,90,"SLB","Solomon Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SLB/slb_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8005,92,"VGB","British Virgin Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/VGB/vgb_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8006,96,"BRN","Brunei","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BRN/brn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8007,100,"BGR","Bulgaria","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BGR/bgr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8008,104,"MMR","Myanmar","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MMR/mmr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8009,108,"BDI","Burundi","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BDI/bdi_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8010,112,"BLR","Belarus","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BLR/blr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8011,116,"KHM","Cambodia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/KHM/khm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8012,120,"CMR","Cameroon","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CMR/cmr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8013,132,"CPV","Cape Verde","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CPV/cpv_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8014,136,"CYM","Cayman Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CYM/cym_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8015,140,"CAF","Central African Republic","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CAF/caf_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8016,144,"LKA","Sri Lanka","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LKA/lka_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8017,148,"TCD","Chad","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TCD/tcd_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8018,158,"TWN","Taiwan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TWN/twn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8019,170,"COL","Colombia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/COL/col_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8020,174,"COM","Comoros","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/COM/com_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8021,175,"MYT","Mayotte","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MYT/myt_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8022,178,"COG","Republic of Congo","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/COG/cog_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8023,180,"COD","Democratic Republic of the Congo","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/COD/cod_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8024,184,"COK","Cook Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/COK/cok_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8025,188,"CRI","Costa Rica","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CRI/cri_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8026,191,"HRV","Croatia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/HRV/hrv_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8027,192,"CUB","Cuba","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CUB/cub_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8028,196,"CYP","Cyprus","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CYP/cyp_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8029,203,"CZE","Czech Republic","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CZE/cze_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8030,204,"BEN","Benin","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BEN/ben_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8031,208,"DNK","Denmark","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/DNK/dnk_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8032,212,"DMA","Dominica","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/DMA/dma_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8033,214,"DOM","Dominican Republic","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/DOM/dom_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8034,218,"ECU","Ecuador","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ECU/ecu_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8035,222,"SLV","El Salvador","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SLV/slv_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8036,226,"GNQ","Equatorial Guinea","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GNQ/gnq_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8037,231,"ETH","Ethiopia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ETH/eth_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8038,232,"ERI","Eritrea","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ERI/eri_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8039,233,"EST","Estonia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/EST/est_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8040,234,"FRO","Faroe Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/FRO/fro_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8041,238,"FLK","Falkland Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/FLK/flk_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8042,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SGS/sgs_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8043,242,"FJI","Fiji","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/FJI/fji_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8044,246,"FIN","Finland","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/FIN/fin_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8045,248,"ALA","Aland Islands ","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ALA/ala_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8046,250,"FRA","France","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/FRA/fra_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8047,254,"GUF","French Guiana","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GUF/guf_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8048,258,"PYF","French Polynesia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PYF/pyf_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8049,260,"ATF","French Southern Territories","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ATF/atf_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8050,262,"DJI","Djibouti","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/DJI/dji_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8051,266,"GAB","Gabon","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GAB/gab_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8052,268,"GEO","Georgia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GEO/geo_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8053,270,"GMB","Gambia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GMB/gmb_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8054,275,"PSE","Palestina","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PSE/pse_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8055,276,"DEU","Germany","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/DEU/deu_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8056,288,"GHA","Ghana","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GHA/gha_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8057,292,"GIB","Gibraltar","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GIB/gib_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8058,296,"KIR","Kiribati","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/KIR/kir_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8059,300,"GRC","Greece","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GRC/grc_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8060,308,"GRD","Grenada","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GRD/grd_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8061,312,"GLP","Guadeloupe","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GLP/glp_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8062,316,"GUM","Guam","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GUM/gum_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8063,320,"GTM","Guatemala","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GTM/gtm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8064,324,"GIN","Guinea","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GIN/gin_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8065,328,"GUY","Guyana","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GUY/guy_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8066,332,"HTI","Haiti","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/HTI/hti_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8067,334,"HMD","Heard Island and McDonald Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/HMD/hmd_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8068,336,"VAT","Vatican City","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/VAT/vat_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8069,340,"HND","Honduras","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/HND/hnd_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8070,344,"HKG","Hong Kong","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/HKG/hkg_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8071,348,"HUN","Hungary","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/HUN/hun_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8072,352,"ISL","Iceland","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ISL/isl_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8073,356,"IND","India","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/IND/ind_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8074,364,"IRN","Iran","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/IRN/irn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8075,368,"IRQ","Iraq","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/IRQ/irq_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8076,372,"IRL","Ireland","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/IRL/irl_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8077,376,"ISR","Israel","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ISR/isr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8078,380,"ITA","Italy","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ITA/ita_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8079,384,"CIV","CIte dIvoire","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CIV/civ_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8080,388,"JAM","Jamaica","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/JAM/jam_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8081,392,"JPN","Japan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/JPN/jpn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8082,398,"KAZ","Kazakhstan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/KAZ/kaz_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8083,400,"JOR","Jordan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/JOR/jor_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8084,404,"KEN","Kenya","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/KEN/ken_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8085,408,"PRK","North Korea","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PRK/prk_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8086,410,"KOR","South Korea","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/KOR/kor_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8087,414,"KWT","Kuwait","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/KWT/kwt_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8088,417,"KGZ","Kyrgyzstan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/KGZ/kgz_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8089,418,"LAO","Laos","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LAO/lao_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8090,422,"LBN","Lebanon","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LBN/lbn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8091,426,"LSO","Lesotho","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LSO/lso_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8092,428,"LVA","Latvia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LVA/lva_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8093,430,"LBR","Liberia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LBR/lbr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8094,434,"LBY","Libya","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LBY/lby_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8095,438,"LIE","Liechtenstein","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LIE/lie_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8096,440,"LTU","Lithuania","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LTU/ltu_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8097,442,"LUX","Luxembourg","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LUX/lux_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8098,446,"MAC","Macao","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MAC/mac_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8099,450,"MDG","Madagascar","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MDG/mdg_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8100,454,"MWI","Malawi","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MWI/mwi_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8101,458,"MYS","Malaysia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MYS/mys_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8102,462,"MDV","Maldives","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MDV/mdv_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8103,466,"MLI","Mali","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MLI/mli_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8104,470,"MLT","Malta","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MLT/mlt_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8105,474,"MTQ","Martinique","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MTQ/mtq_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8106,478,"MRT","Mauritania","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MRT/mrt_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8107,480,"MUS","Mauritius","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MUS/mus_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8108,484,"MEX","Mexico","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MEX/mex_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8109,492,"MCO","Monaco","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MCO/mco_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8110,496,"MNG","Mongolia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MNG/mng_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8111,498,"MDA","Moldova","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MDA/mda_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8112,499,"MNE","Montenegro","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MNE/mne_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8113,500,"MSR","Montserrat","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MSR/msr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8114,504,"MAR","Morocco","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MAR/mar_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8115,508,"MOZ","Mozambique","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MOZ/moz_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8116,512,"OMN","Oman","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/OMN/omn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8117,516,"NAM","Namibia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NAM/nam_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8118,520,"NRU","Nauru","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NRU/nru_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8119,524,"NPL","Nepal","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NPL/npl_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8120,528,"NLD","Netherlands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NLD/nld_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8121,531,"CUW","Curacao","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CUW/cuw_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8122,533,"ABW","Aruba","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ABW/abw_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8123,534,"SXM","Sint Maarten (Dutch part)","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SXM/sxm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8124,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BES/bes_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8125,540,"NCL","New Caledonia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NCL/ncl_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8126,548,"VUT","Vanuatu","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/VUT/vut_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8127,554,"NZL","New Zealand","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NZL/nzl_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8128,558,"NIC","Nicaragua","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NIC/nic_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8129,562,"NER","Niger","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NER/ner_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8130,566,"NGA","Nigeria","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NGA/nga_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8131,570,"NIU","Niue","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NIU/niu_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8132,574,"NFK","Norfolk Island","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NFK/nfk_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8133,578,"NOR","Norway","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/NOR/nor_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8134,580,"MNP","Northern Mariana Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MNP/mnp_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8135,581,"UMI","United States Minor Outlying Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/UMI/umi_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8136,583,"FSM","Micronesia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/FSM/fsm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8137,584,"MHL","Marshall Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MHL/mhl_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8138,585,"PLW","Palau","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PLW/plw_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8139,586,"PAK","Pakistan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PAK/pak_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8140,591,"PAN","Panama","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PAN/pan_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8141,598,"PNG","Papua New Guinea","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PNG/png_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8142,600,"PRY","Paraguay","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PRY/pry_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8143,604,"PER","Peru","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PER/per_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8144,608,"PHL","Philippines","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PHL/phl_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8145,612,"PCN","Pitcairn Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PCN/pcn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8146,616,"POL","Poland","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/POL/pol_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8147,620,"PRT","Portugal","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PRT/prt_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8148,624,"GNB","Guinea-Bissau","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GNB/gnb_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8149,626,"TLS","East Timor","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TLS/tls_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8150,630,"PRI","Puerto Rico","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/PRI/pri_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8151,634,"QAT","Qatar","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/QAT/qat_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8152,638,"REU","Reunion","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/REU/reu_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8153,642,"ROU","Romania","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ROU/rou_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8154,646,"RWA","Rwanda","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/RWA/rwa_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8155,652,"BLM","Saint Barthelemy","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BLM/blm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8156,654,"SHN","Saint Helena","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SHN/shn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8157,659,"KNA","Saint Kitts and Nevis","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/KNA/kna_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8158,660,"AIA","Anguilla","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/AIA/aia_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8159,662,"LCA","Saint Lucia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/LCA/lca_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8160,663,"MAF","Saint Martin (French part)","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MAF/maf_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8161,666,"SPM","Saint Pierre and Miquelon","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SPM/spm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8162,670,"VCT","Saint Vincent and the Grenadines","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/VCT/vct_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8163,674,"SMR","San Marino","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SMR/smr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8164,678,"STP","Sao Tome and Principe","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/STP/stp_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8165,682,"SAU","Saudi Arabia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SAU/sau_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8166,686,"SEN","Senegal","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SEN/sen_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8167,688,"SRB","Serbia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SRB/srb_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8168,690,"SYC","Seychelles","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SYC/syc_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8169,694,"SLE","Sierra Leone","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SLE/sle_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8170,702,"SGP","Singapore","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SGP/sgp_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8171,703,"SVK","Slovakia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SVK/svk_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8172,704,"VNM","Vietnam","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/VNM/vnm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8173,705,"SVN","Slovenia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SVN/svn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8174,706,"SOM","Somalia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SOM/som_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8175,710,"ZAF","South Africa","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ZAF/zaf_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8176,716,"ZWE","Zimbabwe","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ZWE/zwe_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8177,724,"ESP","Spain","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ESP/esp_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8178,728,"SSD","South Sudan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SSD/ssd_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8179,729,"SDN","Sudan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SDN/sdn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8180,732,"ESH","Western Sahara","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ESH/esh_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8181,740,"SUR","Suriname","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SUR/sur_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8182,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SJM/sjm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8183,748,"SWZ","Swaziland","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SWZ/swz_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8184,752,"SWE","Sweden","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SWE/swe_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8185,756,"CHE","Switzerland","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/CHE/che_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8186,760,"SYR","Syria","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SYR/syr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8187,762,"TJK","Tajikistan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TJK/tjk_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8188,764,"THA","Thailand","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/THA/tha_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8189,768,"TGO","Togo","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TGO/tgo_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8190,772,"TKL","Tokelau","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TKL/tkl_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8191,776,"TON","Tonga","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TON/ton_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8192,780,"TTO","Trinidad and Tobago","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TTO/tto_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8193,784,"ARE","United Arab Emirates","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ARE/are_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8194,788,"TUN","Tunisia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TUN/tun_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8195,792,"TUR","Turkey","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TUR/tur_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8196,795,"TKM","Turkmenistan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TKM/tkm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8197,796,"TCA","Turks and Caicos Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TCA/tca_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8198,798,"TUV","Tuvalu","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TUV/tuv_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8199,800,"UGA","Uganda","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/UGA/uga_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8200,804,"UKR","Ukraine","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/UKR/ukr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8201,807,"MKD","Macedonia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/MKD/mkd_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8202,818,"EGY","Egypt","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/EGY/egy_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8203,826,"GBR","United Kingdom","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GBR/gbr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8204,831,"GGY","Guernsey","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/GGY/ggy_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8205,832,"JEY","Jersey","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/JEY/jey_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8206,833,"IMN","Isle of Man","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/IMN/imn_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8207,834,"TZA","Tanzania","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/TZA/tza_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8208,854,"BFA","Burkina Faso","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/BFA/bfa_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8209,858,"URY","Uruguay","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/URY/ury_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8210,860,"UZB","Uzbekistan","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/UZB/uzb_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8211,862,"VEN","Venezuela","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/VEN/ven_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8212,876,"WLF","Wallis and Futuna","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/WLF/wlf_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8213,882,"WSM","Samoa","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/WSM/wsm_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8214,887,"YEM","Yemen","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/YEM/yem_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8215,894,"ZMB","Zambia","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/ZMB/zmb_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8216,900,"KOS","Kosovo","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/KOS/kos_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8217,901,"SPR","Spratly Islands","ppp_2011_UNadj","GIS/Population/Global_2000_2020/2011/SPR/spr_ppp_2011_UNadj.tif","Estimated total number of people per grid-cell 2011 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8218,643,"RUS","Russia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/RUS/rus_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8219,360,"IDN","Indonesia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/IDN/idn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8220,840,"USA","United States","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/USA/usa_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8221,850,"VIR","Virgin_Islands_U_S","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/VIR/vir_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8222,304,"GRL","Greenland","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GRL/grl_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8223,156,"CHN","China","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CHN/chn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8224,36,"AUS","Australia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/AUS/aus_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8225,76,"BRA","Brazil","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BRA/bra_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8226,124,"CAN","Canada","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CAN/can_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8227,152,"CHL","Chile","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CHL/chl_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8228,4,"AFG","Afghanistan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/AFG/afg_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8229,8,"ALB","Albania","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ALB/alb_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8230,10,"ATA","Antarctica","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ATA/ata_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8231,12,"DZA","Algeria","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/DZA/dza_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8232,16,"ASM","American Samoa","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ASM/asm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8233,20,"AND","Andorra","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/AND/and_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8234,24,"AGO","Angola","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/AGO/ago_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8235,28,"ATG","Antigua and Barbuda","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ATG/atg_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8236,31,"AZE","Azerbaijan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/AZE/aze_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8237,32,"ARG","Argentina","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ARG/arg_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8238,40,"AUT","Austria","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/AUT/aut_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8239,44,"BHS","Bahamas","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BHS/bhs_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8240,48,"BHR","Bahrain","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BHR/bhr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8241,50,"BGD","Bangladesh","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BGD/bgd_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8242,51,"ARM","Armenia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ARM/arm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8243,52,"BRB","Barbados","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BRB/brb_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8244,56,"BEL","Belgium","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BEL/bel_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8245,60,"BMU","Bermuda","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BMU/bmu_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8246,64,"BTN","Bhutan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BTN/btn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8247,68,"BOL","Bolivia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BOL/bol_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8248,70,"BIH","Bosnia and Herzegovina","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BIH/bih_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8249,72,"BWA","Botswana","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BWA/bwa_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8250,74,"BVT","Bouvet Island","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BVT/bvt_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8251,84,"BLZ","Belize","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BLZ/blz_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8252,86,"IOT","British Indian Ocean Territory","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/IOT/iot_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8253,90,"SLB","Solomon Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SLB/slb_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8254,92,"VGB","British Virgin Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/VGB/vgb_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8255,96,"BRN","Brunei","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BRN/brn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8256,100,"BGR","Bulgaria","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BGR/bgr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8257,104,"MMR","Myanmar","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MMR/mmr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8258,108,"BDI","Burundi","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BDI/bdi_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8259,112,"BLR","Belarus","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BLR/blr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8260,116,"KHM","Cambodia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/KHM/khm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8261,120,"CMR","Cameroon","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CMR/cmr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8262,132,"CPV","Cape Verde","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CPV/cpv_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8263,136,"CYM","Cayman Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CYM/cym_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8264,140,"CAF","Central African Republic","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CAF/caf_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8265,144,"LKA","Sri Lanka","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LKA/lka_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8266,148,"TCD","Chad","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TCD/tcd_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8267,158,"TWN","Taiwan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TWN/twn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8268,170,"COL","Colombia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/COL/col_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8269,174,"COM","Comoros","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/COM/com_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8270,175,"MYT","Mayotte","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MYT/myt_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8271,178,"COG","Republic of Congo","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/COG/cog_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8272,180,"COD","Democratic Republic of the Congo","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/COD/cod_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8273,184,"COK","Cook Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/COK/cok_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8274,188,"CRI","Costa Rica","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CRI/cri_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8275,191,"HRV","Croatia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/HRV/hrv_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8276,192,"CUB","Cuba","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CUB/cub_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8277,196,"CYP","Cyprus","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CYP/cyp_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8278,203,"CZE","Czech Republic","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CZE/cze_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8279,204,"BEN","Benin","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BEN/ben_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8280,208,"DNK","Denmark","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/DNK/dnk_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8281,212,"DMA","Dominica","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/DMA/dma_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8282,214,"DOM","Dominican Republic","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/DOM/dom_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8283,218,"ECU","Ecuador","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ECU/ecu_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8284,222,"SLV","El Salvador","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SLV/slv_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8285,226,"GNQ","Equatorial Guinea","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GNQ/gnq_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8286,231,"ETH","Ethiopia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ETH/eth_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8287,232,"ERI","Eritrea","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ERI/eri_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8288,233,"EST","Estonia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/EST/est_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8289,234,"FRO","Faroe Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/FRO/fro_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8290,238,"FLK","Falkland Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/FLK/flk_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8291,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SGS/sgs_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8292,242,"FJI","Fiji","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/FJI/fji_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8293,246,"FIN","Finland","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/FIN/fin_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8294,248,"ALA","Aland Islands ","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ALA/ala_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8295,250,"FRA","France","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/FRA/fra_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8296,254,"GUF","French Guiana","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GUF/guf_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8297,258,"PYF","French Polynesia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PYF/pyf_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8298,260,"ATF","French Southern Territories","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ATF/atf_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8299,262,"DJI","Djibouti","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/DJI/dji_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8300,266,"GAB","Gabon","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GAB/gab_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8301,268,"GEO","Georgia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GEO/geo_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8302,270,"GMB","Gambia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GMB/gmb_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8303,275,"PSE","Palestina","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PSE/pse_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8304,276,"DEU","Germany","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/DEU/deu_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8305,288,"GHA","Ghana","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GHA/gha_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8306,292,"GIB","Gibraltar","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GIB/gib_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8307,296,"KIR","Kiribati","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/KIR/kir_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8308,300,"GRC","Greece","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GRC/grc_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8309,308,"GRD","Grenada","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GRD/grd_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8310,312,"GLP","Guadeloupe","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GLP/glp_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8311,316,"GUM","Guam","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GUM/gum_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8312,320,"GTM","Guatemala","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GTM/gtm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8313,324,"GIN","Guinea","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GIN/gin_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8314,328,"GUY","Guyana","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GUY/guy_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8315,332,"HTI","Haiti","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/HTI/hti_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8316,334,"HMD","Heard Island and McDonald Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/HMD/hmd_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8317,336,"VAT","Vatican City","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/VAT/vat_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8318,340,"HND","Honduras","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/HND/hnd_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8319,344,"HKG","Hong Kong","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/HKG/hkg_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8320,348,"HUN","Hungary","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/HUN/hun_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8321,352,"ISL","Iceland","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ISL/isl_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8322,356,"IND","India","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/IND/ind_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8323,364,"IRN","Iran","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/IRN/irn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8324,368,"IRQ","Iraq","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/IRQ/irq_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8325,372,"IRL","Ireland","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/IRL/irl_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8326,376,"ISR","Israel","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ISR/isr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8327,380,"ITA","Italy","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ITA/ita_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8328,384,"CIV","CIte dIvoire","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CIV/civ_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8329,388,"JAM","Jamaica","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/JAM/jam_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8330,392,"JPN","Japan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/JPN/jpn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8331,398,"KAZ","Kazakhstan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/KAZ/kaz_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8332,400,"JOR","Jordan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/JOR/jor_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8333,404,"KEN","Kenya","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/KEN/ken_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8334,408,"PRK","North Korea","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PRK/prk_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8335,410,"KOR","South Korea","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/KOR/kor_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8336,414,"KWT","Kuwait","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/KWT/kwt_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8337,417,"KGZ","Kyrgyzstan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/KGZ/kgz_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8338,418,"LAO","Laos","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LAO/lao_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8339,422,"LBN","Lebanon","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LBN/lbn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8340,426,"LSO","Lesotho","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LSO/lso_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8341,428,"LVA","Latvia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LVA/lva_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8342,430,"LBR","Liberia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LBR/lbr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8343,434,"LBY","Libya","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LBY/lby_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8344,438,"LIE","Liechtenstein","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LIE/lie_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8345,440,"LTU","Lithuania","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LTU/ltu_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8346,442,"LUX","Luxembourg","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LUX/lux_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8347,446,"MAC","Macao","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MAC/mac_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8348,450,"MDG","Madagascar","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MDG/mdg_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8349,454,"MWI","Malawi","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MWI/mwi_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8350,458,"MYS","Malaysia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MYS/mys_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8351,462,"MDV","Maldives","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MDV/mdv_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8352,466,"MLI","Mali","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MLI/mli_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8353,470,"MLT","Malta","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MLT/mlt_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8354,474,"MTQ","Martinique","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MTQ/mtq_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8355,478,"MRT","Mauritania","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MRT/mrt_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8356,480,"MUS","Mauritius","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MUS/mus_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8357,484,"MEX","Mexico","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MEX/mex_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8358,492,"MCO","Monaco","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MCO/mco_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8359,496,"MNG","Mongolia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MNG/mng_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8360,498,"MDA","Moldova","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MDA/mda_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8361,499,"MNE","Montenegro","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MNE/mne_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8362,500,"MSR","Montserrat","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MSR/msr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8363,504,"MAR","Morocco","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MAR/mar_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8364,508,"MOZ","Mozambique","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MOZ/moz_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8365,512,"OMN","Oman","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/OMN/omn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8366,516,"NAM","Namibia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NAM/nam_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8367,520,"NRU","Nauru","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NRU/nru_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8368,524,"NPL","Nepal","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NPL/npl_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8369,528,"NLD","Netherlands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NLD/nld_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8370,531,"CUW","Curacao","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CUW/cuw_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8371,533,"ABW","Aruba","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ABW/abw_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8372,534,"SXM","Sint Maarten (Dutch part)","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SXM/sxm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8373,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BES/bes_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8374,540,"NCL","New Caledonia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NCL/ncl_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8375,548,"VUT","Vanuatu","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/VUT/vut_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8376,554,"NZL","New Zealand","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NZL/nzl_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8377,558,"NIC","Nicaragua","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NIC/nic_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8378,562,"NER","Niger","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NER/ner_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8379,566,"NGA","Nigeria","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NGA/nga_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8380,570,"NIU","Niue","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NIU/niu_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8381,574,"NFK","Norfolk Island","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NFK/nfk_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8382,578,"NOR","Norway","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/NOR/nor_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8383,580,"MNP","Northern Mariana Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MNP/mnp_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8384,581,"UMI","United States Minor Outlying Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/UMI/umi_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8385,583,"FSM","Micronesia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/FSM/fsm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8386,584,"MHL","Marshall Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MHL/mhl_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8387,585,"PLW","Palau","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PLW/plw_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8388,586,"PAK","Pakistan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PAK/pak_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8389,591,"PAN","Panama","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PAN/pan_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8390,598,"PNG","Papua New Guinea","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PNG/png_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8391,600,"PRY","Paraguay","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PRY/pry_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8392,604,"PER","Peru","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PER/per_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8393,608,"PHL","Philippines","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PHL/phl_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8394,612,"PCN","Pitcairn Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PCN/pcn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8395,616,"POL","Poland","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/POL/pol_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8396,620,"PRT","Portugal","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PRT/prt_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8397,624,"GNB","Guinea-Bissau","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GNB/gnb_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8398,626,"TLS","East Timor","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TLS/tls_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8399,630,"PRI","Puerto Rico","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/PRI/pri_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8400,634,"QAT","Qatar","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/QAT/qat_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8401,638,"REU","Reunion","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/REU/reu_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8402,642,"ROU","Romania","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ROU/rou_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8403,646,"RWA","Rwanda","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/RWA/rwa_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8404,652,"BLM","Saint Barthelemy","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BLM/blm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8405,654,"SHN","Saint Helena","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SHN/shn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8406,659,"KNA","Saint Kitts and Nevis","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/KNA/kna_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8407,660,"AIA","Anguilla","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/AIA/aia_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8408,662,"LCA","Saint Lucia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/LCA/lca_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8409,663,"MAF","Saint Martin (French part)","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MAF/maf_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8410,666,"SPM","Saint Pierre and Miquelon","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SPM/spm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8411,670,"VCT","Saint Vincent and the Grenadines","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/VCT/vct_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8412,674,"SMR","San Marino","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SMR/smr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8413,678,"STP","Sao Tome and Principe","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/STP/stp_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8414,682,"SAU","Saudi Arabia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SAU/sau_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8415,686,"SEN","Senegal","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SEN/sen_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8416,688,"SRB","Serbia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SRB/srb_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8417,690,"SYC","Seychelles","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SYC/syc_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8418,694,"SLE","Sierra Leone","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SLE/sle_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8419,702,"SGP","Singapore","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SGP/sgp_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8420,703,"SVK","Slovakia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SVK/svk_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8421,704,"VNM","Vietnam","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/VNM/vnm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8422,705,"SVN","Slovenia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SVN/svn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8423,706,"SOM","Somalia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SOM/som_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8424,710,"ZAF","South Africa","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ZAF/zaf_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8425,716,"ZWE","Zimbabwe","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ZWE/zwe_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8426,724,"ESP","Spain","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ESP/esp_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8427,728,"SSD","South Sudan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SSD/ssd_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8428,729,"SDN","Sudan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SDN/sdn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8429,732,"ESH","Western Sahara","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ESH/esh_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8430,740,"SUR","Suriname","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SUR/sur_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8431,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SJM/sjm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8432,748,"SWZ","Swaziland","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SWZ/swz_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8433,752,"SWE","Sweden","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SWE/swe_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8434,756,"CHE","Switzerland","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/CHE/che_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8435,760,"SYR","Syria","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SYR/syr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8436,762,"TJK","Tajikistan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TJK/tjk_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8437,764,"THA","Thailand","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/THA/tha_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8438,768,"TGO","Togo","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TGO/tgo_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8439,772,"TKL","Tokelau","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TKL/tkl_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8440,776,"TON","Tonga","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TON/ton_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8441,780,"TTO","Trinidad and Tobago","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TTO/tto_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8442,784,"ARE","United Arab Emirates","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ARE/are_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8443,788,"TUN","Tunisia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TUN/tun_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8444,792,"TUR","Turkey","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TUR/tur_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8445,795,"TKM","Turkmenistan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TKM/tkm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8446,796,"TCA","Turks and Caicos Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TCA/tca_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8447,798,"TUV","Tuvalu","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TUV/tuv_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8448,800,"UGA","Uganda","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/UGA/uga_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8449,804,"UKR","Ukraine","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/UKR/ukr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8450,807,"MKD","Macedonia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/MKD/mkd_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8451,818,"EGY","Egypt","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/EGY/egy_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8452,826,"GBR","United Kingdom","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GBR/gbr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8453,831,"GGY","Guernsey","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/GGY/ggy_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8454,832,"JEY","Jersey","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/JEY/jey_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8455,833,"IMN","Isle of Man","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/IMN/imn_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8456,834,"TZA","Tanzania","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/TZA/tza_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8457,854,"BFA","Burkina Faso","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/BFA/bfa_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8458,858,"URY","Uruguay","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/URY/ury_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8459,860,"UZB","Uzbekistan","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/UZB/uzb_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8460,862,"VEN","Venezuela","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/VEN/ven_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8461,876,"WLF","Wallis and Futuna","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/WLF/wlf_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8462,882,"WSM","Samoa","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/WSM/wsm_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8463,887,"YEM","Yemen","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/YEM/yem_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8464,894,"ZMB","Zambia","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/ZMB/zmb_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8465,900,"KOS","Kosovo","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/KOS/kos_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8466,901,"SPR","Spratly Islands","ppp_2012_UNadj","GIS/Population/Global_2000_2020/2012/SPR/spr_ppp_2012_UNadj.tif","Estimated total number of people per grid-cell 2012 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8467,643,"RUS","Russia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/RUS/rus_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8468,360,"IDN","Indonesia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/IDN/idn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8469,840,"USA","United States","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/USA/usa_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8470,850,"VIR","Virgin_Islands_U_S","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/VIR/vir_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8471,304,"GRL","Greenland","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GRL/grl_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8472,156,"CHN","China","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CHN/chn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8473,36,"AUS","Australia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/AUS/aus_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8474,76,"BRA","Brazil","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BRA/bra_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8475,124,"CAN","Canada","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CAN/can_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8476,152,"CHL","Chile","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CHL/chl_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8477,4,"AFG","Afghanistan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/AFG/afg_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8478,8,"ALB","Albania","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ALB/alb_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8479,10,"ATA","Antarctica","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ATA/ata_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8480,12,"DZA","Algeria","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/DZA/dza_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8481,16,"ASM","American Samoa","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ASM/asm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8482,20,"AND","Andorra","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/AND/and_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8483,24,"AGO","Angola","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/AGO/ago_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8484,28,"ATG","Antigua and Barbuda","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ATG/atg_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8485,31,"AZE","Azerbaijan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/AZE/aze_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8486,32,"ARG","Argentina","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ARG/arg_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8487,40,"AUT","Austria","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/AUT/aut_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8488,44,"BHS","Bahamas","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BHS/bhs_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8489,48,"BHR","Bahrain","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BHR/bhr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8490,50,"BGD","Bangladesh","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BGD/bgd_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8491,51,"ARM","Armenia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ARM/arm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8492,52,"BRB","Barbados","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BRB/brb_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8493,56,"BEL","Belgium","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BEL/bel_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8494,60,"BMU","Bermuda","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BMU/bmu_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8495,64,"BTN","Bhutan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BTN/btn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8496,68,"BOL","Bolivia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BOL/bol_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8497,70,"BIH","Bosnia and Herzegovina","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BIH/bih_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8498,72,"BWA","Botswana","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BWA/bwa_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8499,74,"BVT","Bouvet Island","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BVT/bvt_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8500,84,"BLZ","Belize","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BLZ/blz_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8501,86,"IOT","British Indian Ocean Territory","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/IOT/iot_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8502,90,"SLB","Solomon Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SLB/slb_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8503,92,"VGB","British Virgin Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/VGB/vgb_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8504,96,"BRN","Brunei","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BRN/brn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8505,100,"BGR","Bulgaria","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BGR/bgr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8506,104,"MMR","Myanmar","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MMR/mmr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8507,108,"BDI","Burundi","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BDI/bdi_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8508,112,"BLR","Belarus","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BLR/blr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8509,116,"KHM","Cambodia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/KHM/khm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8510,120,"CMR","Cameroon","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CMR/cmr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8511,132,"CPV","Cape Verde","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CPV/cpv_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8512,136,"CYM","Cayman Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CYM/cym_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8513,140,"CAF","Central African Republic","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CAF/caf_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8514,144,"LKA","Sri Lanka","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LKA/lka_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8515,148,"TCD","Chad","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TCD/tcd_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8516,158,"TWN","Taiwan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TWN/twn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8517,170,"COL","Colombia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/COL/col_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8518,174,"COM","Comoros","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/COM/com_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8519,175,"MYT","Mayotte","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MYT/myt_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8520,178,"COG","Republic of Congo","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/COG/cog_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8521,180,"COD","Democratic Republic of the Congo","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/COD/cod_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8522,184,"COK","Cook Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/COK/cok_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8523,188,"CRI","Costa Rica","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CRI/cri_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8524,191,"HRV","Croatia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/HRV/hrv_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8525,192,"CUB","Cuba","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CUB/cub_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8526,196,"CYP","Cyprus","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CYP/cyp_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8527,203,"CZE","Czech Republic","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CZE/cze_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8528,204,"BEN","Benin","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BEN/ben_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8529,208,"DNK","Denmark","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/DNK/dnk_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8530,212,"DMA","Dominica","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/DMA/dma_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8531,214,"DOM","Dominican Republic","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/DOM/dom_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8532,218,"ECU","Ecuador","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ECU/ecu_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8533,222,"SLV","El Salvador","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SLV/slv_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8534,226,"GNQ","Equatorial Guinea","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GNQ/gnq_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8535,231,"ETH","Ethiopia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ETH/eth_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8536,232,"ERI","Eritrea","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ERI/eri_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8537,233,"EST","Estonia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/EST/est_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8538,234,"FRO","Faroe Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/FRO/fro_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8539,238,"FLK","Falkland Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/FLK/flk_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8540,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SGS/sgs_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8541,242,"FJI","Fiji","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/FJI/fji_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8542,246,"FIN","Finland","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/FIN/fin_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8543,248,"ALA","Aland Islands ","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ALA/ala_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8544,250,"FRA","France","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/FRA/fra_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8545,254,"GUF","French Guiana","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GUF/guf_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8546,258,"PYF","French Polynesia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PYF/pyf_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8547,260,"ATF","French Southern Territories","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ATF/atf_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8548,262,"DJI","Djibouti","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/DJI/dji_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8549,266,"GAB","Gabon","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GAB/gab_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8550,268,"GEO","Georgia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GEO/geo_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8551,270,"GMB","Gambia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GMB/gmb_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8552,275,"PSE","Palestina","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PSE/pse_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8553,276,"DEU","Germany","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/DEU/deu_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8554,288,"GHA","Ghana","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GHA/gha_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8555,292,"GIB","Gibraltar","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GIB/gib_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8556,296,"KIR","Kiribati","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/KIR/kir_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8557,300,"GRC","Greece","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GRC/grc_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8558,308,"GRD","Grenada","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GRD/grd_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8559,312,"GLP","Guadeloupe","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GLP/glp_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8560,316,"GUM","Guam","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GUM/gum_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8561,320,"GTM","Guatemala","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GTM/gtm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8562,324,"GIN","Guinea","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GIN/gin_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8563,328,"GUY","Guyana","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GUY/guy_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8564,332,"HTI","Haiti","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/HTI/hti_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8565,334,"HMD","Heard Island and McDonald Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/HMD/hmd_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8566,336,"VAT","Vatican City","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/VAT/vat_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8567,340,"HND","Honduras","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/HND/hnd_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8568,344,"HKG","Hong Kong","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/HKG/hkg_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8569,348,"HUN","Hungary","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/HUN/hun_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8570,352,"ISL","Iceland","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ISL/isl_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8571,356,"IND","India","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/IND/ind_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8572,364,"IRN","Iran","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/IRN/irn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8573,368,"IRQ","Iraq","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/IRQ/irq_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8574,372,"IRL","Ireland","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/IRL/irl_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8575,376,"ISR","Israel","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ISR/isr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8576,380,"ITA","Italy","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ITA/ita_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8577,384,"CIV","CIte dIvoire","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CIV/civ_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8578,388,"JAM","Jamaica","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/JAM/jam_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8579,392,"JPN","Japan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/JPN/jpn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8580,398,"KAZ","Kazakhstan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/KAZ/kaz_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8581,400,"JOR","Jordan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/JOR/jor_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8582,404,"KEN","Kenya","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/KEN/ken_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8583,408,"PRK","North Korea","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PRK/prk_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8584,410,"KOR","South Korea","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/KOR/kor_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8585,414,"KWT","Kuwait","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/KWT/kwt_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8586,417,"KGZ","Kyrgyzstan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/KGZ/kgz_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8587,418,"LAO","Laos","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LAO/lao_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8588,422,"LBN","Lebanon","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LBN/lbn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8589,426,"LSO","Lesotho","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LSO/lso_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8590,428,"LVA","Latvia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LVA/lva_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8591,430,"LBR","Liberia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LBR/lbr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8592,434,"LBY","Libya","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LBY/lby_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8593,438,"LIE","Liechtenstein","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LIE/lie_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8594,440,"LTU","Lithuania","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LTU/ltu_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8595,442,"LUX","Luxembourg","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LUX/lux_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8596,446,"MAC","Macao","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MAC/mac_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8597,450,"MDG","Madagascar","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MDG/mdg_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8598,454,"MWI","Malawi","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MWI/mwi_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8599,458,"MYS","Malaysia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MYS/mys_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8600,462,"MDV","Maldives","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MDV/mdv_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8601,466,"MLI","Mali","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MLI/mli_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8602,470,"MLT","Malta","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MLT/mlt_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8603,474,"MTQ","Martinique","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MTQ/mtq_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8604,478,"MRT","Mauritania","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MRT/mrt_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8605,480,"MUS","Mauritius","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MUS/mus_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8606,484,"MEX","Mexico","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MEX/mex_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8607,492,"MCO","Monaco","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MCO/mco_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8608,496,"MNG","Mongolia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MNG/mng_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8609,498,"MDA","Moldova","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MDA/mda_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8610,499,"MNE","Montenegro","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MNE/mne_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8611,500,"MSR","Montserrat","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MSR/msr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8612,504,"MAR","Morocco","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MAR/mar_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8613,508,"MOZ","Mozambique","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MOZ/moz_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8614,512,"OMN","Oman","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/OMN/omn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8615,516,"NAM","Namibia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NAM/nam_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8616,520,"NRU","Nauru","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NRU/nru_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8617,524,"NPL","Nepal","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NPL/npl_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8618,528,"NLD","Netherlands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NLD/nld_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8619,531,"CUW","Curacao","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CUW/cuw_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8620,533,"ABW","Aruba","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ABW/abw_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8621,534,"SXM","Sint Maarten (Dutch part)","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SXM/sxm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8622,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BES/bes_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8623,540,"NCL","New Caledonia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NCL/ncl_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8624,548,"VUT","Vanuatu","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/VUT/vut_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8625,554,"NZL","New Zealand","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NZL/nzl_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8626,558,"NIC","Nicaragua","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NIC/nic_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8627,562,"NER","Niger","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NER/ner_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8628,566,"NGA","Nigeria","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NGA/nga_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8629,570,"NIU","Niue","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NIU/niu_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8630,574,"NFK","Norfolk Island","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NFK/nfk_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8631,578,"NOR","Norway","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/NOR/nor_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8632,580,"MNP","Northern Mariana Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MNP/mnp_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8633,581,"UMI","United States Minor Outlying Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/UMI/umi_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8634,583,"FSM","Micronesia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/FSM/fsm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8635,584,"MHL","Marshall Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MHL/mhl_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8636,585,"PLW","Palau","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PLW/plw_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8637,586,"PAK","Pakistan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PAK/pak_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8638,591,"PAN","Panama","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PAN/pan_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8639,598,"PNG","Papua New Guinea","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PNG/png_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8640,600,"PRY","Paraguay","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PRY/pry_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8641,604,"PER","Peru","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PER/per_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8642,608,"PHL","Philippines","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PHL/phl_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8643,612,"PCN","Pitcairn Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PCN/pcn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8644,616,"POL","Poland","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/POL/pol_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8645,620,"PRT","Portugal","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PRT/prt_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8646,624,"GNB","Guinea-Bissau","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GNB/gnb_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8647,626,"TLS","East Timor","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TLS/tls_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8648,630,"PRI","Puerto Rico","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/PRI/pri_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8649,634,"QAT","Qatar","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/QAT/qat_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8650,638,"REU","Reunion","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/REU/reu_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8651,642,"ROU","Romania","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ROU/rou_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8652,646,"RWA","Rwanda","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/RWA/rwa_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8653,652,"BLM","Saint Barthelemy","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BLM/blm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8654,654,"SHN","Saint Helena","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SHN/shn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8655,659,"KNA","Saint Kitts and Nevis","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/KNA/kna_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8656,660,"AIA","Anguilla","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/AIA/aia_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8657,662,"LCA","Saint Lucia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/LCA/lca_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8658,663,"MAF","Saint Martin (French part)","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MAF/maf_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8659,666,"SPM","Saint Pierre and Miquelon","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SPM/spm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8660,670,"VCT","Saint Vincent and the Grenadines","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/VCT/vct_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8661,674,"SMR","San Marino","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SMR/smr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8662,678,"STP","Sao Tome and Principe","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/STP/stp_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8663,682,"SAU","Saudi Arabia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SAU/sau_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8664,686,"SEN","Senegal","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SEN/sen_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8665,688,"SRB","Serbia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SRB/srb_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8666,690,"SYC","Seychelles","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SYC/syc_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8667,694,"SLE","Sierra Leone","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SLE/sle_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8668,702,"SGP","Singapore","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SGP/sgp_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8669,703,"SVK","Slovakia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SVK/svk_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8670,704,"VNM","Vietnam","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/VNM/vnm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8671,705,"SVN","Slovenia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SVN/svn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8672,706,"SOM","Somalia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SOM/som_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8673,710,"ZAF","South Africa","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ZAF/zaf_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8674,716,"ZWE","Zimbabwe","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ZWE/zwe_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8675,724,"ESP","Spain","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ESP/esp_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8676,728,"SSD","South Sudan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SSD/ssd_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8677,729,"SDN","Sudan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SDN/sdn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8678,732,"ESH","Western Sahara","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ESH/esh_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8679,740,"SUR","Suriname","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SUR/sur_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8680,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SJM/sjm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8681,748,"SWZ","Swaziland","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SWZ/swz_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8682,752,"SWE","Sweden","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SWE/swe_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8683,756,"CHE","Switzerland","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/CHE/che_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8684,760,"SYR","Syria","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SYR/syr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8685,762,"TJK","Tajikistan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TJK/tjk_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8686,764,"THA","Thailand","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/THA/tha_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8687,768,"TGO","Togo","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TGO/tgo_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8688,772,"TKL","Tokelau","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TKL/tkl_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8689,776,"TON","Tonga","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TON/ton_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8690,780,"TTO","Trinidad and Tobago","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TTO/tto_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8691,784,"ARE","United Arab Emirates","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ARE/are_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8692,788,"TUN","Tunisia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TUN/tun_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8693,792,"TUR","Turkey","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TUR/tur_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8694,795,"TKM","Turkmenistan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TKM/tkm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8695,796,"TCA","Turks and Caicos Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TCA/tca_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8696,798,"TUV","Tuvalu","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TUV/tuv_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8697,800,"UGA","Uganda","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/UGA/uga_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8698,804,"UKR","Ukraine","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/UKR/ukr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8699,807,"MKD","Macedonia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/MKD/mkd_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8700,818,"EGY","Egypt","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/EGY/egy_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8701,826,"GBR","United Kingdom","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GBR/gbr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8702,831,"GGY","Guernsey","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/GGY/ggy_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8703,832,"JEY","Jersey","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/JEY/jey_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8704,833,"IMN","Isle of Man","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/IMN/imn_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8705,834,"TZA","Tanzania","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/TZA/tza_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8706,854,"BFA","Burkina Faso","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/BFA/bfa_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8707,858,"URY","Uruguay","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/URY/ury_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8708,860,"UZB","Uzbekistan","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/UZB/uzb_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8709,862,"VEN","Venezuela","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/VEN/ven_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8710,876,"WLF","Wallis and Futuna","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/WLF/wlf_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8711,882,"WSM","Samoa","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/WSM/wsm_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8712,887,"YEM","Yemen","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/YEM/yem_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8713,894,"ZMB","Zambia","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/ZMB/zmb_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8714,900,"KOS","Kosovo","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/KOS/kos_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8715,901,"SPR","Spratly Islands","ppp_2013_UNadj","GIS/Population/Global_2000_2020/2013/SPR/spr_ppp_2013_UNadj.tif","Estimated total number of people per grid-cell 2013 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8716,643,"RUS","Russia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/RUS/rus_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8717,360,"IDN","Indonesia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/IDN/idn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8718,840,"USA","United States","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/USA/usa_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8719,850,"VIR","Virgin_Islands_U_S","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/VIR/vir_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8720,304,"GRL","Greenland","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GRL/grl_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8721,156,"CHN","China","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CHN/chn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8722,36,"AUS","Australia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/AUS/aus_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8723,76,"BRA","Brazil","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BRA/bra_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8724,124,"CAN","Canada","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CAN/can_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8725,152,"CHL","Chile","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CHL/chl_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8726,4,"AFG","Afghanistan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/AFG/afg_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8727,8,"ALB","Albania","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ALB/alb_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8728,10,"ATA","Antarctica","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ATA/ata_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8729,12,"DZA","Algeria","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/DZA/dza_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8730,16,"ASM","American Samoa","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ASM/asm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8731,20,"AND","Andorra","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/AND/and_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8732,24,"AGO","Angola","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/AGO/ago_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8733,28,"ATG","Antigua and Barbuda","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ATG/atg_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8734,31,"AZE","Azerbaijan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/AZE/aze_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8735,32,"ARG","Argentina","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ARG/arg_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8736,40,"AUT","Austria","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/AUT/aut_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8737,44,"BHS","Bahamas","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BHS/bhs_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8738,48,"BHR","Bahrain","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BHR/bhr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8739,50,"BGD","Bangladesh","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BGD/bgd_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8740,51,"ARM","Armenia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ARM/arm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8741,52,"BRB","Barbados","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BRB/brb_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8742,56,"BEL","Belgium","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BEL/bel_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8743,60,"BMU","Bermuda","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BMU/bmu_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8744,64,"BTN","Bhutan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BTN/btn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8745,68,"BOL","Bolivia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BOL/bol_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8746,70,"BIH","Bosnia and Herzegovina","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BIH/bih_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8747,72,"BWA","Botswana","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BWA/bwa_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8748,74,"BVT","Bouvet Island","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BVT/bvt_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8749,84,"BLZ","Belize","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BLZ/blz_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8750,86,"IOT","British Indian Ocean Territory","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/IOT/iot_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8751,90,"SLB","Solomon Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SLB/slb_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8752,92,"VGB","British Virgin Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/VGB/vgb_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8753,96,"BRN","Brunei","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BRN/brn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8754,100,"BGR","Bulgaria","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BGR/bgr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8755,104,"MMR","Myanmar","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MMR/mmr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8756,108,"BDI","Burundi","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BDI/bdi_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8757,112,"BLR","Belarus","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BLR/blr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8758,116,"KHM","Cambodia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/KHM/khm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8759,120,"CMR","Cameroon","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CMR/cmr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8760,132,"CPV","Cape Verde","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CPV/cpv_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8761,136,"CYM","Cayman Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CYM/cym_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8762,140,"CAF","Central African Republic","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CAF/caf_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8763,144,"LKA","Sri Lanka","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LKA/lka_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8764,148,"TCD","Chad","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TCD/tcd_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8765,158,"TWN","Taiwan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TWN/twn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8766,170,"COL","Colombia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/COL/col_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8767,174,"COM","Comoros","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/COM/com_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8768,175,"MYT","Mayotte","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MYT/myt_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8769,178,"COG","Republic of Congo","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/COG/cog_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8770,180,"COD","Democratic Republic of the Congo","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/COD/cod_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8771,184,"COK","Cook Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/COK/cok_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8772,188,"CRI","Costa Rica","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CRI/cri_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8773,191,"HRV","Croatia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/HRV/hrv_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8774,192,"CUB","Cuba","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CUB/cub_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8775,196,"CYP","Cyprus","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CYP/cyp_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8776,203,"CZE","Czech Republic","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CZE/cze_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8777,204,"BEN","Benin","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BEN/ben_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8778,208,"DNK","Denmark","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/DNK/dnk_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8779,212,"DMA","Dominica","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/DMA/dma_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8780,214,"DOM","Dominican Republic","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/DOM/dom_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8781,218,"ECU","Ecuador","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ECU/ecu_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8782,222,"SLV","El Salvador","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SLV/slv_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8783,226,"GNQ","Equatorial Guinea","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GNQ/gnq_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8784,231,"ETH","Ethiopia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ETH/eth_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8785,232,"ERI","Eritrea","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ERI/eri_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8786,233,"EST","Estonia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/EST/est_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8787,234,"FRO","Faroe Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/FRO/fro_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8788,238,"FLK","Falkland Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/FLK/flk_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8789,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SGS/sgs_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8790,242,"FJI","Fiji","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/FJI/fji_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8791,246,"FIN","Finland","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/FIN/fin_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8792,248,"ALA","Aland Islands ","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ALA/ala_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8793,250,"FRA","France","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/FRA/fra_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8794,254,"GUF","French Guiana","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GUF/guf_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8795,258,"PYF","French Polynesia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PYF/pyf_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8796,260,"ATF","French Southern Territories","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ATF/atf_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8797,262,"DJI","Djibouti","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/DJI/dji_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8798,266,"GAB","Gabon","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GAB/gab_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8799,268,"GEO","Georgia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GEO/geo_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8800,270,"GMB","Gambia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GMB/gmb_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8801,275,"PSE","Palestina","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PSE/pse_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8802,276,"DEU","Germany","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/DEU/deu_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8803,288,"GHA","Ghana","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GHA/gha_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8804,292,"GIB","Gibraltar","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GIB/gib_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8805,296,"KIR","Kiribati","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/KIR/kir_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8806,300,"GRC","Greece","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GRC/grc_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8807,308,"GRD","Grenada","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GRD/grd_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8808,312,"GLP","Guadeloupe","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GLP/glp_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8809,316,"GUM","Guam","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GUM/gum_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8810,320,"GTM","Guatemala","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GTM/gtm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8811,324,"GIN","Guinea","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GIN/gin_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8812,328,"GUY","Guyana","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GUY/guy_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8813,332,"HTI","Haiti","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/HTI/hti_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8814,334,"HMD","Heard Island and McDonald Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/HMD/hmd_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8815,336,"VAT","Vatican City","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/VAT/vat_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8816,340,"HND","Honduras","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/HND/hnd_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8817,344,"HKG","Hong Kong","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/HKG/hkg_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8818,348,"HUN","Hungary","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/HUN/hun_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8819,352,"ISL","Iceland","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ISL/isl_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8820,356,"IND","India","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/IND/ind_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8821,364,"IRN","Iran","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/IRN/irn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8822,368,"IRQ","Iraq","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/IRQ/irq_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8823,372,"IRL","Ireland","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/IRL/irl_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8824,376,"ISR","Israel","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ISR/isr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8825,380,"ITA","Italy","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ITA/ita_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8826,384,"CIV","CIte dIvoire","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CIV/civ_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8827,388,"JAM","Jamaica","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/JAM/jam_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8828,392,"JPN","Japan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/JPN/jpn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8829,398,"KAZ","Kazakhstan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/KAZ/kaz_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8830,400,"JOR","Jordan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/JOR/jor_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8831,404,"KEN","Kenya","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/KEN/ken_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8832,408,"PRK","North Korea","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PRK/prk_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8833,410,"KOR","South Korea","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/KOR/kor_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8834,414,"KWT","Kuwait","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/KWT/kwt_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8835,417,"KGZ","Kyrgyzstan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/KGZ/kgz_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8836,418,"LAO","Laos","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LAO/lao_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8837,422,"LBN","Lebanon","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LBN/lbn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8838,426,"LSO","Lesotho","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LSO/lso_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8839,428,"LVA","Latvia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LVA/lva_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8840,430,"LBR","Liberia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LBR/lbr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8841,434,"LBY","Libya","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LBY/lby_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8842,438,"LIE","Liechtenstein","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LIE/lie_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8843,440,"LTU","Lithuania","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LTU/ltu_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8844,442,"LUX","Luxembourg","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LUX/lux_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8845,446,"MAC","Macao","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MAC/mac_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8846,450,"MDG","Madagascar","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MDG/mdg_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8847,454,"MWI","Malawi","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MWI/mwi_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8848,458,"MYS","Malaysia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MYS/mys_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8849,462,"MDV","Maldives","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MDV/mdv_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8850,466,"MLI","Mali","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MLI/mli_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8851,470,"MLT","Malta","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MLT/mlt_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8852,474,"MTQ","Martinique","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MTQ/mtq_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8853,478,"MRT","Mauritania","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MRT/mrt_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8854,480,"MUS","Mauritius","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MUS/mus_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8855,484,"MEX","Mexico","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MEX/mex_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8856,492,"MCO","Monaco","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MCO/mco_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8857,496,"MNG","Mongolia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MNG/mng_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8858,498,"MDA","Moldova","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MDA/mda_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8859,499,"MNE","Montenegro","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MNE/mne_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8860,500,"MSR","Montserrat","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MSR/msr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8861,504,"MAR","Morocco","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MAR/mar_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8862,508,"MOZ","Mozambique","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MOZ/moz_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8863,512,"OMN","Oman","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/OMN/omn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8864,516,"NAM","Namibia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NAM/nam_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8865,520,"NRU","Nauru","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NRU/nru_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8866,524,"NPL","Nepal","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NPL/npl_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8867,528,"NLD","Netherlands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NLD/nld_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8868,531,"CUW","Curacao","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CUW/cuw_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8869,533,"ABW","Aruba","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ABW/abw_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8870,534,"SXM","Sint Maarten (Dutch part)","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SXM/sxm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8871,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BES/bes_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8872,540,"NCL","New Caledonia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NCL/ncl_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8873,548,"VUT","Vanuatu","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/VUT/vut_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8874,554,"NZL","New Zealand","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NZL/nzl_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8875,558,"NIC","Nicaragua","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NIC/nic_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8876,562,"NER","Niger","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NER/ner_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8877,566,"NGA","Nigeria","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NGA/nga_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8878,570,"NIU","Niue","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NIU/niu_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8879,574,"NFK","Norfolk Island","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NFK/nfk_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8880,578,"NOR","Norway","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/NOR/nor_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8881,580,"MNP","Northern Mariana Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MNP/mnp_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8882,581,"UMI","United States Minor Outlying Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/UMI/umi_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8883,583,"FSM","Micronesia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/FSM/fsm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8884,584,"MHL","Marshall Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MHL/mhl_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8885,585,"PLW","Palau","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PLW/plw_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8886,586,"PAK","Pakistan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PAK/pak_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8887,591,"PAN","Panama","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PAN/pan_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8888,598,"PNG","Papua New Guinea","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PNG/png_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8889,600,"PRY","Paraguay","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PRY/pry_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8890,604,"PER","Peru","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PER/per_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8891,608,"PHL","Philippines","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PHL/phl_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8892,612,"PCN","Pitcairn Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PCN/pcn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8893,616,"POL","Poland","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/POL/pol_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8894,620,"PRT","Portugal","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PRT/prt_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8895,624,"GNB","Guinea-Bissau","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GNB/gnb_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8896,626,"TLS","East Timor","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TLS/tls_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8897,630,"PRI","Puerto Rico","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/PRI/pri_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8898,634,"QAT","Qatar","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/QAT/qat_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8899,638,"REU","Reunion","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/REU/reu_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8900,642,"ROU","Romania","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ROU/rou_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8901,646,"RWA","Rwanda","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/RWA/rwa_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8902,652,"BLM","Saint Barthelemy","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BLM/blm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8903,654,"SHN","Saint Helena","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SHN/shn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8904,659,"KNA","Saint Kitts and Nevis","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/KNA/kna_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8905,660,"AIA","Anguilla","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/AIA/aia_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8906,662,"LCA","Saint Lucia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/LCA/lca_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8907,663,"MAF","Saint Martin (French part)","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MAF/maf_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8908,666,"SPM","Saint Pierre and Miquelon","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SPM/spm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8909,670,"VCT","Saint Vincent and the Grenadines","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/VCT/vct_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8910,674,"SMR","San Marino","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SMR/smr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8911,678,"STP","Sao Tome and Principe","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/STP/stp_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8912,682,"SAU","Saudi Arabia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SAU/sau_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8913,686,"SEN","Senegal","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SEN/sen_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8914,688,"SRB","Serbia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SRB/srb_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8915,690,"SYC","Seychelles","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SYC/syc_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8916,694,"SLE","Sierra Leone","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SLE/sle_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8917,702,"SGP","Singapore","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SGP/sgp_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8918,703,"SVK","Slovakia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SVK/svk_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8919,704,"VNM","Vietnam","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/VNM/vnm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8920,705,"SVN","Slovenia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SVN/svn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8921,706,"SOM","Somalia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SOM/som_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8922,710,"ZAF","South Africa","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ZAF/zaf_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8923,716,"ZWE","Zimbabwe","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ZWE/zwe_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8924,724,"ESP","Spain","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ESP/esp_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8925,728,"SSD","South Sudan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SSD/ssd_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8926,729,"SDN","Sudan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SDN/sdn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8927,732,"ESH","Western Sahara","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ESH/esh_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8928,740,"SUR","Suriname","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SUR/sur_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8929,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SJM/sjm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8930,748,"SWZ","Swaziland","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SWZ/swz_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8931,752,"SWE","Sweden","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SWE/swe_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8932,756,"CHE","Switzerland","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/CHE/che_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8933,760,"SYR","Syria","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SYR/syr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8934,762,"TJK","Tajikistan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TJK/tjk_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8935,764,"THA","Thailand","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/THA/tha_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8936,768,"TGO","Togo","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TGO/tgo_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8937,772,"TKL","Tokelau","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TKL/tkl_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8938,776,"TON","Tonga","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TON/ton_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8939,780,"TTO","Trinidad and Tobago","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TTO/tto_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8940,784,"ARE","United Arab Emirates","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ARE/are_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8941,788,"TUN","Tunisia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TUN/tun_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8942,792,"TUR","Turkey","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TUR/tur_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8943,795,"TKM","Turkmenistan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TKM/tkm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8944,796,"TCA","Turks and Caicos Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TCA/tca_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8945,798,"TUV","Tuvalu","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TUV/tuv_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8946,800,"UGA","Uganda","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/UGA/uga_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8947,804,"UKR","Ukraine","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/UKR/ukr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8948,807,"MKD","Macedonia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/MKD/mkd_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8949,818,"EGY","Egypt","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/EGY/egy_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8950,826,"GBR","United Kingdom","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GBR/gbr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8951,831,"GGY","Guernsey","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/GGY/ggy_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8952,832,"JEY","Jersey","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/JEY/jey_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8953,833,"IMN","Isle of Man","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/IMN/imn_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8954,834,"TZA","Tanzania","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/TZA/tza_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8955,854,"BFA","Burkina Faso","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/BFA/bfa_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8956,858,"URY","Uruguay","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/URY/ury_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8957,860,"UZB","Uzbekistan","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/UZB/uzb_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8958,862,"VEN","Venezuela","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/VEN/ven_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8959,876,"WLF","Wallis and Futuna","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/WLF/wlf_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8960,882,"WSM","Samoa","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/WSM/wsm_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8961,887,"YEM","Yemen","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/YEM/yem_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8962,894,"ZMB","Zambia","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/ZMB/zmb_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8963,900,"KOS","Kosovo","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/KOS/kos_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8964,901,"SPR","Spratly Islands","ppp_2014_UNadj","GIS/Population/Global_2000_2020/2014/SPR/spr_ppp_2014_UNadj.tif","Estimated total number of people per grid-cell 2014 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8965,643,"RUS","Russia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/RUS/rus_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8966,360,"IDN","Indonesia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/IDN/idn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8967,840,"USA","United States","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/USA/usa_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8968,850,"VIR","Virgin_Islands_U_S","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/VIR/vir_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8969,304,"GRL","Greenland","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GRL/grl_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8970,156,"CHN","China","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CHN/chn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8971,36,"AUS","Australia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/AUS/aus_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8972,76,"BRA","Brazil","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BRA/bra_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8973,124,"CAN","Canada","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CAN/can_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8974,152,"CHL","Chile","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CHL/chl_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8975,4,"AFG","Afghanistan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/AFG/afg_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8976,8,"ALB","Albania","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ALB/alb_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8977,10,"ATA","Antarctica","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ATA/ata_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8978,12,"DZA","Algeria","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/DZA/dza_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8979,16,"ASM","American Samoa","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ASM/asm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8980,20,"AND","Andorra","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/AND/and_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8981,24,"AGO","Angola","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/AGO/ago_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8982,28,"ATG","Antigua and Barbuda","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ATG/atg_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8983,31,"AZE","Azerbaijan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/AZE/aze_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8984,32,"ARG","Argentina","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ARG/arg_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8985,40,"AUT","Austria","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/AUT/aut_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8986,44,"BHS","Bahamas","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BHS/bhs_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8987,48,"BHR","Bahrain","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BHR/bhr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8988,50,"BGD","Bangladesh","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BGD/bgd_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8989,51,"ARM","Armenia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ARM/arm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8990,52,"BRB","Barbados","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BRB/brb_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8991,56,"BEL","Belgium","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BEL/bel_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8992,60,"BMU","Bermuda","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BMU/bmu_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8993,64,"BTN","Bhutan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BTN/btn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8994,68,"BOL","Bolivia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BOL/bol_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8995,70,"BIH","Bosnia and Herzegovina","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BIH/bih_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8996,72,"BWA","Botswana","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BWA/bwa_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8997,74,"BVT","Bouvet Island","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BVT/bvt_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8998,84,"BLZ","Belize","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BLZ/blz_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
8999,86,"IOT","British Indian Ocean Territory","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/IOT/iot_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9000,90,"SLB","Solomon Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SLB/slb_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9001,92,"VGB","British Virgin Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/VGB/vgb_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9002,96,"BRN","Brunei","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BRN/brn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9003,100,"BGR","Bulgaria","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BGR/bgr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9004,104,"MMR","Myanmar","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MMR/mmr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9005,108,"BDI","Burundi","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BDI/bdi_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9006,112,"BLR","Belarus","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BLR/blr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9007,116,"KHM","Cambodia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/KHM/khm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9008,120,"CMR","Cameroon","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CMR/cmr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9009,132,"CPV","Cape Verde","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CPV/cpv_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9010,136,"CYM","Cayman Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CYM/cym_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9011,140,"CAF","Central African Republic","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CAF/caf_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9012,144,"LKA","Sri Lanka","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LKA/lka_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9013,148,"TCD","Chad","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TCD/tcd_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9014,158,"TWN","Taiwan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TWN/twn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9015,170,"COL","Colombia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/COL/col_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9016,174,"COM","Comoros","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/COM/com_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9017,175,"MYT","Mayotte","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MYT/myt_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9018,178,"COG","Republic of Congo","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/COG/cog_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9019,180,"COD","Democratic Republic of the Congo","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/COD/cod_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9020,184,"COK","Cook Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/COK/cok_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9021,188,"CRI","Costa Rica","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CRI/cri_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9022,191,"HRV","Croatia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/HRV/hrv_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9023,192,"CUB","Cuba","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CUB/cub_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9024,196,"CYP","Cyprus","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CYP/cyp_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9025,203,"CZE","Czech Republic","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CZE/cze_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9026,204,"BEN","Benin","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BEN/ben_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9027,208,"DNK","Denmark","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/DNK/dnk_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9028,212,"DMA","Dominica","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/DMA/dma_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9029,214,"DOM","Dominican Republic","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/DOM/dom_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9030,218,"ECU","Ecuador","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ECU/ecu_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9031,222,"SLV","El Salvador","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SLV/slv_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9032,226,"GNQ","Equatorial Guinea","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GNQ/gnq_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9033,231,"ETH","Ethiopia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ETH/eth_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9034,232,"ERI","Eritrea","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ERI/eri_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9035,233,"EST","Estonia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/EST/est_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9036,234,"FRO","Faroe Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/FRO/fro_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9037,238,"FLK","Falkland Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/FLK/flk_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9038,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SGS/sgs_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9039,242,"FJI","Fiji","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/FJI/fji_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9040,246,"FIN","Finland","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/FIN/fin_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9041,248,"ALA","Aland Islands ","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ALA/ala_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9042,250,"FRA","France","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/FRA/fra_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9043,254,"GUF","French Guiana","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GUF/guf_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9044,258,"PYF","French Polynesia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PYF/pyf_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9045,260,"ATF","French Southern Territories","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ATF/atf_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9046,262,"DJI","Djibouti","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/DJI/dji_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9047,266,"GAB","Gabon","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GAB/gab_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9048,268,"GEO","Georgia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GEO/geo_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9049,270,"GMB","Gambia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GMB/gmb_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9050,275,"PSE","Palestina","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PSE/pse_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9051,276,"DEU","Germany","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/DEU/deu_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9052,288,"GHA","Ghana","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GHA/gha_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9053,292,"GIB","Gibraltar","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GIB/gib_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9054,296,"KIR","Kiribati","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/KIR/kir_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9055,300,"GRC","Greece","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GRC/grc_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9056,308,"GRD","Grenada","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GRD/grd_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9057,312,"GLP","Guadeloupe","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GLP/glp_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9058,316,"GUM","Guam","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GUM/gum_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9059,320,"GTM","Guatemala","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GTM/gtm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9060,324,"GIN","Guinea","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GIN/gin_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9061,328,"GUY","Guyana","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GUY/guy_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9062,332,"HTI","Haiti","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/HTI/hti_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9063,334,"HMD","Heard Island and McDonald Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/HMD/hmd_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9064,336,"VAT","Vatican City","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/VAT/vat_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9065,340,"HND","Honduras","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/HND/hnd_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9066,344,"HKG","Hong Kong","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/HKG/hkg_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9067,348,"HUN","Hungary","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/HUN/hun_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9068,352,"ISL","Iceland","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ISL/isl_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9069,356,"IND","India","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/IND/ind_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9070,364,"IRN","Iran","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/IRN/irn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9071,368,"IRQ","Iraq","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/IRQ/irq_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9072,372,"IRL","Ireland","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/IRL/irl_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9073,376,"ISR","Israel","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ISR/isr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9074,380,"ITA","Italy","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ITA/ita_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9075,384,"CIV","CIte dIvoire","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CIV/civ_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9076,388,"JAM","Jamaica","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/JAM/jam_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9077,392,"JPN","Japan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/JPN/jpn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9078,398,"KAZ","Kazakhstan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/KAZ/kaz_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9079,400,"JOR","Jordan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/JOR/jor_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9080,404,"KEN","Kenya","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/KEN/ken_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9081,408,"PRK","North Korea","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PRK/prk_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9082,410,"KOR","South Korea","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/KOR/kor_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9083,414,"KWT","Kuwait","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/KWT/kwt_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9084,417,"KGZ","Kyrgyzstan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/KGZ/kgz_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9085,418,"LAO","Laos","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LAO/lao_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9086,422,"LBN","Lebanon","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LBN/lbn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9087,426,"LSO","Lesotho","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LSO/lso_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9088,428,"LVA","Latvia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LVA/lva_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9089,430,"LBR","Liberia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LBR/lbr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9090,434,"LBY","Libya","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LBY/lby_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9091,438,"LIE","Liechtenstein","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LIE/lie_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9092,440,"LTU","Lithuania","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LTU/ltu_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9093,442,"LUX","Luxembourg","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LUX/lux_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9094,446,"MAC","Macao","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MAC/mac_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9095,450,"MDG","Madagascar","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MDG/mdg_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9096,454,"MWI","Malawi","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MWI/mwi_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9097,458,"MYS","Malaysia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MYS/mys_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9098,462,"MDV","Maldives","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MDV/mdv_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9099,466,"MLI","Mali","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MLI/mli_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9100,470,"MLT","Malta","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MLT/mlt_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9101,474,"MTQ","Martinique","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MTQ/mtq_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9102,478,"MRT","Mauritania","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MRT/mrt_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9103,480,"MUS","Mauritius","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MUS/mus_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9104,484,"MEX","Mexico","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MEX/mex_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9105,492,"MCO","Monaco","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MCO/mco_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9106,496,"MNG","Mongolia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MNG/mng_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9107,498,"MDA","Moldova","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MDA/mda_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9108,499,"MNE","Montenegro","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MNE/mne_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9109,500,"MSR","Montserrat","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MSR/msr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9110,504,"MAR","Morocco","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MAR/mar_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9111,508,"MOZ","Mozambique","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MOZ/moz_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9112,512,"OMN","Oman","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/OMN/omn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9113,516,"NAM","Namibia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NAM/nam_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9114,520,"NRU","Nauru","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NRU/nru_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9115,524,"NPL","Nepal","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NPL/npl_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9116,528,"NLD","Netherlands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NLD/nld_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9117,531,"CUW","Curacao","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CUW/cuw_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9118,533,"ABW","Aruba","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ABW/abw_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9119,534,"SXM","Sint Maarten (Dutch part)","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SXM/sxm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9120,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BES/bes_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9121,540,"NCL","New Caledonia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NCL/ncl_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9122,548,"VUT","Vanuatu","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/VUT/vut_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9123,554,"NZL","New Zealand","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NZL/nzl_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9124,558,"NIC","Nicaragua","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NIC/nic_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9125,562,"NER","Niger","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NER/ner_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9126,566,"NGA","Nigeria","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NGA/nga_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9127,570,"NIU","Niue","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NIU/niu_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9128,574,"NFK","Norfolk Island","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NFK/nfk_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9129,578,"NOR","Norway","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/NOR/nor_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9130,580,"MNP","Northern Mariana Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MNP/mnp_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9131,581,"UMI","United States Minor Outlying Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/UMI/umi_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9132,583,"FSM","Micronesia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/FSM/fsm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9133,584,"MHL","Marshall Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MHL/mhl_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9134,585,"PLW","Palau","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PLW/plw_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9135,586,"PAK","Pakistan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PAK/pak_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9136,591,"PAN","Panama","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PAN/pan_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9137,598,"PNG","Papua New Guinea","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PNG/png_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9138,600,"PRY","Paraguay","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PRY/pry_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9139,604,"PER","Peru","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PER/per_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9140,608,"PHL","Philippines","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PHL/phl_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9141,612,"PCN","Pitcairn Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PCN/pcn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9142,616,"POL","Poland","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/POL/pol_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9143,620,"PRT","Portugal","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PRT/prt_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9144,624,"GNB","Guinea-Bissau","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GNB/gnb_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9145,626,"TLS","East Timor","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TLS/tls_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9146,630,"PRI","Puerto Rico","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/PRI/pri_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9147,634,"QAT","Qatar","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/QAT/qat_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9148,638,"REU","Reunion","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/REU/reu_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9149,642,"ROU","Romania","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ROU/rou_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9150,646,"RWA","Rwanda","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/RWA/rwa_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9151,652,"BLM","Saint Barthelemy","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BLM/blm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9152,654,"SHN","Saint Helena","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SHN/shn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9153,659,"KNA","Saint Kitts and Nevis","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/KNA/kna_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9154,660,"AIA","Anguilla","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/AIA/aia_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9155,662,"LCA","Saint Lucia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/LCA/lca_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9156,663,"MAF","Saint Martin (French part)","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MAF/maf_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9157,666,"SPM","Saint Pierre and Miquelon","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SPM/spm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9158,670,"VCT","Saint Vincent and the Grenadines","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/VCT/vct_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9159,674,"SMR","San Marino","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SMR/smr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9160,678,"STP","Sao Tome and Principe","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/STP/stp_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9161,682,"SAU","Saudi Arabia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SAU/sau_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9162,686,"SEN","Senegal","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SEN/sen_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9163,688,"SRB","Serbia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SRB/srb_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9164,690,"SYC","Seychelles","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SYC/syc_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9165,694,"SLE","Sierra Leone","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SLE/sle_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9166,702,"SGP","Singapore","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SGP/sgp_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9167,703,"SVK","Slovakia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SVK/svk_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9168,704,"VNM","Vietnam","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/VNM/vnm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9169,705,"SVN","Slovenia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SVN/svn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9170,706,"SOM","Somalia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SOM/som_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9171,710,"ZAF","South Africa","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ZAF/zaf_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9172,716,"ZWE","Zimbabwe","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ZWE/zwe_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9173,724,"ESP","Spain","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ESP/esp_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9174,728,"SSD","South Sudan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SSD/ssd_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9175,729,"SDN","Sudan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SDN/sdn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9176,732,"ESH","Western Sahara","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ESH/esh_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9177,740,"SUR","Suriname","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SUR/sur_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9178,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SJM/sjm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9179,748,"SWZ","Swaziland","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SWZ/swz_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9180,752,"SWE","Sweden","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SWE/swe_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9181,756,"CHE","Switzerland","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/CHE/che_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9182,760,"SYR","Syria","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SYR/syr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9183,762,"TJK","Tajikistan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TJK/tjk_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9184,764,"THA","Thailand","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/THA/tha_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9185,768,"TGO","Togo","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TGO/tgo_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9186,772,"TKL","Tokelau","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TKL/tkl_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9187,776,"TON","Tonga","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TON/ton_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9188,780,"TTO","Trinidad and Tobago","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TTO/tto_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9189,784,"ARE","United Arab Emirates","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ARE/are_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9190,788,"TUN","Tunisia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TUN/tun_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9191,792,"TUR","Turkey","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TUR/tur_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9192,795,"TKM","Turkmenistan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TKM/tkm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9193,796,"TCA","Turks and Caicos Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TCA/tca_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9194,798,"TUV","Tuvalu","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TUV/tuv_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9195,800,"UGA","Uganda","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/UGA/uga_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9196,804,"UKR","Ukraine","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/UKR/ukr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9197,807,"MKD","Macedonia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/MKD/mkd_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9198,818,"EGY","Egypt","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/EGY/egy_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9199,826,"GBR","United Kingdom","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GBR/gbr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9200,831,"GGY","Guernsey","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/GGY/ggy_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9201,832,"JEY","Jersey","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/JEY/jey_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9202,833,"IMN","Isle of Man","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/IMN/imn_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9203,834,"TZA","Tanzania","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/TZA/tza_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9204,854,"BFA","Burkina Faso","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/BFA/bfa_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9205,858,"URY","Uruguay","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/URY/ury_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9206,860,"UZB","Uzbekistan","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/UZB/uzb_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9207,862,"VEN","Venezuela","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/VEN/ven_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9208,876,"WLF","Wallis and Futuna","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/WLF/wlf_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9209,882,"WSM","Samoa","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/WSM/wsm_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9210,887,"YEM","Yemen","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/YEM/yem_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9211,894,"ZMB","Zambia","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/ZMB/zmb_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9212,900,"KOS","Kosovo","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/KOS/kos_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9213,901,"SPR","Spratly Islands","ppp_2015_UNadj","GIS/Population/Global_2000_2020/2015/SPR/spr_ppp_2015_UNadj.tif","Estimated total number of people per grid-cell 2015 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9214,643,"RUS","Russia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/RUS/rus_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9215,360,"IDN","Indonesia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/IDN/idn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9216,840,"USA","United States","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/USA/usa_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9217,850,"VIR","Virgin_Islands_U_S","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/VIR/vir_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9218,304,"GRL","Greenland","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GRL/grl_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9219,156,"CHN","China","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CHN/chn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9220,36,"AUS","Australia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/AUS/aus_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9221,76,"BRA","Brazil","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BRA/bra_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9222,124,"CAN","Canada","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CAN/can_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9223,152,"CHL","Chile","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CHL/chl_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9224,4,"AFG","Afghanistan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/AFG/afg_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9225,8,"ALB","Albania","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ALB/alb_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9226,10,"ATA","Antarctica","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ATA/ata_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9227,12,"DZA","Algeria","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/DZA/dza_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9228,16,"ASM","American Samoa","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ASM/asm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9229,20,"AND","Andorra","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/AND/and_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9230,24,"AGO","Angola","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/AGO/ago_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9231,28,"ATG","Antigua and Barbuda","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ATG/atg_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9232,31,"AZE","Azerbaijan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/AZE/aze_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9233,32,"ARG","Argentina","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ARG/arg_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9234,40,"AUT","Austria","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/AUT/aut_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9235,44,"BHS","Bahamas","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BHS/bhs_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9236,48,"BHR","Bahrain","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BHR/bhr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9237,50,"BGD","Bangladesh","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BGD/bgd_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9238,51,"ARM","Armenia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ARM/arm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9239,52,"BRB","Barbados","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BRB/brb_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9240,56,"BEL","Belgium","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BEL/bel_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9241,60,"BMU","Bermuda","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BMU/bmu_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9242,64,"BTN","Bhutan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BTN/btn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9243,68,"BOL","Bolivia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BOL/bol_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9244,70,"BIH","Bosnia and Herzegovina","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BIH/bih_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9245,72,"BWA","Botswana","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BWA/bwa_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9246,74,"BVT","Bouvet Island","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BVT/bvt_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9247,84,"BLZ","Belize","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BLZ/blz_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9248,86,"IOT","British Indian Ocean Territory","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/IOT/iot_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9249,90,"SLB","Solomon Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SLB/slb_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9250,92,"VGB","British Virgin Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/VGB/vgb_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9251,96,"BRN","Brunei","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BRN/brn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9252,100,"BGR","Bulgaria","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BGR/bgr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9253,104,"MMR","Myanmar","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MMR/mmr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9254,108,"BDI","Burundi","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BDI/bdi_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9255,112,"BLR","Belarus","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BLR/blr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9256,116,"KHM","Cambodia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/KHM/khm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9257,120,"CMR","Cameroon","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CMR/cmr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9258,132,"CPV","Cape Verde","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CPV/cpv_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9259,136,"CYM","Cayman Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CYM/cym_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9260,140,"CAF","Central African Republic","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CAF/caf_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9261,144,"LKA","Sri Lanka","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LKA/lka_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9262,148,"TCD","Chad","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TCD/tcd_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9263,158,"TWN","Taiwan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TWN/twn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9264,170,"COL","Colombia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/COL/col_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9265,174,"COM","Comoros","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/COM/com_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9266,175,"MYT","Mayotte","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MYT/myt_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9267,178,"COG","Republic of Congo","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/COG/cog_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9268,180,"COD","Democratic Republic of the Congo","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/COD/cod_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9269,184,"COK","Cook Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/COK/cok_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9270,188,"CRI","Costa Rica","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CRI/cri_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9271,191,"HRV","Croatia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/HRV/hrv_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9272,192,"CUB","Cuba","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CUB/cub_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9273,196,"CYP","Cyprus","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CYP/cyp_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9274,203,"CZE","Czech Republic","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CZE/cze_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9275,204,"BEN","Benin","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BEN/ben_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9276,208,"DNK","Denmark","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/DNK/dnk_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9277,212,"DMA","Dominica","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/DMA/dma_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9278,214,"DOM","Dominican Republic","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/DOM/dom_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9279,218,"ECU","Ecuador","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ECU/ecu_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9280,222,"SLV","El Salvador","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SLV/slv_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9281,226,"GNQ","Equatorial Guinea","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GNQ/gnq_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9282,231,"ETH","Ethiopia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ETH/eth_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9283,232,"ERI","Eritrea","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ERI/eri_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9284,233,"EST","Estonia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/EST/est_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9285,234,"FRO","Faroe Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/FRO/fro_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9286,238,"FLK","Falkland Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/FLK/flk_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9287,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SGS/sgs_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9288,242,"FJI","Fiji","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/FJI/fji_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9289,246,"FIN","Finland","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/FIN/fin_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9290,248,"ALA","Aland Islands ","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ALA/ala_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9291,250,"FRA","France","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/FRA/fra_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9292,254,"GUF","French Guiana","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GUF/guf_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9293,258,"PYF","French Polynesia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PYF/pyf_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9294,260,"ATF","French Southern Territories","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ATF/atf_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9295,262,"DJI","Djibouti","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/DJI/dji_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9296,266,"GAB","Gabon","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GAB/gab_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9297,268,"GEO","Georgia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GEO/geo_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9298,270,"GMB","Gambia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GMB/gmb_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9299,275,"PSE","Palestina","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PSE/pse_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9300,276,"DEU","Germany","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/DEU/deu_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9301,288,"GHA","Ghana","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GHA/gha_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9302,292,"GIB","Gibraltar","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GIB/gib_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9303,296,"KIR","Kiribati","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/KIR/kir_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9304,300,"GRC","Greece","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GRC/grc_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9305,308,"GRD","Grenada","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GRD/grd_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9306,312,"GLP","Guadeloupe","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GLP/glp_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9307,316,"GUM","Guam","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GUM/gum_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9308,320,"GTM","Guatemala","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GTM/gtm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9309,324,"GIN","Guinea","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GIN/gin_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9310,328,"GUY","Guyana","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GUY/guy_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9311,332,"HTI","Haiti","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/HTI/hti_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9312,334,"HMD","Heard Island and McDonald Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/HMD/hmd_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9313,336,"VAT","Vatican City","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/VAT/vat_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9314,340,"HND","Honduras","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/HND/hnd_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9315,344,"HKG","Hong Kong","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/HKG/hkg_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9316,348,"HUN","Hungary","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/HUN/hun_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9317,352,"ISL","Iceland","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ISL/isl_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9318,356,"IND","India","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/IND/ind_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9319,364,"IRN","Iran","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/IRN/irn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9320,368,"IRQ","Iraq","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/IRQ/irq_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9321,372,"IRL","Ireland","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/IRL/irl_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9322,376,"ISR","Israel","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ISR/isr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9323,380,"ITA","Italy","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ITA/ita_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9324,384,"CIV","CIte dIvoire","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CIV/civ_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9325,388,"JAM","Jamaica","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/JAM/jam_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9326,392,"JPN","Japan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/JPN/jpn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9327,398,"KAZ","Kazakhstan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/KAZ/kaz_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9328,400,"JOR","Jordan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/JOR/jor_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9329,404,"KEN","Kenya","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/KEN/ken_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9330,408,"PRK","North Korea","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PRK/prk_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9331,410,"KOR","South Korea","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/KOR/kor_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9332,414,"KWT","Kuwait","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/KWT/kwt_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9333,417,"KGZ","Kyrgyzstan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/KGZ/kgz_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9334,418,"LAO","Laos","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LAO/lao_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9335,422,"LBN","Lebanon","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LBN/lbn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9336,426,"LSO","Lesotho","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LSO/lso_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9337,428,"LVA","Latvia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LVA/lva_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9338,430,"LBR","Liberia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LBR/lbr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9339,434,"LBY","Libya","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LBY/lby_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9340,438,"LIE","Liechtenstein","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LIE/lie_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9341,440,"LTU","Lithuania","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LTU/ltu_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9342,442,"LUX","Luxembourg","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LUX/lux_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9343,446,"MAC","Macao","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MAC/mac_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9344,450,"MDG","Madagascar","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MDG/mdg_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9345,454,"MWI","Malawi","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MWI/mwi_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9346,458,"MYS","Malaysia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MYS/mys_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9347,462,"MDV","Maldives","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MDV/mdv_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9348,466,"MLI","Mali","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MLI/mli_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9349,470,"MLT","Malta","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MLT/mlt_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9350,474,"MTQ","Martinique","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MTQ/mtq_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9351,478,"MRT","Mauritania","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MRT/mrt_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9352,480,"MUS","Mauritius","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MUS/mus_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9353,484,"MEX","Mexico","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MEX/mex_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9354,492,"MCO","Monaco","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MCO/mco_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9355,496,"MNG","Mongolia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MNG/mng_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9356,498,"MDA","Moldova","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MDA/mda_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9357,499,"MNE","Montenegro","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MNE/mne_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9358,500,"MSR","Montserrat","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MSR/msr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9359,504,"MAR","Morocco","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MAR/mar_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9360,508,"MOZ","Mozambique","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MOZ/moz_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9361,512,"OMN","Oman","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/OMN/omn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9362,516,"NAM","Namibia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NAM/nam_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9363,520,"NRU","Nauru","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NRU/nru_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9364,524,"NPL","Nepal","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NPL/npl_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9365,528,"NLD","Netherlands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NLD/nld_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9366,531,"CUW","Curacao","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CUW/cuw_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9367,533,"ABW","Aruba","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ABW/abw_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9368,534,"SXM","Sint Maarten (Dutch part)","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SXM/sxm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9369,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BES/bes_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9370,540,"NCL","New Caledonia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NCL/ncl_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9371,548,"VUT","Vanuatu","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/VUT/vut_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9372,554,"NZL","New Zealand","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NZL/nzl_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9373,558,"NIC","Nicaragua","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NIC/nic_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9374,562,"NER","Niger","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NER/ner_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9375,566,"NGA","Nigeria","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NGA/nga_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9376,570,"NIU","Niue","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NIU/niu_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9377,574,"NFK","Norfolk Island","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NFK/nfk_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9378,578,"NOR","Norway","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/NOR/nor_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9379,580,"MNP","Northern Mariana Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MNP/mnp_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9380,581,"UMI","United States Minor Outlying Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/UMI/umi_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9381,583,"FSM","Micronesia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/FSM/fsm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9382,584,"MHL","Marshall Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MHL/mhl_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9383,585,"PLW","Palau","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PLW/plw_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9384,586,"PAK","Pakistan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PAK/pak_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9385,591,"PAN","Panama","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PAN/pan_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9386,598,"PNG","Papua New Guinea","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PNG/png_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9387,600,"PRY","Paraguay","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PRY/pry_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9388,604,"PER","Peru","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PER/per_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9389,608,"PHL","Philippines","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PHL/phl_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9390,612,"PCN","Pitcairn Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PCN/pcn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9391,616,"POL","Poland","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/POL/pol_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9392,620,"PRT","Portugal","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PRT/prt_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9393,624,"GNB","Guinea-Bissau","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GNB/gnb_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9394,626,"TLS","East Timor","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TLS/tls_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9395,630,"PRI","Puerto Rico","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/PRI/pri_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9396,634,"QAT","Qatar","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/QAT/qat_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9397,638,"REU","Reunion","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/REU/reu_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9398,642,"ROU","Romania","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ROU/rou_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9399,646,"RWA","Rwanda","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/RWA/rwa_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9400,652,"BLM","Saint Barthelemy","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BLM/blm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9401,654,"SHN","Saint Helena","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SHN/shn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9402,659,"KNA","Saint Kitts and Nevis","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/KNA/kna_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9403,660,"AIA","Anguilla","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/AIA/aia_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9404,662,"LCA","Saint Lucia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/LCA/lca_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9405,663,"MAF","Saint Martin (French part)","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MAF/maf_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9406,666,"SPM","Saint Pierre and Miquelon","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SPM/spm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9407,670,"VCT","Saint Vincent and the Grenadines","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/VCT/vct_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9408,674,"SMR","San Marino","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SMR/smr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9409,678,"STP","Sao Tome and Principe","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/STP/stp_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9410,682,"SAU","Saudi Arabia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SAU/sau_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9411,686,"SEN","Senegal","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SEN/sen_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9412,688,"SRB","Serbia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SRB/srb_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9413,690,"SYC","Seychelles","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SYC/syc_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9414,694,"SLE","Sierra Leone","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SLE/sle_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9415,702,"SGP","Singapore","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SGP/sgp_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9416,703,"SVK","Slovakia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SVK/svk_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9417,704,"VNM","Vietnam","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/VNM/vnm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9418,705,"SVN","Slovenia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SVN/svn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9419,706,"SOM","Somalia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SOM/som_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9420,710,"ZAF","South Africa","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ZAF/zaf_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9421,716,"ZWE","Zimbabwe","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ZWE/zwe_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9422,724,"ESP","Spain","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ESP/esp_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9423,728,"SSD","South Sudan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SSD/ssd_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9424,729,"SDN","Sudan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SDN/sdn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9425,732,"ESH","Western Sahara","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ESH/esh_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9426,740,"SUR","Suriname","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SUR/sur_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9427,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SJM/sjm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9428,748,"SWZ","Swaziland","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SWZ/swz_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9429,752,"SWE","Sweden","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SWE/swe_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9430,756,"CHE","Switzerland","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/CHE/che_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9431,760,"SYR","Syria","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SYR/syr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9432,762,"TJK","Tajikistan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TJK/tjk_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9433,764,"THA","Thailand","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/THA/tha_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9434,768,"TGO","Togo","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TGO/tgo_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9435,772,"TKL","Tokelau","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TKL/tkl_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9436,776,"TON","Tonga","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TON/ton_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9437,780,"TTO","Trinidad and Tobago","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TTO/tto_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9438,784,"ARE","United Arab Emirates","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ARE/are_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9439,788,"TUN","Tunisia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TUN/tun_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9440,792,"TUR","Turkey","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TUR/tur_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9441,795,"TKM","Turkmenistan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TKM/tkm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9442,796,"TCA","Turks and Caicos Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TCA/tca_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9443,798,"TUV","Tuvalu","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TUV/tuv_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9444,800,"UGA","Uganda","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/UGA/uga_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9445,804,"UKR","Ukraine","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/UKR/ukr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9446,807,"MKD","Macedonia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/MKD/mkd_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9447,818,"EGY","Egypt","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/EGY/egy_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9448,826,"GBR","United Kingdom","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GBR/gbr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9449,831,"GGY","Guernsey","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/GGY/ggy_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9450,832,"JEY","Jersey","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/JEY/jey_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9451,833,"IMN","Isle of Man","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/IMN/imn_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9452,834,"TZA","Tanzania","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/TZA/tza_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9453,854,"BFA","Burkina Faso","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/BFA/bfa_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9454,858,"URY","Uruguay","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/URY/ury_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9455,860,"UZB","Uzbekistan","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/UZB/uzb_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9456,862,"VEN","Venezuela","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/VEN/ven_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9457,876,"WLF","Wallis and Futuna","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/WLF/wlf_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9458,882,"WSM","Samoa","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/WSM/wsm_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9459,887,"YEM","Yemen","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/YEM/yem_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9460,894,"ZMB","Zambia","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/ZMB/zmb_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9461,900,"KOS","Kosovo","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/KOS/kos_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9462,901,"SPR","Spratly Islands","ppp_2016_UNadj","GIS/Population/Global_2000_2020/2016/SPR/spr_ppp_2016_UNadj.tif","Estimated total number of people per grid-cell 2016 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9463,643,"RUS","Russia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/RUS/rus_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9464,360,"IDN","Indonesia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/IDN/idn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9465,840,"USA","United States","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/USA/usa_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9466,850,"VIR","Virgin_Islands_U_S","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/VIR/vir_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9467,304,"GRL","Greenland","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GRL/grl_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9468,156,"CHN","China","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CHN/chn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9469,36,"AUS","Australia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/AUS/aus_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9470,76,"BRA","Brazil","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BRA/bra_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9471,124,"CAN","Canada","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CAN/can_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9472,152,"CHL","Chile","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CHL/chl_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9473,4,"AFG","Afghanistan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/AFG/afg_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9474,8,"ALB","Albania","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ALB/alb_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9475,10,"ATA","Antarctica","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ATA/ata_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9476,12,"DZA","Algeria","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/DZA/dza_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9477,16,"ASM","American Samoa","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ASM/asm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9478,20,"AND","Andorra","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/AND/and_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9479,24,"AGO","Angola","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/AGO/ago_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9480,28,"ATG","Antigua and Barbuda","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ATG/atg_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9481,31,"AZE","Azerbaijan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/AZE/aze_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9482,32,"ARG","Argentina","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ARG/arg_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9483,40,"AUT","Austria","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/AUT/aut_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9484,44,"BHS","Bahamas","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BHS/bhs_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9485,48,"BHR","Bahrain","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BHR/bhr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9486,50,"BGD","Bangladesh","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BGD/bgd_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9487,51,"ARM","Armenia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ARM/arm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9488,52,"BRB","Barbados","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BRB/brb_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9489,56,"BEL","Belgium","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BEL/bel_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9490,60,"BMU","Bermuda","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BMU/bmu_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9491,64,"BTN","Bhutan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BTN/btn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9492,68,"BOL","Bolivia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BOL/bol_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9493,70,"BIH","Bosnia and Herzegovina","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BIH/bih_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9494,72,"BWA","Botswana","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BWA/bwa_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9495,74,"BVT","Bouvet Island","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BVT/bvt_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9496,84,"BLZ","Belize","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BLZ/blz_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9497,86,"IOT","British Indian Ocean Territory","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/IOT/iot_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9498,90,"SLB","Solomon Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SLB/slb_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9499,92,"VGB","British Virgin Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/VGB/vgb_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9500,96,"BRN","Brunei","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BRN/brn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9501,100,"BGR","Bulgaria","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BGR/bgr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9502,104,"MMR","Myanmar","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MMR/mmr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9503,108,"BDI","Burundi","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BDI/bdi_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9504,112,"BLR","Belarus","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BLR/blr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9505,116,"KHM","Cambodia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/KHM/khm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9506,120,"CMR","Cameroon","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CMR/cmr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9507,132,"CPV","Cape Verde","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CPV/cpv_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9508,136,"CYM","Cayman Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CYM/cym_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9509,140,"CAF","Central African Republic","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CAF/caf_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9510,144,"LKA","Sri Lanka","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LKA/lka_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9511,148,"TCD","Chad","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TCD/tcd_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9512,158,"TWN","Taiwan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TWN/twn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9513,170,"COL","Colombia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/COL/col_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9514,174,"COM","Comoros","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/COM/com_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9515,175,"MYT","Mayotte","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MYT/myt_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9516,178,"COG","Republic of Congo","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/COG/cog_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9517,180,"COD","Democratic Republic of the Congo","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/COD/cod_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9518,184,"COK","Cook Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/COK/cok_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9519,188,"CRI","Costa Rica","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CRI/cri_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9520,191,"HRV","Croatia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/HRV/hrv_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9521,192,"CUB","Cuba","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CUB/cub_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9522,196,"CYP","Cyprus","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CYP/cyp_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9523,203,"CZE","Czech Republic","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CZE/cze_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9524,204,"BEN","Benin","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BEN/ben_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9525,208,"DNK","Denmark","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/DNK/dnk_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9526,212,"DMA","Dominica","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/DMA/dma_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9527,214,"DOM","Dominican Republic","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/DOM/dom_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9528,218,"ECU","Ecuador","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ECU/ecu_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9529,222,"SLV","El Salvador","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SLV/slv_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9530,226,"GNQ","Equatorial Guinea","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GNQ/gnq_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9531,231,"ETH","Ethiopia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ETH/eth_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9532,232,"ERI","Eritrea","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ERI/eri_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9533,233,"EST","Estonia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/EST/est_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9534,234,"FRO","Faroe Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/FRO/fro_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9535,238,"FLK","Falkland Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/FLK/flk_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9536,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SGS/sgs_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9537,242,"FJI","Fiji","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/FJI/fji_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9538,246,"FIN","Finland","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/FIN/fin_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9539,248,"ALA","Aland Islands ","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ALA/ala_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9540,250,"FRA","France","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/FRA/fra_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9541,254,"GUF","French Guiana","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GUF/guf_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9542,258,"PYF","French Polynesia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PYF/pyf_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9543,260,"ATF","French Southern Territories","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ATF/atf_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9544,262,"DJI","Djibouti","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/DJI/dji_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9545,266,"GAB","Gabon","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GAB/gab_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9546,268,"GEO","Georgia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GEO/geo_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9547,270,"GMB","Gambia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GMB/gmb_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9548,275,"PSE","Palestina","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PSE/pse_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9549,276,"DEU","Germany","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/DEU/deu_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9550,288,"GHA","Ghana","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GHA/gha_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9551,292,"GIB","Gibraltar","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GIB/gib_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9552,296,"KIR","Kiribati","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/KIR/kir_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9553,300,"GRC","Greece","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GRC/grc_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9554,308,"GRD","Grenada","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GRD/grd_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9555,312,"GLP","Guadeloupe","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GLP/glp_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9556,316,"GUM","Guam","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GUM/gum_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9557,320,"GTM","Guatemala","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GTM/gtm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9558,324,"GIN","Guinea","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GIN/gin_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9559,328,"GUY","Guyana","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GUY/guy_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9560,332,"HTI","Haiti","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/HTI/hti_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9561,334,"HMD","Heard Island and McDonald Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/HMD/hmd_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9562,336,"VAT","Vatican City","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/VAT/vat_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9563,340,"HND","Honduras","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/HND/hnd_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9564,344,"HKG","Hong Kong","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/HKG/hkg_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9565,348,"HUN","Hungary","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/HUN/hun_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9566,352,"ISL","Iceland","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ISL/isl_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9567,356,"IND","India","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/IND/ind_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9568,364,"IRN","Iran","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/IRN/irn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9569,368,"IRQ","Iraq","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/IRQ/irq_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9570,372,"IRL","Ireland","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/IRL/irl_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9571,376,"ISR","Israel","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ISR/isr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9572,380,"ITA","Italy","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ITA/ita_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9573,384,"CIV","CIte dIvoire","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CIV/civ_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9574,388,"JAM","Jamaica","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/JAM/jam_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9575,392,"JPN","Japan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/JPN/jpn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9576,398,"KAZ","Kazakhstan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/KAZ/kaz_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9577,400,"JOR","Jordan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/JOR/jor_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9578,404,"KEN","Kenya","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/KEN/ken_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9579,408,"PRK","North Korea","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PRK/prk_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9580,410,"KOR","South Korea","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/KOR/kor_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9581,414,"KWT","Kuwait","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/KWT/kwt_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9582,417,"KGZ","Kyrgyzstan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/KGZ/kgz_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9583,418,"LAO","Laos","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LAO/lao_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9584,422,"LBN","Lebanon","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LBN/lbn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9585,426,"LSO","Lesotho","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LSO/lso_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9586,428,"LVA","Latvia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LVA/lva_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9587,430,"LBR","Liberia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LBR/lbr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9588,434,"LBY","Libya","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LBY/lby_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9589,438,"LIE","Liechtenstein","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LIE/lie_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9590,440,"LTU","Lithuania","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LTU/ltu_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9591,442,"LUX","Luxembourg","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LUX/lux_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9592,446,"MAC","Macao","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MAC/mac_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9593,450,"MDG","Madagascar","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MDG/mdg_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9594,454,"MWI","Malawi","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MWI/mwi_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9595,458,"MYS","Malaysia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MYS/mys_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9596,462,"MDV","Maldives","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MDV/mdv_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9597,466,"MLI","Mali","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MLI/mli_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9598,470,"MLT","Malta","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MLT/mlt_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9599,474,"MTQ","Martinique","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MTQ/mtq_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9600,478,"MRT","Mauritania","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MRT/mrt_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9601,480,"MUS","Mauritius","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MUS/mus_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9602,484,"MEX","Mexico","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MEX/mex_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9603,492,"MCO","Monaco","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MCO/mco_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9604,496,"MNG","Mongolia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MNG/mng_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9605,498,"MDA","Moldova","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MDA/mda_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9606,499,"MNE","Montenegro","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MNE/mne_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9607,500,"MSR","Montserrat","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MSR/msr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9608,504,"MAR","Morocco","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MAR/mar_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9609,508,"MOZ","Mozambique","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MOZ/moz_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9610,512,"OMN","Oman","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/OMN/omn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9611,516,"NAM","Namibia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NAM/nam_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9612,520,"NRU","Nauru","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NRU/nru_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9613,524,"NPL","Nepal","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NPL/npl_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9614,528,"NLD","Netherlands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NLD/nld_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9615,531,"CUW","Curacao","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CUW/cuw_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9616,533,"ABW","Aruba","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ABW/abw_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9617,534,"SXM","Sint Maarten (Dutch part)","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SXM/sxm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9618,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BES/bes_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9619,540,"NCL","New Caledonia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NCL/ncl_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9620,548,"VUT","Vanuatu","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/VUT/vut_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9621,554,"NZL","New Zealand","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NZL/nzl_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9622,558,"NIC","Nicaragua","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NIC/nic_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9623,562,"NER","Niger","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NER/ner_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9624,566,"NGA","Nigeria","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NGA/nga_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9625,570,"NIU","Niue","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NIU/niu_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9626,574,"NFK","Norfolk Island","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NFK/nfk_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9627,578,"NOR","Norway","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/NOR/nor_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9628,580,"MNP","Northern Mariana Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MNP/mnp_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9629,581,"UMI","United States Minor Outlying Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/UMI/umi_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9630,583,"FSM","Micronesia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/FSM/fsm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9631,584,"MHL","Marshall Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MHL/mhl_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9632,585,"PLW","Palau","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PLW/plw_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9633,586,"PAK","Pakistan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PAK/pak_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9634,591,"PAN","Panama","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PAN/pan_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9635,598,"PNG","Papua New Guinea","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PNG/png_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9636,600,"PRY","Paraguay","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PRY/pry_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9637,604,"PER","Peru","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PER/per_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9638,608,"PHL","Philippines","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PHL/phl_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9639,612,"PCN","Pitcairn Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PCN/pcn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9640,616,"POL","Poland","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/POL/pol_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9641,620,"PRT","Portugal","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PRT/prt_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9642,624,"GNB","Guinea-Bissau","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GNB/gnb_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9643,626,"TLS","East Timor","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TLS/tls_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9644,630,"PRI","Puerto Rico","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/PRI/pri_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9645,634,"QAT","Qatar","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/QAT/qat_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9646,638,"REU","Reunion","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/REU/reu_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9647,642,"ROU","Romania","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ROU/rou_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9648,646,"RWA","Rwanda","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/RWA/rwa_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9649,652,"BLM","Saint Barthelemy","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BLM/blm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9650,654,"SHN","Saint Helena","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SHN/shn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9651,659,"KNA","Saint Kitts and Nevis","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/KNA/kna_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9652,660,"AIA","Anguilla","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/AIA/aia_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9653,662,"LCA","Saint Lucia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/LCA/lca_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9654,663,"MAF","Saint Martin (French part)","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MAF/maf_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9655,666,"SPM","Saint Pierre and Miquelon","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SPM/spm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9656,670,"VCT","Saint Vincent and the Grenadines","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/VCT/vct_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9657,674,"SMR","San Marino","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SMR/smr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9658,678,"STP","Sao Tome and Principe","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/STP/stp_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9659,682,"SAU","Saudi Arabia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SAU/sau_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9660,686,"SEN","Senegal","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SEN/sen_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9661,688,"SRB","Serbia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SRB/srb_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9662,690,"SYC","Seychelles","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SYC/syc_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9663,694,"SLE","Sierra Leone","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SLE/sle_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9664,702,"SGP","Singapore","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SGP/sgp_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9665,703,"SVK","Slovakia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SVK/svk_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9666,704,"VNM","Vietnam","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/VNM/vnm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9667,705,"SVN","Slovenia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SVN/svn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9668,706,"SOM","Somalia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SOM/som_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9669,710,"ZAF","South Africa","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ZAF/zaf_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9670,716,"ZWE","Zimbabwe","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ZWE/zwe_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9671,724,"ESP","Spain","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ESP/esp_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9672,728,"SSD","South Sudan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SSD/ssd_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9673,729,"SDN","Sudan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SDN/sdn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9674,732,"ESH","Western Sahara","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ESH/esh_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9675,740,"SUR","Suriname","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SUR/sur_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9676,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SJM/sjm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9677,748,"SWZ","Swaziland","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SWZ/swz_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9678,752,"SWE","Sweden","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SWE/swe_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9679,756,"CHE","Switzerland","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/CHE/che_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9680,760,"SYR","Syria","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SYR/syr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9681,762,"TJK","Tajikistan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TJK/tjk_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9682,764,"THA","Thailand","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/THA/tha_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9683,768,"TGO","Togo","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TGO/tgo_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9684,772,"TKL","Tokelau","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TKL/tkl_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9685,776,"TON","Tonga","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TON/ton_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9686,780,"TTO","Trinidad and Tobago","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TTO/tto_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9687,784,"ARE","United Arab Emirates","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ARE/are_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9688,788,"TUN","Tunisia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TUN/tun_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9689,792,"TUR","Turkey","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TUR/tur_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9690,795,"TKM","Turkmenistan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TKM/tkm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9691,796,"TCA","Turks and Caicos Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TCA/tca_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9692,798,"TUV","Tuvalu","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TUV/tuv_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9693,800,"UGA","Uganda","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/UGA/uga_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9694,804,"UKR","Ukraine","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/UKR/ukr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9695,807,"MKD","Macedonia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/MKD/mkd_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9696,818,"EGY","Egypt","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/EGY/egy_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9697,826,"GBR","United Kingdom","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GBR/gbr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9698,831,"GGY","Guernsey","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/GGY/ggy_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9699,832,"JEY","Jersey","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/JEY/jey_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9700,833,"IMN","Isle of Man","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/IMN/imn_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9701,834,"TZA","Tanzania","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/TZA/tza_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9702,854,"BFA","Burkina Faso","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/BFA/bfa_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9703,858,"URY","Uruguay","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/URY/ury_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9704,860,"UZB","Uzbekistan","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/UZB/uzb_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9705,862,"VEN","Venezuela","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/VEN/ven_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9706,876,"WLF","Wallis and Futuna","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/WLF/wlf_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9707,882,"WSM","Samoa","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/WSM/wsm_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9708,887,"YEM","Yemen","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/YEM/yem_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9709,894,"ZMB","Zambia","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/ZMB/zmb_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9710,900,"KOS","Kosovo","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/KOS/kos_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9711,901,"SPR","Spratly Islands","ppp_2017_UNadj","GIS/Population/Global_2000_2020/2017/SPR/spr_ppp_2017_UNadj.tif","Estimated total number of people per grid-cell 2017 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9712,643,"RUS","Russia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/RUS/rus_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9713,360,"IDN","Indonesia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/IDN/idn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9714,840,"USA","United States","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/USA/usa_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9715,850,"VIR","Virgin_Islands_U_S","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/VIR/vir_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9716,304,"GRL","Greenland","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GRL/grl_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9717,156,"CHN","China","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CHN/chn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9718,36,"AUS","Australia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/AUS/aus_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9719,76,"BRA","Brazil","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BRA/bra_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9720,124,"CAN","Canada","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CAN/can_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9721,152,"CHL","Chile","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CHL/chl_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9722,4,"AFG","Afghanistan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/AFG/afg_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9723,8,"ALB","Albania","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ALB/alb_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9724,10,"ATA","Antarctica","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ATA/ata_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9725,12,"DZA","Algeria","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/DZA/dza_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9726,16,"ASM","American Samoa","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ASM/asm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9727,20,"AND","Andorra","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/AND/and_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9728,24,"AGO","Angola","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/AGO/ago_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9729,28,"ATG","Antigua and Barbuda","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ATG/atg_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9730,31,"AZE","Azerbaijan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/AZE/aze_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9731,32,"ARG","Argentina","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ARG/arg_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9732,40,"AUT","Austria","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/AUT/aut_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9733,44,"BHS","Bahamas","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BHS/bhs_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9734,48,"BHR","Bahrain","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BHR/bhr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9735,50,"BGD","Bangladesh","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BGD/bgd_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9736,51,"ARM","Armenia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ARM/arm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9737,52,"BRB","Barbados","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BRB/brb_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9738,56,"BEL","Belgium","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BEL/bel_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9739,60,"BMU","Bermuda","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BMU/bmu_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9740,64,"BTN","Bhutan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BTN/btn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9741,68,"BOL","Bolivia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BOL/bol_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9742,70,"BIH","Bosnia and Herzegovina","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BIH/bih_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9743,72,"BWA","Botswana","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BWA/bwa_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9744,74,"BVT","Bouvet Island","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BVT/bvt_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9745,84,"BLZ","Belize","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BLZ/blz_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9746,86,"IOT","British Indian Ocean Territory","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/IOT/iot_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9747,90,"SLB","Solomon Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SLB/slb_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9748,92,"VGB","British Virgin Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/VGB/vgb_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9749,96,"BRN","Brunei","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BRN/brn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9750,100,"BGR","Bulgaria","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BGR/bgr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9751,104,"MMR","Myanmar","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MMR/mmr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9752,108,"BDI","Burundi","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BDI/bdi_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9753,112,"BLR","Belarus","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BLR/blr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9754,116,"KHM","Cambodia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/KHM/khm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9755,120,"CMR","Cameroon","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CMR/cmr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9756,132,"CPV","Cape Verde","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CPV/cpv_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9757,136,"CYM","Cayman Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CYM/cym_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9758,140,"CAF","Central African Republic","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CAF/caf_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9759,144,"LKA","Sri Lanka","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LKA/lka_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9760,148,"TCD","Chad","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TCD/tcd_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9761,158,"TWN","Taiwan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TWN/twn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9762,170,"COL","Colombia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/COL/col_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9763,174,"COM","Comoros","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/COM/com_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9764,175,"MYT","Mayotte","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MYT/myt_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9765,178,"COG","Republic of Congo","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/COG/cog_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9766,180,"COD","Democratic Republic of the Congo","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/COD/cod_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9767,184,"COK","Cook Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/COK/cok_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9768,188,"CRI","Costa Rica","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CRI/cri_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9769,191,"HRV","Croatia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/HRV/hrv_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9770,192,"CUB","Cuba","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CUB/cub_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9771,196,"CYP","Cyprus","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CYP/cyp_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9772,203,"CZE","Czech Republic","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CZE/cze_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9773,204,"BEN","Benin","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BEN/ben_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9774,208,"DNK","Denmark","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/DNK/dnk_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9775,212,"DMA","Dominica","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/DMA/dma_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9776,214,"DOM","Dominican Republic","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/DOM/dom_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9777,218,"ECU","Ecuador","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ECU/ecu_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9778,222,"SLV","El Salvador","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SLV/slv_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9779,226,"GNQ","Equatorial Guinea","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GNQ/gnq_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9780,231,"ETH","Ethiopia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ETH/eth_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9781,232,"ERI","Eritrea","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ERI/eri_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9782,233,"EST","Estonia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/EST/est_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9783,234,"FRO","Faroe Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/FRO/fro_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9784,238,"FLK","Falkland Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/FLK/flk_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9785,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SGS/sgs_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9786,242,"FJI","Fiji","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/FJI/fji_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9787,246,"FIN","Finland","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/FIN/fin_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9788,248,"ALA","Aland Islands ","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ALA/ala_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9789,250,"FRA","France","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/FRA/fra_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9790,254,"GUF","French Guiana","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GUF/guf_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9791,258,"PYF","French Polynesia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PYF/pyf_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9792,260,"ATF","French Southern Territories","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ATF/atf_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9793,262,"DJI","Djibouti","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/DJI/dji_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9794,266,"GAB","Gabon","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GAB/gab_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9795,268,"GEO","Georgia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GEO/geo_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9796,270,"GMB","Gambia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GMB/gmb_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9797,275,"PSE","Palestina","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PSE/pse_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9798,276,"DEU","Germany","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/DEU/deu_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9799,288,"GHA","Ghana","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GHA/gha_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9800,292,"GIB","Gibraltar","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GIB/gib_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9801,296,"KIR","Kiribati","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/KIR/kir_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9802,300,"GRC","Greece","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GRC/grc_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9803,308,"GRD","Grenada","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GRD/grd_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9804,312,"GLP","Guadeloupe","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GLP/glp_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9805,316,"GUM","Guam","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GUM/gum_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9806,320,"GTM","Guatemala","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GTM/gtm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9807,324,"GIN","Guinea","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GIN/gin_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9808,328,"GUY","Guyana","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GUY/guy_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9809,332,"HTI","Haiti","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/HTI/hti_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9810,334,"HMD","Heard Island and McDonald Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/HMD/hmd_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9811,336,"VAT","Vatican City","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/VAT/vat_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9812,340,"HND","Honduras","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/HND/hnd_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9813,344,"HKG","Hong Kong","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/HKG/hkg_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9814,348,"HUN","Hungary","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/HUN/hun_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9815,352,"ISL","Iceland","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ISL/isl_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9816,356,"IND","India","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/IND/ind_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9817,364,"IRN","Iran","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/IRN/irn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9818,368,"IRQ","Iraq","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/IRQ/irq_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9819,372,"IRL","Ireland","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/IRL/irl_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9820,376,"ISR","Israel","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ISR/isr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9821,380,"ITA","Italy","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ITA/ita_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9822,384,"CIV","CIte dIvoire","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CIV/civ_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9823,388,"JAM","Jamaica","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/JAM/jam_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9824,392,"JPN","Japan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/JPN/jpn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9825,398,"KAZ","Kazakhstan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/KAZ/kaz_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9826,400,"JOR","Jordan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/JOR/jor_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9827,404,"KEN","Kenya","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/KEN/ken_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9828,408,"PRK","North Korea","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PRK/prk_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9829,410,"KOR","South Korea","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/KOR/kor_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9830,414,"KWT","Kuwait","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/KWT/kwt_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9831,417,"KGZ","Kyrgyzstan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/KGZ/kgz_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9832,418,"LAO","Laos","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LAO/lao_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9833,422,"LBN","Lebanon","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LBN/lbn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9834,426,"LSO","Lesotho","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LSO/lso_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9835,428,"LVA","Latvia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LVA/lva_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9836,430,"LBR","Liberia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LBR/lbr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9837,434,"LBY","Libya","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LBY/lby_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9838,438,"LIE","Liechtenstein","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LIE/lie_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9839,440,"LTU","Lithuania","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LTU/ltu_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9840,442,"LUX","Luxembourg","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LUX/lux_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9841,446,"MAC","Macao","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MAC/mac_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9842,450,"MDG","Madagascar","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MDG/mdg_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9843,454,"MWI","Malawi","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MWI/mwi_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9844,458,"MYS","Malaysia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MYS/mys_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9845,462,"MDV","Maldives","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MDV/mdv_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9846,466,"MLI","Mali","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MLI/mli_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9847,470,"MLT","Malta","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MLT/mlt_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9848,474,"MTQ","Martinique","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MTQ/mtq_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9849,478,"MRT","Mauritania","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MRT/mrt_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9850,480,"MUS","Mauritius","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MUS/mus_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9851,484,"MEX","Mexico","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MEX/mex_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9852,492,"MCO","Monaco","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MCO/mco_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9853,496,"MNG","Mongolia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MNG/mng_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9854,498,"MDA","Moldova","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MDA/mda_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9855,499,"MNE","Montenegro","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MNE/mne_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9856,500,"MSR","Montserrat","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MSR/msr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9857,504,"MAR","Morocco","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MAR/mar_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9858,508,"MOZ","Mozambique","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MOZ/moz_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9859,512,"OMN","Oman","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/OMN/omn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9860,516,"NAM","Namibia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NAM/nam_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9861,520,"NRU","Nauru","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NRU/nru_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9862,524,"NPL","Nepal","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NPL/npl_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9863,528,"NLD","Netherlands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NLD/nld_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9864,531,"CUW","Curacao","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CUW/cuw_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9865,533,"ABW","Aruba","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ABW/abw_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9866,534,"SXM","Sint Maarten (Dutch part)","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SXM/sxm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9867,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BES/bes_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9868,540,"NCL","New Caledonia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NCL/ncl_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9869,548,"VUT","Vanuatu","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/VUT/vut_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9870,554,"NZL","New Zealand","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NZL/nzl_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9871,558,"NIC","Nicaragua","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NIC/nic_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9872,562,"NER","Niger","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NER/ner_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9873,566,"NGA","Nigeria","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NGA/nga_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9874,570,"NIU","Niue","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NIU/niu_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9875,574,"NFK","Norfolk Island","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NFK/nfk_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9876,578,"NOR","Norway","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/NOR/nor_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9877,580,"MNP","Northern Mariana Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MNP/mnp_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9878,581,"UMI","United States Minor Outlying Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/UMI/umi_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9879,583,"FSM","Micronesia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/FSM/fsm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9880,584,"MHL","Marshall Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MHL/mhl_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9881,585,"PLW","Palau","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PLW/plw_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9882,586,"PAK","Pakistan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PAK/pak_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9883,591,"PAN","Panama","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PAN/pan_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9884,598,"PNG","Papua New Guinea","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PNG/png_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9885,600,"PRY","Paraguay","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PRY/pry_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9886,604,"PER","Peru","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PER/per_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9887,608,"PHL","Philippines","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PHL/phl_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9888,612,"PCN","Pitcairn Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PCN/pcn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9889,616,"POL","Poland","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/POL/pol_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9890,620,"PRT","Portugal","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PRT/prt_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9891,624,"GNB","Guinea-Bissau","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GNB/gnb_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9892,626,"TLS","East Timor","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TLS/tls_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9893,630,"PRI","Puerto Rico","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/PRI/pri_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9894,634,"QAT","Qatar","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/QAT/qat_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9895,638,"REU","Reunion","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/REU/reu_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9896,642,"ROU","Romania","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ROU/rou_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9897,646,"RWA","Rwanda","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/RWA/rwa_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9898,652,"BLM","Saint Barthelemy","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BLM/blm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9899,654,"SHN","Saint Helena","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SHN/shn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9900,659,"KNA","Saint Kitts and Nevis","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/KNA/kna_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9901,660,"AIA","Anguilla","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/AIA/aia_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9902,662,"LCA","Saint Lucia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/LCA/lca_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9903,663,"MAF","Saint Martin (French part)","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MAF/maf_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9904,666,"SPM","Saint Pierre and Miquelon","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SPM/spm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9905,670,"VCT","Saint Vincent and the Grenadines","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/VCT/vct_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9906,674,"SMR","San Marino","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SMR/smr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9907,678,"STP","Sao Tome and Principe","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/STP/stp_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9908,682,"SAU","Saudi Arabia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SAU/sau_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9909,686,"SEN","Senegal","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SEN/sen_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9910,688,"SRB","Serbia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SRB/srb_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9911,690,"SYC","Seychelles","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SYC/syc_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9912,694,"SLE","Sierra Leone","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SLE/sle_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9913,702,"SGP","Singapore","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SGP/sgp_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9914,703,"SVK","Slovakia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SVK/svk_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9915,704,"VNM","Vietnam","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/VNM/vnm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9916,705,"SVN","Slovenia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SVN/svn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9917,706,"SOM","Somalia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SOM/som_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9918,710,"ZAF","South Africa","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ZAF/zaf_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9919,716,"ZWE","Zimbabwe","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ZWE/zwe_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9920,724,"ESP","Spain","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ESP/esp_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9921,728,"SSD","South Sudan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SSD/ssd_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9922,729,"SDN","Sudan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SDN/sdn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9923,732,"ESH","Western Sahara","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ESH/esh_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9924,740,"SUR","Suriname","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SUR/sur_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9925,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SJM/sjm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9926,748,"SWZ","Swaziland","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SWZ/swz_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9927,752,"SWE","Sweden","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SWE/swe_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9928,756,"CHE","Switzerland","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/CHE/che_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9929,760,"SYR","Syria","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SYR/syr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9930,762,"TJK","Tajikistan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TJK/tjk_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9931,764,"THA","Thailand","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/THA/tha_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9932,768,"TGO","Togo","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TGO/tgo_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9933,772,"TKL","Tokelau","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TKL/tkl_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9934,776,"TON","Tonga","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TON/ton_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9935,780,"TTO","Trinidad and Tobago","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TTO/tto_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9936,784,"ARE","United Arab Emirates","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ARE/are_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9937,788,"TUN","Tunisia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TUN/tun_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9938,792,"TUR","Turkey","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TUR/tur_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9939,795,"TKM","Turkmenistan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TKM/tkm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9940,796,"TCA","Turks and Caicos Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TCA/tca_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9941,798,"TUV","Tuvalu","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TUV/tuv_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9942,800,"UGA","Uganda","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/UGA/uga_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9943,804,"UKR","Ukraine","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/UKR/ukr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9944,807,"MKD","Macedonia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/MKD/mkd_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9945,818,"EGY","Egypt","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/EGY/egy_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9946,826,"GBR","United Kingdom","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GBR/gbr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9947,831,"GGY","Guernsey","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/GGY/ggy_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9948,832,"JEY","Jersey","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/JEY/jey_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9949,833,"IMN","Isle of Man","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/IMN/imn_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9950,834,"TZA","Tanzania","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/TZA/tza_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9951,854,"BFA","Burkina Faso","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/BFA/bfa_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9952,858,"URY","Uruguay","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/URY/ury_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9953,860,"UZB","Uzbekistan","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/UZB/uzb_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9954,862,"VEN","Venezuela","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/VEN/ven_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9955,876,"WLF","Wallis and Futuna","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/WLF/wlf_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9956,882,"WSM","Samoa","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/WSM/wsm_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9957,887,"YEM","Yemen","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/YEM/yem_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9958,894,"ZMB","Zambia","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/ZMB/zmb_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9959,900,"KOS","Kosovo","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/KOS/kos_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9960,901,"SPR","Spratly Islands","ppp_2018_UNadj","GIS/Population/Global_2000_2020/2018/SPR/spr_ppp_2018_UNadj.tif","Estimated total number of people per grid-cell 2018 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9961,643,"RUS","Russia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/RUS/rus_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9962,360,"IDN","Indonesia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/IDN/idn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9963,840,"USA","United States","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/USA/usa_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9964,850,"VIR","Virgin_Islands_U_S","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/VIR/vir_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9965,304,"GRL","Greenland","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GRL/grl_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9966,156,"CHN","China","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CHN/chn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9967,36,"AUS","Australia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/AUS/aus_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9968,76,"BRA","Brazil","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BRA/bra_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9969,124,"CAN","Canada","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CAN/can_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9970,152,"CHL","Chile","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CHL/chl_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9971,4,"AFG","Afghanistan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/AFG/afg_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9972,8,"ALB","Albania","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ALB/alb_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9973,10,"ATA","Antarctica","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ATA/ata_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9974,12,"DZA","Algeria","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/DZA/dza_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9975,16,"ASM","American Samoa","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ASM/asm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9976,20,"AND","Andorra","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/AND/and_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9977,24,"AGO","Angola","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/AGO/ago_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9978,28,"ATG","Antigua and Barbuda","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ATG/atg_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9979,31,"AZE","Azerbaijan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/AZE/aze_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9980,32,"ARG","Argentina","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ARG/arg_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9981,40,"AUT","Austria","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/AUT/aut_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9982,44,"BHS","Bahamas","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BHS/bhs_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9983,48,"BHR","Bahrain","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BHR/bhr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9984,50,"BGD","Bangladesh","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BGD/bgd_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9985,51,"ARM","Armenia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ARM/arm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9986,52,"BRB","Barbados","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BRB/brb_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9987,56,"BEL","Belgium","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BEL/bel_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9988,60,"BMU","Bermuda","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BMU/bmu_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9989,64,"BTN","Bhutan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BTN/btn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9990,68,"BOL","Bolivia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BOL/bol_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9991,70,"BIH","Bosnia and Herzegovina","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BIH/bih_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9992,72,"BWA","Botswana","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BWA/bwa_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9993,74,"BVT","Bouvet Island","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BVT/bvt_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9994,84,"BLZ","Belize","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BLZ/blz_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9995,86,"IOT","British Indian Ocean Territory","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/IOT/iot_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9996,90,"SLB","Solomon Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SLB/slb_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9997,92,"VGB","British Virgin Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/VGB/vgb_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9998,96,"BRN","Brunei","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BRN/brn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
9999,100,"BGR","Bulgaria","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BGR/bgr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10000,104,"MMR","Myanmar","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MMR/mmr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10001,108,"BDI","Burundi","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BDI/bdi_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10002,112,"BLR","Belarus","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BLR/blr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10003,116,"KHM","Cambodia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/KHM/khm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10004,120,"CMR","Cameroon","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CMR/cmr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10005,132,"CPV","Cape Verde","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CPV/cpv_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10006,136,"CYM","Cayman Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CYM/cym_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10007,140,"CAF","Central African Republic","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CAF/caf_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10008,144,"LKA","Sri Lanka","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LKA/lka_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10009,148,"TCD","Chad","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TCD/tcd_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10010,158,"TWN","Taiwan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TWN/twn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10011,170,"COL","Colombia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/COL/col_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10012,174,"COM","Comoros","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/COM/com_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10013,175,"MYT","Mayotte","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MYT/myt_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10014,178,"COG","Republic of Congo","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/COG/cog_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10015,180,"COD","Democratic Republic of the Congo","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/COD/cod_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10016,184,"COK","Cook Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/COK/cok_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10017,188,"CRI","Costa Rica","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CRI/cri_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10018,191,"HRV","Croatia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/HRV/hrv_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10019,192,"CUB","Cuba","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CUB/cub_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10020,196,"CYP","Cyprus","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CYP/cyp_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10021,203,"CZE","Czech Republic","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CZE/cze_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10022,204,"BEN","Benin","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BEN/ben_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10023,208,"DNK","Denmark","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/DNK/dnk_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10024,212,"DMA","Dominica","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/DMA/dma_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10025,214,"DOM","Dominican Republic","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/DOM/dom_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10026,218,"ECU","Ecuador","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ECU/ecu_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10027,222,"SLV","El Salvador","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SLV/slv_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10028,226,"GNQ","Equatorial Guinea","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GNQ/gnq_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10029,231,"ETH","Ethiopia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ETH/eth_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10030,232,"ERI","Eritrea","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ERI/eri_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10031,233,"EST","Estonia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/EST/est_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10032,234,"FRO","Faroe Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/FRO/fro_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10033,238,"FLK","Falkland Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/FLK/flk_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10034,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SGS/sgs_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10035,242,"FJI","Fiji","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/FJI/fji_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10036,246,"FIN","Finland","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/FIN/fin_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10037,248,"ALA","Aland Islands ","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ALA/ala_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10038,250,"FRA","France","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/FRA/fra_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10039,254,"GUF","French Guiana","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GUF/guf_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10040,258,"PYF","French Polynesia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PYF/pyf_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10041,260,"ATF","French Southern Territories","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ATF/atf_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10042,262,"DJI","Djibouti","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/DJI/dji_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10043,266,"GAB","Gabon","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GAB/gab_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10044,268,"GEO","Georgia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GEO/geo_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10045,270,"GMB","Gambia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GMB/gmb_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10046,275,"PSE","Palestina","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PSE/pse_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10047,276,"DEU","Germany","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/DEU/deu_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10048,288,"GHA","Ghana","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GHA/gha_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10049,292,"GIB","Gibraltar","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GIB/gib_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10050,296,"KIR","Kiribati","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/KIR/kir_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10051,300,"GRC","Greece","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GRC/grc_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10052,308,"GRD","Grenada","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GRD/grd_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10053,312,"GLP","Guadeloupe","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GLP/glp_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10054,316,"GUM","Guam","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GUM/gum_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10055,320,"GTM","Guatemala","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GTM/gtm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10056,324,"GIN","Guinea","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GIN/gin_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10057,328,"GUY","Guyana","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GUY/guy_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10058,332,"HTI","Haiti","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/HTI/hti_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10059,334,"HMD","Heard Island and McDonald Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/HMD/hmd_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10060,336,"VAT","Vatican City","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/VAT/vat_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10061,340,"HND","Honduras","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/HND/hnd_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10062,344,"HKG","Hong Kong","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/HKG/hkg_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10063,348,"HUN","Hungary","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/HUN/hun_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10064,352,"ISL","Iceland","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ISL/isl_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10065,356,"IND","India","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/IND/ind_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10066,364,"IRN","Iran","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/IRN/irn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10067,368,"IRQ","Iraq","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/IRQ/irq_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10068,372,"IRL","Ireland","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/IRL/irl_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10069,376,"ISR","Israel","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ISR/isr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10070,380,"ITA","Italy","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ITA/ita_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10071,384,"CIV","CIte dIvoire","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CIV/civ_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10072,388,"JAM","Jamaica","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/JAM/jam_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10073,392,"JPN","Japan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/JPN/jpn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10074,398,"KAZ","Kazakhstan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/KAZ/kaz_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10075,400,"JOR","Jordan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/JOR/jor_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10076,404,"KEN","Kenya","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/KEN/ken_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10077,408,"PRK","North Korea","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PRK/prk_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10078,410,"KOR","South Korea","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/KOR/kor_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10079,414,"KWT","Kuwait","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/KWT/kwt_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10080,417,"KGZ","Kyrgyzstan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/KGZ/kgz_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10081,418,"LAO","Laos","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LAO/lao_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10082,422,"LBN","Lebanon","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LBN/lbn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10083,426,"LSO","Lesotho","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LSO/lso_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10084,428,"LVA","Latvia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LVA/lva_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10085,430,"LBR","Liberia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LBR/lbr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10086,434,"LBY","Libya","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LBY/lby_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10087,438,"LIE","Liechtenstein","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LIE/lie_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10088,440,"LTU","Lithuania","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LTU/ltu_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10089,442,"LUX","Luxembourg","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LUX/lux_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10090,446,"MAC","Macao","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MAC/mac_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10091,450,"MDG","Madagascar","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MDG/mdg_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10092,454,"MWI","Malawi","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MWI/mwi_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10093,458,"MYS","Malaysia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MYS/mys_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10094,462,"MDV","Maldives","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MDV/mdv_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10095,466,"MLI","Mali","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MLI/mli_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10096,470,"MLT","Malta","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MLT/mlt_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10097,474,"MTQ","Martinique","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MTQ/mtq_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10098,478,"MRT","Mauritania","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MRT/mrt_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10099,480,"MUS","Mauritius","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MUS/mus_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10100,484,"MEX","Mexico","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MEX/mex_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10101,492,"MCO","Monaco","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MCO/mco_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10102,496,"MNG","Mongolia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MNG/mng_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10103,498,"MDA","Moldova","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MDA/mda_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10104,499,"MNE","Montenegro","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MNE/mne_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10105,500,"MSR","Montserrat","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MSR/msr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10106,504,"MAR","Morocco","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MAR/mar_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10107,508,"MOZ","Mozambique","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MOZ/moz_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10108,512,"OMN","Oman","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/OMN/omn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10109,516,"NAM","Namibia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NAM/nam_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10110,520,"NRU","Nauru","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NRU/nru_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10111,524,"NPL","Nepal","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NPL/npl_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10112,528,"NLD","Netherlands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NLD/nld_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10113,531,"CUW","Curacao","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CUW/cuw_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10114,533,"ABW","Aruba","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ABW/abw_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10115,534,"SXM","Sint Maarten (Dutch part)","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SXM/sxm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10116,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BES/bes_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10117,540,"NCL","New Caledonia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NCL/ncl_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10118,548,"VUT","Vanuatu","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/VUT/vut_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10119,554,"NZL","New Zealand","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NZL/nzl_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10120,558,"NIC","Nicaragua","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NIC/nic_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10121,562,"NER","Niger","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NER/ner_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10122,566,"NGA","Nigeria","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NGA/nga_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10123,570,"NIU","Niue","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NIU/niu_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10124,574,"NFK","Norfolk Island","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NFK/nfk_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10125,578,"NOR","Norway","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/NOR/nor_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10126,580,"MNP","Northern Mariana Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MNP/mnp_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10127,581,"UMI","United States Minor Outlying Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/UMI/umi_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10128,583,"FSM","Micronesia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/FSM/fsm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10129,584,"MHL","Marshall Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MHL/mhl_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10130,585,"PLW","Palau","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PLW/plw_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10131,586,"PAK","Pakistan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PAK/pak_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10132,591,"PAN","Panama","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PAN/pan_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10133,598,"PNG","Papua New Guinea","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PNG/png_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10134,600,"PRY","Paraguay","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PRY/pry_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10135,604,"PER","Peru","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PER/per_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10136,608,"PHL","Philippines","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PHL/phl_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10137,612,"PCN","Pitcairn Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PCN/pcn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10138,616,"POL","Poland","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/POL/pol_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10139,620,"PRT","Portugal","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PRT/prt_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10140,624,"GNB","Guinea-Bissau","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GNB/gnb_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10141,626,"TLS","East Timor","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TLS/tls_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10142,630,"PRI","Puerto Rico","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/PRI/pri_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10143,634,"QAT","Qatar","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/QAT/qat_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10144,638,"REU","Reunion","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/REU/reu_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10145,642,"ROU","Romania","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ROU/rou_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10146,646,"RWA","Rwanda","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/RWA/rwa_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10147,652,"BLM","Saint Barthelemy","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BLM/blm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10148,654,"SHN","Saint Helena","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SHN/shn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10149,659,"KNA","Saint Kitts and Nevis","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/KNA/kna_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10150,660,"AIA","Anguilla","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/AIA/aia_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10151,662,"LCA","Saint Lucia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/LCA/lca_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10152,663,"MAF","Saint Martin (French part)","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MAF/maf_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10153,666,"SPM","Saint Pierre and Miquelon","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SPM/spm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10154,670,"VCT","Saint Vincent and the Grenadines","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/VCT/vct_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10155,674,"SMR","San Marino","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SMR/smr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10156,678,"STP","Sao Tome and Principe","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/STP/stp_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10157,682,"SAU","Saudi Arabia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SAU/sau_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10158,686,"SEN","Senegal","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SEN/sen_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10159,688,"SRB","Serbia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SRB/srb_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10160,690,"SYC","Seychelles","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SYC/syc_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10161,694,"SLE","Sierra Leone","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SLE/sle_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10162,702,"SGP","Singapore","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SGP/sgp_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10163,703,"SVK","Slovakia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SVK/svk_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10164,704,"VNM","Vietnam","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/VNM/vnm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10165,705,"SVN","Slovenia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SVN/svn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10166,706,"SOM","Somalia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SOM/som_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10167,710,"ZAF","South Africa","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ZAF/zaf_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10168,716,"ZWE","Zimbabwe","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ZWE/zwe_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10169,724,"ESP","Spain","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ESP/esp_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10170,728,"SSD","South Sudan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SSD/ssd_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10171,729,"SDN","Sudan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SDN/sdn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10172,732,"ESH","Western Sahara","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ESH/esh_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10173,740,"SUR","Suriname","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SUR/sur_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10174,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SJM/sjm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10175,748,"SWZ","Swaziland","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SWZ/swz_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10176,752,"SWE","Sweden","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SWE/swe_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10177,756,"CHE","Switzerland","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/CHE/che_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10178,760,"SYR","Syria","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SYR/syr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10179,762,"TJK","Tajikistan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TJK/tjk_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10180,764,"THA","Thailand","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/THA/tha_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10181,768,"TGO","Togo","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TGO/tgo_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10182,772,"TKL","Tokelau","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TKL/tkl_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10183,776,"TON","Tonga","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TON/ton_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10184,780,"TTO","Trinidad and Tobago","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TTO/tto_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10185,784,"ARE","United Arab Emirates","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ARE/are_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10186,788,"TUN","Tunisia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TUN/tun_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10187,792,"TUR","Turkey","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TUR/tur_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10188,795,"TKM","Turkmenistan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TKM/tkm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10189,796,"TCA","Turks and Caicos Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TCA/tca_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10190,798,"TUV","Tuvalu","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TUV/tuv_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10191,800,"UGA","Uganda","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/UGA/uga_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10192,804,"UKR","Ukraine","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/UKR/ukr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10193,807,"MKD","Macedonia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/MKD/mkd_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10194,818,"EGY","Egypt","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/EGY/egy_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10195,826,"GBR","United Kingdom","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GBR/gbr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10196,831,"GGY","Guernsey","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/GGY/ggy_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10197,832,"JEY","Jersey","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/JEY/jey_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10198,833,"IMN","Isle of Man","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/IMN/imn_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10199,834,"TZA","Tanzania","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/TZA/tza_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10200,854,"BFA","Burkina Faso","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/BFA/bfa_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10201,858,"URY","Uruguay","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/URY/ury_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10202,860,"UZB","Uzbekistan","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/UZB/uzb_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10203,862,"VEN","Venezuela","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/VEN/ven_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10204,876,"WLF","Wallis and Futuna","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/WLF/wlf_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10205,882,"WSM","Samoa","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/WSM/wsm_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10206,887,"YEM","Yemen","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/YEM/yem_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10207,894,"ZMB","Zambia","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/ZMB/zmb_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10208,900,"KOS","Kosovo","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/KOS/kos_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10209,901,"SPR","Spratly Islands","ppp_2019_UNadj","GIS/Population/Global_2000_2020/2019/SPR/spr_ppp_2019_UNadj.tif","Estimated total number of people per grid-cell 2019 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10210,643,"RUS","Russia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/RUS/rus_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10211,360,"IDN","Indonesia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/IDN/idn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10212,840,"USA","United States","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/USA/usa_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10213,850,"VIR","Virgin_Islands_U_S","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/VIR/vir_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10214,304,"GRL","Greenland","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GRL/grl_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10215,156,"CHN","China","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CHN/chn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10216,36,"AUS","Australia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/AUS/aus_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10217,76,"BRA","Brazil","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BRA/bra_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10218,124,"CAN","Canada","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CAN/can_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10219,152,"CHL","Chile","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CHL/chl_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10220,4,"AFG","Afghanistan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/AFG/afg_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10221,8,"ALB","Albania","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ALB/alb_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10222,10,"ATA","Antarctica","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ATA/ata_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10223,12,"DZA","Algeria","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/DZA/dza_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10224,16,"ASM","American Samoa","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ASM/asm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10225,20,"AND","Andorra","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/AND/and_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10226,24,"AGO","Angola","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/AGO/ago_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10227,28,"ATG","Antigua and Barbuda","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ATG/atg_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10228,31,"AZE","Azerbaijan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/AZE/aze_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10229,32,"ARG","Argentina","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ARG/arg_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10230,40,"AUT","Austria","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/AUT/aut_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10231,44,"BHS","Bahamas","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BHS/bhs_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10232,48,"BHR","Bahrain","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BHR/bhr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10233,50,"BGD","Bangladesh","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BGD/bgd_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10234,51,"ARM","Armenia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ARM/arm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10235,52,"BRB","Barbados","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BRB/brb_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10236,56,"BEL","Belgium","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BEL/bel_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10237,60,"BMU","Bermuda","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BMU/bmu_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10238,64,"BTN","Bhutan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BTN/btn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10239,68,"BOL","Bolivia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BOL/bol_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10240,70,"BIH","Bosnia and Herzegovina","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BIH/bih_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10241,72,"BWA","Botswana","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BWA/bwa_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10242,74,"BVT","Bouvet Island","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BVT/bvt_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10243,84,"BLZ","Belize","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BLZ/blz_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10244,86,"IOT","British Indian Ocean Territory","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/IOT/iot_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10245,90,"SLB","Solomon Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SLB/slb_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10246,92,"VGB","British Virgin Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/VGB/vgb_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10247,96,"BRN","Brunei","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BRN/brn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10248,100,"BGR","Bulgaria","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BGR/bgr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10249,104,"MMR","Myanmar","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MMR/mmr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10250,108,"BDI","Burundi","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BDI/bdi_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10251,112,"BLR","Belarus","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BLR/blr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10252,116,"KHM","Cambodia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/KHM/khm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10253,120,"CMR","Cameroon","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CMR/cmr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10254,132,"CPV","Cape Verde","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CPV/cpv_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10255,136,"CYM","Cayman Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CYM/cym_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10256,140,"CAF","Central African Republic","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CAF/caf_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10257,144,"LKA","Sri Lanka","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LKA/lka_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10258,148,"TCD","Chad","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TCD/tcd_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10259,158,"TWN","Taiwan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TWN/twn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10260,170,"COL","Colombia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/COL/col_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10261,174,"COM","Comoros","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/COM/com_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10262,175,"MYT","Mayotte","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MYT/myt_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10263,178,"COG","Republic of Congo","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/COG/cog_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10264,180,"COD","Democratic Republic of the Congo","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/COD/cod_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10265,184,"COK","Cook Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/COK/cok_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10266,188,"CRI","Costa Rica","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CRI/cri_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10267,191,"HRV","Croatia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/HRV/hrv_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10268,192,"CUB","Cuba","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CUB/cub_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10269,196,"CYP","Cyprus","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CYP/cyp_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10270,203,"CZE","Czech Republic","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CZE/cze_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10271,204,"BEN","Benin","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BEN/ben_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10272,208,"DNK","Denmark","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/DNK/dnk_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10273,212,"DMA","Dominica","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/DMA/dma_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10274,214,"DOM","Dominican Republic","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/DOM/dom_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10275,218,"ECU","Ecuador","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ECU/ecu_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10276,222,"SLV","El Salvador","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SLV/slv_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10277,226,"GNQ","Equatorial Guinea","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GNQ/gnq_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10278,231,"ETH","Ethiopia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ETH/eth_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10279,232,"ERI","Eritrea","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ERI/eri_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10280,233,"EST","Estonia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/EST/est_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10281,234,"FRO","Faroe Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/FRO/fro_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10282,238,"FLK","Falkland Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/FLK/flk_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10283,239,"SGS","South Georgia and the South Sandwich Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SGS/sgs_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10284,242,"FJI","Fiji","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/FJI/fji_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10285,246,"FIN","Finland","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/FIN/fin_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10286,248,"ALA","Aland Islands ","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ALA/ala_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10287,250,"FRA","France","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/FRA/fra_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10288,254,"GUF","French Guiana","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GUF/guf_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10289,258,"PYF","French Polynesia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PYF/pyf_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10290,260,"ATF","French Southern Territories","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ATF/atf_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10291,262,"DJI","Djibouti","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/DJI/dji_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10292,266,"GAB","Gabon","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GAB/gab_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10293,268,"GEO","Georgia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GEO/geo_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10294,270,"GMB","Gambia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GMB/gmb_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10295,275,"PSE","Palestina","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PSE/pse_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10296,276,"DEU","Germany","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/DEU/deu_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10297,288,"GHA","Ghana","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GHA/gha_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10298,292,"GIB","Gibraltar","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GIB/gib_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10299,296,"KIR","Kiribati","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/KIR/kir_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10300,300,"GRC","Greece","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GRC/grc_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10301,308,"GRD","Grenada","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GRD/grd_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10302,312,"GLP","Guadeloupe","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GLP/glp_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10303,316,"GUM","Guam","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GUM/gum_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10304,320,"GTM","Guatemala","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GTM/gtm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10305,324,"GIN","Guinea","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GIN/gin_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10306,328,"GUY","Guyana","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GUY/guy_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10307,332,"HTI","Haiti","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/HTI/hti_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10308,334,"HMD","Heard Island and McDonald Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/HMD/hmd_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10309,336,"VAT","Vatican City","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/VAT/vat_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10310,340,"HND","Honduras","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/HND/hnd_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10311,344,"HKG","Hong Kong","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/HKG/hkg_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10312,348,"HUN","Hungary","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/HUN/hun_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10313,352,"ISL","Iceland","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ISL/isl_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10314,356,"IND","India","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/IND/ind_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10315,364,"IRN","Iran","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/IRN/irn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10316,368,"IRQ","Iraq","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/IRQ/irq_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10317,372,"IRL","Ireland","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/IRL/irl_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10318,376,"ISR","Israel","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ISR/isr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10319,380,"ITA","Italy","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ITA/ita_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10320,384,"CIV","CIte dIvoire","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CIV/civ_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10321,388,"JAM","Jamaica","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/JAM/jam_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10322,392,"JPN","Japan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/JPN/jpn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10323,398,"KAZ","Kazakhstan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/KAZ/kaz_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10324,400,"JOR","Jordan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/JOR/jor_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10325,404,"KEN","Kenya","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/KEN/ken_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10326,408,"PRK","North Korea","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PRK/prk_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10327,410,"KOR","South Korea","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/KOR/kor_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10328,414,"KWT","Kuwait","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/KWT/kwt_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10329,417,"KGZ","Kyrgyzstan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/KGZ/kgz_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10330,418,"LAO","Laos","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LAO/lao_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10331,422,"LBN","Lebanon","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LBN/lbn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10332,426,"LSO","Lesotho","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LSO/lso_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10333,428,"LVA","Latvia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LVA/lva_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10334,430,"LBR","Liberia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LBR/lbr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10335,434,"LBY","Libya","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LBY/lby_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10336,438,"LIE","Liechtenstein","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LIE/lie_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10337,440,"LTU","Lithuania","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LTU/ltu_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10338,442,"LUX","Luxembourg","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LUX/lux_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10339,446,"MAC","Macao","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MAC/mac_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10340,450,"MDG","Madagascar","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MDG/mdg_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10341,454,"MWI","Malawi","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MWI/mwi_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10342,458,"MYS","Malaysia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MYS/mys_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10343,462,"MDV","Maldives","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MDV/mdv_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10344,466,"MLI","Mali","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MLI/mli_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10345,470,"MLT","Malta","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MLT/mlt_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10346,474,"MTQ","Martinique","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MTQ/mtq_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10347,478,"MRT","Mauritania","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MRT/mrt_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10348,480,"MUS","Mauritius","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MUS/mus_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10349,484,"MEX","Mexico","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MEX/mex_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10350,492,"MCO","Monaco","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MCO/mco_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10351,496,"MNG","Mongolia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MNG/mng_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10352,498,"MDA","Moldova","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MDA/mda_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10353,499,"MNE","Montenegro","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MNE/mne_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10354,500,"MSR","Montserrat","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MSR/msr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10355,504,"MAR","Morocco","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MAR/mar_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10356,508,"MOZ","Mozambique","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MOZ/moz_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10357,512,"OMN","Oman","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/OMN/omn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10358,516,"NAM","Namibia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NAM/nam_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10359,520,"NRU","Nauru","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NRU/nru_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10360,524,"NPL","Nepal","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NPL/npl_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10361,528,"NLD","Netherlands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NLD/nld_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10362,531,"CUW","Curacao","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CUW/cuw_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10363,533,"ABW","Aruba","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ABW/abw_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10364,534,"SXM","Sint Maarten (Dutch part)","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SXM/sxm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10365,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BES/bes_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10366,540,"NCL","New Caledonia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NCL/ncl_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10367,548,"VUT","Vanuatu","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/VUT/vut_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10368,554,"NZL","New Zealand","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NZL/nzl_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10369,558,"NIC","Nicaragua","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NIC/nic_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10370,562,"NER","Niger","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NER/ner_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10371,566,"NGA","Nigeria","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NGA/nga_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10372,570,"NIU","Niue","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NIU/niu_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10373,574,"NFK","Norfolk Island","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NFK/nfk_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10374,578,"NOR","Norway","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/NOR/nor_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10375,580,"MNP","Northern Mariana Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MNP/mnp_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10376,581,"UMI","United States Minor Outlying Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/UMI/umi_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10377,583,"FSM","Micronesia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/FSM/fsm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10378,584,"MHL","Marshall Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MHL/mhl_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10379,585,"PLW","Palau","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PLW/plw_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10380,586,"PAK","Pakistan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PAK/pak_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10381,591,"PAN","Panama","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PAN/pan_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10382,598,"PNG","Papua New Guinea","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PNG/png_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10383,600,"PRY","Paraguay","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PRY/pry_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10384,604,"PER","Peru","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PER/per_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10385,608,"PHL","Philippines","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PHL/phl_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10386,612,"PCN","Pitcairn Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PCN/pcn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10387,616,"POL","Poland","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/POL/pol_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10388,620,"PRT","Portugal","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PRT/prt_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10389,624,"GNB","Guinea-Bissau","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GNB/gnb_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10390,626,"TLS","East Timor","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TLS/tls_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10391,630,"PRI","Puerto Rico","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/PRI/pri_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10392,634,"QAT","Qatar","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/QAT/qat_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10393,638,"REU","Reunion","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/REU/reu_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10394,642,"ROU","Romania","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ROU/rou_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10395,646,"RWA","Rwanda","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/RWA/rwa_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10396,652,"BLM","Saint Barthelemy","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BLM/blm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10397,654,"SHN","Saint Helena","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SHN/shn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10398,659,"KNA","Saint Kitts and Nevis","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/KNA/kna_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10399,660,"AIA","Anguilla","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/AIA/aia_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10400,662,"LCA","Saint Lucia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/LCA/lca_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10401,663,"MAF","Saint Martin (French part)","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MAF/maf_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10402,666,"SPM","Saint Pierre and Miquelon","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SPM/spm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10403,670,"VCT","Saint Vincent and the Grenadines","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/VCT/vct_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10404,674,"SMR","San Marino","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SMR/smr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10405,678,"STP","Sao Tome and Principe","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/STP/stp_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10406,682,"SAU","Saudi Arabia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SAU/sau_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10407,686,"SEN","Senegal","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SEN/sen_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10408,688,"SRB","Serbia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SRB/srb_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10409,690,"SYC","Seychelles","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SYC/syc_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10410,694,"SLE","Sierra Leone","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SLE/sle_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10411,702,"SGP","Singapore","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SGP/sgp_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10412,703,"SVK","Slovakia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SVK/svk_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10413,704,"VNM","Vietnam","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/VNM/vnm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10414,705,"SVN","Slovenia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SVN/svn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10415,706,"SOM","Somalia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SOM/som_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10416,710,"ZAF","South Africa","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ZAF/zaf_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10417,716,"ZWE","Zimbabwe","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ZWE/zwe_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10418,724,"ESP","Spain","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ESP/esp_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10419,728,"SSD","South Sudan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SSD/ssd_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10420,729,"SDN","Sudan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SDN/sdn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10421,732,"ESH","Western Sahara","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ESH/esh_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10422,740,"SUR","Suriname","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SUR/sur_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10423,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SJM/sjm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10424,748,"SWZ","Swaziland","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SWZ/swz_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10425,752,"SWE","Sweden","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SWE/swe_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10426,756,"CHE","Switzerland","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/CHE/che_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10427,760,"SYR","Syria","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SYR/syr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10428,762,"TJK","Tajikistan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TJK/tjk_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10429,764,"THA","Thailand","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/THA/tha_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10430,768,"TGO","Togo","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TGO/tgo_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10431,772,"TKL","Tokelau","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TKL/tkl_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10432,776,"TON","Tonga","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TON/ton_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10433,780,"TTO","Trinidad and Tobago","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TTO/tto_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10434,784,"ARE","United Arab Emirates","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ARE/are_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10435,788,"TUN","Tunisia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TUN/tun_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10436,792,"TUR","Turkey","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TUR/tur_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10437,795,"TKM","Turkmenistan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TKM/tkm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10438,796,"TCA","Turks and Caicos Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TCA/tca_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10439,798,"TUV","Tuvalu","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TUV/tuv_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10440,800,"UGA","Uganda","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/UGA/uga_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10441,804,"UKR","Ukraine","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/UKR/ukr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10442,807,"MKD","Macedonia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/MKD/mkd_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10443,818,"EGY","Egypt","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/EGY/egy_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10444,826,"GBR","United Kingdom","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GBR/gbr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10445,831,"GGY","Guernsey","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/GGY/ggy_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10446,832,"JEY","Jersey","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/JEY/jey_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10447,833,"IMN","Isle of Man","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/IMN/imn_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10448,834,"TZA","Tanzania","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/TZA/tza_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10449,854,"BFA","Burkina Faso","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/BFA/bfa_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10450,858,"URY","Uruguay","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/URY/ury_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10451,860,"UZB","Uzbekistan","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/UZB/uzb_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10452,862,"VEN","Venezuela","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/VEN/ven_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10453,876,"WLF","Wallis and Futuna","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/WLF/wlf_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10454,882,"WSM","Samoa","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/WSM/wsm_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10455,887,"YEM","Yemen","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/YEM/yem_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10456,894,"ZMB","Zambia","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/ZMB/zmb_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10457,900,"KOS","Kosovo","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/KOS/kos_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10458,901,"SPR","Spratly Islands","ppp_2020_UNadj","GIS/Population/Global_2000_2020/2020/SPR/spr_ppp_2020_UNadj.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator)"
10459,643,"RUS","Russia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/RUS/rus_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10460,360,"IDN","Indonesia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IDN/idn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10461,840,"USA","United States","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/USA/usa_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10462,850,"VIR","Virgin_Islands_U_S","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VIR/vir_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10463,304,"GRL","Greenland","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GRL/grl_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10464,156,"CHN","China","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CHN/chn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10465,36,"AUS","Australia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AUS/aus_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10466,76,"BRA","Brazil","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BRA/bra_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10467,124,"CAN","Canada","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CAN/can_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10468,152,"CHL","Chile","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CHL/chl_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10469,4,"AFG","Afghanistan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AFG/afg_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10470,8,"ALB","Albania","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ALB/alb_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10471,12,"DZA","Algeria","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/DZA/dza_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10472,16,"ASM","American Samoa","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ASM/asm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10473,20,"AND","Andorra","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AND/and_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10474,24,"AGO","Angola","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/AGO/ago_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10475,28,"ATG","Antigua and Barbuda","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ATG/atg_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10476,31,"AZE","Azerbaijan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AZE/aze_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10477,32,"ARG","Argentina","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ARG/arg_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10478,40,"AUT","Austria","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AUT/aut_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10479,44,"BHS","Bahamas","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BHS/bhs_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10480,48,"BHR","Bahrain","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BHR/bhr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10481,50,"BGD","Bangladesh","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BGD/bgd_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10482,51,"ARM","Armenia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ARM/arm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10483,52,"BRB","Barbados","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BRB/brb_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10484,56,"BEL","Belgium","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BEL/bel_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10485,60,"BMU","Bermuda","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BMU/bmu_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10486,64,"BTN","Bhutan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BTN/btn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10487,68,"BOL","Bolivia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BOL/bol_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10488,70,"BIH","Bosnia and Herzegovina","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BIH/bih_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10489,72,"BWA","Botswana","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/BWA/bwa_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10490,84,"BLZ","Belize","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BLZ/blz_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10491,90,"SLB","Solomon Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SLB/slb_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10492,92,"VGB","British Virgin Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VGB/vgb_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10493,96,"BRN","Brunei","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BRN/brn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10494,100,"BGR","Bulgaria","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BGR/bgr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10495,104,"MMR","Myanmar","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MMR/mmr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10496,108,"BDI","Burundi","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/BDI/bdi_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10497,112,"BLR","Belarus","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BLR/blr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10498,116,"KHM","Cambodia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KHM/khm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10499,120,"CMR","Cameroon","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/CMR/cmr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10500,132,"CPV","Cape Verde","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/CPV/cpv_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10501,136,"CYM","Cayman Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CYM/cym_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10502,140,"CAF","Central African Republic","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/CAF/caf_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10503,144,"LKA","Sri Lanka","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LKA/lka_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10504,148,"TCD","Chad","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/TCD/tcd_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10505,158,"TWN","Taiwan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TWN/twn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10506,170,"COL","Colombia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/COL/col_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10507,174,"COM","Comoros","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/COM/com_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10508,175,"MYT","Mayotte","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MYT/myt_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10509,178,"COG","Republic of Congo","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/COG/cog_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10510,180,"COD","Democratic Republic of the Congo","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/COD/cod_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10511,184,"COK","Cook Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/COK/cok_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10512,188,"CRI","Costa Rica","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CRI/cri_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10513,191,"HRV","Croatia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/HRV/hrv_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10514,192,"CUB","Cuba","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CUB/cub_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10515,196,"CYP","Cyprus","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CYP/cyp_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10516,203,"CZE","Czech Republic","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CZE/cze_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10517,204,"BEN","Benin","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/BEN/ben_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10518,208,"DNK","Denmark","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/DNK/dnk_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10519,212,"DMA","Dominica","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/DMA/dma_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10520,214,"DOM","Dominican Republic","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/DOM/dom_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10521,218,"ECU","Ecuador","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ECU/ecu_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10522,222,"SLV","El Salvador","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SLV/slv_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10523,226,"GNQ","Equatorial Guinea","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GNQ/gnq_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10524,231,"ETH","Ethiopia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ETH/eth_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10525,232,"ERI","Eritrea","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ERI/eri_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10526,233,"EST","Estonia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/EST/est_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10527,234,"FRO","Faroe Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FRO/fro_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10528,238,"FLK","Falkland Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FLK/flk_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10529,242,"FJI","Fiji","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FJI/fji_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10530,246,"FIN","Finland","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FIN/fin_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10531,248,"ALA","Aland Islands ","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ALA/ala_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10532,250,"FRA","France","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FRA/fra_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10533,254,"GUF","French Guiana","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GUF/guf_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10534,258,"PYF","French Polynesia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PYF/pyf_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10535,262,"DJI","Djibouti","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/DJI/dji_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10536,266,"GAB","Gabon","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GAB/gab_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10537,268,"GEO","Georgia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GEO/geo_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10538,270,"GMB","Gambia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GMB/gmb_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10539,275,"PSE","Palestina","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PSE/pse_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10540,276,"DEU","Germany","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/DEU/deu_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10541,288,"GHA","Ghana","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GHA/gha_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10542,292,"GIB","Gibraltar","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GIB/gib_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10543,296,"KIR","Kiribati","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KIR/kir_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10544,300,"GRC","Greece","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GRC/grc_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10545,308,"GRD","Grenada","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GRD/grd_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10546,312,"GLP","Guadeloupe","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GLP/glp_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10547,316,"GUM","Guam","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GUM/gum_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10548,320,"GTM","Guatemala","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GTM/gtm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10549,324,"GIN","Guinea","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GIN/gin_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10550,328,"GUY","Guyana","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GUY/guy_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10551,332,"HTI","Haiti","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/HTI/hti_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10552,336,"VAT","Vatican City","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VAT/vat_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10553,340,"HND","Honduras","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/HND/hnd_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10554,344,"HKG","Hong Kong","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/HKG/hkg_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10555,348,"HUN","Hungary","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/HUN/hun_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10556,352,"ISL","Iceland","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ISL/isl_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10557,356,"IND","India","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IND/ind_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10558,364,"IRN","Iran","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IRN/irn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10559,368,"IRQ","Iraq","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IRQ/irq_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10560,372,"IRL","Ireland","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IRL/irl_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10561,376,"ISR","Israel","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ISR/isr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10562,380,"ITA","Italy","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ITA/ita_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10563,384,"CIV","CIte dIvoire","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/CIV/civ_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10564,388,"JAM","Jamaica","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/JAM/jam_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10565,392,"JPN","Japan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/JPN/jpn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10566,398,"KAZ","Kazakhstan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KAZ/kaz_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10567,400,"JOR","Jordan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/JOR/jor_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10568,404,"KEN","Kenya","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/KEN/ken_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10569,408,"PRK","North Korea","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PRK/prk_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10570,410,"KOR","South Korea","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KOR/kor_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10571,414,"KWT","Kuwait","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KWT/kwt_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10572,417,"KGZ","Kyrgyzstan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KGZ/kgz_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10573,418,"LAO","Laos","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LAO/lao_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10574,422,"LBN","Lebanon","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LBN/lbn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10575,426,"LSO","Lesotho","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/LSO/lso_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10576,428,"LVA","Latvia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LVA/lva_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10577,430,"LBR","Liberia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/LBR/lbr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10578,434,"LBY","Libya","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LBY/lby_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10579,438,"LIE","Liechtenstein","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LIE/lie_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10580,440,"LTU","Lithuania","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LTU/ltu_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10581,442,"LUX","Luxembourg","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LUX/lux_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10582,446,"MAC","Macao","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MAC/mac_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10583,450,"MDG","Madagascar","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MDG/mdg_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10584,454,"MWI","Malawi","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MWI/mwi_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10585,458,"MYS","Malaysia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MYS/mys_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10586,462,"MDV","Maldives","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MDV/mdv_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10587,466,"MLI","Mali","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MLI/mli_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10588,470,"MLT","Malta","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MLT/mlt_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10589,474,"MTQ","Martinique","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MTQ/mtq_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10590,478,"MRT","Mauritania","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MRT/mrt_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10591,480,"MUS","Mauritius","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MUS/mus_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10592,484,"MEX","Mexico","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MEX/mex_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10593,492,"MCO","Monaco","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MCO/mco_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10594,496,"MNG","Mongolia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MNG/mng_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10595,498,"MDA","Moldova","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MDA/mda_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10596,499,"MNE","Montenegro","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MNE/mne_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10597,500,"MSR","Montserrat","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MSR/msr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10598,504,"MAR","Morocco","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MAR/mar_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10599,508,"MOZ","Mozambique","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MOZ/moz_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10600,512,"OMN","Oman","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/OMN/omn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10601,516,"NAM","Namibia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/NAM/nam_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10602,520,"NRU","Nauru","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NRU/nru_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10603,524,"NPL","Nepal","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NPL/npl_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10604,528,"NLD","Netherlands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NLD/nld_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10605,531,"CUW","Curacao","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CUW/cuw_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10606,533,"ABW","Aruba","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ABW/abw_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10607,534,"SXM","Sint Maarten (Dutch part)","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SXM/sxm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10608,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BES/bes_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10609,540,"NCL","New Caledonia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NCL/ncl_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10610,548,"VUT","Vanuatu","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VUT/vut_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10611,554,"NZL","New Zealand","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NZL/nzl_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10612,558,"NIC","Nicaragua","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NIC/nic_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10613,562,"NER","Niger","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/NER/ner_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10614,566,"NGA","Nigeria","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/NGA/nga_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10615,570,"NIU","Niue","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NIU/niu_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10616,574,"NFK","Norfolk Island","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NFK/nfk_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10617,578,"NOR","Norway","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NOR/nor_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10618,580,"MNP","Northern Mariana Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MNP/mnp_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10619,583,"FSM","Micronesia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FSM/fsm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10620,584,"MHL","Marshall Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MHL/mhl_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10621,585,"PLW","Palau","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PLW/plw_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10622,586,"PAK","Pakistan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PAK/pak_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10623,591,"PAN","Panama","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PAN/pan_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10624,598,"PNG","Papua New Guinea","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PNG/png_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10625,600,"PRY","Paraguay","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PRY/pry_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10626,604,"PER","Peru","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PER/per_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10627,608,"PHL","Philippines","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PHL/phl_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10628,612,"PCN","Pitcairn Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PCN/pcn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10629,616,"POL","Poland","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/POL/pol_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10630,620,"PRT","Portugal","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PRT/prt_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10631,624,"GNB","Guinea-Bissau","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GNB/gnb_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10632,626,"TLS","East Timor","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TLS/tls_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10633,630,"PRI","Puerto Rico","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PRI/pri_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10634,634,"QAT","Qatar","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/QAT/qat_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10635,638,"REU","Reunion","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/REU/reu_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10636,642,"ROU","Romania","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ROU/rou_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10637,646,"RWA","Rwanda","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/RWA/rwa_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10638,652,"BLM","Saint Barthelemy","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BLM/blm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10639,654,"SHN","Saint Helena","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SHN/shn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10640,659,"KNA","Saint Kitts and Nevis","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KNA/kna_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10641,660,"AIA","Anguilla","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AIA/aia_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10642,662,"LCA","Saint Lucia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LCA/lca_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10643,663,"MAF","Saint Martin (French part)","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MAF/maf_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10644,666,"SPM","Saint Pierre and Miquelon","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SPM/spm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10645,670,"VCT","Saint Vincent and the Grenadines","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VCT/vct_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10646,674,"SMR","San Marino","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SMR/smr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10647,678,"STP","Sao Tome and Principe","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/STP/stp_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10648,682,"SAU","Saudi Arabia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SAU/sau_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10649,686,"SEN","Senegal","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SEN/sen_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10650,688,"SRB","Serbia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SRB/srb_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10651,690,"SYC","Seychelles","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SYC/syc_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10652,694,"SLE","Sierra Leone","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SLE/sle_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10653,702,"SGP","Singapore","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SGP/sgp_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10654,703,"SVK","Slovakia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SVK/svk_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10655,704,"VNM","Vietnam","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VNM/vnm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10656,705,"SVN","Slovenia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SVN/svn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10657,706,"SOM","Somalia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SOM/som_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10658,710,"ZAF","South Africa","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ZAF/zaf_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10659,716,"ZWE","Zimbabwe","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ZWE/zwe_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10660,724,"ESP","Spain","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ESP/esp_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10661,728,"SSD","South Sudan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SSD/ssd_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10662,729,"SDN","Sudan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SDN/sdn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10663,732,"ESH","Western Sahara","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ESH/esh_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10664,740,"SUR","Suriname","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SUR/sur_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10665,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SJM/sjm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10666,748,"SWZ","Swaziland","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SWZ/swz_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10667,752,"SWE","Sweden","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SWE/swe_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10668,756,"CHE","Switzerland","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CHE/che_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10669,760,"SYR","Syria","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SYR/syr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10670,762,"TJK","Tajikistan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TJK/tjk_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10671,764,"THA","Thailand","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/THA/tha_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10672,768,"TGO","Togo","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/TGO/tgo_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10673,772,"TKL","Tokelau","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TKL/tkl_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10674,776,"TON","Tonga","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TON/ton_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10675,780,"TTO","Trinidad and Tobago","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TTO/tto_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10676,784,"ARE","United Arab Emirates","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ARE/are_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10677,788,"TUN","Tunisia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TUN/tun_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10678,792,"TUR","Turkey","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TUR/tur_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10679,795,"TKM","Turkmenistan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TKM/tkm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10680,796,"TCA","Turks and Caicos Islands","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TCA/tca_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10681,798,"TUV","Tuvalu","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TUV/tuv_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10682,800,"UGA","Uganda","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/UGA/uga_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10683,804,"UKR","Ukraine","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/UKR/ukr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10684,807,"MKD","Macedonia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MKD/mkd_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10685,818,"EGY","Egypt","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/EGY/egy_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10686,826,"GBR","United Kingdom","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GBR/gbr_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10687,831,"GGY","Guernsey","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GGY/ggy_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10688,832,"JEY","Jersey","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/JEY/jey_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10689,833,"IMN","Isle of Man","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IMN/imn_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10690,834,"TZA","Tanzania","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/TZA/tza_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10691,854,"BFA","Burkina Faso","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/BFA/bfa_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10692,858,"URY","Uruguay","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/URY/ury_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10693,860,"UZB","Uzbekistan","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/UZB/uzb_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10694,862,"VEN","Venezuela","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VEN/ven_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10695,876,"WLF","Wallis and Futuna","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/WLF/wlf_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10696,882,"WSM","Samoa","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/WSM/wsm_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10697,887,"YEM","Yemen","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/YEM/yem_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10698,894,"ZMB","Zambia","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ZMB/zmb_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10699,900,"KOS","Kosovo","ppp_2020_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KOS/kos_ppp_2020_constrained.tif","Estimated total number of people per grid-cell 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10700,643,"RUS","Russia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/RUS/rus_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10701,360,"IDN","Indonesia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IDN/idn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10702,840,"USA","United States","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/USA/usa_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10703,850,"VIR","Virgin_Islands_U_S","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VIR/vir_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10704,304,"GRL","Greenland","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GRL/grl_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10705,156,"CHN","China","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CHN/chn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10706,36,"AUS","Australia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AUS/aus_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10707,76,"BRA","Brazil","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BRA/bra_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10708,124,"CAN","Canada","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CAN/can_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10709,152,"CHL","Chile","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CHL/chl_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10710,4,"AFG","Afghanistan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AFG/afg_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10711,8,"ALB","Albania","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ALB/alb_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10712,12,"DZA","Algeria","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/DZA/dza_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10713,16,"ASM","American Samoa","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ASM/asm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10714,20,"AND","Andorra","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AND/and_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10715,24,"AGO","Angola","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/AGO/ago_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10716,28,"ATG","Antigua and Barbuda","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ATG/atg_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10717,31,"AZE","Azerbaijan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AZE/aze_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10718,32,"ARG","Argentina","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ARG/arg_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10719,40,"AUT","Austria","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AUT/aut_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10720,44,"BHS","Bahamas","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BHS/bhs_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10721,48,"BHR","Bahrain","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BHR/bhr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10722,50,"BGD","Bangladesh","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BGD/bgd_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10723,51,"ARM","Armenia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ARM/arm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10724,52,"BRB","Barbados","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BRB/brb_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10725,56,"BEL","Belgium","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BEL/bel_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10726,60,"BMU","Bermuda","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BMU/bmu_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10727,64,"BTN","Bhutan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BTN/btn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10728,68,"BOL","Bolivia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BOL/bol_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10729,70,"BIH","Bosnia and Herzegovina","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BIH/bih_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10730,72,"BWA","Botswana","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/BWA/bwa_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10731,84,"BLZ","Belize","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BLZ/blz_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10732,90,"SLB","Solomon Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SLB/slb_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10733,92,"VGB","British Virgin Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VGB/vgb_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10734,96,"BRN","Brunei","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BRN/brn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10735,100,"BGR","Bulgaria","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BGR/bgr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10736,104,"MMR","Myanmar","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MMR/mmr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10737,108,"BDI","Burundi","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/BDI/bdi_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10738,112,"BLR","Belarus","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BLR/blr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10739,116,"KHM","Cambodia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KHM/khm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10740,120,"CMR","Cameroon","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/CMR/cmr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10741,132,"CPV","Cape Verde","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/CPV/cpv_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10742,136,"CYM","Cayman Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CYM/cym_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10743,140,"CAF","Central African Republic","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/CAF/caf_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10744,144,"LKA","Sri Lanka","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LKA/lka_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10745,148,"TCD","Chad","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/TCD/tcd_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10746,158,"TWN","Taiwan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TWN/twn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10747,170,"COL","Colombia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/COL/col_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10748,174,"COM","Comoros","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/COM/com_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10749,175,"MYT","Mayotte","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MYT/myt_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10750,178,"COG","Republic of Congo","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/COG/cog_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10751,180,"COD","Democratic Republic of the Congo","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/COD/cod_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10752,184,"COK","Cook Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/COK/cok_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10753,188,"CRI","Costa Rica","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CRI/cri_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10754,191,"HRV","Croatia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/HRV/hrv_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10755,192,"CUB","Cuba","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CUB/cub_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10756,196,"CYP","Cyprus","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CYP/cyp_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10757,203,"CZE","Czech Republic","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CZE/cze_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10758,204,"BEN","Benin","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/BEN/ben_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10759,208,"DNK","Denmark","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/DNK/dnk_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10760,212,"DMA","Dominica","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/DMA/dma_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10761,214,"DOM","Dominican Republic","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/DOM/dom_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10762,218,"ECU","Ecuador","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ECU/ecu_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10763,222,"SLV","El Salvador","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SLV/slv_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10764,226,"GNQ","Equatorial Guinea","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GNQ/gnq_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10765,231,"ETH","Ethiopia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ETH/eth_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10766,232,"ERI","Eritrea","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ERI/eri_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10767,233,"EST","Estonia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/EST/est_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10768,234,"FRO","Faroe Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FRO/fro_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10769,238,"FLK","Falkland Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FLK/flk_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10770,242,"FJI","Fiji","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FJI/fji_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10771,246,"FIN","Finland","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FIN/fin_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10772,248,"ALA","Aland Islands ","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ALA/ala_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10773,250,"FRA","France","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FRA/fra_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10774,254,"GUF","French Guiana","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GUF/guf_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10775,258,"PYF","French Polynesia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PYF/pyf_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10776,262,"DJI","Djibouti","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/DJI/dji_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10777,266,"GAB","Gabon","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GAB/gab_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10778,268,"GEO","Georgia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GEO/geo_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10779,270,"GMB","Gambia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GMB/gmb_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10780,275,"PSE","Palestina","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PSE/pse_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10781,276,"DEU","Germany","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/DEU/deu_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10782,288,"GHA","Ghana","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GHA/gha_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10783,292,"GIB","Gibraltar","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GIB/gib_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10784,296,"KIR","Kiribati","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KIR/kir_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10785,300,"GRC","Greece","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GRC/grc_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10786,308,"GRD","Grenada","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GRD/grd_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10787,312,"GLP","Guadeloupe","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GLP/glp_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10788,316,"GUM","Guam","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GUM/gum_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10789,320,"GTM","Guatemala","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GTM/gtm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10790,324,"GIN","Guinea","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GIN/gin_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10791,328,"GUY","Guyana","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GUY/guy_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10792,332,"HTI","Haiti","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/HTI/hti_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10793,336,"VAT","Vatican City","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VAT/vat_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10794,340,"HND","Honduras","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/HND/hnd_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10795,344,"HKG","Hong Kong","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/HKG/hkg_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10796,348,"HUN","Hungary","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/HUN/hun_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10797,352,"ISL","Iceland","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ISL/isl_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10798,356,"IND","India","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IND/ind_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10799,364,"IRN","Iran","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IRN/irn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10800,368,"IRQ","Iraq","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IRQ/irq_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10801,372,"IRL","Ireland","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IRL/irl_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10802,376,"ISR","Israel","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ISR/isr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10803,380,"ITA","Italy","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ITA/ita_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10804,384,"CIV","CIte dIvoire","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/CIV/civ_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10805,388,"JAM","Jamaica","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/JAM/jam_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10806,392,"JPN","Japan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/JPN/jpn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10807,398,"KAZ","Kazakhstan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KAZ/kaz_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10808,400,"JOR","Jordan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/JOR/jor_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10809,404,"KEN","Kenya","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/KEN/ken_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10810,408,"PRK","North Korea","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PRK/prk_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10811,410,"KOR","South Korea","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KOR/kor_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10812,414,"KWT","Kuwait","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KWT/kwt_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10813,417,"KGZ","Kyrgyzstan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KGZ/kgz_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10814,418,"LAO","Laos","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LAO/lao_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10815,422,"LBN","Lebanon","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LBN/lbn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10816,426,"LSO","Lesotho","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/LSO/lso_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10817,428,"LVA","Latvia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LVA/lva_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10818,430,"LBR","Liberia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/LBR/lbr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10819,434,"LBY","Libya","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LBY/lby_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10820,438,"LIE","Liechtenstein","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LIE/lie_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10821,440,"LTU","Lithuania","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LTU/ltu_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10822,442,"LUX","Luxembourg","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LUX/lux_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10823,446,"MAC","Macao","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MAC/mac_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10824,450,"MDG","Madagascar","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MDG/mdg_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10825,454,"MWI","Malawi","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MWI/mwi_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10826,458,"MYS","Malaysia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MYS/mys_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10827,462,"MDV","Maldives","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MDV/mdv_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10828,466,"MLI","Mali","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MLI/mli_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10829,470,"MLT","Malta","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MLT/mlt_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10830,474,"MTQ","Martinique","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MTQ/mtq_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10831,478,"MRT","Mauritania","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MRT/mrt_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10832,480,"MUS","Mauritius","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MUS/mus_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10833,484,"MEX","Mexico","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MEX/mex_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10834,492,"MCO","Monaco","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MCO/mco_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10835,496,"MNG","Mongolia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MNG/mng_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10836,498,"MDA","Moldova","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MDA/mda_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10837,499,"MNE","Montenegro","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MNE/mne_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10838,500,"MSR","Montserrat","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MSR/msr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10839,504,"MAR","Morocco","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MAR/mar_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10840,508,"MOZ","Mozambique","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/MOZ/moz_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10841,512,"OMN","Oman","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/OMN/omn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10842,516,"NAM","Namibia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/NAM/nam_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10843,520,"NRU","Nauru","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NRU/nru_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10844,524,"NPL","Nepal","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NPL/npl_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10845,528,"NLD","Netherlands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NLD/nld_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10846,531,"CUW","Curacao","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CUW/cuw_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10847,533,"ABW","Aruba","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ABW/abw_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10848,534,"SXM","Sint Maarten (Dutch part)","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SXM/sxm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10849,535,"BES","Bonaire, Sint Eustatius and Saba","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BES/bes_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10850,540,"NCL","New Caledonia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NCL/ncl_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10851,548,"VUT","Vanuatu","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VUT/vut_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10852,554,"NZL","New Zealand","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NZL/nzl_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10853,558,"NIC","Nicaragua","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NIC/nic_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10854,562,"NER","Niger","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/NER/ner_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10855,566,"NGA","Nigeria","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/NGA/nga_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10856,570,"NIU","Niue","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NIU/niu_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10857,574,"NFK","Norfolk Island","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NFK/nfk_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10858,578,"NOR","Norway","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/NOR/nor_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10859,580,"MNP","Northern Mariana Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MNP/mnp_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10860,583,"FSM","Micronesia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/FSM/fsm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10861,584,"MHL","Marshall Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MHL/mhl_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10862,585,"PLW","Palau","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PLW/plw_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10863,586,"PAK","Pakistan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PAK/pak_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10864,591,"PAN","Panama","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PAN/pan_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10865,598,"PNG","Papua New Guinea","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PNG/png_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10866,600,"PRY","Paraguay","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PRY/pry_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10867,604,"PER","Peru","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PER/per_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10868,608,"PHL","Philippines","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PHL/phl_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10869,612,"PCN","Pitcairn Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PCN/pcn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10870,616,"POL","Poland","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/POL/pol_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10871,620,"PRT","Portugal","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PRT/prt_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10872,624,"GNB","Guinea-Bissau","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/GNB/gnb_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10873,626,"TLS","East Timor","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TLS/tls_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10874,630,"PRI","Puerto Rico","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/PRI/pri_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10875,634,"QAT","Qatar","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/QAT/qat_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10876,638,"REU","Reunion","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/REU/reu_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10877,642,"ROU","Romania","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ROU/rou_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10878,646,"RWA","Rwanda","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/RWA/rwa_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10879,652,"BLM","Saint Barthelemy","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/BLM/blm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10880,654,"SHN","Saint Helena","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SHN/shn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10881,659,"KNA","Saint Kitts and Nevis","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KNA/kna_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10882,660,"AIA","Anguilla","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/AIA/aia_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10883,662,"LCA","Saint Lucia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/LCA/lca_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10884,663,"MAF","Saint Martin (French part)","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MAF/maf_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10885,666,"SPM","Saint Pierre and Miquelon","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SPM/spm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10886,670,"VCT","Saint Vincent and the Grenadines","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VCT/vct_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10887,674,"SMR","San Marino","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SMR/smr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10888,678,"STP","Sao Tome and Principe","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/STP/stp_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10889,682,"SAU","Saudi Arabia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SAU/sau_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10890,686,"SEN","Senegal","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SEN/sen_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10891,688,"SRB","Serbia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SRB/srb_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10892,690,"SYC","Seychelles","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SYC/syc_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10893,694,"SLE","Sierra Leone","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SLE/sle_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10894,702,"SGP","Singapore","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SGP/sgp_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10895,703,"SVK","Slovakia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SVK/svk_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10896,704,"VNM","Vietnam","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VNM/vnm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10897,705,"SVN","Slovenia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SVN/svn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10898,706,"SOM","Somalia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SOM/som_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10899,710,"ZAF","South Africa","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ZAF/zaf_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10900,716,"ZWE","Zimbabwe","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ZWE/zwe_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10901,724,"ESP","Spain","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ESP/esp_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10902,728,"SSD","South Sudan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SSD/ssd_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10903,729,"SDN","Sudan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SDN/sdn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10904,732,"ESH","Western Sahara","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ESH/esh_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10905,740,"SUR","Suriname","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SUR/sur_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10906,744,"SJM","Svalbard and Jan Mayen Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SJM/sjm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10907,748,"SWZ","Swaziland","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/SWZ/swz_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10908,752,"SWE","Sweden","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SWE/swe_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10909,756,"CHE","Switzerland","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/CHE/che_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10910,760,"SYR","Syria","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/SYR/syr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10911,762,"TJK","Tajikistan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TJK/tjk_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10912,764,"THA","Thailand","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/THA/tha_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10913,768,"TGO","Togo","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/TGO/tgo_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10914,772,"TKL","Tokelau","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TKL/tkl_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10915,776,"TON","Tonga","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TON/ton_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10916,780,"TTO","Trinidad and Tobago","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TTO/tto_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10917,784,"ARE","United Arab Emirates","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/ARE/are_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10918,788,"TUN","Tunisia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TUN/tun_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10919,792,"TUR","Turkey","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TUR/tur_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10920,795,"TKM","Turkmenistan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TKM/tkm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10921,796,"TCA","Turks and Caicos Islands","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TCA/tca_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10922,798,"TUV","Tuvalu","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/TUV/tuv_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10923,800,"UGA","Uganda","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/UGA/uga_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10924,804,"UKR","Ukraine","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/UKR/ukr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10925,807,"MKD","Macedonia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/MKD/mkd_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10926,818,"EGY","Egypt","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/EGY/egy_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10927,826,"GBR","United Kingdom","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GBR/gbr_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10928,831,"GGY","Guernsey","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/GGY/ggy_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10929,832,"JEY","Jersey","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/JEY/jey_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10930,833,"IMN","Isle of Man","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/IMN/imn_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10931,834,"TZA","Tanzania","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/TZA/tza_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10932,854,"BFA","Burkina Faso","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/BFA/bfa_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10933,858,"URY","Uruguay","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/URY/ury_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10934,860,"UZB","Uzbekistan","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/UZB/uzb_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10935,862,"VEN","Venezuela","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/VEN/ven_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10936,876,"WLF","Wallis and Futuna","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/WLF/wlf_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10937,882,"WSM","Samoa","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/WSM/wsm_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10938,887,"YEM","Yemen","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/YEM/yem_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10939,894,"ZMB","Zambia","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/maxar_v1/ZMB/zmb_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
10940,900,"KOS","Kosovo","ppp_2020_UNadj_constrained","GIS/Population/Global_2000_2020_Constrained/2020/BSGM/KOS/kos_ppp_2020_UNadj_constrained.tif","Estimated total number of people per grid-cell 2020 with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The units are number of people per pixel. NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
10941,643,"RUS","Russia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/RUS/Accessibility/rus_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10942,840,"USA","United States","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/USA/Accessibility/usa_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10943,850,"VIR","Virgin_Islands_U_S","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/VIR/Accessibility/vir_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10944,304,"GRL","Greenland","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GRL/Accessibility/grl_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10945,156,"CHN","China","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CHN/Accessibility/chn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10946,36,"AUS","Australia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/AUS/Accessibility/aus_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10947,76,"BRA","Brazil","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BRA/Accessibility/bra_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10948,124,"CAN","Canada","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CAN/Accessibility/can_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10949,152,"CHL","Chile","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CHL/Accessibility/chl_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10950,4,"AFG","Afghanistan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/AFG/Accessibility/afg_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10951,8,"ALB","Albania","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ALB/Accessibility/alb_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10952,10,"ATA","Antarctica","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ATA/Accessibility/ata_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10953,12,"DZA","Algeria","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/DZA/Accessibility/dza_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10954,16,"ASM","American Samoa","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ASM/Accessibility/asm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10955,20,"AND","Andorra","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/AND/Accessibility/and_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10956,24,"AGO","Angola","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/AGO/Accessibility/ago_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10957,28,"ATG","Antigua and Barbuda","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ATG/Accessibility/atg_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10958,31,"AZE","Azerbaijan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/AZE/Accessibility/aze_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10959,32,"ARG","Argentina","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ARG/Accessibility/arg_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10960,40,"AUT","Austria","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/AUT/Accessibility/aut_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10961,44,"BHS","Bahamas","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BHS/Accessibility/bhs_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10962,48,"BHR","Bahrain","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BHR/Accessibility/bhr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10963,50,"BGD","Bangladesh","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BGD/Accessibility/bgd_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10964,51,"ARM","Armenia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ARM/Accessibility/arm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10965,52,"BRB","Barbados","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BRB/Accessibility/brb_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10966,56,"BEL","Belgium","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BEL/Accessibility/bel_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10967,60,"BMU","Bermuda","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BMU/Accessibility/bmu_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10968,64,"BTN","Bhutan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BTN/Accessibility/btn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10969,68,"BOL","Bolivia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BOL/Accessibility/bol_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10970,70,"BIH","Bosnia and Herzegovina","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BIH/Accessibility/bih_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10971,72,"BWA","Botswana","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BWA/Accessibility/bwa_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10972,74,"BVT","Bouvet Island","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BVT/Accessibility/bvt_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10973,84,"BLZ","Belize","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/Accessibility/blz_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10974,86,"IOT","British Indian Ocean Territory","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/IOT/Accessibility/iot_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10975,90,"SLB","Solomon Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SLB/Accessibility/slb_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10976,92,"VGB","British Virgin Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/VGB/Accessibility/vgb_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10977,96,"BRN","Brunei","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BRN/Accessibility/brn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10978,100,"BGR","Bulgaria","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BGR/Accessibility/bgr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10979,104,"MMR","Myanmar","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MMR/Accessibility/mmr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10980,108,"BDI","Burundi","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BDI/Accessibility/bdi_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10981,112,"BLR","Belarus","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BLR/Accessibility/blr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10982,116,"KHM","Cambodia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/KHM/Accessibility/khm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10983,120,"CMR","Cameroon","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CMR/Accessibility/cmr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10984,132,"CPV","Cape Verde","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CPV/Accessibility/cpv_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10985,136,"CYM","Cayman Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CYM/Accessibility/cym_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10986,140,"CAF","Central African Republic","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CAF/Accessibility/caf_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10987,144,"LKA","Sri Lanka","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LKA/Accessibility/lka_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10988,148,"TCD","Chad","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TCD/Accessibility/tcd_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10989,158,"TWN","Taiwan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TWN/Accessibility/twn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10990,170,"COL","Colombia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/COL/Accessibility/col_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10991,174,"COM","Comoros","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/COM/Accessibility/com_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10992,175,"MYT","Mayotte","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MYT/Accessibility/myt_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10993,178,"COG","Republic of Congo","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/COG/Accessibility/cog_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10994,180,"COD","Democratic Republic of the Congo","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/COD/Accessibility/cod_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10995,184,"COK","Cook Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/COK/Accessibility/cok_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10996,188,"CRI","Costa Rica","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CRI/Accessibility/cri_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10997,191,"HRV","Croatia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/HRV/Accessibility/hrv_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10998,192,"CUB","Cuba","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CUB/Accessibility/cub_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
10999,196,"CYP","Cyprus","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CYP/Accessibility/cyp_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11000,203,"CZE","Czech Republic","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CZE/Accessibility/cze_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11001,204,"BEN","Benin","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BEN/Accessibility/ben_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11002,208,"DNK","Denmark","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/DNK/Accessibility/dnk_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11003,212,"DMA","Dominica","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/DMA/Accessibility/dma_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11004,214,"DOM","Dominican Republic","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/DOM/Accessibility/dom_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11005,218,"ECU","Ecuador","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ECU/Accessibility/ecu_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11006,222,"SLV","El Salvador","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SLV/Accessibility/slv_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11007,226,"GNQ","Equatorial Guinea","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/Accessibility/gnq_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11008,231,"ETH","Ethiopia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ETH/Accessibility/eth_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11009,232,"ERI","Eritrea","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ERI/Accessibility/eri_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11010,233,"EST","Estonia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/EST/Accessibility/est_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11011,234,"FRO","Faroe Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/FRO/Accessibility/fro_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11012,238,"FLK","Falkland Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/FLK/Accessibility/flk_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11013,239,"SGS","South Georgia and the South Sandwich Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SGS/Accessibility/sgs_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11014,242,"FJI","Fiji","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/FJI/Accessibility/fji_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11015,246,"FIN","Finland","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/FIN/Accessibility/fin_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11016,248,"ALA","Aland Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ALA/Accessibility/ala_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11017,250,"FRA","France","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/FRA/Accessibility/fra_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11018,254,"GUF","French Guiana","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GUF/Accessibility/guf_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11019,258,"PYF","French Polynesia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PYF/Accessibility/pyf_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11020,260,"ATF","French Southern Territories","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ATF/Accessibility/atf_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11021,262,"DJI","Djibouti","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/DJI/Accessibility/dji_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11022,266,"GAB","Gabon","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GAB/Accessibility/gab_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11023,268,"GEO","Georgia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GEO/Accessibility/geo_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11024,270,"GMB","Gambia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GMB/Accessibility/gmb_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11025,275,"PSE","Palestina","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PSE/Accessibility/pse_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11026,276,"DEU","Germany","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/DEU/Accessibility/deu_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11027,288,"GHA","Ghana","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GHA/Accessibility/gha_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11028,292,"GIB","Gibraltar","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GIB/Accessibility/gib_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11029,296,"KIR","Kiribati","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/KIR/Accessibility/kir_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11030,300,"GRC","Greece","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GRC/Accessibility/grc_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11031,308,"GRD","Grenada","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GRD/Accessibility/grd_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11032,312,"GLP","Guadeloupe","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GLP/Accessibility/glp_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11033,316,"GUM","Guam","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GUM/Accessibility/gum_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11034,320,"GTM","Guatemala","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GTM/Accessibility/gtm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11035,324,"GIN","Guinea","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GIN/Accessibility/gin_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11036,328,"GUY","Guyana","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GUY/Accessibility/guy_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11037,332,"HTI","Haiti","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/HTI/Accessibility/hti_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11038,334,"HMD","Heard Island and McDonald Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/HMD/Accessibility/hmd_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11039,336,"VAT","Vatican City","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/VAT/Accessibility/vat_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11040,340,"HND","Honduras","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/HND/Accessibility/hnd_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11041,344,"HKG","Hong Kong","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/HKG/Accessibility/hkg_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11042,348,"HUN","Hungary","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/HUN/Accessibility/hun_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11043,352,"ISL","Iceland","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ISL/Accessibility/isl_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11044,356,"IND","India","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/IND/Accessibility/ind_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11045,364,"IRN","Iran","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/IRN/Accessibility/irn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11046,368,"IRQ","Iraq","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/Accessibility/irq_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11047,372,"IRL","Ireland","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/IRL/Accessibility/irl_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11048,376,"ISR","Israel","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ISR/Accessibility/isr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11049,380,"ITA","Italy","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ITA/Accessibility/ita_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11050,384,"CIV","CIte dIvoire","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CIV/Accessibility/civ_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11051,388,"JAM","Jamaica","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/JAM/Accessibility/jam_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11052,392,"JPN","Japan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/JPN/Accessibility/jpn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11053,398,"KAZ","Kazakhstan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/Accessibility/kaz_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11054,400,"JOR","Jordan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/JOR/Accessibility/jor_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11055,404,"KEN","Kenya","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/KEN/Accessibility/ken_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11056,408,"PRK","North Korea","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PRK/Accessibility/prk_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11057,410,"KOR","South Korea","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/KOR/Accessibility/kor_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11058,414,"KWT","Kuwait","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/KWT/Accessibility/kwt_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11059,417,"KGZ","Kyrgyzstan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/Accessibility/kgz_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11060,418,"LAO","Laos","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LAO/Accessibility/lao_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11061,422,"LBN","Lebanon","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LBN/Accessibility/lbn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11062,426,"LSO","Lesotho","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LSO/Accessibility/lso_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11063,428,"LVA","Latvia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LVA/Accessibility/lva_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11064,430,"LBR","Liberia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LBR/Accessibility/lbr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11065,434,"LBY","Libya","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LBY/Accessibility/lby_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11066,438,"LIE","Liechtenstein","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LIE/Accessibility/lie_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11067,440,"LTU","Lithuania","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LTU/Accessibility/ltu_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11068,442,"LUX","Luxembourg","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LUX/Accessibility/lux_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11069,446,"MAC","Macao","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MAC/Accessibility/mac_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11070,450,"MDG","Madagascar","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MDG/Accessibility/mdg_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11071,454,"MWI","Malawi","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MWI/Accessibility/mwi_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11072,458,"MYS","Malaysia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MYS/Accessibility/mys_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11073,462,"MDV","Maldives","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MDV/Accessibility/mdv_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11074,466,"MLI","Mali","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MLI/Accessibility/mli_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11075,470,"MLT","Malta","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MLT/Accessibility/mlt_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11076,474,"MTQ","Martinique","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/Accessibility/mtq_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11077,478,"MRT","Mauritania","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MRT/Accessibility/mrt_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11078,480,"MUS","Mauritius","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MUS/Accessibility/mus_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11079,484,"MEX","Mexico","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MEX/Accessibility/mex_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11080,492,"MCO","Monaco","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MCO/Accessibility/mco_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11081,496,"MNG","Mongolia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MNG/Accessibility/mng_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11082,498,"MDA","Moldova","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MDA/Accessibility/mda_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11083,499,"MNE","Montenegro","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MNE/Accessibility/mne_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11084,500,"MSR","Montserrat","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MSR/Accessibility/msr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11085,504,"MAR","Morocco","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MAR/Accessibility/mar_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11086,508,"MOZ","Mozambique","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/Accessibility/moz_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11087,512,"OMN","Oman","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/OMN/Accessibility/omn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11088,516,"NAM","Namibia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NAM/Accessibility/nam_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11089,520,"NRU","Nauru","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NRU/Accessibility/nru_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11090,524,"NPL","Nepal","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NPL/Accessibility/npl_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11091,528,"NLD","Netherlands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NLD/Accessibility/nld_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11092,531,"CUW","Curacao","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CUW/Accessibility/cuw_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11093,533,"ABW","Aruba","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ABW/Accessibility/abw_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11094,534,"SXM","Sint Maarten (Dutch part)","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SXM/Accessibility/sxm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11095,535,"BES","Bonaire, Sint Eustatius and Saba","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BES/Accessibility/bes_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11096,540,"NCL","New Caledonia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NCL/Accessibility/ncl_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11097,548,"VUT","Vanuatu","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/VUT/Accessibility/vut_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11098,554,"NZL","New Zealand","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NZL/Accessibility/nzl_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11099,558,"NIC","Nicaragua","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NIC/Accessibility/nic_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11100,562,"NER","Niger","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NER/Accessibility/ner_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11101,566,"NGA","Nigeria","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NGA/Accessibility/nga_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11102,570,"NIU","Niue","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NIU/Accessibility/niu_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11103,574,"NFK","Norfolk Island","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NFK/Accessibility/nfk_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11104,578,"NOR","Norway","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/NOR/Accessibility/nor_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11105,580,"MNP","Northern Mariana Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MNP/Accessibility/mnp_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11106,581,"UMI","United States Minor Outlying Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/UMI/Accessibility/umi_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11107,583,"FSM","Micronesia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/FSM/Accessibility/fsm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11108,584,"MHL","Marshall Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MHL/Accessibility/mhl_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11109,585,"PLW","Palau","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PLW/Accessibility/plw_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11110,586,"PAK","Pakistan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PAK/Accessibility/pak_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11111,591,"PAN","Panama","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PAN/Accessibility/pan_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11112,598,"PNG","Papua New Guinea","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PNG/Accessibility/png_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11113,600,"PRY","Paraguay","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PRY/Accessibility/pry_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11114,604,"PER","Peru","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PER/Accessibility/per_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11115,608,"PHL","Philippines","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PHL/Accessibility/phl_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11116,612,"PCN","Pitcairn Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PCN/Accessibility/pcn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11117,616,"POL","Poland","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/POL/Accessibility/pol_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11118,620,"PRT","Portugal","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PRT/Accessibility/prt_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11119,624,"GNB","Guinea-Bissau","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GNB/Accessibility/gnb_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11120,626,"TLS","East Timor","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TLS/Accessibility/tls_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11121,630,"PRI","Puerto Rico","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/PRI/Accessibility/pri_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11122,634,"QAT","Qatar","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/QAT/Accessibility/qat_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11123,638,"REU","Reunion","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/REU/Accessibility/reu_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11124,642,"ROU","Romania","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ROU/Accessibility/rou_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11125,646,"RWA","Rwanda","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/RWA/Accessibility/rwa_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11126,652,"BLM","Saint Barthelemy","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BLM/Accessibility/blm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11127,654,"SHN","Saint Helena","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SHN/Accessibility/shn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11128,659,"KNA","Saint Kitts and Nevis","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/KNA/Accessibility/kna_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11129,660,"AIA","Anguilla","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/AIA/Accessibility/aia_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11130,662,"LCA","Saint Lucia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/LCA/Accessibility/lca_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11131,663,"MAF","Saint Martin (French part)","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MAF/Accessibility/maf_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11132,666,"SPM","Saint Pierre and Miquelon","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SPM/Accessibility/spm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11133,670,"VCT","Saint Vincent and the Grenadines","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/VCT/Accessibility/vct_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11134,674,"SMR","San Marino","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SMR/Accessibility/smr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11135,678,"STP","Sao Tome and Principe","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/STP/Accessibility/stp_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11136,682,"SAU","Saudi Arabia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SAU/Accessibility/sau_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11137,686,"SEN","Senegal","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SEN/Accessibility/sen_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11138,688,"SRB","Serbia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SRB/Accessibility/srb_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11139,690,"SYC","Seychelles","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SYC/Accessibility/syc_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11140,694,"SLE","Sierra Leone","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SLE/Accessibility/sle_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11141,702,"SGP","Singapore","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SGP/Accessibility/sgp_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11142,703,"SVK","Slovakia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SVK/Accessibility/svk_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11143,704,"VNM","Vietnam","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/VNM/Accessibility/vnm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11144,705,"SVN","Slovenia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SVN/Accessibility/svn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11145,706,"SOM","Somalia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SOM/Accessibility/som_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11146,710,"ZAF","South Africa","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/Accessibility/zaf_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11147,716,"ZWE","Zimbabwe","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/Accessibility/zwe_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11148,724,"ESP","Spain","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ESP/Accessibility/esp_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11149,728,"SSD","South Sudan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SSD/Accessibility/ssd_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11150,729,"SDN","Sudan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SDN/Accessibility/sdn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11151,732,"ESH","Western Sahara","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ESH/Accessibility/esh_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11152,740,"SUR","Suriname","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SUR/Accessibility/sur_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11153,744,"SJM","Svalbard and Jan Mayen Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SJM/Accessibility/sjm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11154,748,"SWZ","Swaziland","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/Accessibility/swz_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11155,752,"SWE","Sweden","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SWE/Accessibility/swe_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11156,756,"CHE","Switzerland","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/CHE/Accessibility/che_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11157,760,"SYR","Syria","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SYR/Accessibility/syr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11158,762,"TJK","Tajikistan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TJK/Accessibility/tjk_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11159,764,"THA","Thailand","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/THA/Accessibility/tha_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11160,768,"TGO","Togo","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TGO/Accessibility/tgo_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11161,772,"TKL","Tokelau","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TKL/Accessibility/tkl_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11162,776,"TON","Tonga","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TON/Accessibility/ton_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11163,780,"TTO","Trinidad and Tobago","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TTO/Accessibility/tto_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11164,784,"ARE","United Arab Emirates","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ARE/Accessibility/are_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11165,788,"TUN","Tunisia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TUN/Accessibility/tun_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11166,792,"TUR","Turkey","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TUR/Accessibility/tur_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11167,795,"TKM","Turkmenistan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TKM/Accessibility/tkm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11168,796,"TCA","Turks and Caicos Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TCA/Accessibility/tca_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11169,798,"TUV","Tuvalu","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TUV/Accessibility/tuv_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11170,800,"UGA","Uganda","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/UGA/Accessibility/uga_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11171,804,"UKR","Ukraine","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/UKR/Accessibility/ukr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11172,807,"MKD","Macedonia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/MKD/Accessibility/mkd_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11173,818,"EGY","Egypt","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/EGY/Accessibility/egy_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11174,826,"GBR","United Kingdom","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GBR/Accessibility/gbr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11175,831,"GGY","Guernsey","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/GGY/Accessibility/ggy_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11176,832,"JEY","Jersey","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/JEY/Accessibility/jey_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11177,833,"IMN","Isle of Man","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/IMN/Accessibility/imn_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11178,834,"TZA","Tanzania","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/TZA/Accessibility/tza_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11179,854,"BFA","Burkina Faso","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/BFA/Accessibility/bfa_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11180,858,"URY","Uruguay","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/URY/Accessibility/ury_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11181,860,"UZB","Uzbekistan","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/UZB/Accessibility/uzb_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11182,862,"VEN","Venezuela","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/VEN/Accessibility/ven_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11183,876,"WLF","Wallis and Futuna","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/WLF/Accessibility/wlf_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11184,882,"WSM","Samoa","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/WSM/Accessibility/wsm_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11185,887,"YEM","Yemen","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/YEM/Accessibility/yem_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11186,894,"ZMB","Zambia","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/Accessibility/zmb_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11187,900,"KOS","Kosovo","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/KOS/Accessibility/kos_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11188,901,"SPR","Spratly Islands","tt50k_100m_2000","GIS/Covariates/Global_2000_2020/SPR/Accessibility/spr_tt50k_100m_2000.tif","EC-JRC travel time to major cities 2000"
11189,643,"RUS","Russia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/RUS/BSGM/2001/Binary/rus_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11190,643,"RUS","Russia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/RUS/BSGM/2001/DTE/rus_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11191,643,"RUS","Russia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/RUS/BSGM/2002/Binary/rus_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11192,643,"RUS","Russia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/RUS/BSGM/2002/DTE/rus_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11193,643,"RUS","Russia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/RUS/BSGM/2003/Binary/rus_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11194,643,"RUS","Russia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/RUS/BSGM/2003/DTE/rus_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11195,643,"RUS","Russia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/RUS/BSGM/2004/Binary/rus_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11196,643,"RUS","Russia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/RUS/BSGM/2004/DTE/rus_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11197,643,"RUS","Russia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/RUS/BSGM/2005/Binary/rus_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11198,643,"RUS","Russia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/RUS/BSGM/2005/DTE/rus_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11199,643,"RUS","Russia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/RUS/BSGM/2006/Binary/rus_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11200,643,"RUS","Russia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/RUS/BSGM/2006/DTE/rus_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11201,643,"RUS","Russia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/RUS/BSGM/2007/Binary/rus_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11202,643,"RUS","Russia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/RUS/BSGM/2007/DTE/rus_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11203,643,"RUS","Russia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/RUS/BSGM/2008/Binary/rus_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11204,643,"RUS","Russia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/RUS/BSGM/2008/DTE/rus_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11205,643,"RUS","Russia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/RUS/BSGM/2009/Binary/rus_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11206,643,"RUS","Russia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/RUS/BSGM/2009/DTE/rus_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11207,643,"RUS","Russia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/RUS/BSGM/2010/Binary/rus_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11208,643,"RUS","Russia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/RUS/BSGM/2010/DTE/rus_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11209,643,"RUS","Russia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/RUS/BSGM/2011/Binary/rus_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11210,643,"RUS","Russia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/RUS/BSGM/2011/DTE/rus_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11211,643,"RUS","Russia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/RUS/BSGM/2013/Binary/rus_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11212,643,"RUS","Russia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/RUS/BSGM/2013/DTE/rus_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11213,643,"RUS","Russia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/RUS/BSGM/2015/DTE/rus_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11214,643,"RUS","Russia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/RUS/BSGM/2016/DTE/rus_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11215,643,"RUS","Russia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/RUS/BSGM/2017/DTE/rus_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11216,643,"RUS","Russia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/RUS/BSGM/2018/DTE/rus_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11217,643,"RUS","Russia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/RUS/BSGM/2019/DTE/rus_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11218,643,"RUS","Russia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/RUS/BSGM/2020/DTE/rus_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11219,360,"IDN","Indonesia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IDN/BSGM/2001/Binary/idn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11220,360,"IDN","Indonesia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IDN/BSGM/2001/DTE/idn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11221,360,"IDN","Indonesia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IDN/BSGM/2002/Binary/idn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11222,360,"IDN","Indonesia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IDN/BSGM/2002/DTE/idn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11223,360,"IDN","Indonesia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IDN/BSGM/2003/Binary/idn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11224,360,"IDN","Indonesia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IDN/BSGM/2003/DTE/idn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11225,360,"IDN","Indonesia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IDN/BSGM/2004/Binary/idn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11226,360,"IDN","Indonesia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IDN/BSGM/2004/DTE/idn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11227,360,"IDN","Indonesia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IDN/BSGM/2005/Binary/idn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11228,360,"IDN","Indonesia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IDN/BSGM/2005/DTE/idn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11229,360,"IDN","Indonesia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IDN/BSGM/2006/Binary/idn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11230,360,"IDN","Indonesia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IDN/BSGM/2006/DTE/idn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11231,360,"IDN","Indonesia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IDN/BSGM/2007/Binary/idn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11232,360,"IDN","Indonesia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IDN/BSGM/2007/DTE/idn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11233,360,"IDN","Indonesia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IDN/BSGM/2008/Binary/idn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11234,360,"IDN","Indonesia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IDN/BSGM/2008/DTE/idn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11235,360,"IDN","Indonesia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IDN/BSGM/2009/Binary/idn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11236,360,"IDN","Indonesia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IDN/BSGM/2009/DTE/idn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11237,360,"IDN","Indonesia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IDN/BSGM/2010/Binary/idn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11238,360,"IDN","Indonesia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IDN/BSGM/2010/DTE/idn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11239,360,"IDN","Indonesia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IDN/BSGM/2011/Binary/idn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11240,360,"IDN","Indonesia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IDN/BSGM/2011/DTE/idn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11241,360,"IDN","Indonesia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IDN/BSGM/2013/Binary/idn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11242,360,"IDN","Indonesia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IDN/BSGM/2013/DTE/idn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11243,360,"IDN","Indonesia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/IDN/BSGM/2015/DTE/idn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11244,360,"IDN","Indonesia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/IDN/BSGM/2016/DTE/idn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11245,360,"IDN","Indonesia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/IDN/BSGM/2017/DTE/idn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11246,360,"IDN","Indonesia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/IDN/BSGM/2018/DTE/idn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11247,360,"IDN","Indonesia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/IDN/BSGM/2019/DTE/idn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11248,360,"IDN","Indonesia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/IDN/BSGM/2020/DTE/idn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11249,840,"USA","United States","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/USA/BSGM/2001/Binary/usa_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11250,840,"USA","United States","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/USA/BSGM/2001/DTE/usa_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11251,840,"USA","United States","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/USA/BSGM/2002/Binary/usa_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11252,840,"USA","United States","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/USA/BSGM/2002/DTE/usa_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11253,840,"USA","United States","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/USA/BSGM/2003/Binary/usa_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11254,840,"USA","United States","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/USA/BSGM/2003/DTE/usa_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11255,840,"USA","United States","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/USA/BSGM/2004/Binary/usa_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11256,840,"USA","United States","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/USA/BSGM/2004/DTE/usa_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11257,840,"USA","United States","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/USA/BSGM/2005/Binary/usa_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11258,840,"USA","United States","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/USA/BSGM/2005/DTE/usa_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11259,840,"USA","United States","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/USA/BSGM/2006/Binary/usa_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11260,840,"USA","United States","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/USA/BSGM/2006/DTE/usa_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11261,840,"USA","United States","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/USA/BSGM/2007/Binary/usa_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11262,840,"USA","United States","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/USA/BSGM/2007/DTE/usa_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11263,840,"USA","United States","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/USA/BSGM/2008/Binary/usa_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11264,840,"USA","United States","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/USA/BSGM/2008/DTE/usa_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11265,840,"USA","United States","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/USA/BSGM/2009/Binary/usa_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11266,840,"USA","United States","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/USA/BSGM/2009/DTE/usa_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11267,840,"USA","United States","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/USA/BSGM/2010/Binary/usa_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11268,840,"USA","United States","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/USA/BSGM/2010/DTE/usa_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11269,840,"USA","United States","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/USA/BSGM/2011/Binary/usa_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11270,840,"USA","United States","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/USA/BSGM/2011/DTE/usa_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11271,840,"USA","United States","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/USA/BSGM/2013/Binary/usa_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11272,840,"USA","United States","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/USA/BSGM/2013/DTE/usa_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11273,840,"USA","United States","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/USA/BSGM/2015/DTE/usa_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11274,840,"USA","United States","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/USA/BSGM/2016/DTE/usa_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11275,840,"USA","United States","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/USA/BSGM/2017/DTE/usa_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11276,840,"USA","United States","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/USA/BSGM/2018/DTE/usa_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11277,840,"USA","United States","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/USA/BSGM/2019/DTE/usa_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11278,840,"USA","United States","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/USA/BSGM/2020/DTE/usa_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11279,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VIR/BSGM/2001/Binary/vir_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11280,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VIR/BSGM/2001/DTE/vir_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11281,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VIR/BSGM/2002/Binary/vir_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11282,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VIR/BSGM/2002/DTE/vir_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11283,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VIR/BSGM/2003/Binary/vir_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11284,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VIR/BSGM/2003/DTE/vir_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11285,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VIR/BSGM/2004/Binary/vir_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11286,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VIR/BSGM/2004/DTE/vir_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11287,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VIR/BSGM/2005/Binary/vir_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11288,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VIR/BSGM/2005/DTE/vir_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11289,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VIR/BSGM/2006/Binary/vir_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11290,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VIR/BSGM/2006/DTE/vir_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11291,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VIR/BSGM/2007/Binary/vir_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11292,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VIR/BSGM/2007/DTE/vir_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11293,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VIR/BSGM/2008/Binary/vir_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11294,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VIR/BSGM/2008/DTE/vir_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11295,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VIR/BSGM/2009/Binary/vir_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11296,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VIR/BSGM/2009/DTE/vir_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11297,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VIR/BSGM/2010/Binary/vir_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11298,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VIR/BSGM/2010/DTE/vir_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11299,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VIR/BSGM/2011/Binary/vir_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11300,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VIR/BSGM/2011/DTE/vir_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11301,850,"VIR","Virgin_Islands_U_S","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VIR/BSGM/2013/Binary/vir_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11302,850,"VIR","Virgin_Islands_U_S","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VIR/BSGM/2013/DTE/vir_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11303,850,"VIR","Virgin_Islands_U_S","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/VIR/BSGM/2015/DTE/vir_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11304,850,"VIR","Virgin_Islands_U_S","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/VIR/BSGM/2016/DTE/vir_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11305,850,"VIR","Virgin_Islands_U_S","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/VIR/BSGM/2017/DTE/vir_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11306,850,"VIR","Virgin_Islands_U_S","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/VIR/BSGM/2018/DTE/vir_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11307,850,"VIR","Virgin_Islands_U_S","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/VIR/BSGM/2019/DTE/vir_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11308,850,"VIR","Virgin_Islands_U_S","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/VIR/BSGM/2020/DTE/vir_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11309,304,"GRL","Greenland","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GRL/BSGM/2001/Binary/grl_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11310,304,"GRL","Greenland","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GRL/BSGM/2001/DTE/grl_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11311,304,"GRL","Greenland","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GRL/BSGM/2002/Binary/grl_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11312,304,"GRL","Greenland","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GRL/BSGM/2002/DTE/grl_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11313,304,"GRL","Greenland","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GRL/BSGM/2003/Binary/grl_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11314,304,"GRL","Greenland","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GRL/BSGM/2003/DTE/grl_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11315,304,"GRL","Greenland","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GRL/BSGM/2004/Binary/grl_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11316,304,"GRL","Greenland","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GRL/BSGM/2004/DTE/grl_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11317,304,"GRL","Greenland","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GRL/BSGM/2005/Binary/grl_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11318,304,"GRL","Greenland","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GRL/BSGM/2005/DTE/grl_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11319,304,"GRL","Greenland","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GRL/BSGM/2006/Binary/grl_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11320,304,"GRL","Greenland","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GRL/BSGM/2006/DTE/grl_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11321,304,"GRL","Greenland","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GRL/BSGM/2007/Binary/grl_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11322,304,"GRL","Greenland","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GRL/BSGM/2007/DTE/grl_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11323,304,"GRL","Greenland","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GRL/BSGM/2008/Binary/grl_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11324,304,"GRL","Greenland","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GRL/BSGM/2008/DTE/grl_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11325,304,"GRL","Greenland","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GRL/BSGM/2009/Binary/grl_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11326,304,"GRL","Greenland","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GRL/BSGM/2009/DTE/grl_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11327,304,"GRL","Greenland","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GRL/BSGM/2010/Binary/grl_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11328,304,"GRL","Greenland","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GRL/BSGM/2010/DTE/grl_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11329,304,"GRL","Greenland","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GRL/BSGM/2011/Binary/grl_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11330,304,"GRL","Greenland","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GRL/BSGM/2011/DTE/grl_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11331,304,"GRL","Greenland","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GRL/BSGM/2013/Binary/grl_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11332,304,"GRL","Greenland","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GRL/BSGM/2013/DTE/grl_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11333,304,"GRL","Greenland","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GRL/BSGM/2015/DTE/grl_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11334,304,"GRL","Greenland","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GRL/BSGM/2016/DTE/grl_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11335,304,"GRL","Greenland","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GRL/BSGM/2017/DTE/grl_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11336,304,"GRL","Greenland","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GRL/BSGM/2018/DTE/grl_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11337,304,"GRL","Greenland","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GRL/BSGM/2019/DTE/grl_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11338,304,"GRL","Greenland","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GRL/BSGM/2020/DTE/grl_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11339,156,"CHN","China","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CHN/BSGM/2001/Binary/chn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11340,156,"CHN","China","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CHN/BSGM/2001/DTE/chn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11341,156,"CHN","China","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CHN/BSGM/2002/Binary/chn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11342,156,"CHN","China","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CHN/BSGM/2002/DTE/chn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11343,156,"CHN","China","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CHN/BSGM/2003/Binary/chn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11344,156,"CHN","China","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CHN/BSGM/2003/DTE/chn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11345,156,"CHN","China","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CHN/BSGM/2004/Binary/chn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11346,156,"CHN","China","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CHN/BSGM/2004/DTE/chn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11347,156,"CHN","China","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CHN/BSGM/2005/Binary/chn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11348,156,"CHN","China","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CHN/BSGM/2005/DTE/chn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11349,156,"CHN","China","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CHN/BSGM/2006/Binary/chn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11350,156,"CHN","China","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CHN/BSGM/2006/DTE/chn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11351,156,"CHN","China","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CHN/BSGM/2007/Binary/chn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11352,156,"CHN","China","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CHN/BSGM/2007/DTE/chn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11353,156,"CHN","China","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CHN/BSGM/2008/Binary/chn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11354,156,"CHN","China","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CHN/BSGM/2008/DTE/chn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11355,156,"CHN","China","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CHN/BSGM/2009/Binary/chn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11356,156,"CHN","China","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CHN/BSGM/2009/DTE/chn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11357,156,"CHN","China","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CHN/BSGM/2010/Binary/chn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11358,156,"CHN","China","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CHN/BSGM/2010/DTE/chn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11359,156,"CHN","China","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CHN/BSGM/2011/Binary/chn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11360,156,"CHN","China","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CHN/BSGM/2011/DTE/chn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11361,156,"CHN","China","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CHN/BSGM/2013/Binary/chn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11362,156,"CHN","China","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CHN/BSGM/2013/DTE/chn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11363,156,"CHN","China","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CHN/BSGM/2015/DTE/chn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11364,156,"CHN","China","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CHN/BSGM/2016/DTE/chn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11365,156,"CHN","China","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CHN/BSGM/2017/DTE/chn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11366,156,"CHN","China","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CHN/BSGM/2018/DTE/chn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11367,156,"CHN","China","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CHN/BSGM/2019/DTE/chn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11368,156,"CHN","China","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CHN/BSGM/2020/DTE/chn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11369,36,"AUS","Australia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AUS/BSGM/2001/Binary/aus_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11370,36,"AUS","Australia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AUS/BSGM/2001/DTE/aus_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11371,36,"AUS","Australia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AUS/BSGM/2002/Binary/aus_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11372,36,"AUS","Australia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AUS/BSGM/2002/DTE/aus_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11373,36,"AUS","Australia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AUS/BSGM/2003/Binary/aus_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11374,36,"AUS","Australia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AUS/BSGM/2003/DTE/aus_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11375,36,"AUS","Australia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AUS/BSGM/2004/Binary/aus_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11376,36,"AUS","Australia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AUS/BSGM/2004/DTE/aus_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11377,36,"AUS","Australia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AUS/BSGM/2005/Binary/aus_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11378,36,"AUS","Australia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AUS/BSGM/2005/DTE/aus_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11379,36,"AUS","Australia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AUS/BSGM/2006/Binary/aus_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11380,36,"AUS","Australia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AUS/BSGM/2006/DTE/aus_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11381,36,"AUS","Australia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AUS/BSGM/2007/Binary/aus_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11382,36,"AUS","Australia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AUS/BSGM/2007/DTE/aus_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11383,36,"AUS","Australia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AUS/BSGM/2008/Binary/aus_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11384,36,"AUS","Australia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AUS/BSGM/2008/DTE/aus_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11385,36,"AUS","Australia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AUS/BSGM/2009/Binary/aus_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11386,36,"AUS","Australia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AUS/BSGM/2009/DTE/aus_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11387,36,"AUS","Australia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AUS/BSGM/2010/Binary/aus_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11388,36,"AUS","Australia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AUS/BSGM/2010/DTE/aus_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11389,36,"AUS","Australia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AUS/BSGM/2011/Binary/aus_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11390,36,"AUS","Australia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AUS/BSGM/2011/DTE/aus_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11391,36,"AUS","Australia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AUS/BSGM/2013/Binary/aus_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11392,36,"AUS","Australia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AUS/BSGM/2013/DTE/aus_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11393,36,"AUS","Australia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/AUS/BSGM/2015/DTE/aus_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11394,36,"AUS","Australia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/AUS/BSGM/2016/DTE/aus_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11395,36,"AUS","Australia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/AUS/BSGM/2017/DTE/aus_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11396,36,"AUS","Australia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/AUS/BSGM/2018/DTE/aus_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11397,36,"AUS","Australia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/AUS/BSGM/2019/DTE/aus_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11398,36,"AUS","Australia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/AUS/BSGM/2020/DTE/aus_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11399,76,"BRA","Brazil","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BRA/BSGM/2001/Binary/bra_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11400,76,"BRA","Brazil","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BRA/BSGM/2001/DTE/bra_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11401,76,"BRA","Brazil","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BRA/BSGM/2002/Binary/bra_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11402,76,"BRA","Brazil","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BRA/BSGM/2002/DTE/bra_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11403,76,"BRA","Brazil","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BRA/BSGM/2003/Binary/bra_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11404,76,"BRA","Brazil","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BRA/BSGM/2003/DTE/bra_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11405,76,"BRA","Brazil","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BRA/BSGM/2004/Binary/bra_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11406,76,"BRA","Brazil","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BRA/BSGM/2004/DTE/bra_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11407,76,"BRA","Brazil","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BRA/BSGM/2005/Binary/bra_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11408,76,"BRA","Brazil","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BRA/BSGM/2005/DTE/bra_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11409,76,"BRA","Brazil","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BRA/BSGM/2006/Binary/bra_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11410,76,"BRA","Brazil","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BRA/BSGM/2006/DTE/bra_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11411,76,"BRA","Brazil","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BRA/BSGM/2007/Binary/bra_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11412,76,"BRA","Brazil","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BRA/BSGM/2007/DTE/bra_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11413,76,"BRA","Brazil","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BRA/BSGM/2008/Binary/bra_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11414,76,"BRA","Brazil","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BRA/BSGM/2008/DTE/bra_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11415,76,"BRA","Brazil","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BRA/BSGM/2009/Binary/bra_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11416,76,"BRA","Brazil","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BRA/BSGM/2009/DTE/bra_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11417,76,"BRA","Brazil","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BRA/BSGM/2010/Binary/bra_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11418,76,"BRA","Brazil","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BRA/BSGM/2010/DTE/bra_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11419,76,"BRA","Brazil","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BRA/BSGM/2011/Binary/bra_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11420,76,"BRA","Brazil","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BRA/BSGM/2011/DTE/bra_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11421,76,"BRA","Brazil","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BRA/BSGM/2013/Binary/bra_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11422,76,"BRA","Brazil","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BRA/BSGM/2013/DTE/bra_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11423,76,"BRA","Brazil","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BRA/BSGM/2015/DTE/bra_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11424,76,"BRA","Brazil","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BRA/BSGM/2016/DTE/bra_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11425,76,"BRA","Brazil","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BRA/BSGM/2017/DTE/bra_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11426,76,"BRA","Brazil","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BRA/BSGM/2018/DTE/bra_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11427,76,"BRA","Brazil","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BRA/BSGM/2019/DTE/bra_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11428,76,"BRA","Brazil","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BRA/BSGM/2020/DTE/bra_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11429,124,"CAN","Canada","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CAN/BSGM/2001/Binary/can_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11430,124,"CAN","Canada","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CAN/BSGM/2001/DTE/can_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11431,124,"CAN","Canada","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CAN/BSGM/2002/Binary/can_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11432,124,"CAN","Canada","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CAN/BSGM/2002/DTE/can_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11433,124,"CAN","Canada","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CAN/BSGM/2003/Binary/can_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11434,124,"CAN","Canada","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CAN/BSGM/2003/DTE/can_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11435,124,"CAN","Canada","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CAN/BSGM/2004/Binary/can_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11436,124,"CAN","Canada","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CAN/BSGM/2004/DTE/can_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11437,124,"CAN","Canada","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CAN/BSGM/2005/Binary/can_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11438,124,"CAN","Canada","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CAN/BSGM/2005/DTE/can_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11439,124,"CAN","Canada","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CAN/BSGM/2006/Binary/can_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11440,124,"CAN","Canada","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CAN/BSGM/2006/DTE/can_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11441,124,"CAN","Canada","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CAN/BSGM/2007/Binary/can_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11442,124,"CAN","Canada","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CAN/BSGM/2007/DTE/can_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11443,124,"CAN","Canada","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CAN/BSGM/2008/Binary/can_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11444,124,"CAN","Canada","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CAN/BSGM/2008/DTE/can_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11445,124,"CAN","Canada","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CAN/BSGM/2009/Binary/can_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11446,124,"CAN","Canada","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CAN/BSGM/2009/DTE/can_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11447,124,"CAN","Canada","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CAN/BSGM/2010/Binary/can_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11448,124,"CAN","Canada","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CAN/BSGM/2010/DTE/can_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11449,124,"CAN","Canada","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CAN/BSGM/2011/Binary/can_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11450,124,"CAN","Canada","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CAN/BSGM/2011/DTE/can_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11451,124,"CAN","Canada","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CAN/BSGM/2013/Binary/can_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11452,124,"CAN","Canada","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CAN/BSGM/2013/DTE/can_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11453,124,"CAN","Canada","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CAN/BSGM/2015/DTE/can_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11454,124,"CAN","Canada","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CAN/BSGM/2016/DTE/can_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11455,124,"CAN","Canada","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CAN/BSGM/2017/DTE/can_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11456,124,"CAN","Canada","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CAN/BSGM/2018/DTE/can_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11457,124,"CAN","Canada","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CAN/BSGM/2019/DTE/can_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11458,124,"CAN","Canada","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CAN/BSGM/2020/DTE/can_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11459,152,"CHL","Chile","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CHL/BSGM/2001/Binary/chl_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11460,152,"CHL","Chile","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CHL/BSGM/2001/DTE/chl_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11461,152,"CHL","Chile","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CHL/BSGM/2002/Binary/chl_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11462,152,"CHL","Chile","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CHL/BSGM/2002/DTE/chl_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11463,152,"CHL","Chile","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CHL/BSGM/2003/Binary/chl_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11464,152,"CHL","Chile","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CHL/BSGM/2003/DTE/chl_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11465,152,"CHL","Chile","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CHL/BSGM/2004/Binary/chl_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11466,152,"CHL","Chile","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CHL/BSGM/2004/DTE/chl_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11467,152,"CHL","Chile","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CHL/BSGM/2005/Binary/chl_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11468,152,"CHL","Chile","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CHL/BSGM/2005/DTE/chl_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11469,152,"CHL","Chile","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CHL/BSGM/2006/Binary/chl_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11470,152,"CHL","Chile","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CHL/BSGM/2006/DTE/chl_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11471,152,"CHL","Chile","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CHL/BSGM/2007/Binary/chl_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11472,152,"CHL","Chile","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CHL/BSGM/2007/DTE/chl_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11473,152,"CHL","Chile","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CHL/BSGM/2008/Binary/chl_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11474,152,"CHL","Chile","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CHL/BSGM/2008/DTE/chl_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11475,152,"CHL","Chile","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CHL/BSGM/2009/Binary/chl_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11476,152,"CHL","Chile","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CHL/BSGM/2009/DTE/chl_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11477,152,"CHL","Chile","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CHL/BSGM/2010/Binary/chl_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11478,152,"CHL","Chile","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CHL/BSGM/2010/DTE/chl_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11479,152,"CHL","Chile","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CHL/BSGM/2011/Binary/chl_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11480,152,"CHL","Chile","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CHL/BSGM/2011/DTE/chl_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11481,152,"CHL","Chile","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CHL/BSGM/2013/Binary/chl_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11482,152,"CHL","Chile","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CHL/BSGM/2013/DTE/chl_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11483,152,"CHL","Chile","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CHL/BSGM/2015/DTE/chl_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11484,152,"CHL","Chile","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CHL/BSGM/2016/DTE/chl_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11485,152,"CHL","Chile","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CHL/BSGM/2017/DTE/chl_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11486,152,"CHL","Chile","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CHL/BSGM/2018/DTE/chl_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11487,152,"CHL","Chile","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CHL/BSGM/2019/DTE/chl_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11488,152,"CHL","Chile","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CHL/BSGM/2020/DTE/chl_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11489,4,"AFG","Afghanistan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AFG/BSGM/2001/Binary/afg_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11490,4,"AFG","Afghanistan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AFG/BSGM/2001/DTE/afg_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11491,4,"AFG","Afghanistan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AFG/BSGM/2002/Binary/afg_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11492,4,"AFG","Afghanistan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AFG/BSGM/2002/DTE/afg_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11493,4,"AFG","Afghanistan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AFG/BSGM/2003/Binary/afg_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11494,4,"AFG","Afghanistan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AFG/BSGM/2003/DTE/afg_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11495,4,"AFG","Afghanistan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AFG/BSGM/2004/Binary/afg_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11496,4,"AFG","Afghanistan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AFG/BSGM/2004/DTE/afg_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11497,4,"AFG","Afghanistan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AFG/BSGM/2005/Binary/afg_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11498,4,"AFG","Afghanistan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AFG/BSGM/2005/DTE/afg_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11499,4,"AFG","Afghanistan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AFG/BSGM/2006/Binary/afg_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11500,4,"AFG","Afghanistan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AFG/BSGM/2006/DTE/afg_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11501,4,"AFG","Afghanistan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AFG/BSGM/2007/Binary/afg_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11502,4,"AFG","Afghanistan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AFG/BSGM/2007/DTE/afg_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11503,4,"AFG","Afghanistan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AFG/BSGM/2008/Binary/afg_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11504,4,"AFG","Afghanistan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AFG/BSGM/2008/DTE/afg_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11505,4,"AFG","Afghanistan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AFG/BSGM/2009/Binary/afg_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11506,4,"AFG","Afghanistan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AFG/BSGM/2009/DTE/afg_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11507,4,"AFG","Afghanistan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AFG/BSGM/2010/Binary/afg_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11508,4,"AFG","Afghanistan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AFG/BSGM/2010/DTE/afg_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11509,4,"AFG","Afghanistan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AFG/BSGM/2011/Binary/afg_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11510,4,"AFG","Afghanistan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AFG/BSGM/2011/DTE/afg_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11511,4,"AFG","Afghanistan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AFG/BSGM/2013/Binary/afg_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11512,4,"AFG","Afghanistan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AFG/BSGM/2013/DTE/afg_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11513,4,"AFG","Afghanistan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/AFG/BSGM/2015/DTE/afg_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11514,4,"AFG","Afghanistan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/AFG/BSGM/2016/DTE/afg_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11515,4,"AFG","Afghanistan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/AFG/BSGM/2017/DTE/afg_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11516,4,"AFG","Afghanistan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/AFG/BSGM/2018/DTE/afg_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11517,4,"AFG","Afghanistan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/AFG/BSGM/2019/DTE/afg_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11518,4,"AFG","Afghanistan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/AFG/BSGM/2020/DTE/afg_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11519,8,"ALB","Albania","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ALB/BSGM/2001/Binary/alb_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11520,8,"ALB","Albania","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ALB/BSGM/2001/DTE/alb_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11521,8,"ALB","Albania","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ALB/BSGM/2002/Binary/alb_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11522,8,"ALB","Albania","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ALB/BSGM/2002/DTE/alb_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11523,8,"ALB","Albania","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ALB/BSGM/2003/Binary/alb_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11524,8,"ALB","Albania","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ALB/BSGM/2003/DTE/alb_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11525,8,"ALB","Albania","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ALB/BSGM/2004/Binary/alb_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11526,8,"ALB","Albania","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ALB/BSGM/2004/DTE/alb_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11527,8,"ALB","Albania","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ALB/BSGM/2005/Binary/alb_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11528,8,"ALB","Albania","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ALB/BSGM/2005/DTE/alb_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11529,8,"ALB","Albania","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ALB/BSGM/2006/Binary/alb_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11530,8,"ALB","Albania","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ALB/BSGM/2006/DTE/alb_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11531,8,"ALB","Albania","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ALB/BSGM/2007/Binary/alb_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11532,8,"ALB","Albania","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ALB/BSGM/2007/DTE/alb_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11533,8,"ALB","Albania","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ALB/BSGM/2008/Binary/alb_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11534,8,"ALB","Albania","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ALB/BSGM/2008/DTE/alb_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11535,8,"ALB","Albania","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ALB/BSGM/2009/Binary/alb_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11536,8,"ALB","Albania","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ALB/BSGM/2009/DTE/alb_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11537,8,"ALB","Albania","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ALB/BSGM/2010/Binary/alb_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11538,8,"ALB","Albania","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ALB/BSGM/2010/DTE/alb_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11539,8,"ALB","Albania","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ALB/BSGM/2011/Binary/alb_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11540,8,"ALB","Albania","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ALB/BSGM/2011/DTE/alb_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11541,8,"ALB","Albania","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ALB/BSGM/2013/Binary/alb_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11542,8,"ALB","Albania","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ALB/BSGM/2013/DTE/alb_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11543,8,"ALB","Albania","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ALB/BSGM/2015/DTE/alb_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11544,8,"ALB","Albania","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ALB/BSGM/2016/DTE/alb_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11545,8,"ALB","Albania","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ALB/BSGM/2017/DTE/alb_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11546,8,"ALB","Albania","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ALB/BSGM/2018/DTE/alb_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11547,8,"ALB","Albania","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ALB/BSGM/2019/DTE/alb_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11548,8,"ALB","Albania","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ALB/BSGM/2020/DTE/alb_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11549,10,"ATA","Antarctica","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ATA/BSGM/2001/Binary/ata_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11550,10,"ATA","Antarctica","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ATA/BSGM/2001/DTE/ata_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11551,10,"ATA","Antarctica","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ATA/BSGM/2002/Binary/ata_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11552,10,"ATA","Antarctica","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ATA/BSGM/2002/DTE/ata_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11553,10,"ATA","Antarctica","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ATA/BSGM/2003/Binary/ata_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11554,10,"ATA","Antarctica","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ATA/BSGM/2003/DTE/ata_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11555,10,"ATA","Antarctica","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ATA/BSGM/2004/Binary/ata_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11556,10,"ATA","Antarctica","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ATA/BSGM/2004/DTE/ata_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11557,10,"ATA","Antarctica","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ATA/BSGM/2005/Binary/ata_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11558,10,"ATA","Antarctica","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ATA/BSGM/2005/DTE/ata_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11559,10,"ATA","Antarctica","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ATA/BSGM/2006/Binary/ata_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11560,10,"ATA","Antarctica","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ATA/BSGM/2006/DTE/ata_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11561,10,"ATA","Antarctica","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ATA/BSGM/2007/Binary/ata_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11562,10,"ATA","Antarctica","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ATA/BSGM/2007/DTE/ata_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11563,10,"ATA","Antarctica","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ATA/BSGM/2008/Binary/ata_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11564,10,"ATA","Antarctica","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ATA/BSGM/2008/DTE/ata_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11565,10,"ATA","Antarctica","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ATA/BSGM/2009/Binary/ata_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11566,10,"ATA","Antarctica","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ATA/BSGM/2009/DTE/ata_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11567,10,"ATA","Antarctica","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ATA/BSGM/2010/Binary/ata_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11568,10,"ATA","Antarctica","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ATA/BSGM/2010/DTE/ata_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11569,10,"ATA","Antarctica","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ATA/BSGM/2011/Binary/ata_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11570,10,"ATA","Antarctica","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ATA/BSGM/2011/DTE/ata_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11571,10,"ATA","Antarctica","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ATA/BSGM/2013/Binary/ata_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11572,10,"ATA","Antarctica","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ATA/BSGM/2013/DTE/ata_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11573,10,"ATA","Antarctica","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ATA/BSGM/2015/DTE/ata_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11574,10,"ATA","Antarctica","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ATA/BSGM/2016/DTE/ata_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11575,10,"ATA","Antarctica","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ATA/BSGM/2017/DTE/ata_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11576,10,"ATA","Antarctica","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ATA/BSGM/2018/DTE/ata_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11577,10,"ATA","Antarctica","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ATA/BSGM/2019/DTE/ata_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11578,10,"ATA","Antarctica","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ATA/BSGM/2020/DTE/ata_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11579,12,"DZA","Algeria","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DZA/BSGM/2001/Binary/dza_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11580,12,"DZA","Algeria","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DZA/BSGM/2001/DTE/dza_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11581,12,"DZA","Algeria","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DZA/BSGM/2002/Binary/dza_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11582,12,"DZA","Algeria","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DZA/BSGM/2002/DTE/dza_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11583,12,"DZA","Algeria","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DZA/BSGM/2003/Binary/dza_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11584,12,"DZA","Algeria","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DZA/BSGM/2003/DTE/dza_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11585,12,"DZA","Algeria","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DZA/BSGM/2004/Binary/dza_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11586,12,"DZA","Algeria","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DZA/BSGM/2004/DTE/dza_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11587,12,"DZA","Algeria","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DZA/BSGM/2005/Binary/dza_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11588,12,"DZA","Algeria","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DZA/BSGM/2005/DTE/dza_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11589,12,"DZA","Algeria","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DZA/BSGM/2006/Binary/dza_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11590,12,"DZA","Algeria","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DZA/BSGM/2006/DTE/dza_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11591,12,"DZA","Algeria","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DZA/BSGM/2007/Binary/dza_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11592,12,"DZA","Algeria","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DZA/BSGM/2007/DTE/dza_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11593,12,"DZA","Algeria","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DZA/BSGM/2008/Binary/dza_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11594,12,"DZA","Algeria","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DZA/BSGM/2008/DTE/dza_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11595,12,"DZA","Algeria","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DZA/BSGM/2009/Binary/dza_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11596,12,"DZA","Algeria","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DZA/BSGM/2009/DTE/dza_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11597,12,"DZA","Algeria","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DZA/BSGM/2010/Binary/dza_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11598,12,"DZA","Algeria","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DZA/BSGM/2010/DTE/dza_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11599,12,"DZA","Algeria","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DZA/BSGM/2011/Binary/dza_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11600,12,"DZA","Algeria","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DZA/BSGM/2011/DTE/dza_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11601,12,"DZA","Algeria","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DZA/BSGM/2013/Binary/dza_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11602,12,"DZA","Algeria","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DZA/BSGM/2013/DTE/dza_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11603,12,"DZA","Algeria","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/DZA/BSGM/2015/DTE/dza_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11604,12,"DZA","Algeria","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/DZA/BSGM/2016/DTE/dza_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11605,12,"DZA","Algeria","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/DZA/BSGM/2017/DTE/dza_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11606,12,"DZA","Algeria","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/DZA/BSGM/2018/DTE/dza_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11607,12,"DZA","Algeria","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/DZA/BSGM/2019/DTE/dza_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11608,12,"DZA","Algeria","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/DZA/BSGM/2020/DTE/dza_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11609,16,"ASM","American Samoa","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ASM/BSGM/2001/Binary/asm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11610,16,"ASM","American Samoa","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ASM/BSGM/2001/DTE/asm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11611,16,"ASM","American Samoa","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ASM/BSGM/2002/Binary/asm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11612,16,"ASM","American Samoa","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ASM/BSGM/2002/DTE/asm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11613,16,"ASM","American Samoa","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ASM/BSGM/2003/Binary/asm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11614,16,"ASM","American Samoa","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ASM/BSGM/2003/DTE/asm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11615,16,"ASM","American Samoa","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ASM/BSGM/2004/Binary/asm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11616,16,"ASM","American Samoa","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ASM/BSGM/2004/DTE/asm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11617,16,"ASM","American Samoa","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ASM/BSGM/2005/Binary/asm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11618,16,"ASM","American Samoa","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ASM/BSGM/2005/DTE/asm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11619,16,"ASM","American Samoa","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ASM/BSGM/2006/Binary/asm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11620,16,"ASM","American Samoa","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ASM/BSGM/2006/DTE/asm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11621,16,"ASM","American Samoa","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ASM/BSGM/2007/Binary/asm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11622,16,"ASM","American Samoa","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ASM/BSGM/2007/DTE/asm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11623,16,"ASM","American Samoa","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ASM/BSGM/2008/Binary/asm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11624,16,"ASM","American Samoa","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ASM/BSGM/2008/DTE/asm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11625,16,"ASM","American Samoa","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ASM/BSGM/2009/Binary/asm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11626,16,"ASM","American Samoa","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ASM/BSGM/2009/DTE/asm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11627,16,"ASM","American Samoa","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ASM/BSGM/2010/Binary/asm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11628,16,"ASM","American Samoa","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ASM/BSGM/2010/DTE/asm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11629,16,"ASM","American Samoa","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ASM/BSGM/2011/Binary/asm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11630,16,"ASM","American Samoa","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ASM/BSGM/2011/DTE/asm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11631,16,"ASM","American Samoa","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ASM/BSGM/2013/Binary/asm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11632,16,"ASM","American Samoa","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ASM/BSGM/2013/DTE/asm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11633,16,"ASM","American Samoa","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ASM/BSGM/2015/DTE/asm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11634,16,"ASM","American Samoa","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ASM/BSGM/2016/DTE/asm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11635,16,"ASM","American Samoa","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ASM/BSGM/2017/DTE/asm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11636,16,"ASM","American Samoa","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ASM/BSGM/2018/DTE/asm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11637,16,"ASM","American Samoa","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ASM/BSGM/2019/DTE/asm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11638,16,"ASM","American Samoa","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ASM/BSGM/2020/DTE/asm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11639,20,"AND","Andorra","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AND/BSGM/2001/Binary/and_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11640,20,"AND","Andorra","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AND/BSGM/2001/DTE/and_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11641,20,"AND","Andorra","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AND/BSGM/2002/Binary/and_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11642,20,"AND","Andorra","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AND/BSGM/2002/DTE/and_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11643,20,"AND","Andorra","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AND/BSGM/2003/Binary/and_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11644,20,"AND","Andorra","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AND/BSGM/2003/DTE/and_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11645,20,"AND","Andorra","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AND/BSGM/2004/Binary/and_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11646,20,"AND","Andorra","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AND/BSGM/2004/DTE/and_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11647,20,"AND","Andorra","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AND/BSGM/2005/Binary/and_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11648,20,"AND","Andorra","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AND/BSGM/2005/DTE/and_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11649,20,"AND","Andorra","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AND/BSGM/2006/Binary/and_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11650,20,"AND","Andorra","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AND/BSGM/2006/DTE/and_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11651,20,"AND","Andorra","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AND/BSGM/2007/Binary/and_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11652,20,"AND","Andorra","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AND/BSGM/2007/DTE/and_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11653,20,"AND","Andorra","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AND/BSGM/2008/Binary/and_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11654,20,"AND","Andorra","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AND/BSGM/2008/DTE/and_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11655,20,"AND","Andorra","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AND/BSGM/2009/Binary/and_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11656,20,"AND","Andorra","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AND/BSGM/2009/DTE/and_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11657,20,"AND","Andorra","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AND/BSGM/2010/Binary/and_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11658,20,"AND","Andorra","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AND/BSGM/2010/DTE/and_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11659,20,"AND","Andorra","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AND/BSGM/2011/Binary/and_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11660,20,"AND","Andorra","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AND/BSGM/2011/DTE/and_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11661,20,"AND","Andorra","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AND/BSGM/2013/Binary/and_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11662,20,"AND","Andorra","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AND/BSGM/2013/DTE/and_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11663,20,"AND","Andorra","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/AND/BSGM/2015/DTE/and_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11664,20,"AND","Andorra","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/AND/BSGM/2016/DTE/and_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11665,20,"AND","Andorra","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/AND/BSGM/2017/DTE/and_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11666,20,"AND","Andorra","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/AND/BSGM/2018/DTE/and_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11667,20,"AND","Andorra","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/AND/BSGM/2019/DTE/and_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11668,20,"AND","Andorra","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/AND/BSGM/2020/DTE/and_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11669,24,"AGO","Angola","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AGO/BSGM/2001/Binary/ago_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11670,24,"AGO","Angola","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AGO/BSGM/2001/DTE/ago_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11671,24,"AGO","Angola","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AGO/BSGM/2002/Binary/ago_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11672,24,"AGO","Angola","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AGO/BSGM/2002/DTE/ago_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11673,24,"AGO","Angola","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AGO/BSGM/2003/Binary/ago_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11674,24,"AGO","Angola","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AGO/BSGM/2003/DTE/ago_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11675,24,"AGO","Angola","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AGO/BSGM/2004/Binary/ago_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11676,24,"AGO","Angola","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AGO/BSGM/2004/DTE/ago_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11677,24,"AGO","Angola","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AGO/BSGM/2005/Binary/ago_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11678,24,"AGO","Angola","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AGO/BSGM/2005/DTE/ago_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11679,24,"AGO","Angola","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AGO/BSGM/2006/Binary/ago_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11680,24,"AGO","Angola","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AGO/BSGM/2006/DTE/ago_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11681,24,"AGO","Angola","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AGO/BSGM/2007/Binary/ago_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11682,24,"AGO","Angola","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AGO/BSGM/2007/DTE/ago_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11683,24,"AGO","Angola","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AGO/BSGM/2008/Binary/ago_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11684,24,"AGO","Angola","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AGO/BSGM/2008/DTE/ago_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11685,24,"AGO","Angola","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AGO/BSGM/2009/Binary/ago_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11686,24,"AGO","Angola","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AGO/BSGM/2009/DTE/ago_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11687,24,"AGO","Angola","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AGO/BSGM/2010/Binary/ago_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11688,24,"AGO","Angola","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AGO/BSGM/2010/DTE/ago_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11689,24,"AGO","Angola","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AGO/BSGM/2011/Binary/ago_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11690,24,"AGO","Angola","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AGO/BSGM/2011/DTE/ago_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11691,24,"AGO","Angola","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AGO/BSGM/2013/Binary/ago_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11692,24,"AGO","Angola","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AGO/BSGM/2013/DTE/ago_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11693,24,"AGO","Angola","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/AGO/BSGM/2015/DTE/ago_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11694,24,"AGO","Angola","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/AGO/BSGM/2016/DTE/ago_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11695,24,"AGO","Angola","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/AGO/BSGM/2017/DTE/ago_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11696,24,"AGO","Angola","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/AGO/BSGM/2018/DTE/ago_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11697,24,"AGO","Angola","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/AGO/BSGM/2019/DTE/ago_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11698,24,"AGO","Angola","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/AGO/BSGM/2020/DTE/ago_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11699,28,"ATG","Antigua and Barbuda","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ATG/BSGM/2001/Binary/atg_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11700,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ATG/BSGM/2001/DTE/atg_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11701,28,"ATG","Antigua and Barbuda","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ATG/BSGM/2002/Binary/atg_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11702,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ATG/BSGM/2002/DTE/atg_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11703,28,"ATG","Antigua and Barbuda","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ATG/BSGM/2003/Binary/atg_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11704,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ATG/BSGM/2003/DTE/atg_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11705,28,"ATG","Antigua and Barbuda","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ATG/BSGM/2004/Binary/atg_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11706,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ATG/BSGM/2004/DTE/atg_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11707,28,"ATG","Antigua and Barbuda","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ATG/BSGM/2005/Binary/atg_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11708,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ATG/BSGM/2005/DTE/atg_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11709,28,"ATG","Antigua and Barbuda","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ATG/BSGM/2006/Binary/atg_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11710,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ATG/BSGM/2006/DTE/atg_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11711,28,"ATG","Antigua and Barbuda","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ATG/BSGM/2007/Binary/atg_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11712,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ATG/BSGM/2007/DTE/atg_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11713,28,"ATG","Antigua and Barbuda","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ATG/BSGM/2008/Binary/atg_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11714,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ATG/BSGM/2008/DTE/atg_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11715,28,"ATG","Antigua and Barbuda","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ATG/BSGM/2009/Binary/atg_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11716,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ATG/BSGM/2009/DTE/atg_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11717,28,"ATG","Antigua and Barbuda","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ATG/BSGM/2010/Binary/atg_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11718,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ATG/BSGM/2010/DTE/atg_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11719,28,"ATG","Antigua and Barbuda","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ATG/BSGM/2011/Binary/atg_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11720,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ATG/BSGM/2011/DTE/atg_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11721,28,"ATG","Antigua and Barbuda","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ATG/BSGM/2013/Binary/atg_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11722,28,"ATG","Antigua and Barbuda","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ATG/BSGM/2013/DTE/atg_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11723,28,"ATG","Antigua and Barbuda","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ATG/BSGM/2015/DTE/atg_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11724,28,"ATG","Antigua and Barbuda","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ATG/BSGM/2016/DTE/atg_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11725,28,"ATG","Antigua and Barbuda","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ATG/BSGM/2017/DTE/atg_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11726,28,"ATG","Antigua and Barbuda","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ATG/BSGM/2018/DTE/atg_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11727,28,"ATG","Antigua and Barbuda","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ATG/BSGM/2019/DTE/atg_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11728,28,"ATG","Antigua and Barbuda","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ATG/BSGM/2020/DTE/atg_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11729,31,"AZE","Azerbaijan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AZE/BSGM/2001/Binary/aze_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11730,31,"AZE","Azerbaijan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AZE/BSGM/2001/DTE/aze_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11731,31,"AZE","Azerbaijan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AZE/BSGM/2002/Binary/aze_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11732,31,"AZE","Azerbaijan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AZE/BSGM/2002/DTE/aze_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11733,31,"AZE","Azerbaijan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AZE/BSGM/2003/Binary/aze_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11734,31,"AZE","Azerbaijan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AZE/BSGM/2003/DTE/aze_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11735,31,"AZE","Azerbaijan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AZE/BSGM/2004/Binary/aze_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11736,31,"AZE","Azerbaijan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AZE/BSGM/2004/DTE/aze_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11737,31,"AZE","Azerbaijan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AZE/BSGM/2005/Binary/aze_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11738,31,"AZE","Azerbaijan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AZE/BSGM/2005/DTE/aze_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11739,31,"AZE","Azerbaijan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AZE/BSGM/2006/Binary/aze_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11740,31,"AZE","Azerbaijan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AZE/BSGM/2006/DTE/aze_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11741,31,"AZE","Azerbaijan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AZE/BSGM/2007/Binary/aze_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11742,31,"AZE","Azerbaijan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AZE/BSGM/2007/DTE/aze_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11743,31,"AZE","Azerbaijan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AZE/BSGM/2008/Binary/aze_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11744,31,"AZE","Azerbaijan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AZE/BSGM/2008/DTE/aze_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11745,31,"AZE","Azerbaijan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AZE/BSGM/2009/Binary/aze_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11746,31,"AZE","Azerbaijan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AZE/BSGM/2009/DTE/aze_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11747,31,"AZE","Azerbaijan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AZE/BSGM/2010/Binary/aze_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11748,31,"AZE","Azerbaijan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AZE/BSGM/2010/DTE/aze_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11749,31,"AZE","Azerbaijan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AZE/BSGM/2011/Binary/aze_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11750,31,"AZE","Azerbaijan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AZE/BSGM/2011/DTE/aze_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11751,31,"AZE","Azerbaijan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AZE/BSGM/2013/Binary/aze_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11752,31,"AZE","Azerbaijan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AZE/BSGM/2013/DTE/aze_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11753,31,"AZE","Azerbaijan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/AZE/BSGM/2015/DTE/aze_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11754,31,"AZE","Azerbaijan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/AZE/BSGM/2016/DTE/aze_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11755,31,"AZE","Azerbaijan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/AZE/BSGM/2017/DTE/aze_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11756,31,"AZE","Azerbaijan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/AZE/BSGM/2018/DTE/aze_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11757,31,"AZE","Azerbaijan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/AZE/BSGM/2019/DTE/aze_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11758,31,"AZE","Azerbaijan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/AZE/BSGM/2020/DTE/aze_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11759,32,"ARG","Argentina","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ARG/BSGM/2001/Binary/arg_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11760,32,"ARG","Argentina","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ARG/BSGM/2001/DTE/arg_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11761,32,"ARG","Argentina","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ARG/BSGM/2002/Binary/arg_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11762,32,"ARG","Argentina","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ARG/BSGM/2002/DTE/arg_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11763,32,"ARG","Argentina","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ARG/BSGM/2003/Binary/arg_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11764,32,"ARG","Argentina","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ARG/BSGM/2003/DTE/arg_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11765,32,"ARG","Argentina","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ARG/BSGM/2004/Binary/arg_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11766,32,"ARG","Argentina","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ARG/BSGM/2004/DTE/arg_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11767,32,"ARG","Argentina","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ARG/BSGM/2005/Binary/arg_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11768,32,"ARG","Argentina","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ARG/BSGM/2005/DTE/arg_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11769,32,"ARG","Argentina","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ARG/BSGM/2006/Binary/arg_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11770,32,"ARG","Argentina","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ARG/BSGM/2006/DTE/arg_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11771,32,"ARG","Argentina","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ARG/BSGM/2007/Binary/arg_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11772,32,"ARG","Argentina","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ARG/BSGM/2007/DTE/arg_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11773,32,"ARG","Argentina","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ARG/BSGM/2008/Binary/arg_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11774,32,"ARG","Argentina","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ARG/BSGM/2008/DTE/arg_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11775,32,"ARG","Argentina","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ARG/BSGM/2009/Binary/arg_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11776,32,"ARG","Argentina","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ARG/BSGM/2009/DTE/arg_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11777,32,"ARG","Argentina","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ARG/BSGM/2010/Binary/arg_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11778,32,"ARG","Argentina","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ARG/BSGM/2010/DTE/arg_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11779,32,"ARG","Argentina","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ARG/BSGM/2011/Binary/arg_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11780,32,"ARG","Argentina","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ARG/BSGM/2011/DTE/arg_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11781,32,"ARG","Argentina","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ARG/BSGM/2013/Binary/arg_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11782,32,"ARG","Argentina","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ARG/BSGM/2013/DTE/arg_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11783,32,"ARG","Argentina","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ARG/BSGM/2015/DTE/arg_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11784,32,"ARG","Argentina","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ARG/BSGM/2016/DTE/arg_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11785,32,"ARG","Argentina","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ARG/BSGM/2017/DTE/arg_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11786,32,"ARG","Argentina","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ARG/BSGM/2018/DTE/arg_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11787,32,"ARG","Argentina","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ARG/BSGM/2019/DTE/arg_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11788,32,"ARG","Argentina","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ARG/BSGM/2020/DTE/arg_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11789,40,"AUT","Austria","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AUT/BSGM/2001/Binary/aut_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11790,40,"AUT","Austria","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AUT/BSGM/2001/DTE/aut_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11791,40,"AUT","Austria","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AUT/BSGM/2002/Binary/aut_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11792,40,"AUT","Austria","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AUT/BSGM/2002/DTE/aut_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11793,40,"AUT","Austria","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AUT/BSGM/2003/Binary/aut_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11794,40,"AUT","Austria","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AUT/BSGM/2003/DTE/aut_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11795,40,"AUT","Austria","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AUT/BSGM/2004/Binary/aut_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11796,40,"AUT","Austria","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AUT/BSGM/2004/DTE/aut_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11797,40,"AUT","Austria","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AUT/BSGM/2005/Binary/aut_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11798,40,"AUT","Austria","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AUT/BSGM/2005/DTE/aut_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11799,40,"AUT","Austria","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AUT/BSGM/2006/Binary/aut_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11800,40,"AUT","Austria","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AUT/BSGM/2006/DTE/aut_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11801,40,"AUT","Austria","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AUT/BSGM/2007/Binary/aut_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11802,40,"AUT","Austria","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AUT/BSGM/2007/DTE/aut_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11803,40,"AUT","Austria","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AUT/BSGM/2008/Binary/aut_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11804,40,"AUT","Austria","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AUT/BSGM/2008/DTE/aut_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11805,40,"AUT","Austria","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AUT/BSGM/2009/Binary/aut_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11806,40,"AUT","Austria","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AUT/BSGM/2009/DTE/aut_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11807,40,"AUT","Austria","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AUT/BSGM/2010/Binary/aut_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11808,40,"AUT","Austria","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AUT/BSGM/2010/DTE/aut_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11809,40,"AUT","Austria","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AUT/BSGM/2011/Binary/aut_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11810,40,"AUT","Austria","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AUT/BSGM/2011/DTE/aut_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11811,40,"AUT","Austria","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AUT/BSGM/2013/Binary/aut_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11812,40,"AUT","Austria","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AUT/BSGM/2013/DTE/aut_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11813,40,"AUT","Austria","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/AUT/BSGM/2015/DTE/aut_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11814,40,"AUT","Austria","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/AUT/BSGM/2016/DTE/aut_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11815,40,"AUT","Austria","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/AUT/BSGM/2017/DTE/aut_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11816,40,"AUT","Austria","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/AUT/BSGM/2018/DTE/aut_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11817,40,"AUT","Austria","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/AUT/BSGM/2019/DTE/aut_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11818,40,"AUT","Austria","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/AUT/BSGM/2020/DTE/aut_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11819,44,"BHS","Bahamas","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BHS/BSGM/2001/Binary/bhs_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11820,44,"BHS","Bahamas","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BHS/BSGM/2001/DTE/bhs_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11821,44,"BHS","Bahamas","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BHS/BSGM/2002/Binary/bhs_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11822,44,"BHS","Bahamas","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BHS/BSGM/2002/DTE/bhs_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11823,44,"BHS","Bahamas","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BHS/BSGM/2003/Binary/bhs_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11824,44,"BHS","Bahamas","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BHS/BSGM/2003/DTE/bhs_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11825,44,"BHS","Bahamas","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BHS/BSGM/2004/Binary/bhs_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11826,44,"BHS","Bahamas","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BHS/BSGM/2004/DTE/bhs_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11827,44,"BHS","Bahamas","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BHS/BSGM/2005/Binary/bhs_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11828,44,"BHS","Bahamas","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BHS/BSGM/2005/DTE/bhs_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11829,44,"BHS","Bahamas","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BHS/BSGM/2006/Binary/bhs_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11830,44,"BHS","Bahamas","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BHS/BSGM/2006/DTE/bhs_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11831,44,"BHS","Bahamas","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BHS/BSGM/2007/Binary/bhs_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11832,44,"BHS","Bahamas","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BHS/BSGM/2007/DTE/bhs_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11833,44,"BHS","Bahamas","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BHS/BSGM/2008/Binary/bhs_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11834,44,"BHS","Bahamas","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BHS/BSGM/2008/DTE/bhs_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11835,44,"BHS","Bahamas","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BHS/BSGM/2009/Binary/bhs_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11836,44,"BHS","Bahamas","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BHS/BSGM/2009/DTE/bhs_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11837,44,"BHS","Bahamas","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BHS/BSGM/2010/Binary/bhs_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11838,44,"BHS","Bahamas","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BHS/BSGM/2010/DTE/bhs_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11839,44,"BHS","Bahamas","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BHS/BSGM/2011/Binary/bhs_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11840,44,"BHS","Bahamas","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BHS/BSGM/2011/DTE/bhs_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11841,44,"BHS","Bahamas","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BHS/BSGM/2013/Binary/bhs_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11842,44,"BHS","Bahamas","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BHS/BSGM/2013/DTE/bhs_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11843,44,"BHS","Bahamas","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BHS/BSGM/2015/DTE/bhs_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11844,44,"BHS","Bahamas","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BHS/BSGM/2016/DTE/bhs_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11845,44,"BHS","Bahamas","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BHS/BSGM/2017/DTE/bhs_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11846,44,"BHS","Bahamas","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BHS/BSGM/2018/DTE/bhs_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11847,44,"BHS","Bahamas","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BHS/BSGM/2019/DTE/bhs_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11848,44,"BHS","Bahamas","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BHS/BSGM/2020/DTE/bhs_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11849,48,"BHR","Bahrain","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BHR/BSGM/2001/Binary/bhr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11850,48,"BHR","Bahrain","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BHR/BSGM/2001/DTE/bhr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11851,48,"BHR","Bahrain","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BHR/BSGM/2002/Binary/bhr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11852,48,"BHR","Bahrain","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BHR/BSGM/2002/DTE/bhr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11853,48,"BHR","Bahrain","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BHR/BSGM/2003/Binary/bhr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11854,48,"BHR","Bahrain","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BHR/BSGM/2003/DTE/bhr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11855,48,"BHR","Bahrain","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BHR/BSGM/2004/Binary/bhr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11856,48,"BHR","Bahrain","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BHR/BSGM/2004/DTE/bhr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11857,48,"BHR","Bahrain","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BHR/BSGM/2005/Binary/bhr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11858,48,"BHR","Bahrain","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BHR/BSGM/2005/DTE/bhr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11859,48,"BHR","Bahrain","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BHR/BSGM/2006/Binary/bhr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11860,48,"BHR","Bahrain","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BHR/BSGM/2006/DTE/bhr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11861,48,"BHR","Bahrain","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BHR/BSGM/2007/Binary/bhr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11862,48,"BHR","Bahrain","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BHR/BSGM/2007/DTE/bhr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11863,48,"BHR","Bahrain","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BHR/BSGM/2008/Binary/bhr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11864,48,"BHR","Bahrain","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BHR/BSGM/2008/DTE/bhr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11865,48,"BHR","Bahrain","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BHR/BSGM/2009/Binary/bhr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11866,48,"BHR","Bahrain","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BHR/BSGM/2009/DTE/bhr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11867,48,"BHR","Bahrain","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BHR/BSGM/2010/Binary/bhr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11868,48,"BHR","Bahrain","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BHR/BSGM/2010/DTE/bhr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11869,48,"BHR","Bahrain","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BHR/BSGM/2011/Binary/bhr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11870,48,"BHR","Bahrain","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BHR/BSGM/2011/DTE/bhr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11871,48,"BHR","Bahrain","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BHR/BSGM/2013/Binary/bhr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11872,48,"BHR","Bahrain","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BHR/BSGM/2013/DTE/bhr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11873,48,"BHR","Bahrain","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BHR/BSGM/2015/DTE/bhr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11874,48,"BHR","Bahrain","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BHR/BSGM/2016/DTE/bhr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11875,48,"BHR","Bahrain","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BHR/BSGM/2017/DTE/bhr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11876,48,"BHR","Bahrain","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BHR/BSGM/2018/DTE/bhr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11877,48,"BHR","Bahrain","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BHR/BSGM/2019/DTE/bhr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11878,48,"BHR","Bahrain","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BHR/BSGM/2020/DTE/bhr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11879,50,"BGD","Bangladesh","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BGD/BSGM/2001/Binary/bgd_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11880,50,"BGD","Bangladesh","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BGD/BSGM/2001/DTE/bgd_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11881,50,"BGD","Bangladesh","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BGD/BSGM/2002/Binary/bgd_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11882,50,"BGD","Bangladesh","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BGD/BSGM/2002/DTE/bgd_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11883,50,"BGD","Bangladesh","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BGD/BSGM/2003/Binary/bgd_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11884,50,"BGD","Bangladesh","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BGD/BSGM/2003/DTE/bgd_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11885,50,"BGD","Bangladesh","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BGD/BSGM/2004/Binary/bgd_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11886,50,"BGD","Bangladesh","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BGD/BSGM/2004/DTE/bgd_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11887,50,"BGD","Bangladesh","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BGD/BSGM/2005/Binary/bgd_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11888,50,"BGD","Bangladesh","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BGD/BSGM/2005/DTE/bgd_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11889,50,"BGD","Bangladesh","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BGD/BSGM/2006/Binary/bgd_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11890,50,"BGD","Bangladesh","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BGD/BSGM/2006/DTE/bgd_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11891,50,"BGD","Bangladesh","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BGD/BSGM/2007/Binary/bgd_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11892,50,"BGD","Bangladesh","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BGD/BSGM/2007/DTE/bgd_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11893,50,"BGD","Bangladesh","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BGD/BSGM/2008/Binary/bgd_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11894,50,"BGD","Bangladesh","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BGD/BSGM/2008/DTE/bgd_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11895,50,"BGD","Bangladesh","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BGD/BSGM/2009/Binary/bgd_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11896,50,"BGD","Bangladesh","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BGD/BSGM/2009/DTE/bgd_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11897,50,"BGD","Bangladesh","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BGD/BSGM/2010/Binary/bgd_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11898,50,"BGD","Bangladesh","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BGD/BSGM/2010/DTE/bgd_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11899,50,"BGD","Bangladesh","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BGD/BSGM/2011/Binary/bgd_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11900,50,"BGD","Bangladesh","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BGD/BSGM/2011/DTE/bgd_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11901,50,"BGD","Bangladesh","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BGD/BSGM/2013/Binary/bgd_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11902,50,"BGD","Bangladesh","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BGD/BSGM/2013/DTE/bgd_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11903,50,"BGD","Bangladesh","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BGD/BSGM/2015/DTE/bgd_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11904,50,"BGD","Bangladesh","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BGD/BSGM/2016/DTE/bgd_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11905,50,"BGD","Bangladesh","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BGD/BSGM/2017/DTE/bgd_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11906,50,"BGD","Bangladesh","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BGD/BSGM/2018/DTE/bgd_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11907,50,"BGD","Bangladesh","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BGD/BSGM/2019/DTE/bgd_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11908,50,"BGD","Bangladesh","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BGD/BSGM/2020/DTE/bgd_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11909,51,"ARM","Armenia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ARM/BSGM/2001/Binary/arm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11910,51,"ARM","Armenia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ARM/BSGM/2001/DTE/arm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11911,51,"ARM","Armenia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ARM/BSGM/2002/Binary/arm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11912,51,"ARM","Armenia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ARM/BSGM/2002/DTE/arm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11913,51,"ARM","Armenia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ARM/BSGM/2003/Binary/arm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11914,51,"ARM","Armenia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ARM/BSGM/2003/DTE/arm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11915,51,"ARM","Armenia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ARM/BSGM/2004/Binary/arm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11916,51,"ARM","Armenia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ARM/BSGM/2004/DTE/arm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11917,51,"ARM","Armenia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ARM/BSGM/2005/Binary/arm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11918,51,"ARM","Armenia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ARM/BSGM/2005/DTE/arm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11919,51,"ARM","Armenia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ARM/BSGM/2006/Binary/arm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11920,51,"ARM","Armenia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ARM/BSGM/2006/DTE/arm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11921,51,"ARM","Armenia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ARM/BSGM/2007/Binary/arm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11922,51,"ARM","Armenia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ARM/BSGM/2007/DTE/arm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11923,51,"ARM","Armenia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ARM/BSGM/2008/Binary/arm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11924,51,"ARM","Armenia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ARM/BSGM/2008/DTE/arm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11925,51,"ARM","Armenia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ARM/BSGM/2009/Binary/arm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11926,51,"ARM","Armenia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ARM/BSGM/2009/DTE/arm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11927,51,"ARM","Armenia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ARM/BSGM/2010/Binary/arm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11928,51,"ARM","Armenia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ARM/BSGM/2010/DTE/arm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11929,51,"ARM","Armenia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ARM/BSGM/2011/Binary/arm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11930,51,"ARM","Armenia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ARM/BSGM/2011/DTE/arm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11931,51,"ARM","Armenia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ARM/BSGM/2013/Binary/arm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11932,51,"ARM","Armenia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ARM/BSGM/2013/DTE/arm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11933,51,"ARM","Armenia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ARM/BSGM/2015/DTE/arm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11934,51,"ARM","Armenia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ARM/BSGM/2016/DTE/arm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11935,51,"ARM","Armenia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ARM/BSGM/2017/DTE/arm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11936,51,"ARM","Armenia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ARM/BSGM/2018/DTE/arm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11937,51,"ARM","Armenia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ARM/BSGM/2019/DTE/arm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11938,51,"ARM","Armenia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ARM/BSGM/2020/DTE/arm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11939,52,"BRB","Barbados","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BRB/BSGM/2001/Binary/brb_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11940,52,"BRB","Barbados","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BRB/BSGM/2001/DTE/brb_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11941,52,"BRB","Barbados","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BRB/BSGM/2002/Binary/brb_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11942,52,"BRB","Barbados","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BRB/BSGM/2002/DTE/brb_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11943,52,"BRB","Barbados","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BRB/BSGM/2003/Binary/brb_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11944,52,"BRB","Barbados","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BRB/BSGM/2003/DTE/brb_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11945,52,"BRB","Barbados","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BRB/BSGM/2004/Binary/brb_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11946,52,"BRB","Barbados","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BRB/BSGM/2004/DTE/brb_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11947,52,"BRB","Barbados","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BRB/BSGM/2005/Binary/brb_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11948,52,"BRB","Barbados","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BRB/BSGM/2005/DTE/brb_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11949,52,"BRB","Barbados","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BRB/BSGM/2006/Binary/brb_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11950,52,"BRB","Barbados","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BRB/BSGM/2006/DTE/brb_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11951,52,"BRB","Barbados","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BRB/BSGM/2007/Binary/brb_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11952,52,"BRB","Barbados","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BRB/BSGM/2007/DTE/brb_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11953,52,"BRB","Barbados","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BRB/BSGM/2008/Binary/brb_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11954,52,"BRB","Barbados","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BRB/BSGM/2008/DTE/brb_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11955,52,"BRB","Barbados","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BRB/BSGM/2009/Binary/brb_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11956,52,"BRB","Barbados","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BRB/BSGM/2009/DTE/brb_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11957,52,"BRB","Barbados","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BRB/BSGM/2010/Binary/brb_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11958,52,"BRB","Barbados","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BRB/BSGM/2010/DTE/brb_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11959,52,"BRB","Barbados","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BRB/BSGM/2011/Binary/brb_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11960,52,"BRB","Barbados","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BRB/BSGM/2011/DTE/brb_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11961,52,"BRB","Barbados","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BRB/BSGM/2013/Binary/brb_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11962,52,"BRB","Barbados","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BRB/BSGM/2013/DTE/brb_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11963,52,"BRB","Barbados","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BRB/BSGM/2015/DTE/brb_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11964,52,"BRB","Barbados","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BRB/BSGM/2016/DTE/brb_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11965,52,"BRB","Barbados","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BRB/BSGM/2017/DTE/brb_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11966,52,"BRB","Barbados","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BRB/BSGM/2018/DTE/brb_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11967,52,"BRB","Barbados","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BRB/BSGM/2019/DTE/brb_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11968,52,"BRB","Barbados","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BRB/BSGM/2020/DTE/brb_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11969,56,"BEL","Belgium","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BEL/BSGM/2001/Binary/bel_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
11970,56,"BEL","Belgium","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BEL/BSGM/2001/DTE/bel_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
11971,56,"BEL","Belgium","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BEL/BSGM/2002/Binary/bel_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
11972,56,"BEL","Belgium","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BEL/BSGM/2002/DTE/bel_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
11973,56,"BEL","Belgium","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BEL/BSGM/2003/Binary/bel_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
11974,56,"BEL","Belgium","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BEL/BSGM/2003/DTE/bel_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
11975,56,"BEL","Belgium","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BEL/BSGM/2004/Binary/bel_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
11976,56,"BEL","Belgium","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BEL/BSGM/2004/DTE/bel_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
11977,56,"BEL","Belgium","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BEL/BSGM/2005/Binary/bel_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
11978,56,"BEL","Belgium","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BEL/BSGM/2005/DTE/bel_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
11979,56,"BEL","Belgium","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BEL/BSGM/2006/Binary/bel_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
11980,56,"BEL","Belgium","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BEL/BSGM/2006/DTE/bel_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
11981,56,"BEL","Belgium","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BEL/BSGM/2007/Binary/bel_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
11982,56,"BEL","Belgium","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BEL/BSGM/2007/DTE/bel_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
11983,56,"BEL","Belgium","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BEL/BSGM/2008/Binary/bel_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
11984,56,"BEL","Belgium","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BEL/BSGM/2008/DTE/bel_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
11985,56,"BEL","Belgium","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BEL/BSGM/2009/Binary/bel_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
11986,56,"BEL","Belgium","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BEL/BSGM/2009/DTE/bel_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
11987,56,"BEL","Belgium","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BEL/BSGM/2010/Binary/bel_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
11988,56,"BEL","Belgium","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BEL/BSGM/2010/DTE/bel_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
11989,56,"BEL","Belgium","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BEL/BSGM/2011/Binary/bel_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
11990,56,"BEL","Belgium","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BEL/BSGM/2011/DTE/bel_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
11991,56,"BEL","Belgium","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BEL/BSGM/2013/Binary/bel_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
11992,56,"BEL","Belgium","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BEL/BSGM/2013/DTE/bel_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
11993,56,"BEL","Belgium","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BEL/BSGM/2015/DTE/bel_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
11994,56,"BEL","Belgium","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BEL/BSGM/2016/DTE/bel_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
11995,56,"BEL","Belgium","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BEL/BSGM/2017/DTE/bel_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
11996,56,"BEL","Belgium","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BEL/BSGM/2018/DTE/bel_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
11997,56,"BEL","Belgium","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BEL/BSGM/2019/DTE/bel_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
11998,56,"BEL","Belgium","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BEL/BSGM/2020/DTE/bel_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
11999,60,"BMU","Bermuda","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BMU/BSGM/2001/Binary/bmu_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12000,60,"BMU","Bermuda","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BMU/BSGM/2001/DTE/bmu_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12001,60,"BMU","Bermuda","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BMU/BSGM/2002/Binary/bmu_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12002,60,"BMU","Bermuda","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BMU/BSGM/2002/DTE/bmu_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12003,60,"BMU","Bermuda","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BMU/BSGM/2003/Binary/bmu_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12004,60,"BMU","Bermuda","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BMU/BSGM/2003/DTE/bmu_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12005,60,"BMU","Bermuda","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BMU/BSGM/2004/Binary/bmu_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12006,60,"BMU","Bermuda","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BMU/BSGM/2004/DTE/bmu_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12007,60,"BMU","Bermuda","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BMU/BSGM/2005/Binary/bmu_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12008,60,"BMU","Bermuda","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BMU/BSGM/2005/DTE/bmu_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12009,60,"BMU","Bermuda","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BMU/BSGM/2006/Binary/bmu_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12010,60,"BMU","Bermuda","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BMU/BSGM/2006/DTE/bmu_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12011,60,"BMU","Bermuda","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BMU/BSGM/2007/Binary/bmu_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12012,60,"BMU","Bermuda","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BMU/BSGM/2007/DTE/bmu_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12013,60,"BMU","Bermuda","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BMU/BSGM/2008/Binary/bmu_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12014,60,"BMU","Bermuda","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BMU/BSGM/2008/DTE/bmu_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12015,60,"BMU","Bermuda","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BMU/BSGM/2009/Binary/bmu_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12016,60,"BMU","Bermuda","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BMU/BSGM/2009/DTE/bmu_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12017,60,"BMU","Bermuda","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BMU/BSGM/2010/Binary/bmu_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12018,60,"BMU","Bermuda","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BMU/BSGM/2010/DTE/bmu_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12019,60,"BMU","Bermuda","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BMU/BSGM/2011/Binary/bmu_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12020,60,"BMU","Bermuda","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BMU/BSGM/2011/DTE/bmu_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12021,60,"BMU","Bermuda","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BMU/BSGM/2013/Binary/bmu_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12022,60,"BMU","Bermuda","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BMU/BSGM/2013/DTE/bmu_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12023,60,"BMU","Bermuda","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BMU/BSGM/2015/DTE/bmu_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12024,60,"BMU","Bermuda","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BMU/BSGM/2016/DTE/bmu_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12025,60,"BMU","Bermuda","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BMU/BSGM/2017/DTE/bmu_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12026,60,"BMU","Bermuda","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BMU/BSGM/2018/DTE/bmu_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12027,60,"BMU","Bermuda","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BMU/BSGM/2019/DTE/bmu_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12028,60,"BMU","Bermuda","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BMU/BSGM/2020/DTE/bmu_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12029,64,"BTN","Bhutan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BTN/BSGM/2001/Binary/btn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12030,64,"BTN","Bhutan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BTN/BSGM/2001/DTE/btn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12031,64,"BTN","Bhutan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BTN/BSGM/2002/Binary/btn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12032,64,"BTN","Bhutan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BTN/BSGM/2002/DTE/btn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12033,64,"BTN","Bhutan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BTN/BSGM/2003/Binary/btn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12034,64,"BTN","Bhutan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BTN/BSGM/2003/DTE/btn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12035,64,"BTN","Bhutan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BTN/BSGM/2004/Binary/btn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12036,64,"BTN","Bhutan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BTN/BSGM/2004/DTE/btn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12037,64,"BTN","Bhutan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BTN/BSGM/2005/Binary/btn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12038,64,"BTN","Bhutan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BTN/BSGM/2005/DTE/btn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12039,64,"BTN","Bhutan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BTN/BSGM/2006/Binary/btn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12040,64,"BTN","Bhutan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BTN/BSGM/2006/DTE/btn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12041,64,"BTN","Bhutan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BTN/BSGM/2007/Binary/btn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12042,64,"BTN","Bhutan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BTN/BSGM/2007/DTE/btn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12043,64,"BTN","Bhutan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BTN/BSGM/2008/Binary/btn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12044,64,"BTN","Bhutan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BTN/BSGM/2008/DTE/btn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12045,64,"BTN","Bhutan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BTN/BSGM/2009/Binary/btn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12046,64,"BTN","Bhutan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BTN/BSGM/2009/DTE/btn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12047,64,"BTN","Bhutan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BTN/BSGM/2010/Binary/btn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12048,64,"BTN","Bhutan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BTN/BSGM/2010/DTE/btn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12049,64,"BTN","Bhutan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BTN/BSGM/2011/Binary/btn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12050,64,"BTN","Bhutan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BTN/BSGM/2011/DTE/btn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12051,64,"BTN","Bhutan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BTN/BSGM/2013/Binary/btn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12052,64,"BTN","Bhutan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BTN/BSGM/2013/DTE/btn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12053,64,"BTN","Bhutan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BTN/BSGM/2015/DTE/btn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12054,64,"BTN","Bhutan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BTN/BSGM/2016/DTE/btn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12055,64,"BTN","Bhutan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BTN/BSGM/2017/DTE/btn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12056,64,"BTN","Bhutan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BTN/BSGM/2018/DTE/btn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12057,64,"BTN","Bhutan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BTN/BSGM/2019/DTE/btn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12058,64,"BTN","Bhutan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BTN/BSGM/2020/DTE/btn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12059,68,"BOL","Bolivia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BOL/BSGM/2001/Binary/bol_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12060,68,"BOL","Bolivia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BOL/BSGM/2001/DTE/bol_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12061,68,"BOL","Bolivia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BOL/BSGM/2002/Binary/bol_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12062,68,"BOL","Bolivia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BOL/BSGM/2002/DTE/bol_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12063,68,"BOL","Bolivia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BOL/BSGM/2003/Binary/bol_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12064,68,"BOL","Bolivia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BOL/BSGM/2003/DTE/bol_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12065,68,"BOL","Bolivia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BOL/BSGM/2004/Binary/bol_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12066,68,"BOL","Bolivia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BOL/BSGM/2004/DTE/bol_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12067,68,"BOL","Bolivia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BOL/BSGM/2005/Binary/bol_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12068,68,"BOL","Bolivia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BOL/BSGM/2005/DTE/bol_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12069,68,"BOL","Bolivia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BOL/BSGM/2006/Binary/bol_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12070,68,"BOL","Bolivia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BOL/BSGM/2006/DTE/bol_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12071,68,"BOL","Bolivia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BOL/BSGM/2007/Binary/bol_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12072,68,"BOL","Bolivia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BOL/BSGM/2007/DTE/bol_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12073,68,"BOL","Bolivia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BOL/BSGM/2008/Binary/bol_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12074,68,"BOL","Bolivia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BOL/BSGM/2008/DTE/bol_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12075,68,"BOL","Bolivia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BOL/BSGM/2009/Binary/bol_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12076,68,"BOL","Bolivia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BOL/BSGM/2009/DTE/bol_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12077,68,"BOL","Bolivia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BOL/BSGM/2010/Binary/bol_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12078,68,"BOL","Bolivia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BOL/BSGM/2010/DTE/bol_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12079,68,"BOL","Bolivia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BOL/BSGM/2011/Binary/bol_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12080,68,"BOL","Bolivia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BOL/BSGM/2011/DTE/bol_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12081,68,"BOL","Bolivia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BOL/BSGM/2013/Binary/bol_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12082,68,"BOL","Bolivia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BOL/BSGM/2013/DTE/bol_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12083,68,"BOL","Bolivia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BOL/BSGM/2015/DTE/bol_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12084,68,"BOL","Bolivia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BOL/BSGM/2016/DTE/bol_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12085,68,"BOL","Bolivia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BOL/BSGM/2017/DTE/bol_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12086,68,"BOL","Bolivia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BOL/BSGM/2018/DTE/bol_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12087,68,"BOL","Bolivia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BOL/BSGM/2019/DTE/bol_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12088,68,"BOL","Bolivia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BOL/BSGM/2020/DTE/bol_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12089,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BIH/BSGM/2001/Binary/bih_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12090,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BIH/BSGM/2001/DTE/bih_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12091,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BIH/BSGM/2002/Binary/bih_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12092,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BIH/BSGM/2002/DTE/bih_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12093,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BIH/BSGM/2003/Binary/bih_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12094,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BIH/BSGM/2003/DTE/bih_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12095,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BIH/BSGM/2004/Binary/bih_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12096,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BIH/BSGM/2004/DTE/bih_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12097,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BIH/BSGM/2005/Binary/bih_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12098,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BIH/BSGM/2005/DTE/bih_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12099,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BIH/BSGM/2006/Binary/bih_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12100,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BIH/BSGM/2006/DTE/bih_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12101,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BIH/BSGM/2007/Binary/bih_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12102,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BIH/BSGM/2007/DTE/bih_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12103,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BIH/BSGM/2008/Binary/bih_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12104,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BIH/BSGM/2008/DTE/bih_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12105,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BIH/BSGM/2009/Binary/bih_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12106,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BIH/BSGM/2009/DTE/bih_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12107,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BIH/BSGM/2010/Binary/bih_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12108,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BIH/BSGM/2010/DTE/bih_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12109,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BIH/BSGM/2011/Binary/bih_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12110,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BIH/BSGM/2011/DTE/bih_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12111,70,"BIH","Bosnia and Herzegovina","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BIH/BSGM/2013/Binary/bih_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12112,70,"BIH","Bosnia and Herzegovina","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BIH/BSGM/2013/DTE/bih_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12113,70,"BIH","Bosnia and Herzegovina","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BIH/BSGM/2015/DTE/bih_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12114,70,"BIH","Bosnia and Herzegovina","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BIH/BSGM/2016/DTE/bih_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12115,70,"BIH","Bosnia and Herzegovina","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BIH/BSGM/2017/DTE/bih_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12116,70,"BIH","Bosnia and Herzegovina","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BIH/BSGM/2018/DTE/bih_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12117,70,"BIH","Bosnia and Herzegovina","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BIH/BSGM/2019/DTE/bih_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12118,70,"BIH","Bosnia and Herzegovina","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BIH/BSGM/2020/DTE/bih_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12119,72,"BWA","Botswana","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BWA/BSGM/2001/Binary/bwa_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12120,72,"BWA","Botswana","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BWA/BSGM/2001/DTE/bwa_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12121,72,"BWA","Botswana","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BWA/BSGM/2002/Binary/bwa_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12122,72,"BWA","Botswana","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BWA/BSGM/2002/DTE/bwa_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12123,72,"BWA","Botswana","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BWA/BSGM/2003/Binary/bwa_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12124,72,"BWA","Botswana","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BWA/BSGM/2003/DTE/bwa_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12125,72,"BWA","Botswana","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BWA/BSGM/2004/Binary/bwa_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12126,72,"BWA","Botswana","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BWA/BSGM/2004/DTE/bwa_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12127,72,"BWA","Botswana","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BWA/BSGM/2005/Binary/bwa_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12128,72,"BWA","Botswana","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BWA/BSGM/2005/DTE/bwa_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12129,72,"BWA","Botswana","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BWA/BSGM/2006/Binary/bwa_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12130,72,"BWA","Botswana","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BWA/BSGM/2006/DTE/bwa_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12131,72,"BWA","Botswana","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BWA/BSGM/2007/Binary/bwa_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12132,72,"BWA","Botswana","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BWA/BSGM/2007/DTE/bwa_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12133,72,"BWA","Botswana","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BWA/BSGM/2008/Binary/bwa_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12134,72,"BWA","Botswana","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BWA/BSGM/2008/DTE/bwa_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12135,72,"BWA","Botswana","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BWA/BSGM/2009/Binary/bwa_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12136,72,"BWA","Botswana","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BWA/BSGM/2009/DTE/bwa_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12137,72,"BWA","Botswana","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BWA/BSGM/2010/Binary/bwa_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12138,72,"BWA","Botswana","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BWA/BSGM/2010/DTE/bwa_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12139,72,"BWA","Botswana","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BWA/BSGM/2011/Binary/bwa_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12140,72,"BWA","Botswana","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BWA/BSGM/2011/DTE/bwa_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12141,72,"BWA","Botswana","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BWA/BSGM/2013/Binary/bwa_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12142,72,"BWA","Botswana","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BWA/BSGM/2013/DTE/bwa_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12143,72,"BWA","Botswana","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BWA/BSGM/2015/DTE/bwa_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12144,72,"BWA","Botswana","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BWA/BSGM/2016/DTE/bwa_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12145,72,"BWA","Botswana","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BWA/BSGM/2017/DTE/bwa_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12146,72,"BWA","Botswana","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BWA/BSGM/2018/DTE/bwa_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12147,72,"BWA","Botswana","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BWA/BSGM/2019/DTE/bwa_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12148,72,"BWA","Botswana","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BWA/BSGM/2020/DTE/bwa_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12149,74,"BVT","Bouvet Island","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BVT/BSGM/2001/Binary/bvt_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12150,74,"BVT","Bouvet Island","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BVT/BSGM/2001/DTE/bvt_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12151,74,"BVT","Bouvet Island","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BVT/BSGM/2002/Binary/bvt_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12152,74,"BVT","Bouvet Island","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BVT/BSGM/2002/DTE/bvt_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12153,74,"BVT","Bouvet Island","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BVT/BSGM/2003/Binary/bvt_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12154,74,"BVT","Bouvet Island","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BVT/BSGM/2003/DTE/bvt_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12155,74,"BVT","Bouvet Island","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BVT/BSGM/2004/Binary/bvt_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12156,74,"BVT","Bouvet Island","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BVT/BSGM/2004/DTE/bvt_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12157,74,"BVT","Bouvet Island","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BVT/BSGM/2005/Binary/bvt_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12158,74,"BVT","Bouvet Island","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BVT/BSGM/2005/DTE/bvt_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12159,74,"BVT","Bouvet Island","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BVT/BSGM/2006/Binary/bvt_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12160,74,"BVT","Bouvet Island","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BVT/BSGM/2006/DTE/bvt_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12161,74,"BVT","Bouvet Island","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BVT/BSGM/2007/Binary/bvt_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12162,74,"BVT","Bouvet Island","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BVT/BSGM/2007/DTE/bvt_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12163,74,"BVT","Bouvet Island","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BVT/BSGM/2008/Binary/bvt_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12164,74,"BVT","Bouvet Island","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BVT/BSGM/2008/DTE/bvt_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12165,74,"BVT","Bouvet Island","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BVT/BSGM/2009/Binary/bvt_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12166,74,"BVT","Bouvet Island","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BVT/BSGM/2009/DTE/bvt_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12167,74,"BVT","Bouvet Island","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BVT/BSGM/2010/Binary/bvt_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12168,74,"BVT","Bouvet Island","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BVT/BSGM/2010/DTE/bvt_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12169,74,"BVT","Bouvet Island","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BVT/BSGM/2011/Binary/bvt_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12170,74,"BVT","Bouvet Island","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BVT/BSGM/2011/DTE/bvt_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12171,74,"BVT","Bouvet Island","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BVT/BSGM/2013/Binary/bvt_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12172,74,"BVT","Bouvet Island","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BVT/BSGM/2013/DTE/bvt_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12173,74,"BVT","Bouvet Island","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BVT/BSGM/2015/DTE/bvt_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12174,74,"BVT","Bouvet Island","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BVT/BSGM/2016/DTE/bvt_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12175,74,"BVT","Bouvet Island","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BVT/BSGM/2017/DTE/bvt_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12176,74,"BVT","Bouvet Island","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BVT/BSGM/2018/DTE/bvt_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12177,74,"BVT","Bouvet Island","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BVT/BSGM/2019/DTE/bvt_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12178,74,"BVT","Bouvet Island","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BVT/BSGM/2020/DTE/bvt_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12179,84,"BLZ","Belize","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2001/Binary/blz_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12180,84,"BLZ","Belize","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2001/DTE/blz_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12181,84,"BLZ","Belize","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2002/Binary/blz_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12182,84,"BLZ","Belize","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2002/DTE/blz_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12183,84,"BLZ","Belize","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2003/Binary/blz_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12184,84,"BLZ","Belize","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2003/DTE/blz_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12185,84,"BLZ","Belize","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2004/Binary/blz_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12186,84,"BLZ","Belize","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2004/DTE/blz_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12187,84,"BLZ","Belize","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2005/Binary/blz_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12188,84,"BLZ","Belize","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2005/DTE/blz_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12189,84,"BLZ","Belize","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2006/Binary/blz_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12190,84,"BLZ","Belize","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2006/DTE/blz_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12191,84,"BLZ","Belize","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2007/Binary/blz_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12192,84,"BLZ","Belize","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2007/DTE/blz_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12193,84,"BLZ","Belize","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2008/Binary/blz_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12194,84,"BLZ","Belize","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2008/DTE/blz_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12195,84,"BLZ","Belize","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2009/Binary/blz_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12196,84,"BLZ","Belize","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2009/DTE/blz_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12197,84,"BLZ","Belize","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2010/Binary/blz_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12198,84,"BLZ","Belize","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2010/DTE/blz_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12199,84,"BLZ","Belize","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2011/Binary/blz_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12200,84,"BLZ","Belize","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2011/DTE/blz_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12201,84,"BLZ","Belize","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2013/Binary/blz_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12202,84,"BLZ","Belize","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2013/DTE/blz_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12203,84,"BLZ","Belize","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2015/DTE/blz_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12204,84,"BLZ","Belize","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2016/DTE/blz_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12205,84,"BLZ","Belize","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2017/DTE/blz_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12206,84,"BLZ","Belize","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2018/DTE/blz_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12207,84,"BLZ","Belize","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2019/DTE/blz_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12208,84,"BLZ","Belize","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BLZ/BSGM/2020/DTE/blz_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12209,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IOT/BSGM/2001/Binary/iot_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12210,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IOT/BSGM/2001/DTE/iot_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12211,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IOT/BSGM/2002/Binary/iot_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12212,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IOT/BSGM/2002/DTE/iot_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12213,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IOT/BSGM/2003/Binary/iot_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12214,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IOT/BSGM/2003/DTE/iot_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12215,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IOT/BSGM/2004/Binary/iot_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12216,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IOT/BSGM/2004/DTE/iot_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12217,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IOT/BSGM/2005/Binary/iot_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12218,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IOT/BSGM/2005/DTE/iot_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12219,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IOT/BSGM/2006/Binary/iot_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12220,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IOT/BSGM/2006/DTE/iot_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12221,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IOT/BSGM/2007/Binary/iot_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12222,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IOT/BSGM/2007/DTE/iot_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12223,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IOT/BSGM/2008/Binary/iot_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12224,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IOT/BSGM/2008/DTE/iot_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12225,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IOT/BSGM/2009/Binary/iot_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12226,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IOT/BSGM/2009/DTE/iot_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12227,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IOT/BSGM/2010/Binary/iot_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12228,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IOT/BSGM/2010/DTE/iot_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12229,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IOT/BSGM/2011/Binary/iot_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12230,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IOT/BSGM/2011/DTE/iot_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12231,86,"IOT","British Indian Ocean Territory","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IOT/BSGM/2013/Binary/iot_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12232,86,"IOT","British Indian Ocean Territory","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IOT/BSGM/2013/DTE/iot_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12233,86,"IOT","British Indian Ocean Territory","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/IOT/BSGM/2015/DTE/iot_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12234,86,"IOT","British Indian Ocean Territory","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/IOT/BSGM/2016/DTE/iot_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12235,86,"IOT","British Indian Ocean Territory","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/IOT/BSGM/2017/DTE/iot_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12236,86,"IOT","British Indian Ocean Territory","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/IOT/BSGM/2018/DTE/iot_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12237,86,"IOT","British Indian Ocean Territory","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/IOT/BSGM/2019/DTE/iot_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12238,86,"IOT","British Indian Ocean Territory","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/IOT/BSGM/2020/DTE/iot_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12239,90,"SLB","Solomon Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SLB/BSGM/2001/Binary/slb_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12240,90,"SLB","Solomon Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SLB/BSGM/2001/DTE/slb_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12241,90,"SLB","Solomon Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SLB/BSGM/2002/Binary/slb_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12242,90,"SLB","Solomon Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SLB/BSGM/2002/DTE/slb_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12243,90,"SLB","Solomon Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SLB/BSGM/2003/Binary/slb_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12244,90,"SLB","Solomon Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SLB/BSGM/2003/DTE/slb_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12245,90,"SLB","Solomon Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SLB/BSGM/2004/Binary/slb_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12246,90,"SLB","Solomon Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SLB/BSGM/2004/DTE/slb_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12247,90,"SLB","Solomon Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SLB/BSGM/2005/Binary/slb_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12248,90,"SLB","Solomon Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SLB/BSGM/2005/DTE/slb_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12249,90,"SLB","Solomon Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SLB/BSGM/2006/Binary/slb_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12250,90,"SLB","Solomon Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SLB/BSGM/2006/DTE/slb_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12251,90,"SLB","Solomon Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SLB/BSGM/2007/Binary/slb_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12252,90,"SLB","Solomon Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SLB/BSGM/2007/DTE/slb_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12253,90,"SLB","Solomon Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SLB/BSGM/2008/Binary/slb_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12254,90,"SLB","Solomon Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SLB/BSGM/2008/DTE/slb_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12255,90,"SLB","Solomon Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SLB/BSGM/2009/Binary/slb_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12256,90,"SLB","Solomon Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SLB/BSGM/2009/DTE/slb_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12257,90,"SLB","Solomon Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SLB/BSGM/2010/Binary/slb_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12258,90,"SLB","Solomon Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SLB/BSGM/2010/DTE/slb_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12259,90,"SLB","Solomon Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SLB/BSGM/2011/Binary/slb_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12260,90,"SLB","Solomon Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SLB/BSGM/2011/DTE/slb_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12261,90,"SLB","Solomon Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SLB/BSGM/2013/Binary/slb_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12262,90,"SLB","Solomon Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SLB/BSGM/2013/DTE/slb_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12263,90,"SLB","Solomon Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SLB/BSGM/2015/DTE/slb_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12264,90,"SLB","Solomon Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SLB/BSGM/2016/DTE/slb_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12265,90,"SLB","Solomon Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SLB/BSGM/2017/DTE/slb_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12266,90,"SLB","Solomon Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SLB/BSGM/2018/DTE/slb_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12267,90,"SLB","Solomon Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SLB/BSGM/2019/DTE/slb_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12268,90,"SLB","Solomon Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SLB/BSGM/2020/DTE/slb_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12269,92,"VGB","British Virgin Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VGB/BSGM/2001/Binary/vgb_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12270,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VGB/BSGM/2001/DTE/vgb_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12271,92,"VGB","British Virgin Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VGB/BSGM/2002/Binary/vgb_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12272,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VGB/BSGM/2002/DTE/vgb_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12273,92,"VGB","British Virgin Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VGB/BSGM/2003/Binary/vgb_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12274,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VGB/BSGM/2003/DTE/vgb_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12275,92,"VGB","British Virgin Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VGB/BSGM/2004/Binary/vgb_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12276,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VGB/BSGM/2004/DTE/vgb_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12277,92,"VGB","British Virgin Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VGB/BSGM/2005/Binary/vgb_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12278,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VGB/BSGM/2005/DTE/vgb_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12279,92,"VGB","British Virgin Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VGB/BSGM/2006/Binary/vgb_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12280,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VGB/BSGM/2006/DTE/vgb_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12281,92,"VGB","British Virgin Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VGB/BSGM/2007/Binary/vgb_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12282,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VGB/BSGM/2007/DTE/vgb_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12283,92,"VGB","British Virgin Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VGB/BSGM/2008/Binary/vgb_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12284,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VGB/BSGM/2008/DTE/vgb_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12285,92,"VGB","British Virgin Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VGB/BSGM/2009/Binary/vgb_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12286,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VGB/BSGM/2009/DTE/vgb_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12287,92,"VGB","British Virgin Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VGB/BSGM/2010/Binary/vgb_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12288,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VGB/BSGM/2010/DTE/vgb_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12289,92,"VGB","British Virgin Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VGB/BSGM/2011/Binary/vgb_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12290,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VGB/BSGM/2011/DTE/vgb_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12291,92,"VGB","British Virgin Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VGB/BSGM/2013/Binary/vgb_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12292,92,"VGB","British Virgin Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VGB/BSGM/2013/DTE/vgb_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12293,92,"VGB","British Virgin Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/VGB/BSGM/2015/DTE/vgb_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12294,92,"VGB","British Virgin Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/VGB/BSGM/2016/DTE/vgb_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12295,92,"VGB","British Virgin Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/VGB/BSGM/2017/DTE/vgb_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12296,92,"VGB","British Virgin Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/VGB/BSGM/2018/DTE/vgb_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12297,92,"VGB","British Virgin Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/VGB/BSGM/2019/DTE/vgb_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12298,92,"VGB","British Virgin Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/VGB/BSGM/2020/DTE/vgb_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12299,96,"BRN","Brunei","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BRN/BSGM/2001/Binary/brn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12300,96,"BRN","Brunei","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BRN/BSGM/2001/DTE/brn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12301,96,"BRN","Brunei","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BRN/BSGM/2002/Binary/brn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12302,96,"BRN","Brunei","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BRN/BSGM/2002/DTE/brn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12303,96,"BRN","Brunei","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BRN/BSGM/2003/Binary/brn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12304,96,"BRN","Brunei","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BRN/BSGM/2003/DTE/brn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12305,96,"BRN","Brunei","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BRN/BSGM/2004/Binary/brn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12306,96,"BRN","Brunei","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BRN/BSGM/2004/DTE/brn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12307,96,"BRN","Brunei","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BRN/BSGM/2005/Binary/brn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12308,96,"BRN","Brunei","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BRN/BSGM/2005/DTE/brn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12309,96,"BRN","Brunei","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BRN/BSGM/2006/Binary/brn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12310,96,"BRN","Brunei","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BRN/BSGM/2006/DTE/brn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12311,96,"BRN","Brunei","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BRN/BSGM/2007/Binary/brn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12312,96,"BRN","Brunei","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BRN/BSGM/2007/DTE/brn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12313,96,"BRN","Brunei","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BRN/BSGM/2008/Binary/brn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12314,96,"BRN","Brunei","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BRN/BSGM/2008/DTE/brn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12315,96,"BRN","Brunei","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BRN/BSGM/2009/Binary/brn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12316,96,"BRN","Brunei","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BRN/BSGM/2009/DTE/brn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12317,96,"BRN","Brunei","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BRN/BSGM/2010/Binary/brn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12318,96,"BRN","Brunei","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BRN/BSGM/2010/DTE/brn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12319,96,"BRN","Brunei","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BRN/BSGM/2011/Binary/brn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12320,96,"BRN","Brunei","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BRN/BSGM/2011/DTE/brn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12321,96,"BRN","Brunei","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BRN/BSGM/2013/Binary/brn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12322,96,"BRN","Brunei","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BRN/BSGM/2013/DTE/brn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12323,96,"BRN","Brunei","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BRN/BSGM/2015/DTE/brn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12324,96,"BRN","Brunei","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BRN/BSGM/2016/DTE/brn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12325,96,"BRN","Brunei","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BRN/BSGM/2017/DTE/brn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12326,96,"BRN","Brunei","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BRN/BSGM/2018/DTE/brn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12327,96,"BRN","Brunei","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BRN/BSGM/2019/DTE/brn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12328,96,"BRN","Brunei","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BRN/BSGM/2020/DTE/brn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12329,100,"BGR","Bulgaria","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BGR/BSGM/2001/Binary/bgr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12330,100,"BGR","Bulgaria","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BGR/BSGM/2001/DTE/bgr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12331,100,"BGR","Bulgaria","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BGR/BSGM/2002/Binary/bgr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12332,100,"BGR","Bulgaria","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BGR/BSGM/2002/DTE/bgr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12333,100,"BGR","Bulgaria","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BGR/BSGM/2003/Binary/bgr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12334,100,"BGR","Bulgaria","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BGR/BSGM/2003/DTE/bgr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12335,100,"BGR","Bulgaria","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BGR/BSGM/2004/Binary/bgr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12336,100,"BGR","Bulgaria","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BGR/BSGM/2004/DTE/bgr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12337,100,"BGR","Bulgaria","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BGR/BSGM/2005/Binary/bgr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12338,100,"BGR","Bulgaria","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BGR/BSGM/2005/DTE/bgr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12339,100,"BGR","Bulgaria","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BGR/BSGM/2006/Binary/bgr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12340,100,"BGR","Bulgaria","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BGR/BSGM/2006/DTE/bgr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12341,100,"BGR","Bulgaria","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BGR/BSGM/2007/Binary/bgr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12342,100,"BGR","Bulgaria","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BGR/BSGM/2007/DTE/bgr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12343,100,"BGR","Bulgaria","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BGR/BSGM/2008/Binary/bgr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12344,100,"BGR","Bulgaria","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BGR/BSGM/2008/DTE/bgr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12345,100,"BGR","Bulgaria","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BGR/BSGM/2009/Binary/bgr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12346,100,"BGR","Bulgaria","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BGR/BSGM/2009/DTE/bgr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12347,100,"BGR","Bulgaria","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BGR/BSGM/2010/Binary/bgr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12348,100,"BGR","Bulgaria","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BGR/BSGM/2010/DTE/bgr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12349,100,"BGR","Bulgaria","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BGR/BSGM/2011/Binary/bgr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12350,100,"BGR","Bulgaria","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BGR/BSGM/2011/DTE/bgr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12351,100,"BGR","Bulgaria","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BGR/BSGM/2013/Binary/bgr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12352,100,"BGR","Bulgaria","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BGR/BSGM/2013/DTE/bgr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12353,100,"BGR","Bulgaria","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BGR/BSGM/2015/DTE/bgr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12354,100,"BGR","Bulgaria","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BGR/BSGM/2016/DTE/bgr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12355,100,"BGR","Bulgaria","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BGR/BSGM/2017/DTE/bgr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12356,100,"BGR","Bulgaria","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BGR/BSGM/2018/DTE/bgr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12357,100,"BGR","Bulgaria","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BGR/BSGM/2019/DTE/bgr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12358,100,"BGR","Bulgaria","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BGR/BSGM/2020/DTE/bgr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12359,104,"MMR","Myanmar","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MMR/BSGM/2001/Binary/mmr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12360,104,"MMR","Myanmar","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MMR/BSGM/2001/DTE/mmr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12361,104,"MMR","Myanmar","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MMR/BSGM/2002/Binary/mmr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12362,104,"MMR","Myanmar","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MMR/BSGM/2002/DTE/mmr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12363,104,"MMR","Myanmar","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MMR/BSGM/2003/Binary/mmr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12364,104,"MMR","Myanmar","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MMR/BSGM/2003/DTE/mmr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12365,104,"MMR","Myanmar","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MMR/BSGM/2004/Binary/mmr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12366,104,"MMR","Myanmar","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MMR/BSGM/2004/DTE/mmr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12367,104,"MMR","Myanmar","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MMR/BSGM/2005/Binary/mmr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12368,104,"MMR","Myanmar","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MMR/BSGM/2005/DTE/mmr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12369,104,"MMR","Myanmar","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MMR/BSGM/2006/Binary/mmr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12370,104,"MMR","Myanmar","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MMR/BSGM/2006/DTE/mmr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12371,104,"MMR","Myanmar","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MMR/BSGM/2007/Binary/mmr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12372,104,"MMR","Myanmar","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MMR/BSGM/2007/DTE/mmr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12373,104,"MMR","Myanmar","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MMR/BSGM/2008/Binary/mmr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12374,104,"MMR","Myanmar","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MMR/BSGM/2008/DTE/mmr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12375,104,"MMR","Myanmar","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MMR/BSGM/2009/Binary/mmr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12376,104,"MMR","Myanmar","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MMR/BSGM/2009/DTE/mmr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12377,104,"MMR","Myanmar","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MMR/BSGM/2010/Binary/mmr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12378,104,"MMR","Myanmar","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MMR/BSGM/2010/DTE/mmr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12379,104,"MMR","Myanmar","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MMR/BSGM/2011/Binary/mmr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12380,104,"MMR","Myanmar","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MMR/BSGM/2011/DTE/mmr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12381,104,"MMR","Myanmar","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MMR/BSGM/2013/Binary/mmr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12382,104,"MMR","Myanmar","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MMR/BSGM/2013/DTE/mmr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12383,104,"MMR","Myanmar","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MMR/BSGM/2015/DTE/mmr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12384,104,"MMR","Myanmar","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MMR/BSGM/2016/DTE/mmr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12385,104,"MMR","Myanmar","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MMR/BSGM/2017/DTE/mmr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12386,104,"MMR","Myanmar","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MMR/BSGM/2018/DTE/mmr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12387,104,"MMR","Myanmar","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MMR/BSGM/2019/DTE/mmr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12388,104,"MMR","Myanmar","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MMR/BSGM/2020/DTE/mmr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12389,108,"BDI","Burundi","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BDI/BSGM/2001/Binary/bdi_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12390,108,"BDI","Burundi","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BDI/BSGM/2001/DTE/bdi_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12391,108,"BDI","Burundi","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BDI/BSGM/2002/Binary/bdi_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12392,108,"BDI","Burundi","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BDI/BSGM/2002/DTE/bdi_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12393,108,"BDI","Burundi","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BDI/BSGM/2003/Binary/bdi_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12394,108,"BDI","Burundi","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BDI/BSGM/2003/DTE/bdi_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12395,108,"BDI","Burundi","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BDI/BSGM/2004/Binary/bdi_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12396,108,"BDI","Burundi","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BDI/BSGM/2004/DTE/bdi_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12397,108,"BDI","Burundi","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BDI/BSGM/2005/Binary/bdi_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12398,108,"BDI","Burundi","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BDI/BSGM/2005/DTE/bdi_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12399,108,"BDI","Burundi","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BDI/BSGM/2006/Binary/bdi_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12400,108,"BDI","Burundi","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BDI/BSGM/2006/DTE/bdi_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12401,108,"BDI","Burundi","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BDI/BSGM/2007/Binary/bdi_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12402,108,"BDI","Burundi","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BDI/BSGM/2007/DTE/bdi_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12403,108,"BDI","Burundi","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BDI/BSGM/2008/Binary/bdi_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12404,108,"BDI","Burundi","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BDI/BSGM/2008/DTE/bdi_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12405,108,"BDI","Burundi","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BDI/BSGM/2009/Binary/bdi_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12406,108,"BDI","Burundi","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BDI/BSGM/2009/DTE/bdi_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12407,108,"BDI","Burundi","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BDI/BSGM/2010/Binary/bdi_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12408,108,"BDI","Burundi","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BDI/BSGM/2010/DTE/bdi_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12409,108,"BDI","Burundi","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BDI/BSGM/2011/Binary/bdi_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12410,108,"BDI","Burundi","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BDI/BSGM/2011/DTE/bdi_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12411,108,"BDI","Burundi","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BDI/BSGM/2013/Binary/bdi_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12412,108,"BDI","Burundi","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BDI/BSGM/2013/DTE/bdi_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12413,108,"BDI","Burundi","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BDI/BSGM/2015/DTE/bdi_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12414,108,"BDI","Burundi","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BDI/BSGM/2016/DTE/bdi_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12415,108,"BDI","Burundi","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BDI/BSGM/2017/DTE/bdi_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12416,108,"BDI","Burundi","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BDI/BSGM/2018/DTE/bdi_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12417,108,"BDI","Burundi","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BDI/BSGM/2019/DTE/bdi_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12418,108,"BDI","Burundi","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BDI/BSGM/2020/DTE/bdi_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12419,112,"BLR","Belarus","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BLR/BSGM/2001/Binary/blr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12420,112,"BLR","Belarus","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BLR/BSGM/2001/DTE/blr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12421,112,"BLR","Belarus","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BLR/BSGM/2002/Binary/blr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12422,112,"BLR","Belarus","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BLR/BSGM/2002/DTE/blr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12423,112,"BLR","Belarus","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BLR/BSGM/2003/Binary/blr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12424,112,"BLR","Belarus","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BLR/BSGM/2003/DTE/blr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12425,112,"BLR","Belarus","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BLR/BSGM/2004/Binary/blr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12426,112,"BLR","Belarus","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BLR/BSGM/2004/DTE/blr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12427,112,"BLR","Belarus","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BLR/BSGM/2005/Binary/blr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12428,112,"BLR","Belarus","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BLR/BSGM/2005/DTE/blr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12429,112,"BLR","Belarus","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BLR/BSGM/2006/Binary/blr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12430,112,"BLR","Belarus","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BLR/BSGM/2006/DTE/blr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12431,112,"BLR","Belarus","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BLR/BSGM/2007/Binary/blr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12432,112,"BLR","Belarus","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BLR/BSGM/2007/DTE/blr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12433,112,"BLR","Belarus","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BLR/BSGM/2008/Binary/blr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12434,112,"BLR","Belarus","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BLR/BSGM/2008/DTE/blr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12435,112,"BLR","Belarus","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BLR/BSGM/2009/Binary/blr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12436,112,"BLR","Belarus","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BLR/BSGM/2009/DTE/blr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12437,112,"BLR","Belarus","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BLR/BSGM/2010/Binary/blr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12438,112,"BLR","Belarus","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BLR/BSGM/2010/DTE/blr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12439,112,"BLR","Belarus","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BLR/BSGM/2011/Binary/blr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12440,112,"BLR","Belarus","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BLR/BSGM/2011/DTE/blr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12441,112,"BLR","Belarus","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BLR/BSGM/2013/Binary/blr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12442,112,"BLR","Belarus","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BLR/BSGM/2013/DTE/blr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12443,112,"BLR","Belarus","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BLR/BSGM/2015/DTE/blr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12444,112,"BLR","Belarus","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BLR/BSGM/2016/DTE/blr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12445,112,"BLR","Belarus","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BLR/BSGM/2017/DTE/blr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12446,112,"BLR","Belarus","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BLR/BSGM/2018/DTE/blr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12447,112,"BLR","Belarus","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BLR/BSGM/2019/DTE/blr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12448,112,"BLR","Belarus","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BLR/BSGM/2020/DTE/blr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12449,116,"KHM","Cambodia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KHM/BSGM/2001/Binary/khm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12450,116,"KHM","Cambodia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KHM/BSGM/2001/DTE/khm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12451,116,"KHM","Cambodia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KHM/BSGM/2002/Binary/khm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12452,116,"KHM","Cambodia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KHM/BSGM/2002/DTE/khm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12453,116,"KHM","Cambodia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KHM/BSGM/2003/Binary/khm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12454,116,"KHM","Cambodia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KHM/BSGM/2003/DTE/khm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12455,116,"KHM","Cambodia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KHM/BSGM/2004/Binary/khm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12456,116,"KHM","Cambodia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KHM/BSGM/2004/DTE/khm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12457,116,"KHM","Cambodia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KHM/BSGM/2005/Binary/khm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12458,116,"KHM","Cambodia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KHM/BSGM/2005/DTE/khm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12459,116,"KHM","Cambodia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KHM/BSGM/2006/Binary/khm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12460,116,"KHM","Cambodia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KHM/BSGM/2006/DTE/khm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12461,116,"KHM","Cambodia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KHM/BSGM/2007/Binary/khm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12462,116,"KHM","Cambodia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KHM/BSGM/2007/DTE/khm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12463,116,"KHM","Cambodia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KHM/BSGM/2008/Binary/khm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12464,116,"KHM","Cambodia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KHM/BSGM/2008/DTE/khm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12465,116,"KHM","Cambodia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KHM/BSGM/2009/Binary/khm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12466,116,"KHM","Cambodia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KHM/BSGM/2009/DTE/khm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12467,116,"KHM","Cambodia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KHM/BSGM/2010/Binary/khm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12468,116,"KHM","Cambodia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KHM/BSGM/2010/DTE/khm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12469,116,"KHM","Cambodia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KHM/BSGM/2011/Binary/khm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12470,116,"KHM","Cambodia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KHM/BSGM/2011/DTE/khm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12471,116,"KHM","Cambodia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KHM/BSGM/2013/Binary/khm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12472,116,"KHM","Cambodia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KHM/BSGM/2013/DTE/khm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12473,116,"KHM","Cambodia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/KHM/BSGM/2015/DTE/khm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12474,116,"KHM","Cambodia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/KHM/BSGM/2016/DTE/khm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12475,116,"KHM","Cambodia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/KHM/BSGM/2017/DTE/khm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12476,116,"KHM","Cambodia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/KHM/BSGM/2018/DTE/khm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12477,116,"KHM","Cambodia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/KHM/BSGM/2019/DTE/khm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12478,116,"KHM","Cambodia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/KHM/BSGM/2020/DTE/khm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12479,120,"CMR","Cameroon","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CMR/BSGM/2001/Binary/cmr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12480,120,"CMR","Cameroon","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CMR/BSGM/2001/DTE/cmr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12481,120,"CMR","Cameroon","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CMR/BSGM/2002/Binary/cmr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12482,120,"CMR","Cameroon","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CMR/BSGM/2002/DTE/cmr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12483,120,"CMR","Cameroon","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CMR/BSGM/2003/Binary/cmr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12484,120,"CMR","Cameroon","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CMR/BSGM/2003/DTE/cmr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12485,120,"CMR","Cameroon","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CMR/BSGM/2004/Binary/cmr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12486,120,"CMR","Cameroon","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CMR/BSGM/2004/DTE/cmr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12487,120,"CMR","Cameroon","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CMR/BSGM/2005/Binary/cmr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12488,120,"CMR","Cameroon","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CMR/BSGM/2005/DTE/cmr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12489,120,"CMR","Cameroon","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CMR/BSGM/2006/Binary/cmr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12490,120,"CMR","Cameroon","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CMR/BSGM/2006/DTE/cmr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12491,120,"CMR","Cameroon","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CMR/BSGM/2007/Binary/cmr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12492,120,"CMR","Cameroon","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CMR/BSGM/2007/DTE/cmr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12493,120,"CMR","Cameroon","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CMR/BSGM/2008/Binary/cmr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12494,120,"CMR","Cameroon","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CMR/BSGM/2008/DTE/cmr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12495,120,"CMR","Cameroon","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CMR/BSGM/2009/Binary/cmr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12496,120,"CMR","Cameroon","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CMR/BSGM/2009/DTE/cmr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12497,120,"CMR","Cameroon","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CMR/BSGM/2010/Binary/cmr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12498,120,"CMR","Cameroon","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CMR/BSGM/2010/DTE/cmr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12499,120,"CMR","Cameroon","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CMR/BSGM/2011/Binary/cmr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12500,120,"CMR","Cameroon","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CMR/BSGM/2011/DTE/cmr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12501,120,"CMR","Cameroon","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CMR/BSGM/2013/Binary/cmr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12502,120,"CMR","Cameroon","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CMR/BSGM/2013/DTE/cmr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12503,120,"CMR","Cameroon","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CMR/BSGM/2015/DTE/cmr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12504,120,"CMR","Cameroon","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CMR/BSGM/2016/DTE/cmr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12505,120,"CMR","Cameroon","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CMR/BSGM/2017/DTE/cmr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12506,120,"CMR","Cameroon","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CMR/BSGM/2018/DTE/cmr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12507,120,"CMR","Cameroon","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CMR/BSGM/2019/DTE/cmr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12508,120,"CMR","Cameroon","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CMR/BSGM/2020/DTE/cmr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12509,132,"CPV","Cape Verde","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CPV/BSGM/2001/Binary/cpv_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12510,132,"CPV","Cape Verde","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CPV/BSGM/2001/DTE/cpv_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12511,132,"CPV","Cape Verde","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CPV/BSGM/2002/Binary/cpv_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12512,132,"CPV","Cape Verde","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CPV/BSGM/2002/DTE/cpv_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12513,132,"CPV","Cape Verde","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CPV/BSGM/2003/Binary/cpv_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12514,132,"CPV","Cape Verde","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CPV/BSGM/2003/DTE/cpv_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12515,132,"CPV","Cape Verde","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CPV/BSGM/2004/Binary/cpv_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12516,132,"CPV","Cape Verde","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CPV/BSGM/2004/DTE/cpv_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12517,132,"CPV","Cape Verde","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CPV/BSGM/2005/Binary/cpv_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12518,132,"CPV","Cape Verde","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CPV/BSGM/2005/DTE/cpv_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12519,132,"CPV","Cape Verde","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CPV/BSGM/2006/Binary/cpv_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12520,132,"CPV","Cape Verde","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CPV/BSGM/2006/DTE/cpv_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12521,132,"CPV","Cape Verde","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CPV/BSGM/2007/Binary/cpv_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12522,132,"CPV","Cape Verde","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CPV/BSGM/2007/DTE/cpv_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12523,132,"CPV","Cape Verde","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CPV/BSGM/2008/Binary/cpv_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12524,132,"CPV","Cape Verde","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CPV/BSGM/2008/DTE/cpv_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12525,132,"CPV","Cape Verde","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CPV/BSGM/2009/Binary/cpv_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12526,132,"CPV","Cape Verde","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CPV/BSGM/2009/DTE/cpv_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12527,132,"CPV","Cape Verde","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CPV/BSGM/2010/Binary/cpv_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12528,132,"CPV","Cape Verde","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CPV/BSGM/2010/DTE/cpv_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12529,132,"CPV","Cape Verde","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CPV/BSGM/2011/Binary/cpv_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12530,132,"CPV","Cape Verde","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CPV/BSGM/2011/DTE/cpv_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12531,132,"CPV","Cape Verde","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CPV/BSGM/2013/Binary/cpv_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12532,132,"CPV","Cape Verde","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CPV/BSGM/2013/DTE/cpv_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12533,132,"CPV","Cape Verde","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CPV/BSGM/2015/DTE/cpv_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12534,132,"CPV","Cape Verde","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CPV/BSGM/2016/DTE/cpv_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12535,132,"CPV","Cape Verde","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CPV/BSGM/2017/DTE/cpv_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12536,132,"CPV","Cape Verde","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CPV/BSGM/2018/DTE/cpv_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12537,132,"CPV","Cape Verde","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CPV/BSGM/2019/DTE/cpv_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12538,132,"CPV","Cape Verde","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CPV/BSGM/2020/DTE/cpv_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12539,136,"CYM","Cayman Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CYM/BSGM/2001/Binary/cym_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12540,136,"CYM","Cayman Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CYM/BSGM/2001/DTE/cym_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12541,136,"CYM","Cayman Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CYM/BSGM/2002/Binary/cym_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12542,136,"CYM","Cayman Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CYM/BSGM/2002/DTE/cym_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12543,136,"CYM","Cayman Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CYM/BSGM/2003/Binary/cym_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12544,136,"CYM","Cayman Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CYM/BSGM/2003/DTE/cym_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12545,136,"CYM","Cayman Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CYM/BSGM/2004/Binary/cym_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12546,136,"CYM","Cayman Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CYM/BSGM/2004/DTE/cym_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12547,136,"CYM","Cayman Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CYM/BSGM/2005/Binary/cym_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12548,136,"CYM","Cayman Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CYM/BSGM/2005/DTE/cym_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12549,136,"CYM","Cayman Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CYM/BSGM/2006/Binary/cym_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12550,136,"CYM","Cayman Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CYM/BSGM/2006/DTE/cym_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12551,136,"CYM","Cayman Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CYM/BSGM/2007/Binary/cym_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12552,136,"CYM","Cayman Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CYM/BSGM/2007/DTE/cym_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12553,136,"CYM","Cayman Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CYM/BSGM/2008/Binary/cym_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12554,136,"CYM","Cayman Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CYM/BSGM/2008/DTE/cym_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12555,136,"CYM","Cayman Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CYM/BSGM/2009/Binary/cym_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12556,136,"CYM","Cayman Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CYM/BSGM/2009/DTE/cym_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12557,136,"CYM","Cayman Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CYM/BSGM/2010/Binary/cym_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12558,136,"CYM","Cayman Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CYM/BSGM/2010/DTE/cym_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12559,136,"CYM","Cayman Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CYM/BSGM/2011/Binary/cym_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12560,136,"CYM","Cayman Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CYM/BSGM/2011/DTE/cym_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12561,136,"CYM","Cayman Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CYM/BSGM/2013/Binary/cym_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12562,136,"CYM","Cayman Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CYM/BSGM/2013/DTE/cym_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12563,136,"CYM","Cayman Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CYM/BSGM/2015/DTE/cym_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12564,136,"CYM","Cayman Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CYM/BSGM/2016/DTE/cym_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12565,136,"CYM","Cayman Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CYM/BSGM/2017/DTE/cym_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12566,136,"CYM","Cayman Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CYM/BSGM/2018/DTE/cym_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12567,136,"CYM","Cayman Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CYM/BSGM/2019/DTE/cym_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12568,136,"CYM","Cayman Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CYM/BSGM/2020/DTE/cym_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12569,140,"CAF","Central African Republic","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CAF/BSGM/2001/Binary/caf_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12570,140,"CAF","Central African Republic","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CAF/BSGM/2001/DTE/caf_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12571,140,"CAF","Central African Republic","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CAF/BSGM/2002/Binary/caf_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12572,140,"CAF","Central African Republic","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CAF/BSGM/2002/DTE/caf_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12573,140,"CAF","Central African Republic","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CAF/BSGM/2003/Binary/caf_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12574,140,"CAF","Central African Republic","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CAF/BSGM/2003/DTE/caf_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12575,140,"CAF","Central African Republic","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CAF/BSGM/2004/Binary/caf_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12576,140,"CAF","Central African Republic","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CAF/BSGM/2004/DTE/caf_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12577,140,"CAF","Central African Republic","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CAF/BSGM/2005/Binary/caf_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12578,140,"CAF","Central African Republic","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CAF/BSGM/2005/DTE/caf_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12579,140,"CAF","Central African Republic","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CAF/BSGM/2006/Binary/caf_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12580,140,"CAF","Central African Republic","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CAF/BSGM/2006/DTE/caf_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12581,140,"CAF","Central African Republic","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CAF/BSGM/2007/Binary/caf_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12582,140,"CAF","Central African Republic","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CAF/BSGM/2007/DTE/caf_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12583,140,"CAF","Central African Republic","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CAF/BSGM/2008/Binary/caf_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12584,140,"CAF","Central African Republic","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CAF/BSGM/2008/DTE/caf_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12585,140,"CAF","Central African Republic","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CAF/BSGM/2009/Binary/caf_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12586,140,"CAF","Central African Republic","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CAF/BSGM/2009/DTE/caf_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12587,140,"CAF","Central African Republic","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CAF/BSGM/2010/Binary/caf_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12588,140,"CAF","Central African Republic","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CAF/BSGM/2010/DTE/caf_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12589,140,"CAF","Central African Republic","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CAF/BSGM/2011/Binary/caf_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12590,140,"CAF","Central African Republic","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CAF/BSGM/2011/DTE/caf_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12591,140,"CAF","Central African Republic","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CAF/BSGM/2013/Binary/caf_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12592,140,"CAF","Central African Republic","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CAF/BSGM/2013/DTE/caf_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12593,140,"CAF","Central African Republic","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CAF/BSGM/2015/DTE/caf_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12594,140,"CAF","Central African Republic","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CAF/BSGM/2016/DTE/caf_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12595,140,"CAF","Central African Republic","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CAF/BSGM/2017/DTE/caf_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12596,140,"CAF","Central African Republic","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CAF/BSGM/2018/DTE/caf_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12597,140,"CAF","Central African Republic","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CAF/BSGM/2019/DTE/caf_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12598,140,"CAF","Central African Republic","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CAF/BSGM/2020/DTE/caf_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12599,144,"LKA","Sri Lanka","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LKA/BSGM/2001/Binary/lka_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12600,144,"LKA","Sri Lanka","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LKA/BSGM/2001/DTE/lka_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12601,144,"LKA","Sri Lanka","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LKA/BSGM/2002/Binary/lka_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12602,144,"LKA","Sri Lanka","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LKA/BSGM/2002/DTE/lka_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12603,144,"LKA","Sri Lanka","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LKA/BSGM/2003/Binary/lka_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12604,144,"LKA","Sri Lanka","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LKA/BSGM/2003/DTE/lka_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12605,144,"LKA","Sri Lanka","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LKA/BSGM/2004/Binary/lka_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12606,144,"LKA","Sri Lanka","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LKA/BSGM/2004/DTE/lka_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12607,144,"LKA","Sri Lanka","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LKA/BSGM/2005/Binary/lka_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12608,144,"LKA","Sri Lanka","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LKA/BSGM/2005/DTE/lka_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12609,144,"LKA","Sri Lanka","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LKA/BSGM/2006/Binary/lka_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12610,144,"LKA","Sri Lanka","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LKA/BSGM/2006/DTE/lka_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12611,144,"LKA","Sri Lanka","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LKA/BSGM/2007/Binary/lka_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12612,144,"LKA","Sri Lanka","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LKA/BSGM/2007/DTE/lka_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12613,144,"LKA","Sri Lanka","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LKA/BSGM/2008/Binary/lka_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12614,144,"LKA","Sri Lanka","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LKA/BSGM/2008/DTE/lka_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12615,144,"LKA","Sri Lanka","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LKA/BSGM/2009/Binary/lka_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12616,144,"LKA","Sri Lanka","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LKA/BSGM/2009/DTE/lka_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12617,144,"LKA","Sri Lanka","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LKA/BSGM/2010/Binary/lka_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12618,144,"LKA","Sri Lanka","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LKA/BSGM/2010/DTE/lka_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12619,144,"LKA","Sri Lanka","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LKA/BSGM/2011/Binary/lka_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12620,144,"LKA","Sri Lanka","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LKA/BSGM/2011/DTE/lka_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12621,144,"LKA","Sri Lanka","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LKA/BSGM/2013/Binary/lka_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12622,144,"LKA","Sri Lanka","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LKA/BSGM/2013/DTE/lka_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12623,144,"LKA","Sri Lanka","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LKA/BSGM/2015/DTE/lka_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12624,144,"LKA","Sri Lanka","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LKA/BSGM/2016/DTE/lka_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12625,144,"LKA","Sri Lanka","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LKA/BSGM/2017/DTE/lka_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12626,144,"LKA","Sri Lanka","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LKA/BSGM/2018/DTE/lka_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12627,144,"LKA","Sri Lanka","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LKA/BSGM/2019/DTE/lka_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12628,144,"LKA","Sri Lanka","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LKA/BSGM/2020/DTE/lka_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12629,148,"TCD","Chad","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TCD/BSGM/2001/Binary/tcd_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12630,148,"TCD","Chad","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TCD/BSGM/2001/DTE/tcd_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12631,148,"TCD","Chad","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TCD/BSGM/2002/Binary/tcd_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12632,148,"TCD","Chad","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TCD/BSGM/2002/DTE/tcd_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12633,148,"TCD","Chad","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TCD/BSGM/2003/Binary/tcd_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12634,148,"TCD","Chad","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TCD/BSGM/2003/DTE/tcd_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12635,148,"TCD","Chad","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TCD/BSGM/2004/Binary/tcd_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12636,148,"TCD","Chad","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TCD/BSGM/2004/DTE/tcd_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12637,148,"TCD","Chad","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TCD/BSGM/2005/Binary/tcd_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12638,148,"TCD","Chad","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TCD/BSGM/2005/DTE/tcd_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12639,148,"TCD","Chad","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TCD/BSGM/2006/Binary/tcd_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12640,148,"TCD","Chad","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TCD/BSGM/2006/DTE/tcd_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12641,148,"TCD","Chad","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TCD/BSGM/2007/Binary/tcd_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12642,148,"TCD","Chad","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TCD/BSGM/2007/DTE/tcd_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12643,148,"TCD","Chad","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TCD/BSGM/2008/Binary/tcd_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12644,148,"TCD","Chad","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TCD/BSGM/2008/DTE/tcd_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12645,148,"TCD","Chad","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TCD/BSGM/2009/Binary/tcd_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12646,148,"TCD","Chad","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TCD/BSGM/2009/DTE/tcd_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12647,148,"TCD","Chad","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TCD/BSGM/2010/Binary/tcd_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12648,148,"TCD","Chad","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TCD/BSGM/2010/DTE/tcd_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12649,148,"TCD","Chad","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TCD/BSGM/2011/Binary/tcd_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12650,148,"TCD","Chad","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TCD/BSGM/2011/DTE/tcd_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12651,148,"TCD","Chad","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TCD/BSGM/2013/Binary/tcd_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12652,148,"TCD","Chad","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TCD/BSGM/2013/DTE/tcd_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12653,148,"TCD","Chad","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TCD/BSGM/2015/DTE/tcd_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12654,148,"TCD","Chad","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TCD/BSGM/2016/DTE/tcd_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12655,148,"TCD","Chad","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TCD/BSGM/2017/DTE/tcd_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12656,148,"TCD","Chad","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TCD/BSGM/2018/DTE/tcd_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12657,148,"TCD","Chad","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TCD/BSGM/2019/DTE/tcd_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12658,148,"TCD","Chad","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TCD/BSGM/2020/DTE/tcd_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12659,158,"TWN","Taiwan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TWN/BSGM/2001/Binary/twn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12660,158,"TWN","Taiwan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TWN/BSGM/2001/DTE/twn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12661,158,"TWN","Taiwan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TWN/BSGM/2002/Binary/twn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12662,158,"TWN","Taiwan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TWN/BSGM/2002/DTE/twn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12663,158,"TWN","Taiwan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TWN/BSGM/2003/Binary/twn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12664,158,"TWN","Taiwan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TWN/BSGM/2003/DTE/twn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12665,158,"TWN","Taiwan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TWN/BSGM/2004/Binary/twn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12666,158,"TWN","Taiwan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TWN/BSGM/2004/DTE/twn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12667,158,"TWN","Taiwan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TWN/BSGM/2005/Binary/twn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12668,158,"TWN","Taiwan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TWN/BSGM/2005/DTE/twn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12669,158,"TWN","Taiwan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TWN/BSGM/2006/Binary/twn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12670,158,"TWN","Taiwan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TWN/BSGM/2006/DTE/twn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12671,158,"TWN","Taiwan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TWN/BSGM/2007/Binary/twn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12672,158,"TWN","Taiwan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TWN/BSGM/2007/DTE/twn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12673,158,"TWN","Taiwan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TWN/BSGM/2008/Binary/twn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12674,158,"TWN","Taiwan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TWN/BSGM/2008/DTE/twn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12675,158,"TWN","Taiwan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TWN/BSGM/2009/Binary/twn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12676,158,"TWN","Taiwan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TWN/BSGM/2009/DTE/twn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12677,158,"TWN","Taiwan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TWN/BSGM/2010/Binary/twn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12678,158,"TWN","Taiwan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TWN/BSGM/2010/DTE/twn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12679,158,"TWN","Taiwan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TWN/BSGM/2011/Binary/twn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12680,158,"TWN","Taiwan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TWN/BSGM/2011/DTE/twn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12681,158,"TWN","Taiwan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TWN/BSGM/2013/Binary/twn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12682,158,"TWN","Taiwan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TWN/BSGM/2013/DTE/twn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12683,158,"TWN","Taiwan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TWN/BSGM/2015/DTE/twn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12684,158,"TWN","Taiwan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TWN/BSGM/2016/DTE/twn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12685,158,"TWN","Taiwan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TWN/BSGM/2017/DTE/twn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12686,158,"TWN","Taiwan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TWN/BSGM/2018/DTE/twn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12687,158,"TWN","Taiwan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TWN/BSGM/2019/DTE/twn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12688,158,"TWN","Taiwan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TWN/BSGM/2020/DTE/twn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12689,170,"COL","Colombia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/COL/BSGM/2001/Binary/col_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12690,170,"COL","Colombia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/COL/BSGM/2001/DTE/col_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12691,170,"COL","Colombia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/COL/BSGM/2002/Binary/col_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12692,170,"COL","Colombia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/COL/BSGM/2002/DTE/col_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12693,170,"COL","Colombia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/COL/BSGM/2003/Binary/col_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12694,170,"COL","Colombia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/COL/BSGM/2003/DTE/col_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12695,170,"COL","Colombia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/COL/BSGM/2004/Binary/col_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12696,170,"COL","Colombia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/COL/BSGM/2004/DTE/col_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12697,170,"COL","Colombia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/COL/BSGM/2005/Binary/col_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12698,170,"COL","Colombia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/COL/BSGM/2005/DTE/col_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12699,170,"COL","Colombia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/COL/BSGM/2006/Binary/col_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12700,170,"COL","Colombia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/COL/BSGM/2006/DTE/col_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12701,170,"COL","Colombia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/COL/BSGM/2007/Binary/col_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12702,170,"COL","Colombia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/COL/BSGM/2007/DTE/col_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12703,170,"COL","Colombia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/COL/BSGM/2008/Binary/col_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12704,170,"COL","Colombia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/COL/BSGM/2008/DTE/col_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12705,170,"COL","Colombia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/COL/BSGM/2009/Binary/col_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12706,170,"COL","Colombia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/COL/BSGM/2009/DTE/col_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12707,170,"COL","Colombia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/COL/BSGM/2010/Binary/col_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12708,170,"COL","Colombia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/COL/BSGM/2010/DTE/col_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12709,170,"COL","Colombia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/COL/BSGM/2011/Binary/col_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12710,170,"COL","Colombia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/COL/BSGM/2011/DTE/col_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12711,170,"COL","Colombia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/COL/BSGM/2013/Binary/col_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12712,170,"COL","Colombia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/COL/BSGM/2013/DTE/col_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12713,170,"COL","Colombia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/COL/BSGM/2015/DTE/col_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12714,170,"COL","Colombia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/COL/BSGM/2016/DTE/col_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12715,170,"COL","Colombia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/COL/BSGM/2017/DTE/col_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12716,170,"COL","Colombia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/COL/BSGM/2018/DTE/col_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12717,170,"COL","Colombia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/COL/BSGM/2019/DTE/col_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12718,170,"COL","Colombia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/COL/BSGM/2020/DTE/col_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12719,174,"COM","Comoros","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/COM/BSGM/2001/Binary/com_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12720,174,"COM","Comoros","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/COM/BSGM/2001/DTE/com_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12721,174,"COM","Comoros","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/COM/BSGM/2002/Binary/com_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12722,174,"COM","Comoros","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/COM/BSGM/2002/DTE/com_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12723,174,"COM","Comoros","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/COM/BSGM/2003/Binary/com_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12724,174,"COM","Comoros","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/COM/BSGM/2003/DTE/com_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12725,174,"COM","Comoros","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/COM/BSGM/2004/Binary/com_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12726,174,"COM","Comoros","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/COM/BSGM/2004/DTE/com_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12727,174,"COM","Comoros","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/COM/BSGM/2005/Binary/com_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12728,174,"COM","Comoros","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/COM/BSGM/2005/DTE/com_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12729,174,"COM","Comoros","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/COM/BSGM/2006/Binary/com_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12730,174,"COM","Comoros","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/COM/BSGM/2006/DTE/com_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12731,174,"COM","Comoros","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/COM/BSGM/2007/Binary/com_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12732,174,"COM","Comoros","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/COM/BSGM/2007/DTE/com_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12733,174,"COM","Comoros","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/COM/BSGM/2008/Binary/com_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12734,174,"COM","Comoros","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/COM/BSGM/2008/DTE/com_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12735,174,"COM","Comoros","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/COM/BSGM/2009/Binary/com_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12736,174,"COM","Comoros","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/COM/BSGM/2009/DTE/com_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12737,174,"COM","Comoros","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/COM/BSGM/2010/Binary/com_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12738,174,"COM","Comoros","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/COM/BSGM/2010/DTE/com_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12739,174,"COM","Comoros","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/COM/BSGM/2011/Binary/com_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12740,174,"COM","Comoros","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/COM/BSGM/2011/DTE/com_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12741,174,"COM","Comoros","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/COM/BSGM/2013/Binary/com_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12742,174,"COM","Comoros","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/COM/BSGM/2013/DTE/com_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12743,174,"COM","Comoros","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/COM/BSGM/2015/DTE/com_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12744,174,"COM","Comoros","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/COM/BSGM/2016/DTE/com_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12745,174,"COM","Comoros","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/COM/BSGM/2017/DTE/com_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12746,174,"COM","Comoros","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/COM/BSGM/2018/DTE/com_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12747,174,"COM","Comoros","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/COM/BSGM/2019/DTE/com_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12748,174,"COM","Comoros","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/COM/BSGM/2020/DTE/com_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12749,175,"MYT","Mayotte","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MYT/BSGM/2001/Binary/myt_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12750,175,"MYT","Mayotte","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MYT/BSGM/2001/DTE/myt_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12751,175,"MYT","Mayotte","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MYT/BSGM/2002/Binary/myt_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12752,175,"MYT","Mayotte","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MYT/BSGM/2002/DTE/myt_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12753,175,"MYT","Mayotte","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MYT/BSGM/2003/Binary/myt_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12754,175,"MYT","Mayotte","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MYT/BSGM/2003/DTE/myt_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12755,175,"MYT","Mayotte","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MYT/BSGM/2004/Binary/myt_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12756,175,"MYT","Mayotte","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MYT/BSGM/2004/DTE/myt_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12757,175,"MYT","Mayotte","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MYT/BSGM/2005/Binary/myt_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12758,175,"MYT","Mayotte","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MYT/BSGM/2005/DTE/myt_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12759,175,"MYT","Mayotte","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MYT/BSGM/2006/Binary/myt_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12760,175,"MYT","Mayotte","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MYT/BSGM/2006/DTE/myt_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12761,175,"MYT","Mayotte","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MYT/BSGM/2007/Binary/myt_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12762,175,"MYT","Mayotte","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MYT/BSGM/2007/DTE/myt_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12763,175,"MYT","Mayotte","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MYT/BSGM/2008/Binary/myt_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12764,175,"MYT","Mayotte","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MYT/BSGM/2008/DTE/myt_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12765,175,"MYT","Mayotte","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MYT/BSGM/2009/Binary/myt_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12766,175,"MYT","Mayotte","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MYT/BSGM/2009/DTE/myt_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12767,175,"MYT","Mayotte","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MYT/BSGM/2010/Binary/myt_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12768,175,"MYT","Mayotte","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MYT/BSGM/2010/DTE/myt_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12769,175,"MYT","Mayotte","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MYT/BSGM/2011/Binary/myt_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12770,175,"MYT","Mayotte","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MYT/BSGM/2011/DTE/myt_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12771,175,"MYT","Mayotte","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MYT/BSGM/2013/Binary/myt_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12772,175,"MYT","Mayotte","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MYT/BSGM/2013/DTE/myt_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12773,175,"MYT","Mayotte","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MYT/BSGM/2015/DTE/myt_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12774,175,"MYT","Mayotte","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MYT/BSGM/2016/DTE/myt_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12775,175,"MYT","Mayotte","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MYT/BSGM/2017/DTE/myt_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12776,175,"MYT","Mayotte","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MYT/BSGM/2018/DTE/myt_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12777,175,"MYT","Mayotte","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MYT/BSGM/2019/DTE/myt_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12778,175,"MYT","Mayotte","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MYT/BSGM/2020/DTE/myt_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12779,178,"COG","Republic of Congo","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/COG/BSGM/2001/Binary/cog_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12780,178,"COG","Republic of Congo","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/COG/BSGM/2001/DTE/cog_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12781,178,"COG","Republic of Congo","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/COG/BSGM/2002/Binary/cog_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12782,178,"COG","Republic of Congo","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/COG/BSGM/2002/DTE/cog_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12783,178,"COG","Republic of Congo","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/COG/BSGM/2003/Binary/cog_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12784,178,"COG","Republic of Congo","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/COG/BSGM/2003/DTE/cog_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12785,178,"COG","Republic of Congo","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/COG/BSGM/2004/Binary/cog_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12786,178,"COG","Republic of Congo","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/COG/BSGM/2004/DTE/cog_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12787,178,"COG","Republic of Congo","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/COG/BSGM/2005/Binary/cog_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12788,178,"COG","Republic of Congo","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/COG/BSGM/2005/DTE/cog_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12789,178,"COG","Republic of Congo","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/COG/BSGM/2006/Binary/cog_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12790,178,"COG","Republic of Congo","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/COG/BSGM/2006/DTE/cog_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12791,178,"COG","Republic of Congo","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/COG/BSGM/2007/Binary/cog_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12792,178,"COG","Republic of Congo","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/COG/BSGM/2007/DTE/cog_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12793,178,"COG","Republic of Congo","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/COG/BSGM/2008/Binary/cog_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12794,178,"COG","Republic of Congo","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/COG/BSGM/2008/DTE/cog_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12795,178,"COG","Republic of Congo","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/COG/BSGM/2009/Binary/cog_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12796,178,"COG","Republic of Congo","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/COG/BSGM/2009/DTE/cog_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12797,178,"COG","Republic of Congo","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/COG/BSGM/2010/Binary/cog_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12798,178,"COG","Republic of Congo","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/COG/BSGM/2010/DTE/cog_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12799,178,"COG","Republic of Congo","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/COG/BSGM/2011/Binary/cog_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12800,178,"COG","Republic of Congo","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/COG/BSGM/2011/DTE/cog_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12801,178,"COG","Republic of Congo","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/COG/BSGM/2013/Binary/cog_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12802,178,"COG","Republic of Congo","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/COG/BSGM/2013/DTE/cog_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12803,178,"COG","Republic of Congo","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/COG/BSGM/2015/DTE/cog_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12804,178,"COG","Republic of Congo","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/COG/BSGM/2016/DTE/cog_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12805,178,"COG","Republic of Congo","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/COG/BSGM/2017/DTE/cog_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12806,178,"COG","Republic of Congo","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/COG/BSGM/2018/DTE/cog_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12807,178,"COG","Republic of Congo","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/COG/BSGM/2019/DTE/cog_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12808,178,"COG","Republic of Congo","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/COG/BSGM/2020/DTE/cog_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12809,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/COD/BSGM/2001/Binary/cod_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12810,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/COD/BSGM/2001/DTE/cod_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12811,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/COD/BSGM/2002/Binary/cod_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12812,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/COD/BSGM/2002/DTE/cod_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12813,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/COD/BSGM/2003/Binary/cod_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12814,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/COD/BSGM/2003/DTE/cod_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12815,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/COD/BSGM/2004/Binary/cod_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12816,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/COD/BSGM/2004/DTE/cod_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12817,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/COD/BSGM/2005/Binary/cod_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12818,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/COD/BSGM/2005/DTE/cod_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12819,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/COD/BSGM/2006/Binary/cod_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12820,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/COD/BSGM/2006/DTE/cod_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12821,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/COD/BSGM/2007/Binary/cod_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12822,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/COD/BSGM/2007/DTE/cod_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12823,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/COD/BSGM/2008/Binary/cod_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12824,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/COD/BSGM/2008/DTE/cod_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12825,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/COD/BSGM/2009/Binary/cod_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12826,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/COD/BSGM/2009/DTE/cod_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12827,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/COD/BSGM/2010/Binary/cod_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12828,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/COD/BSGM/2010/DTE/cod_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12829,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/COD/BSGM/2011/Binary/cod_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12830,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/COD/BSGM/2011/DTE/cod_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12831,180,"COD","Democratic Republic of the Congo","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/COD/BSGM/2013/Binary/cod_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12832,180,"COD","Democratic Republic of the Congo","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/COD/BSGM/2013/DTE/cod_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12833,180,"COD","Democratic Republic of the Congo","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/COD/BSGM/2015/DTE/cod_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12834,180,"COD","Democratic Republic of the Congo","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/COD/BSGM/2016/DTE/cod_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12835,180,"COD","Democratic Republic of the Congo","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/COD/BSGM/2017/DTE/cod_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12836,180,"COD","Democratic Republic of the Congo","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/COD/BSGM/2018/DTE/cod_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12837,180,"COD","Democratic Republic of the Congo","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/COD/BSGM/2019/DTE/cod_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12838,180,"COD","Democratic Republic of the Congo","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/COD/BSGM/2020/DTE/cod_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12839,184,"COK","Cook Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/COK/BSGM/2001/Binary/cok_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12840,184,"COK","Cook Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/COK/BSGM/2001/DTE/cok_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12841,184,"COK","Cook Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/COK/BSGM/2002/Binary/cok_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12842,184,"COK","Cook Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/COK/BSGM/2002/DTE/cok_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12843,184,"COK","Cook Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/COK/BSGM/2003/Binary/cok_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12844,184,"COK","Cook Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/COK/BSGM/2003/DTE/cok_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12845,184,"COK","Cook Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/COK/BSGM/2004/Binary/cok_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12846,184,"COK","Cook Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/COK/BSGM/2004/DTE/cok_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12847,184,"COK","Cook Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/COK/BSGM/2005/Binary/cok_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12848,184,"COK","Cook Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/COK/BSGM/2005/DTE/cok_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12849,184,"COK","Cook Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/COK/BSGM/2006/Binary/cok_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12850,184,"COK","Cook Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/COK/BSGM/2006/DTE/cok_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12851,184,"COK","Cook Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/COK/BSGM/2007/Binary/cok_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12852,184,"COK","Cook Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/COK/BSGM/2007/DTE/cok_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12853,184,"COK","Cook Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/COK/BSGM/2008/Binary/cok_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12854,184,"COK","Cook Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/COK/BSGM/2008/DTE/cok_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12855,184,"COK","Cook Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/COK/BSGM/2009/Binary/cok_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12856,184,"COK","Cook Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/COK/BSGM/2009/DTE/cok_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12857,184,"COK","Cook Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/COK/BSGM/2010/Binary/cok_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12858,184,"COK","Cook Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/COK/BSGM/2010/DTE/cok_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12859,184,"COK","Cook Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/COK/BSGM/2011/Binary/cok_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12860,184,"COK","Cook Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/COK/BSGM/2011/DTE/cok_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12861,184,"COK","Cook Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/COK/BSGM/2013/Binary/cok_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12862,184,"COK","Cook Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/COK/BSGM/2013/DTE/cok_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12863,184,"COK","Cook Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/COK/BSGM/2015/DTE/cok_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12864,184,"COK","Cook Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/COK/BSGM/2016/DTE/cok_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12865,184,"COK","Cook Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/COK/BSGM/2017/DTE/cok_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12866,184,"COK","Cook Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/COK/BSGM/2018/DTE/cok_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12867,184,"COK","Cook Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/COK/BSGM/2019/DTE/cok_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12868,184,"COK","Cook Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/COK/BSGM/2020/DTE/cok_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12869,188,"CRI","Costa Rica","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CRI/BSGM/2001/Binary/cri_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12870,188,"CRI","Costa Rica","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CRI/BSGM/2001/DTE/cri_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12871,188,"CRI","Costa Rica","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CRI/BSGM/2002/Binary/cri_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12872,188,"CRI","Costa Rica","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CRI/BSGM/2002/DTE/cri_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12873,188,"CRI","Costa Rica","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CRI/BSGM/2003/Binary/cri_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12874,188,"CRI","Costa Rica","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CRI/BSGM/2003/DTE/cri_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12875,188,"CRI","Costa Rica","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CRI/BSGM/2004/Binary/cri_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12876,188,"CRI","Costa Rica","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CRI/BSGM/2004/DTE/cri_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12877,188,"CRI","Costa Rica","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CRI/BSGM/2005/Binary/cri_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12878,188,"CRI","Costa Rica","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CRI/BSGM/2005/DTE/cri_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12879,188,"CRI","Costa Rica","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CRI/BSGM/2006/Binary/cri_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12880,188,"CRI","Costa Rica","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CRI/BSGM/2006/DTE/cri_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12881,188,"CRI","Costa Rica","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CRI/BSGM/2007/Binary/cri_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12882,188,"CRI","Costa Rica","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CRI/BSGM/2007/DTE/cri_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12883,188,"CRI","Costa Rica","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CRI/BSGM/2008/Binary/cri_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12884,188,"CRI","Costa Rica","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CRI/BSGM/2008/DTE/cri_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12885,188,"CRI","Costa Rica","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CRI/BSGM/2009/Binary/cri_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12886,188,"CRI","Costa Rica","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CRI/BSGM/2009/DTE/cri_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12887,188,"CRI","Costa Rica","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CRI/BSGM/2010/Binary/cri_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12888,188,"CRI","Costa Rica","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CRI/BSGM/2010/DTE/cri_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12889,188,"CRI","Costa Rica","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CRI/BSGM/2011/Binary/cri_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12890,188,"CRI","Costa Rica","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CRI/BSGM/2011/DTE/cri_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12891,188,"CRI","Costa Rica","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CRI/BSGM/2013/Binary/cri_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12892,188,"CRI","Costa Rica","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CRI/BSGM/2013/DTE/cri_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12893,188,"CRI","Costa Rica","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CRI/BSGM/2015/DTE/cri_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12894,188,"CRI","Costa Rica","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CRI/BSGM/2016/DTE/cri_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12895,188,"CRI","Costa Rica","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CRI/BSGM/2017/DTE/cri_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12896,188,"CRI","Costa Rica","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CRI/BSGM/2018/DTE/cri_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12897,188,"CRI","Costa Rica","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CRI/BSGM/2019/DTE/cri_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12898,188,"CRI","Costa Rica","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CRI/BSGM/2020/DTE/cri_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12899,191,"HRV","Croatia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HRV/BSGM/2001/Binary/hrv_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12900,191,"HRV","Croatia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HRV/BSGM/2001/DTE/hrv_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12901,191,"HRV","Croatia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HRV/BSGM/2002/Binary/hrv_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12902,191,"HRV","Croatia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HRV/BSGM/2002/DTE/hrv_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12903,191,"HRV","Croatia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HRV/BSGM/2003/Binary/hrv_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12904,191,"HRV","Croatia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HRV/BSGM/2003/DTE/hrv_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12905,191,"HRV","Croatia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HRV/BSGM/2004/Binary/hrv_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12906,191,"HRV","Croatia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HRV/BSGM/2004/DTE/hrv_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12907,191,"HRV","Croatia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HRV/BSGM/2005/Binary/hrv_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12908,191,"HRV","Croatia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HRV/BSGM/2005/DTE/hrv_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12909,191,"HRV","Croatia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HRV/BSGM/2006/Binary/hrv_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12910,191,"HRV","Croatia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HRV/BSGM/2006/DTE/hrv_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12911,191,"HRV","Croatia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HRV/BSGM/2007/Binary/hrv_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12912,191,"HRV","Croatia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HRV/BSGM/2007/DTE/hrv_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12913,191,"HRV","Croatia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HRV/BSGM/2008/Binary/hrv_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12914,191,"HRV","Croatia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HRV/BSGM/2008/DTE/hrv_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12915,191,"HRV","Croatia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HRV/BSGM/2009/Binary/hrv_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12916,191,"HRV","Croatia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HRV/BSGM/2009/DTE/hrv_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12917,191,"HRV","Croatia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HRV/BSGM/2010/Binary/hrv_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12918,191,"HRV","Croatia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HRV/BSGM/2010/DTE/hrv_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12919,191,"HRV","Croatia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HRV/BSGM/2011/Binary/hrv_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12920,191,"HRV","Croatia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HRV/BSGM/2011/DTE/hrv_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12921,191,"HRV","Croatia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HRV/BSGM/2013/Binary/hrv_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12922,191,"HRV","Croatia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HRV/BSGM/2013/DTE/hrv_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12923,191,"HRV","Croatia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/HRV/BSGM/2015/DTE/hrv_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12924,191,"HRV","Croatia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/HRV/BSGM/2016/DTE/hrv_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12925,191,"HRV","Croatia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/HRV/BSGM/2017/DTE/hrv_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12926,191,"HRV","Croatia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/HRV/BSGM/2018/DTE/hrv_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12927,191,"HRV","Croatia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/HRV/BSGM/2019/DTE/hrv_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12928,191,"HRV","Croatia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/HRV/BSGM/2020/DTE/hrv_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12929,192,"CUB","Cuba","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CUB/BSGM/2001/Binary/cub_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12930,192,"CUB","Cuba","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CUB/BSGM/2001/DTE/cub_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12931,192,"CUB","Cuba","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CUB/BSGM/2002/Binary/cub_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12932,192,"CUB","Cuba","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CUB/BSGM/2002/DTE/cub_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12933,192,"CUB","Cuba","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CUB/BSGM/2003/Binary/cub_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12934,192,"CUB","Cuba","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CUB/BSGM/2003/DTE/cub_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12935,192,"CUB","Cuba","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CUB/BSGM/2004/Binary/cub_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12936,192,"CUB","Cuba","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CUB/BSGM/2004/DTE/cub_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12937,192,"CUB","Cuba","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CUB/BSGM/2005/Binary/cub_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12938,192,"CUB","Cuba","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CUB/BSGM/2005/DTE/cub_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12939,192,"CUB","Cuba","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CUB/BSGM/2006/Binary/cub_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12940,192,"CUB","Cuba","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CUB/BSGM/2006/DTE/cub_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12941,192,"CUB","Cuba","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CUB/BSGM/2007/Binary/cub_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12942,192,"CUB","Cuba","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CUB/BSGM/2007/DTE/cub_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12943,192,"CUB","Cuba","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CUB/BSGM/2008/Binary/cub_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12944,192,"CUB","Cuba","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CUB/BSGM/2008/DTE/cub_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12945,192,"CUB","Cuba","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CUB/BSGM/2009/Binary/cub_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12946,192,"CUB","Cuba","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CUB/BSGM/2009/DTE/cub_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12947,192,"CUB","Cuba","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CUB/BSGM/2010/Binary/cub_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12948,192,"CUB","Cuba","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CUB/BSGM/2010/DTE/cub_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12949,192,"CUB","Cuba","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CUB/BSGM/2011/Binary/cub_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12950,192,"CUB","Cuba","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CUB/BSGM/2011/DTE/cub_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12951,192,"CUB","Cuba","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CUB/BSGM/2013/Binary/cub_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12952,192,"CUB","Cuba","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CUB/BSGM/2013/DTE/cub_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12953,192,"CUB","Cuba","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CUB/BSGM/2015/DTE/cub_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12954,192,"CUB","Cuba","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CUB/BSGM/2016/DTE/cub_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12955,192,"CUB","Cuba","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CUB/BSGM/2017/DTE/cub_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12956,192,"CUB","Cuba","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CUB/BSGM/2018/DTE/cub_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12957,192,"CUB","Cuba","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CUB/BSGM/2019/DTE/cub_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12958,192,"CUB","Cuba","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CUB/BSGM/2020/DTE/cub_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12959,196,"CYP","Cyprus","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CYP/BSGM/2001/Binary/cyp_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12960,196,"CYP","Cyprus","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CYP/BSGM/2001/DTE/cyp_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12961,196,"CYP","Cyprus","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CYP/BSGM/2002/Binary/cyp_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12962,196,"CYP","Cyprus","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CYP/BSGM/2002/DTE/cyp_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12963,196,"CYP","Cyprus","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CYP/BSGM/2003/Binary/cyp_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12964,196,"CYP","Cyprus","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CYP/BSGM/2003/DTE/cyp_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12965,196,"CYP","Cyprus","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CYP/BSGM/2004/Binary/cyp_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12966,196,"CYP","Cyprus","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CYP/BSGM/2004/DTE/cyp_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12967,196,"CYP","Cyprus","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CYP/BSGM/2005/Binary/cyp_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12968,196,"CYP","Cyprus","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CYP/BSGM/2005/DTE/cyp_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12969,196,"CYP","Cyprus","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CYP/BSGM/2006/Binary/cyp_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
12970,196,"CYP","Cyprus","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CYP/BSGM/2006/DTE/cyp_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
12971,196,"CYP","Cyprus","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CYP/BSGM/2007/Binary/cyp_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
12972,196,"CYP","Cyprus","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CYP/BSGM/2007/DTE/cyp_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
12973,196,"CYP","Cyprus","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CYP/BSGM/2008/Binary/cyp_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
12974,196,"CYP","Cyprus","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CYP/BSGM/2008/DTE/cyp_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
12975,196,"CYP","Cyprus","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CYP/BSGM/2009/Binary/cyp_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
12976,196,"CYP","Cyprus","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CYP/BSGM/2009/DTE/cyp_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
12977,196,"CYP","Cyprus","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CYP/BSGM/2010/Binary/cyp_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
12978,196,"CYP","Cyprus","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CYP/BSGM/2010/DTE/cyp_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
12979,196,"CYP","Cyprus","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CYP/BSGM/2011/Binary/cyp_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
12980,196,"CYP","Cyprus","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CYP/BSGM/2011/DTE/cyp_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
12981,196,"CYP","Cyprus","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CYP/BSGM/2013/Binary/cyp_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
12982,196,"CYP","Cyprus","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CYP/BSGM/2013/DTE/cyp_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
12983,196,"CYP","Cyprus","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CYP/BSGM/2015/DTE/cyp_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
12984,196,"CYP","Cyprus","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CYP/BSGM/2016/DTE/cyp_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
12985,196,"CYP","Cyprus","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CYP/BSGM/2017/DTE/cyp_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
12986,196,"CYP","Cyprus","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CYP/BSGM/2018/DTE/cyp_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
12987,196,"CYP","Cyprus","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CYP/BSGM/2019/DTE/cyp_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
12988,196,"CYP","Cyprus","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CYP/BSGM/2020/DTE/cyp_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
12989,203,"CZE","Czech Republic","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CZE/BSGM/2001/Binary/cze_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
12990,203,"CZE","Czech Republic","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CZE/BSGM/2001/DTE/cze_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
12991,203,"CZE","Czech Republic","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CZE/BSGM/2002/Binary/cze_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
12992,203,"CZE","Czech Republic","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CZE/BSGM/2002/DTE/cze_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
12993,203,"CZE","Czech Republic","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CZE/BSGM/2003/Binary/cze_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
12994,203,"CZE","Czech Republic","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CZE/BSGM/2003/DTE/cze_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
12995,203,"CZE","Czech Republic","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CZE/BSGM/2004/Binary/cze_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
12996,203,"CZE","Czech Republic","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CZE/BSGM/2004/DTE/cze_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
12997,203,"CZE","Czech Republic","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CZE/BSGM/2005/Binary/cze_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
12998,203,"CZE","Czech Republic","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CZE/BSGM/2005/DTE/cze_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
12999,203,"CZE","Czech Republic","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CZE/BSGM/2006/Binary/cze_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13000,203,"CZE","Czech Republic","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CZE/BSGM/2006/DTE/cze_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13001,203,"CZE","Czech Republic","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CZE/BSGM/2007/Binary/cze_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13002,203,"CZE","Czech Republic","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CZE/BSGM/2007/DTE/cze_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13003,203,"CZE","Czech Republic","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CZE/BSGM/2008/Binary/cze_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13004,203,"CZE","Czech Republic","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CZE/BSGM/2008/DTE/cze_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13005,203,"CZE","Czech Republic","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CZE/BSGM/2009/Binary/cze_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13006,203,"CZE","Czech Republic","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CZE/BSGM/2009/DTE/cze_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13007,203,"CZE","Czech Republic","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CZE/BSGM/2010/Binary/cze_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13008,203,"CZE","Czech Republic","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CZE/BSGM/2010/DTE/cze_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13009,203,"CZE","Czech Republic","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CZE/BSGM/2011/Binary/cze_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13010,203,"CZE","Czech Republic","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CZE/BSGM/2011/DTE/cze_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13011,203,"CZE","Czech Republic","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CZE/BSGM/2013/Binary/cze_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13012,203,"CZE","Czech Republic","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CZE/BSGM/2013/DTE/cze_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13013,203,"CZE","Czech Republic","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CZE/BSGM/2015/DTE/cze_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13014,203,"CZE","Czech Republic","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CZE/BSGM/2016/DTE/cze_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13015,203,"CZE","Czech Republic","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CZE/BSGM/2017/DTE/cze_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13016,203,"CZE","Czech Republic","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CZE/BSGM/2018/DTE/cze_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13017,203,"CZE","Czech Republic","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CZE/BSGM/2019/DTE/cze_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13018,203,"CZE","Czech Republic","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CZE/BSGM/2020/DTE/cze_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13019,204,"BEN","Benin","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BEN/BSGM/2001/Binary/ben_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13020,204,"BEN","Benin","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BEN/BSGM/2001/DTE/ben_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13021,204,"BEN","Benin","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BEN/BSGM/2002/Binary/ben_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13022,204,"BEN","Benin","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BEN/BSGM/2002/DTE/ben_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13023,204,"BEN","Benin","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BEN/BSGM/2003/Binary/ben_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13024,204,"BEN","Benin","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BEN/BSGM/2003/DTE/ben_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13025,204,"BEN","Benin","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BEN/BSGM/2004/Binary/ben_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13026,204,"BEN","Benin","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BEN/BSGM/2004/DTE/ben_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13027,204,"BEN","Benin","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BEN/BSGM/2005/Binary/ben_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13028,204,"BEN","Benin","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BEN/BSGM/2005/DTE/ben_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13029,204,"BEN","Benin","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BEN/BSGM/2006/Binary/ben_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13030,204,"BEN","Benin","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BEN/BSGM/2006/DTE/ben_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13031,204,"BEN","Benin","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BEN/BSGM/2007/Binary/ben_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13032,204,"BEN","Benin","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BEN/BSGM/2007/DTE/ben_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13033,204,"BEN","Benin","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BEN/BSGM/2008/Binary/ben_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13034,204,"BEN","Benin","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BEN/BSGM/2008/DTE/ben_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13035,204,"BEN","Benin","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BEN/BSGM/2009/Binary/ben_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13036,204,"BEN","Benin","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BEN/BSGM/2009/DTE/ben_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13037,204,"BEN","Benin","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BEN/BSGM/2010/Binary/ben_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13038,204,"BEN","Benin","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BEN/BSGM/2010/DTE/ben_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13039,204,"BEN","Benin","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BEN/BSGM/2011/Binary/ben_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13040,204,"BEN","Benin","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BEN/BSGM/2011/DTE/ben_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13041,204,"BEN","Benin","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BEN/BSGM/2013/Binary/ben_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13042,204,"BEN","Benin","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BEN/BSGM/2013/DTE/ben_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13043,204,"BEN","Benin","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BEN/BSGM/2015/DTE/ben_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13044,204,"BEN","Benin","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BEN/BSGM/2016/DTE/ben_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13045,204,"BEN","Benin","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BEN/BSGM/2017/DTE/ben_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13046,204,"BEN","Benin","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BEN/BSGM/2018/DTE/ben_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13047,204,"BEN","Benin","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BEN/BSGM/2019/DTE/ben_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13048,204,"BEN","Benin","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BEN/BSGM/2020/DTE/ben_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13049,208,"DNK","Denmark","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DNK/BSGM/2001/Binary/dnk_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13050,208,"DNK","Denmark","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DNK/BSGM/2001/DTE/dnk_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13051,208,"DNK","Denmark","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DNK/BSGM/2002/Binary/dnk_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13052,208,"DNK","Denmark","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DNK/BSGM/2002/DTE/dnk_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13053,208,"DNK","Denmark","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DNK/BSGM/2003/Binary/dnk_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13054,208,"DNK","Denmark","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DNK/BSGM/2003/DTE/dnk_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13055,208,"DNK","Denmark","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DNK/BSGM/2004/Binary/dnk_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13056,208,"DNK","Denmark","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DNK/BSGM/2004/DTE/dnk_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13057,208,"DNK","Denmark","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DNK/BSGM/2005/Binary/dnk_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13058,208,"DNK","Denmark","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DNK/BSGM/2005/DTE/dnk_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13059,208,"DNK","Denmark","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DNK/BSGM/2006/Binary/dnk_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13060,208,"DNK","Denmark","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DNK/BSGM/2006/DTE/dnk_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13061,208,"DNK","Denmark","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DNK/BSGM/2007/Binary/dnk_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13062,208,"DNK","Denmark","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DNK/BSGM/2007/DTE/dnk_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13063,208,"DNK","Denmark","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DNK/BSGM/2008/Binary/dnk_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13064,208,"DNK","Denmark","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DNK/BSGM/2008/DTE/dnk_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13065,208,"DNK","Denmark","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DNK/BSGM/2009/Binary/dnk_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13066,208,"DNK","Denmark","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DNK/BSGM/2009/DTE/dnk_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13067,208,"DNK","Denmark","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DNK/BSGM/2010/Binary/dnk_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13068,208,"DNK","Denmark","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DNK/BSGM/2010/DTE/dnk_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13069,208,"DNK","Denmark","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DNK/BSGM/2011/Binary/dnk_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13070,208,"DNK","Denmark","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DNK/BSGM/2011/DTE/dnk_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13071,208,"DNK","Denmark","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DNK/BSGM/2013/Binary/dnk_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13072,208,"DNK","Denmark","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DNK/BSGM/2013/DTE/dnk_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13073,208,"DNK","Denmark","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/DNK/BSGM/2015/DTE/dnk_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13074,208,"DNK","Denmark","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/DNK/BSGM/2016/DTE/dnk_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13075,208,"DNK","Denmark","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/DNK/BSGM/2017/DTE/dnk_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13076,208,"DNK","Denmark","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/DNK/BSGM/2018/DTE/dnk_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13077,208,"DNK","Denmark","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/DNK/BSGM/2019/DTE/dnk_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13078,208,"DNK","Denmark","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/DNK/BSGM/2020/DTE/dnk_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13079,212,"DMA","Dominica","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DMA/BSGM/2001/Binary/dma_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13080,212,"DMA","Dominica","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DMA/BSGM/2001/DTE/dma_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13081,212,"DMA","Dominica","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DMA/BSGM/2002/Binary/dma_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13082,212,"DMA","Dominica","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DMA/BSGM/2002/DTE/dma_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13083,212,"DMA","Dominica","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DMA/BSGM/2003/Binary/dma_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13084,212,"DMA","Dominica","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DMA/BSGM/2003/DTE/dma_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13085,212,"DMA","Dominica","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DMA/BSGM/2004/Binary/dma_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13086,212,"DMA","Dominica","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DMA/BSGM/2004/DTE/dma_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13087,212,"DMA","Dominica","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DMA/BSGM/2005/Binary/dma_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13088,212,"DMA","Dominica","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DMA/BSGM/2005/DTE/dma_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13089,212,"DMA","Dominica","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DMA/BSGM/2006/Binary/dma_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13090,212,"DMA","Dominica","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DMA/BSGM/2006/DTE/dma_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13091,212,"DMA","Dominica","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DMA/BSGM/2007/Binary/dma_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13092,212,"DMA","Dominica","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DMA/BSGM/2007/DTE/dma_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13093,212,"DMA","Dominica","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DMA/BSGM/2008/Binary/dma_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13094,212,"DMA","Dominica","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DMA/BSGM/2008/DTE/dma_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13095,212,"DMA","Dominica","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DMA/BSGM/2009/Binary/dma_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13096,212,"DMA","Dominica","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DMA/BSGM/2009/DTE/dma_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13097,212,"DMA","Dominica","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DMA/BSGM/2010/Binary/dma_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13098,212,"DMA","Dominica","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DMA/BSGM/2010/DTE/dma_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13099,212,"DMA","Dominica","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DMA/BSGM/2011/Binary/dma_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13100,212,"DMA","Dominica","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DMA/BSGM/2011/DTE/dma_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13101,212,"DMA","Dominica","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DMA/BSGM/2013/Binary/dma_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13102,212,"DMA","Dominica","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DMA/BSGM/2013/DTE/dma_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13103,212,"DMA","Dominica","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/DMA/BSGM/2015/DTE/dma_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13104,212,"DMA","Dominica","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/DMA/BSGM/2016/DTE/dma_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13105,212,"DMA","Dominica","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/DMA/BSGM/2017/DTE/dma_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13106,212,"DMA","Dominica","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/DMA/BSGM/2018/DTE/dma_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13107,212,"DMA","Dominica","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/DMA/BSGM/2019/DTE/dma_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13108,212,"DMA","Dominica","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/DMA/BSGM/2020/DTE/dma_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13109,214,"DOM","Dominican Republic","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DOM/BSGM/2001/Binary/dom_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13110,214,"DOM","Dominican Republic","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DOM/BSGM/2001/DTE/dom_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13111,214,"DOM","Dominican Republic","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DOM/BSGM/2002/Binary/dom_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13112,214,"DOM","Dominican Republic","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DOM/BSGM/2002/DTE/dom_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13113,214,"DOM","Dominican Republic","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DOM/BSGM/2003/Binary/dom_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13114,214,"DOM","Dominican Republic","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DOM/BSGM/2003/DTE/dom_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13115,214,"DOM","Dominican Republic","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DOM/BSGM/2004/Binary/dom_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13116,214,"DOM","Dominican Republic","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DOM/BSGM/2004/DTE/dom_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13117,214,"DOM","Dominican Republic","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DOM/BSGM/2005/Binary/dom_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13118,214,"DOM","Dominican Republic","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DOM/BSGM/2005/DTE/dom_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13119,214,"DOM","Dominican Republic","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DOM/BSGM/2006/Binary/dom_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13120,214,"DOM","Dominican Republic","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DOM/BSGM/2006/DTE/dom_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13121,214,"DOM","Dominican Republic","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DOM/BSGM/2007/Binary/dom_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13122,214,"DOM","Dominican Republic","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DOM/BSGM/2007/DTE/dom_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13123,214,"DOM","Dominican Republic","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DOM/BSGM/2008/Binary/dom_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13124,214,"DOM","Dominican Republic","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DOM/BSGM/2008/DTE/dom_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13125,214,"DOM","Dominican Republic","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DOM/BSGM/2009/Binary/dom_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13126,214,"DOM","Dominican Republic","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DOM/BSGM/2009/DTE/dom_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13127,214,"DOM","Dominican Republic","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DOM/BSGM/2010/Binary/dom_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13128,214,"DOM","Dominican Republic","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DOM/BSGM/2010/DTE/dom_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13129,214,"DOM","Dominican Republic","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DOM/BSGM/2011/Binary/dom_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13130,214,"DOM","Dominican Republic","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DOM/BSGM/2011/DTE/dom_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13131,214,"DOM","Dominican Republic","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DOM/BSGM/2013/Binary/dom_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13132,214,"DOM","Dominican Republic","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DOM/BSGM/2013/DTE/dom_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13133,214,"DOM","Dominican Republic","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/DOM/BSGM/2015/DTE/dom_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13134,214,"DOM","Dominican Republic","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/DOM/BSGM/2016/DTE/dom_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13135,214,"DOM","Dominican Republic","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/DOM/BSGM/2017/DTE/dom_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13136,214,"DOM","Dominican Republic","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/DOM/BSGM/2018/DTE/dom_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13137,214,"DOM","Dominican Republic","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/DOM/BSGM/2019/DTE/dom_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13138,214,"DOM","Dominican Republic","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/DOM/BSGM/2020/DTE/dom_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13139,218,"ECU","Ecuador","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ECU/BSGM/2001/Binary/ecu_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13140,218,"ECU","Ecuador","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ECU/BSGM/2001/DTE/ecu_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13141,218,"ECU","Ecuador","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ECU/BSGM/2002/Binary/ecu_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13142,218,"ECU","Ecuador","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ECU/BSGM/2002/DTE/ecu_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13143,218,"ECU","Ecuador","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ECU/BSGM/2003/Binary/ecu_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13144,218,"ECU","Ecuador","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ECU/BSGM/2003/DTE/ecu_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13145,218,"ECU","Ecuador","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ECU/BSGM/2004/Binary/ecu_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13146,218,"ECU","Ecuador","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ECU/BSGM/2004/DTE/ecu_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13147,218,"ECU","Ecuador","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ECU/BSGM/2005/Binary/ecu_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13148,218,"ECU","Ecuador","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ECU/BSGM/2005/DTE/ecu_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13149,218,"ECU","Ecuador","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ECU/BSGM/2006/Binary/ecu_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13150,218,"ECU","Ecuador","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ECU/BSGM/2006/DTE/ecu_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13151,218,"ECU","Ecuador","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ECU/BSGM/2007/Binary/ecu_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13152,218,"ECU","Ecuador","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ECU/BSGM/2007/DTE/ecu_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13153,218,"ECU","Ecuador","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ECU/BSGM/2008/Binary/ecu_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13154,218,"ECU","Ecuador","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ECU/BSGM/2008/DTE/ecu_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13155,218,"ECU","Ecuador","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ECU/BSGM/2009/Binary/ecu_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13156,218,"ECU","Ecuador","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ECU/BSGM/2009/DTE/ecu_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13157,218,"ECU","Ecuador","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ECU/BSGM/2010/Binary/ecu_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13158,218,"ECU","Ecuador","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ECU/BSGM/2010/DTE/ecu_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13159,218,"ECU","Ecuador","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ECU/BSGM/2011/Binary/ecu_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13160,218,"ECU","Ecuador","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ECU/BSGM/2011/DTE/ecu_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13161,218,"ECU","Ecuador","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ECU/BSGM/2013/Binary/ecu_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13162,218,"ECU","Ecuador","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ECU/BSGM/2013/DTE/ecu_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13163,218,"ECU","Ecuador","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ECU/BSGM/2015/DTE/ecu_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13164,218,"ECU","Ecuador","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ECU/BSGM/2016/DTE/ecu_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13165,218,"ECU","Ecuador","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ECU/BSGM/2017/DTE/ecu_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13166,218,"ECU","Ecuador","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ECU/BSGM/2018/DTE/ecu_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13167,218,"ECU","Ecuador","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ECU/BSGM/2019/DTE/ecu_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13168,218,"ECU","Ecuador","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ECU/BSGM/2020/DTE/ecu_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13169,222,"SLV","El Salvador","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SLV/BSGM/2001/Binary/slv_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13170,222,"SLV","El Salvador","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SLV/BSGM/2001/DTE/slv_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13171,222,"SLV","El Salvador","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SLV/BSGM/2002/Binary/slv_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13172,222,"SLV","El Salvador","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SLV/BSGM/2002/DTE/slv_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13173,222,"SLV","El Salvador","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SLV/BSGM/2003/Binary/slv_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13174,222,"SLV","El Salvador","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SLV/BSGM/2003/DTE/slv_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13175,222,"SLV","El Salvador","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SLV/BSGM/2004/Binary/slv_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13176,222,"SLV","El Salvador","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SLV/BSGM/2004/DTE/slv_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13177,222,"SLV","El Salvador","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SLV/BSGM/2005/Binary/slv_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13178,222,"SLV","El Salvador","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SLV/BSGM/2005/DTE/slv_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13179,222,"SLV","El Salvador","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SLV/BSGM/2006/Binary/slv_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13180,222,"SLV","El Salvador","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SLV/BSGM/2006/DTE/slv_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13181,222,"SLV","El Salvador","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SLV/BSGM/2007/Binary/slv_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13182,222,"SLV","El Salvador","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SLV/BSGM/2007/DTE/slv_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13183,222,"SLV","El Salvador","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SLV/BSGM/2008/Binary/slv_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13184,222,"SLV","El Salvador","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SLV/BSGM/2008/DTE/slv_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13185,222,"SLV","El Salvador","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SLV/BSGM/2009/Binary/slv_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13186,222,"SLV","El Salvador","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SLV/BSGM/2009/DTE/slv_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13187,222,"SLV","El Salvador","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SLV/BSGM/2010/Binary/slv_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13188,222,"SLV","El Salvador","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SLV/BSGM/2010/DTE/slv_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13189,222,"SLV","El Salvador","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SLV/BSGM/2011/Binary/slv_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13190,222,"SLV","El Salvador","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SLV/BSGM/2011/DTE/slv_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13191,222,"SLV","El Salvador","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SLV/BSGM/2013/Binary/slv_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13192,222,"SLV","El Salvador","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SLV/BSGM/2013/DTE/slv_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13193,222,"SLV","El Salvador","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SLV/BSGM/2015/DTE/slv_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13194,222,"SLV","El Salvador","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SLV/BSGM/2016/DTE/slv_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13195,222,"SLV","El Salvador","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SLV/BSGM/2017/DTE/slv_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13196,222,"SLV","El Salvador","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SLV/BSGM/2018/DTE/slv_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13197,222,"SLV","El Salvador","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SLV/BSGM/2019/DTE/slv_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13198,222,"SLV","El Salvador","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SLV/BSGM/2020/DTE/slv_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13199,226,"GNQ","Equatorial Guinea","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2001/Binary/gnq_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13200,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2001/DTE/gnq_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13201,226,"GNQ","Equatorial Guinea","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2002/Binary/gnq_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13202,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2002/DTE/gnq_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13203,226,"GNQ","Equatorial Guinea","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2003/Binary/gnq_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13204,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2003/DTE/gnq_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13205,226,"GNQ","Equatorial Guinea","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2004/Binary/gnq_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13206,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2004/DTE/gnq_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13207,226,"GNQ","Equatorial Guinea","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2005/Binary/gnq_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13208,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2005/DTE/gnq_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13209,226,"GNQ","Equatorial Guinea","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2006/Binary/gnq_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13210,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2006/DTE/gnq_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13211,226,"GNQ","Equatorial Guinea","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2007/Binary/gnq_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13212,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2007/DTE/gnq_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13213,226,"GNQ","Equatorial Guinea","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2008/Binary/gnq_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13214,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2008/DTE/gnq_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13215,226,"GNQ","Equatorial Guinea","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2009/Binary/gnq_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13216,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2009/DTE/gnq_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13217,226,"GNQ","Equatorial Guinea","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2010/Binary/gnq_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13218,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2010/DTE/gnq_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13219,226,"GNQ","Equatorial Guinea","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2011/Binary/gnq_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13220,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2011/DTE/gnq_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13221,226,"GNQ","Equatorial Guinea","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2013/Binary/gnq_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13222,226,"GNQ","Equatorial Guinea","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2013/DTE/gnq_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13223,226,"GNQ","Equatorial Guinea","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2015/DTE/gnq_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13224,226,"GNQ","Equatorial Guinea","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2016/DTE/gnq_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13225,226,"GNQ","Equatorial Guinea","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2017/DTE/gnq_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13226,226,"GNQ","Equatorial Guinea","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2018/DTE/gnq_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13227,226,"GNQ","Equatorial Guinea","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2019/DTE/gnq_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13228,226,"GNQ","Equatorial Guinea","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GNQ/BSGM/2020/DTE/gnq_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13229,231,"ETH","Ethiopia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ETH/BSGM/2001/Binary/eth_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13230,231,"ETH","Ethiopia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ETH/BSGM/2001/DTE/eth_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13231,231,"ETH","Ethiopia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ETH/BSGM/2002/Binary/eth_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13232,231,"ETH","Ethiopia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ETH/BSGM/2002/DTE/eth_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13233,231,"ETH","Ethiopia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ETH/BSGM/2003/Binary/eth_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13234,231,"ETH","Ethiopia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ETH/BSGM/2003/DTE/eth_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13235,231,"ETH","Ethiopia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ETH/BSGM/2004/Binary/eth_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13236,231,"ETH","Ethiopia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ETH/BSGM/2004/DTE/eth_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13237,231,"ETH","Ethiopia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ETH/BSGM/2005/Binary/eth_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13238,231,"ETH","Ethiopia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ETH/BSGM/2005/DTE/eth_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13239,231,"ETH","Ethiopia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ETH/BSGM/2006/Binary/eth_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13240,231,"ETH","Ethiopia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ETH/BSGM/2006/DTE/eth_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13241,231,"ETH","Ethiopia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ETH/BSGM/2007/Binary/eth_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13242,231,"ETH","Ethiopia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ETH/BSGM/2007/DTE/eth_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13243,231,"ETH","Ethiopia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ETH/BSGM/2008/Binary/eth_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13244,231,"ETH","Ethiopia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ETH/BSGM/2008/DTE/eth_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13245,231,"ETH","Ethiopia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ETH/BSGM/2009/Binary/eth_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13246,231,"ETH","Ethiopia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ETH/BSGM/2009/DTE/eth_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13247,231,"ETH","Ethiopia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ETH/BSGM/2010/Binary/eth_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13248,231,"ETH","Ethiopia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ETH/BSGM/2010/DTE/eth_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13249,231,"ETH","Ethiopia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ETH/BSGM/2011/Binary/eth_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13250,231,"ETH","Ethiopia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ETH/BSGM/2011/DTE/eth_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13251,231,"ETH","Ethiopia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ETH/BSGM/2013/Binary/eth_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13252,231,"ETH","Ethiopia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ETH/BSGM/2013/DTE/eth_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13253,231,"ETH","Ethiopia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ETH/BSGM/2015/DTE/eth_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13254,231,"ETH","Ethiopia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ETH/BSGM/2016/DTE/eth_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13255,231,"ETH","Ethiopia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ETH/BSGM/2017/DTE/eth_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13256,231,"ETH","Ethiopia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ETH/BSGM/2018/DTE/eth_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13257,231,"ETH","Ethiopia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ETH/BSGM/2019/DTE/eth_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13258,231,"ETH","Ethiopia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ETH/BSGM/2020/DTE/eth_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13259,232,"ERI","Eritrea","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ERI/BSGM/2001/Binary/eri_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13260,232,"ERI","Eritrea","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ERI/BSGM/2001/DTE/eri_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13261,232,"ERI","Eritrea","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ERI/BSGM/2002/Binary/eri_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13262,232,"ERI","Eritrea","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ERI/BSGM/2002/DTE/eri_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13263,232,"ERI","Eritrea","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ERI/BSGM/2003/Binary/eri_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13264,232,"ERI","Eritrea","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ERI/BSGM/2003/DTE/eri_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13265,232,"ERI","Eritrea","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ERI/BSGM/2004/Binary/eri_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13266,232,"ERI","Eritrea","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ERI/BSGM/2004/DTE/eri_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13267,232,"ERI","Eritrea","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ERI/BSGM/2005/Binary/eri_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13268,232,"ERI","Eritrea","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ERI/BSGM/2005/DTE/eri_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13269,232,"ERI","Eritrea","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ERI/BSGM/2006/Binary/eri_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13270,232,"ERI","Eritrea","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ERI/BSGM/2006/DTE/eri_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13271,232,"ERI","Eritrea","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ERI/BSGM/2007/Binary/eri_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13272,232,"ERI","Eritrea","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ERI/BSGM/2007/DTE/eri_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13273,232,"ERI","Eritrea","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ERI/BSGM/2008/Binary/eri_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13274,232,"ERI","Eritrea","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ERI/BSGM/2008/DTE/eri_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13275,232,"ERI","Eritrea","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ERI/BSGM/2009/Binary/eri_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13276,232,"ERI","Eritrea","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ERI/BSGM/2009/DTE/eri_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13277,232,"ERI","Eritrea","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ERI/BSGM/2010/Binary/eri_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13278,232,"ERI","Eritrea","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ERI/BSGM/2010/DTE/eri_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13279,232,"ERI","Eritrea","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ERI/BSGM/2011/Binary/eri_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13280,232,"ERI","Eritrea","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ERI/BSGM/2011/DTE/eri_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13281,232,"ERI","Eritrea","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ERI/BSGM/2013/Binary/eri_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13282,232,"ERI","Eritrea","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ERI/BSGM/2013/DTE/eri_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13283,232,"ERI","Eritrea","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ERI/BSGM/2015/DTE/eri_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13284,232,"ERI","Eritrea","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ERI/BSGM/2016/DTE/eri_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13285,232,"ERI","Eritrea","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ERI/BSGM/2017/DTE/eri_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13286,232,"ERI","Eritrea","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ERI/BSGM/2018/DTE/eri_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13287,232,"ERI","Eritrea","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ERI/BSGM/2019/DTE/eri_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13288,232,"ERI","Eritrea","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ERI/BSGM/2020/DTE/eri_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13289,233,"EST","Estonia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/EST/BSGM/2001/Binary/est_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13290,233,"EST","Estonia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/EST/BSGM/2001/DTE/est_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13291,233,"EST","Estonia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/EST/BSGM/2002/Binary/est_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13292,233,"EST","Estonia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/EST/BSGM/2002/DTE/est_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13293,233,"EST","Estonia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/EST/BSGM/2003/Binary/est_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13294,233,"EST","Estonia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/EST/BSGM/2003/DTE/est_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13295,233,"EST","Estonia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/EST/BSGM/2004/Binary/est_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13296,233,"EST","Estonia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/EST/BSGM/2004/DTE/est_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13297,233,"EST","Estonia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/EST/BSGM/2005/Binary/est_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13298,233,"EST","Estonia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/EST/BSGM/2005/DTE/est_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13299,233,"EST","Estonia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/EST/BSGM/2006/Binary/est_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13300,233,"EST","Estonia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/EST/BSGM/2006/DTE/est_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13301,233,"EST","Estonia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/EST/BSGM/2007/Binary/est_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13302,233,"EST","Estonia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/EST/BSGM/2007/DTE/est_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13303,233,"EST","Estonia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/EST/BSGM/2008/Binary/est_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13304,233,"EST","Estonia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/EST/BSGM/2008/DTE/est_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13305,233,"EST","Estonia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/EST/BSGM/2009/Binary/est_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13306,233,"EST","Estonia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/EST/BSGM/2009/DTE/est_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13307,233,"EST","Estonia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/EST/BSGM/2010/Binary/est_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13308,233,"EST","Estonia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/EST/BSGM/2010/DTE/est_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13309,233,"EST","Estonia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/EST/BSGM/2011/Binary/est_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13310,233,"EST","Estonia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/EST/BSGM/2011/DTE/est_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13311,233,"EST","Estonia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/EST/BSGM/2013/Binary/est_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13312,233,"EST","Estonia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/EST/BSGM/2013/DTE/est_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13313,233,"EST","Estonia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/EST/BSGM/2015/DTE/est_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13314,233,"EST","Estonia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/EST/BSGM/2016/DTE/est_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13315,233,"EST","Estonia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/EST/BSGM/2017/DTE/est_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13316,233,"EST","Estonia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/EST/BSGM/2018/DTE/est_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13317,233,"EST","Estonia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/EST/BSGM/2019/DTE/est_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13318,233,"EST","Estonia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/EST/BSGM/2020/DTE/est_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13319,234,"FRO","Faroe Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FRO/BSGM/2001/Binary/fro_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13320,234,"FRO","Faroe Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FRO/BSGM/2001/DTE/fro_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13321,234,"FRO","Faroe Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FRO/BSGM/2002/Binary/fro_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13322,234,"FRO","Faroe Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FRO/BSGM/2002/DTE/fro_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13323,234,"FRO","Faroe Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FRO/BSGM/2003/Binary/fro_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13324,234,"FRO","Faroe Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FRO/BSGM/2003/DTE/fro_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13325,234,"FRO","Faroe Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FRO/BSGM/2004/Binary/fro_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13326,234,"FRO","Faroe Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FRO/BSGM/2004/DTE/fro_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13327,234,"FRO","Faroe Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FRO/BSGM/2005/Binary/fro_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13328,234,"FRO","Faroe Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FRO/BSGM/2005/DTE/fro_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13329,234,"FRO","Faroe Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FRO/BSGM/2006/Binary/fro_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13330,234,"FRO","Faroe Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FRO/BSGM/2006/DTE/fro_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13331,234,"FRO","Faroe Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FRO/BSGM/2007/Binary/fro_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13332,234,"FRO","Faroe Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FRO/BSGM/2007/DTE/fro_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13333,234,"FRO","Faroe Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FRO/BSGM/2008/Binary/fro_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13334,234,"FRO","Faroe Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FRO/BSGM/2008/DTE/fro_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13335,234,"FRO","Faroe Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FRO/BSGM/2009/Binary/fro_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13336,234,"FRO","Faroe Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FRO/BSGM/2009/DTE/fro_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13337,234,"FRO","Faroe Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FRO/BSGM/2010/Binary/fro_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13338,234,"FRO","Faroe Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FRO/BSGM/2010/DTE/fro_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13339,234,"FRO","Faroe Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FRO/BSGM/2011/Binary/fro_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13340,234,"FRO","Faroe Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FRO/BSGM/2011/DTE/fro_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13341,234,"FRO","Faroe Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FRO/BSGM/2013/Binary/fro_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13342,234,"FRO","Faroe Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FRO/BSGM/2013/DTE/fro_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13343,234,"FRO","Faroe Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/FRO/BSGM/2015/DTE/fro_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13344,234,"FRO","Faroe Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/FRO/BSGM/2016/DTE/fro_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13345,234,"FRO","Faroe Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/FRO/BSGM/2017/DTE/fro_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13346,234,"FRO","Faroe Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/FRO/BSGM/2018/DTE/fro_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13347,234,"FRO","Faroe Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/FRO/BSGM/2019/DTE/fro_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13348,234,"FRO","Faroe Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/FRO/BSGM/2020/DTE/fro_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13349,238,"FLK","Falkland Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FLK/BSGM/2001/Binary/flk_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13350,238,"FLK","Falkland Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FLK/BSGM/2001/DTE/flk_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13351,238,"FLK","Falkland Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FLK/BSGM/2002/Binary/flk_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13352,238,"FLK","Falkland Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FLK/BSGM/2002/DTE/flk_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13353,238,"FLK","Falkland Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FLK/BSGM/2003/Binary/flk_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13354,238,"FLK","Falkland Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FLK/BSGM/2003/DTE/flk_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13355,238,"FLK","Falkland Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FLK/BSGM/2004/Binary/flk_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13356,238,"FLK","Falkland Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FLK/BSGM/2004/DTE/flk_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13357,238,"FLK","Falkland Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FLK/BSGM/2005/Binary/flk_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13358,238,"FLK","Falkland Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FLK/BSGM/2005/DTE/flk_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13359,238,"FLK","Falkland Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FLK/BSGM/2006/Binary/flk_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13360,238,"FLK","Falkland Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FLK/BSGM/2006/DTE/flk_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13361,238,"FLK","Falkland Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FLK/BSGM/2007/Binary/flk_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13362,238,"FLK","Falkland Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FLK/BSGM/2007/DTE/flk_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13363,238,"FLK","Falkland Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FLK/BSGM/2008/Binary/flk_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13364,238,"FLK","Falkland Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FLK/BSGM/2008/DTE/flk_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13365,238,"FLK","Falkland Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FLK/BSGM/2009/Binary/flk_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13366,238,"FLK","Falkland Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FLK/BSGM/2009/DTE/flk_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13367,238,"FLK","Falkland Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FLK/BSGM/2010/Binary/flk_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13368,238,"FLK","Falkland Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FLK/BSGM/2010/DTE/flk_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13369,238,"FLK","Falkland Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FLK/BSGM/2011/Binary/flk_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13370,238,"FLK","Falkland Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FLK/BSGM/2011/DTE/flk_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13371,238,"FLK","Falkland Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FLK/BSGM/2013/Binary/flk_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13372,238,"FLK","Falkland Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FLK/BSGM/2013/DTE/flk_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13373,238,"FLK","Falkland Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/FLK/BSGM/2015/DTE/flk_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13374,238,"FLK","Falkland Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/FLK/BSGM/2016/DTE/flk_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13375,238,"FLK","Falkland Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/FLK/BSGM/2017/DTE/flk_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13376,238,"FLK","Falkland Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/FLK/BSGM/2018/DTE/flk_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13377,238,"FLK","Falkland Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/FLK/BSGM/2019/DTE/flk_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13378,238,"FLK","Falkland Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/FLK/BSGM/2020/DTE/flk_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13379,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SGS/BSGM/2001/Binary/sgs_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13380,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SGS/BSGM/2001/DTE/sgs_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13381,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SGS/BSGM/2002/Binary/sgs_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13382,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SGS/BSGM/2002/DTE/sgs_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13383,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SGS/BSGM/2003/Binary/sgs_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13384,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SGS/BSGM/2003/DTE/sgs_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13385,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SGS/BSGM/2004/Binary/sgs_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13386,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SGS/BSGM/2004/DTE/sgs_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13387,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SGS/BSGM/2005/Binary/sgs_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13388,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SGS/BSGM/2005/DTE/sgs_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13389,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SGS/BSGM/2006/Binary/sgs_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13390,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SGS/BSGM/2006/DTE/sgs_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13391,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SGS/BSGM/2007/Binary/sgs_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13392,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SGS/BSGM/2007/DTE/sgs_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13393,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SGS/BSGM/2008/Binary/sgs_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13394,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SGS/BSGM/2008/DTE/sgs_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13395,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SGS/BSGM/2009/Binary/sgs_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13396,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SGS/BSGM/2009/DTE/sgs_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13397,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SGS/BSGM/2010/Binary/sgs_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13398,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SGS/BSGM/2010/DTE/sgs_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13399,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SGS/BSGM/2011/Binary/sgs_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13400,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SGS/BSGM/2011/DTE/sgs_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13401,239,"SGS","South Georgia and the South Sandwich Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SGS/BSGM/2013/Binary/sgs_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13402,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SGS/BSGM/2013/DTE/sgs_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13403,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SGS/BSGM/2015/DTE/sgs_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13404,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SGS/BSGM/2016/DTE/sgs_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13405,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SGS/BSGM/2017/DTE/sgs_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13406,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SGS/BSGM/2018/DTE/sgs_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13407,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SGS/BSGM/2019/DTE/sgs_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13408,239,"SGS","South Georgia and the South Sandwich Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SGS/BSGM/2020/DTE/sgs_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13409,242,"FJI","Fiji","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FJI/BSGM/2001/Binary/fji_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13410,242,"FJI","Fiji","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FJI/BSGM/2001/DTE/fji_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13411,242,"FJI","Fiji","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FJI/BSGM/2002/Binary/fji_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13412,242,"FJI","Fiji","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FJI/BSGM/2002/DTE/fji_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13413,242,"FJI","Fiji","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FJI/BSGM/2003/Binary/fji_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13414,242,"FJI","Fiji","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FJI/BSGM/2003/DTE/fji_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13415,242,"FJI","Fiji","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FJI/BSGM/2004/Binary/fji_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13416,242,"FJI","Fiji","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FJI/BSGM/2004/DTE/fji_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13417,242,"FJI","Fiji","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FJI/BSGM/2005/Binary/fji_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13418,242,"FJI","Fiji","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FJI/BSGM/2005/DTE/fji_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13419,242,"FJI","Fiji","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FJI/BSGM/2006/Binary/fji_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13420,242,"FJI","Fiji","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FJI/BSGM/2006/DTE/fji_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13421,242,"FJI","Fiji","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FJI/BSGM/2007/Binary/fji_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13422,242,"FJI","Fiji","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FJI/BSGM/2007/DTE/fji_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13423,242,"FJI","Fiji","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FJI/BSGM/2008/Binary/fji_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13424,242,"FJI","Fiji","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FJI/BSGM/2008/DTE/fji_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13425,242,"FJI","Fiji","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FJI/BSGM/2009/Binary/fji_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13426,242,"FJI","Fiji","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FJI/BSGM/2009/DTE/fji_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13427,242,"FJI","Fiji","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FJI/BSGM/2010/Binary/fji_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13428,242,"FJI","Fiji","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FJI/BSGM/2010/DTE/fji_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13429,242,"FJI","Fiji","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FJI/BSGM/2011/Binary/fji_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13430,242,"FJI","Fiji","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FJI/BSGM/2011/DTE/fji_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13431,242,"FJI","Fiji","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FJI/BSGM/2013/Binary/fji_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13432,242,"FJI","Fiji","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FJI/BSGM/2013/DTE/fji_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13433,242,"FJI","Fiji","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/FJI/BSGM/2015/DTE/fji_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13434,242,"FJI","Fiji","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/FJI/BSGM/2016/DTE/fji_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13435,242,"FJI","Fiji","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/FJI/BSGM/2017/DTE/fji_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13436,242,"FJI","Fiji","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/FJI/BSGM/2018/DTE/fji_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13437,242,"FJI","Fiji","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/FJI/BSGM/2019/DTE/fji_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13438,242,"FJI","Fiji","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/FJI/BSGM/2020/DTE/fji_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13439,246,"FIN","Finland","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FIN/BSGM/2001/Binary/fin_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13440,246,"FIN","Finland","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FIN/BSGM/2001/DTE/fin_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13441,246,"FIN","Finland","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FIN/BSGM/2002/Binary/fin_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13442,246,"FIN","Finland","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FIN/BSGM/2002/DTE/fin_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13443,246,"FIN","Finland","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FIN/BSGM/2003/Binary/fin_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13444,246,"FIN","Finland","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FIN/BSGM/2003/DTE/fin_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13445,246,"FIN","Finland","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FIN/BSGM/2004/Binary/fin_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13446,246,"FIN","Finland","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FIN/BSGM/2004/DTE/fin_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13447,246,"FIN","Finland","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FIN/BSGM/2005/Binary/fin_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13448,246,"FIN","Finland","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FIN/BSGM/2005/DTE/fin_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13449,246,"FIN","Finland","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FIN/BSGM/2006/Binary/fin_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13450,246,"FIN","Finland","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FIN/BSGM/2006/DTE/fin_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13451,246,"FIN","Finland","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FIN/BSGM/2007/Binary/fin_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13452,246,"FIN","Finland","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FIN/BSGM/2007/DTE/fin_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13453,246,"FIN","Finland","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FIN/BSGM/2008/Binary/fin_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13454,246,"FIN","Finland","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FIN/BSGM/2008/DTE/fin_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13455,246,"FIN","Finland","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FIN/BSGM/2009/Binary/fin_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13456,246,"FIN","Finland","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FIN/BSGM/2009/DTE/fin_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13457,246,"FIN","Finland","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FIN/BSGM/2010/Binary/fin_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13458,246,"FIN","Finland","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FIN/BSGM/2010/DTE/fin_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13459,246,"FIN","Finland","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FIN/BSGM/2011/Binary/fin_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13460,246,"FIN","Finland","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FIN/BSGM/2011/DTE/fin_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13461,246,"FIN","Finland","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FIN/BSGM/2013/Binary/fin_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13462,246,"FIN","Finland","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FIN/BSGM/2013/DTE/fin_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13463,246,"FIN","Finland","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/FIN/BSGM/2015/DTE/fin_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13464,246,"FIN","Finland","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/FIN/BSGM/2016/DTE/fin_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13465,246,"FIN","Finland","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/FIN/BSGM/2017/DTE/fin_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13466,246,"FIN","Finland","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/FIN/BSGM/2018/DTE/fin_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13467,246,"FIN","Finland","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/FIN/BSGM/2019/DTE/fin_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13468,246,"FIN","Finland","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/FIN/BSGM/2020/DTE/fin_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13469,248,"ALA","Aland Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ALA/BSGM/2001/Binary/ala_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13470,248,"ALA","Aland Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ALA/BSGM/2001/DTE/ala_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13471,248,"ALA","Aland Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ALA/BSGM/2002/Binary/ala_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13472,248,"ALA","Aland Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ALA/BSGM/2002/DTE/ala_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13473,248,"ALA","Aland Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ALA/BSGM/2003/Binary/ala_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13474,248,"ALA","Aland Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ALA/BSGM/2003/DTE/ala_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13475,248,"ALA","Aland Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ALA/BSGM/2004/Binary/ala_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13476,248,"ALA","Aland Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ALA/BSGM/2004/DTE/ala_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13477,248,"ALA","Aland Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ALA/BSGM/2005/Binary/ala_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13478,248,"ALA","Aland Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ALA/BSGM/2005/DTE/ala_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13479,248,"ALA","Aland Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ALA/BSGM/2006/Binary/ala_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13480,248,"ALA","Aland Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ALA/BSGM/2006/DTE/ala_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13481,248,"ALA","Aland Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ALA/BSGM/2007/Binary/ala_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13482,248,"ALA","Aland Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ALA/BSGM/2007/DTE/ala_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13483,248,"ALA","Aland Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ALA/BSGM/2008/Binary/ala_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13484,248,"ALA","Aland Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ALA/BSGM/2008/DTE/ala_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13485,248,"ALA","Aland Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ALA/BSGM/2009/Binary/ala_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13486,248,"ALA","Aland Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ALA/BSGM/2009/DTE/ala_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13487,248,"ALA","Aland Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ALA/BSGM/2010/Binary/ala_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13488,248,"ALA","Aland Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ALA/BSGM/2010/DTE/ala_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13489,248,"ALA","Aland Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ALA/BSGM/2011/Binary/ala_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13490,248,"ALA","Aland Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ALA/BSGM/2011/DTE/ala_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13491,248,"ALA","Aland Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ALA/BSGM/2013/Binary/ala_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13492,248,"ALA","Aland Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ALA/BSGM/2013/DTE/ala_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13493,248,"ALA","Aland Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ALA/BSGM/2015/DTE/ala_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13494,248,"ALA","Aland Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ALA/BSGM/2016/DTE/ala_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13495,248,"ALA","Aland Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ALA/BSGM/2017/DTE/ala_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13496,248,"ALA","Aland Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ALA/BSGM/2018/DTE/ala_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13497,248,"ALA","Aland Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ALA/BSGM/2019/DTE/ala_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13498,248,"ALA","Aland Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ALA/BSGM/2020/DTE/ala_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13499,250,"FRA","France","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FRA/BSGM/2001/Binary/fra_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13500,250,"FRA","France","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FRA/BSGM/2001/DTE/fra_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13501,250,"FRA","France","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FRA/BSGM/2002/Binary/fra_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13502,250,"FRA","France","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FRA/BSGM/2002/DTE/fra_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13503,250,"FRA","France","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FRA/BSGM/2003/Binary/fra_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13504,250,"FRA","France","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FRA/BSGM/2003/DTE/fra_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13505,250,"FRA","France","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FRA/BSGM/2004/Binary/fra_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13506,250,"FRA","France","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FRA/BSGM/2004/DTE/fra_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13507,250,"FRA","France","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FRA/BSGM/2005/Binary/fra_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13508,250,"FRA","France","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FRA/BSGM/2005/DTE/fra_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13509,250,"FRA","France","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FRA/BSGM/2006/Binary/fra_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13510,250,"FRA","France","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FRA/BSGM/2006/DTE/fra_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13511,250,"FRA","France","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FRA/BSGM/2007/Binary/fra_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13512,250,"FRA","France","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FRA/BSGM/2007/DTE/fra_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13513,250,"FRA","France","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FRA/BSGM/2008/Binary/fra_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13514,250,"FRA","France","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FRA/BSGM/2008/DTE/fra_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13515,250,"FRA","France","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FRA/BSGM/2009/Binary/fra_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13516,250,"FRA","France","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FRA/BSGM/2009/DTE/fra_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13517,250,"FRA","France","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FRA/BSGM/2010/Binary/fra_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13518,250,"FRA","France","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FRA/BSGM/2010/DTE/fra_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13519,250,"FRA","France","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FRA/BSGM/2011/Binary/fra_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13520,250,"FRA","France","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FRA/BSGM/2011/DTE/fra_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13521,250,"FRA","France","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FRA/BSGM/2013/Binary/fra_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13522,250,"FRA","France","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FRA/BSGM/2013/DTE/fra_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13523,250,"FRA","France","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/FRA/BSGM/2015/DTE/fra_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13524,250,"FRA","France","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/FRA/BSGM/2016/DTE/fra_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13525,250,"FRA","France","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/FRA/BSGM/2017/DTE/fra_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13526,250,"FRA","France","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/FRA/BSGM/2018/DTE/fra_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13527,250,"FRA","France","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/FRA/BSGM/2019/DTE/fra_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13528,250,"FRA","France","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/FRA/BSGM/2020/DTE/fra_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13529,254,"GUF","French Guiana","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GUF/BSGM/2001/Binary/guf_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13530,254,"GUF","French Guiana","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GUF/BSGM/2001/DTE/guf_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13531,254,"GUF","French Guiana","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GUF/BSGM/2002/Binary/guf_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13532,254,"GUF","French Guiana","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GUF/BSGM/2002/DTE/guf_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13533,254,"GUF","French Guiana","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GUF/BSGM/2003/Binary/guf_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13534,254,"GUF","French Guiana","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GUF/BSGM/2003/DTE/guf_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13535,254,"GUF","French Guiana","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GUF/BSGM/2004/Binary/guf_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13536,254,"GUF","French Guiana","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GUF/BSGM/2004/DTE/guf_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13537,254,"GUF","French Guiana","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GUF/BSGM/2005/Binary/guf_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13538,254,"GUF","French Guiana","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GUF/BSGM/2005/DTE/guf_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13539,254,"GUF","French Guiana","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GUF/BSGM/2006/Binary/guf_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13540,254,"GUF","French Guiana","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GUF/BSGM/2006/DTE/guf_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13541,254,"GUF","French Guiana","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GUF/BSGM/2007/Binary/guf_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13542,254,"GUF","French Guiana","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GUF/BSGM/2007/DTE/guf_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13543,254,"GUF","French Guiana","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GUF/BSGM/2008/Binary/guf_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13544,254,"GUF","French Guiana","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GUF/BSGM/2008/DTE/guf_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13545,254,"GUF","French Guiana","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GUF/BSGM/2009/Binary/guf_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13546,254,"GUF","French Guiana","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GUF/BSGM/2009/DTE/guf_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13547,254,"GUF","French Guiana","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GUF/BSGM/2010/Binary/guf_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13548,254,"GUF","French Guiana","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GUF/BSGM/2010/DTE/guf_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13549,254,"GUF","French Guiana","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GUF/BSGM/2011/Binary/guf_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13550,254,"GUF","French Guiana","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GUF/BSGM/2011/DTE/guf_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13551,254,"GUF","French Guiana","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GUF/BSGM/2013/Binary/guf_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13552,254,"GUF","French Guiana","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GUF/BSGM/2013/DTE/guf_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13553,254,"GUF","French Guiana","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GUF/BSGM/2015/DTE/guf_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13554,254,"GUF","French Guiana","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GUF/BSGM/2016/DTE/guf_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13555,254,"GUF","French Guiana","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GUF/BSGM/2017/DTE/guf_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13556,254,"GUF","French Guiana","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GUF/BSGM/2018/DTE/guf_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13557,254,"GUF","French Guiana","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GUF/BSGM/2019/DTE/guf_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13558,254,"GUF","French Guiana","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GUF/BSGM/2020/DTE/guf_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13559,258,"PYF","French Polynesia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PYF/BSGM/2001/Binary/pyf_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13560,258,"PYF","French Polynesia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PYF/BSGM/2001/DTE/pyf_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13561,258,"PYF","French Polynesia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PYF/BSGM/2002/Binary/pyf_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13562,258,"PYF","French Polynesia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PYF/BSGM/2002/DTE/pyf_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13563,258,"PYF","French Polynesia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PYF/BSGM/2003/Binary/pyf_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13564,258,"PYF","French Polynesia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PYF/BSGM/2003/DTE/pyf_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13565,258,"PYF","French Polynesia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PYF/BSGM/2004/Binary/pyf_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13566,258,"PYF","French Polynesia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PYF/BSGM/2004/DTE/pyf_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13567,258,"PYF","French Polynesia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PYF/BSGM/2005/Binary/pyf_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13568,258,"PYF","French Polynesia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PYF/BSGM/2005/DTE/pyf_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13569,258,"PYF","French Polynesia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PYF/BSGM/2006/Binary/pyf_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13570,258,"PYF","French Polynesia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PYF/BSGM/2006/DTE/pyf_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13571,258,"PYF","French Polynesia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PYF/BSGM/2007/Binary/pyf_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13572,258,"PYF","French Polynesia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PYF/BSGM/2007/DTE/pyf_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13573,258,"PYF","French Polynesia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PYF/BSGM/2008/Binary/pyf_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13574,258,"PYF","French Polynesia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PYF/BSGM/2008/DTE/pyf_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13575,258,"PYF","French Polynesia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PYF/BSGM/2009/Binary/pyf_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13576,258,"PYF","French Polynesia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PYF/BSGM/2009/DTE/pyf_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13577,258,"PYF","French Polynesia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PYF/BSGM/2010/Binary/pyf_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13578,258,"PYF","French Polynesia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PYF/BSGM/2010/DTE/pyf_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13579,258,"PYF","French Polynesia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PYF/BSGM/2011/Binary/pyf_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13580,258,"PYF","French Polynesia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PYF/BSGM/2011/DTE/pyf_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13581,258,"PYF","French Polynesia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PYF/BSGM/2013/Binary/pyf_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13582,258,"PYF","French Polynesia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PYF/BSGM/2013/DTE/pyf_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13583,258,"PYF","French Polynesia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PYF/BSGM/2015/DTE/pyf_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13584,258,"PYF","French Polynesia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PYF/BSGM/2016/DTE/pyf_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13585,258,"PYF","French Polynesia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PYF/BSGM/2017/DTE/pyf_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13586,258,"PYF","French Polynesia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PYF/BSGM/2018/DTE/pyf_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13587,258,"PYF","French Polynesia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PYF/BSGM/2019/DTE/pyf_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13588,258,"PYF","French Polynesia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PYF/BSGM/2020/DTE/pyf_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13589,260,"ATF","French Southern Territories","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ATF/BSGM/2001/Binary/atf_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13590,260,"ATF","French Southern Territories","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ATF/BSGM/2001/DTE/atf_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13591,260,"ATF","French Southern Territories","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ATF/BSGM/2002/Binary/atf_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13592,260,"ATF","French Southern Territories","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ATF/BSGM/2002/DTE/atf_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13593,260,"ATF","French Southern Territories","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ATF/BSGM/2003/Binary/atf_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13594,260,"ATF","French Southern Territories","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ATF/BSGM/2003/DTE/atf_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13595,260,"ATF","French Southern Territories","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ATF/BSGM/2004/Binary/atf_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13596,260,"ATF","French Southern Territories","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ATF/BSGM/2004/DTE/atf_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13597,260,"ATF","French Southern Territories","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ATF/BSGM/2005/Binary/atf_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13598,260,"ATF","French Southern Territories","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ATF/BSGM/2005/DTE/atf_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13599,260,"ATF","French Southern Territories","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ATF/BSGM/2006/Binary/atf_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13600,260,"ATF","French Southern Territories","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ATF/BSGM/2006/DTE/atf_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13601,260,"ATF","French Southern Territories","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ATF/BSGM/2007/Binary/atf_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13602,260,"ATF","French Southern Territories","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ATF/BSGM/2007/DTE/atf_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13603,260,"ATF","French Southern Territories","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ATF/BSGM/2008/Binary/atf_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13604,260,"ATF","French Southern Territories","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ATF/BSGM/2008/DTE/atf_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13605,260,"ATF","French Southern Territories","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ATF/BSGM/2009/Binary/atf_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13606,260,"ATF","French Southern Territories","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ATF/BSGM/2009/DTE/atf_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13607,260,"ATF","French Southern Territories","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ATF/BSGM/2010/Binary/atf_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13608,260,"ATF","French Southern Territories","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ATF/BSGM/2010/DTE/atf_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13609,260,"ATF","French Southern Territories","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ATF/BSGM/2011/Binary/atf_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13610,260,"ATF","French Southern Territories","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ATF/BSGM/2011/DTE/atf_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13611,260,"ATF","French Southern Territories","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ATF/BSGM/2013/Binary/atf_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13612,260,"ATF","French Southern Territories","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ATF/BSGM/2013/DTE/atf_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13613,260,"ATF","French Southern Territories","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ATF/BSGM/2015/DTE/atf_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13614,260,"ATF","French Southern Territories","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ATF/BSGM/2016/DTE/atf_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13615,260,"ATF","French Southern Territories","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ATF/BSGM/2017/DTE/atf_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13616,260,"ATF","French Southern Territories","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ATF/BSGM/2018/DTE/atf_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13617,260,"ATF","French Southern Territories","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ATF/BSGM/2019/DTE/atf_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13618,260,"ATF","French Southern Territories","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ATF/BSGM/2020/DTE/atf_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13619,262,"DJI","Djibouti","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DJI/BSGM/2001/Binary/dji_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13620,262,"DJI","Djibouti","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DJI/BSGM/2001/DTE/dji_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13621,262,"DJI","Djibouti","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DJI/BSGM/2002/Binary/dji_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13622,262,"DJI","Djibouti","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DJI/BSGM/2002/DTE/dji_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13623,262,"DJI","Djibouti","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DJI/BSGM/2003/Binary/dji_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13624,262,"DJI","Djibouti","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DJI/BSGM/2003/DTE/dji_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13625,262,"DJI","Djibouti","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DJI/BSGM/2004/Binary/dji_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13626,262,"DJI","Djibouti","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DJI/BSGM/2004/DTE/dji_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13627,262,"DJI","Djibouti","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DJI/BSGM/2005/Binary/dji_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13628,262,"DJI","Djibouti","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DJI/BSGM/2005/DTE/dji_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13629,262,"DJI","Djibouti","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DJI/BSGM/2006/Binary/dji_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13630,262,"DJI","Djibouti","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DJI/BSGM/2006/DTE/dji_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13631,262,"DJI","Djibouti","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DJI/BSGM/2007/Binary/dji_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13632,262,"DJI","Djibouti","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DJI/BSGM/2007/DTE/dji_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13633,262,"DJI","Djibouti","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DJI/BSGM/2008/Binary/dji_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13634,262,"DJI","Djibouti","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DJI/BSGM/2008/DTE/dji_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13635,262,"DJI","Djibouti","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DJI/BSGM/2009/Binary/dji_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13636,262,"DJI","Djibouti","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DJI/BSGM/2009/DTE/dji_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13637,262,"DJI","Djibouti","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DJI/BSGM/2010/Binary/dji_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13638,262,"DJI","Djibouti","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DJI/BSGM/2010/DTE/dji_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13639,262,"DJI","Djibouti","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DJI/BSGM/2011/Binary/dji_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13640,262,"DJI","Djibouti","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DJI/BSGM/2011/DTE/dji_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13641,262,"DJI","Djibouti","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DJI/BSGM/2013/Binary/dji_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13642,262,"DJI","Djibouti","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DJI/BSGM/2013/DTE/dji_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13643,262,"DJI","Djibouti","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/DJI/BSGM/2015/DTE/dji_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13644,262,"DJI","Djibouti","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/DJI/BSGM/2016/DTE/dji_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13645,262,"DJI","Djibouti","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/DJI/BSGM/2017/DTE/dji_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13646,262,"DJI","Djibouti","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/DJI/BSGM/2018/DTE/dji_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13647,262,"DJI","Djibouti","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/DJI/BSGM/2019/DTE/dji_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13648,262,"DJI","Djibouti","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/DJI/BSGM/2020/DTE/dji_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13649,266,"GAB","Gabon","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GAB/BSGM/2001/Binary/gab_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13650,266,"GAB","Gabon","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GAB/BSGM/2001/DTE/gab_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13651,266,"GAB","Gabon","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GAB/BSGM/2002/Binary/gab_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13652,266,"GAB","Gabon","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GAB/BSGM/2002/DTE/gab_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13653,266,"GAB","Gabon","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GAB/BSGM/2003/Binary/gab_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13654,266,"GAB","Gabon","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GAB/BSGM/2003/DTE/gab_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13655,266,"GAB","Gabon","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GAB/BSGM/2004/Binary/gab_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13656,266,"GAB","Gabon","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GAB/BSGM/2004/DTE/gab_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13657,266,"GAB","Gabon","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GAB/BSGM/2005/Binary/gab_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13658,266,"GAB","Gabon","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GAB/BSGM/2005/DTE/gab_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13659,266,"GAB","Gabon","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GAB/BSGM/2006/Binary/gab_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13660,266,"GAB","Gabon","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GAB/BSGM/2006/DTE/gab_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13661,266,"GAB","Gabon","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GAB/BSGM/2007/Binary/gab_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13662,266,"GAB","Gabon","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GAB/BSGM/2007/DTE/gab_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13663,266,"GAB","Gabon","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GAB/BSGM/2008/Binary/gab_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13664,266,"GAB","Gabon","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GAB/BSGM/2008/DTE/gab_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13665,266,"GAB","Gabon","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GAB/BSGM/2009/Binary/gab_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13666,266,"GAB","Gabon","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GAB/BSGM/2009/DTE/gab_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13667,266,"GAB","Gabon","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GAB/BSGM/2010/Binary/gab_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13668,266,"GAB","Gabon","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GAB/BSGM/2010/DTE/gab_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13669,266,"GAB","Gabon","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GAB/BSGM/2011/Binary/gab_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13670,266,"GAB","Gabon","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GAB/BSGM/2011/DTE/gab_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13671,266,"GAB","Gabon","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GAB/BSGM/2013/Binary/gab_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13672,266,"GAB","Gabon","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GAB/BSGM/2013/DTE/gab_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13673,266,"GAB","Gabon","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GAB/BSGM/2015/DTE/gab_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13674,266,"GAB","Gabon","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GAB/BSGM/2016/DTE/gab_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13675,266,"GAB","Gabon","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GAB/BSGM/2017/DTE/gab_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13676,266,"GAB","Gabon","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GAB/BSGM/2018/DTE/gab_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13677,266,"GAB","Gabon","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GAB/BSGM/2019/DTE/gab_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13678,266,"GAB","Gabon","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GAB/BSGM/2020/DTE/gab_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13679,268,"GEO","Georgia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GEO/BSGM/2001/Binary/geo_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13680,268,"GEO","Georgia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GEO/BSGM/2001/DTE/geo_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13681,268,"GEO","Georgia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GEO/BSGM/2002/Binary/geo_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13682,268,"GEO","Georgia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GEO/BSGM/2002/DTE/geo_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13683,268,"GEO","Georgia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GEO/BSGM/2003/Binary/geo_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13684,268,"GEO","Georgia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GEO/BSGM/2003/DTE/geo_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13685,268,"GEO","Georgia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GEO/BSGM/2004/Binary/geo_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13686,268,"GEO","Georgia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GEO/BSGM/2004/DTE/geo_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13687,268,"GEO","Georgia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GEO/BSGM/2005/Binary/geo_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13688,268,"GEO","Georgia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GEO/BSGM/2005/DTE/geo_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13689,268,"GEO","Georgia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GEO/BSGM/2006/Binary/geo_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13690,268,"GEO","Georgia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GEO/BSGM/2006/DTE/geo_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13691,268,"GEO","Georgia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GEO/BSGM/2007/Binary/geo_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13692,268,"GEO","Georgia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GEO/BSGM/2007/DTE/geo_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13693,268,"GEO","Georgia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GEO/BSGM/2008/Binary/geo_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13694,268,"GEO","Georgia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GEO/BSGM/2008/DTE/geo_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13695,268,"GEO","Georgia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GEO/BSGM/2009/Binary/geo_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13696,268,"GEO","Georgia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GEO/BSGM/2009/DTE/geo_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13697,268,"GEO","Georgia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GEO/BSGM/2010/Binary/geo_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13698,268,"GEO","Georgia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GEO/BSGM/2010/DTE/geo_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13699,268,"GEO","Georgia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GEO/BSGM/2011/Binary/geo_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13700,268,"GEO","Georgia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GEO/BSGM/2011/DTE/geo_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13701,268,"GEO","Georgia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GEO/BSGM/2013/Binary/geo_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13702,268,"GEO","Georgia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GEO/BSGM/2013/DTE/geo_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13703,268,"GEO","Georgia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GEO/BSGM/2015/DTE/geo_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13704,268,"GEO","Georgia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GEO/BSGM/2016/DTE/geo_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13705,268,"GEO","Georgia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GEO/BSGM/2017/DTE/geo_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13706,268,"GEO","Georgia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GEO/BSGM/2018/DTE/geo_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13707,268,"GEO","Georgia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GEO/BSGM/2019/DTE/geo_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13708,268,"GEO","Georgia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GEO/BSGM/2020/DTE/geo_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13709,270,"GMB","Gambia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GMB/BSGM/2001/Binary/gmb_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13710,270,"GMB","Gambia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GMB/BSGM/2001/DTE/gmb_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13711,270,"GMB","Gambia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GMB/BSGM/2002/Binary/gmb_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13712,270,"GMB","Gambia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GMB/BSGM/2002/DTE/gmb_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13713,270,"GMB","Gambia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GMB/BSGM/2003/Binary/gmb_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13714,270,"GMB","Gambia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GMB/BSGM/2003/DTE/gmb_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13715,270,"GMB","Gambia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GMB/BSGM/2004/Binary/gmb_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13716,270,"GMB","Gambia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GMB/BSGM/2004/DTE/gmb_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13717,270,"GMB","Gambia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GMB/BSGM/2005/Binary/gmb_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13718,270,"GMB","Gambia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GMB/BSGM/2005/DTE/gmb_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13719,270,"GMB","Gambia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GMB/BSGM/2006/Binary/gmb_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13720,270,"GMB","Gambia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GMB/BSGM/2006/DTE/gmb_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13721,270,"GMB","Gambia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GMB/BSGM/2007/Binary/gmb_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13722,270,"GMB","Gambia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GMB/BSGM/2007/DTE/gmb_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13723,270,"GMB","Gambia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GMB/BSGM/2008/Binary/gmb_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13724,270,"GMB","Gambia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GMB/BSGM/2008/DTE/gmb_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13725,270,"GMB","Gambia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GMB/BSGM/2009/Binary/gmb_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13726,270,"GMB","Gambia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GMB/BSGM/2009/DTE/gmb_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13727,270,"GMB","Gambia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GMB/BSGM/2010/Binary/gmb_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13728,270,"GMB","Gambia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GMB/BSGM/2010/DTE/gmb_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13729,270,"GMB","Gambia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GMB/BSGM/2011/Binary/gmb_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13730,270,"GMB","Gambia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GMB/BSGM/2011/DTE/gmb_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13731,270,"GMB","Gambia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GMB/BSGM/2013/Binary/gmb_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13732,270,"GMB","Gambia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GMB/BSGM/2013/DTE/gmb_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13733,270,"GMB","Gambia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GMB/BSGM/2015/DTE/gmb_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13734,270,"GMB","Gambia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GMB/BSGM/2016/DTE/gmb_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13735,270,"GMB","Gambia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GMB/BSGM/2017/DTE/gmb_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13736,270,"GMB","Gambia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GMB/BSGM/2018/DTE/gmb_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13737,270,"GMB","Gambia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GMB/BSGM/2019/DTE/gmb_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13738,270,"GMB","Gambia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GMB/BSGM/2020/DTE/gmb_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13739,275,"PSE","Palestina","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PSE/BSGM/2001/Binary/pse_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13740,275,"PSE","Palestina","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PSE/BSGM/2001/DTE/pse_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13741,275,"PSE","Palestina","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PSE/BSGM/2002/Binary/pse_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13742,275,"PSE","Palestina","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PSE/BSGM/2002/DTE/pse_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13743,275,"PSE","Palestina","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PSE/BSGM/2003/Binary/pse_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13744,275,"PSE","Palestina","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PSE/BSGM/2003/DTE/pse_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13745,275,"PSE","Palestina","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PSE/BSGM/2004/Binary/pse_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13746,275,"PSE","Palestina","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PSE/BSGM/2004/DTE/pse_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13747,275,"PSE","Palestina","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PSE/BSGM/2005/Binary/pse_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13748,275,"PSE","Palestina","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PSE/BSGM/2005/DTE/pse_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13749,275,"PSE","Palestina","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PSE/BSGM/2006/Binary/pse_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13750,275,"PSE","Palestina","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PSE/BSGM/2006/DTE/pse_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13751,275,"PSE","Palestina","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PSE/BSGM/2007/Binary/pse_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13752,275,"PSE","Palestina","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PSE/BSGM/2007/DTE/pse_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13753,275,"PSE","Palestina","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PSE/BSGM/2008/Binary/pse_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13754,275,"PSE","Palestina","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PSE/BSGM/2008/DTE/pse_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13755,275,"PSE","Palestina","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PSE/BSGM/2009/Binary/pse_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13756,275,"PSE","Palestina","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PSE/BSGM/2009/DTE/pse_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13757,275,"PSE","Palestina","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PSE/BSGM/2010/Binary/pse_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13758,275,"PSE","Palestina","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PSE/BSGM/2010/DTE/pse_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13759,275,"PSE","Palestina","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PSE/BSGM/2011/Binary/pse_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13760,275,"PSE","Palestina","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PSE/BSGM/2011/DTE/pse_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13761,275,"PSE","Palestina","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PSE/BSGM/2013/Binary/pse_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13762,275,"PSE","Palestina","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PSE/BSGM/2013/DTE/pse_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13763,275,"PSE","Palestina","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PSE/BSGM/2015/DTE/pse_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13764,275,"PSE","Palestina","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PSE/BSGM/2016/DTE/pse_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13765,275,"PSE","Palestina","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PSE/BSGM/2017/DTE/pse_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13766,275,"PSE","Palestina","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PSE/BSGM/2018/DTE/pse_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13767,275,"PSE","Palestina","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PSE/BSGM/2019/DTE/pse_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13768,275,"PSE","Palestina","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PSE/BSGM/2020/DTE/pse_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13769,276,"DEU","Germany","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DEU/BSGM/2001/Binary/deu_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13770,276,"DEU","Germany","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/DEU/BSGM/2001/DTE/deu_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13771,276,"DEU","Germany","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DEU/BSGM/2002/Binary/deu_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13772,276,"DEU","Germany","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/DEU/BSGM/2002/DTE/deu_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13773,276,"DEU","Germany","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DEU/BSGM/2003/Binary/deu_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13774,276,"DEU","Germany","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/DEU/BSGM/2003/DTE/deu_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13775,276,"DEU","Germany","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DEU/BSGM/2004/Binary/deu_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13776,276,"DEU","Germany","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/DEU/BSGM/2004/DTE/deu_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13777,276,"DEU","Germany","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DEU/BSGM/2005/Binary/deu_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13778,276,"DEU","Germany","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/DEU/BSGM/2005/DTE/deu_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13779,276,"DEU","Germany","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DEU/BSGM/2006/Binary/deu_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13780,276,"DEU","Germany","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/DEU/BSGM/2006/DTE/deu_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13781,276,"DEU","Germany","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DEU/BSGM/2007/Binary/deu_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13782,276,"DEU","Germany","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/DEU/BSGM/2007/DTE/deu_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13783,276,"DEU","Germany","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DEU/BSGM/2008/Binary/deu_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13784,276,"DEU","Germany","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/DEU/BSGM/2008/DTE/deu_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13785,276,"DEU","Germany","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DEU/BSGM/2009/Binary/deu_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13786,276,"DEU","Germany","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/DEU/BSGM/2009/DTE/deu_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13787,276,"DEU","Germany","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DEU/BSGM/2010/Binary/deu_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13788,276,"DEU","Germany","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/DEU/BSGM/2010/DTE/deu_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13789,276,"DEU","Germany","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DEU/BSGM/2011/Binary/deu_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13790,276,"DEU","Germany","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/DEU/BSGM/2011/DTE/deu_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13791,276,"DEU","Germany","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DEU/BSGM/2013/Binary/deu_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13792,276,"DEU","Germany","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/DEU/BSGM/2013/DTE/deu_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13793,276,"DEU","Germany","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/DEU/BSGM/2015/DTE/deu_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13794,276,"DEU","Germany","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/DEU/BSGM/2016/DTE/deu_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13795,276,"DEU","Germany","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/DEU/BSGM/2017/DTE/deu_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13796,276,"DEU","Germany","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/DEU/BSGM/2018/DTE/deu_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13797,276,"DEU","Germany","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/DEU/BSGM/2019/DTE/deu_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13798,276,"DEU","Germany","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/DEU/BSGM/2020/DTE/deu_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13799,288,"GHA","Ghana","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GHA/BSGM/2001/Binary/gha_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13800,288,"GHA","Ghana","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GHA/BSGM/2001/DTE/gha_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13801,288,"GHA","Ghana","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GHA/BSGM/2002/Binary/gha_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13802,288,"GHA","Ghana","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GHA/BSGM/2002/DTE/gha_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13803,288,"GHA","Ghana","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GHA/BSGM/2003/Binary/gha_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13804,288,"GHA","Ghana","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GHA/BSGM/2003/DTE/gha_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13805,288,"GHA","Ghana","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GHA/BSGM/2004/Binary/gha_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13806,288,"GHA","Ghana","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GHA/BSGM/2004/DTE/gha_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13807,288,"GHA","Ghana","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GHA/BSGM/2005/Binary/gha_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13808,288,"GHA","Ghana","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GHA/BSGM/2005/DTE/gha_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13809,288,"GHA","Ghana","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GHA/BSGM/2006/Binary/gha_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13810,288,"GHA","Ghana","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GHA/BSGM/2006/DTE/gha_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13811,288,"GHA","Ghana","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GHA/BSGM/2007/Binary/gha_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13812,288,"GHA","Ghana","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GHA/BSGM/2007/DTE/gha_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13813,288,"GHA","Ghana","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GHA/BSGM/2008/Binary/gha_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13814,288,"GHA","Ghana","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GHA/BSGM/2008/DTE/gha_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13815,288,"GHA","Ghana","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GHA/BSGM/2009/Binary/gha_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13816,288,"GHA","Ghana","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GHA/BSGM/2009/DTE/gha_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13817,288,"GHA","Ghana","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GHA/BSGM/2010/Binary/gha_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13818,288,"GHA","Ghana","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GHA/BSGM/2010/DTE/gha_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13819,288,"GHA","Ghana","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GHA/BSGM/2011/Binary/gha_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13820,288,"GHA","Ghana","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GHA/BSGM/2011/DTE/gha_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13821,288,"GHA","Ghana","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GHA/BSGM/2013/Binary/gha_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13822,288,"GHA","Ghana","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GHA/BSGM/2013/DTE/gha_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13823,288,"GHA","Ghana","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GHA/BSGM/2015/DTE/gha_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13824,288,"GHA","Ghana","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GHA/BSGM/2016/DTE/gha_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13825,288,"GHA","Ghana","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GHA/BSGM/2017/DTE/gha_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13826,288,"GHA","Ghana","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GHA/BSGM/2018/DTE/gha_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13827,288,"GHA","Ghana","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GHA/BSGM/2019/DTE/gha_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13828,288,"GHA","Ghana","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GHA/BSGM/2020/DTE/gha_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13829,292,"GIB","Gibraltar","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GIB/BSGM/2001/Binary/gib_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13830,292,"GIB","Gibraltar","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GIB/BSGM/2001/DTE/gib_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13831,292,"GIB","Gibraltar","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GIB/BSGM/2002/Binary/gib_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13832,292,"GIB","Gibraltar","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GIB/BSGM/2002/DTE/gib_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13833,292,"GIB","Gibraltar","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GIB/BSGM/2003/Binary/gib_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13834,292,"GIB","Gibraltar","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GIB/BSGM/2003/DTE/gib_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13835,292,"GIB","Gibraltar","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GIB/BSGM/2004/Binary/gib_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13836,292,"GIB","Gibraltar","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GIB/BSGM/2004/DTE/gib_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13837,292,"GIB","Gibraltar","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GIB/BSGM/2005/Binary/gib_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13838,292,"GIB","Gibraltar","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GIB/BSGM/2005/DTE/gib_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13839,292,"GIB","Gibraltar","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GIB/BSGM/2006/Binary/gib_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13840,292,"GIB","Gibraltar","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GIB/BSGM/2006/DTE/gib_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13841,292,"GIB","Gibraltar","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GIB/BSGM/2007/Binary/gib_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13842,292,"GIB","Gibraltar","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GIB/BSGM/2007/DTE/gib_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13843,292,"GIB","Gibraltar","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GIB/BSGM/2008/Binary/gib_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13844,292,"GIB","Gibraltar","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GIB/BSGM/2008/DTE/gib_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13845,292,"GIB","Gibraltar","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GIB/BSGM/2009/Binary/gib_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13846,292,"GIB","Gibraltar","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GIB/BSGM/2009/DTE/gib_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13847,292,"GIB","Gibraltar","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GIB/BSGM/2010/Binary/gib_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13848,292,"GIB","Gibraltar","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GIB/BSGM/2010/DTE/gib_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13849,292,"GIB","Gibraltar","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GIB/BSGM/2011/Binary/gib_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13850,292,"GIB","Gibraltar","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GIB/BSGM/2011/DTE/gib_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13851,292,"GIB","Gibraltar","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GIB/BSGM/2013/DTE/gib_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13852,292,"GIB","Gibraltar","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GIB/BSGM/2015/DTE/gib_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13853,292,"GIB","Gibraltar","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GIB/BSGM/2016/DTE/gib_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13854,292,"GIB","Gibraltar","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GIB/BSGM/2017/DTE/gib_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13855,292,"GIB","Gibraltar","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GIB/BSGM/2018/DTE/gib_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13856,292,"GIB","Gibraltar","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GIB/BSGM/2019/DTE/gib_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13857,292,"GIB","Gibraltar","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GIB/BSGM/2020/DTE/gib_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13858,296,"KIR","Kiribati","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KIR/BSGM/2001/Binary/kir_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13859,296,"KIR","Kiribati","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KIR/BSGM/2001/DTE/kir_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13860,296,"KIR","Kiribati","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KIR/BSGM/2002/Binary/kir_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13861,296,"KIR","Kiribati","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KIR/BSGM/2002/DTE/kir_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13862,296,"KIR","Kiribati","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KIR/BSGM/2003/Binary/kir_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13863,296,"KIR","Kiribati","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KIR/BSGM/2003/DTE/kir_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13864,296,"KIR","Kiribati","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KIR/BSGM/2004/Binary/kir_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13865,296,"KIR","Kiribati","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KIR/BSGM/2004/DTE/kir_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13866,296,"KIR","Kiribati","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KIR/BSGM/2005/Binary/kir_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13867,296,"KIR","Kiribati","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KIR/BSGM/2005/DTE/kir_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13868,296,"KIR","Kiribati","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KIR/BSGM/2006/Binary/kir_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13869,296,"KIR","Kiribati","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KIR/BSGM/2006/DTE/kir_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13870,296,"KIR","Kiribati","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KIR/BSGM/2007/Binary/kir_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13871,296,"KIR","Kiribati","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KIR/BSGM/2007/DTE/kir_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13872,296,"KIR","Kiribati","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KIR/BSGM/2008/Binary/kir_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13873,296,"KIR","Kiribati","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KIR/BSGM/2008/DTE/kir_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13874,296,"KIR","Kiribati","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KIR/BSGM/2009/Binary/kir_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13875,296,"KIR","Kiribati","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KIR/BSGM/2009/DTE/kir_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13876,296,"KIR","Kiribati","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KIR/BSGM/2010/Binary/kir_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13877,296,"KIR","Kiribati","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KIR/BSGM/2010/DTE/kir_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13878,296,"KIR","Kiribati","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KIR/BSGM/2011/Binary/kir_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13879,296,"KIR","Kiribati","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KIR/BSGM/2011/DTE/kir_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13880,296,"KIR","Kiribati","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KIR/BSGM/2013/Binary/kir_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13881,296,"KIR","Kiribati","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KIR/BSGM/2013/DTE/kir_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13882,296,"KIR","Kiribati","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/KIR/BSGM/2015/DTE/kir_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13883,296,"KIR","Kiribati","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/KIR/BSGM/2016/DTE/kir_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13884,296,"KIR","Kiribati","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/KIR/BSGM/2017/DTE/kir_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13885,296,"KIR","Kiribati","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/KIR/BSGM/2018/DTE/kir_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13886,296,"KIR","Kiribati","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/KIR/BSGM/2019/DTE/kir_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13887,296,"KIR","Kiribati","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/KIR/BSGM/2020/DTE/kir_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13888,300,"GRC","Greece","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GRC/BSGM/2001/Binary/grc_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13889,300,"GRC","Greece","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GRC/BSGM/2001/DTE/grc_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13890,300,"GRC","Greece","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GRC/BSGM/2002/Binary/grc_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13891,300,"GRC","Greece","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GRC/BSGM/2002/DTE/grc_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13892,300,"GRC","Greece","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GRC/BSGM/2003/Binary/grc_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13893,300,"GRC","Greece","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GRC/BSGM/2003/DTE/grc_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13894,300,"GRC","Greece","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GRC/BSGM/2004/Binary/grc_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13895,300,"GRC","Greece","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GRC/BSGM/2004/DTE/grc_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13896,300,"GRC","Greece","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GRC/BSGM/2005/Binary/grc_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13897,300,"GRC","Greece","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GRC/BSGM/2005/DTE/grc_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13898,300,"GRC","Greece","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GRC/BSGM/2006/Binary/grc_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13899,300,"GRC","Greece","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GRC/BSGM/2006/DTE/grc_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13900,300,"GRC","Greece","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GRC/BSGM/2007/Binary/grc_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13901,300,"GRC","Greece","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GRC/BSGM/2007/DTE/grc_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13902,300,"GRC","Greece","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GRC/BSGM/2008/Binary/grc_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13903,300,"GRC","Greece","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GRC/BSGM/2008/DTE/grc_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13904,300,"GRC","Greece","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GRC/BSGM/2009/Binary/grc_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13905,300,"GRC","Greece","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GRC/BSGM/2009/DTE/grc_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13906,300,"GRC","Greece","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GRC/BSGM/2010/Binary/grc_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13907,300,"GRC","Greece","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GRC/BSGM/2010/DTE/grc_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13908,300,"GRC","Greece","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GRC/BSGM/2011/Binary/grc_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13909,300,"GRC","Greece","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GRC/BSGM/2011/DTE/grc_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13910,300,"GRC","Greece","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GRC/BSGM/2013/Binary/grc_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13911,300,"GRC","Greece","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GRC/BSGM/2013/DTE/grc_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13912,300,"GRC","Greece","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GRC/BSGM/2015/DTE/grc_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13913,300,"GRC","Greece","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GRC/BSGM/2016/DTE/grc_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13914,300,"GRC","Greece","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GRC/BSGM/2017/DTE/grc_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13915,300,"GRC","Greece","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GRC/BSGM/2018/DTE/grc_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13916,300,"GRC","Greece","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GRC/BSGM/2019/DTE/grc_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13917,300,"GRC","Greece","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GRC/BSGM/2020/DTE/grc_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13918,308,"GRD","Grenada","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GRD/BSGM/2001/Binary/grd_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13919,308,"GRD","Grenada","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GRD/BSGM/2001/DTE/grd_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13920,308,"GRD","Grenada","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GRD/BSGM/2002/Binary/grd_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13921,308,"GRD","Grenada","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GRD/BSGM/2002/DTE/grd_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13922,308,"GRD","Grenada","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GRD/BSGM/2003/Binary/grd_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13923,308,"GRD","Grenada","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GRD/BSGM/2003/DTE/grd_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13924,308,"GRD","Grenada","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GRD/BSGM/2004/Binary/grd_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13925,308,"GRD","Grenada","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GRD/BSGM/2004/DTE/grd_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13926,308,"GRD","Grenada","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GRD/BSGM/2005/Binary/grd_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13927,308,"GRD","Grenada","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GRD/BSGM/2005/DTE/grd_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13928,308,"GRD","Grenada","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GRD/BSGM/2006/Binary/grd_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13929,308,"GRD","Grenada","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GRD/BSGM/2006/DTE/grd_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13930,308,"GRD","Grenada","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GRD/BSGM/2007/Binary/grd_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13931,308,"GRD","Grenada","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GRD/BSGM/2007/DTE/grd_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13932,308,"GRD","Grenada","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GRD/BSGM/2008/Binary/grd_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13933,308,"GRD","Grenada","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GRD/BSGM/2008/DTE/grd_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13934,308,"GRD","Grenada","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GRD/BSGM/2009/Binary/grd_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13935,308,"GRD","Grenada","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GRD/BSGM/2009/DTE/grd_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13936,308,"GRD","Grenada","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GRD/BSGM/2010/Binary/grd_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13937,308,"GRD","Grenada","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GRD/BSGM/2010/DTE/grd_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13938,308,"GRD","Grenada","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GRD/BSGM/2011/Binary/grd_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13939,308,"GRD","Grenada","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GRD/BSGM/2011/DTE/grd_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13940,308,"GRD","Grenada","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GRD/BSGM/2013/Binary/grd_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13941,308,"GRD","Grenada","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GRD/BSGM/2013/DTE/grd_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13942,308,"GRD","Grenada","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GRD/BSGM/2015/DTE/grd_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13943,308,"GRD","Grenada","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GRD/BSGM/2016/DTE/grd_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13944,308,"GRD","Grenada","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GRD/BSGM/2017/DTE/grd_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13945,308,"GRD","Grenada","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GRD/BSGM/2018/DTE/grd_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13946,308,"GRD","Grenada","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GRD/BSGM/2019/DTE/grd_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13947,308,"GRD","Grenada","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GRD/BSGM/2020/DTE/grd_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13948,312,"GLP","Guadeloupe","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GLP/BSGM/2001/Binary/glp_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13949,312,"GLP","Guadeloupe","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GLP/BSGM/2001/DTE/glp_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13950,312,"GLP","Guadeloupe","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GLP/BSGM/2002/Binary/glp_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13951,312,"GLP","Guadeloupe","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GLP/BSGM/2002/DTE/glp_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13952,312,"GLP","Guadeloupe","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GLP/BSGM/2003/Binary/glp_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13953,312,"GLP","Guadeloupe","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GLP/BSGM/2003/DTE/glp_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13954,312,"GLP","Guadeloupe","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GLP/BSGM/2004/Binary/glp_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13955,312,"GLP","Guadeloupe","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GLP/BSGM/2004/DTE/glp_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13956,312,"GLP","Guadeloupe","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GLP/BSGM/2005/Binary/glp_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13957,312,"GLP","Guadeloupe","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GLP/BSGM/2005/DTE/glp_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13958,312,"GLP","Guadeloupe","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GLP/BSGM/2006/Binary/glp_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13959,312,"GLP","Guadeloupe","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GLP/BSGM/2006/DTE/glp_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13960,312,"GLP","Guadeloupe","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GLP/BSGM/2007/Binary/glp_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13961,312,"GLP","Guadeloupe","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GLP/BSGM/2007/DTE/glp_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13962,312,"GLP","Guadeloupe","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GLP/BSGM/2008/Binary/glp_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13963,312,"GLP","Guadeloupe","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GLP/BSGM/2008/DTE/glp_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13964,312,"GLP","Guadeloupe","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GLP/BSGM/2009/Binary/glp_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13965,312,"GLP","Guadeloupe","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GLP/BSGM/2009/DTE/glp_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13966,312,"GLP","Guadeloupe","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GLP/BSGM/2010/Binary/glp_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13967,312,"GLP","Guadeloupe","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GLP/BSGM/2010/DTE/glp_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13968,312,"GLP","Guadeloupe","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GLP/BSGM/2011/Binary/glp_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13969,312,"GLP","Guadeloupe","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GLP/BSGM/2011/DTE/glp_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
13970,312,"GLP","Guadeloupe","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GLP/BSGM/2013/Binary/glp_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
13971,312,"GLP","Guadeloupe","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GLP/BSGM/2013/DTE/glp_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
13972,312,"GLP","Guadeloupe","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GLP/BSGM/2015/DTE/glp_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
13973,312,"GLP","Guadeloupe","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GLP/BSGM/2016/DTE/glp_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
13974,312,"GLP","Guadeloupe","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GLP/BSGM/2017/DTE/glp_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
13975,312,"GLP","Guadeloupe","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GLP/BSGM/2018/DTE/glp_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
13976,312,"GLP","Guadeloupe","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GLP/BSGM/2019/DTE/glp_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
13977,312,"GLP","Guadeloupe","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GLP/BSGM/2020/DTE/glp_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
13978,316,"GUM","Guam","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GUM/BSGM/2001/Binary/gum_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
13979,316,"GUM","Guam","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GUM/BSGM/2001/DTE/gum_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
13980,316,"GUM","Guam","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GUM/BSGM/2002/Binary/gum_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
13981,316,"GUM","Guam","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GUM/BSGM/2002/DTE/gum_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
13982,316,"GUM","Guam","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GUM/BSGM/2003/Binary/gum_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
13983,316,"GUM","Guam","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GUM/BSGM/2003/DTE/gum_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
13984,316,"GUM","Guam","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GUM/BSGM/2004/Binary/gum_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
13985,316,"GUM","Guam","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GUM/BSGM/2004/DTE/gum_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
13986,316,"GUM","Guam","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GUM/BSGM/2005/Binary/gum_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
13987,316,"GUM","Guam","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GUM/BSGM/2005/DTE/gum_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
13988,316,"GUM","Guam","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GUM/BSGM/2006/Binary/gum_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
13989,316,"GUM","Guam","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GUM/BSGM/2006/DTE/gum_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
13990,316,"GUM","Guam","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GUM/BSGM/2007/Binary/gum_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
13991,316,"GUM","Guam","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GUM/BSGM/2007/DTE/gum_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
13992,316,"GUM","Guam","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GUM/BSGM/2008/Binary/gum_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
13993,316,"GUM","Guam","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GUM/BSGM/2008/DTE/gum_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
13994,316,"GUM","Guam","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GUM/BSGM/2009/Binary/gum_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
13995,316,"GUM","Guam","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GUM/BSGM/2009/DTE/gum_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
13996,316,"GUM","Guam","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GUM/BSGM/2010/Binary/gum_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
13997,316,"GUM","Guam","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GUM/BSGM/2010/DTE/gum_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
13998,316,"GUM","Guam","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GUM/BSGM/2011/Binary/gum_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
13999,316,"GUM","Guam","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GUM/BSGM/2011/DTE/gum_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14000,316,"GUM","Guam","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GUM/BSGM/2013/Binary/gum_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14001,316,"GUM","Guam","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GUM/BSGM/2013/DTE/gum_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14002,316,"GUM","Guam","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GUM/BSGM/2015/DTE/gum_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14003,316,"GUM","Guam","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GUM/BSGM/2016/DTE/gum_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14004,316,"GUM","Guam","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GUM/BSGM/2017/DTE/gum_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14005,316,"GUM","Guam","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GUM/BSGM/2018/DTE/gum_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14006,316,"GUM","Guam","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GUM/BSGM/2019/DTE/gum_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14007,316,"GUM","Guam","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GUM/BSGM/2020/DTE/gum_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14008,320,"GTM","Guatemala","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GTM/BSGM/2001/Binary/gtm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14009,320,"GTM","Guatemala","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GTM/BSGM/2001/DTE/gtm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14010,320,"GTM","Guatemala","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GTM/BSGM/2002/Binary/gtm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14011,320,"GTM","Guatemala","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GTM/BSGM/2002/DTE/gtm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14012,320,"GTM","Guatemala","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GTM/BSGM/2003/Binary/gtm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14013,320,"GTM","Guatemala","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GTM/BSGM/2003/DTE/gtm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14014,320,"GTM","Guatemala","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GTM/BSGM/2004/Binary/gtm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14015,320,"GTM","Guatemala","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GTM/BSGM/2004/DTE/gtm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14016,320,"GTM","Guatemala","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GTM/BSGM/2005/Binary/gtm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14017,320,"GTM","Guatemala","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GTM/BSGM/2005/DTE/gtm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14018,320,"GTM","Guatemala","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GTM/BSGM/2006/Binary/gtm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14019,320,"GTM","Guatemala","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GTM/BSGM/2006/DTE/gtm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14020,320,"GTM","Guatemala","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GTM/BSGM/2007/Binary/gtm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14021,320,"GTM","Guatemala","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GTM/BSGM/2007/DTE/gtm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14022,320,"GTM","Guatemala","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GTM/BSGM/2008/Binary/gtm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14023,320,"GTM","Guatemala","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GTM/BSGM/2008/DTE/gtm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14024,320,"GTM","Guatemala","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GTM/BSGM/2009/Binary/gtm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14025,320,"GTM","Guatemala","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GTM/BSGM/2009/DTE/gtm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14026,320,"GTM","Guatemala","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GTM/BSGM/2010/Binary/gtm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14027,320,"GTM","Guatemala","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GTM/BSGM/2010/DTE/gtm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14028,320,"GTM","Guatemala","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GTM/BSGM/2011/Binary/gtm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14029,320,"GTM","Guatemala","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GTM/BSGM/2011/DTE/gtm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14030,320,"GTM","Guatemala","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GTM/BSGM/2013/Binary/gtm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14031,320,"GTM","Guatemala","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GTM/BSGM/2013/DTE/gtm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14032,320,"GTM","Guatemala","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GTM/BSGM/2015/DTE/gtm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14033,320,"GTM","Guatemala","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GTM/BSGM/2016/DTE/gtm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14034,320,"GTM","Guatemala","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GTM/BSGM/2017/DTE/gtm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14035,320,"GTM","Guatemala","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GTM/BSGM/2018/DTE/gtm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14036,320,"GTM","Guatemala","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GTM/BSGM/2019/DTE/gtm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14037,320,"GTM","Guatemala","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GTM/BSGM/2020/DTE/gtm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14038,324,"GIN","Guinea","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GIN/BSGM/2001/Binary/gin_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14039,324,"GIN","Guinea","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GIN/BSGM/2001/DTE/gin_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14040,324,"GIN","Guinea","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GIN/BSGM/2002/Binary/gin_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14041,324,"GIN","Guinea","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GIN/BSGM/2002/DTE/gin_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14042,324,"GIN","Guinea","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GIN/BSGM/2003/Binary/gin_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14043,324,"GIN","Guinea","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GIN/BSGM/2003/DTE/gin_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14044,324,"GIN","Guinea","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GIN/BSGM/2004/Binary/gin_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14045,324,"GIN","Guinea","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GIN/BSGM/2004/DTE/gin_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14046,324,"GIN","Guinea","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GIN/BSGM/2005/Binary/gin_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14047,324,"GIN","Guinea","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GIN/BSGM/2005/DTE/gin_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14048,324,"GIN","Guinea","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GIN/BSGM/2006/Binary/gin_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14049,324,"GIN","Guinea","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GIN/BSGM/2006/DTE/gin_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14050,324,"GIN","Guinea","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GIN/BSGM/2007/Binary/gin_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14051,324,"GIN","Guinea","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GIN/BSGM/2007/DTE/gin_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14052,324,"GIN","Guinea","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GIN/BSGM/2008/Binary/gin_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14053,324,"GIN","Guinea","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GIN/BSGM/2008/DTE/gin_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14054,324,"GIN","Guinea","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GIN/BSGM/2009/Binary/gin_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14055,324,"GIN","Guinea","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GIN/BSGM/2009/DTE/gin_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14056,324,"GIN","Guinea","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GIN/BSGM/2010/Binary/gin_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14057,324,"GIN","Guinea","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GIN/BSGM/2010/DTE/gin_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14058,324,"GIN","Guinea","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GIN/BSGM/2011/Binary/gin_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14059,324,"GIN","Guinea","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GIN/BSGM/2011/DTE/gin_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14060,324,"GIN","Guinea","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GIN/BSGM/2013/Binary/gin_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14061,324,"GIN","Guinea","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GIN/BSGM/2013/DTE/gin_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14062,324,"GIN","Guinea","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GIN/BSGM/2015/DTE/gin_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14063,324,"GIN","Guinea","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GIN/BSGM/2016/DTE/gin_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14064,324,"GIN","Guinea","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GIN/BSGM/2017/DTE/gin_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14065,324,"GIN","Guinea","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GIN/BSGM/2018/DTE/gin_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14066,324,"GIN","Guinea","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GIN/BSGM/2019/DTE/gin_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14067,324,"GIN","Guinea","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GIN/BSGM/2020/DTE/gin_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14068,328,"GUY","Guyana","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GUY/BSGM/2001/Binary/guy_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14069,328,"GUY","Guyana","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GUY/BSGM/2001/DTE/guy_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14070,328,"GUY","Guyana","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GUY/BSGM/2002/Binary/guy_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14071,328,"GUY","Guyana","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GUY/BSGM/2002/DTE/guy_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14072,328,"GUY","Guyana","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GUY/BSGM/2003/Binary/guy_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14073,328,"GUY","Guyana","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GUY/BSGM/2003/DTE/guy_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14074,328,"GUY","Guyana","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GUY/BSGM/2004/Binary/guy_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14075,328,"GUY","Guyana","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GUY/BSGM/2004/DTE/guy_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14076,328,"GUY","Guyana","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GUY/BSGM/2005/Binary/guy_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14077,328,"GUY","Guyana","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GUY/BSGM/2005/DTE/guy_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14078,328,"GUY","Guyana","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GUY/BSGM/2006/Binary/guy_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14079,328,"GUY","Guyana","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GUY/BSGM/2006/DTE/guy_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14080,328,"GUY","Guyana","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GUY/BSGM/2007/Binary/guy_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14081,328,"GUY","Guyana","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GUY/BSGM/2007/DTE/guy_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14082,328,"GUY","Guyana","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GUY/BSGM/2008/Binary/guy_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14083,328,"GUY","Guyana","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GUY/BSGM/2008/DTE/guy_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14084,328,"GUY","Guyana","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GUY/BSGM/2009/Binary/guy_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14085,328,"GUY","Guyana","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GUY/BSGM/2009/DTE/guy_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14086,328,"GUY","Guyana","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GUY/BSGM/2010/Binary/guy_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14087,328,"GUY","Guyana","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GUY/BSGM/2010/DTE/guy_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14088,328,"GUY","Guyana","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GUY/BSGM/2011/Binary/guy_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14089,328,"GUY","Guyana","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GUY/BSGM/2011/DTE/guy_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14090,328,"GUY","Guyana","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GUY/BSGM/2013/Binary/guy_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14091,328,"GUY","Guyana","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GUY/BSGM/2013/DTE/guy_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14092,328,"GUY","Guyana","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GUY/BSGM/2015/DTE/guy_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14093,328,"GUY","Guyana","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GUY/BSGM/2016/DTE/guy_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14094,328,"GUY","Guyana","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GUY/BSGM/2017/DTE/guy_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14095,328,"GUY","Guyana","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GUY/BSGM/2018/DTE/guy_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14096,328,"GUY","Guyana","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GUY/BSGM/2019/DTE/guy_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14097,328,"GUY","Guyana","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GUY/BSGM/2020/DTE/guy_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14098,332,"HTI","Haiti","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HTI/BSGM/2001/Binary/hti_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14099,332,"HTI","Haiti","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HTI/BSGM/2001/DTE/hti_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14100,332,"HTI","Haiti","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HTI/BSGM/2002/Binary/hti_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14101,332,"HTI","Haiti","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HTI/BSGM/2002/DTE/hti_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14102,332,"HTI","Haiti","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HTI/BSGM/2003/Binary/hti_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14103,332,"HTI","Haiti","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HTI/BSGM/2003/DTE/hti_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14104,332,"HTI","Haiti","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HTI/BSGM/2004/Binary/hti_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14105,332,"HTI","Haiti","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HTI/BSGM/2004/DTE/hti_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14106,332,"HTI","Haiti","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HTI/BSGM/2005/Binary/hti_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14107,332,"HTI","Haiti","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HTI/BSGM/2005/DTE/hti_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14108,332,"HTI","Haiti","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HTI/BSGM/2006/Binary/hti_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14109,332,"HTI","Haiti","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HTI/BSGM/2006/DTE/hti_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14110,332,"HTI","Haiti","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HTI/BSGM/2007/Binary/hti_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14111,332,"HTI","Haiti","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HTI/BSGM/2007/DTE/hti_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14112,332,"HTI","Haiti","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HTI/BSGM/2008/Binary/hti_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14113,332,"HTI","Haiti","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HTI/BSGM/2008/DTE/hti_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14114,332,"HTI","Haiti","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HTI/BSGM/2009/Binary/hti_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14115,332,"HTI","Haiti","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HTI/BSGM/2009/DTE/hti_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14116,332,"HTI","Haiti","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HTI/BSGM/2010/Binary/hti_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14117,332,"HTI","Haiti","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HTI/BSGM/2010/DTE/hti_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14118,332,"HTI","Haiti","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HTI/BSGM/2011/Binary/hti_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14119,332,"HTI","Haiti","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HTI/BSGM/2011/DTE/hti_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14120,332,"HTI","Haiti","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HTI/BSGM/2013/Binary/hti_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14121,332,"HTI","Haiti","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HTI/BSGM/2013/DTE/hti_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14122,332,"HTI","Haiti","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/HTI/BSGM/2015/DTE/hti_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14123,332,"HTI","Haiti","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/HTI/BSGM/2016/DTE/hti_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14124,332,"HTI","Haiti","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/HTI/BSGM/2017/DTE/hti_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14125,332,"HTI","Haiti","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/HTI/BSGM/2018/DTE/hti_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14126,332,"HTI","Haiti","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/HTI/BSGM/2019/DTE/hti_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14127,332,"HTI","Haiti","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/HTI/BSGM/2020/DTE/hti_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14128,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HMD/BSGM/2001/Binary/hmd_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14129,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HMD/BSGM/2001/DTE/hmd_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14130,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HMD/BSGM/2002/Binary/hmd_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14131,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HMD/BSGM/2002/DTE/hmd_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14132,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HMD/BSGM/2003/Binary/hmd_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14133,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HMD/BSGM/2003/DTE/hmd_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14134,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HMD/BSGM/2004/Binary/hmd_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14135,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HMD/BSGM/2004/DTE/hmd_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14136,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HMD/BSGM/2005/Binary/hmd_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14137,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HMD/BSGM/2005/DTE/hmd_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14138,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HMD/BSGM/2006/Binary/hmd_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14139,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HMD/BSGM/2006/DTE/hmd_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14140,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HMD/BSGM/2007/Binary/hmd_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14141,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HMD/BSGM/2007/DTE/hmd_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14142,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HMD/BSGM/2008/Binary/hmd_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14143,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HMD/BSGM/2008/DTE/hmd_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14144,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HMD/BSGM/2009/Binary/hmd_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14145,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HMD/BSGM/2009/DTE/hmd_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14146,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HMD/BSGM/2010/Binary/hmd_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14147,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HMD/BSGM/2010/DTE/hmd_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14148,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HMD/BSGM/2011/Binary/hmd_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14149,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HMD/BSGM/2011/DTE/hmd_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14150,334,"HMD","Heard Island and McDonald Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HMD/BSGM/2013/Binary/hmd_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14151,334,"HMD","Heard Island and McDonald Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HMD/BSGM/2013/DTE/hmd_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14152,334,"HMD","Heard Island and McDonald Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/HMD/BSGM/2015/DTE/hmd_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14153,334,"HMD","Heard Island and McDonald Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/HMD/BSGM/2016/DTE/hmd_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14154,334,"HMD","Heard Island and McDonald Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/HMD/BSGM/2017/DTE/hmd_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14155,334,"HMD","Heard Island and McDonald Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/HMD/BSGM/2018/DTE/hmd_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14156,334,"HMD","Heard Island and McDonald Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/HMD/BSGM/2019/DTE/hmd_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14157,334,"HMD","Heard Island and McDonald Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/HMD/BSGM/2020/DTE/hmd_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14158,336,"VAT","Vatican City","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VAT/BSGM/2001/Binary/vat_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14159,336,"VAT","Vatican City","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VAT/BSGM/2001/DTE/vat_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14160,336,"VAT","Vatican City","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VAT/BSGM/2002/Binary/vat_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14161,336,"VAT","Vatican City","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VAT/BSGM/2002/DTE/vat_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14162,336,"VAT","Vatican City","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VAT/BSGM/2003/Binary/vat_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14163,336,"VAT","Vatican City","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VAT/BSGM/2003/DTE/vat_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14164,336,"VAT","Vatican City","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VAT/BSGM/2004/Binary/vat_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14165,336,"VAT","Vatican City","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VAT/BSGM/2004/DTE/vat_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14166,336,"VAT","Vatican City","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VAT/BSGM/2005/Binary/vat_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14167,336,"VAT","Vatican City","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VAT/BSGM/2005/DTE/vat_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14168,336,"VAT","Vatican City","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VAT/BSGM/2006/Binary/vat_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14169,336,"VAT","Vatican City","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VAT/BSGM/2006/DTE/vat_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14170,336,"VAT","Vatican City","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VAT/BSGM/2007/Binary/vat_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14171,336,"VAT","Vatican City","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VAT/BSGM/2007/DTE/vat_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14172,336,"VAT","Vatican City","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VAT/BSGM/2008/Binary/vat_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14173,336,"VAT","Vatican City","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VAT/BSGM/2008/DTE/vat_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14174,336,"VAT","Vatican City","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VAT/BSGM/2009/Binary/vat_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14175,336,"VAT","Vatican City","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VAT/BSGM/2009/DTE/vat_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14176,336,"VAT","Vatican City","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VAT/BSGM/2010/Binary/vat_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14177,336,"VAT","Vatican City","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VAT/BSGM/2010/DTE/vat_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14178,336,"VAT","Vatican City","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VAT/BSGM/2011/Binary/vat_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14179,336,"VAT","Vatican City","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VAT/BSGM/2011/DTE/vat_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14180,336,"VAT","Vatican City","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VAT/BSGM/2013/Binary/vat_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14181,336,"VAT","Vatican City","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VAT/BSGM/2013/DTE/vat_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14182,336,"VAT","Vatican City","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/VAT/BSGM/2015/DTE/vat_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14183,336,"VAT","Vatican City","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/VAT/BSGM/2016/DTE/vat_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14184,336,"VAT","Vatican City","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/VAT/BSGM/2017/DTE/vat_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14185,336,"VAT","Vatican City","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/VAT/BSGM/2018/DTE/vat_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14186,336,"VAT","Vatican City","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/VAT/BSGM/2019/DTE/vat_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14187,336,"VAT","Vatican City","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/VAT/BSGM/2020/DTE/vat_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14188,340,"HND","Honduras","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HND/BSGM/2001/Binary/hnd_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14189,340,"HND","Honduras","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HND/BSGM/2001/DTE/hnd_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14190,340,"HND","Honduras","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HND/BSGM/2002/Binary/hnd_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14191,340,"HND","Honduras","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HND/BSGM/2002/DTE/hnd_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14192,340,"HND","Honduras","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HND/BSGM/2003/Binary/hnd_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14193,340,"HND","Honduras","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HND/BSGM/2003/DTE/hnd_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14194,340,"HND","Honduras","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HND/BSGM/2004/Binary/hnd_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14195,340,"HND","Honduras","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HND/BSGM/2004/DTE/hnd_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14196,340,"HND","Honduras","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HND/BSGM/2005/Binary/hnd_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14197,340,"HND","Honduras","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HND/BSGM/2005/DTE/hnd_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14198,340,"HND","Honduras","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HND/BSGM/2006/Binary/hnd_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14199,340,"HND","Honduras","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HND/BSGM/2006/DTE/hnd_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14200,340,"HND","Honduras","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HND/BSGM/2007/Binary/hnd_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14201,340,"HND","Honduras","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HND/BSGM/2007/DTE/hnd_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14202,340,"HND","Honduras","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HND/BSGM/2008/Binary/hnd_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14203,340,"HND","Honduras","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HND/BSGM/2008/DTE/hnd_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14204,340,"HND","Honduras","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HND/BSGM/2009/Binary/hnd_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14205,340,"HND","Honduras","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HND/BSGM/2009/DTE/hnd_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14206,340,"HND","Honduras","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HND/BSGM/2010/Binary/hnd_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14207,340,"HND","Honduras","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HND/BSGM/2010/DTE/hnd_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14208,340,"HND","Honduras","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HND/BSGM/2011/Binary/hnd_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14209,340,"HND","Honduras","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HND/BSGM/2011/DTE/hnd_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14210,340,"HND","Honduras","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HND/BSGM/2013/Binary/hnd_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14211,340,"HND","Honduras","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HND/BSGM/2013/DTE/hnd_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14212,340,"HND","Honduras","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/HND/BSGM/2015/DTE/hnd_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14213,340,"HND","Honduras","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/HND/BSGM/2016/DTE/hnd_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14214,340,"HND","Honduras","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/HND/BSGM/2017/DTE/hnd_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14215,340,"HND","Honduras","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/HND/BSGM/2018/DTE/hnd_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14216,340,"HND","Honduras","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/HND/BSGM/2019/DTE/hnd_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14217,340,"HND","Honduras","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/HND/BSGM/2020/DTE/hnd_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14218,344,"HKG","Hong Kong","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HKG/BSGM/2001/Binary/hkg_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14219,344,"HKG","Hong Kong","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HKG/BSGM/2001/DTE/hkg_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14220,344,"HKG","Hong Kong","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HKG/BSGM/2002/Binary/hkg_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14221,344,"HKG","Hong Kong","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HKG/BSGM/2002/DTE/hkg_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14222,344,"HKG","Hong Kong","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HKG/BSGM/2003/Binary/hkg_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14223,344,"HKG","Hong Kong","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HKG/BSGM/2003/DTE/hkg_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14224,344,"HKG","Hong Kong","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HKG/BSGM/2004/Binary/hkg_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14225,344,"HKG","Hong Kong","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HKG/BSGM/2004/DTE/hkg_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14226,344,"HKG","Hong Kong","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HKG/BSGM/2005/Binary/hkg_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14227,344,"HKG","Hong Kong","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HKG/BSGM/2005/DTE/hkg_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14228,344,"HKG","Hong Kong","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HKG/BSGM/2006/Binary/hkg_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14229,344,"HKG","Hong Kong","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HKG/BSGM/2006/DTE/hkg_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14230,344,"HKG","Hong Kong","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HKG/BSGM/2007/Binary/hkg_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14231,344,"HKG","Hong Kong","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HKG/BSGM/2007/DTE/hkg_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14232,344,"HKG","Hong Kong","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HKG/BSGM/2008/Binary/hkg_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14233,344,"HKG","Hong Kong","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HKG/BSGM/2008/DTE/hkg_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14234,344,"HKG","Hong Kong","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HKG/BSGM/2009/Binary/hkg_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14235,344,"HKG","Hong Kong","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HKG/BSGM/2009/DTE/hkg_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14236,344,"HKG","Hong Kong","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HKG/BSGM/2010/Binary/hkg_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14237,344,"HKG","Hong Kong","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HKG/BSGM/2010/DTE/hkg_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14238,344,"HKG","Hong Kong","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HKG/BSGM/2011/Binary/hkg_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14239,344,"HKG","Hong Kong","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HKG/BSGM/2011/DTE/hkg_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14240,344,"HKG","Hong Kong","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HKG/BSGM/2013/Binary/hkg_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14241,344,"HKG","Hong Kong","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HKG/BSGM/2013/DTE/hkg_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14242,344,"HKG","Hong Kong","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/HKG/BSGM/2015/DTE/hkg_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14243,344,"HKG","Hong Kong","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/HKG/BSGM/2016/DTE/hkg_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14244,344,"HKG","Hong Kong","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/HKG/BSGM/2017/DTE/hkg_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14245,344,"HKG","Hong Kong","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/HKG/BSGM/2018/DTE/hkg_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14246,344,"HKG","Hong Kong","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/HKG/BSGM/2019/DTE/hkg_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14247,344,"HKG","Hong Kong","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/HKG/BSGM/2020/DTE/hkg_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14248,348,"HUN","Hungary","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HUN/BSGM/2001/Binary/hun_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14249,348,"HUN","Hungary","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/HUN/BSGM/2001/DTE/hun_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14250,348,"HUN","Hungary","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HUN/BSGM/2002/Binary/hun_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14251,348,"HUN","Hungary","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/HUN/BSGM/2002/DTE/hun_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14252,348,"HUN","Hungary","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HUN/BSGM/2003/Binary/hun_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14253,348,"HUN","Hungary","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/HUN/BSGM/2003/DTE/hun_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14254,348,"HUN","Hungary","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HUN/BSGM/2004/Binary/hun_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14255,348,"HUN","Hungary","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/HUN/BSGM/2004/DTE/hun_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14256,348,"HUN","Hungary","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HUN/BSGM/2005/Binary/hun_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14257,348,"HUN","Hungary","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/HUN/BSGM/2005/DTE/hun_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14258,348,"HUN","Hungary","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HUN/BSGM/2006/Binary/hun_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14259,348,"HUN","Hungary","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/HUN/BSGM/2006/DTE/hun_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14260,348,"HUN","Hungary","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HUN/BSGM/2007/Binary/hun_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14261,348,"HUN","Hungary","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/HUN/BSGM/2007/DTE/hun_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14262,348,"HUN","Hungary","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HUN/BSGM/2008/Binary/hun_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14263,348,"HUN","Hungary","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/HUN/BSGM/2008/DTE/hun_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14264,348,"HUN","Hungary","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HUN/BSGM/2009/Binary/hun_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14265,348,"HUN","Hungary","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/HUN/BSGM/2009/DTE/hun_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14266,348,"HUN","Hungary","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HUN/BSGM/2010/Binary/hun_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14267,348,"HUN","Hungary","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/HUN/BSGM/2010/DTE/hun_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14268,348,"HUN","Hungary","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HUN/BSGM/2011/Binary/hun_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14269,348,"HUN","Hungary","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/HUN/BSGM/2011/DTE/hun_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14270,348,"HUN","Hungary","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HUN/BSGM/2013/Binary/hun_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14271,348,"HUN","Hungary","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/HUN/BSGM/2013/DTE/hun_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14272,348,"HUN","Hungary","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/HUN/BSGM/2015/DTE/hun_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14273,348,"HUN","Hungary","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/HUN/BSGM/2016/DTE/hun_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14274,348,"HUN","Hungary","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/HUN/BSGM/2017/DTE/hun_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14275,348,"HUN","Hungary","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/HUN/BSGM/2018/DTE/hun_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14276,348,"HUN","Hungary","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/HUN/BSGM/2019/DTE/hun_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14277,348,"HUN","Hungary","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/HUN/BSGM/2020/DTE/hun_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14278,352,"ISL","Iceland","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ISL/BSGM/2001/Binary/isl_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14279,352,"ISL","Iceland","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ISL/BSGM/2001/DTE/isl_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14280,352,"ISL","Iceland","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ISL/BSGM/2002/Binary/isl_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14281,352,"ISL","Iceland","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ISL/BSGM/2002/DTE/isl_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14282,352,"ISL","Iceland","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ISL/BSGM/2003/Binary/isl_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14283,352,"ISL","Iceland","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ISL/BSGM/2003/DTE/isl_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14284,352,"ISL","Iceland","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ISL/BSGM/2004/Binary/isl_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14285,352,"ISL","Iceland","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ISL/BSGM/2004/DTE/isl_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14286,352,"ISL","Iceland","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ISL/BSGM/2005/Binary/isl_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14287,352,"ISL","Iceland","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ISL/BSGM/2005/DTE/isl_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14288,352,"ISL","Iceland","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ISL/BSGM/2006/Binary/isl_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14289,352,"ISL","Iceland","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ISL/BSGM/2006/DTE/isl_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14290,352,"ISL","Iceland","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ISL/BSGM/2007/Binary/isl_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14291,352,"ISL","Iceland","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ISL/BSGM/2007/DTE/isl_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14292,352,"ISL","Iceland","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ISL/BSGM/2008/Binary/isl_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14293,352,"ISL","Iceland","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ISL/BSGM/2008/DTE/isl_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14294,352,"ISL","Iceland","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ISL/BSGM/2009/Binary/isl_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14295,352,"ISL","Iceland","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ISL/BSGM/2009/DTE/isl_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14296,352,"ISL","Iceland","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ISL/BSGM/2010/Binary/isl_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14297,352,"ISL","Iceland","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ISL/BSGM/2010/DTE/isl_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14298,352,"ISL","Iceland","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ISL/BSGM/2011/Binary/isl_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14299,352,"ISL","Iceland","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ISL/BSGM/2011/DTE/isl_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14300,352,"ISL","Iceland","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ISL/BSGM/2013/Binary/isl_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14301,352,"ISL","Iceland","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ISL/BSGM/2013/DTE/isl_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14302,352,"ISL","Iceland","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ISL/BSGM/2015/DTE/isl_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14303,352,"ISL","Iceland","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ISL/BSGM/2016/DTE/isl_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14304,352,"ISL","Iceland","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ISL/BSGM/2017/DTE/isl_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14305,352,"ISL","Iceland","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ISL/BSGM/2018/DTE/isl_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14306,352,"ISL","Iceland","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ISL/BSGM/2019/DTE/isl_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14307,352,"ISL","Iceland","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ISL/BSGM/2020/DTE/isl_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14308,356,"IND","India","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IND/BSGM/2001/Binary/ind_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14309,356,"IND","India","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IND/BSGM/2001/DTE/ind_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14310,356,"IND","India","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IND/BSGM/2002/Binary/ind_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14311,356,"IND","India","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IND/BSGM/2002/DTE/ind_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14312,356,"IND","India","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IND/BSGM/2003/Binary/ind_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14313,356,"IND","India","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IND/BSGM/2003/DTE/ind_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14314,356,"IND","India","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IND/BSGM/2004/Binary/ind_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14315,356,"IND","India","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IND/BSGM/2004/DTE/ind_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14316,356,"IND","India","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IND/BSGM/2005/Binary/ind_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14317,356,"IND","India","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IND/BSGM/2005/DTE/ind_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14318,356,"IND","India","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IND/BSGM/2006/Binary/ind_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14319,356,"IND","India","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IND/BSGM/2006/DTE/ind_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14320,356,"IND","India","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IND/BSGM/2007/Binary/ind_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14321,356,"IND","India","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IND/BSGM/2007/DTE/ind_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14322,356,"IND","India","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IND/BSGM/2008/Binary/ind_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14323,356,"IND","India","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IND/BSGM/2008/DTE/ind_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14324,356,"IND","India","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IND/BSGM/2009/Binary/ind_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14325,356,"IND","India","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IND/BSGM/2009/DTE/ind_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14326,356,"IND","India","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IND/BSGM/2010/Binary/ind_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14327,356,"IND","India","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IND/BSGM/2010/DTE/ind_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14328,356,"IND","India","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IND/BSGM/2011/Binary/ind_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14329,356,"IND","India","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IND/BSGM/2011/DTE/ind_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14330,356,"IND","India","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IND/BSGM/2013/Binary/ind_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14331,356,"IND","India","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IND/BSGM/2013/DTE/ind_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14332,356,"IND","India","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/IND/BSGM/2015/DTE/ind_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14333,356,"IND","India","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/IND/BSGM/2016/DTE/ind_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14334,356,"IND","India","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/IND/BSGM/2017/DTE/ind_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14335,356,"IND","India","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/IND/BSGM/2018/DTE/ind_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14336,356,"IND","India","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/IND/BSGM/2019/DTE/ind_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14337,356,"IND","India","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/IND/BSGM/2020/DTE/ind_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14338,364,"IRN","Iran","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IRN/BSGM/2001/Binary/irn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14339,364,"IRN","Iran","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IRN/BSGM/2001/DTE/irn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14340,364,"IRN","Iran","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IRN/BSGM/2002/Binary/irn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14341,364,"IRN","Iran","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IRN/BSGM/2002/DTE/irn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14342,364,"IRN","Iran","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IRN/BSGM/2003/Binary/irn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14343,364,"IRN","Iran","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IRN/BSGM/2003/DTE/irn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14344,364,"IRN","Iran","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IRN/BSGM/2004/Binary/irn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14345,364,"IRN","Iran","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IRN/BSGM/2004/DTE/irn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14346,364,"IRN","Iran","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IRN/BSGM/2005/Binary/irn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14347,364,"IRN","Iran","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IRN/BSGM/2005/DTE/irn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14348,364,"IRN","Iran","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IRN/BSGM/2006/Binary/irn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14349,364,"IRN","Iran","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IRN/BSGM/2006/DTE/irn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14350,364,"IRN","Iran","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IRN/BSGM/2007/Binary/irn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14351,364,"IRN","Iran","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IRN/BSGM/2007/DTE/irn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14352,364,"IRN","Iran","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IRN/BSGM/2008/Binary/irn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14353,364,"IRN","Iran","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IRN/BSGM/2008/DTE/irn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14354,364,"IRN","Iran","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IRN/BSGM/2009/Binary/irn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14355,364,"IRN","Iran","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IRN/BSGM/2009/DTE/irn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14356,364,"IRN","Iran","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IRN/BSGM/2010/Binary/irn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14357,364,"IRN","Iran","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IRN/BSGM/2010/DTE/irn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14358,364,"IRN","Iran","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IRN/BSGM/2011/Binary/irn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14359,364,"IRN","Iran","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IRN/BSGM/2011/DTE/irn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14360,364,"IRN","Iran","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IRN/BSGM/2013/Binary/irn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14361,364,"IRN","Iran","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IRN/BSGM/2013/DTE/irn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14362,364,"IRN","Iran","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/IRN/BSGM/2015/DTE/irn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14363,364,"IRN","Iran","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/IRN/BSGM/2016/DTE/irn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14364,364,"IRN","Iran","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/IRN/BSGM/2017/DTE/irn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14365,364,"IRN","Iran","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/IRN/BSGM/2018/DTE/irn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14366,364,"IRN","Iran","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/IRN/BSGM/2019/DTE/irn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14367,364,"IRN","Iran","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/IRN/BSGM/2020/DTE/irn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14368,368,"IRQ","Iraq","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2001/Binary/irq_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14369,368,"IRQ","Iraq","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2001/DTE/irq_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14370,368,"IRQ","Iraq","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2002/Binary/irq_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14371,368,"IRQ","Iraq","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2002/DTE/irq_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14372,368,"IRQ","Iraq","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2003/Binary/irq_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14373,368,"IRQ","Iraq","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2003/DTE/irq_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14374,368,"IRQ","Iraq","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2004/Binary/irq_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14375,368,"IRQ","Iraq","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2004/DTE/irq_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14376,368,"IRQ","Iraq","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2005/Binary/irq_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14377,368,"IRQ","Iraq","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2005/DTE/irq_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14378,368,"IRQ","Iraq","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2006/Binary/irq_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14379,368,"IRQ","Iraq","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2006/DTE/irq_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14380,368,"IRQ","Iraq","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2007/Binary/irq_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14381,368,"IRQ","Iraq","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2007/DTE/irq_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14382,368,"IRQ","Iraq","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2008/Binary/irq_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14383,368,"IRQ","Iraq","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2008/DTE/irq_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14384,368,"IRQ","Iraq","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2009/Binary/irq_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14385,368,"IRQ","Iraq","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2009/DTE/irq_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14386,368,"IRQ","Iraq","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2010/Binary/irq_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14387,368,"IRQ","Iraq","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2010/DTE/irq_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14388,368,"IRQ","Iraq","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2011/Binary/irq_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14389,368,"IRQ","Iraq","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2011/DTE/irq_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14390,368,"IRQ","Iraq","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2013/Binary/irq_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14391,368,"IRQ","Iraq","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2013/DTE/irq_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14392,368,"IRQ","Iraq","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2015/DTE/irq_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14393,368,"IRQ","Iraq","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2016/DTE/irq_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14394,368,"IRQ","Iraq","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2017/DTE/irq_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14395,368,"IRQ","Iraq","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2018/DTE/irq_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14396,368,"IRQ","Iraq","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2019/DTE/irq_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14397,368,"IRQ","Iraq","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/IRQ/BSGM/2020/DTE/irq_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14398,372,"IRL","Ireland","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IRL/BSGM/2001/Binary/irl_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14399,372,"IRL","Ireland","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IRL/BSGM/2001/DTE/irl_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14400,372,"IRL","Ireland","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IRL/BSGM/2002/Binary/irl_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14401,372,"IRL","Ireland","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IRL/BSGM/2002/DTE/irl_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14402,372,"IRL","Ireland","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IRL/BSGM/2003/Binary/irl_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14403,372,"IRL","Ireland","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IRL/BSGM/2003/DTE/irl_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14404,372,"IRL","Ireland","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IRL/BSGM/2004/Binary/irl_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14405,372,"IRL","Ireland","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IRL/BSGM/2004/DTE/irl_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14406,372,"IRL","Ireland","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IRL/BSGM/2005/Binary/irl_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14407,372,"IRL","Ireland","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IRL/BSGM/2005/DTE/irl_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14408,372,"IRL","Ireland","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IRL/BSGM/2006/Binary/irl_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14409,372,"IRL","Ireland","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IRL/BSGM/2006/DTE/irl_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14410,372,"IRL","Ireland","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IRL/BSGM/2007/Binary/irl_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14411,372,"IRL","Ireland","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IRL/BSGM/2007/DTE/irl_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14412,372,"IRL","Ireland","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IRL/BSGM/2008/Binary/irl_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14413,372,"IRL","Ireland","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IRL/BSGM/2008/DTE/irl_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14414,372,"IRL","Ireland","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IRL/BSGM/2009/Binary/irl_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14415,372,"IRL","Ireland","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IRL/BSGM/2009/DTE/irl_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14416,372,"IRL","Ireland","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IRL/BSGM/2010/Binary/irl_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14417,372,"IRL","Ireland","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IRL/BSGM/2010/DTE/irl_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14418,372,"IRL","Ireland","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IRL/BSGM/2011/Binary/irl_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14419,372,"IRL","Ireland","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IRL/BSGM/2011/DTE/irl_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14420,372,"IRL","Ireland","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IRL/BSGM/2013/Binary/irl_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14421,372,"IRL","Ireland","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IRL/BSGM/2013/DTE/irl_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14422,372,"IRL","Ireland","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/IRL/BSGM/2015/DTE/irl_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14423,372,"IRL","Ireland","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/IRL/BSGM/2016/DTE/irl_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14424,372,"IRL","Ireland","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/IRL/BSGM/2017/DTE/irl_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14425,372,"IRL","Ireland","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/IRL/BSGM/2018/DTE/irl_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14426,372,"IRL","Ireland","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/IRL/BSGM/2019/DTE/irl_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14427,372,"IRL","Ireland","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/IRL/BSGM/2020/DTE/irl_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14428,376,"ISR","Israel","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ISR/BSGM/2001/Binary/isr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14429,376,"ISR","Israel","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ISR/BSGM/2001/DTE/isr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14430,376,"ISR","Israel","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ISR/BSGM/2002/Binary/isr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14431,376,"ISR","Israel","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ISR/BSGM/2002/DTE/isr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14432,376,"ISR","Israel","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ISR/BSGM/2003/Binary/isr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14433,376,"ISR","Israel","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ISR/BSGM/2003/DTE/isr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14434,376,"ISR","Israel","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ISR/BSGM/2004/Binary/isr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14435,376,"ISR","Israel","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ISR/BSGM/2004/DTE/isr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14436,376,"ISR","Israel","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ISR/BSGM/2005/Binary/isr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14437,376,"ISR","Israel","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ISR/BSGM/2005/DTE/isr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14438,376,"ISR","Israel","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ISR/BSGM/2006/Binary/isr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14439,376,"ISR","Israel","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ISR/BSGM/2006/DTE/isr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14440,376,"ISR","Israel","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ISR/BSGM/2007/Binary/isr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14441,376,"ISR","Israel","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ISR/BSGM/2007/DTE/isr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14442,376,"ISR","Israel","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ISR/BSGM/2008/Binary/isr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14443,376,"ISR","Israel","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ISR/BSGM/2008/DTE/isr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14444,376,"ISR","Israel","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ISR/BSGM/2009/Binary/isr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14445,376,"ISR","Israel","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ISR/BSGM/2009/DTE/isr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14446,376,"ISR","Israel","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ISR/BSGM/2010/Binary/isr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14447,376,"ISR","Israel","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ISR/BSGM/2010/DTE/isr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14448,376,"ISR","Israel","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ISR/BSGM/2011/Binary/isr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14449,376,"ISR","Israel","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ISR/BSGM/2011/DTE/isr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14450,376,"ISR","Israel","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ISR/BSGM/2013/Binary/isr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14451,376,"ISR","Israel","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ISR/BSGM/2013/DTE/isr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14452,376,"ISR","Israel","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ISR/BSGM/2015/DTE/isr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14453,376,"ISR","Israel","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ISR/BSGM/2016/DTE/isr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14454,376,"ISR","Israel","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ISR/BSGM/2017/DTE/isr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14455,376,"ISR","Israel","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ISR/BSGM/2018/DTE/isr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14456,376,"ISR","Israel","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ISR/BSGM/2019/DTE/isr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14457,376,"ISR","Israel","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ISR/BSGM/2020/DTE/isr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14458,380,"ITA","Italy","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ITA/BSGM/2001/Binary/ita_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14459,380,"ITA","Italy","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ITA/BSGM/2001/DTE/ita_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14460,380,"ITA","Italy","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ITA/BSGM/2002/Binary/ita_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14461,380,"ITA","Italy","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ITA/BSGM/2002/DTE/ita_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14462,380,"ITA","Italy","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ITA/BSGM/2003/Binary/ita_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14463,380,"ITA","Italy","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ITA/BSGM/2003/DTE/ita_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14464,380,"ITA","Italy","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ITA/BSGM/2004/Binary/ita_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14465,380,"ITA","Italy","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ITA/BSGM/2004/DTE/ita_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14466,380,"ITA","Italy","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ITA/BSGM/2005/Binary/ita_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14467,380,"ITA","Italy","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ITA/BSGM/2005/DTE/ita_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14468,380,"ITA","Italy","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ITA/BSGM/2006/Binary/ita_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14469,380,"ITA","Italy","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ITA/BSGM/2006/DTE/ita_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14470,380,"ITA","Italy","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ITA/BSGM/2007/Binary/ita_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14471,380,"ITA","Italy","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ITA/BSGM/2007/DTE/ita_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14472,380,"ITA","Italy","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ITA/BSGM/2008/Binary/ita_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14473,380,"ITA","Italy","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ITA/BSGM/2008/DTE/ita_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14474,380,"ITA","Italy","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ITA/BSGM/2009/Binary/ita_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14475,380,"ITA","Italy","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ITA/BSGM/2009/DTE/ita_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14476,380,"ITA","Italy","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ITA/BSGM/2010/Binary/ita_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14477,380,"ITA","Italy","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ITA/BSGM/2010/DTE/ita_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14478,380,"ITA","Italy","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ITA/BSGM/2011/Binary/ita_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14479,380,"ITA","Italy","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ITA/BSGM/2011/DTE/ita_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14480,380,"ITA","Italy","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ITA/BSGM/2013/Binary/ita_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14481,380,"ITA","Italy","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ITA/BSGM/2013/DTE/ita_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14482,380,"ITA","Italy","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ITA/BSGM/2015/DTE/ita_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14483,380,"ITA","Italy","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ITA/BSGM/2016/DTE/ita_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14484,380,"ITA","Italy","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ITA/BSGM/2017/DTE/ita_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14485,380,"ITA","Italy","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ITA/BSGM/2018/DTE/ita_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14486,380,"ITA","Italy","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ITA/BSGM/2019/DTE/ita_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14487,380,"ITA","Italy","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ITA/BSGM/2020/DTE/ita_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14488,384,"CIV","CIte dIvoire","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CIV/BSGM/2001/Binary/civ_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14489,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CIV/BSGM/2001/DTE/civ_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14490,384,"CIV","CIte dIvoire","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CIV/BSGM/2002/Binary/civ_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14491,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CIV/BSGM/2002/DTE/civ_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14492,384,"CIV","CIte dIvoire","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CIV/BSGM/2003/Binary/civ_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14493,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CIV/BSGM/2003/DTE/civ_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14494,384,"CIV","CIte dIvoire","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CIV/BSGM/2004/Binary/civ_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14495,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CIV/BSGM/2004/DTE/civ_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14496,384,"CIV","CIte dIvoire","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CIV/BSGM/2005/Binary/civ_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14497,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CIV/BSGM/2005/DTE/civ_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14498,384,"CIV","CIte dIvoire","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CIV/BSGM/2006/Binary/civ_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14499,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CIV/BSGM/2006/DTE/civ_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14500,384,"CIV","CIte dIvoire","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CIV/BSGM/2007/Binary/civ_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14501,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CIV/BSGM/2007/DTE/civ_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14502,384,"CIV","CIte dIvoire","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CIV/BSGM/2008/Binary/civ_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14503,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CIV/BSGM/2008/DTE/civ_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14504,384,"CIV","CIte dIvoire","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CIV/BSGM/2009/Binary/civ_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14505,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CIV/BSGM/2009/DTE/civ_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14506,384,"CIV","CIte dIvoire","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CIV/BSGM/2010/Binary/civ_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14507,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CIV/BSGM/2010/DTE/civ_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14508,384,"CIV","CIte dIvoire","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CIV/BSGM/2011/Binary/civ_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14509,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CIV/BSGM/2011/DTE/civ_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14510,384,"CIV","CIte dIvoire","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CIV/BSGM/2013/Binary/civ_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14511,384,"CIV","CIte dIvoire","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CIV/BSGM/2013/DTE/civ_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14512,384,"CIV","CIte dIvoire","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CIV/BSGM/2015/DTE/civ_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14513,384,"CIV","CIte dIvoire","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CIV/BSGM/2016/DTE/civ_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14514,384,"CIV","CIte dIvoire","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CIV/BSGM/2017/DTE/civ_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14515,384,"CIV","CIte dIvoire","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CIV/BSGM/2018/DTE/civ_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14516,384,"CIV","CIte dIvoire","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CIV/BSGM/2019/DTE/civ_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14517,384,"CIV","CIte dIvoire","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CIV/BSGM/2020/DTE/civ_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14518,388,"JAM","Jamaica","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/JAM/BSGM/2001/Binary/jam_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14519,388,"JAM","Jamaica","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/JAM/BSGM/2001/DTE/jam_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14520,388,"JAM","Jamaica","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/JAM/BSGM/2002/Binary/jam_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14521,388,"JAM","Jamaica","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/JAM/BSGM/2002/DTE/jam_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14522,388,"JAM","Jamaica","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/JAM/BSGM/2003/Binary/jam_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14523,388,"JAM","Jamaica","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/JAM/BSGM/2003/DTE/jam_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14524,388,"JAM","Jamaica","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/JAM/BSGM/2004/Binary/jam_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14525,388,"JAM","Jamaica","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/JAM/BSGM/2004/DTE/jam_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14526,388,"JAM","Jamaica","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/JAM/BSGM/2005/Binary/jam_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14527,388,"JAM","Jamaica","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/JAM/BSGM/2005/DTE/jam_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14528,388,"JAM","Jamaica","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/JAM/BSGM/2006/Binary/jam_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14529,388,"JAM","Jamaica","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/JAM/BSGM/2006/DTE/jam_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14530,388,"JAM","Jamaica","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/JAM/BSGM/2007/Binary/jam_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14531,388,"JAM","Jamaica","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/JAM/BSGM/2007/DTE/jam_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14532,388,"JAM","Jamaica","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/JAM/BSGM/2008/Binary/jam_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14533,388,"JAM","Jamaica","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/JAM/BSGM/2008/DTE/jam_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14534,388,"JAM","Jamaica","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/JAM/BSGM/2009/Binary/jam_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14535,388,"JAM","Jamaica","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/JAM/BSGM/2009/DTE/jam_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14536,388,"JAM","Jamaica","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/JAM/BSGM/2010/Binary/jam_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14537,388,"JAM","Jamaica","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/JAM/BSGM/2010/DTE/jam_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14538,388,"JAM","Jamaica","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/JAM/BSGM/2011/Binary/jam_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14539,388,"JAM","Jamaica","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/JAM/BSGM/2011/DTE/jam_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14540,388,"JAM","Jamaica","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/JAM/BSGM/2013/Binary/jam_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14541,388,"JAM","Jamaica","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/JAM/BSGM/2013/DTE/jam_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14542,388,"JAM","Jamaica","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/JAM/BSGM/2015/DTE/jam_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14543,388,"JAM","Jamaica","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/JAM/BSGM/2016/DTE/jam_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14544,388,"JAM","Jamaica","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/JAM/BSGM/2017/DTE/jam_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14545,388,"JAM","Jamaica","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/JAM/BSGM/2018/DTE/jam_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14546,388,"JAM","Jamaica","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/JAM/BSGM/2019/DTE/jam_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14547,388,"JAM","Jamaica","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/JAM/BSGM/2020/DTE/jam_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14548,392,"JPN","Japan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/JPN/BSGM/2001/Binary/jpn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14549,392,"JPN","Japan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/JPN/BSGM/2001/DTE/jpn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14550,392,"JPN","Japan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/JPN/BSGM/2002/Binary/jpn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14551,392,"JPN","Japan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/JPN/BSGM/2002/DTE/jpn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14552,392,"JPN","Japan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/JPN/BSGM/2003/Binary/jpn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14553,392,"JPN","Japan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/JPN/BSGM/2003/DTE/jpn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14554,392,"JPN","Japan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/JPN/BSGM/2004/Binary/jpn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14555,392,"JPN","Japan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/JPN/BSGM/2004/DTE/jpn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14556,392,"JPN","Japan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/JPN/BSGM/2005/Binary/jpn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14557,392,"JPN","Japan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/JPN/BSGM/2005/DTE/jpn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14558,392,"JPN","Japan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/JPN/BSGM/2006/Binary/jpn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14559,392,"JPN","Japan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/JPN/BSGM/2006/DTE/jpn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14560,392,"JPN","Japan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/JPN/BSGM/2007/Binary/jpn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14561,392,"JPN","Japan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/JPN/BSGM/2007/DTE/jpn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14562,392,"JPN","Japan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/JPN/BSGM/2008/Binary/jpn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14563,392,"JPN","Japan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/JPN/BSGM/2008/DTE/jpn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14564,392,"JPN","Japan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/JPN/BSGM/2009/Binary/jpn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14565,392,"JPN","Japan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/JPN/BSGM/2009/DTE/jpn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14566,392,"JPN","Japan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/JPN/BSGM/2010/Binary/jpn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14567,392,"JPN","Japan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/JPN/BSGM/2010/DTE/jpn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14568,392,"JPN","Japan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/JPN/BSGM/2011/Binary/jpn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14569,392,"JPN","Japan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/JPN/BSGM/2011/DTE/jpn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14570,392,"JPN","Japan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/JPN/BSGM/2013/Binary/jpn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14571,392,"JPN","Japan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/JPN/BSGM/2013/DTE/jpn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14572,392,"JPN","Japan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/JPN/BSGM/2015/DTE/jpn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14573,392,"JPN","Japan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/JPN/BSGM/2016/DTE/jpn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14574,392,"JPN","Japan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/JPN/BSGM/2017/DTE/jpn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14575,392,"JPN","Japan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/JPN/BSGM/2018/DTE/jpn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14576,392,"JPN","Japan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/JPN/BSGM/2019/DTE/jpn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14577,392,"JPN","Japan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/JPN/BSGM/2020/DTE/jpn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14578,398,"KAZ","Kazakhstan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2001/Binary/kaz_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14579,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2001/DTE/kaz_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14580,398,"KAZ","Kazakhstan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2002/Binary/kaz_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14581,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2002/DTE/kaz_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14582,398,"KAZ","Kazakhstan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2003/Binary/kaz_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14583,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2003/DTE/kaz_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14584,398,"KAZ","Kazakhstan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2004/Binary/kaz_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14585,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2004/DTE/kaz_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14586,398,"KAZ","Kazakhstan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2005/Binary/kaz_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14587,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2005/DTE/kaz_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14588,398,"KAZ","Kazakhstan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2006/Binary/kaz_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14589,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2006/DTE/kaz_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14590,398,"KAZ","Kazakhstan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2007/Binary/kaz_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14591,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2007/DTE/kaz_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14592,398,"KAZ","Kazakhstan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2008/Binary/kaz_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14593,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2008/DTE/kaz_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14594,398,"KAZ","Kazakhstan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2009/Binary/kaz_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14595,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2009/DTE/kaz_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14596,398,"KAZ","Kazakhstan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2010/Binary/kaz_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14597,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2010/DTE/kaz_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14598,398,"KAZ","Kazakhstan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2011/Binary/kaz_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14599,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2011/DTE/kaz_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14600,398,"KAZ","Kazakhstan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2013/Binary/kaz_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14601,398,"KAZ","Kazakhstan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2013/DTE/kaz_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14602,398,"KAZ","Kazakhstan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2015/DTE/kaz_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14603,398,"KAZ","Kazakhstan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2016/DTE/kaz_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14604,398,"KAZ","Kazakhstan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2017/DTE/kaz_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14605,398,"KAZ","Kazakhstan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2018/DTE/kaz_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14606,398,"KAZ","Kazakhstan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2019/DTE/kaz_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14607,398,"KAZ","Kazakhstan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/KAZ/BSGM/2020/DTE/kaz_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14608,400,"JOR","Jordan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/JOR/BSGM/2001/Binary/jor_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14609,400,"JOR","Jordan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/JOR/BSGM/2001/DTE/jor_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14610,400,"JOR","Jordan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/JOR/BSGM/2002/Binary/jor_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14611,400,"JOR","Jordan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/JOR/BSGM/2002/DTE/jor_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14612,400,"JOR","Jordan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/JOR/BSGM/2003/Binary/jor_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14613,400,"JOR","Jordan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/JOR/BSGM/2003/DTE/jor_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14614,400,"JOR","Jordan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/JOR/BSGM/2004/Binary/jor_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14615,400,"JOR","Jordan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/JOR/BSGM/2004/DTE/jor_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14616,400,"JOR","Jordan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/JOR/BSGM/2005/Binary/jor_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14617,400,"JOR","Jordan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/JOR/BSGM/2005/DTE/jor_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14618,400,"JOR","Jordan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/JOR/BSGM/2006/Binary/jor_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14619,400,"JOR","Jordan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/JOR/BSGM/2006/DTE/jor_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14620,400,"JOR","Jordan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/JOR/BSGM/2007/Binary/jor_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14621,400,"JOR","Jordan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/JOR/BSGM/2007/DTE/jor_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14622,400,"JOR","Jordan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/JOR/BSGM/2008/Binary/jor_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14623,400,"JOR","Jordan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/JOR/BSGM/2008/DTE/jor_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14624,400,"JOR","Jordan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/JOR/BSGM/2009/Binary/jor_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14625,400,"JOR","Jordan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/JOR/BSGM/2009/DTE/jor_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14626,400,"JOR","Jordan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/JOR/BSGM/2010/Binary/jor_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14627,400,"JOR","Jordan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/JOR/BSGM/2010/DTE/jor_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14628,400,"JOR","Jordan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/JOR/BSGM/2011/Binary/jor_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14629,400,"JOR","Jordan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/JOR/BSGM/2011/DTE/jor_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14630,400,"JOR","Jordan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/JOR/BSGM/2013/Binary/jor_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14631,400,"JOR","Jordan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/JOR/BSGM/2013/DTE/jor_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14632,400,"JOR","Jordan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/JOR/BSGM/2015/DTE/jor_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14633,400,"JOR","Jordan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/JOR/BSGM/2016/DTE/jor_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14634,400,"JOR","Jordan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/JOR/BSGM/2017/DTE/jor_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14635,400,"JOR","Jordan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/JOR/BSGM/2018/DTE/jor_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14636,400,"JOR","Jordan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/JOR/BSGM/2019/DTE/jor_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14637,400,"JOR","Jordan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/JOR/BSGM/2020/DTE/jor_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14638,404,"KEN","Kenya","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KEN/BSGM/2001/Binary/ken_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14639,404,"KEN","Kenya","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KEN/BSGM/2001/DTE/ken_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14640,404,"KEN","Kenya","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KEN/BSGM/2002/Binary/ken_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14641,404,"KEN","Kenya","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KEN/BSGM/2002/DTE/ken_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14642,404,"KEN","Kenya","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KEN/BSGM/2003/Binary/ken_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14643,404,"KEN","Kenya","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KEN/BSGM/2003/DTE/ken_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14644,404,"KEN","Kenya","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KEN/BSGM/2004/Binary/ken_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14645,404,"KEN","Kenya","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KEN/BSGM/2004/DTE/ken_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14646,404,"KEN","Kenya","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KEN/BSGM/2005/Binary/ken_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14647,404,"KEN","Kenya","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KEN/BSGM/2005/DTE/ken_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14648,404,"KEN","Kenya","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KEN/BSGM/2006/Binary/ken_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14649,404,"KEN","Kenya","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KEN/BSGM/2006/DTE/ken_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14650,404,"KEN","Kenya","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KEN/BSGM/2007/Binary/ken_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14651,404,"KEN","Kenya","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KEN/BSGM/2007/DTE/ken_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14652,404,"KEN","Kenya","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KEN/BSGM/2008/Binary/ken_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14653,404,"KEN","Kenya","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KEN/BSGM/2008/DTE/ken_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14654,404,"KEN","Kenya","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KEN/BSGM/2009/Binary/ken_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14655,404,"KEN","Kenya","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KEN/BSGM/2009/DTE/ken_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14656,404,"KEN","Kenya","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KEN/BSGM/2010/Binary/ken_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14657,404,"KEN","Kenya","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KEN/BSGM/2010/DTE/ken_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14658,404,"KEN","Kenya","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KEN/BSGM/2011/Binary/ken_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14659,404,"KEN","Kenya","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KEN/BSGM/2011/DTE/ken_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14660,404,"KEN","Kenya","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KEN/BSGM/2013/Binary/ken_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14661,404,"KEN","Kenya","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KEN/BSGM/2013/DTE/ken_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14662,404,"KEN","Kenya","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/KEN/BSGM/2015/DTE/ken_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14663,404,"KEN","Kenya","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/KEN/BSGM/2016/DTE/ken_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14664,404,"KEN","Kenya","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/KEN/BSGM/2017/DTE/ken_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14665,404,"KEN","Kenya","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/KEN/BSGM/2018/DTE/ken_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14666,404,"KEN","Kenya","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/KEN/BSGM/2019/DTE/ken_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14667,404,"KEN","Kenya","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/KEN/BSGM/2020/DTE/ken_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14668,408,"PRK","North Korea","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PRK/BSGM/2001/Binary/prk_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14669,408,"PRK","North Korea","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PRK/BSGM/2001/DTE/prk_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14670,408,"PRK","North Korea","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PRK/BSGM/2002/Binary/prk_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14671,408,"PRK","North Korea","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PRK/BSGM/2002/DTE/prk_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14672,408,"PRK","North Korea","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PRK/BSGM/2003/Binary/prk_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14673,408,"PRK","North Korea","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PRK/BSGM/2003/DTE/prk_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14674,408,"PRK","North Korea","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PRK/BSGM/2004/Binary/prk_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14675,408,"PRK","North Korea","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PRK/BSGM/2004/DTE/prk_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14676,408,"PRK","North Korea","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PRK/BSGM/2005/Binary/prk_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14677,408,"PRK","North Korea","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PRK/BSGM/2005/DTE/prk_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14678,408,"PRK","North Korea","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PRK/BSGM/2006/Binary/prk_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14679,408,"PRK","North Korea","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PRK/BSGM/2006/DTE/prk_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14680,408,"PRK","North Korea","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PRK/BSGM/2007/Binary/prk_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14681,408,"PRK","North Korea","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PRK/BSGM/2007/DTE/prk_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14682,408,"PRK","North Korea","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PRK/BSGM/2008/Binary/prk_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14683,408,"PRK","North Korea","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PRK/BSGM/2008/DTE/prk_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14684,408,"PRK","North Korea","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PRK/BSGM/2009/Binary/prk_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14685,408,"PRK","North Korea","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PRK/BSGM/2009/DTE/prk_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14686,408,"PRK","North Korea","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PRK/BSGM/2010/Binary/prk_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14687,408,"PRK","North Korea","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PRK/BSGM/2010/DTE/prk_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14688,408,"PRK","North Korea","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PRK/BSGM/2011/Binary/prk_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14689,408,"PRK","North Korea","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PRK/BSGM/2011/DTE/prk_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14690,408,"PRK","North Korea","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PRK/BSGM/2013/Binary/prk_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14691,408,"PRK","North Korea","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PRK/BSGM/2013/DTE/prk_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14692,408,"PRK","North Korea","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PRK/BSGM/2015/DTE/prk_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14693,408,"PRK","North Korea","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PRK/BSGM/2016/DTE/prk_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14694,408,"PRK","North Korea","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PRK/BSGM/2017/DTE/prk_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14695,408,"PRK","North Korea","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PRK/BSGM/2018/DTE/prk_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14696,408,"PRK","North Korea","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PRK/BSGM/2019/DTE/prk_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14697,408,"PRK","North Korea","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PRK/BSGM/2020/DTE/prk_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14698,410,"KOR","South Korea","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KOR/BSGM/2001/Binary/kor_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14699,410,"KOR","South Korea","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KOR/BSGM/2001/DTE/kor_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14700,410,"KOR","South Korea","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KOR/BSGM/2002/Binary/kor_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14701,410,"KOR","South Korea","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KOR/BSGM/2002/DTE/kor_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14702,410,"KOR","South Korea","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KOR/BSGM/2003/Binary/kor_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14703,410,"KOR","South Korea","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KOR/BSGM/2003/DTE/kor_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14704,410,"KOR","South Korea","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KOR/BSGM/2004/Binary/kor_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14705,410,"KOR","South Korea","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KOR/BSGM/2004/DTE/kor_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14706,410,"KOR","South Korea","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KOR/BSGM/2005/Binary/kor_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14707,410,"KOR","South Korea","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KOR/BSGM/2005/DTE/kor_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14708,410,"KOR","South Korea","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KOR/BSGM/2006/Binary/kor_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14709,410,"KOR","South Korea","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KOR/BSGM/2006/DTE/kor_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14710,410,"KOR","South Korea","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KOR/BSGM/2007/Binary/kor_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14711,410,"KOR","South Korea","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KOR/BSGM/2007/DTE/kor_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14712,410,"KOR","South Korea","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KOR/BSGM/2008/Binary/kor_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14713,410,"KOR","South Korea","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KOR/BSGM/2008/DTE/kor_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14714,410,"KOR","South Korea","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KOR/BSGM/2009/Binary/kor_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14715,410,"KOR","South Korea","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KOR/BSGM/2009/DTE/kor_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14716,410,"KOR","South Korea","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KOR/BSGM/2010/Binary/kor_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14717,410,"KOR","South Korea","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KOR/BSGM/2010/DTE/kor_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14718,410,"KOR","South Korea","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KOR/BSGM/2011/Binary/kor_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14719,410,"KOR","South Korea","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KOR/BSGM/2011/DTE/kor_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14720,410,"KOR","South Korea","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KOR/BSGM/2013/Binary/kor_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14721,410,"KOR","South Korea","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KOR/BSGM/2013/DTE/kor_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14722,410,"KOR","South Korea","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/KOR/BSGM/2015/DTE/kor_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14723,410,"KOR","South Korea","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/KOR/BSGM/2016/DTE/kor_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14724,410,"KOR","South Korea","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/KOR/BSGM/2017/DTE/kor_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14725,410,"KOR","South Korea","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/KOR/BSGM/2018/DTE/kor_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14726,410,"KOR","South Korea","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/KOR/BSGM/2019/DTE/kor_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14727,410,"KOR","South Korea","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/KOR/BSGM/2020/DTE/kor_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14728,414,"KWT","Kuwait","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KWT/BSGM/2001/Binary/kwt_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14729,414,"KWT","Kuwait","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KWT/BSGM/2001/DTE/kwt_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14730,414,"KWT","Kuwait","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KWT/BSGM/2002/Binary/kwt_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14731,414,"KWT","Kuwait","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KWT/BSGM/2002/DTE/kwt_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14732,414,"KWT","Kuwait","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KWT/BSGM/2003/Binary/kwt_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14733,414,"KWT","Kuwait","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KWT/BSGM/2003/DTE/kwt_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14734,414,"KWT","Kuwait","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KWT/BSGM/2004/Binary/kwt_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14735,414,"KWT","Kuwait","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KWT/BSGM/2004/DTE/kwt_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14736,414,"KWT","Kuwait","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KWT/BSGM/2005/Binary/kwt_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14737,414,"KWT","Kuwait","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KWT/BSGM/2005/DTE/kwt_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14738,414,"KWT","Kuwait","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KWT/BSGM/2006/Binary/kwt_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14739,414,"KWT","Kuwait","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KWT/BSGM/2006/DTE/kwt_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14740,414,"KWT","Kuwait","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KWT/BSGM/2007/Binary/kwt_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14741,414,"KWT","Kuwait","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KWT/BSGM/2007/DTE/kwt_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14742,414,"KWT","Kuwait","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KWT/BSGM/2008/Binary/kwt_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14743,414,"KWT","Kuwait","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KWT/BSGM/2008/DTE/kwt_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14744,414,"KWT","Kuwait","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KWT/BSGM/2009/Binary/kwt_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14745,414,"KWT","Kuwait","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KWT/BSGM/2009/DTE/kwt_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14746,414,"KWT","Kuwait","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KWT/BSGM/2010/Binary/kwt_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14747,414,"KWT","Kuwait","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KWT/BSGM/2010/DTE/kwt_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14748,414,"KWT","Kuwait","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KWT/BSGM/2011/Binary/kwt_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14749,414,"KWT","Kuwait","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KWT/BSGM/2011/DTE/kwt_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14750,414,"KWT","Kuwait","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KWT/BSGM/2013/Binary/kwt_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14751,414,"KWT","Kuwait","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KWT/BSGM/2013/DTE/kwt_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14752,414,"KWT","Kuwait","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/KWT/BSGM/2015/DTE/kwt_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14753,414,"KWT","Kuwait","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/KWT/BSGM/2016/DTE/kwt_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14754,414,"KWT","Kuwait","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/KWT/BSGM/2017/DTE/kwt_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14755,414,"KWT","Kuwait","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/KWT/BSGM/2018/DTE/kwt_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14756,414,"KWT","Kuwait","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/KWT/BSGM/2019/DTE/kwt_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14757,414,"KWT","Kuwait","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/KWT/BSGM/2020/DTE/kwt_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14758,417,"KGZ","Kyrgyzstan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2001/Binary/kgz_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14759,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2001/DTE/kgz_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14760,417,"KGZ","Kyrgyzstan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2002/Binary/kgz_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14761,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2002/DTE/kgz_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14762,417,"KGZ","Kyrgyzstan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2003/Binary/kgz_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14763,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2003/DTE/kgz_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14764,417,"KGZ","Kyrgyzstan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2004/Binary/kgz_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14765,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2004/DTE/kgz_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14766,417,"KGZ","Kyrgyzstan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2005/Binary/kgz_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14767,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2005/DTE/kgz_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14768,417,"KGZ","Kyrgyzstan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2006/Binary/kgz_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14769,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2006/DTE/kgz_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14770,417,"KGZ","Kyrgyzstan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2007/Binary/kgz_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14771,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2007/DTE/kgz_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14772,417,"KGZ","Kyrgyzstan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2008/Binary/kgz_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14773,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2008/DTE/kgz_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14774,417,"KGZ","Kyrgyzstan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2009/Binary/kgz_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14775,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2009/DTE/kgz_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14776,417,"KGZ","Kyrgyzstan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2010/Binary/kgz_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14777,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2010/DTE/kgz_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14778,417,"KGZ","Kyrgyzstan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2011/Binary/kgz_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14779,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2011/DTE/kgz_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14780,417,"KGZ","Kyrgyzstan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2013/Binary/kgz_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14781,417,"KGZ","Kyrgyzstan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2013/DTE/kgz_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14782,417,"KGZ","Kyrgyzstan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2015/DTE/kgz_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14783,417,"KGZ","Kyrgyzstan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2016/DTE/kgz_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14784,417,"KGZ","Kyrgyzstan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2017/DTE/kgz_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14785,417,"KGZ","Kyrgyzstan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2018/DTE/kgz_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14786,417,"KGZ","Kyrgyzstan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2019/DTE/kgz_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14787,417,"KGZ","Kyrgyzstan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/KGZ/BSGM/2020/DTE/kgz_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14788,418,"LAO","Laos","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LAO/BSGM/2001/Binary/lao_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14789,418,"LAO","Laos","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LAO/BSGM/2001/DTE/lao_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14790,418,"LAO","Laos","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LAO/BSGM/2002/Binary/lao_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14791,418,"LAO","Laos","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LAO/BSGM/2002/DTE/lao_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14792,418,"LAO","Laos","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LAO/BSGM/2003/Binary/lao_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14793,418,"LAO","Laos","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LAO/BSGM/2003/DTE/lao_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14794,418,"LAO","Laos","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LAO/BSGM/2004/Binary/lao_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14795,418,"LAO","Laos","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LAO/BSGM/2004/DTE/lao_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14796,418,"LAO","Laos","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LAO/BSGM/2005/Binary/lao_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14797,418,"LAO","Laos","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LAO/BSGM/2005/DTE/lao_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14798,418,"LAO","Laos","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LAO/BSGM/2006/Binary/lao_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14799,418,"LAO","Laos","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LAO/BSGM/2006/DTE/lao_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14800,418,"LAO","Laos","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LAO/BSGM/2007/Binary/lao_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14801,418,"LAO","Laos","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LAO/BSGM/2007/DTE/lao_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14802,418,"LAO","Laos","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LAO/BSGM/2008/Binary/lao_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14803,418,"LAO","Laos","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LAO/BSGM/2008/DTE/lao_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14804,418,"LAO","Laos","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LAO/BSGM/2009/Binary/lao_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14805,418,"LAO","Laos","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LAO/BSGM/2009/DTE/lao_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14806,418,"LAO","Laos","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LAO/BSGM/2010/Binary/lao_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14807,418,"LAO","Laos","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LAO/BSGM/2010/DTE/lao_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14808,418,"LAO","Laos","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LAO/BSGM/2011/Binary/lao_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14809,418,"LAO","Laos","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LAO/BSGM/2011/DTE/lao_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14810,418,"LAO","Laos","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LAO/BSGM/2013/Binary/lao_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14811,418,"LAO","Laos","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LAO/BSGM/2013/DTE/lao_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14812,418,"LAO","Laos","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LAO/BSGM/2015/DTE/lao_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14813,418,"LAO","Laos","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LAO/BSGM/2016/DTE/lao_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14814,418,"LAO","Laos","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LAO/BSGM/2017/DTE/lao_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14815,418,"LAO","Laos","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LAO/BSGM/2018/DTE/lao_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14816,418,"LAO","Laos","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LAO/BSGM/2019/DTE/lao_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14817,418,"LAO","Laos","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LAO/BSGM/2020/DTE/lao_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14818,422,"LBN","Lebanon","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LBN/BSGM/2001/Binary/lbn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14819,422,"LBN","Lebanon","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LBN/BSGM/2001/DTE/lbn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14820,422,"LBN","Lebanon","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LBN/BSGM/2002/Binary/lbn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14821,422,"LBN","Lebanon","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LBN/BSGM/2002/DTE/lbn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14822,422,"LBN","Lebanon","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LBN/BSGM/2003/Binary/lbn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14823,422,"LBN","Lebanon","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LBN/BSGM/2003/DTE/lbn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14824,422,"LBN","Lebanon","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LBN/BSGM/2004/Binary/lbn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14825,422,"LBN","Lebanon","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LBN/BSGM/2004/DTE/lbn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14826,422,"LBN","Lebanon","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LBN/BSGM/2005/Binary/lbn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14827,422,"LBN","Lebanon","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LBN/BSGM/2005/DTE/lbn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14828,422,"LBN","Lebanon","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LBN/BSGM/2006/Binary/lbn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14829,422,"LBN","Lebanon","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LBN/BSGM/2006/DTE/lbn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14830,422,"LBN","Lebanon","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LBN/BSGM/2007/Binary/lbn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14831,422,"LBN","Lebanon","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LBN/BSGM/2007/DTE/lbn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14832,422,"LBN","Lebanon","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LBN/BSGM/2008/Binary/lbn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14833,422,"LBN","Lebanon","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LBN/BSGM/2008/DTE/lbn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14834,422,"LBN","Lebanon","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LBN/BSGM/2009/Binary/lbn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14835,422,"LBN","Lebanon","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LBN/BSGM/2009/DTE/lbn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14836,422,"LBN","Lebanon","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LBN/BSGM/2010/Binary/lbn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14837,422,"LBN","Lebanon","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LBN/BSGM/2010/DTE/lbn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14838,422,"LBN","Lebanon","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LBN/BSGM/2011/Binary/lbn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14839,422,"LBN","Lebanon","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LBN/BSGM/2011/DTE/lbn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14840,422,"LBN","Lebanon","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LBN/BSGM/2013/Binary/lbn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14841,422,"LBN","Lebanon","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LBN/BSGM/2013/DTE/lbn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14842,422,"LBN","Lebanon","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LBN/BSGM/2015/DTE/lbn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14843,422,"LBN","Lebanon","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LBN/BSGM/2016/DTE/lbn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14844,422,"LBN","Lebanon","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LBN/BSGM/2017/DTE/lbn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14845,422,"LBN","Lebanon","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LBN/BSGM/2018/DTE/lbn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14846,422,"LBN","Lebanon","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LBN/BSGM/2019/DTE/lbn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14847,422,"LBN","Lebanon","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LBN/BSGM/2020/DTE/lbn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14848,426,"LSO","Lesotho","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LSO/BSGM/2001/Binary/lso_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14849,426,"LSO","Lesotho","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LSO/BSGM/2001/DTE/lso_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14850,426,"LSO","Lesotho","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LSO/BSGM/2002/Binary/lso_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14851,426,"LSO","Lesotho","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LSO/BSGM/2002/DTE/lso_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14852,426,"LSO","Lesotho","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LSO/BSGM/2003/Binary/lso_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14853,426,"LSO","Lesotho","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LSO/BSGM/2003/DTE/lso_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14854,426,"LSO","Lesotho","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LSO/BSGM/2004/Binary/lso_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14855,426,"LSO","Lesotho","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LSO/BSGM/2004/DTE/lso_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14856,426,"LSO","Lesotho","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LSO/BSGM/2005/Binary/lso_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14857,426,"LSO","Lesotho","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LSO/BSGM/2005/DTE/lso_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14858,426,"LSO","Lesotho","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LSO/BSGM/2006/Binary/lso_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14859,426,"LSO","Lesotho","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LSO/BSGM/2006/DTE/lso_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14860,426,"LSO","Lesotho","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LSO/BSGM/2007/Binary/lso_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14861,426,"LSO","Lesotho","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LSO/BSGM/2007/DTE/lso_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14862,426,"LSO","Lesotho","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LSO/BSGM/2008/Binary/lso_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14863,426,"LSO","Lesotho","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LSO/BSGM/2008/DTE/lso_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14864,426,"LSO","Lesotho","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LSO/BSGM/2009/Binary/lso_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14865,426,"LSO","Lesotho","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LSO/BSGM/2009/DTE/lso_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14866,426,"LSO","Lesotho","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LSO/BSGM/2010/Binary/lso_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14867,426,"LSO","Lesotho","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LSO/BSGM/2010/DTE/lso_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14868,426,"LSO","Lesotho","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LSO/BSGM/2011/Binary/lso_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14869,426,"LSO","Lesotho","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LSO/BSGM/2011/DTE/lso_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14870,426,"LSO","Lesotho","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LSO/BSGM/2013/Binary/lso_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14871,426,"LSO","Lesotho","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LSO/BSGM/2013/DTE/lso_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14872,426,"LSO","Lesotho","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LSO/BSGM/2015/DTE/lso_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14873,426,"LSO","Lesotho","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LSO/BSGM/2016/DTE/lso_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14874,426,"LSO","Lesotho","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LSO/BSGM/2017/DTE/lso_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14875,426,"LSO","Lesotho","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LSO/BSGM/2018/DTE/lso_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14876,426,"LSO","Lesotho","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LSO/BSGM/2019/DTE/lso_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14877,426,"LSO","Lesotho","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LSO/BSGM/2020/DTE/lso_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14878,428,"LVA","Latvia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LVA/BSGM/2001/Binary/lva_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14879,428,"LVA","Latvia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LVA/BSGM/2001/DTE/lva_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14880,428,"LVA","Latvia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LVA/BSGM/2002/Binary/lva_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14881,428,"LVA","Latvia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LVA/BSGM/2002/DTE/lva_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14882,428,"LVA","Latvia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LVA/BSGM/2003/Binary/lva_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14883,428,"LVA","Latvia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LVA/BSGM/2003/DTE/lva_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14884,428,"LVA","Latvia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LVA/BSGM/2004/Binary/lva_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14885,428,"LVA","Latvia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LVA/BSGM/2004/DTE/lva_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14886,428,"LVA","Latvia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LVA/BSGM/2005/Binary/lva_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14887,428,"LVA","Latvia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LVA/BSGM/2005/DTE/lva_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14888,428,"LVA","Latvia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LVA/BSGM/2006/Binary/lva_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14889,428,"LVA","Latvia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LVA/BSGM/2006/DTE/lva_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14890,428,"LVA","Latvia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LVA/BSGM/2007/Binary/lva_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14891,428,"LVA","Latvia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LVA/BSGM/2007/DTE/lva_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14892,428,"LVA","Latvia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LVA/BSGM/2008/Binary/lva_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14893,428,"LVA","Latvia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LVA/BSGM/2008/DTE/lva_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14894,428,"LVA","Latvia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LVA/BSGM/2009/Binary/lva_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14895,428,"LVA","Latvia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LVA/BSGM/2009/DTE/lva_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14896,428,"LVA","Latvia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LVA/BSGM/2010/Binary/lva_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14897,428,"LVA","Latvia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LVA/BSGM/2010/DTE/lva_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14898,428,"LVA","Latvia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LVA/BSGM/2011/Binary/lva_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14899,428,"LVA","Latvia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LVA/BSGM/2011/DTE/lva_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14900,428,"LVA","Latvia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LVA/BSGM/2013/Binary/lva_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14901,428,"LVA","Latvia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LVA/BSGM/2013/DTE/lva_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14902,428,"LVA","Latvia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LVA/BSGM/2015/DTE/lva_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14903,428,"LVA","Latvia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LVA/BSGM/2016/DTE/lva_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14904,428,"LVA","Latvia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LVA/BSGM/2017/DTE/lva_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14905,428,"LVA","Latvia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LVA/BSGM/2018/DTE/lva_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14906,428,"LVA","Latvia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LVA/BSGM/2019/DTE/lva_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14907,428,"LVA","Latvia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LVA/BSGM/2020/DTE/lva_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14908,430,"LBR","Liberia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LBR/BSGM/2001/Binary/lbr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14909,430,"LBR","Liberia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LBR/BSGM/2001/DTE/lbr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14910,430,"LBR","Liberia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LBR/BSGM/2002/Binary/lbr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14911,430,"LBR","Liberia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LBR/BSGM/2002/DTE/lbr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14912,430,"LBR","Liberia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LBR/BSGM/2003/Binary/lbr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14913,430,"LBR","Liberia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LBR/BSGM/2003/DTE/lbr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14914,430,"LBR","Liberia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LBR/BSGM/2004/Binary/lbr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14915,430,"LBR","Liberia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LBR/BSGM/2004/DTE/lbr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14916,430,"LBR","Liberia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LBR/BSGM/2005/Binary/lbr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14917,430,"LBR","Liberia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LBR/BSGM/2005/DTE/lbr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14918,430,"LBR","Liberia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LBR/BSGM/2006/Binary/lbr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14919,430,"LBR","Liberia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LBR/BSGM/2006/DTE/lbr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14920,430,"LBR","Liberia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LBR/BSGM/2007/Binary/lbr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14921,430,"LBR","Liberia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LBR/BSGM/2007/DTE/lbr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14922,430,"LBR","Liberia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LBR/BSGM/2008/Binary/lbr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14923,430,"LBR","Liberia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LBR/BSGM/2008/DTE/lbr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14924,430,"LBR","Liberia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LBR/BSGM/2009/Binary/lbr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14925,430,"LBR","Liberia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LBR/BSGM/2009/DTE/lbr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14926,430,"LBR","Liberia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LBR/BSGM/2010/Binary/lbr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14927,430,"LBR","Liberia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LBR/BSGM/2010/DTE/lbr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14928,430,"LBR","Liberia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LBR/BSGM/2011/Binary/lbr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14929,430,"LBR","Liberia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LBR/BSGM/2011/DTE/lbr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14930,430,"LBR","Liberia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LBR/BSGM/2013/Binary/lbr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14931,430,"LBR","Liberia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LBR/BSGM/2013/DTE/lbr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14932,430,"LBR","Liberia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LBR/BSGM/2015/DTE/lbr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14933,430,"LBR","Liberia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LBR/BSGM/2016/DTE/lbr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14934,430,"LBR","Liberia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LBR/BSGM/2017/DTE/lbr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14935,430,"LBR","Liberia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LBR/BSGM/2018/DTE/lbr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14936,430,"LBR","Liberia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LBR/BSGM/2019/DTE/lbr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14937,430,"LBR","Liberia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LBR/BSGM/2020/DTE/lbr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14938,434,"LBY","Libya","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LBY/BSGM/2001/Binary/lby_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14939,434,"LBY","Libya","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LBY/BSGM/2001/DTE/lby_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14940,434,"LBY","Libya","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LBY/BSGM/2002/Binary/lby_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14941,434,"LBY","Libya","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LBY/BSGM/2002/DTE/lby_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14942,434,"LBY","Libya","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LBY/BSGM/2003/Binary/lby_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14943,434,"LBY","Libya","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LBY/BSGM/2003/DTE/lby_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14944,434,"LBY","Libya","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LBY/BSGM/2004/Binary/lby_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14945,434,"LBY","Libya","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LBY/BSGM/2004/DTE/lby_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14946,434,"LBY","Libya","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LBY/BSGM/2005/Binary/lby_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14947,434,"LBY","Libya","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LBY/BSGM/2005/DTE/lby_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14948,434,"LBY","Libya","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LBY/BSGM/2006/Binary/lby_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14949,434,"LBY","Libya","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LBY/BSGM/2006/DTE/lby_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14950,434,"LBY","Libya","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LBY/BSGM/2007/Binary/lby_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14951,434,"LBY","Libya","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LBY/BSGM/2007/DTE/lby_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14952,434,"LBY","Libya","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LBY/BSGM/2008/Binary/lby_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14953,434,"LBY","Libya","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LBY/BSGM/2008/DTE/lby_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14954,434,"LBY","Libya","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LBY/BSGM/2009/Binary/lby_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14955,434,"LBY","Libya","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LBY/BSGM/2009/DTE/lby_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14956,434,"LBY","Libya","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LBY/BSGM/2010/Binary/lby_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14957,434,"LBY","Libya","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LBY/BSGM/2010/DTE/lby_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14958,434,"LBY","Libya","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LBY/BSGM/2011/Binary/lby_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14959,434,"LBY","Libya","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LBY/BSGM/2011/DTE/lby_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14960,434,"LBY","Libya","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LBY/BSGM/2013/Binary/lby_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14961,434,"LBY","Libya","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LBY/BSGM/2013/DTE/lby_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14962,434,"LBY","Libya","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LBY/BSGM/2015/DTE/lby_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14963,434,"LBY","Libya","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LBY/BSGM/2016/DTE/lby_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14964,434,"LBY","Libya","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LBY/BSGM/2017/DTE/lby_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14965,434,"LBY","Libya","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LBY/BSGM/2018/DTE/lby_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14966,434,"LBY","Libya","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LBY/BSGM/2019/DTE/lby_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14967,434,"LBY","Libya","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LBY/BSGM/2020/DTE/lby_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14968,438,"LIE","Liechtenstein","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LIE/BSGM/2001/Binary/lie_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14969,438,"LIE","Liechtenstein","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LIE/BSGM/2001/DTE/lie_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
14970,438,"LIE","Liechtenstein","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LIE/BSGM/2002/Binary/lie_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
14971,438,"LIE","Liechtenstein","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LIE/BSGM/2002/DTE/lie_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
14972,438,"LIE","Liechtenstein","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LIE/BSGM/2003/Binary/lie_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
14973,438,"LIE","Liechtenstein","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LIE/BSGM/2003/DTE/lie_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
14974,438,"LIE","Liechtenstein","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LIE/BSGM/2004/Binary/lie_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
14975,438,"LIE","Liechtenstein","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LIE/BSGM/2004/DTE/lie_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
14976,438,"LIE","Liechtenstein","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LIE/BSGM/2005/Binary/lie_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
14977,438,"LIE","Liechtenstein","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LIE/BSGM/2005/DTE/lie_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
14978,438,"LIE","Liechtenstein","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LIE/BSGM/2006/Binary/lie_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
14979,438,"LIE","Liechtenstein","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LIE/BSGM/2006/DTE/lie_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
14980,438,"LIE","Liechtenstein","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LIE/BSGM/2007/Binary/lie_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
14981,438,"LIE","Liechtenstein","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LIE/BSGM/2007/DTE/lie_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
14982,438,"LIE","Liechtenstein","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LIE/BSGM/2008/Binary/lie_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
14983,438,"LIE","Liechtenstein","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LIE/BSGM/2008/DTE/lie_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
14984,438,"LIE","Liechtenstein","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LIE/BSGM/2009/Binary/lie_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
14985,438,"LIE","Liechtenstein","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LIE/BSGM/2009/DTE/lie_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
14986,438,"LIE","Liechtenstein","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LIE/BSGM/2010/Binary/lie_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
14987,438,"LIE","Liechtenstein","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LIE/BSGM/2010/DTE/lie_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
14988,438,"LIE","Liechtenstein","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LIE/BSGM/2011/Binary/lie_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
14989,438,"LIE","Liechtenstein","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LIE/BSGM/2011/DTE/lie_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
14990,438,"LIE","Liechtenstein","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LIE/BSGM/2013/Binary/lie_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
14991,438,"LIE","Liechtenstein","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LIE/BSGM/2013/DTE/lie_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
14992,438,"LIE","Liechtenstein","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LIE/BSGM/2015/DTE/lie_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
14993,438,"LIE","Liechtenstein","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LIE/BSGM/2016/DTE/lie_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
14994,438,"LIE","Liechtenstein","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LIE/BSGM/2017/DTE/lie_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
14995,438,"LIE","Liechtenstein","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LIE/BSGM/2018/DTE/lie_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
14996,438,"LIE","Liechtenstein","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LIE/BSGM/2019/DTE/lie_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
14997,438,"LIE","Liechtenstein","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LIE/BSGM/2020/DTE/lie_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
14998,440,"LTU","Lithuania","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LTU/BSGM/2001/Binary/ltu_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
14999,440,"LTU","Lithuania","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LTU/BSGM/2001/DTE/ltu_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15000,440,"LTU","Lithuania","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LTU/BSGM/2002/Binary/ltu_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15001,440,"LTU","Lithuania","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LTU/BSGM/2002/DTE/ltu_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15002,440,"LTU","Lithuania","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LTU/BSGM/2003/Binary/ltu_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15003,440,"LTU","Lithuania","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LTU/BSGM/2003/DTE/ltu_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15004,440,"LTU","Lithuania","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LTU/BSGM/2004/Binary/ltu_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15005,440,"LTU","Lithuania","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LTU/BSGM/2004/DTE/ltu_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15006,440,"LTU","Lithuania","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LTU/BSGM/2005/Binary/ltu_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15007,440,"LTU","Lithuania","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LTU/BSGM/2005/DTE/ltu_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15008,440,"LTU","Lithuania","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LTU/BSGM/2006/Binary/ltu_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15009,440,"LTU","Lithuania","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LTU/BSGM/2006/DTE/ltu_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15010,440,"LTU","Lithuania","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LTU/BSGM/2007/Binary/ltu_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15011,440,"LTU","Lithuania","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LTU/BSGM/2007/DTE/ltu_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15012,440,"LTU","Lithuania","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LTU/BSGM/2008/Binary/ltu_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15013,440,"LTU","Lithuania","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LTU/BSGM/2008/DTE/ltu_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15014,440,"LTU","Lithuania","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LTU/BSGM/2009/Binary/ltu_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15015,440,"LTU","Lithuania","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LTU/BSGM/2009/DTE/ltu_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15016,440,"LTU","Lithuania","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LTU/BSGM/2010/Binary/ltu_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15017,440,"LTU","Lithuania","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LTU/BSGM/2010/DTE/ltu_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15018,440,"LTU","Lithuania","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LTU/BSGM/2011/Binary/ltu_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15019,440,"LTU","Lithuania","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LTU/BSGM/2011/DTE/ltu_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15020,440,"LTU","Lithuania","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LTU/BSGM/2013/Binary/ltu_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15021,440,"LTU","Lithuania","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LTU/BSGM/2013/DTE/ltu_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15022,440,"LTU","Lithuania","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LTU/BSGM/2015/DTE/ltu_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15023,440,"LTU","Lithuania","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LTU/BSGM/2016/DTE/ltu_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15024,440,"LTU","Lithuania","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LTU/BSGM/2017/DTE/ltu_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15025,440,"LTU","Lithuania","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LTU/BSGM/2018/DTE/ltu_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15026,440,"LTU","Lithuania","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LTU/BSGM/2019/DTE/ltu_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15027,440,"LTU","Lithuania","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LTU/BSGM/2020/DTE/ltu_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15028,442,"LUX","Luxembourg","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LUX/BSGM/2001/Binary/lux_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15029,442,"LUX","Luxembourg","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LUX/BSGM/2001/DTE/lux_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15030,442,"LUX","Luxembourg","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LUX/BSGM/2002/Binary/lux_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15031,442,"LUX","Luxembourg","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LUX/BSGM/2002/DTE/lux_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15032,442,"LUX","Luxembourg","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LUX/BSGM/2003/Binary/lux_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15033,442,"LUX","Luxembourg","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LUX/BSGM/2003/DTE/lux_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15034,442,"LUX","Luxembourg","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LUX/BSGM/2004/Binary/lux_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15035,442,"LUX","Luxembourg","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LUX/BSGM/2004/DTE/lux_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15036,442,"LUX","Luxembourg","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LUX/BSGM/2005/Binary/lux_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15037,442,"LUX","Luxembourg","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LUX/BSGM/2005/DTE/lux_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15038,442,"LUX","Luxembourg","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LUX/BSGM/2006/Binary/lux_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15039,442,"LUX","Luxembourg","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LUX/BSGM/2006/DTE/lux_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15040,442,"LUX","Luxembourg","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LUX/BSGM/2007/Binary/lux_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15041,442,"LUX","Luxembourg","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LUX/BSGM/2007/DTE/lux_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15042,442,"LUX","Luxembourg","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LUX/BSGM/2008/Binary/lux_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15043,442,"LUX","Luxembourg","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LUX/BSGM/2008/DTE/lux_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15044,442,"LUX","Luxembourg","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LUX/BSGM/2009/Binary/lux_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15045,442,"LUX","Luxembourg","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LUX/BSGM/2009/DTE/lux_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15046,442,"LUX","Luxembourg","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LUX/BSGM/2010/Binary/lux_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15047,442,"LUX","Luxembourg","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LUX/BSGM/2010/DTE/lux_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15048,442,"LUX","Luxembourg","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LUX/BSGM/2011/Binary/lux_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15049,442,"LUX","Luxembourg","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LUX/BSGM/2011/DTE/lux_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15050,442,"LUX","Luxembourg","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LUX/BSGM/2013/Binary/lux_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15051,442,"LUX","Luxembourg","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LUX/BSGM/2013/DTE/lux_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15052,442,"LUX","Luxembourg","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LUX/BSGM/2015/DTE/lux_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15053,442,"LUX","Luxembourg","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LUX/BSGM/2016/DTE/lux_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15054,442,"LUX","Luxembourg","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LUX/BSGM/2017/DTE/lux_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15055,442,"LUX","Luxembourg","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LUX/BSGM/2018/DTE/lux_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15056,442,"LUX","Luxembourg","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LUX/BSGM/2019/DTE/lux_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15057,442,"LUX","Luxembourg","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LUX/BSGM/2020/DTE/lux_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15058,446,"MAC","Macao","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MAC/BSGM/2001/Binary/mac_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15059,446,"MAC","Macao","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MAC/BSGM/2001/DTE/mac_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15060,446,"MAC","Macao","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MAC/BSGM/2002/Binary/mac_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15061,446,"MAC","Macao","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MAC/BSGM/2002/DTE/mac_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15062,446,"MAC","Macao","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MAC/BSGM/2003/Binary/mac_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15063,446,"MAC","Macao","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MAC/BSGM/2003/DTE/mac_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15064,446,"MAC","Macao","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MAC/BSGM/2004/Binary/mac_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15065,446,"MAC","Macao","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MAC/BSGM/2004/DTE/mac_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15066,446,"MAC","Macao","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MAC/BSGM/2005/Binary/mac_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15067,446,"MAC","Macao","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MAC/BSGM/2005/DTE/mac_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15068,446,"MAC","Macao","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MAC/BSGM/2006/Binary/mac_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15069,446,"MAC","Macao","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MAC/BSGM/2006/DTE/mac_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15070,446,"MAC","Macao","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MAC/BSGM/2007/Binary/mac_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15071,446,"MAC","Macao","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MAC/BSGM/2007/DTE/mac_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15072,446,"MAC","Macao","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MAC/BSGM/2008/Binary/mac_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15073,446,"MAC","Macao","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MAC/BSGM/2008/DTE/mac_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15074,446,"MAC","Macao","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MAC/BSGM/2009/Binary/mac_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15075,446,"MAC","Macao","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MAC/BSGM/2009/DTE/mac_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15076,446,"MAC","Macao","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MAC/BSGM/2010/Binary/mac_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15077,446,"MAC","Macao","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MAC/BSGM/2010/DTE/mac_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15078,446,"MAC","Macao","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MAC/BSGM/2011/Binary/mac_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15079,446,"MAC","Macao","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MAC/BSGM/2011/DTE/mac_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15080,446,"MAC","Macao","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MAC/BSGM/2013/Binary/mac_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15081,446,"MAC","Macao","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MAC/BSGM/2013/DTE/mac_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15082,446,"MAC","Macao","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MAC/BSGM/2015/DTE/mac_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15083,446,"MAC","Macao","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MAC/BSGM/2016/DTE/mac_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15084,446,"MAC","Macao","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MAC/BSGM/2017/DTE/mac_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15085,446,"MAC","Macao","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MAC/BSGM/2018/DTE/mac_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15086,446,"MAC","Macao","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MAC/BSGM/2019/DTE/mac_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15087,446,"MAC","Macao","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MAC/BSGM/2020/DTE/mac_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15088,450,"MDG","Madagascar","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MDG/BSGM/2001/Binary/mdg_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15089,450,"MDG","Madagascar","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MDG/BSGM/2001/DTE/mdg_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15090,450,"MDG","Madagascar","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MDG/BSGM/2002/Binary/mdg_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15091,450,"MDG","Madagascar","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MDG/BSGM/2002/DTE/mdg_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15092,450,"MDG","Madagascar","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MDG/BSGM/2003/Binary/mdg_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15093,450,"MDG","Madagascar","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MDG/BSGM/2003/DTE/mdg_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15094,450,"MDG","Madagascar","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MDG/BSGM/2004/Binary/mdg_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15095,450,"MDG","Madagascar","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MDG/BSGM/2004/DTE/mdg_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15096,450,"MDG","Madagascar","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MDG/BSGM/2005/Binary/mdg_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15097,450,"MDG","Madagascar","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MDG/BSGM/2005/DTE/mdg_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15098,450,"MDG","Madagascar","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MDG/BSGM/2006/Binary/mdg_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15099,450,"MDG","Madagascar","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MDG/BSGM/2006/DTE/mdg_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15100,450,"MDG","Madagascar","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MDG/BSGM/2007/Binary/mdg_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15101,450,"MDG","Madagascar","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MDG/BSGM/2007/DTE/mdg_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15102,450,"MDG","Madagascar","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MDG/BSGM/2008/Binary/mdg_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15103,450,"MDG","Madagascar","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MDG/BSGM/2008/DTE/mdg_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15104,450,"MDG","Madagascar","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MDG/BSGM/2009/Binary/mdg_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15105,450,"MDG","Madagascar","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MDG/BSGM/2009/DTE/mdg_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15106,450,"MDG","Madagascar","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MDG/BSGM/2010/Binary/mdg_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15107,450,"MDG","Madagascar","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MDG/BSGM/2010/DTE/mdg_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15108,450,"MDG","Madagascar","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MDG/BSGM/2011/Binary/mdg_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15109,450,"MDG","Madagascar","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MDG/BSGM/2011/DTE/mdg_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15110,450,"MDG","Madagascar","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MDG/BSGM/2013/Binary/mdg_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15111,450,"MDG","Madagascar","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MDG/BSGM/2013/DTE/mdg_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15112,450,"MDG","Madagascar","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MDG/BSGM/2015/DTE/mdg_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15113,450,"MDG","Madagascar","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MDG/BSGM/2016/DTE/mdg_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15114,450,"MDG","Madagascar","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MDG/BSGM/2017/DTE/mdg_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15115,450,"MDG","Madagascar","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MDG/BSGM/2018/DTE/mdg_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15116,450,"MDG","Madagascar","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MDG/BSGM/2019/DTE/mdg_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15117,450,"MDG","Madagascar","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MDG/BSGM/2020/DTE/mdg_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15118,454,"MWI","Malawi","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MWI/BSGM/2001/Binary/mwi_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15119,454,"MWI","Malawi","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MWI/BSGM/2001/DTE/mwi_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15120,454,"MWI","Malawi","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MWI/BSGM/2002/Binary/mwi_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15121,454,"MWI","Malawi","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MWI/BSGM/2002/DTE/mwi_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15122,454,"MWI","Malawi","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MWI/BSGM/2003/Binary/mwi_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15123,454,"MWI","Malawi","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MWI/BSGM/2003/DTE/mwi_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15124,454,"MWI","Malawi","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MWI/BSGM/2004/Binary/mwi_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15125,454,"MWI","Malawi","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MWI/BSGM/2004/DTE/mwi_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15126,454,"MWI","Malawi","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MWI/BSGM/2005/Binary/mwi_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15127,454,"MWI","Malawi","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MWI/BSGM/2005/DTE/mwi_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15128,454,"MWI","Malawi","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MWI/BSGM/2006/Binary/mwi_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15129,454,"MWI","Malawi","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MWI/BSGM/2006/DTE/mwi_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15130,454,"MWI","Malawi","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MWI/BSGM/2007/Binary/mwi_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15131,454,"MWI","Malawi","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MWI/BSGM/2007/DTE/mwi_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15132,454,"MWI","Malawi","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MWI/BSGM/2008/Binary/mwi_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15133,454,"MWI","Malawi","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MWI/BSGM/2008/DTE/mwi_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15134,454,"MWI","Malawi","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MWI/BSGM/2009/Binary/mwi_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15135,454,"MWI","Malawi","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MWI/BSGM/2009/DTE/mwi_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15136,454,"MWI","Malawi","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MWI/BSGM/2010/Binary/mwi_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15137,454,"MWI","Malawi","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MWI/BSGM/2010/DTE/mwi_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15138,454,"MWI","Malawi","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MWI/BSGM/2011/Binary/mwi_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15139,454,"MWI","Malawi","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MWI/BSGM/2011/DTE/mwi_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15140,454,"MWI","Malawi","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MWI/BSGM/2013/Binary/mwi_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15141,454,"MWI","Malawi","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MWI/BSGM/2013/DTE/mwi_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15142,454,"MWI","Malawi","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MWI/BSGM/2015/DTE/mwi_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15143,454,"MWI","Malawi","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MWI/BSGM/2016/DTE/mwi_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15144,454,"MWI","Malawi","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MWI/BSGM/2017/DTE/mwi_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15145,454,"MWI","Malawi","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MWI/BSGM/2018/DTE/mwi_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15146,454,"MWI","Malawi","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MWI/BSGM/2019/DTE/mwi_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15147,454,"MWI","Malawi","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MWI/BSGM/2020/DTE/mwi_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15148,458,"MYS","Malaysia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MYS/BSGM/2001/Binary/mys_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15149,458,"MYS","Malaysia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MYS/BSGM/2001/DTE/mys_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15150,458,"MYS","Malaysia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MYS/BSGM/2002/Binary/mys_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15151,458,"MYS","Malaysia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MYS/BSGM/2002/DTE/mys_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15152,458,"MYS","Malaysia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MYS/BSGM/2003/Binary/mys_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15153,458,"MYS","Malaysia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MYS/BSGM/2003/DTE/mys_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15154,458,"MYS","Malaysia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MYS/BSGM/2004/Binary/mys_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15155,458,"MYS","Malaysia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MYS/BSGM/2004/DTE/mys_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15156,458,"MYS","Malaysia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MYS/BSGM/2005/Binary/mys_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15157,458,"MYS","Malaysia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MYS/BSGM/2005/DTE/mys_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15158,458,"MYS","Malaysia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MYS/BSGM/2006/Binary/mys_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15159,458,"MYS","Malaysia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MYS/BSGM/2006/DTE/mys_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15160,458,"MYS","Malaysia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MYS/BSGM/2007/Binary/mys_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15161,458,"MYS","Malaysia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MYS/BSGM/2007/DTE/mys_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15162,458,"MYS","Malaysia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MYS/BSGM/2008/Binary/mys_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15163,458,"MYS","Malaysia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MYS/BSGM/2008/DTE/mys_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15164,458,"MYS","Malaysia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MYS/BSGM/2009/Binary/mys_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15165,458,"MYS","Malaysia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MYS/BSGM/2009/DTE/mys_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15166,458,"MYS","Malaysia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MYS/BSGM/2010/Binary/mys_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15167,458,"MYS","Malaysia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MYS/BSGM/2010/DTE/mys_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15168,458,"MYS","Malaysia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MYS/BSGM/2011/Binary/mys_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15169,458,"MYS","Malaysia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MYS/BSGM/2011/DTE/mys_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15170,458,"MYS","Malaysia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MYS/BSGM/2013/Binary/mys_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15171,458,"MYS","Malaysia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MYS/BSGM/2013/DTE/mys_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15172,458,"MYS","Malaysia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MYS/BSGM/2015/DTE/mys_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15173,458,"MYS","Malaysia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MYS/BSGM/2016/DTE/mys_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15174,458,"MYS","Malaysia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MYS/BSGM/2017/DTE/mys_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15175,458,"MYS","Malaysia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MYS/BSGM/2018/DTE/mys_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15176,458,"MYS","Malaysia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MYS/BSGM/2019/DTE/mys_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15177,458,"MYS","Malaysia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MYS/BSGM/2020/DTE/mys_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15178,462,"MDV","Maldives","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MDV/BSGM/2001/Binary/mdv_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15179,462,"MDV","Maldives","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MDV/BSGM/2001/DTE/mdv_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15180,462,"MDV","Maldives","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MDV/BSGM/2002/Binary/mdv_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15181,462,"MDV","Maldives","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MDV/BSGM/2002/DTE/mdv_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15182,462,"MDV","Maldives","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MDV/BSGM/2003/Binary/mdv_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15183,462,"MDV","Maldives","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MDV/BSGM/2003/DTE/mdv_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15184,462,"MDV","Maldives","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MDV/BSGM/2004/Binary/mdv_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15185,462,"MDV","Maldives","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MDV/BSGM/2004/DTE/mdv_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15186,462,"MDV","Maldives","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MDV/BSGM/2005/Binary/mdv_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15187,462,"MDV","Maldives","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MDV/BSGM/2005/DTE/mdv_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15188,462,"MDV","Maldives","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MDV/BSGM/2006/Binary/mdv_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15189,462,"MDV","Maldives","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MDV/BSGM/2006/DTE/mdv_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15190,462,"MDV","Maldives","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MDV/BSGM/2007/Binary/mdv_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15191,462,"MDV","Maldives","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MDV/BSGM/2007/DTE/mdv_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15192,462,"MDV","Maldives","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MDV/BSGM/2008/Binary/mdv_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15193,462,"MDV","Maldives","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MDV/BSGM/2008/DTE/mdv_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15194,462,"MDV","Maldives","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MDV/BSGM/2009/Binary/mdv_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15195,462,"MDV","Maldives","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MDV/BSGM/2009/DTE/mdv_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15196,462,"MDV","Maldives","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MDV/BSGM/2010/Binary/mdv_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15197,462,"MDV","Maldives","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MDV/BSGM/2010/DTE/mdv_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15198,462,"MDV","Maldives","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MDV/BSGM/2011/Binary/mdv_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15199,462,"MDV","Maldives","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MDV/BSGM/2011/DTE/mdv_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15200,462,"MDV","Maldives","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MDV/BSGM/2013/Binary/mdv_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15201,462,"MDV","Maldives","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MDV/BSGM/2013/DTE/mdv_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15202,462,"MDV","Maldives","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MDV/BSGM/2015/DTE/mdv_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15203,462,"MDV","Maldives","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MDV/BSGM/2016/DTE/mdv_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15204,462,"MDV","Maldives","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MDV/BSGM/2017/DTE/mdv_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15205,462,"MDV","Maldives","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MDV/BSGM/2018/DTE/mdv_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15206,462,"MDV","Maldives","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MDV/BSGM/2019/DTE/mdv_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15207,462,"MDV","Maldives","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MDV/BSGM/2020/DTE/mdv_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15208,466,"MLI","Mali","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MLI/BSGM/2001/Binary/mli_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15209,466,"MLI","Mali","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MLI/BSGM/2001/DTE/mli_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15210,466,"MLI","Mali","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MLI/BSGM/2002/Binary/mli_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15211,466,"MLI","Mali","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MLI/BSGM/2002/DTE/mli_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15212,466,"MLI","Mali","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MLI/BSGM/2003/Binary/mli_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15213,466,"MLI","Mali","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MLI/BSGM/2003/DTE/mli_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15214,466,"MLI","Mali","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MLI/BSGM/2004/Binary/mli_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15215,466,"MLI","Mali","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MLI/BSGM/2004/DTE/mli_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15216,466,"MLI","Mali","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MLI/BSGM/2005/Binary/mli_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15217,466,"MLI","Mali","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MLI/BSGM/2005/DTE/mli_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15218,466,"MLI","Mali","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MLI/BSGM/2006/Binary/mli_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15219,466,"MLI","Mali","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MLI/BSGM/2006/DTE/mli_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15220,466,"MLI","Mali","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MLI/BSGM/2007/Binary/mli_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15221,466,"MLI","Mali","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MLI/BSGM/2007/DTE/mli_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15222,466,"MLI","Mali","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MLI/BSGM/2008/Binary/mli_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15223,466,"MLI","Mali","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MLI/BSGM/2008/DTE/mli_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15224,466,"MLI","Mali","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MLI/BSGM/2009/Binary/mli_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15225,466,"MLI","Mali","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MLI/BSGM/2009/DTE/mli_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15226,466,"MLI","Mali","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MLI/BSGM/2010/Binary/mli_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15227,466,"MLI","Mali","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MLI/BSGM/2010/DTE/mli_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15228,466,"MLI","Mali","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MLI/BSGM/2011/Binary/mli_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15229,466,"MLI","Mali","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MLI/BSGM/2011/DTE/mli_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15230,466,"MLI","Mali","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MLI/BSGM/2013/Binary/mli_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15231,466,"MLI","Mali","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MLI/BSGM/2013/DTE/mli_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15232,466,"MLI","Mali","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MLI/BSGM/2015/DTE/mli_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15233,466,"MLI","Mali","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MLI/BSGM/2016/DTE/mli_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15234,466,"MLI","Mali","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MLI/BSGM/2017/DTE/mli_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15235,466,"MLI","Mali","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MLI/BSGM/2018/DTE/mli_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15236,466,"MLI","Mali","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MLI/BSGM/2019/DTE/mli_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15237,466,"MLI","Mali","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MLI/BSGM/2020/DTE/mli_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15238,470,"MLT","Malta","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MLT/BSGM/2001/Binary/mlt_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15239,470,"MLT","Malta","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MLT/BSGM/2001/DTE/mlt_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15240,470,"MLT","Malta","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MLT/BSGM/2002/Binary/mlt_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15241,470,"MLT","Malta","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MLT/BSGM/2002/DTE/mlt_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15242,470,"MLT","Malta","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MLT/BSGM/2003/Binary/mlt_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15243,470,"MLT","Malta","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MLT/BSGM/2003/DTE/mlt_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15244,470,"MLT","Malta","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MLT/BSGM/2004/Binary/mlt_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15245,470,"MLT","Malta","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MLT/BSGM/2004/DTE/mlt_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15246,470,"MLT","Malta","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MLT/BSGM/2005/Binary/mlt_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15247,470,"MLT","Malta","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MLT/BSGM/2005/DTE/mlt_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15248,470,"MLT","Malta","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MLT/BSGM/2006/Binary/mlt_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15249,470,"MLT","Malta","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MLT/BSGM/2006/DTE/mlt_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15250,470,"MLT","Malta","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MLT/BSGM/2007/Binary/mlt_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15251,470,"MLT","Malta","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MLT/BSGM/2007/DTE/mlt_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15252,470,"MLT","Malta","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MLT/BSGM/2008/Binary/mlt_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15253,470,"MLT","Malta","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MLT/BSGM/2008/DTE/mlt_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15254,470,"MLT","Malta","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MLT/BSGM/2009/Binary/mlt_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15255,470,"MLT","Malta","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MLT/BSGM/2009/DTE/mlt_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15256,470,"MLT","Malta","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MLT/BSGM/2010/Binary/mlt_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15257,470,"MLT","Malta","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MLT/BSGM/2010/DTE/mlt_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15258,470,"MLT","Malta","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MLT/BSGM/2011/Binary/mlt_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15259,470,"MLT","Malta","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MLT/BSGM/2011/DTE/mlt_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15260,470,"MLT","Malta","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MLT/BSGM/2013/Binary/mlt_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15261,470,"MLT","Malta","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MLT/BSGM/2013/DTE/mlt_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15262,470,"MLT","Malta","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MLT/BSGM/2015/DTE/mlt_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15263,470,"MLT","Malta","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MLT/BSGM/2016/DTE/mlt_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15264,470,"MLT","Malta","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MLT/BSGM/2017/DTE/mlt_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15265,470,"MLT","Malta","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MLT/BSGM/2018/DTE/mlt_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15266,470,"MLT","Malta","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MLT/BSGM/2019/DTE/mlt_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15267,470,"MLT","Malta","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MLT/BSGM/2020/DTE/mlt_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15268,474,"MTQ","Martinique","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2001/Binary/mtq_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15269,474,"MTQ","Martinique","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2001/DTE/mtq_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15270,474,"MTQ","Martinique","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2002/Binary/mtq_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15271,474,"MTQ","Martinique","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2002/DTE/mtq_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15272,474,"MTQ","Martinique","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2003/Binary/mtq_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15273,474,"MTQ","Martinique","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2003/DTE/mtq_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15274,474,"MTQ","Martinique","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2004/Binary/mtq_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15275,474,"MTQ","Martinique","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2004/DTE/mtq_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15276,474,"MTQ","Martinique","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2005/Binary/mtq_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15277,474,"MTQ","Martinique","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2005/DTE/mtq_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15278,474,"MTQ","Martinique","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2006/Binary/mtq_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15279,474,"MTQ","Martinique","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2006/DTE/mtq_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15280,474,"MTQ","Martinique","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2007/Binary/mtq_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15281,474,"MTQ","Martinique","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2007/DTE/mtq_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15282,474,"MTQ","Martinique","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2008/Binary/mtq_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15283,474,"MTQ","Martinique","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2008/DTE/mtq_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15284,474,"MTQ","Martinique","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2009/Binary/mtq_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15285,474,"MTQ","Martinique","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2009/DTE/mtq_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15286,474,"MTQ","Martinique","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2010/Binary/mtq_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15287,474,"MTQ","Martinique","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2010/DTE/mtq_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15288,474,"MTQ","Martinique","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2011/Binary/mtq_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15289,474,"MTQ","Martinique","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2011/DTE/mtq_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15290,474,"MTQ","Martinique","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2013/Binary/mtq_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15291,474,"MTQ","Martinique","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2013/DTE/mtq_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15292,474,"MTQ","Martinique","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2015/DTE/mtq_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15293,474,"MTQ","Martinique","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2016/DTE/mtq_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15294,474,"MTQ","Martinique","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2017/DTE/mtq_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15295,474,"MTQ","Martinique","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2018/DTE/mtq_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15296,474,"MTQ","Martinique","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2019/DTE/mtq_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15297,474,"MTQ","Martinique","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MTQ/BSGM/2020/DTE/mtq_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15298,478,"MRT","Mauritania","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MRT/BSGM/2001/Binary/mrt_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15299,478,"MRT","Mauritania","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MRT/BSGM/2001/DTE/mrt_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15300,478,"MRT","Mauritania","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MRT/BSGM/2002/Binary/mrt_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15301,478,"MRT","Mauritania","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MRT/BSGM/2002/DTE/mrt_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15302,478,"MRT","Mauritania","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MRT/BSGM/2003/Binary/mrt_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15303,478,"MRT","Mauritania","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MRT/BSGM/2003/DTE/mrt_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15304,478,"MRT","Mauritania","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MRT/BSGM/2004/Binary/mrt_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15305,478,"MRT","Mauritania","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MRT/BSGM/2004/DTE/mrt_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15306,478,"MRT","Mauritania","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MRT/BSGM/2005/Binary/mrt_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15307,478,"MRT","Mauritania","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MRT/BSGM/2005/DTE/mrt_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15308,478,"MRT","Mauritania","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MRT/BSGM/2006/Binary/mrt_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15309,478,"MRT","Mauritania","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MRT/BSGM/2006/DTE/mrt_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15310,478,"MRT","Mauritania","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MRT/BSGM/2007/Binary/mrt_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15311,478,"MRT","Mauritania","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MRT/BSGM/2007/DTE/mrt_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15312,478,"MRT","Mauritania","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MRT/BSGM/2008/Binary/mrt_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15313,478,"MRT","Mauritania","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MRT/BSGM/2008/DTE/mrt_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15314,478,"MRT","Mauritania","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MRT/BSGM/2009/Binary/mrt_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15315,478,"MRT","Mauritania","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MRT/BSGM/2009/DTE/mrt_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15316,478,"MRT","Mauritania","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MRT/BSGM/2010/Binary/mrt_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15317,478,"MRT","Mauritania","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MRT/BSGM/2010/DTE/mrt_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15318,478,"MRT","Mauritania","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MRT/BSGM/2011/Binary/mrt_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15319,478,"MRT","Mauritania","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MRT/BSGM/2011/DTE/mrt_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15320,478,"MRT","Mauritania","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MRT/BSGM/2013/Binary/mrt_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15321,478,"MRT","Mauritania","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MRT/BSGM/2013/DTE/mrt_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15322,478,"MRT","Mauritania","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MRT/BSGM/2015/DTE/mrt_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15323,478,"MRT","Mauritania","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MRT/BSGM/2016/DTE/mrt_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15324,478,"MRT","Mauritania","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MRT/BSGM/2017/DTE/mrt_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15325,478,"MRT","Mauritania","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MRT/BSGM/2018/DTE/mrt_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15326,478,"MRT","Mauritania","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MRT/BSGM/2019/DTE/mrt_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15327,478,"MRT","Mauritania","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MRT/BSGM/2020/DTE/mrt_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15328,480,"MUS","Mauritius","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MUS/BSGM/2001/Binary/mus_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15329,480,"MUS","Mauritius","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MUS/BSGM/2001/DTE/mus_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15330,480,"MUS","Mauritius","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MUS/BSGM/2002/Binary/mus_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15331,480,"MUS","Mauritius","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MUS/BSGM/2002/DTE/mus_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15332,480,"MUS","Mauritius","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MUS/BSGM/2003/Binary/mus_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15333,480,"MUS","Mauritius","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MUS/BSGM/2003/DTE/mus_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15334,480,"MUS","Mauritius","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MUS/BSGM/2004/Binary/mus_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15335,480,"MUS","Mauritius","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MUS/BSGM/2004/DTE/mus_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15336,480,"MUS","Mauritius","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MUS/BSGM/2005/Binary/mus_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15337,480,"MUS","Mauritius","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MUS/BSGM/2005/DTE/mus_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15338,480,"MUS","Mauritius","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MUS/BSGM/2006/Binary/mus_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15339,480,"MUS","Mauritius","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MUS/BSGM/2006/DTE/mus_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15340,480,"MUS","Mauritius","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MUS/BSGM/2007/Binary/mus_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15341,480,"MUS","Mauritius","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MUS/BSGM/2007/DTE/mus_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15342,480,"MUS","Mauritius","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MUS/BSGM/2008/Binary/mus_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15343,480,"MUS","Mauritius","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MUS/BSGM/2008/DTE/mus_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15344,480,"MUS","Mauritius","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MUS/BSGM/2009/Binary/mus_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15345,480,"MUS","Mauritius","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MUS/BSGM/2009/DTE/mus_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15346,480,"MUS","Mauritius","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MUS/BSGM/2010/Binary/mus_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15347,480,"MUS","Mauritius","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MUS/BSGM/2010/DTE/mus_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15348,480,"MUS","Mauritius","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MUS/BSGM/2011/Binary/mus_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15349,480,"MUS","Mauritius","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MUS/BSGM/2011/DTE/mus_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15350,480,"MUS","Mauritius","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MUS/BSGM/2013/Binary/mus_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15351,480,"MUS","Mauritius","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MUS/BSGM/2013/DTE/mus_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15352,480,"MUS","Mauritius","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MUS/BSGM/2015/DTE/mus_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15353,480,"MUS","Mauritius","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MUS/BSGM/2016/DTE/mus_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15354,480,"MUS","Mauritius","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MUS/BSGM/2017/DTE/mus_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15355,480,"MUS","Mauritius","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MUS/BSGM/2018/DTE/mus_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15356,480,"MUS","Mauritius","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MUS/BSGM/2019/DTE/mus_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15357,480,"MUS","Mauritius","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MUS/BSGM/2020/DTE/mus_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15358,484,"MEX","Mexico","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MEX/BSGM/2001/Binary/mex_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15359,484,"MEX","Mexico","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MEX/BSGM/2001/DTE/mex_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15360,484,"MEX","Mexico","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MEX/BSGM/2002/Binary/mex_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15361,484,"MEX","Mexico","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MEX/BSGM/2002/DTE/mex_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15362,484,"MEX","Mexico","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MEX/BSGM/2003/Binary/mex_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15363,484,"MEX","Mexico","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MEX/BSGM/2003/DTE/mex_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15364,484,"MEX","Mexico","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MEX/BSGM/2004/Binary/mex_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15365,484,"MEX","Mexico","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MEX/BSGM/2004/DTE/mex_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15366,484,"MEX","Mexico","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MEX/BSGM/2005/Binary/mex_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15367,484,"MEX","Mexico","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MEX/BSGM/2005/DTE/mex_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15368,484,"MEX","Mexico","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MEX/BSGM/2006/Binary/mex_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15369,484,"MEX","Mexico","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MEX/BSGM/2006/DTE/mex_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15370,484,"MEX","Mexico","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MEX/BSGM/2007/Binary/mex_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15371,484,"MEX","Mexico","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MEX/BSGM/2007/DTE/mex_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15372,484,"MEX","Mexico","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MEX/BSGM/2008/Binary/mex_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15373,484,"MEX","Mexico","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MEX/BSGM/2008/DTE/mex_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15374,484,"MEX","Mexico","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MEX/BSGM/2009/Binary/mex_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15375,484,"MEX","Mexico","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MEX/BSGM/2009/DTE/mex_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15376,484,"MEX","Mexico","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MEX/BSGM/2010/Binary/mex_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15377,484,"MEX","Mexico","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MEX/BSGM/2010/DTE/mex_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15378,484,"MEX","Mexico","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MEX/BSGM/2011/Binary/mex_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15379,484,"MEX","Mexico","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MEX/BSGM/2011/DTE/mex_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15380,484,"MEX","Mexico","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MEX/BSGM/2013/Binary/mex_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15381,484,"MEX","Mexico","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MEX/BSGM/2013/DTE/mex_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15382,484,"MEX","Mexico","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MEX/BSGM/2015/DTE/mex_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15383,484,"MEX","Mexico","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MEX/BSGM/2016/DTE/mex_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15384,484,"MEX","Mexico","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MEX/BSGM/2017/DTE/mex_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15385,484,"MEX","Mexico","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MEX/BSGM/2018/DTE/mex_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15386,484,"MEX","Mexico","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MEX/BSGM/2019/DTE/mex_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15387,484,"MEX","Mexico","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MEX/BSGM/2020/DTE/mex_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15388,492,"MCO","Monaco","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MCO/BSGM/2001/Binary/mco_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15389,492,"MCO","Monaco","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MCO/BSGM/2001/DTE/mco_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15390,492,"MCO","Monaco","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MCO/BSGM/2002/Binary/mco_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15391,492,"MCO","Monaco","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MCO/BSGM/2002/DTE/mco_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15392,492,"MCO","Monaco","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MCO/BSGM/2003/Binary/mco_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15393,492,"MCO","Monaco","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MCO/BSGM/2003/DTE/mco_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15394,492,"MCO","Monaco","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MCO/BSGM/2004/Binary/mco_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15395,492,"MCO","Monaco","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MCO/BSGM/2004/DTE/mco_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15396,492,"MCO","Monaco","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MCO/BSGM/2005/Binary/mco_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15397,492,"MCO","Monaco","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MCO/BSGM/2005/DTE/mco_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15398,492,"MCO","Monaco","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MCO/BSGM/2006/Binary/mco_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15399,492,"MCO","Monaco","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MCO/BSGM/2006/DTE/mco_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15400,492,"MCO","Monaco","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MCO/BSGM/2007/Binary/mco_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15401,492,"MCO","Monaco","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MCO/BSGM/2007/DTE/mco_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15402,492,"MCO","Monaco","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MCO/BSGM/2008/Binary/mco_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15403,492,"MCO","Monaco","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MCO/BSGM/2008/DTE/mco_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15404,492,"MCO","Monaco","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MCO/BSGM/2009/Binary/mco_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15405,492,"MCO","Monaco","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MCO/BSGM/2009/DTE/mco_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15406,492,"MCO","Monaco","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MCO/BSGM/2010/Binary/mco_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15407,492,"MCO","Monaco","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MCO/BSGM/2010/DTE/mco_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15408,492,"MCO","Monaco","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MCO/BSGM/2011/Binary/mco_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15409,492,"MCO","Monaco","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MCO/BSGM/2011/DTE/mco_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15410,492,"MCO","Monaco","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MCO/BSGM/2013/Binary/mco_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15411,492,"MCO","Monaco","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MCO/BSGM/2013/DTE/mco_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15412,492,"MCO","Monaco","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MCO/BSGM/2015/DTE/mco_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15413,492,"MCO","Monaco","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MCO/BSGM/2016/DTE/mco_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15414,492,"MCO","Monaco","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MCO/BSGM/2017/DTE/mco_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15415,492,"MCO","Monaco","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MCO/BSGM/2018/DTE/mco_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15416,492,"MCO","Monaco","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MCO/BSGM/2019/DTE/mco_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15417,492,"MCO","Monaco","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MCO/BSGM/2020/DTE/mco_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15418,496,"MNG","Mongolia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MNG/BSGM/2001/Binary/mng_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15419,496,"MNG","Mongolia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MNG/BSGM/2001/DTE/mng_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15420,496,"MNG","Mongolia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MNG/BSGM/2002/Binary/mng_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15421,496,"MNG","Mongolia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MNG/BSGM/2002/DTE/mng_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15422,496,"MNG","Mongolia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MNG/BSGM/2003/Binary/mng_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15423,496,"MNG","Mongolia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MNG/BSGM/2003/DTE/mng_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15424,496,"MNG","Mongolia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MNG/BSGM/2004/Binary/mng_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15425,496,"MNG","Mongolia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MNG/BSGM/2004/DTE/mng_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15426,496,"MNG","Mongolia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MNG/BSGM/2005/Binary/mng_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15427,496,"MNG","Mongolia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MNG/BSGM/2005/DTE/mng_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15428,496,"MNG","Mongolia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MNG/BSGM/2006/Binary/mng_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15429,496,"MNG","Mongolia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MNG/BSGM/2006/DTE/mng_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15430,496,"MNG","Mongolia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MNG/BSGM/2007/Binary/mng_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15431,496,"MNG","Mongolia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MNG/BSGM/2007/DTE/mng_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15432,496,"MNG","Mongolia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MNG/BSGM/2008/Binary/mng_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15433,496,"MNG","Mongolia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MNG/BSGM/2008/DTE/mng_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15434,496,"MNG","Mongolia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MNG/BSGM/2009/Binary/mng_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15435,496,"MNG","Mongolia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MNG/BSGM/2009/DTE/mng_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15436,496,"MNG","Mongolia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MNG/BSGM/2010/Binary/mng_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15437,496,"MNG","Mongolia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MNG/BSGM/2010/DTE/mng_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15438,496,"MNG","Mongolia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MNG/BSGM/2011/Binary/mng_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15439,496,"MNG","Mongolia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MNG/BSGM/2011/DTE/mng_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15440,496,"MNG","Mongolia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MNG/BSGM/2013/Binary/mng_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15441,496,"MNG","Mongolia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MNG/BSGM/2013/DTE/mng_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15442,496,"MNG","Mongolia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MNG/BSGM/2015/DTE/mng_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15443,496,"MNG","Mongolia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MNG/BSGM/2016/DTE/mng_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15444,496,"MNG","Mongolia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MNG/BSGM/2017/DTE/mng_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15445,496,"MNG","Mongolia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MNG/BSGM/2018/DTE/mng_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15446,496,"MNG","Mongolia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MNG/BSGM/2019/DTE/mng_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15447,496,"MNG","Mongolia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MNG/BSGM/2020/DTE/mng_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15448,498,"MDA","Moldova","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MDA/BSGM/2001/Binary/mda_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15449,498,"MDA","Moldova","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MDA/BSGM/2001/DTE/mda_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15450,498,"MDA","Moldova","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MDA/BSGM/2002/Binary/mda_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15451,498,"MDA","Moldova","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MDA/BSGM/2002/DTE/mda_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15452,498,"MDA","Moldova","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MDA/BSGM/2003/Binary/mda_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15453,498,"MDA","Moldova","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MDA/BSGM/2003/DTE/mda_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15454,498,"MDA","Moldova","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MDA/BSGM/2004/Binary/mda_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15455,498,"MDA","Moldova","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MDA/BSGM/2004/DTE/mda_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15456,498,"MDA","Moldova","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MDA/BSGM/2005/Binary/mda_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15457,498,"MDA","Moldova","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MDA/BSGM/2005/DTE/mda_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15458,498,"MDA","Moldova","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MDA/BSGM/2006/Binary/mda_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15459,498,"MDA","Moldova","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MDA/BSGM/2006/DTE/mda_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15460,498,"MDA","Moldova","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MDA/BSGM/2007/Binary/mda_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15461,498,"MDA","Moldova","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MDA/BSGM/2007/DTE/mda_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15462,498,"MDA","Moldova","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MDA/BSGM/2008/Binary/mda_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15463,498,"MDA","Moldova","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MDA/BSGM/2008/DTE/mda_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15464,498,"MDA","Moldova","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MDA/BSGM/2009/Binary/mda_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15465,498,"MDA","Moldova","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MDA/BSGM/2009/DTE/mda_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15466,498,"MDA","Moldova","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MDA/BSGM/2010/Binary/mda_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15467,498,"MDA","Moldova","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MDA/BSGM/2010/DTE/mda_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15468,498,"MDA","Moldova","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MDA/BSGM/2011/Binary/mda_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15469,498,"MDA","Moldova","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MDA/BSGM/2011/DTE/mda_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15470,498,"MDA","Moldova","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MDA/BSGM/2013/Binary/mda_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15471,498,"MDA","Moldova","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MDA/BSGM/2013/DTE/mda_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15472,498,"MDA","Moldova","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MDA/BSGM/2015/DTE/mda_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15473,498,"MDA","Moldova","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MDA/BSGM/2016/DTE/mda_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15474,498,"MDA","Moldova","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MDA/BSGM/2017/DTE/mda_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15475,498,"MDA","Moldova","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MDA/BSGM/2018/DTE/mda_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15476,498,"MDA","Moldova","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MDA/BSGM/2019/DTE/mda_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15477,498,"MDA","Moldova","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MDA/BSGM/2020/DTE/mda_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15478,499,"MNE","Montenegro","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MNE/BSGM/2001/Binary/mne_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15479,499,"MNE","Montenegro","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MNE/BSGM/2001/DTE/mne_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15480,499,"MNE","Montenegro","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MNE/BSGM/2002/Binary/mne_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15481,499,"MNE","Montenegro","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MNE/BSGM/2002/DTE/mne_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15482,499,"MNE","Montenegro","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MNE/BSGM/2003/Binary/mne_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15483,499,"MNE","Montenegro","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MNE/BSGM/2003/DTE/mne_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15484,499,"MNE","Montenegro","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MNE/BSGM/2004/Binary/mne_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15485,499,"MNE","Montenegro","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MNE/BSGM/2004/DTE/mne_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15486,499,"MNE","Montenegro","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MNE/BSGM/2005/Binary/mne_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15487,499,"MNE","Montenegro","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MNE/BSGM/2005/DTE/mne_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15488,499,"MNE","Montenegro","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MNE/BSGM/2006/Binary/mne_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15489,499,"MNE","Montenegro","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MNE/BSGM/2006/DTE/mne_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15490,499,"MNE","Montenegro","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MNE/BSGM/2007/Binary/mne_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15491,499,"MNE","Montenegro","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MNE/BSGM/2007/DTE/mne_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15492,499,"MNE","Montenegro","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MNE/BSGM/2008/Binary/mne_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15493,499,"MNE","Montenegro","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MNE/BSGM/2008/DTE/mne_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15494,499,"MNE","Montenegro","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MNE/BSGM/2009/Binary/mne_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15495,499,"MNE","Montenegro","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MNE/BSGM/2009/DTE/mne_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15496,499,"MNE","Montenegro","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MNE/BSGM/2010/Binary/mne_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15497,499,"MNE","Montenegro","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MNE/BSGM/2010/DTE/mne_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15498,499,"MNE","Montenegro","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MNE/BSGM/2011/Binary/mne_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15499,499,"MNE","Montenegro","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MNE/BSGM/2011/DTE/mne_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15500,499,"MNE","Montenegro","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MNE/BSGM/2013/Binary/mne_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15501,499,"MNE","Montenegro","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MNE/BSGM/2013/DTE/mne_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15502,499,"MNE","Montenegro","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MNE/BSGM/2015/DTE/mne_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15503,499,"MNE","Montenegro","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MNE/BSGM/2016/DTE/mne_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15504,499,"MNE","Montenegro","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MNE/BSGM/2017/DTE/mne_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15505,499,"MNE","Montenegro","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MNE/BSGM/2018/DTE/mne_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15506,499,"MNE","Montenegro","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MNE/BSGM/2019/DTE/mne_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15507,499,"MNE","Montenegro","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MNE/BSGM/2020/DTE/mne_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15508,500,"MSR","Montserrat","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MSR/BSGM/2001/Binary/msr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15509,500,"MSR","Montserrat","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MSR/BSGM/2001/DTE/msr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15510,500,"MSR","Montserrat","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MSR/BSGM/2002/Binary/msr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15511,500,"MSR","Montserrat","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MSR/BSGM/2002/DTE/msr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15512,500,"MSR","Montserrat","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MSR/BSGM/2003/Binary/msr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15513,500,"MSR","Montserrat","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MSR/BSGM/2003/DTE/msr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15514,500,"MSR","Montserrat","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MSR/BSGM/2004/Binary/msr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15515,500,"MSR","Montserrat","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MSR/BSGM/2004/DTE/msr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15516,500,"MSR","Montserrat","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MSR/BSGM/2005/Binary/msr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15517,500,"MSR","Montserrat","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MSR/BSGM/2005/DTE/msr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15518,500,"MSR","Montserrat","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MSR/BSGM/2006/Binary/msr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15519,500,"MSR","Montserrat","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MSR/BSGM/2006/DTE/msr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15520,500,"MSR","Montserrat","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MSR/BSGM/2007/Binary/msr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15521,500,"MSR","Montserrat","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MSR/BSGM/2007/DTE/msr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15522,500,"MSR","Montserrat","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MSR/BSGM/2008/Binary/msr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15523,500,"MSR","Montserrat","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MSR/BSGM/2008/DTE/msr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15524,500,"MSR","Montserrat","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MSR/BSGM/2009/Binary/msr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15525,500,"MSR","Montserrat","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MSR/BSGM/2009/DTE/msr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15526,500,"MSR","Montserrat","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MSR/BSGM/2010/Binary/msr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15527,500,"MSR","Montserrat","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MSR/BSGM/2010/DTE/msr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15528,500,"MSR","Montserrat","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MSR/BSGM/2011/Binary/msr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15529,500,"MSR","Montserrat","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MSR/BSGM/2011/DTE/msr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15530,500,"MSR","Montserrat","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MSR/BSGM/2013/Binary/msr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15531,500,"MSR","Montserrat","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MSR/BSGM/2013/DTE/msr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15532,500,"MSR","Montserrat","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MSR/BSGM/2015/DTE/msr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15533,500,"MSR","Montserrat","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MSR/BSGM/2016/DTE/msr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15534,500,"MSR","Montserrat","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MSR/BSGM/2017/DTE/msr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15535,500,"MSR","Montserrat","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MSR/BSGM/2018/DTE/msr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15536,500,"MSR","Montserrat","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MSR/BSGM/2019/DTE/msr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15537,500,"MSR","Montserrat","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MSR/BSGM/2020/DTE/msr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15538,504,"MAR","Morocco","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MAR/BSGM/2001/Binary/mar_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15539,504,"MAR","Morocco","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MAR/BSGM/2001/DTE/mar_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15540,504,"MAR","Morocco","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MAR/BSGM/2002/Binary/mar_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15541,504,"MAR","Morocco","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MAR/BSGM/2002/DTE/mar_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15542,504,"MAR","Morocco","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MAR/BSGM/2003/Binary/mar_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15543,504,"MAR","Morocco","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MAR/BSGM/2003/DTE/mar_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15544,504,"MAR","Morocco","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MAR/BSGM/2004/Binary/mar_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15545,504,"MAR","Morocco","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MAR/BSGM/2004/DTE/mar_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15546,504,"MAR","Morocco","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MAR/BSGM/2005/Binary/mar_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15547,504,"MAR","Morocco","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MAR/BSGM/2005/DTE/mar_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15548,504,"MAR","Morocco","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MAR/BSGM/2006/Binary/mar_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15549,504,"MAR","Morocco","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MAR/BSGM/2006/DTE/mar_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15550,504,"MAR","Morocco","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MAR/BSGM/2007/Binary/mar_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15551,504,"MAR","Morocco","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MAR/BSGM/2007/DTE/mar_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15552,504,"MAR","Morocco","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MAR/BSGM/2008/Binary/mar_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15553,504,"MAR","Morocco","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MAR/BSGM/2008/DTE/mar_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15554,504,"MAR","Morocco","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MAR/BSGM/2009/Binary/mar_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15555,504,"MAR","Morocco","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MAR/BSGM/2009/DTE/mar_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15556,504,"MAR","Morocco","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MAR/BSGM/2010/Binary/mar_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15557,504,"MAR","Morocco","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MAR/BSGM/2010/DTE/mar_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15558,504,"MAR","Morocco","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MAR/BSGM/2011/Binary/mar_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15559,504,"MAR","Morocco","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MAR/BSGM/2011/DTE/mar_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15560,504,"MAR","Morocco","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MAR/BSGM/2013/Binary/mar_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15561,504,"MAR","Morocco","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MAR/BSGM/2013/DTE/mar_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15562,504,"MAR","Morocco","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MAR/BSGM/2015/DTE/mar_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15563,504,"MAR","Morocco","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MAR/BSGM/2016/DTE/mar_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15564,504,"MAR","Morocco","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MAR/BSGM/2017/DTE/mar_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15565,504,"MAR","Morocco","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MAR/BSGM/2018/DTE/mar_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15566,504,"MAR","Morocco","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MAR/BSGM/2019/DTE/mar_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15567,504,"MAR","Morocco","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MAR/BSGM/2020/DTE/mar_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15568,508,"MOZ","Mozambique","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2001/Binary/moz_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15569,508,"MOZ","Mozambique","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2001/DTE/moz_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15570,508,"MOZ","Mozambique","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2002/Binary/moz_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15571,508,"MOZ","Mozambique","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2002/DTE/moz_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15572,508,"MOZ","Mozambique","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2003/Binary/moz_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15573,508,"MOZ","Mozambique","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2003/DTE/moz_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15574,508,"MOZ","Mozambique","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2004/Binary/moz_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15575,508,"MOZ","Mozambique","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2004/DTE/moz_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15576,508,"MOZ","Mozambique","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2005/Binary/moz_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15577,508,"MOZ","Mozambique","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2005/DTE/moz_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15578,508,"MOZ","Mozambique","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2006/Binary/moz_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15579,508,"MOZ","Mozambique","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2006/DTE/moz_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15580,508,"MOZ","Mozambique","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2007/Binary/moz_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15581,508,"MOZ","Mozambique","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2007/DTE/moz_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15582,508,"MOZ","Mozambique","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2008/Binary/moz_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15583,508,"MOZ","Mozambique","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2008/DTE/moz_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15584,508,"MOZ","Mozambique","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2009/Binary/moz_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15585,508,"MOZ","Mozambique","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2009/DTE/moz_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15586,508,"MOZ","Mozambique","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2010/Binary/moz_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15587,508,"MOZ","Mozambique","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2010/DTE/moz_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15588,508,"MOZ","Mozambique","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2011/Binary/moz_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15589,508,"MOZ","Mozambique","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2011/DTE/moz_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15590,508,"MOZ","Mozambique","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2013/Binary/moz_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15591,508,"MOZ","Mozambique","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2013/DTE/moz_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15592,508,"MOZ","Mozambique","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2015/DTE/moz_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15593,508,"MOZ","Mozambique","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2016/DTE/moz_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15594,508,"MOZ","Mozambique","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2017/DTE/moz_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15595,508,"MOZ","Mozambique","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2018/DTE/moz_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15596,508,"MOZ","Mozambique","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2019/DTE/moz_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15597,508,"MOZ","Mozambique","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MOZ/BSGM/2020/DTE/moz_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15598,512,"OMN","Oman","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/OMN/BSGM/2001/Binary/omn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15599,512,"OMN","Oman","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/OMN/BSGM/2001/DTE/omn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15600,512,"OMN","Oman","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/OMN/BSGM/2002/Binary/omn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15601,512,"OMN","Oman","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/OMN/BSGM/2002/DTE/omn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15602,512,"OMN","Oman","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/OMN/BSGM/2003/Binary/omn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15603,512,"OMN","Oman","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/OMN/BSGM/2003/DTE/omn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15604,512,"OMN","Oman","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/OMN/BSGM/2004/Binary/omn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15605,512,"OMN","Oman","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/OMN/BSGM/2004/DTE/omn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15606,512,"OMN","Oman","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/OMN/BSGM/2005/Binary/omn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15607,512,"OMN","Oman","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/OMN/BSGM/2005/DTE/omn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15608,512,"OMN","Oman","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/OMN/BSGM/2006/Binary/omn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15609,512,"OMN","Oman","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/OMN/BSGM/2006/DTE/omn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15610,512,"OMN","Oman","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/OMN/BSGM/2007/Binary/omn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15611,512,"OMN","Oman","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/OMN/BSGM/2007/DTE/omn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15612,512,"OMN","Oman","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/OMN/BSGM/2008/Binary/omn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15613,512,"OMN","Oman","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/OMN/BSGM/2008/DTE/omn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15614,512,"OMN","Oman","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/OMN/BSGM/2009/Binary/omn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15615,512,"OMN","Oman","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/OMN/BSGM/2009/DTE/omn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15616,512,"OMN","Oman","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/OMN/BSGM/2010/Binary/omn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15617,512,"OMN","Oman","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/OMN/BSGM/2010/DTE/omn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15618,512,"OMN","Oman","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/OMN/BSGM/2011/Binary/omn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15619,512,"OMN","Oman","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/OMN/BSGM/2011/DTE/omn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15620,512,"OMN","Oman","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/OMN/BSGM/2013/Binary/omn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15621,512,"OMN","Oman","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/OMN/BSGM/2013/DTE/omn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15622,512,"OMN","Oman","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/OMN/BSGM/2015/DTE/omn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15623,512,"OMN","Oman","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/OMN/BSGM/2016/DTE/omn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15624,512,"OMN","Oman","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/OMN/BSGM/2017/DTE/omn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15625,512,"OMN","Oman","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/OMN/BSGM/2018/DTE/omn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15626,512,"OMN","Oman","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/OMN/BSGM/2019/DTE/omn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15627,512,"OMN","Oman","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/OMN/BSGM/2020/DTE/omn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15628,516,"NAM","Namibia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NAM/BSGM/2001/Binary/nam_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15629,516,"NAM","Namibia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NAM/BSGM/2001/DTE/nam_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15630,516,"NAM","Namibia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NAM/BSGM/2002/Binary/nam_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15631,516,"NAM","Namibia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NAM/BSGM/2002/DTE/nam_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15632,516,"NAM","Namibia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NAM/BSGM/2003/Binary/nam_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15633,516,"NAM","Namibia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NAM/BSGM/2003/DTE/nam_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15634,516,"NAM","Namibia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NAM/BSGM/2004/Binary/nam_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15635,516,"NAM","Namibia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NAM/BSGM/2004/DTE/nam_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15636,516,"NAM","Namibia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NAM/BSGM/2005/Binary/nam_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15637,516,"NAM","Namibia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NAM/BSGM/2005/DTE/nam_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15638,516,"NAM","Namibia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NAM/BSGM/2006/Binary/nam_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15639,516,"NAM","Namibia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NAM/BSGM/2006/DTE/nam_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15640,516,"NAM","Namibia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NAM/BSGM/2007/Binary/nam_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15641,516,"NAM","Namibia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NAM/BSGM/2007/DTE/nam_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15642,516,"NAM","Namibia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NAM/BSGM/2008/Binary/nam_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15643,516,"NAM","Namibia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NAM/BSGM/2008/DTE/nam_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15644,516,"NAM","Namibia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NAM/BSGM/2009/Binary/nam_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15645,516,"NAM","Namibia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NAM/BSGM/2009/DTE/nam_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15646,516,"NAM","Namibia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NAM/BSGM/2010/Binary/nam_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15647,516,"NAM","Namibia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NAM/BSGM/2010/DTE/nam_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15648,516,"NAM","Namibia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NAM/BSGM/2011/Binary/nam_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15649,516,"NAM","Namibia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NAM/BSGM/2011/DTE/nam_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15650,516,"NAM","Namibia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NAM/BSGM/2013/Binary/nam_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15651,516,"NAM","Namibia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NAM/BSGM/2013/DTE/nam_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15652,516,"NAM","Namibia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NAM/BSGM/2015/DTE/nam_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15653,516,"NAM","Namibia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NAM/BSGM/2016/DTE/nam_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15654,516,"NAM","Namibia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NAM/BSGM/2017/DTE/nam_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15655,516,"NAM","Namibia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NAM/BSGM/2018/DTE/nam_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15656,516,"NAM","Namibia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NAM/BSGM/2019/DTE/nam_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15657,516,"NAM","Namibia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NAM/BSGM/2020/DTE/nam_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15658,520,"NRU","Nauru","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NRU/BSGM/2001/Binary/nru_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15659,520,"NRU","Nauru","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NRU/BSGM/2001/DTE/nru_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15660,520,"NRU","Nauru","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NRU/BSGM/2002/Binary/nru_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15661,520,"NRU","Nauru","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NRU/BSGM/2002/DTE/nru_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15662,520,"NRU","Nauru","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NRU/BSGM/2003/Binary/nru_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15663,520,"NRU","Nauru","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NRU/BSGM/2003/DTE/nru_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15664,520,"NRU","Nauru","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NRU/BSGM/2004/Binary/nru_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15665,520,"NRU","Nauru","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NRU/BSGM/2004/DTE/nru_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15666,520,"NRU","Nauru","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NRU/BSGM/2005/Binary/nru_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15667,520,"NRU","Nauru","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NRU/BSGM/2005/DTE/nru_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15668,520,"NRU","Nauru","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NRU/BSGM/2006/Binary/nru_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15669,520,"NRU","Nauru","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NRU/BSGM/2006/DTE/nru_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15670,520,"NRU","Nauru","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NRU/BSGM/2007/Binary/nru_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15671,520,"NRU","Nauru","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NRU/BSGM/2007/DTE/nru_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15672,520,"NRU","Nauru","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NRU/BSGM/2008/Binary/nru_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15673,520,"NRU","Nauru","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NRU/BSGM/2008/DTE/nru_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15674,520,"NRU","Nauru","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NRU/BSGM/2009/Binary/nru_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15675,520,"NRU","Nauru","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NRU/BSGM/2009/DTE/nru_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15676,520,"NRU","Nauru","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NRU/BSGM/2010/Binary/nru_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15677,520,"NRU","Nauru","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NRU/BSGM/2010/DTE/nru_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15678,520,"NRU","Nauru","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NRU/BSGM/2011/Binary/nru_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15679,520,"NRU","Nauru","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NRU/BSGM/2011/DTE/nru_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15680,520,"NRU","Nauru","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NRU/BSGM/2013/Binary/nru_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15681,520,"NRU","Nauru","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NRU/BSGM/2013/DTE/nru_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15682,520,"NRU","Nauru","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NRU/BSGM/2015/DTE/nru_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15683,520,"NRU","Nauru","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NRU/BSGM/2016/DTE/nru_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15684,520,"NRU","Nauru","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NRU/BSGM/2017/DTE/nru_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15685,520,"NRU","Nauru","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NRU/BSGM/2018/DTE/nru_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15686,520,"NRU","Nauru","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NRU/BSGM/2019/DTE/nru_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15687,520,"NRU","Nauru","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NRU/BSGM/2020/DTE/nru_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15688,524,"NPL","Nepal","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NPL/BSGM/2001/Binary/npl_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15689,524,"NPL","Nepal","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NPL/BSGM/2001/DTE/npl_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15690,524,"NPL","Nepal","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NPL/BSGM/2002/Binary/npl_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15691,524,"NPL","Nepal","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NPL/BSGM/2002/DTE/npl_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15692,524,"NPL","Nepal","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NPL/BSGM/2003/Binary/npl_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15693,524,"NPL","Nepal","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NPL/BSGM/2003/DTE/npl_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15694,524,"NPL","Nepal","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NPL/BSGM/2004/Binary/npl_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15695,524,"NPL","Nepal","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NPL/BSGM/2004/DTE/npl_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15696,524,"NPL","Nepal","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NPL/BSGM/2005/Binary/npl_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15697,524,"NPL","Nepal","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NPL/BSGM/2005/DTE/npl_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15698,524,"NPL","Nepal","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NPL/BSGM/2006/Binary/npl_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15699,524,"NPL","Nepal","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NPL/BSGM/2006/DTE/npl_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15700,524,"NPL","Nepal","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NPL/BSGM/2007/Binary/npl_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15701,524,"NPL","Nepal","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NPL/BSGM/2007/DTE/npl_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15702,524,"NPL","Nepal","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NPL/BSGM/2008/Binary/npl_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15703,524,"NPL","Nepal","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NPL/BSGM/2008/DTE/npl_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15704,524,"NPL","Nepal","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NPL/BSGM/2009/Binary/npl_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15705,524,"NPL","Nepal","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NPL/BSGM/2009/DTE/npl_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15706,524,"NPL","Nepal","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NPL/BSGM/2010/Binary/npl_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15707,524,"NPL","Nepal","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NPL/BSGM/2010/DTE/npl_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15708,524,"NPL","Nepal","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NPL/BSGM/2011/Binary/npl_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15709,524,"NPL","Nepal","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NPL/BSGM/2011/DTE/npl_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15710,524,"NPL","Nepal","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NPL/BSGM/2013/Binary/npl_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15711,524,"NPL","Nepal","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NPL/BSGM/2013/DTE/npl_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15712,524,"NPL","Nepal","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NPL/BSGM/2015/DTE/npl_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15713,524,"NPL","Nepal","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NPL/BSGM/2016/DTE/npl_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15714,524,"NPL","Nepal","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NPL/BSGM/2017/DTE/npl_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15715,524,"NPL","Nepal","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NPL/BSGM/2018/DTE/npl_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15716,524,"NPL","Nepal","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NPL/BSGM/2019/DTE/npl_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15717,524,"NPL","Nepal","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NPL/BSGM/2020/DTE/npl_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15718,528,"NLD","Netherlands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NLD/BSGM/2001/Binary/nld_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15719,528,"NLD","Netherlands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NLD/BSGM/2001/DTE/nld_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15720,528,"NLD","Netherlands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NLD/BSGM/2002/Binary/nld_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15721,528,"NLD","Netherlands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NLD/BSGM/2002/DTE/nld_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15722,528,"NLD","Netherlands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NLD/BSGM/2003/Binary/nld_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15723,528,"NLD","Netherlands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NLD/BSGM/2003/DTE/nld_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15724,528,"NLD","Netherlands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NLD/BSGM/2004/Binary/nld_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15725,528,"NLD","Netherlands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NLD/BSGM/2004/DTE/nld_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15726,528,"NLD","Netherlands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NLD/BSGM/2005/Binary/nld_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15727,528,"NLD","Netherlands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NLD/BSGM/2005/DTE/nld_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15728,528,"NLD","Netherlands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NLD/BSGM/2006/Binary/nld_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15729,528,"NLD","Netherlands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NLD/BSGM/2006/DTE/nld_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15730,528,"NLD","Netherlands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NLD/BSGM/2007/Binary/nld_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15731,528,"NLD","Netherlands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NLD/BSGM/2007/DTE/nld_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15732,528,"NLD","Netherlands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NLD/BSGM/2008/Binary/nld_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15733,528,"NLD","Netherlands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NLD/BSGM/2008/DTE/nld_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15734,528,"NLD","Netherlands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NLD/BSGM/2009/Binary/nld_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15735,528,"NLD","Netherlands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NLD/BSGM/2009/DTE/nld_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15736,528,"NLD","Netherlands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NLD/BSGM/2010/Binary/nld_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15737,528,"NLD","Netherlands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NLD/BSGM/2010/DTE/nld_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15738,528,"NLD","Netherlands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NLD/BSGM/2011/Binary/nld_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15739,528,"NLD","Netherlands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NLD/BSGM/2011/DTE/nld_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15740,528,"NLD","Netherlands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NLD/BSGM/2013/Binary/nld_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15741,528,"NLD","Netherlands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NLD/BSGM/2013/DTE/nld_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15742,528,"NLD","Netherlands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NLD/BSGM/2015/DTE/nld_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15743,528,"NLD","Netherlands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NLD/BSGM/2016/DTE/nld_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15744,528,"NLD","Netherlands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NLD/BSGM/2017/DTE/nld_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15745,528,"NLD","Netherlands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NLD/BSGM/2018/DTE/nld_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15746,528,"NLD","Netherlands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NLD/BSGM/2019/DTE/nld_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15747,528,"NLD","Netherlands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NLD/BSGM/2020/DTE/nld_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15748,531,"CUW","Curacao","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CUW/BSGM/2001/Binary/cuw_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15749,531,"CUW","Curacao","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CUW/BSGM/2001/DTE/cuw_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15750,531,"CUW","Curacao","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CUW/BSGM/2002/Binary/cuw_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15751,531,"CUW","Curacao","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CUW/BSGM/2002/DTE/cuw_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15752,531,"CUW","Curacao","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CUW/BSGM/2003/Binary/cuw_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15753,531,"CUW","Curacao","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CUW/BSGM/2003/DTE/cuw_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15754,531,"CUW","Curacao","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CUW/BSGM/2004/Binary/cuw_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15755,531,"CUW","Curacao","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CUW/BSGM/2004/DTE/cuw_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15756,531,"CUW","Curacao","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CUW/BSGM/2005/Binary/cuw_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15757,531,"CUW","Curacao","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CUW/BSGM/2005/DTE/cuw_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15758,531,"CUW","Curacao","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CUW/BSGM/2006/Binary/cuw_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15759,531,"CUW","Curacao","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CUW/BSGM/2006/DTE/cuw_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15760,531,"CUW","Curacao","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CUW/BSGM/2007/Binary/cuw_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15761,531,"CUW","Curacao","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CUW/BSGM/2007/DTE/cuw_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15762,531,"CUW","Curacao","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CUW/BSGM/2008/Binary/cuw_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15763,531,"CUW","Curacao","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CUW/BSGM/2008/DTE/cuw_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15764,531,"CUW","Curacao","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CUW/BSGM/2009/Binary/cuw_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15765,531,"CUW","Curacao","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CUW/BSGM/2009/DTE/cuw_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15766,531,"CUW","Curacao","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CUW/BSGM/2010/Binary/cuw_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15767,531,"CUW","Curacao","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CUW/BSGM/2010/DTE/cuw_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15768,531,"CUW","Curacao","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CUW/BSGM/2011/Binary/cuw_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15769,531,"CUW","Curacao","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CUW/BSGM/2011/DTE/cuw_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15770,531,"CUW","Curacao","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CUW/BSGM/2013/Binary/cuw_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15771,531,"CUW","Curacao","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CUW/BSGM/2013/DTE/cuw_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15772,531,"CUW","Curacao","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CUW/BSGM/2015/DTE/cuw_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15773,531,"CUW","Curacao","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CUW/BSGM/2016/DTE/cuw_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15774,531,"CUW","Curacao","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CUW/BSGM/2017/DTE/cuw_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15775,531,"CUW","Curacao","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CUW/BSGM/2018/DTE/cuw_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15776,531,"CUW","Curacao","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CUW/BSGM/2019/DTE/cuw_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15777,531,"CUW","Curacao","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CUW/BSGM/2020/DTE/cuw_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15778,533,"ABW","Aruba","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ABW/BSGM/2001/Binary/abw_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15779,533,"ABW","Aruba","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ABW/BSGM/2001/DTE/abw_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15780,533,"ABW","Aruba","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ABW/BSGM/2002/Binary/abw_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15781,533,"ABW","Aruba","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ABW/BSGM/2002/DTE/abw_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15782,533,"ABW","Aruba","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ABW/BSGM/2003/Binary/abw_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15783,533,"ABW","Aruba","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ABW/BSGM/2003/DTE/abw_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15784,533,"ABW","Aruba","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ABW/BSGM/2004/Binary/abw_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15785,533,"ABW","Aruba","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ABW/BSGM/2004/DTE/abw_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15786,533,"ABW","Aruba","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ABW/BSGM/2005/Binary/abw_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15787,533,"ABW","Aruba","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ABW/BSGM/2005/DTE/abw_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15788,533,"ABW","Aruba","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ABW/BSGM/2006/Binary/abw_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15789,533,"ABW","Aruba","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ABW/BSGM/2006/DTE/abw_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15790,533,"ABW","Aruba","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ABW/BSGM/2007/Binary/abw_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15791,533,"ABW","Aruba","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ABW/BSGM/2007/DTE/abw_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15792,533,"ABW","Aruba","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ABW/BSGM/2008/Binary/abw_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15793,533,"ABW","Aruba","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ABW/BSGM/2008/DTE/abw_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15794,533,"ABW","Aruba","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ABW/BSGM/2009/Binary/abw_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15795,533,"ABW","Aruba","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ABW/BSGM/2009/DTE/abw_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15796,533,"ABW","Aruba","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ABW/BSGM/2010/Binary/abw_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15797,533,"ABW","Aruba","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ABW/BSGM/2010/DTE/abw_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15798,533,"ABW","Aruba","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ABW/BSGM/2011/Binary/abw_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15799,533,"ABW","Aruba","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ABW/BSGM/2011/DTE/abw_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15800,533,"ABW","Aruba","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ABW/BSGM/2013/Binary/abw_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15801,533,"ABW","Aruba","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ABW/BSGM/2013/DTE/abw_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15802,533,"ABW","Aruba","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ABW/BSGM/2015/DTE/abw_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15803,533,"ABW","Aruba","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ABW/BSGM/2016/DTE/abw_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15804,533,"ABW","Aruba","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ABW/BSGM/2017/DTE/abw_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15805,533,"ABW","Aruba","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ABW/BSGM/2018/DTE/abw_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15806,533,"ABW","Aruba","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ABW/BSGM/2019/DTE/abw_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15807,533,"ABW","Aruba","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ABW/BSGM/2020/DTE/abw_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15808,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SXM/BSGM/2001/Binary/sxm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15809,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SXM/BSGM/2001/DTE/sxm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15810,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SXM/BSGM/2002/Binary/sxm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15811,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SXM/BSGM/2002/DTE/sxm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15812,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SXM/BSGM/2003/Binary/sxm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15813,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SXM/BSGM/2003/DTE/sxm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15814,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SXM/BSGM/2004/Binary/sxm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15815,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SXM/BSGM/2004/DTE/sxm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15816,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SXM/BSGM/2005/Binary/sxm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15817,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SXM/BSGM/2005/DTE/sxm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15818,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SXM/BSGM/2006/Binary/sxm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15819,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SXM/BSGM/2006/DTE/sxm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15820,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SXM/BSGM/2007/Binary/sxm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15821,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SXM/BSGM/2007/DTE/sxm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15822,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SXM/BSGM/2008/Binary/sxm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15823,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SXM/BSGM/2008/DTE/sxm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15824,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SXM/BSGM/2009/Binary/sxm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15825,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SXM/BSGM/2009/DTE/sxm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15826,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SXM/BSGM/2010/Binary/sxm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15827,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SXM/BSGM/2010/DTE/sxm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15828,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SXM/BSGM/2011/Binary/sxm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15829,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SXM/BSGM/2011/DTE/sxm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15830,534,"SXM","Sint Maarten (Dutch part)","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SXM/BSGM/2013/Binary/sxm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15831,534,"SXM","Sint Maarten (Dutch part)","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SXM/BSGM/2013/DTE/sxm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15832,534,"SXM","Sint Maarten (Dutch part)","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SXM/BSGM/2015/DTE/sxm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15833,534,"SXM","Sint Maarten (Dutch part)","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SXM/BSGM/2016/DTE/sxm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15834,534,"SXM","Sint Maarten (Dutch part)","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SXM/BSGM/2017/DTE/sxm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15835,534,"SXM","Sint Maarten (Dutch part)","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SXM/BSGM/2018/DTE/sxm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15836,534,"SXM","Sint Maarten (Dutch part)","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SXM/BSGM/2019/DTE/sxm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15837,534,"SXM","Sint Maarten (Dutch part)","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SXM/BSGM/2020/DTE/sxm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15838,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BES/BSGM/2001/Binary/bes_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15839,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BES/BSGM/2001/DTE/bes_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15840,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BES/BSGM/2002/Binary/bes_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15841,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BES/BSGM/2002/DTE/bes_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15842,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BES/BSGM/2003/Binary/bes_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15843,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BES/BSGM/2003/DTE/bes_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15844,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BES/BSGM/2004/Binary/bes_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15845,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BES/BSGM/2004/DTE/bes_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15846,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BES/BSGM/2005/Binary/bes_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15847,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BES/BSGM/2005/DTE/bes_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15848,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BES/BSGM/2006/Binary/bes_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15849,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BES/BSGM/2006/DTE/bes_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15850,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BES/BSGM/2007/Binary/bes_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15851,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BES/BSGM/2007/DTE/bes_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15852,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BES/BSGM/2008/Binary/bes_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15853,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BES/BSGM/2008/DTE/bes_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15854,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BES/BSGM/2009/Binary/bes_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15855,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BES/BSGM/2009/DTE/bes_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15856,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BES/BSGM/2010/Binary/bes_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15857,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BES/BSGM/2010/DTE/bes_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15858,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BES/BSGM/2011/Binary/bes_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15859,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BES/BSGM/2011/DTE/bes_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15860,535,"BES","Bonaire, Sint Eustatius and Saba","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BES/BSGM/2013/Binary/bes_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15861,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BES/BSGM/2013/DTE/bes_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15862,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BES/BSGM/2015/DTE/bes_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15863,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BES/BSGM/2016/DTE/bes_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15864,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BES/BSGM/2017/DTE/bes_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15865,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BES/BSGM/2018/DTE/bes_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15866,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BES/BSGM/2019/DTE/bes_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15867,535,"BES","Bonaire, Sint Eustatius and Saba","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BES/BSGM/2020/DTE/bes_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15868,540,"NCL","New Caledonia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NCL/BSGM/2001/Binary/ncl_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15869,540,"NCL","New Caledonia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NCL/BSGM/2001/DTE/ncl_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15870,540,"NCL","New Caledonia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NCL/BSGM/2002/Binary/ncl_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15871,540,"NCL","New Caledonia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NCL/BSGM/2002/DTE/ncl_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15872,540,"NCL","New Caledonia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NCL/BSGM/2003/Binary/ncl_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15873,540,"NCL","New Caledonia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NCL/BSGM/2003/DTE/ncl_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15874,540,"NCL","New Caledonia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NCL/BSGM/2004/Binary/ncl_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15875,540,"NCL","New Caledonia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NCL/BSGM/2004/DTE/ncl_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15876,540,"NCL","New Caledonia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NCL/BSGM/2005/Binary/ncl_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15877,540,"NCL","New Caledonia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NCL/BSGM/2005/DTE/ncl_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15878,540,"NCL","New Caledonia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NCL/BSGM/2006/Binary/ncl_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15879,540,"NCL","New Caledonia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NCL/BSGM/2006/DTE/ncl_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15880,540,"NCL","New Caledonia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NCL/BSGM/2007/Binary/ncl_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15881,540,"NCL","New Caledonia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NCL/BSGM/2007/DTE/ncl_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15882,540,"NCL","New Caledonia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NCL/BSGM/2008/Binary/ncl_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15883,540,"NCL","New Caledonia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NCL/BSGM/2008/DTE/ncl_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15884,540,"NCL","New Caledonia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NCL/BSGM/2009/Binary/ncl_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15885,540,"NCL","New Caledonia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NCL/BSGM/2009/DTE/ncl_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15886,540,"NCL","New Caledonia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NCL/BSGM/2010/Binary/ncl_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15887,540,"NCL","New Caledonia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NCL/BSGM/2010/DTE/ncl_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15888,540,"NCL","New Caledonia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NCL/BSGM/2011/Binary/ncl_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15889,540,"NCL","New Caledonia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NCL/BSGM/2011/DTE/ncl_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15890,540,"NCL","New Caledonia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NCL/BSGM/2013/Binary/ncl_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15891,540,"NCL","New Caledonia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NCL/BSGM/2013/DTE/ncl_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15892,540,"NCL","New Caledonia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NCL/BSGM/2015/DTE/ncl_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15893,540,"NCL","New Caledonia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NCL/BSGM/2016/DTE/ncl_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15894,540,"NCL","New Caledonia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NCL/BSGM/2017/DTE/ncl_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15895,540,"NCL","New Caledonia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NCL/BSGM/2018/DTE/ncl_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15896,540,"NCL","New Caledonia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NCL/BSGM/2019/DTE/ncl_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15897,540,"NCL","New Caledonia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NCL/BSGM/2020/DTE/ncl_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15898,548,"VUT","Vanuatu","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VUT/BSGM/2001/Binary/vut_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15899,548,"VUT","Vanuatu","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VUT/BSGM/2001/DTE/vut_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15900,548,"VUT","Vanuatu","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VUT/BSGM/2002/Binary/vut_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15901,548,"VUT","Vanuatu","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VUT/BSGM/2002/DTE/vut_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15902,548,"VUT","Vanuatu","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VUT/BSGM/2003/Binary/vut_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15903,548,"VUT","Vanuatu","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VUT/BSGM/2003/DTE/vut_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15904,548,"VUT","Vanuatu","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VUT/BSGM/2004/Binary/vut_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15905,548,"VUT","Vanuatu","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VUT/BSGM/2004/DTE/vut_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15906,548,"VUT","Vanuatu","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VUT/BSGM/2005/Binary/vut_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15907,548,"VUT","Vanuatu","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VUT/BSGM/2005/DTE/vut_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15908,548,"VUT","Vanuatu","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VUT/BSGM/2006/Binary/vut_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15909,548,"VUT","Vanuatu","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VUT/BSGM/2006/DTE/vut_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15910,548,"VUT","Vanuatu","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VUT/BSGM/2007/Binary/vut_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15911,548,"VUT","Vanuatu","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VUT/BSGM/2007/DTE/vut_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15912,548,"VUT","Vanuatu","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VUT/BSGM/2008/Binary/vut_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15913,548,"VUT","Vanuatu","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VUT/BSGM/2008/DTE/vut_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15914,548,"VUT","Vanuatu","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VUT/BSGM/2009/Binary/vut_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15915,548,"VUT","Vanuatu","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VUT/BSGM/2009/DTE/vut_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15916,548,"VUT","Vanuatu","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VUT/BSGM/2010/Binary/vut_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15917,548,"VUT","Vanuatu","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VUT/BSGM/2010/DTE/vut_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15918,548,"VUT","Vanuatu","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VUT/BSGM/2011/Binary/vut_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15919,548,"VUT","Vanuatu","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VUT/BSGM/2011/DTE/vut_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15920,548,"VUT","Vanuatu","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VUT/BSGM/2013/Binary/vut_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15921,548,"VUT","Vanuatu","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VUT/BSGM/2013/DTE/vut_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15922,548,"VUT","Vanuatu","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/VUT/BSGM/2015/DTE/vut_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15923,548,"VUT","Vanuatu","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/VUT/BSGM/2016/DTE/vut_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15924,548,"VUT","Vanuatu","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/VUT/BSGM/2017/DTE/vut_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15925,548,"VUT","Vanuatu","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/VUT/BSGM/2018/DTE/vut_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15926,548,"VUT","Vanuatu","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/VUT/BSGM/2019/DTE/vut_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15927,548,"VUT","Vanuatu","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/VUT/BSGM/2020/DTE/vut_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15928,554,"NZL","New Zealand","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NZL/BSGM/2001/Binary/nzl_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15929,554,"NZL","New Zealand","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NZL/BSGM/2001/DTE/nzl_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15930,554,"NZL","New Zealand","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NZL/BSGM/2002/Binary/nzl_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15931,554,"NZL","New Zealand","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NZL/BSGM/2002/DTE/nzl_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15932,554,"NZL","New Zealand","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NZL/BSGM/2003/Binary/nzl_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15933,554,"NZL","New Zealand","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NZL/BSGM/2003/DTE/nzl_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15934,554,"NZL","New Zealand","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NZL/BSGM/2004/Binary/nzl_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15935,554,"NZL","New Zealand","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NZL/BSGM/2004/DTE/nzl_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15936,554,"NZL","New Zealand","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NZL/BSGM/2005/Binary/nzl_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15937,554,"NZL","New Zealand","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NZL/BSGM/2005/DTE/nzl_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15938,554,"NZL","New Zealand","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NZL/BSGM/2006/Binary/nzl_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15939,554,"NZL","New Zealand","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NZL/BSGM/2006/DTE/nzl_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15940,554,"NZL","New Zealand","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NZL/BSGM/2007/Binary/nzl_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15941,554,"NZL","New Zealand","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NZL/BSGM/2007/DTE/nzl_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15942,554,"NZL","New Zealand","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NZL/BSGM/2008/Binary/nzl_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15943,554,"NZL","New Zealand","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NZL/BSGM/2008/DTE/nzl_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15944,554,"NZL","New Zealand","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NZL/BSGM/2009/Binary/nzl_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15945,554,"NZL","New Zealand","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NZL/BSGM/2009/DTE/nzl_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15946,554,"NZL","New Zealand","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NZL/BSGM/2010/Binary/nzl_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15947,554,"NZL","New Zealand","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NZL/BSGM/2010/DTE/nzl_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15948,554,"NZL","New Zealand","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NZL/BSGM/2011/Binary/nzl_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15949,554,"NZL","New Zealand","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NZL/BSGM/2011/DTE/nzl_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15950,554,"NZL","New Zealand","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NZL/BSGM/2013/Binary/nzl_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15951,554,"NZL","New Zealand","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NZL/BSGM/2013/DTE/nzl_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15952,554,"NZL","New Zealand","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NZL/BSGM/2015/DTE/nzl_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15953,554,"NZL","New Zealand","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NZL/BSGM/2016/DTE/nzl_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15954,554,"NZL","New Zealand","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NZL/BSGM/2017/DTE/nzl_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15955,554,"NZL","New Zealand","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NZL/BSGM/2018/DTE/nzl_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15956,554,"NZL","New Zealand","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NZL/BSGM/2019/DTE/nzl_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15957,554,"NZL","New Zealand","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NZL/BSGM/2020/DTE/nzl_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15958,558,"NIC","Nicaragua","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NIC/BSGM/2001/Binary/nic_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15959,558,"NIC","Nicaragua","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NIC/BSGM/2001/DTE/nic_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15960,558,"NIC","Nicaragua","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NIC/BSGM/2002/Binary/nic_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15961,558,"NIC","Nicaragua","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NIC/BSGM/2002/DTE/nic_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15962,558,"NIC","Nicaragua","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NIC/BSGM/2003/Binary/nic_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15963,558,"NIC","Nicaragua","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NIC/BSGM/2003/DTE/nic_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15964,558,"NIC","Nicaragua","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NIC/BSGM/2004/Binary/nic_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15965,558,"NIC","Nicaragua","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NIC/BSGM/2004/DTE/nic_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15966,558,"NIC","Nicaragua","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NIC/BSGM/2005/Binary/nic_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15967,558,"NIC","Nicaragua","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NIC/BSGM/2005/DTE/nic_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15968,558,"NIC","Nicaragua","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NIC/BSGM/2006/Binary/nic_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15969,558,"NIC","Nicaragua","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NIC/BSGM/2006/DTE/nic_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
15970,558,"NIC","Nicaragua","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NIC/BSGM/2007/Binary/nic_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
15971,558,"NIC","Nicaragua","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NIC/BSGM/2007/DTE/nic_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
15972,558,"NIC","Nicaragua","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NIC/BSGM/2008/Binary/nic_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
15973,558,"NIC","Nicaragua","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NIC/BSGM/2008/DTE/nic_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
15974,558,"NIC","Nicaragua","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NIC/BSGM/2009/Binary/nic_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
15975,558,"NIC","Nicaragua","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NIC/BSGM/2009/DTE/nic_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
15976,558,"NIC","Nicaragua","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NIC/BSGM/2010/Binary/nic_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
15977,558,"NIC","Nicaragua","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NIC/BSGM/2010/DTE/nic_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
15978,558,"NIC","Nicaragua","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NIC/BSGM/2011/Binary/nic_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
15979,558,"NIC","Nicaragua","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NIC/BSGM/2011/DTE/nic_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
15980,558,"NIC","Nicaragua","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NIC/BSGM/2013/Binary/nic_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
15981,558,"NIC","Nicaragua","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NIC/BSGM/2013/DTE/nic_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
15982,558,"NIC","Nicaragua","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NIC/BSGM/2015/DTE/nic_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
15983,558,"NIC","Nicaragua","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NIC/BSGM/2016/DTE/nic_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
15984,558,"NIC","Nicaragua","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NIC/BSGM/2017/DTE/nic_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
15985,558,"NIC","Nicaragua","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NIC/BSGM/2018/DTE/nic_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
15986,558,"NIC","Nicaragua","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NIC/BSGM/2019/DTE/nic_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
15987,558,"NIC","Nicaragua","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NIC/BSGM/2020/DTE/nic_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
15988,562,"NER","Niger","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NER/BSGM/2001/Binary/ner_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
15989,562,"NER","Niger","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NER/BSGM/2001/DTE/ner_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
15990,562,"NER","Niger","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NER/BSGM/2002/Binary/ner_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
15991,562,"NER","Niger","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NER/BSGM/2002/DTE/ner_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
15992,562,"NER","Niger","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NER/BSGM/2003/Binary/ner_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
15993,562,"NER","Niger","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NER/BSGM/2003/DTE/ner_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
15994,562,"NER","Niger","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NER/BSGM/2004/Binary/ner_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
15995,562,"NER","Niger","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NER/BSGM/2004/DTE/ner_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
15996,562,"NER","Niger","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NER/BSGM/2005/Binary/ner_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
15997,562,"NER","Niger","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NER/BSGM/2005/DTE/ner_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
15998,562,"NER","Niger","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NER/BSGM/2006/Binary/ner_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
15999,562,"NER","Niger","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NER/BSGM/2006/DTE/ner_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16000,562,"NER","Niger","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NER/BSGM/2007/Binary/ner_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16001,562,"NER","Niger","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NER/BSGM/2007/DTE/ner_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16002,562,"NER","Niger","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NER/BSGM/2008/Binary/ner_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16003,562,"NER","Niger","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NER/BSGM/2008/DTE/ner_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16004,562,"NER","Niger","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NER/BSGM/2009/Binary/ner_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16005,562,"NER","Niger","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NER/BSGM/2009/DTE/ner_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16006,562,"NER","Niger","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NER/BSGM/2010/Binary/ner_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16007,562,"NER","Niger","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NER/BSGM/2010/DTE/ner_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16008,562,"NER","Niger","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NER/BSGM/2011/Binary/ner_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16009,562,"NER","Niger","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NER/BSGM/2011/DTE/ner_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16010,562,"NER","Niger","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NER/BSGM/2013/Binary/ner_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16011,562,"NER","Niger","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NER/BSGM/2013/DTE/ner_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16012,562,"NER","Niger","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NER/BSGM/2015/DTE/ner_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16013,562,"NER","Niger","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NER/BSGM/2016/DTE/ner_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16014,562,"NER","Niger","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NER/BSGM/2017/DTE/ner_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16015,562,"NER","Niger","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NER/BSGM/2018/DTE/ner_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16016,562,"NER","Niger","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NER/BSGM/2019/DTE/ner_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16017,562,"NER","Niger","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NER/BSGM/2020/DTE/ner_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16018,566,"NGA","Nigeria","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NGA/BSGM/2001/Binary/nga_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16019,566,"NGA","Nigeria","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NGA/BSGM/2001/DTE/nga_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16020,566,"NGA","Nigeria","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NGA/BSGM/2002/Binary/nga_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16021,566,"NGA","Nigeria","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NGA/BSGM/2002/DTE/nga_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16022,566,"NGA","Nigeria","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NGA/BSGM/2003/Binary/nga_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16023,566,"NGA","Nigeria","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NGA/BSGM/2003/DTE/nga_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16024,566,"NGA","Nigeria","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NGA/BSGM/2004/Binary/nga_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16025,566,"NGA","Nigeria","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NGA/BSGM/2004/DTE/nga_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16026,566,"NGA","Nigeria","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NGA/BSGM/2005/Binary/nga_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16027,566,"NGA","Nigeria","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NGA/BSGM/2005/DTE/nga_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16028,566,"NGA","Nigeria","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NGA/BSGM/2006/Binary/nga_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16029,566,"NGA","Nigeria","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NGA/BSGM/2006/DTE/nga_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16030,566,"NGA","Nigeria","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NGA/BSGM/2007/Binary/nga_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16031,566,"NGA","Nigeria","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NGA/BSGM/2007/DTE/nga_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16032,566,"NGA","Nigeria","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NGA/BSGM/2008/Binary/nga_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16033,566,"NGA","Nigeria","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NGA/BSGM/2008/DTE/nga_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16034,566,"NGA","Nigeria","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NGA/BSGM/2009/Binary/nga_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16035,566,"NGA","Nigeria","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NGA/BSGM/2009/DTE/nga_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16036,566,"NGA","Nigeria","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NGA/BSGM/2010/Binary/nga_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16037,566,"NGA","Nigeria","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NGA/BSGM/2010/DTE/nga_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16038,566,"NGA","Nigeria","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NGA/BSGM/2011/Binary/nga_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16039,566,"NGA","Nigeria","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NGA/BSGM/2011/DTE/nga_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16040,566,"NGA","Nigeria","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NGA/BSGM/2013/Binary/nga_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16041,566,"NGA","Nigeria","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NGA/BSGM/2013/DTE/nga_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16042,566,"NGA","Nigeria","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NGA/BSGM/2015/DTE/nga_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16043,566,"NGA","Nigeria","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NGA/BSGM/2016/DTE/nga_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16044,566,"NGA","Nigeria","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NGA/BSGM/2017/DTE/nga_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16045,566,"NGA","Nigeria","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NGA/BSGM/2018/DTE/nga_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16046,566,"NGA","Nigeria","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NGA/BSGM/2019/DTE/nga_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16047,566,"NGA","Nigeria","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NGA/BSGM/2020/DTE/nga_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16048,570,"NIU","Niue","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NIU/BSGM/2001/Binary/niu_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16049,570,"NIU","Niue","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NIU/BSGM/2001/DTE/niu_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16050,570,"NIU","Niue","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NIU/BSGM/2002/Binary/niu_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16051,570,"NIU","Niue","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NIU/BSGM/2002/DTE/niu_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16052,570,"NIU","Niue","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NIU/BSGM/2003/Binary/niu_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16053,570,"NIU","Niue","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NIU/BSGM/2003/DTE/niu_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16054,570,"NIU","Niue","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NIU/BSGM/2004/Binary/niu_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16055,570,"NIU","Niue","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NIU/BSGM/2004/DTE/niu_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16056,570,"NIU","Niue","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NIU/BSGM/2005/Binary/niu_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16057,570,"NIU","Niue","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NIU/BSGM/2005/DTE/niu_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16058,570,"NIU","Niue","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NIU/BSGM/2006/Binary/niu_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16059,570,"NIU","Niue","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NIU/BSGM/2006/DTE/niu_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16060,570,"NIU","Niue","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NIU/BSGM/2007/Binary/niu_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16061,570,"NIU","Niue","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NIU/BSGM/2007/DTE/niu_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16062,570,"NIU","Niue","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NIU/BSGM/2008/Binary/niu_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16063,570,"NIU","Niue","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NIU/BSGM/2008/DTE/niu_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16064,570,"NIU","Niue","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NIU/BSGM/2009/Binary/niu_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16065,570,"NIU","Niue","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NIU/BSGM/2009/DTE/niu_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16066,570,"NIU","Niue","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NIU/BSGM/2010/Binary/niu_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16067,570,"NIU","Niue","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NIU/BSGM/2010/DTE/niu_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16068,570,"NIU","Niue","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NIU/BSGM/2011/Binary/niu_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16069,570,"NIU","Niue","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NIU/BSGM/2011/DTE/niu_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16070,570,"NIU","Niue","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NIU/BSGM/2013/DTE/niu_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16071,570,"NIU","Niue","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NIU/BSGM/2015/DTE/niu_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16072,570,"NIU","Niue","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NIU/BSGM/2016/DTE/niu_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16073,570,"NIU","Niue","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NIU/BSGM/2017/DTE/niu_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16074,570,"NIU","Niue","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NIU/BSGM/2018/DTE/niu_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16075,570,"NIU","Niue","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NIU/BSGM/2019/DTE/niu_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16076,570,"NIU","Niue","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NIU/BSGM/2020/DTE/niu_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16077,574,"NFK","Norfolk Island","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NFK/BSGM/2001/Binary/nfk_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16078,574,"NFK","Norfolk Island","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NFK/BSGM/2001/DTE/nfk_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16079,574,"NFK","Norfolk Island","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NFK/BSGM/2002/Binary/nfk_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16080,574,"NFK","Norfolk Island","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NFK/BSGM/2002/DTE/nfk_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16081,574,"NFK","Norfolk Island","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NFK/BSGM/2003/Binary/nfk_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16082,574,"NFK","Norfolk Island","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NFK/BSGM/2003/DTE/nfk_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16083,574,"NFK","Norfolk Island","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NFK/BSGM/2004/Binary/nfk_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16084,574,"NFK","Norfolk Island","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NFK/BSGM/2004/DTE/nfk_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16085,574,"NFK","Norfolk Island","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NFK/BSGM/2005/Binary/nfk_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16086,574,"NFK","Norfolk Island","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NFK/BSGM/2005/DTE/nfk_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16087,574,"NFK","Norfolk Island","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NFK/BSGM/2006/Binary/nfk_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16088,574,"NFK","Norfolk Island","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NFK/BSGM/2006/DTE/nfk_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16089,574,"NFK","Norfolk Island","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NFK/BSGM/2007/Binary/nfk_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16090,574,"NFK","Norfolk Island","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NFK/BSGM/2007/DTE/nfk_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16091,574,"NFK","Norfolk Island","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NFK/BSGM/2008/Binary/nfk_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16092,574,"NFK","Norfolk Island","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NFK/BSGM/2008/DTE/nfk_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16093,574,"NFK","Norfolk Island","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NFK/BSGM/2009/Binary/nfk_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16094,574,"NFK","Norfolk Island","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NFK/BSGM/2009/DTE/nfk_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16095,574,"NFK","Norfolk Island","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NFK/BSGM/2010/Binary/nfk_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16096,574,"NFK","Norfolk Island","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NFK/BSGM/2010/DTE/nfk_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16097,574,"NFK","Norfolk Island","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NFK/BSGM/2011/Binary/nfk_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16098,574,"NFK","Norfolk Island","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NFK/BSGM/2011/DTE/nfk_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16099,574,"NFK","Norfolk Island","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NFK/BSGM/2013/Binary/nfk_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16100,574,"NFK","Norfolk Island","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NFK/BSGM/2013/DTE/nfk_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16101,574,"NFK","Norfolk Island","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NFK/BSGM/2015/DTE/nfk_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16102,574,"NFK","Norfolk Island","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NFK/BSGM/2016/DTE/nfk_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16103,574,"NFK","Norfolk Island","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NFK/BSGM/2017/DTE/nfk_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16104,574,"NFK","Norfolk Island","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NFK/BSGM/2018/DTE/nfk_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16105,574,"NFK","Norfolk Island","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NFK/BSGM/2019/DTE/nfk_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16106,574,"NFK","Norfolk Island","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NFK/BSGM/2020/DTE/nfk_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16107,578,"NOR","Norway","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NOR/BSGM/2001/Binary/nor_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16108,578,"NOR","Norway","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/NOR/BSGM/2001/DTE/nor_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16109,578,"NOR","Norway","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NOR/BSGM/2002/Binary/nor_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16110,578,"NOR","Norway","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/NOR/BSGM/2002/DTE/nor_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16111,578,"NOR","Norway","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NOR/BSGM/2003/Binary/nor_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16112,578,"NOR","Norway","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/NOR/BSGM/2003/DTE/nor_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16113,578,"NOR","Norway","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NOR/BSGM/2004/Binary/nor_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16114,578,"NOR","Norway","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/NOR/BSGM/2004/DTE/nor_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16115,578,"NOR","Norway","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NOR/BSGM/2005/Binary/nor_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16116,578,"NOR","Norway","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/NOR/BSGM/2005/DTE/nor_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16117,578,"NOR","Norway","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NOR/BSGM/2006/Binary/nor_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16118,578,"NOR","Norway","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/NOR/BSGM/2006/DTE/nor_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16119,578,"NOR","Norway","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NOR/BSGM/2007/Binary/nor_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16120,578,"NOR","Norway","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/NOR/BSGM/2007/DTE/nor_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16121,578,"NOR","Norway","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NOR/BSGM/2008/Binary/nor_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16122,578,"NOR","Norway","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/NOR/BSGM/2008/DTE/nor_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16123,578,"NOR","Norway","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NOR/BSGM/2009/Binary/nor_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16124,578,"NOR","Norway","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/NOR/BSGM/2009/DTE/nor_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16125,578,"NOR","Norway","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NOR/BSGM/2010/Binary/nor_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16126,578,"NOR","Norway","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/NOR/BSGM/2010/DTE/nor_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16127,578,"NOR","Norway","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NOR/BSGM/2011/Binary/nor_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16128,578,"NOR","Norway","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/NOR/BSGM/2011/DTE/nor_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16129,578,"NOR","Norway","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NOR/BSGM/2013/Binary/nor_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16130,578,"NOR","Norway","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/NOR/BSGM/2013/DTE/nor_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16131,578,"NOR","Norway","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/NOR/BSGM/2015/DTE/nor_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16132,578,"NOR","Norway","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/NOR/BSGM/2016/DTE/nor_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16133,578,"NOR","Norway","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/NOR/BSGM/2017/DTE/nor_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16134,578,"NOR","Norway","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/NOR/BSGM/2018/DTE/nor_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16135,578,"NOR","Norway","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/NOR/BSGM/2019/DTE/nor_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16136,578,"NOR","Norway","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/NOR/BSGM/2020/DTE/nor_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16137,580,"MNP","Northern Mariana Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MNP/BSGM/2001/Binary/mnp_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16138,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MNP/BSGM/2001/DTE/mnp_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16139,580,"MNP","Northern Mariana Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MNP/BSGM/2002/Binary/mnp_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16140,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MNP/BSGM/2002/DTE/mnp_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16141,580,"MNP","Northern Mariana Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MNP/BSGM/2003/Binary/mnp_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16142,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MNP/BSGM/2003/DTE/mnp_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16143,580,"MNP","Northern Mariana Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MNP/BSGM/2004/Binary/mnp_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16144,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MNP/BSGM/2004/DTE/mnp_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16145,580,"MNP","Northern Mariana Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MNP/BSGM/2005/Binary/mnp_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16146,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MNP/BSGM/2005/DTE/mnp_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16147,580,"MNP","Northern Mariana Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MNP/BSGM/2006/Binary/mnp_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16148,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MNP/BSGM/2006/DTE/mnp_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16149,580,"MNP","Northern Mariana Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MNP/BSGM/2007/Binary/mnp_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16150,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MNP/BSGM/2007/DTE/mnp_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16151,580,"MNP","Northern Mariana Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MNP/BSGM/2008/Binary/mnp_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16152,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MNP/BSGM/2008/DTE/mnp_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16153,580,"MNP","Northern Mariana Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MNP/BSGM/2009/Binary/mnp_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16154,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MNP/BSGM/2009/DTE/mnp_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16155,580,"MNP","Northern Mariana Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MNP/BSGM/2010/Binary/mnp_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16156,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MNP/BSGM/2010/DTE/mnp_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16157,580,"MNP","Northern Mariana Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MNP/BSGM/2011/Binary/mnp_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16158,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MNP/BSGM/2011/DTE/mnp_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16159,580,"MNP","Northern Mariana Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MNP/BSGM/2013/Binary/mnp_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16160,580,"MNP","Northern Mariana Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MNP/BSGM/2013/DTE/mnp_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16161,580,"MNP","Northern Mariana Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MNP/BSGM/2015/DTE/mnp_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16162,580,"MNP","Northern Mariana Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MNP/BSGM/2016/DTE/mnp_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16163,580,"MNP","Northern Mariana Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MNP/BSGM/2017/DTE/mnp_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16164,580,"MNP","Northern Mariana Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MNP/BSGM/2018/DTE/mnp_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16165,580,"MNP","Northern Mariana Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MNP/BSGM/2019/DTE/mnp_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16166,580,"MNP","Northern Mariana Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MNP/BSGM/2020/DTE/mnp_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16167,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/UMI/BSGM/2001/Binary/umi_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16168,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/UMI/BSGM/2001/DTE/umi_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16169,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/UMI/BSGM/2002/Binary/umi_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16170,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/UMI/BSGM/2002/DTE/umi_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16171,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/UMI/BSGM/2003/Binary/umi_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16172,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/UMI/BSGM/2003/DTE/umi_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16173,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/UMI/BSGM/2004/Binary/umi_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16174,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/UMI/BSGM/2004/DTE/umi_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16175,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/UMI/BSGM/2005/Binary/umi_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16176,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/UMI/BSGM/2005/DTE/umi_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16177,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/UMI/BSGM/2006/Binary/umi_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16178,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/UMI/BSGM/2006/DTE/umi_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16179,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/UMI/BSGM/2007/Binary/umi_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16180,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/UMI/BSGM/2007/DTE/umi_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16181,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/UMI/BSGM/2008/Binary/umi_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16182,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/UMI/BSGM/2008/DTE/umi_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16183,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/UMI/BSGM/2009/Binary/umi_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16184,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/UMI/BSGM/2009/DTE/umi_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16185,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/UMI/BSGM/2010/Binary/umi_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16186,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/UMI/BSGM/2010/DTE/umi_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16187,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/UMI/BSGM/2011/Binary/umi_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16188,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/UMI/BSGM/2011/DTE/umi_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16189,581,"UMI","United States Minor Outlying Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/UMI/BSGM/2013/Binary/umi_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16190,581,"UMI","United States Minor Outlying Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/UMI/BSGM/2013/DTE/umi_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16191,581,"UMI","United States Minor Outlying Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/UMI/BSGM/2015/DTE/umi_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16192,581,"UMI","United States Minor Outlying Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/UMI/BSGM/2016/DTE/umi_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16193,581,"UMI","United States Minor Outlying Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/UMI/BSGM/2017/DTE/umi_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16194,581,"UMI","United States Minor Outlying Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/UMI/BSGM/2018/DTE/umi_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16195,581,"UMI","United States Minor Outlying Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/UMI/BSGM/2019/DTE/umi_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16196,581,"UMI","United States Minor Outlying Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/UMI/BSGM/2020/DTE/umi_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16197,583,"FSM","Micronesia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FSM/BSGM/2001/Binary/fsm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16198,583,"FSM","Micronesia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/FSM/BSGM/2001/DTE/fsm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16199,583,"FSM","Micronesia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FSM/BSGM/2002/Binary/fsm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16200,583,"FSM","Micronesia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/FSM/BSGM/2002/DTE/fsm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16201,583,"FSM","Micronesia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FSM/BSGM/2003/Binary/fsm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16202,583,"FSM","Micronesia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/FSM/BSGM/2003/DTE/fsm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16203,583,"FSM","Micronesia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FSM/BSGM/2004/Binary/fsm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16204,583,"FSM","Micronesia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/FSM/BSGM/2004/DTE/fsm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16205,583,"FSM","Micronesia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FSM/BSGM/2005/Binary/fsm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16206,583,"FSM","Micronesia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/FSM/BSGM/2005/DTE/fsm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16207,583,"FSM","Micronesia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FSM/BSGM/2006/Binary/fsm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16208,583,"FSM","Micronesia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/FSM/BSGM/2006/DTE/fsm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16209,583,"FSM","Micronesia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FSM/BSGM/2007/Binary/fsm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16210,583,"FSM","Micronesia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/FSM/BSGM/2007/DTE/fsm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16211,583,"FSM","Micronesia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FSM/BSGM/2008/Binary/fsm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16212,583,"FSM","Micronesia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/FSM/BSGM/2008/DTE/fsm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16213,583,"FSM","Micronesia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FSM/BSGM/2009/Binary/fsm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16214,583,"FSM","Micronesia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/FSM/BSGM/2009/DTE/fsm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16215,583,"FSM","Micronesia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FSM/BSGM/2010/Binary/fsm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16216,583,"FSM","Micronesia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/FSM/BSGM/2010/DTE/fsm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16217,583,"FSM","Micronesia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FSM/BSGM/2011/Binary/fsm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16218,583,"FSM","Micronesia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/FSM/BSGM/2011/DTE/fsm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16219,583,"FSM","Micronesia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FSM/BSGM/2013/Binary/fsm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16220,583,"FSM","Micronesia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/FSM/BSGM/2013/DTE/fsm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16221,583,"FSM","Micronesia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/FSM/BSGM/2015/DTE/fsm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16222,583,"FSM","Micronesia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/FSM/BSGM/2016/DTE/fsm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16223,583,"FSM","Micronesia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/FSM/BSGM/2017/DTE/fsm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16224,583,"FSM","Micronesia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/FSM/BSGM/2018/DTE/fsm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16225,583,"FSM","Micronesia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/FSM/BSGM/2019/DTE/fsm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16226,583,"FSM","Micronesia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/FSM/BSGM/2020/DTE/fsm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16227,584,"MHL","Marshall Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MHL/BSGM/2001/Binary/mhl_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16228,584,"MHL","Marshall Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MHL/BSGM/2001/DTE/mhl_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16229,584,"MHL","Marshall Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MHL/BSGM/2002/Binary/mhl_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16230,584,"MHL","Marshall Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MHL/BSGM/2002/DTE/mhl_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16231,584,"MHL","Marshall Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MHL/BSGM/2003/Binary/mhl_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16232,584,"MHL","Marshall Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MHL/BSGM/2003/DTE/mhl_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16233,584,"MHL","Marshall Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MHL/BSGM/2004/Binary/mhl_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16234,584,"MHL","Marshall Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MHL/BSGM/2004/DTE/mhl_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16235,584,"MHL","Marshall Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MHL/BSGM/2005/Binary/mhl_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16236,584,"MHL","Marshall Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MHL/BSGM/2005/DTE/mhl_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16237,584,"MHL","Marshall Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MHL/BSGM/2006/Binary/mhl_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16238,584,"MHL","Marshall Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MHL/BSGM/2006/DTE/mhl_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16239,584,"MHL","Marshall Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MHL/BSGM/2007/Binary/mhl_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16240,584,"MHL","Marshall Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MHL/BSGM/2007/DTE/mhl_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16241,584,"MHL","Marshall Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MHL/BSGM/2008/Binary/mhl_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16242,584,"MHL","Marshall Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MHL/BSGM/2008/DTE/mhl_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16243,584,"MHL","Marshall Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MHL/BSGM/2009/Binary/mhl_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16244,584,"MHL","Marshall Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MHL/BSGM/2009/DTE/mhl_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16245,584,"MHL","Marshall Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MHL/BSGM/2010/Binary/mhl_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16246,584,"MHL","Marshall Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MHL/BSGM/2010/DTE/mhl_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16247,584,"MHL","Marshall Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MHL/BSGM/2011/Binary/mhl_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16248,584,"MHL","Marshall Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MHL/BSGM/2011/DTE/mhl_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16249,584,"MHL","Marshall Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MHL/BSGM/2013/Binary/mhl_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16250,584,"MHL","Marshall Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MHL/BSGM/2013/DTE/mhl_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16251,584,"MHL","Marshall Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MHL/BSGM/2015/DTE/mhl_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16252,584,"MHL","Marshall Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MHL/BSGM/2016/DTE/mhl_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16253,584,"MHL","Marshall Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MHL/BSGM/2017/DTE/mhl_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16254,584,"MHL","Marshall Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MHL/BSGM/2018/DTE/mhl_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16255,584,"MHL","Marshall Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MHL/BSGM/2019/DTE/mhl_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16256,584,"MHL","Marshall Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MHL/BSGM/2020/DTE/mhl_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16257,585,"PLW","Palau","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PLW/BSGM/2001/Binary/plw_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16258,585,"PLW","Palau","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PLW/BSGM/2001/DTE/plw_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16259,585,"PLW","Palau","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PLW/BSGM/2002/Binary/plw_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16260,585,"PLW","Palau","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PLW/BSGM/2002/DTE/plw_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16261,585,"PLW","Palau","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PLW/BSGM/2003/Binary/plw_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16262,585,"PLW","Palau","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PLW/BSGM/2003/DTE/plw_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16263,585,"PLW","Palau","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PLW/BSGM/2004/Binary/plw_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16264,585,"PLW","Palau","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PLW/BSGM/2004/DTE/plw_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16265,585,"PLW","Palau","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PLW/BSGM/2005/Binary/plw_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16266,585,"PLW","Palau","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PLW/BSGM/2005/DTE/plw_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16267,585,"PLW","Palau","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PLW/BSGM/2006/Binary/plw_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16268,585,"PLW","Palau","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PLW/BSGM/2006/DTE/plw_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16269,585,"PLW","Palau","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PLW/BSGM/2007/Binary/plw_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16270,585,"PLW","Palau","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PLW/BSGM/2007/DTE/plw_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16271,585,"PLW","Palau","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PLW/BSGM/2008/Binary/plw_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16272,585,"PLW","Palau","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PLW/BSGM/2008/DTE/plw_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16273,585,"PLW","Palau","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PLW/BSGM/2009/Binary/plw_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16274,585,"PLW","Palau","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PLW/BSGM/2009/DTE/plw_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16275,585,"PLW","Palau","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PLW/BSGM/2010/Binary/plw_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16276,585,"PLW","Palau","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PLW/BSGM/2010/DTE/plw_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16277,585,"PLW","Palau","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PLW/BSGM/2011/Binary/plw_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16278,585,"PLW","Palau","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PLW/BSGM/2011/DTE/plw_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16279,585,"PLW","Palau","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PLW/BSGM/2013/Binary/plw_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16280,585,"PLW","Palau","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PLW/BSGM/2013/DTE/plw_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16281,585,"PLW","Palau","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PLW/BSGM/2015/DTE/plw_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16282,585,"PLW","Palau","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PLW/BSGM/2016/DTE/plw_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16283,585,"PLW","Palau","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PLW/BSGM/2017/DTE/plw_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16284,585,"PLW","Palau","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PLW/BSGM/2018/DTE/plw_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16285,585,"PLW","Palau","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PLW/BSGM/2019/DTE/plw_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16286,585,"PLW","Palau","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PLW/BSGM/2020/DTE/plw_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16287,586,"PAK","Pakistan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PAK/BSGM/2001/Binary/pak_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16288,586,"PAK","Pakistan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PAK/BSGM/2001/DTE/pak_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16289,586,"PAK","Pakistan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PAK/BSGM/2002/Binary/pak_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16290,586,"PAK","Pakistan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PAK/BSGM/2002/DTE/pak_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16291,586,"PAK","Pakistan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PAK/BSGM/2003/Binary/pak_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16292,586,"PAK","Pakistan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PAK/BSGM/2003/DTE/pak_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16293,586,"PAK","Pakistan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PAK/BSGM/2004/Binary/pak_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16294,586,"PAK","Pakistan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PAK/BSGM/2004/DTE/pak_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16295,586,"PAK","Pakistan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PAK/BSGM/2005/Binary/pak_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16296,586,"PAK","Pakistan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PAK/BSGM/2005/DTE/pak_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16297,586,"PAK","Pakistan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PAK/BSGM/2006/Binary/pak_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16298,586,"PAK","Pakistan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PAK/BSGM/2006/DTE/pak_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16299,586,"PAK","Pakistan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PAK/BSGM/2007/Binary/pak_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16300,586,"PAK","Pakistan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PAK/BSGM/2007/DTE/pak_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16301,586,"PAK","Pakistan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PAK/BSGM/2008/Binary/pak_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16302,586,"PAK","Pakistan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PAK/BSGM/2008/DTE/pak_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16303,586,"PAK","Pakistan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PAK/BSGM/2009/Binary/pak_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16304,586,"PAK","Pakistan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PAK/BSGM/2009/DTE/pak_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16305,586,"PAK","Pakistan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PAK/BSGM/2010/Binary/pak_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16306,586,"PAK","Pakistan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PAK/BSGM/2010/DTE/pak_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16307,586,"PAK","Pakistan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PAK/BSGM/2011/Binary/pak_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16308,586,"PAK","Pakistan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PAK/BSGM/2011/DTE/pak_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16309,586,"PAK","Pakistan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PAK/BSGM/2013/Binary/pak_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16310,586,"PAK","Pakistan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PAK/BSGM/2013/DTE/pak_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16311,586,"PAK","Pakistan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PAK/BSGM/2015/DTE/pak_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16312,586,"PAK","Pakistan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PAK/BSGM/2016/DTE/pak_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16313,586,"PAK","Pakistan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PAK/BSGM/2017/DTE/pak_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16314,586,"PAK","Pakistan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PAK/BSGM/2018/DTE/pak_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16315,586,"PAK","Pakistan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PAK/BSGM/2019/DTE/pak_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16316,586,"PAK","Pakistan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PAK/BSGM/2020/DTE/pak_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16317,591,"PAN","Panama","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PAN/BSGM/2001/Binary/pan_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16318,591,"PAN","Panama","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PAN/BSGM/2001/DTE/pan_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16319,591,"PAN","Panama","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PAN/BSGM/2002/Binary/pan_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16320,591,"PAN","Panama","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PAN/BSGM/2002/DTE/pan_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16321,591,"PAN","Panama","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PAN/BSGM/2003/Binary/pan_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16322,591,"PAN","Panama","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PAN/BSGM/2003/DTE/pan_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16323,591,"PAN","Panama","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PAN/BSGM/2004/Binary/pan_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16324,591,"PAN","Panama","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PAN/BSGM/2004/DTE/pan_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16325,591,"PAN","Panama","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PAN/BSGM/2005/Binary/pan_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16326,591,"PAN","Panama","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PAN/BSGM/2005/DTE/pan_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16327,591,"PAN","Panama","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PAN/BSGM/2006/Binary/pan_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16328,591,"PAN","Panama","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PAN/BSGM/2006/DTE/pan_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16329,591,"PAN","Panama","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PAN/BSGM/2007/Binary/pan_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16330,591,"PAN","Panama","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PAN/BSGM/2007/DTE/pan_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16331,591,"PAN","Panama","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PAN/BSGM/2008/Binary/pan_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16332,591,"PAN","Panama","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PAN/BSGM/2008/DTE/pan_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16333,591,"PAN","Panama","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PAN/BSGM/2009/Binary/pan_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16334,591,"PAN","Panama","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PAN/BSGM/2009/DTE/pan_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16335,591,"PAN","Panama","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PAN/BSGM/2010/Binary/pan_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16336,591,"PAN","Panama","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PAN/BSGM/2010/DTE/pan_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16337,591,"PAN","Panama","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PAN/BSGM/2011/Binary/pan_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16338,591,"PAN","Panama","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PAN/BSGM/2011/DTE/pan_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16339,591,"PAN","Panama","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PAN/BSGM/2013/Binary/pan_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16340,591,"PAN","Panama","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PAN/BSGM/2013/DTE/pan_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16341,591,"PAN","Panama","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PAN/BSGM/2015/DTE/pan_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16342,591,"PAN","Panama","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PAN/BSGM/2016/DTE/pan_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16343,591,"PAN","Panama","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PAN/BSGM/2017/DTE/pan_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16344,591,"PAN","Panama","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PAN/BSGM/2018/DTE/pan_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16345,591,"PAN","Panama","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PAN/BSGM/2019/DTE/pan_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16346,591,"PAN","Panama","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PAN/BSGM/2020/DTE/pan_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16347,598,"PNG","Papua New Guinea","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PNG/BSGM/2001/Binary/png_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16348,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PNG/BSGM/2001/DTE/png_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16349,598,"PNG","Papua New Guinea","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PNG/BSGM/2002/Binary/png_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16350,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PNG/BSGM/2002/DTE/png_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16351,598,"PNG","Papua New Guinea","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PNG/BSGM/2003/Binary/png_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16352,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PNG/BSGM/2003/DTE/png_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16353,598,"PNG","Papua New Guinea","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PNG/BSGM/2004/Binary/png_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16354,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PNG/BSGM/2004/DTE/png_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16355,598,"PNG","Papua New Guinea","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PNG/BSGM/2005/Binary/png_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16356,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PNG/BSGM/2005/DTE/png_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16357,598,"PNG","Papua New Guinea","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PNG/BSGM/2006/Binary/png_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16358,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PNG/BSGM/2006/DTE/png_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16359,598,"PNG","Papua New Guinea","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PNG/BSGM/2007/Binary/png_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16360,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PNG/BSGM/2007/DTE/png_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16361,598,"PNG","Papua New Guinea","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PNG/BSGM/2008/Binary/png_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16362,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PNG/BSGM/2008/DTE/png_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16363,598,"PNG","Papua New Guinea","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PNG/BSGM/2009/Binary/png_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16364,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PNG/BSGM/2009/DTE/png_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16365,598,"PNG","Papua New Guinea","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PNG/BSGM/2010/Binary/png_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16366,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PNG/BSGM/2010/DTE/png_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16367,598,"PNG","Papua New Guinea","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PNG/BSGM/2011/Binary/png_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16368,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PNG/BSGM/2011/DTE/png_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16369,598,"PNG","Papua New Guinea","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PNG/BSGM/2013/Binary/png_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16370,598,"PNG","Papua New Guinea","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PNG/BSGM/2013/DTE/png_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16371,598,"PNG","Papua New Guinea","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PNG/BSGM/2015/DTE/png_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16372,598,"PNG","Papua New Guinea","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PNG/BSGM/2016/DTE/png_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16373,598,"PNG","Papua New Guinea","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PNG/BSGM/2017/DTE/png_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16374,598,"PNG","Papua New Guinea","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PNG/BSGM/2018/DTE/png_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16375,598,"PNG","Papua New Guinea","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PNG/BSGM/2019/DTE/png_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16376,598,"PNG","Papua New Guinea","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PNG/BSGM/2020/DTE/png_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16377,600,"PRY","Paraguay","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PRY/BSGM/2001/Binary/pry_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16378,600,"PRY","Paraguay","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PRY/BSGM/2001/DTE/pry_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16379,600,"PRY","Paraguay","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PRY/BSGM/2002/Binary/pry_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16380,600,"PRY","Paraguay","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PRY/BSGM/2002/DTE/pry_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16381,600,"PRY","Paraguay","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PRY/BSGM/2003/Binary/pry_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16382,600,"PRY","Paraguay","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PRY/BSGM/2003/DTE/pry_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16383,600,"PRY","Paraguay","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PRY/BSGM/2004/Binary/pry_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16384,600,"PRY","Paraguay","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PRY/BSGM/2004/DTE/pry_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16385,600,"PRY","Paraguay","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PRY/BSGM/2005/Binary/pry_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16386,600,"PRY","Paraguay","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PRY/BSGM/2005/DTE/pry_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16387,600,"PRY","Paraguay","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PRY/BSGM/2006/Binary/pry_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16388,600,"PRY","Paraguay","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PRY/BSGM/2006/DTE/pry_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16389,600,"PRY","Paraguay","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PRY/BSGM/2007/Binary/pry_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16390,600,"PRY","Paraguay","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PRY/BSGM/2007/DTE/pry_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16391,600,"PRY","Paraguay","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PRY/BSGM/2008/Binary/pry_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16392,600,"PRY","Paraguay","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PRY/BSGM/2008/DTE/pry_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16393,600,"PRY","Paraguay","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PRY/BSGM/2009/Binary/pry_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16394,600,"PRY","Paraguay","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PRY/BSGM/2009/DTE/pry_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16395,600,"PRY","Paraguay","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PRY/BSGM/2010/Binary/pry_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16396,600,"PRY","Paraguay","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PRY/BSGM/2010/DTE/pry_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16397,600,"PRY","Paraguay","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PRY/BSGM/2011/Binary/pry_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16398,600,"PRY","Paraguay","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PRY/BSGM/2011/DTE/pry_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16399,600,"PRY","Paraguay","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PRY/BSGM/2013/Binary/pry_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16400,600,"PRY","Paraguay","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PRY/BSGM/2013/DTE/pry_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16401,600,"PRY","Paraguay","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PRY/BSGM/2015/DTE/pry_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16402,600,"PRY","Paraguay","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PRY/BSGM/2016/DTE/pry_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16403,600,"PRY","Paraguay","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PRY/BSGM/2017/DTE/pry_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16404,600,"PRY","Paraguay","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PRY/BSGM/2018/DTE/pry_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16405,600,"PRY","Paraguay","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PRY/BSGM/2019/DTE/pry_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16406,600,"PRY","Paraguay","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PRY/BSGM/2020/DTE/pry_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16407,604,"PER","Peru","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PER/BSGM/2001/Binary/per_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16408,604,"PER","Peru","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PER/BSGM/2001/DTE/per_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16409,604,"PER","Peru","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PER/BSGM/2002/Binary/per_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16410,604,"PER","Peru","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PER/BSGM/2002/DTE/per_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16411,604,"PER","Peru","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PER/BSGM/2003/Binary/per_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16412,604,"PER","Peru","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PER/BSGM/2003/DTE/per_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16413,604,"PER","Peru","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PER/BSGM/2004/Binary/per_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16414,604,"PER","Peru","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PER/BSGM/2004/DTE/per_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16415,604,"PER","Peru","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PER/BSGM/2005/Binary/per_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16416,604,"PER","Peru","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PER/BSGM/2005/DTE/per_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16417,604,"PER","Peru","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PER/BSGM/2006/Binary/per_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16418,604,"PER","Peru","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PER/BSGM/2006/DTE/per_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16419,604,"PER","Peru","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PER/BSGM/2007/Binary/per_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16420,604,"PER","Peru","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PER/BSGM/2007/DTE/per_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16421,604,"PER","Peru","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PER/BSGM/2008/Binary/per_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16422,604,"PER","Peru","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PER/BSGM/2008/DTE/per_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16423,604,"PER","Peru","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PER/BSGM/2009/Binary/per_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16424,604,"PER","Peru","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PER/BSGM/2009/DTE/per_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16425,604,"PER","Peru","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PER/BSGM/2010/Binary/per_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16426,604,"PER","Peru","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PER/BSGM/2010/DTE/per_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16427,604,"PER","Peru","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PER/BSGM/2011/Binary/per_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16428,604,"PER","Peru","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PER/BSGM/2011/DTE/per_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16429,604,"PER","Peru","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PER/BSGM/2013/Binary/per_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16430,604,"PER","Peru","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PER/BSGM/2013/DTE/per_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16431,604,"PER","Peru","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PER/BSGM/2015/DTE/per_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16432,604,"PER","Peru","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PER/BSGM/2016/DTE/per_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16433,604,"PER","Peru","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PER/BSGM/2017/DTE/per_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16434,604,"PER","Peru","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PER/BSGM/2018/DTE/per_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16435,604,"PER","Peru","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PER/BSGM/2019/DTE/per_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16436,604,"PER","Peru","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PER/BSGM/2020/DTE/per_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16437,608,"PHL","Philippines","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PHL/BSGM/2001/Binary/phl_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16438,608,"PHL","Philippines","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PHL/BSGM/2001/DTE/phl_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16439,608,"PHL","Philippines","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PHL/BSGM/2002/Binary/phl_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16440,608,"PHL","Philippines","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PHL/BSGM/2002/DTE/phl_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16441,608,"PHL","Philippines","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PHL/BSGM/2003/Binary/phl_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16442,608,"PHL","Philippines","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PHL/BSGM/2003/DTE/phl_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16443,608,"PHL","Philippines","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PHL/BSGM/2004/Binary/phl_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16444,608,"PHL","Philippines","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PHL/BSGM/2004/DTE/phl_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16445,608,"PHL","Philippines","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PHL/BSGM/2005/Binary/phl_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16446,608,"PHL","Philippines","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PHL/BSGM/2005/DTE/phl_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16447,608,"PHL","Philippines","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PHL/BSGM/2006/Binary/phl_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16448,608,"PHL","Philippines","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PHL/BSGM/2006/DTE/phl_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16449,608,"PHL","Philippines","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PHL/BSGM/2007/Binary/phl_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16450,608,"PHL","Philippines","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PHL/BSGM/2007/DTE/phl_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16451,608,"PHL","Philippines","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PHL/BSGM/2008/Binary/phl_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16452,608,"PHL","Philippines","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PHL/BSGM/2008/DTE/phl_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16453,608,"PHL","Philippines","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PHL/BSGM/2009/Binary/phl_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16454,608,"PHL","Philippines","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PHL/BSGM/2009/DTE/phl_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16455,608,"PHL","Philippines","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PHL/BSGM/2010/Binary/phl_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16456,608,"PHL","Philippines","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PHL/BSGM/2010/DTE/phl_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16457,608,"PHL","Philippines","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PHL/BSGM/2011/Binary/phl_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16458,608,"PHL","Philippines","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PHL/BSGM/2011/DTE/phl_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16459,608,"PHL","Philippines","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PHL/BSGM/2013/Binary/phl_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16460,608,"PHL","Philippines","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PHL/BSGM/2013/DTE/phl_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16461,608,"PHL","Philippines","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PHL/BSGM/2015/DTE/phl_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16462,608,"PHL","Philippines","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PHL/BSGM/2016/DTE/phl_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16463,608,"PHL","Philippines","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PHL/BSGM/2017/DTE/phl_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16464,608,"PHL","Philippines","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PHL/BSGM/2018/DTE/phl_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16465,608,"PHL","Philippines","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PHL/BSGM/2019/DTE/phl_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16466,608,"PHL","Philippines","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PHL/BSGM/2020/DTE/phl_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16467,612,"PCN","Pitcairn Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PCN/BSGM/2001/Binary/pcn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16468,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PCN/BSGM/2001/DTE/pcn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16469,612,"PCN","Pitcairn Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PCN/BSGM/2002/Binary/pcn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16470,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PCN/BSGM/2002/DTE/pcn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16471,612,"PCN","Pitcairn Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PCN/BSGM/2003/Binary/pcn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16472,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PCN/BSGM/2003/DTE/pcn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16473,612,"PCN","Pitcairn Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PCN/BSGM/2004/Binary/pcn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16474,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PCN/BSGM/2004/DTE/pcn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16475,612,"PCN","Pitcairn Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PCN/BSGM/2005/Binary/pcn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16476,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PCN/BSGM/2005/DTE/pcn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16477,612,"PCN","Pitcairn Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PCN/BSGM/2006/Binary/pcn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16478,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PCN/BSGM/2006/DTE/pcn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16479,612,"PCN","Pitcairn Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PCN/BSGM/2007/Binary/pcn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16480,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PCN/BSGM/2007/DTE/pcn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16481,612,"PCN","Pitcairn Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PCN/BSGM/2008/Binary/pcn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16482,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PCN/BSGM/2008/DTE/pcn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16483,612,"PCN","Pitcairn Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PCN/BSGM/2009/Binary/pcn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16484,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PCN/BSGM/2009/DTE/pcn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16485,612,"PCN","Pitcairn Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PCN/BSGM/2010/Binary/pcn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16486,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PCN/BSGM/2010/DTE/pcn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16487,612,"PCN","Pitcairn Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PCN/BSGM/2011/Binary/pcn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16488,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PCN/BSGM/2011/DTE/pcn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16489,612,"PCN","Pitcairn Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PCN/BSGM/2013/Binary/pcn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16490,612,"PCN","Pitcairn Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PCN/BSGM/2013/DTE/pcn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16491,612,"PCN","Pitcairn Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PCN/BSGM/2015/DTE/pcn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16492,612,"PCN","Pitcairn Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PCN/BSGM/2016/DTE/pcn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16493,612,"PCN","Pitcairn Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PCN/BSGM/2017/DTE/pcn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16494,612,"PCN","Pitcairn Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PCN/BSGM/2018/DTE/pcn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16495,612,"PCN","Pitcairn Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PCN/BSGM/2019/DTE/pcn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16496,612,"PCN","Pitcairn Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PCN/BSGM/2020/DTE/pcn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16497,616,"POL","Poland","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/POL/BSGM/2001/Binary/pol_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16498,616,"POL","Poland","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/POL/BSGM/2001/DTE/pol_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16499,616,"POL","Poland","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/POL/BSGM/2002/Binary/pol_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16500,616,"POL","Poland","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/POL/BSGM/2002/DTE/pol_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16501,616,"POL","Poland","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/POL/BSGM/2003/Binary/pol_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16502,616,"POL","Poland","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/POL/BSGM/2003/DTE/pol_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16503,616,"POL","Poland","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/POL/BSGM/2004/Binary/pol_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16504,616,"POL","Poland","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/POL/BSGM/2004/DTE/pol_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16505,616,"POL","Poland","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/POL/BSGM/2005/Binary/pol_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16506,616,"POL","Poland","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/POL/BSGM/2005/DTE/pol_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16507,616,"POL","Poland","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/POL/BSGM/2006/Binary/pol_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16508,616,"POL","Poland","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/POL/BSGM/2006/DTE/pol_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16509,616,"POL","Poland","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/POL/BSGM/2007/Binary/pol_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16510,616,"POL","Poland","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/POL/BSGM/2007/DTE/pol_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16511,616,"POL","Poland","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/POL/BSGM/2008/Binary/pol_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16512,616,"POL","Poland","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/POL/BSGM/2008/DTE/pol_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16513,616,"POL","Poland","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/POL/BSGM/2009/Binary/pol_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16514,616,"POL","Poland","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/POL/BSGM/2009/DTE/pol_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16515,616,"POL","Poland","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/POL/BSGM/2010/Binary/pol_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16516,616,"POL","Poland","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/POL/BSGM/2010/DTE/pol_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16517,616,"POL","Poland","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/POL/BSGM/2011/Binary/pol_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16518,616,"POL","Poland","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/POL/BSGM/2011/DTE/pol_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16519,616,"POL","Poland","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/POL/BSGM/2013/Binary/pol_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16520,616,"POL","Poland","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/POL/BSGM/2013/DTE/pol_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16521,616,"POL","Poland","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/POL/BSGM/2015/DTE/pol_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16522,616,"POL","Poland","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/POL/BSGM/2016/DTE/pol_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16523,616,"POL","Poland","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/POL/BSGM/2017/DTE/pol_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16524,616,"POL","Poland","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/POL/BSGM/2018/DTE/pol_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16525,616,"POL","Poland","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/POL/BSGM/2019/DTE/pol_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16526,616,"POL","Poland","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/POL/BSGM/2020/DTE/pol_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16527,620,"PRT","Portugal","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PRT/BSGM/2001/Binary/prt_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16528,620,"PRT","Portugal","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PRT/BSGM/2001/DTE/prt_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16529,620,"PRT","Portugal","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PRT/BSGM/2002/Binary/prt_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16530,620,"PRT","Portugal","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PRT/BSGM/2002/DTE/prt_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16531,620,"PRT","Portugal","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PRT/BSGM/2003/Binary/prt_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16532,620,"PRT","Portugal","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PRT/BSGM/2003/DTE/prt_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16533,620,"PRT","Portugal","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PRT/BSGM/2004/Binary/prt_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16534,620,"PRT","Portugal","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PRT/BSGM/2004/DTE/prt_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16535,620,"PRT","Portugal","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PRT/BSGM/2005/Binary/prt_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16536,620,"PRT","Portugal","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PRT/BSGM/2005/DTE/prt_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16537,620,"PRT","Portugal","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PRT/BSGM/2006/Binary/prt_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16538,620,"PRT","Portugal","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PRT/BSGM/2006/DTE/prt_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16539,620,"PRT","Portugal","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PRT/BSGM/2007/Binary/prt_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16540,620,"PRT","Portugal","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PRT/BSGM/2007/DTE/prt_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16541,620,"PRT","Portugal","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PRT/BSGM/2008/Binary/prt_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16542,620,"PRT","Portugal","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PRT/BSGM/2008/DTE/prt_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16543,620,"PRT","Portugal","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PRT/BSGM/2009/Binary/prt_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16544,620,"PRT","Portugal","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PRT/BSGM/2009/DTE/prt_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16545,620,"PRT","Portugal","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PRT/BSGM/2010/Binary/prt_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16546,620,"PRT","Portugal","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PRT/BSGM/2010/DTE/prt_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16547,620,"PRT","Portugal","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PRT/BSGM/2011/Binary/prt_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16548,620,"PRT","Portugal","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PRT/BSGM/2011/DTE/prt_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16549,620,"PRT","Portugal","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PRT/BSGM/2013/Binary/prt_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16550,620,"PRT","Portugal","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PRT/BSGM/2013/DTE/prt_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16551,620,"PRT","Portugal","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PRT/BSGM/2015/DTE/prt_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16552,620,"PRT","Portugal","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PRT/BSGM/2016/DTE/prt_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16553,620,"PRT","Portugal","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PRT/BSGM/2017/DTE/prt_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16554,620,"PRT","Portugal","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PRT/BSGM/2018/DTE/prt_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16555,620,"PRT","Portugal","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PRT/BSGM/2019/DTE/prt_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16556,620,"PRT","Portugal","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PRT/BSGM/2020/DTE/prt_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16557,624,"GNB","Guinea-Bissau","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GNB/BSGM/2001/Binary/gnb_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16558,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GNB/BSGM/2001/DTE/gnb_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16559,624,"GNB","Guinea-Bissau","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GNB/BSGM/2002/Binary/gnb_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16560,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GNB/BSGM/2002/DTE/gnb_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16561,624,"GNB","Guinea-Bissau","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GNB/BSGM/2003/Binary/gnb_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16562,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GNB/BSGM/2003/DTE/gnb_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16563,624,"GNB","Guinea-Bissau","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GNB/BSGM/2004/Binary/gnb_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16564,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GNB/BSGM/2004/DTE/gnb_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16565,624,"GNB","Guinea-Bissau","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GNB/BSGM/2005/Binary/gnb_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16566,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GNB/BSGM/2005/DTE/gnb_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16567,624,"GNB","Guinea-Bissau","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GNB/BSGM/2006/Binary/gnb_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16568,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GNB/BSGM/2006/DTE/gnb_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16569,624,"GNB","Guinea-Bissau","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GNB/BSGM/2007/Binary/gnb_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16570,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GNB/BSGM/2007/DTE/gnb_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16571,624,"GNB","Guinea-Bissau","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GNB/BSGM/2008/Binary/gnb_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16572,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GNB/BSGM/2008/DTE/gnb_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16573,624,"GNB","Guinea-Bissau","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GNB/BSGM/2009/Binary/gnb_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16574,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GNB/BSGM/2009/DTE/gnb_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16575,624,"GNB","Guinea-Bissau","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GNB/BSGM/2010/Binary/gnb_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16576,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GNB/BSGM/2010/DTE/gnb_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16577,624,"GNB","Guinea-Bissau","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GNB/BSGM/2011/Binary/gnb_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16578,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GNB/BSGM/2011/DTE/gnb_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16579,624,"GNB","Guinea-Bissau","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GNB/BSGM/2013/Binary/gnb_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16580,624,"GNB","Guinea-Bissau","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GNB/BSGM/2013/DTE/gnb_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16581,624,"GNB","Guinea-Bissau","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GNB/BSGM/2015/DTE/gnb_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16582,624,"GNB","Guinea-Bissau","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GNB/BSGM/2016/DTE/gnb_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16583,624,"GNB","Guinea-Bissau","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GNB/BSGM/2017/DTE/gnb_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16584,624,"GNB","Guinea-Bissau","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GNB/BSGM/2018/DTE/gnb_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16585,624,"GNB","Guinea-Bissau","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GNB/BSGM/2019/DTE/gnb_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16586,624,"GNB","Guinea-Bissau","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GNB/BSGM/2020/DTE/gnb_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16587,626,"TLS","East Timor","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TLS/BSGM/2001/Binary/tls_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16588,626,"TLS","East Timor","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TLS/BSGM/2001/DTE/tls_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16589,626,"TLS","East Timor","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TLS/BSGM/2002/Binary/tls_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16590,626,"TLS","East Timor","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TLS/BSGM/2002/DTE/tls_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16591,626,"TLS","East Timor","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TLS/BSGM/2003/Binary/tls_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16592,626,"TLS","East Timor","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TLS/BSGM/2003/DTE/tls_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16593,626,"TLS","East Timor","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TLS/BSGM/2004/Binary/tls_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16594,626,"TLS","East Timor","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TLS/BSGM/2004/DTE/tls_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16595,626,"TLS","East Timor","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TLS/BSGM/2005/Binary/tls_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16596,626,"TLS","East Timor","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TLS/BSGM/2005/DTE/tls_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16597,626,"TLS","East Timor","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TLS/BSGM/2006/Binary/tls_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16598,626,"TLS","East Timor","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TLS/BSGM/2006/DTE/tls_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16599,626,"TLS","East Timor","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TLS/BSGM/2007/Binary/tls_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16600,626,"TLS","East Timor","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TLS/BSGM/2007/DTE/tls_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16601,626,"TLS","East Timor","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TLS/BSGM/2008/Binary/tls_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16602,626,"TLS","East Timor","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TLS/BSGM/2008/DTE/tls_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16603,626,"TLS","East Timor","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TLS/BSGM/2009/Binary/tls_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16604,626,"TLS","East Timor","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TLS/BSGM/2009/DTE/tls_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16605,626,"TLS","East Timor","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TLS/BSGM/2010/Binary/tls_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16606,626,"TLS","East Timor","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TLS/BSGM/2010/DTE/tls_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16607,626,"TLS","East Timor","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TLS/BSGM/2011/Binary/tls_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16608,626,"TLS","East Timor","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TLS/BSGM/2011/DTE/tls_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16609,626,"TLS","East Timor","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TLS/BSGM/2013/Binary/tls_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16610,626,"TLS","East Timor","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TLS/BSGM/2013/DTE/tls_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16611,626,"TLS","East Timor","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TLS/BSGM/2015/DTE/tls_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16612,626,"TLS","East Timor","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TLS/BSGM/2016/DTE/tls_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16613,626,"TLS","East Timor","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TLS/BSGM/2017/DTE/tls_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16614,626,"TLS","East Timor","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TLS/BSGM/2018/DTE/tls_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16615,626,"TLS","East Timor","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TLS/BSGM/2019/DTE/tls_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16616,626,"TLS","East Timor","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TLS/BSGM/2020/DTE/tls_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16617,630,"PRI","Puerto Rico","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PRI/BSGM/2001/Binary/pri_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16618,630,"PRI","Puerto Rico","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/PRI/BSGM/2001/DTE/pri_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16619,630,"PRI","Puerto Rico","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PRI/BSGM/2002/Binary/pri_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16620,630,"PRI","Puerto Rico","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/PRI/BSGM/2002/DTE/pri_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16621,630,"PRI","Puerto Rico","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PRI/BSGM/2003/Binary/pri_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16622,630,"PRI","Puerto Rico","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/PRI/BSGM/2003/DTE/pri_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16623,630,"PRI","Puerto Rico","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PRI/BSGM/2004/Binary/pri_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16624,630,"PRI","Puerto Rico","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/PRI/BSGM/2004/DTE/pri_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16625,630,"PRI","Puerto Rico","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PRI/BSGM/2005/Binary/pri_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16626,630,"PRI","Puerto Rico","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/PRI/BSGM/2005/DTE/pri_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16627,630,"PRI","Puerto Rico","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PRI/BSGM/2006/Binary/pri_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16628,630,"PRI","Puerto Rico","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/PRI/BSGM/2006/DTE/pri_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16629,630,"PRI","Puerto Rico","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PRI/BSGM/2007/Binary/pri_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16630,630,"PRI","Puerto Rico","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/PRI/BSGM/2007/DTE/pri_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16631,630,"PRI","Puerto Rico","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PRI/BSGM/2008/Binary/pri_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16632,630,"PRI","Puerto Rico","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/PRI/BSGM/2008/DTE/pri_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16633,630,"PRI","Puerto Rico","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PRI/BSGM/2009/Binary/pri_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16634,630,"PRI","Puerto Rico","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/PRI/BSGM/2009/DTE/pri_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16635,630,"PRI","Puerto Rico","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PRI/BSGM/2010/Binary/pri_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16636,630,"PRI","Puerto Rico","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/PRI/BSGM/2010/DTE/pri_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16637,630,"PRI","Puerto Rico","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PRI/BSGM/2011/Binary/pri_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16638,630,"PRI","Puerto Rico","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/PRI/BSGM/2011/DTE/pri_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16639,630,"PRI","Puerto Rico","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PRI/BSGM/2013/Binary/pri_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16640,630,"PRI","Puerto Rico","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/PRI/BSGM/2013/DTE/pri_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16641,630,"PRI","Puerto Rico","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/PRI/BSGM/2015/DTE/pri_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16642,630,"PRI","Puerto Rico","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/PRI/BSGM/2016/DTE/pri_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16643,630,"PRI","Puerto Rico","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/PRI/BSGM/2017/DTE/pri_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16644,630,"PRI","Puerto Rico","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/PRI/BSGM/2018/DTE/pri_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16645,630,"PRI","Puerto Rico","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/PRI/BSGM/2019/DTE/pri_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16646,630,"PRI","Puerto Rico","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/PRI/BSGM/2020/DTE/pri_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16647,634,"QAT","Qatar","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/QAT/BSGM/2001/Binary/qat_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16648,634,"QAT","Qatar","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/QAT/BSGM/2001/DTE/qat_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16649,634,"QAT","Qatar","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/QAT/BSGM/2002/Binary/qat_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16650,634,"QAT","Qatar","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/QAT/BSGM/2002/DTE/qat_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16651,634,"QAT","Qatar","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/QAT/BSGM/2003/Binary/qat_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16652,634,"QAT","Qatar","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/QAT/BSGM/2003/DTE/qat_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16653,634,"QAT","Qatar","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/QAT/BSGM/2004/Binary/qat_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16654,634,"QAT","Qatar","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/QAT/BSGM/2004/DTE/qat_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16655,634,"QAT","Qatar","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/QAT/BSGM/2005/Binary/qat_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16656,634,"QAT","Qatar","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/QAT/BSGM/2005/DTE/qat_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16657,634,"QAT","Qatar","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/QAT/BSGM/2006/Binary/qat_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16658,634,"QAT","Qatar","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/QAT/BSGM/2006/DTE/qat_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16659,634,"QAT","Qatar","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/QAT/BSGM/2007/Binary/qat_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16660,634,"QAT","Qatar","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/QAT/BSGM/2007/DTE/qat_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16661,634,"QAT","Qatar","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/QAT/BSGM/2008/Binary/qat_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16662,634,"QAT","Qatar","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/QAT/BSGM/2008/DTE/qat_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16663,634,"QAT","Qatar","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/QAT/BSGM/2009/Binary/qat_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16664,634,"QAT","Qatar","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/QAT/BSGM/2009/DTE/qat_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16665,634,"QAT","Qatar","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/QAT/BSGM/2010/Binary/qat_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16666,634,"QAT","Qatar","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/QAT/BSGM/2010/DTE/qat_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16667,634,"QAT","Qatar","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/QAT/BSGM/2011/Binary/qat_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16668,634,"QAT","Qatar","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/QAT/BSGM/2011/DTE/qat_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16669,634,"QAT","Qatar","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/QAT/BSGM/2013/Binary/qat_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16670,634,"QAT","Qatar","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/QAT/BSGM/2013/DTE/qat_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16671,634,"QAT","Qatar","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/QAT/BSGM/2015/DTE/qat_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16672,634,"QAT","Qatar","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/QAT/BSGM/2016/DTE/qat_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16673,634,"QAT","Qatar","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/QAT/BSGM/2017/DTE/qat_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16674,634,"QAT","Qatar","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/QAT/BSGM/2018/DTE/qat_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16675,634,"QAT","Qatar","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/QAT/BSGM/2019/DTE/qat_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16676,634,"QAT","Qatar","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/QAT/BSGM/2020/DTE/qat_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16677,638,"REU","Reunion","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/REU/BSGM/2001/Binary/reu_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16678,638,"REU","Reunion","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/REU/BSGM/2001/DTE/reu_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16679,638,"REU","Reunion","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/REU/BSGM/2002/Binary/reu_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16680,638,"REU","Reunion","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/REU/BSGM/2002/DTE/reu_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16681,638,"REU","Reunion","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/REU/BSGM/2003/Binary/reu_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16682,638,"REU","Reunion","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/REU/BSGM/2003/DTE/reu_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16683,638,"REU","Reunion","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/REU/BSGM/2004/Binary/reu_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16684,638,"REU","Reunion","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/REU/BSGM/2004/DTE/reu_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16685,638,"REU","Reunion","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/REU/BSGM/2005/Binary/reu_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16686,638,"REU","Reunion","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/REU/BSGM/2005/DTE/reu_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16687,638,"REU","Reunion","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/REU/BSGM/2006/Binary/reu_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16688,638,"REU","Reunion","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/REU/BSGM/2006/DTE/reu_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16689,638,"REU","Reunion","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/REU/BSGM/2007/Binary/reu_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16690,638,"REU","Reunion","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/REU/BSGM/2007/DTE/reu_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16691,638,"REU","Reunion","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/REU/BSGM/2008/Binary/reu_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16692,638,"REU","Reunion","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/REU/BSGM/2008/DTE/reu_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16693,638,"REU","Reunion","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/REU/BSGM/2009/Binary/reu_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16694,638,"REU","Reunion","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/REU/BSGM/2009/DTE/reu_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16695,638,"REU","Reunion","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/REU/BSGM/2010/Binary/reu_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16696,638,"REU","Reunion","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/REU/BSGM/2010/DTE/reu_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16697,638,"REU","Reunion","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/REU/BSGM/2011/Binary/reu_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16698,638,"REU","Reunion","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/REU/BSGM/2011/DTE/reu_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16699,638,"REU","Reunion","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/REU/BSGM/2013/Binary/reu_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16700,638,"REU","Reunion","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/REU/BSGM/2013/DTE/reu_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16701,638,"REU","Reunion","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/REU/BSGM/2015/DTE/reu_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16702,638,"REU","Reunion","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/REU/BSGM/2016/DTE/reu_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16703,638,"REU","Reunion","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/REU/BSGM/2017/DTE/reu_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16704,638,"REU","Reunion","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/REU/BSGM/2018/DTE/reu_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16705,638,"REU","Reunion","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/REU/BSGM/2019/DTE/reu_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16706,638,"REU","Reunion","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/REU/BSGM/2020/DTE/reu_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16707,642,"ROU","Romania","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ROU/BSGM/2001/Binary/rou_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16708,642,"ROU","Romania","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ROU/BSGM/2001/DTE/rou_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16709,642,"ROU","Romania","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ROU/BSGM/2002/Binary/rou_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16710,642,"ROU","Romania","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ROU/BSGM/2002/DTE/rou_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16711,642,"ROU","Romania","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ROU/BSGM/2003/Binary/rou_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16712,642,"ROU","Romania","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ROU/BSGM/2003/DTE/rou_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16713,642,"ROU","Romania","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ROU/BSGM/2004/Binary/rou_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16714,642,"ROU","Romania","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ROU/BSGM/2004/DTE/rou_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16715,642,"ROU","Romania","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ROU/BSGM/2005/Binary/rou_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16716,642,"ROU","Romania","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ROU/BSGM/2005/DTE/rou_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16717,642,"ROU","Romania","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ROU/BSGM/2006/Binary/rou_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16718,642,"ROU","Romania","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ROU/BSGM/2006/DTE/rou_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16719,642,"ROU","Romania","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ROU/BSGM/2007/Binary/rou_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16720,642,"ROU","Romania","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ROU/BSGM/2007/DTE/rou_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16721,642,"ROU","Romania","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ROU/BSGM/2008/Binary/rou_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16722,642,"ROU","Romania","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ROU/BSGM/2008/DTE/rou_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16723,642,"ROU","Romania","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ROU/BSGM/2009/Binary/rou_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16724,642,"ROU","Romania","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ROU/BSGM/2009/DTE/rou_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16725,642,"ROU","Romania","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ROU/BSGM/2010/Binary/rou_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16726,642,"ROU","Romania","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ROU/BSGM/2010/DTE/rou_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16727,642,"ROU","Romania","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ROU/BSGM/2011/Binary/rou_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16728,642,"ROU","Romania","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ROU/BSGM/2011/DTE/rou_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16729,642,"ROU","Romania","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ROU/BSGM/2013/Binary/rou_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16730,642,"ROU","Romania","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ROU/BSGM/2013/DTE/rou_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16731,642,"ROU","Romania","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ROU/BSGM/2015/DTE/rou_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16732,642,"ROU","Romania","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ROU/BSGM/2016/DTE/rou_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16733,642,"ROU","Romania","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ROU/BSGM/2017/DTE/rou_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16734,642,"ROU","Romania","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ROU/BSGM/2018/DTE/rou_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16735,642,"ROU","Romania","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ROU/BSGM/2019/DTE/rou_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16736,642,"ROU","Romania","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ROU/BSGM/2020/DTE/rou_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16737,646,"RWA","Rwanda","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/RWA/BSGM/2001/Binary/rwa_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16738,646,"RWA","Rwanda","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/RWA/BSGM/2001/DTE/rwa_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16739,646,"RWA","Rwanda","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/RWA/BSGM/2002/Binary/rwa_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16740,646,"RWA","Rwanda","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/RWA/BSGM/2002/DTE/rwa_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16741,646,"RWA","Rwanda","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/RWA/BSGM/2003/Binary/rwa_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16742,646,"RWA","Rwanda","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/RWA/BSGM/2003/DTE/rwa_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16743,646,"RWA","Rwanda","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/RWA/BSGM/2004/Binary/rwa_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16744,646,"RWA","Rwanda","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/RWA/BSGM/2004/DTE/rwa_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16745,646,"RWA","Rwanda","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/RWA/BSGM/2005/Binary/rwa_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16746,646,"RWA","Rwanda","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/RWA/BSGM/2005/DTE/rwa_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16747,646,"RWA","Rwanda","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/RWA/BSGM/2006/Binary/rwa_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16748,646,"RWA","Rwanda","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/RWA/BSGM/2006/DTE/rwa_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16749,646,"RWA","Rwanda","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/RWA/BSGM/2007/Binary/rwa_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16750,646,"RWA","Rwanda","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/RWA/BSGM/2007/DTE/rwa_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16751,646,"RWA","Rwanda","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/RWA/BSGM/2008/Binary/rwa_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16752,646,"RWA","Rwanda","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/RWA/BSGM/2008/DTE/rwa_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16753,646,"RWA","Rwanda","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/RWA/BSGM/2009/Binary/rwa_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16754,646,"RWA","Rwanda","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/RWA/BSGM/2009/DTE/rwa_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16755,646,"RWA","Rwanda","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/RWA/BSGM/2010/Binary/rwa_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16756,646,"RWA","Rwanda","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/RWA/BSGM/2010/DTE/rwa_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16757,646,"RWA","Rwanda","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/RWA/BSGM/2011/Binary/rwa_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16758,646,"RWA","Rwanda","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/RWA/BSGM/2011/DTE/rwa_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16759,646,"RWA","Rwanda","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/RWA/BSGM/2013/Binary/rwa_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16760,646,"RWA","Rwanda","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/RWA/BSGM/2013/DTE/rwa_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16761,646,"RWA","Rwanda","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/RWA/BSGM/2015/DTE/rwa_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16762,646,"RWA","Rwanda","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/RWA/BSGM/2016/DTE/rwa_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16763,646,"RWA","Rwanda","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/RWA/BSGM/2017/DTE/rwa_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16764,646,"RWA","Rwanda","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/RWA/BSGM/2018/DTE/rwa_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16765,646,"RWA","Rwanda","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/RWA/BSGM/2019/DTE/rwa_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16766,646,"RWA","Rwanda","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/RWA/BSGM/2020/DTE/rwa_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16767,652,"BLM","Saint Barthelemy","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BLM/BSGM/2001/Binary/blm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16768,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BLM/BSGM/2001/DTE/blm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16769,652,"BLM","Saint Barthelemy","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BLM/BSGM/2002/Binary/blm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16770,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BLM/BSGM/2002/DTE/blm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16771,652,"BLM","Saint Barthelemy","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BLM/BSGM/2003/Binary/blm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16772,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BLM/BSGM/2003/DTE/blm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16773,652,"BLM","Saint Barthelemy","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BLM/BSGM/2004/Binary/blm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16774,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BLM/BSGM/2004/DTE/blm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16775,652,"BLM","Saint Barthelemy","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BLM/BSGM/2005/Binary/blm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16776,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BLM/BSGM/2005/DTE/blm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16777,652,"BLM","Saint Barthelemy","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BLM/BSGM/2006/Binary/blm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16778,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BLM/BSGM/2006/DTE/blm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16779,652,"BLM","Saint Barthelemy","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BLM/BSGM/2007/Binary/blm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16780,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BLM/BSGM/2007/DTE/blm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16781,652,"BLM","Saint Barthelemy","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BLM/BSGM/2008/Binary/blm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16782,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BLM/BSGM/2008/DTE/blm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16783,652,"BLM","Saint Barthelemy","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BLM/BSGM/2009/Binary/blm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16784,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BLM/BSGM/2009/DTE/blm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16785,652,"BLM","Saint Barthelemy","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BLM/BSGM/2010/Binary/blm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16786,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BLM/BSGM/2010/DTE/blm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16787,652,"BLM","Saint Barthelemy","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BLM/BSGM/2011/Binary/blm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16788,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BLM/BSGM/2011/DTE/blm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16789,652,"BLM","Saint Barthelemy","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BLM/BSGM/2013/Binary/blm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16790,652,"BLM","Saint Barthelemy","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BLM/BSGM/2013/DTE/blm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16791,652,"BLM","Saint Barthelemy","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BLM/BSGM/2015/DTE/blm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16792,652,"BLM","Saint Barthelemy","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BLM/BSGM/2016/DTE/blm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16793,652,"BLM","Saint Barthelemy","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BLM/BSGM/2017/DTE/blm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16794,652,"BLM","Saint Barthelemy","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BLM/BSGM/2018/DTE/blm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16795,652,"BLM","Saint Barthelemy","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BLM/BSGM/2019/DTE/blm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16796,652,"BLM","Saint Barthelemy","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BLM/BSGM/2020/DTE/blm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16797,654,"SHN","Saint Helena","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SHN/BSGM/2001/Binary/shn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16798,654,"SHN","Saint Helena","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SHN/BSGM/2001/DTE/shn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16799,654,"SHN","Saint Helena","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SHN/BSGM/2002/Binary/shn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16800,654,"SHN","Saint Helena","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SHN/BSGM/2002/DTE/shn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16801,654,"SHN","Saint Helena","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SHN/BSGM/2003/Binary/shn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16802,654,"SHN","Saint Helena","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SHN/BSGM/2003/DTE/shn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16803,654,"SHN","Saint Helena","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SHN/BSGM/2004/Binary/shn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16804,654,"SHN","Saint Helena","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SHN/BSGM/2004/DTE/shn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16805,654,"SHN","Saint Helena","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SHN/BSGM/2005/Binary/shn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16806,654,"SHN","Saint Helena","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SHN/BSGM/2005/DTE/shn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16807,654,"SHN","Saint Helena","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SHN/BSGM/2006/Binary/shn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16808,654,"SHN","Saint Helena","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SHN/BSGM/2006/DTE/shn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16809,654,"SHN","Saint Helena","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SHN/BSGM/2007/Binary/shn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16810,654,"SHN","Saint Helena","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SHN/BSGM/2007/DTE/shn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16811,654,"SHN","Saint Helena","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SHN/BSGM/2008/Binary/shn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16812,654,"SHN","Saint Helena","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SHN/BSGM/2008/DTE/shn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16813,654,"SHN","Saint Helena","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SHN/BSGM/2009/Binary/shn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16814,654,"SHN","Saint Helena","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SHN/BSGM/2009/DTE/shn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16815,654,"SHN","Saint Helena","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SHN/BSGM/2010/Binary/shn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16816,654,"SHN","Saint Helena","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SHN/BSGM/2010/DTE/shn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16817,654,"SHN","Saint Helena","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SHN/BSGM/2011/Binary/shn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16818,654,"SHN","Saint Helena","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SHN/BSGM/2011/DTE/shn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16819,654,"SHN","Saint Helena","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SHN/BSGM/2013/Binary/shn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16820,654,"SHN","Saint Helena","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SHN/BSGM/2013/DTE/shn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16821,654,"SHN","Saint Helena","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SHN/BSGM/2015/DTE/shn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16822,654,"SHN","Saint Helena","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SHN/BSGM/2016/DTE/shn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16823,654,"SHN","Saint Helena","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SHN/BSGM/2017/DTE/shn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16824,654,"SHN","Saint Helena","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SHN/BSGM/2018/DTE/shn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16825,654,"SHN","Saint Helena","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SHN/BSGM/2019/DTE/shn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16826,654,"SHN","Saint Helena","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SHN/BSGM/2020/DTE/shn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16827,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KNA/BSGM/2001/Binary/kna_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16828,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KNA/BSGM/2001/DTE/kna_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16829,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KNA/BSGM/2002/Binary/kna_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16830,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KNA/BSGM/2002/DTE/kna_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16831,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KNA/BSGM/2003/Binary/kna_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16832,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KNA/BSGM/2003/DTE/kna_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16833,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KNA/BSGM/2004/Binary/kna_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16834,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KNA/BSGM/2004/DTE/kna_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16835,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KNA/BSGM/2005/Binary/kna_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16836,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KNA/BSGM/2005/DTE/kna_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16837,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KNA/BSGM/2006/Binary/kna_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16838,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KNA/BSGM/2006/DTE/kna_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16839,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KNA/BSGM/2007/Binary/kna_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16840,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KNA/BSGM/2007/DTE/kna_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16841,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KNA/BSGM/2008/Binary/kna_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16842,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KNA/BSGM/2008/DTE/kna_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16843,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KNA/BSGM/2009/Binary/kna_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16844,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KNA/BSGM/2009/DTE/kna_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16845,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KNA/BSGM/2010/Binary/kna_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16846,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KNA/BSGM/2010/DTE/kna_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16847,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KNA/BSGM/2011/Binary/kna_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16848,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KNA/BSGM/2011/DTE/kna_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16849,659,"KNA","Saint Kitts and Nevis","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KNA/BSGM/2013/Binary/kna_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16850,659,"KNA","Saint Kitts and Nevis","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KNA/BSGM/2013/DTE/kna_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16851,659,"KNA","Saint Kitts and Nevis","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/KNA/BSGM/2015/DTE/kna_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16852,659,"KNA","Saint Kitts and Nevis","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/KNA/BSGM/2016/DTE/kna_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16853,659,"KNA","Saint Kitts and Nevis","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/KNA/BSGM/2017/DTE/kna_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16854,659,"KNA","Saint Kitts and Nevis","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/KNA/BSGM/2018/DTE/kna_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16855,659,"KNA","Saint Kitts and Nevis","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/KNA/BSGM/2019/DTE/kna_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16856,659,"KNA","Saint Kitts and Nevis","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/KNA/BSGM/2020/DTE/kna_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16857,660,"AIA","Anguilla","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AIA/BSGM/2001/Binary/aia_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16858,660,"AIA","Anguilla","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/AIA/BSGM/2001/DTE/aia_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16859,660,"AIA","Anguilla","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AIA/BSGM/2002/Binary/aia_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16860,660,"AIA","Anguilla","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/AIA/BSGM/2002/DTE/aia_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16861,660,"AIA","Anguilla","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AIA/BSGM/2003/Binary/aia_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16862,660,"AIA","Anguilla","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/AIA/BSGM/2003/DTE/aia_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16863,660,"AIA","Anguilla","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AIA/BSGM/2004/Binary/aia_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16864,660,"AIA","Anguilla","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/AIA/BSGM/2004/DTE/aia_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16865,660,"AIA","Anguilla","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AIA/BSGM/2005/Binary/aia_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16866,660,"AIA","Anguilla","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/AIA/BSGM/2005/DTE/aia_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16867,660,"AIA","Anguilla","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AIA/BSGM/2006/Binary/aia_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16868,660,"AIA","Anguilla","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/AIA/BSGM/2006/DTE/aia_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16869,660,"AIA","Anguilla","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AIA/BSGM/2007/Binary/aia_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16870,660,"AIA","Anguilla","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/AIA/BSGM/2007/DTE/aia_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16871,660,"AIA","Anguilla","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AIA/BSGM/2008/Binary/aia_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16872,660,"AIA","Anguilla","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/AIA/BSGM/2008/DTE/aia_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16873,660,"AIA","Anguilla","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AIA/BSGM/2009/Binary/aia_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16874,660,"AIA","Anguilla","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/AIA/BSGM/2009/DTE/aia_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16875,660,"AIA","Anguilla","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AIA/BSGM/2010/Binary/aia_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16876,660,"AIA","Anguilla","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/AIA/BSGM/2010/DTE/aia_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16877,660,"AIA","Anguilla","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AIA/BSGM/2011/Binary/aia_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16878,660,"AIA","Anguilla","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/AIA/BSGM/2011/DTE/aia_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16879,660,"AIA","Anguilla","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AIA/BSGM/2013/Binary/aia_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16880,660,"AIA","Anguilla","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/AIA/BSGM/2013/DTE/aia_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16881,660,"AIA","Anguilla","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/AIA/BSGM/2015/DTE/aia_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16882,660,"AIA","Anguilla","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/AIA/BSGM/2016/DTE/aia_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16883,660,"AIA","Anguilla","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/AIA/BSGM/2017/DTE/aia_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16884,660,"AIA","Anguilla","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/AIA/BSGM/2018/DTE/aia_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16885,660,"AIA","Anguilla","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/AIA/BSGM/2019/DTE/aia_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16886,660,"AIA","Anguilla","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/AIA/BSGM/2020/DTE/aia_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16887,662,"LCA","Saint Lucia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LCA/BSGM/2001/Binary/lca_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16888,662,"LCA","Saint Lucia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/LCA/BSGM/2001/DTE/lca_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16889,662,"LCA","Saint Lucia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LCA/BSGM/2002/Binary/lca_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16890,662,"LCA","Saint Lucia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/LCA/BSGM/2002/DTE/lca_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16891,662,"LCA","Saint Lucia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LCA/BSGM/2003/Binary/lca_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16892,662,"LCA","Saint Lucia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/LCA/BSGM/2003/DTE/lca_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16893,662,"LCA","Saint Lucia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LCA/BSGM/2004/Binary/lca_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16894,662,"LCA","Saint Lucia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/LCA/BSGM/2004/DTE/lca_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16895,662,"LCA","Saint Lucia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LCA/BSGM/2005/Binary/lca_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16896,662,"LCA","Saint Lucia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/LCA/BSGM/2005/DTE/lca_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16897,662,"LCA","Saint Lucia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LCA/BSGM/2006/Binary/lca_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16898,662,"LCA","Saint Lucia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/LCA/BSGM/2006/DTE/lca_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16899,662,"LCA","Saint Lucia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LCA/BSGM/2007/Binary/lca_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16900,662,"LCA","Saint Lucia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/LCA/BSGM/2007/DTE/lca_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16901,662,"LCA","Saint Lucia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LCA/BSGM/2008/Binary/lca_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16902,662,"LCA","Saint Lucia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/LCA/BSGM/2008/DTE/lca_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16903,662,"LCA","Saint Lucia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LCA/BSGM/2009/Binary/lca_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16904,662,"LCA","Saint Lucia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/LCA/BSGM/2009/DTE/lca_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16905,662,"LCA","Saint Lucia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LCA/BSGM/2010/Binary/lca_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16906,662,"LCA","Saint Lucia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/LCA/BSGM/2010/DTE/lca_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16907,662,"LCA","Saint Lucia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LCA/BSGM/2011/Binary/lca_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16908,662,"LCA","Saint Lucia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/LCA/BSGM/2011/DTE/lca_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16909,662,"LCA","Saint Lucia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LCA/BSGM/2013/Binary/lca_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16910,662,"LCA","Saint Lucia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/LCA/BSGM/2013/DTE/lca_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16911,662,"LCA","Saint Lucia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/LCA/BSGM/2015/DTE/lca_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16912,662,"LCA","Saint Lucia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/LCA/BSGM/2016/DTE/lca_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16913,662,"LCA","Saint Lucia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/LCA/BSGM/2017/DTE/lca_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16914,662,"LCA","Saint Lucia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/LCA/BSGM/2018/DTE/lca_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16915,662,"LCA","Saint Lucia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/LCA/BSGM/2019/DTE/lca_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16916,662,"LCA","Saint Lucia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/LCA/BSGM/2020/DTE/lca_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16917,663,"MAF","Saint Martin (French part)","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MAF/BSGM/2001/Binary/maf_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16918,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MAF/BSGM/2001/DTE/maf_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16919,663,"MAF","Saint Martin (French part)","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MAF/BSGM/2002/Binary/maf_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16920,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MAF/BSGM/2002/DTE/maf_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16921,663,"MAF","Saint Martin (French part)","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MAF/BSGM/2003/Binary/maf_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16922,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MAF/BSGM/2003/DTE/maf_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16923,663,"MAF","Saint Martin (French part)","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MAF/BSGM/2004/Binary/maf_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16924,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MAF/BSGM/2004/DTE/maf_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16925,663,"MAF","Saint Martin (French part)","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MAF/BSGM/2005/Binary/maf_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16926,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MAF/BSGM/2005/DTE/maf_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16927,663,"MAF","Saint Martin (French part)","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MAF/BSGM/2006/Binary/maf_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16928,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MAF/BSGM/2006/DTE/maf_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16929,663,"MAF","Saint Martin (French part)","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MAF/BSGM/2007/Binary/maf_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16930,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MAF/BSGM/2007/DTE/maf_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16931,663,"MAF","Saint Martin (French part)","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MAF/BSGM/2008/Binary/maf_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16932,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MAF/BSGM/2008/DTE/maf_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16933,663,"MAF","Saint Martin (French part)","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MAF/BSGM/2009/Binary/maf_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16934,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MAF/BSGM/2009/DTE/maf_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16935,663,"MAF","Saint Martin (French part)","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MAF/BSGM/2010/Binary/maf_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16936,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MAF/BSGM/2010/DTE/maf_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16937,663,"MAF","Saint Martin (French part)","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MAF/BSGM/2011/Binary/maf_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16938,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MAF/BSGM/2011/DTE/maf_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16939,663,"MAF","Saint Martin (French part)","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MAF/BSGM/2013/Binary/maf_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16940,663,"MAF","Saint Martin (French part)","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MAF/BSGM/2013/DTE/maf_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16941,663,"MAF","Saint Martin (French part)","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MAF/BSGM/2015/DTE/maf_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16942,663,"MAF","Saint Martin (French part)","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MAF/BSGM/2016/DTE/maf_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16943,663,"MAF","Saint Martin (French part)","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MAF/BSGM/2017/DTE/maf_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16944,663,"MAF","Saint Martin (French part)","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MAF/BSGM/2018/DTE/maf_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16945,663,"MAF","Saint Martin (French part)","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MAF/BSGM/2019/DTE/maf_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16946,663,"MAF","Saint Martin (French part)","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MAF/BSGM/2020/DTE/maf_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16947,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SPM/BSGM/2001/Binary/spm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16948,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SPM/BSGM/2001/DTE/spm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16949,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SPM/BSGM/2002/Binary/spm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16950,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SPM/BSGM/2002/DTE/spm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16951,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SPM/BSGM/2003/Binary/spm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16952,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SPM/BSGM/2003/DTE/spm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16953,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SPM/BSGM/2004/Binary/spm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16954,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SPM/BSGM/2004/DTE/spm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16955,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SPM/BSGM/2005/Binary/spm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16956,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SPM/BSGM/2005/DTE/spm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16957,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SPM/BSGM/2006/Binary/spm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16958,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SPM/BSGM/2006/DTE/spm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16959,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SPM/BSGM/2007/Binary/spm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16960,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SPM/BSGM/2007/DTE/spm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16961,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SPM/BSGM/2008/Binary/spm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16962,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SPM/BSGM/2008/DTE/spm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16963,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SPM/BSGM/2009/Binary/spm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16964,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SPM/BSGM/2009/DTE/spm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16965,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SPM/BSGM/2010/Binary/spm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16966,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SPM/BSGM/2010/DTE/spm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16967,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SPM/BSGM/2011/Binary/spm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16968,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SPM/BSGM/2011/DTE/spm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16969,666,"SPM","Saint Pierre and Miquelon","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SPM/BSGM/2013/Binary/spm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
16970,666,"SPM","Saint Pierre and Miquelon","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SPM/BSGM/2013/DTE/spm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
16971,666,"SPM","Saint Pierre and Miquelon","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SPM/BSGM/2015/DTE/spm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
16972,666,"SPM","Saint Pierre and Miquelon","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SPM/BSGM/2016/DTE/spm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
16973,666,"SPM","Saint Pierre and Miquelon","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SPM/BSGM/2017/DTE/spm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
16974,666,"SPM","Saint Pierre and Miquelon","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SPM/BSGM/2018/DTE/spm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
16975,666,"SPM","Saint Pierre and Miquelon","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SPM/BSGM/2019/DTE/spm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
16976,666,"SPM","Saint Pierre and Miquelon","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SPM/BSGM/2020/DTE/spm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
16977,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VCT/BSGM/2001/Binary/vct_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
16978,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VCT/BSGM/2001/DTE/vct_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
16979,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VCT/BSGM/2002/Binary/vct_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
16980,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VCT/BSGM/2002/DTE/vct_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
16981,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VCT/BSGM/2003/Binary/vct_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
16982,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VCT/BSGM/2003/DTE/vct_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
16983,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VCT/BSGM/2004/Binary/vct_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
16984,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VCT/BSGM/2004/DTE/vct_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
16985,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VCT/BSGM/2005/Binary/vct_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
16986,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VCT/BSGM/2005/DTE/vct_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
16987,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VCT/BSGM/2006/Binary/vct_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
16988,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VCT/BSGM/2006/DTE/vct_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
16989,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VCT/BSGM/2007/Binary/vct_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
16990,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VCT/BSGM/2007/DTE/vct_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
16991,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VCT/BSGM/2008/Binary/vct_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
16992,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VCT/BSGM/2008/DTE/vct_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
16993,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VCT/BSGM/2009/Binary/vct_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
16994,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VCT/BSGM/2009/DTE/vct_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
16995,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VCT/BSGM/2010/Binary/vct_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
16996,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VCT/BSGM/2010/DTE/vct_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
16997,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VCT/BSGM/2011/Binary/vct_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
16998,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VCT/BSGM/2011/DTE/vct_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
16999,670,"VCT","Saint Vincent and the Grenadines","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VCT/BSGM/2013/Binary/vct_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17000,670,"VCT","Saint Vincent and the Grenadines","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VCT/BSGM/2013/DTE/vct_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17001,670,"VCT","Saint Vincent and the Grenadines","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/VCT/BSGM/2015/DTE/vct_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17002,670,"VCT","Saint Vincent and the Grenadines","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/VCT/BSGM/2016/DTE/vct_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17003,670,"VCT","Saint Vincent and the Grenadines","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/VCT/BSGM/2017/DTE/vct_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17004,670,"VCT","Saint Vincent and the Grenadines","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/VCT/BSGM/2018/DTE/vct_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17005,670,"VCT","Saint Vincent and the Grenadines","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/VCT/BSGM/2019/DTE/vct_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17006,670,"VCT","Saint Vincent and the Grenadines","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/VCT/BSGM/2020/DTE/vct_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17007,674,"SMR","San Marino","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SMR/BSGM/2001/Binary/smr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17008,674,"SMR","San Marino","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SMR/BSGM/2001/DTE/smr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17009,674,"SMR","San Marino","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SMR/BSGM/2002/Binary/smr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17010,674,"SMR","San Marino","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SMR/BSGM/2002/DTE/smr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17011,674,"SMR","San Marino","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SMR/BSGM/2003/Binary/smr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17012,674,"SMR","San Marino","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SMR/BSGM/2003/DTE/smr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17013,674,"SMR","San Marino","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SMR/BSGM/2004/Binary/smr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17014,674,"SMR","San Marino","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SMR/BSGM/2004/DTE/smr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17015,674,"SMR","San Marino","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SMR/BSGM/2005/Binary/smr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17016,674,"SMR","San Marino","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SMR/BSGM/2005/DTE/smr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17017,674,"SMR","San Marino","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SMR/BSGM/2006/Binary/smr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17018,674,"SMR","San Marino","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SMR/BSGM/2006/DTE/smr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17019,674,"SMR","San Marino","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SMR/BSGM/2007/Binary/smr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17020,674,"SMR","San Marino","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SMR/BSGM/2007/DTE/smr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17021,674,"SMR","San Marino","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SMR/BSGM/2008/Binary/smr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17022,674,"SMR","San Marino","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SMR/BSGM/2008/DTE/smr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17023,674,"SMR","San Marino","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SMR/BSGM/2009/Binary/smr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17024,674,"SMR","San Marino","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SMR/BSGM/2009/DTE/smr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17025,674,"SMR","San Marino","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SMR/BSGM/2010/Binary/smr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17026,674,"SMR","San Marino","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SMR/BSGM/2010/DTE/smr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17027,674,"SMR","San Marino","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SMR/BSGM/2011/Binary/smr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17028,674,"SMR","San Marino","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SMR/BSGM/2011/DTE/smr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17029,674,"SMR","San Marino","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SMR/BSGM/2013/Binary/smr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17030,674,"SMR","San Marino","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SMR/BSGM/2013/DTE/smr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17031,674,"SMR","San Marino","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SMR/BSGM/2015/DTE/smr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17032,674,"SMR","San Marino","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SMR/BSGM/2016/DTE/smr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17033,674,"SMR","San Marino","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SMR/BSGM/2017/DTE/smr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17034,674,"SMR","San Marino","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SMR/BSGM/2018/DTE/smr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17035,674,"SMR","San Marino","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SMR/BSGM/2019/DTE/smr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17036,674,"SMR","San Marino","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SMR/BSGM/2020/DTE/smr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17037,678,"STP","Sao Tome and Principe","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/STP/BSGM/2001/Binary/stp_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17038,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/STP/BSGM/2001/DTE/stp_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17039,678,"STP","Sao Tome and Principe","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/STP/BSGM/2002/Binary/stp_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17040,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/STP/BSGM/2002/DTE/stp_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17041,678,"STP","Sao Tome and Principe","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/STP/BSGM/2003/Binary/stp_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17042,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/STP/BSGM/2003/DTE/stp_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17043,678,"STP","Sao Tome and Principe","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/STP/BSGM/2004/Binary/stp_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17044,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/STP/BSGM/2004/DTE/stp_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17045,678,"STP","Sao Tome and Principe","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/STP/BSGM/2005/Binary/stp_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17046,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/STP/BSGM/2005/DTE/stp_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17047,678,"STP","Sao Tome and Principe","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/STP/BSGM/2006/Binary/stp_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17048,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/STP/BSGM/2006/DTE/stp_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17049,678,"STP","Sao Tome and Principe","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/STP/BSGM/2007/Binary/stp_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17050,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/STP/BSGM/2007/DTE/stp_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17051,678,"STP","Sao Tome and Principe","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/STP/BSGM/2008/Binary/stp_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17052,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/STP/BSGM/2008/DTE/stp_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17053,678,"STP","Sao Tome and Principe","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/STP/BSGM/2009/Binary/stp_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17054,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/STP/BSGM/2009/DTE/stp_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17055,678,"STP","Sao Tome and Principe","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/STP/BSGM/2010/Binary/stp_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17056,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/STP/BSGM/2010/DTE/stp_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17057,678,"STP","Sao Tome and Principe","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/STP/BSGM/2011/Binary/stp_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17058,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/STP/BSGM/2011/DTE/stp_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17059,678,"STP","Sao Tome and Principe","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/STP/BSGM/2013/Binary/stp_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17060,678,"STP","Sao Tome and Principe","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/STP/BSGM/2013/DTE/stp_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17061,678,"STP","Sao Tome and Principe","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/STP/BSGM/2015/DTE/stp_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17062,678,"STP","Sao Tome and Principe","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/STP/BSGM/2016/DTE/stp_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17063,678,"STP","Sao Tome and Principe","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/STP/BSGM/2017/DTE/stp_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17064,678,"STP","Sao Tome and Principe","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/STP/BSGM/2018/DTE/stp_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17065,678,"STP","Sao Tome and Principe","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/STP/BSGM/2019/DTE/stp_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17066,678,"STP","Sao Tome and Principe","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/STP/BSGM/2020/DTE/stp_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17067,682,"SAU","Saudi Arabia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SAU/BSGM/2001/Binary/sau_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17068,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SAU/BSGM/2001/DTE/sau_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17069,682,"SAU","Saudi Arabia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SAU/BSGM/2002/Binary/sau_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17070,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SAU/BSGM/2002/DTE/sau_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17071,682,"SAU","Saudi Arabia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SAU/BSGM/2003/Binary/sau_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17072,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SAU/BSGM/2003/DTE/sau_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17073,682,"SAU","Saudi Arabia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SAU/BSGM/2004/Binary/sau_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17074,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SAU/BSGM/2004/DTE/sau_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17075,682,"SAU","Saudi Arabia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SAU/BSGM/2005/Binary/sau_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17076,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SAU/BSGM/2005/DTE/sau_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17077,682,"SAU","Saudi Arabia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SAU/BSGM/2006/Binary/sau_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17078,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SAU/BSGM/2006/DTE/sau_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17079,682,"SAU","Saudi Arabia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SAU/BSGM/2007/Binary/sau_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17080,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SAU/BSGM/2007/DTE/sau_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17081,682,"SAU","Saudi Arabia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SAU/BSGM/2008/Binary/sau_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17082,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SAU/BSGM/2008/DTE/sau_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17083,682,"SAU","Saudi Arabia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SAU/BSGM/2009/Binary/sau_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17084,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SAU/BSGM/2009/DTE/sau_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17085,682,"SAU","Saudi Arabia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SAU/BSGM/2010/Binary/sau_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17086,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SAU/BSGM/2010/DTE/sau_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17087,682,"SAU","Saudi Arabia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SAU/BSGM/2011/Binary/sau_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17088,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SAU/BSGM/2011/DTE/sau_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17089,682,"SAU","Saudi Arabia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SAU/BSGM/2013/Binary/sau_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17090,682,"SAU","Saudi Arabia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SAU/BSGM/2013/DTE/sau_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17091,682,"SAU","Saudi Arabia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SAU/BSGM/2015/DTE/sau_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17092,682,"SAU","Saudi Arabia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SAU/BSGM/2016/DTE/sau_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17093,682,"SAU","Saudi Arabia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SAU/BSGM/2017/DTE/sau_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17094,682,"SAU","Saudi Arabia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SAU/BSGM/2018/DTE/sau_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17095,682,"SAU","Saudi Arabia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SAU/BSGM/2019/DTE/sau_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17096,682,"SAU","Saudi Arabia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SAU/BSGM/2020/DTE/sau_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17097,686,"SEN","Senegal","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SEN/BSGM/2001/Binary/sen_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17098,686,"SEN","Senegal","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SEN/BSGM/2001/DTE/sen_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17099,686,"SEN","Senegal","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SEN/BSGM/2002/Binary/sen_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17100,686,"SEN","Senegal","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SEN/BSGM/2002/DTE/sen_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17101,686,"SEN","Senegal","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SEN/BSGM/2003/Binary/sen_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17102,686,"SEN","Senegal","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SEN/BSGM/2003/DTE/sen_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17103,686,"SEN","Senegal","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SEN/BSGM/2004/Binary/sen_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17104,686,"SEN","Senegal","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SEN/BSGM/2004/DTE/sen_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17105,686,"SEN","Senegal","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SEN/BSGM/2005/Binary/sen_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17106,686,"SEN","Senegal","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SEN/BSGM/2005/DTE/sen_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17107,686,"SEN","Senegal","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SEN/BSGM/2006/Binary/sen_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17108,686,"SEN","Senegal","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SEN/BSGM/2006/DTE/sen_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17109,686,"SEN","Senegal","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SEN/BSGM/2007/Binary/sen_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17110,686,"SEN","Senegal","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SEN/BSGM/2007/DTE/sen_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17111,686,"SEN","Senegal","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SEN/BSGM/2008/Binary/sen_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17112,686,"SEN","Senegal","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SEN/BSGM/2008/DTE/sen_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17113,686,"SEN","Senegal","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SEN/BSGM/2009/Binary/sen_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17114,686,"SEN","Senegal","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SEN/BSGM/2009/DTE/sen_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17115,686,"SEN","Senegal","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SEN/BSGM/2010/Binary/sen_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17116,686,"SEN","Senegal","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SEN/BSGM/2010/DTE/sen_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17117,686,"SEN","Senegal","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SEN/BSGM/2011/Binary/sen_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17118,686,"SEN","Senegal","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SEN/BSGM/2011/DTE/sen_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17119,686,"SEN","Senegal","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SEN/BSGM/2013/Binary/sen_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17120,686,"SEN","Senegal","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SEN/BSGM/2013/DTE/sen_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17121,686,"SEN","Senegal","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SEN/BSGM/2015/DTE/sen_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17122,686,"SEN","Senegal","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SEN/BSGM/2016/DTE/sen_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17123,686,"SEN","Senegal","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SEN/BSGM/2017/DTE/sen_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17124,686,"SEN","Senegal","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SEN/BSGM/2018/DTE/sen_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17125,686,"SEN","Senegal","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SEN/BSGM/2019/DTE/sen_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17126,686,"SEN","Senegal","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SEN/BSGM/2020/DTE/sen_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17127,688,"SRB","Serbia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SRB/BSGM/2001/Binary/srb_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17128,688,"SRB","Serbia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SRB/BSGM/2001/DTE/srb_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17129,688,"SRB","Serbia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SRB/BSGM/2002/Binary/srb_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17130,688,"SRB","Serbia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SRB/BSGM/2002/DTE/srb_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17131,688,"SRB","Serbia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SRB/BSGM/2003/Binary/srb_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17132,688,"SRB","Serbia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SRB/BSGM/2003/DTE/srb_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17133,688,"SRB","Serbia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SRB/BSGM/2004/Binary/srb_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17134,688,"SRB","Serbia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SRB/BSGM/2004/DTE/srb_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17135,688,"SRB","Serbia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SRB/BSGM/2005/Binary/srb_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17136,688,"SRB","Serbia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SRB/BSGM/2005/DTE/srb_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17137,688,"SRB","Serbia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SRB/BSGM/2006/Binary/srb_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17138,688,"SRB","Serbia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SRB/BSGM/2006/DTE/srb_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17139,688,"SRB","Serbia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SRB/BSGM/2007/Binary/srb_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17140,688,"SRB","Serbia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SRB/BSGM/2007/DTE/srb_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17141,688,"SRB","Serbia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SRB/BSGM/2008/Binary/srb_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17142,688,"SRB","Serbia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SRB/BSGM/2008/DTE/srb_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17143,688,"SRB","Serbia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SRB/BSGM/2009/Binary/srb_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17144,688,"SRB","Serbia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SRB/BSGM/2009/DTE/srb_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17145,688,"SRB","Serbia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SRB/BSGM/2010/Binary/srb_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17146,688,"SRB","Serbia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SRB/BSGM/2010/DTE/srb_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17147,688,"SRB","Serbia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SRB/BSGM/2011/Binary/srb_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17148,688,"SRB","Serbia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SRB/BSGM/2011/DTE/srb_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17149,688,"SRB","Serbia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SRB/BSGM/2013/Binary/srb_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17150,688,"SRB","Serbia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SRB/BSGM/2013/DTE/srb_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17151,688,"SRB","Serbia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SRB/BSGM/2015/DTE/srb_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17152,688,"SRB","Serbia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SRB/BSGM/2016/DTE/srb_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17153,688,"SRB","Serbia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SRB/BSGM/2017/DTE/srb_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17154,688,"SRB","Serbia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SRB/BSGM/2018/DTE/srb_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17155,688,"SRB","Serbia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SRB/BSGM/2019/DTE/srb_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17156,688,"SRB","Serbia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SRB/BSGM/2020/DTE/srb_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17157,690,"SYC","Seychelles","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SYC/BSGM/2001/Binary/syc_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17158,690,"SYC","Seychelles","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SYC/BSGM/2001/DTE/syc_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17159,690,"SYC","Seychelles","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SYC/BSGM/2002/Binary/syc_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17160,690,"SYC","Seychelles","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SYC/BSGM/2002/DTE/syc_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17161,690,"SYC","Seychelles","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SYC/BSGM/2003/Binary/syc_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17162,690,"SYC","Seychelles","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SYC/BSGM/2003/DTE/syc_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17163,690,"SYC","Seychelles","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SYC/BSGM/2004/Binary/syc_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17164,690,"SYC","Seychelles","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SYC/BSGM/2004/DTE/syc_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17165,690,"SYC","Seychelles","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SYC/BSGM/2005/Binary/syc_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17166,690,"SYC","Seychelles","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SYC/BSGM/2005/DTE/syc_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17167,690,"SYC","Seychelles","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SYC/BSGM/2006/Binary/syc_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17168,690,"SYC","Seychelles","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SYC/BSGM/2006/DTE/syc_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17169,690,"SYC","Seychelles","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SYC/BSGM/2007/Binary/syc_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17170,690,"SYC","Seychelles","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SYC/BSGM/2007/DTE/syc_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17171,690,"SYC","Seychelles","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SYC/BSGM/2008/Binary/syc_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17172,690,"SYC","Seychelles","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SYC/BSGM/2008/DTE/syc_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17173,690,"SYC","Seychelles","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SYC/BSGM/2009/Binary/syc_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17174,690,"SYC","Seychelles","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SYC/BSGM/2009/DTE/syc_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17175,690,"SYC","Seychelles","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SYC/BSGM/2010/Binary/syc_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17176,690,"SYC","Seychelles","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SYC/BSGM/2010/DTE/syc_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17177,690,"SYC","Seychelles","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SYC/BSGM/2011/Binary/syc_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17178,690,"SYC","Seychelles","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SYC/BSGM/2011/DTE/syc_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17179,690,"SYC","Seychelles","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SYC/BSGM/2013/Binary/syc_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17180,690,"SYC","Seychelles","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SYC/BSGM/2013/DTE/syc_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17181,690,"SYC","Seychelles","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SYC/BSGM/2015/DTE/syc_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17182,690,"SYC","Seychelles","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SYC/BSGM/2016/DTE/syc_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17183,690,"SYC","Seychelles","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SYC/BSGM/2017/DTE/syc_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17184,690,"SYC","Seychelles","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SYC/BSGM/2018/DTE/syc_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17185,690,"SYC","Seychelles","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SYC/BSGM/2019/DTE/syc_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17186,690,"SYC","Seychelles","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SYC/BSGM/2020/DTE/syc_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17187,694,"SLE","Sierra Leone","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SLE/BSGM/2001/Binary/sle_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17188,694,"SLE","Sierra Leone","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SLE/BSGM/2001/DTE/sle_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17189,694,"SLE","Sierra Leone","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SLE/BSGM/2002/Binary/sle_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17190,694,"SLE","Sierra Leone","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SLE/BSGM/2002/DTE/sle_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17191,694,"SLE","Sierra Leone","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SLE/BSGM/2003/Binary/sle_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17192,694,"SLE","Sierra Leone","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SLE/BSGM/2003/DTE/sle_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17193,694,"SLE","Sierra Leone","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SLE/BSGM/2004/Binary/sle_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17194,694,"SLE","Sierra Leone","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SLE/BSGM/2004/DTE/sle_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17195,694,"SLE","Sierra Leone","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SLE/BSGM/2005/Binary/sle_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17196,694,"SLE","Sierra Leone","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SLE/BSGM/2005/DTE/sle_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17197,694,"SLE","Sierra Leone","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SLE/BSGM/2006/Binary/sle_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17198,694,"SLE","Sierra Leone","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SLE/BSGM/2006/DTE/sle_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17199,694,"SLE","Sierra Leone","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SLE/BSGM/2007/Binary/sle_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17200,694,"SLE","Sierra Leone","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SLE/BSGM/2007/DTE/sle_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17201,694,"SLE","Sierra Leone","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SLE/BSGM/2008/Binary/sle_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17202,694,"SLE","Sierra Leone","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SLE/BSGM/2008/DTE/sle_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17203,694,"SLE","Sierra Leone","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SLE/BSGM/2009/Binary/sle_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17204,694,"SLE","Sierra Leone","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SLE/BSGM/2009/DTE/sle_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17205,694,"SLE","Sierra Leone","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SLE/BSGM/2010/Binary/sle_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17206,694,"SLE","Sierra Leone","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SLE/BSGM/2010/DTE/sle_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17207,694,"SLE","Sierra Leone","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SLE/BSGM/2011/Binary/sle_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17208,694,"SLE","Sierra Leone","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SLE/BSGM/2011/DTE/sle_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17209,694,"SLE","Sierra Leone","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SLE/BSGM/2013/Binary/sle_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17210,694,"SLE","Sierra Leone","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SLE/BSGM/2013/DTE/sle_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17211,694,"SLE","Sierra Leone","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SLE/BSGM/2015/DTE/sle_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17212,694,"SLE","Sierra Leone","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SLE/BSGM/2016/DTE/sle_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17213,694,"SLE","Sierra Leone","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SLE/BSGM/2017/DTE/sle_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17214,694,"SLE","Sierra Leone","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SLE/BSGM/2018/DTE/sle_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17215,694,"SLE","Sierra Leone","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SLE/BSGM/2019/DTE/sle_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17216,694,"SLE","Sierra Leone","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SLE/BSGM/2020/DTE/sle_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17217,702,"SGP","Singapore","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SGP/BSGM/2001/Binary/sgp_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17218,702,"SGP","Singapore","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SGP/BSGM/2001/DTE/sgp_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17219,702,"SGP","Singapore","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SGP/BSGM/2002/Binary/sgp_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17220,702,"SGP","Singapore","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SGP/BSGM/2002/DTE/sgp_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17221,702,"SGP","Singapore","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SGP/BSGM/2003/Binary/sgp_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17222,702,"SGP","Singapore","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SGP/BSGM/2003/DTE/sgp_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17223,702,"SGP","Singapore","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SGP/BSGM/2004/Binary/sgp_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17224,702,"SGP","Singapore","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SGP/BSGM/2004/DTE/sgp_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17225,702,"SGP","Singapore","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SGP/BSGM/2005/Binary/sgp_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17226,702,"SGP","Singapore","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SGP/BSGM/2005/DTE/sgp_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17227,702,"SGP","Singapore","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SGP/BSGM/2006/Binary/sgp_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17228,702,"SGP","Singapore","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SGP/BSGM/2006/DTE/sgp_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17229,702,"SGP","Singapore","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SGP/BSGM/2007/Binary/sgp_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17230,702,"SGP","Singapore","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SGP/BSGM/2007/DTE/sgp_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17231,702,"SGP","Singapore","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SGP/BSGM/2008/Binary/sgp_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17232,702,"SGP","Singapore","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SGP/BSGM/2008/DTE/sgp_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17233,702,"SGP","Singapore","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SGP/BSGM/2009/Binary/sgp_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17234,702,"SGP","Singapore","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SGP/BSGM/2009/DTE/sgp_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17235,702,"SGP","Singapore","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SGP/BSGM/2010/Binary/sgp_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17236,702,"SGP","Singapore","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SGP/BSGM/2010/DTE/sgp_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17237,702,"SGP","Singapore","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SGP/BSGM/2011/Binary/sgp_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17238,702,"SGP","Singapore","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SGP/BSGM/2011/DTE/sgp_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17239,702,"SGP","Singapore","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SGP/BSGM/2013/Binary/sgp_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17240,702,"SGP","Singapore","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SGP/BSGM/2013/DTE/sgp_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17241,702,"SGP","Singapore","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SGP/BSGM/2015/DTE/sgp_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17242,702,"SGP","Singapore","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SGP/BSGM/2016/DTE/sgp_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17243,702,"SGP","Singapore","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SGP/BSGM/2017/DTE/sgp_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17244,702,"SGP","Singapore","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SGP/BSGM/2018/DTE/sgp_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17245,702,"SGP","Singapore","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SGP/BSGM/2019/DTE/sgp_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17246,702,"SGP","Singapore","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SGP/BSGM/2020/DTE/sgp_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17247,703,"SVK","Slovakia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SVK/BSGM/2001/Binary/svk_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17248,703,"SVK","Slovakia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SVK/BSGM/2001/DTE/svk_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17249,703,"SVK","Slovakia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SVK/BSGM/2002/Binary/svk_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17250,703,"SVK","Slovakia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SVK/BSGM/2002/DTE/svk_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17251,703,"SVK","Slovakia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SVK/BSGM/2003/Binary/svk_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17252,703,"SVK","Slovakia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SVK/BSGM/2003/DTE/svk_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17253,703,"SVK","Slovakia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SVK/BSGM/2004/Binary/svk_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17254,703,"SVK","Slovakia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SVK/BSGM/2004/DTE/svk_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17255,703,"SVK","Slovakia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SVK/BSGM/2005/Binary/svk_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17256,703,"SVK","Slovakia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SVK/BSGM/2005/DTE/svk_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17257,703,"SVK","Slovakia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SVK/BSGM/2006/Binary/svk_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17258,703,"SVK","Slovakia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SVK/BSGM/2006/DTE/svk_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17259,703,"SVK","Slovakia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SVK/BSGM/2007/Binary/svk_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17260,703,"SVK","Slovakia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SVK/BSGM/2007/DTE/svk_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17261,703,"SVK","Slovakia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SVK/BSGM/2008/Binary/svk_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17262,703,"SVK","Slovakia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SVK/BSGM/2008/DTE/svk_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17263,703,"SVK","Slovakia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SVK/BSGM/2009/Binary/svk_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17264,703,"SVK","Slovakia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SVK/BSGM/2009/DTE/svk_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17265,703,"SVK","Slovakia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SVK/BSGM/2010/Binary/svk_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17266,703,"SVK","Slovakia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SVK/BSGM/2010/DTE/svk_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17267,703,"SVK","Slovakia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SVK/BSGM/2011/Binary/svk_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17268,703,"SVK","Slovakia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SVK/BSGM/2011/DTE/svk_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17269,703,"SVK","Slovakia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SVK/BSGM/2013/Binary/svk_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17270,703,"SVK","Slovakia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SVK/BSGM/2013/DTE/svk_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17271,703,"SVK","Slovakia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SVK/BSGM/2015/DTE/svk_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17272,703,"SVK","Slovakia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SVK/BSGM/2016/DTE/svk_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17273,703,"SVK","Slovakia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SVK/BSGM/2017/DTE/svk_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17274,703,"SVK","Slovakia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SVK/BSGM/2018/DTE/svk_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17275,703,"SVK","Slovakia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SVK/BSGM/2019/DTE/svk_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17276,703,"SVK","Slovakia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SVK/BSGM/2020/DTE/svk_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17277,704,"VNM","Vietnam","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VNM/BSGM/2001/Binary/vnm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17278,704,"VNM","Vietnam","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VNM/BSGM/2001/DTE/vnm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17279,704,"VNM","Vietnam","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VNM/BSGM/2002/Binary/vnm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17280,704,"VNM","Vietnam","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VNM/BSGM/2002/DTE/vnm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17281,704,"VNM","Vietnam","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VNM/BSGM/2003/Binary/vnm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17282,704,"VNM","Vietnam","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VNM/BSGM/2003/DTE/vnm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17283,704,"VNM","Vietnam","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VNM/BSGM/2004/Binary/vnm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17284,704,"VNM","Vietnam","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VNM/BSGM/2004/DTE/vnm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17285,704,"VNM","Vietnam","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VNM/BSGM/2005/Binary/vnm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17286,704,"VNM","Vietnam","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VNM/BSGM/2005/DTE/vnm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17287,704,"VNM","Vietnam","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VNM/BSGM/2006/Binary/vnm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17288,704,"VNM","Vietnam","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VNM/BSGM/2006/DTE/vnm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17289,704,"VNM","Vietnam","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VNM/BSGM/2007/Binary/vnm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17290,704,"VNM","Vietnam","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VNM/BSGM/2007/DTE/vnm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17291,704,"VNM","Vietnam","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VNM/BSGM/2008/Binary/vnm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17292,704,"VNM","Vietnam","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VNM/BSGM/2008/DTE/vnm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17293,704,"VNM","Vietnam","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VNM/BSGM/2009/Binary/vnm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17294,704,"VNM","Vietnam","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VNM/BSGM/2009/DTE/vnm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17295,704,"VNM","Vietnam","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VNM/BSGM/2010/Binary/vnm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17296,704,"VNM","Vietnam","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VNM/BSGM/2010/DTE/vnm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17297,704,"VNM","Vietnam","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VNM/BSGM/2011/Binary/vnm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17298,704,"VNM","Vietnam","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VNM/BSGM/2011/DTE/vnm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17299,704,"VNM","Vietnam","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VNM/BSGM/2013/Binary/vnm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17300,704,"VNM","Vietnam","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VNM/BSGM/2013/DTE/vnm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17301,704,"VNM","Vietnam","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/VNM/BSGM/2015/DTE/vnm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17302,704,"VNM","Vietnam","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/VNM/BSGM/2016/DTE/vnm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17303,704,"VNM","Vietnam","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/VNM/BSGM/2017/DTE/vnm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17304,704,"VNM","Vietnam","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/VNM/BSGM/2018/DTE/vnm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17305,704,"VNM","Vietnam","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/VNM/BSGM/2019/DTE/vnm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17306,704,"VNM","Vietnam","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/VNM/BSGM/2020/DTE/vnm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17307,705,"SVN","Slovenia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SVN/BSGM/2001/Binary/svn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17308,705,"SVN","Slovenia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SVN/BSGM/2001/DTE/svn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17309,705,"SVN","Slovenia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SVN/BSGM/2002/Binary/svn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17310,705,"SVN","Slovenia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SVN/BSGM/2002/DTE/svn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17311,705,"SVN","Slovenia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SVN/BSGM/2003/Binary/svn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17312,705,"SVN","Slovenia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SVN/BSGM/2003/DTE/svn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17313,705,"SVN","Slovenia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SVN/BSGM/2004/Binary/svn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17314,705,"SVN","Slovenia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SVN/BSGM/2004/DTE/svn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17315,705,"SVN","Slovenia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SVN/BSGM/2005/Binary/svn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17316,705,"SVN","Slovenia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SVN/BSGM/2005/DTE/svn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17317,705,"SVN","Slovenia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SVN/BSGM/2006/Binary/svn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17318,705,"SVN","Slovenia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SVN/BSGM/2006/DTE/svn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17319,705,"SVN","Slovenia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SVN/BSGM/2007/Binary/svn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17320,705,"SVN","Slovenia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SVN/BSGM/2007/DTE/svn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17321,705,"SVN","Slovenia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SVN/BSGM/2008/Binary/svn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17322,705,"SVN","Slovenia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SVN/BSGM/2008/DTE/svn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17323,705,"SVN","Slovenia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SVN/BSGM/2009/Binary/svn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17324,705,"SVN","Slovenia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SVN/BSGM/2009/DTE/svn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17325,705,"SVN","Slovenia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SVN/BSGM/2010/Binary/svn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17326,705,"SVN","Slovenia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SVN/BSGM/2010/DTE/svn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17327,705,"SVN","Slovenia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SVN/BSGM/2011/Binary/svn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17328,705,"SVN","Slovenia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SVN/BSGM/2011/DTE/svn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17329,705,"SVN","Slovenia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SVN/BSGM/2013/Binary/svn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17330,705,"SVN","Slovenia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SVN/BSGM/2013/DTE/svn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17331,705,"SVN","Slovenia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SVN/BSGM/2015/DTE/svn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17332,705,"SVN","Slovenia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SVN/BSGM/2016/DTE/svn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17333,705,"SVN","Slovenia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SVN/BSGM/2017/DTE/svn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17334,705,"SVN","Slovenia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SVN/BSGM/2018/DTE/svn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17335,705,"SVN","Slovenia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SVN/BSGM/2019/DTE/svn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17336,705,"SVN","Slovenia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SVN/BSGM/2020/DTE/svn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17337,706,"SOM","Somalia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SOM/BSGM/2001/Binary/som_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17338,706,"SOM","Somalia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SOM/BSGM/2001/DTE/som_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17339,706,"SOM","Somalia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SOM/BSGM/2002/Binary/som_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17340,706,"SOM","Somalia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SOM/BSGM/2002/DTE/som_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17341,706,"SOM","Somalia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SOM/BSGM/2003/Binary/som_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17342,706,"SOM","Somalia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SOM/BSGM/2003/DTE/som_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17343,706,"SOM","Somalia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SOM/BSGM/2004/Binary/som_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17344,706,"SOM","Somalia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SOM/BSGM/2004/DTE/som_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17345,706,"SOM","Somalia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SOM/BSGM/2005/Binary/som_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17346,706,"SOM","Somalia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SOM/BSGM/2005/DTE/som_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17347,706,"SOM","Somalia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SOM/BSGM/2006/Binary/som_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17348,706,"SOM","Somalia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SOM/BSGM/2006/DTE/som_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17349,706,"SOM","Somalia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SOM/BSGM/2007/Binary/som_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17350,706,"SOM","Somalia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SOM/BSGM/2007/DTE/som_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17351,706,"SOM","Somalia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SOM/BSGM/2008/Binary/som_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17352,706,"SOM","Somalia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SOM/BSGM/2008/DTE/som_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17353,706,"SOM","Somalia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SOM/BSGM/2009/Binary/som_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17354,706,"SOM","Somalia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SOM/BSGM/2009/DTE/som_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17355,706,"SOM","Somalia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SOM/BSGM/2010/Binary/som_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17356,706,"SOM","Somalia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SOM/BSGM/2010/DTE/som_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17357,706,"SOM","Somalia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SOM/BSGM/2011/Binary/som_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17358,706,"SOM","Somalia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SOM/BSGM/2011/DTE/som_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17359,706,"SOM","Somalia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SOM/BSGM/2013/Binary/som_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17360,706,"SOM","Somalia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SOM/BSGM/2013/DTE/som_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17361,706,"SOM","Somalia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SOM/BSGM/2015/DTE/som_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17362,706,"SOM","Somalia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SOM/BSGM/2016/DTE/som_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17363,706,"SOM","Somalia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SOM/BSGM/2017/DTE/som_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17364,706,"SOM","Somalia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SOM/BSGM/2018/DTE/som_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17365,706,"SOM","Somalia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SOM/BSGM/2019/DTE/som_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17366,706,"SOM","Somalia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SOM/BSGM/2020/DTE/som_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17367,710,"ZAF","South Africa","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2001/Binary/zaf_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17368,710,"ZAF","South Africa","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2001/DTE/zaf_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17369,710,"ZAF","South Africa","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2002/Binary/zaf_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17370,710,"ZAF","South Africa","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2002/DTE/zaf_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17371,710,"ZAF","South Africa","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2003/Binary/zaf_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17372,710,"ZAF","South Africa","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2003/DTE/zaf_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17373,710,"ZAF","South Africa","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2004/Binary/zaf_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17374,710,"ZAF","South Africa","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2004/DTE/zaf_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17375,710,"ZAF","South Africa","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2005/Binary/zaf_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17376,710,"ZAF","South Africa","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2005/DTE/zaf_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17377,710,"ZAF","South Africa","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2006/Binary/zaf_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17378,710,"ZAF","South Africa","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2006/DTE/zaf_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17379,710,"ZAF","South Africa","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2007/Binary/zaf_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17380,710,"ZAF","South Africa","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2007/DTE/zaf_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17381,710,"ZAF","South Africa","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2008/Binary/zaf_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17382,710,"ZAF","South Africa","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2008/DTE/zaf_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17383,710,"ZAF","South Africa","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2009/Binary/zaf_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17384,710,"ZAF","South Africa","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2009/DTE/zaf_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17385,710,"ZAF","South Africa","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2010/Binary/zaf_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17386,710,"ZAF","South Africa","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2010/DTE/zaf_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17387,710,"ZAF","South Africa","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2011/Binary/zaf_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17388,710,"ZAF","South Africa","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2011/DTE/zaf_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17389,710,"ZAF","South Africa","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2013/Binary/zaf_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17390,710,"ZAF","South Africa","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2013/DTE/zaf_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17391,710,"ZAF","South Africa","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2015/DTE/zaf_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17392,710,"ZAF","South Africa","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2016/DTE/zaf_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17393,710,"ZAF","South Africa","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2017/DTE/zaf_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17394,710,"ZAF","South Africa","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2018/DTE/zaf_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17395,710,"ZAF","South Africa","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2019/DTE/zaf_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17396,710,"ZAF","South Africa","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ZAF/BSGM/2020/DTE/zaf_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17397,716,"ZWE","Zimbabwe","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2001/Binary/zwe_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17398,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2001/DTE/zwe_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17399,716,"ZWE","Zimbabwe","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2002/Binary/zwe_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17400,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2002/DTE/zwe_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17401,716,"ZWE","Zimbabwe","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2003/Binary/zwe_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17402,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2003/DTE/zwe_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17403,716,"ZWE","Zimbabwe","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2004/Binary/zwe_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17404,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2004/DTE/zwe_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17405,716,"ZWE","Zimbabwe","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2005/Binary/zwe_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17406,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2005/DTE/zwe_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17407,716,"ZWE","Zimbabwe","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2006/Binary/zwe_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17408,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2006/DTE/zwe_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17409,716,"ZWE","Zimbabwe","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2007/Binary/zwe_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17410,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2007/DTE/zwe_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17411,716,"ZWE","Zimbabwe","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2008/Binary/zwe_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17412,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2008/DTE/zwe_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17413,716,"ZWE","Zimbabwe","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2009/Binary/zwe_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17414,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2009/DTE/zwe_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17415,716,"ZWE","Zimbabwe","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2010/Binary/zwe_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17416,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2010/DTE/zwe_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17417,716,"ZWE","Zimbabwe","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2011/Binary/zwe_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17418,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2011/DTE/zwe_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17419,716,"ZWE","Zimbabwe","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2013/Binary/zwe_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17420,716,"ZWE","Zimbabwe","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2013/DTE/zwe_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17421,716,"ZWE","Zimbabwe","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2015/DTE/zwe_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17422,716,"ZWE","Zimbabwe","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2016/DTE/zwe_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17423,716,"ZWE","Zimbabwe","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2017/DTE/zwe_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17424,716,"ZWE","Zimbabwe","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2018/DTE/zwe_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17425,716,"ZWE","Zimbabwe","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2019/DTE/zwe_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17426,716,"ZWE","Zimbabwe","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ZWE/BSGM/2020/DTE/zwe_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17427,724,"ESP","Spain","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ESP/BSGM/2001/Binary/esp_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17428,724,"ESP","Spain","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ESP/BSGM/2001/DTE/esp_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17429,724,"ESP","Spain","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ESP/BSGM/2002/Binary/esp_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17430,724,"ESP","Spain","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ESP/BSGM/2002/DTE/esp_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17431,724,"ESP","Spain","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ESP/BSGM/2003/Binary/esp_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17432,724,"ESP","Spain","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ESP/BSGM/2003/DTE/esp_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17433,724,"ESP","Spain","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ESP/BSGM/2004/Binary/esp_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17434,724,"ESP","Spain","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ESP/BSGM/2004/DTE/esp_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17435,724,"ESP","Spain","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ESP/BSGM/2005/Binary/esp_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17436,724,"ESP","Spain","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ESP/BSGM/2005/DTE/esp_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17437,724,"ESP","Spain","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ESP/BSGM/2006/Binary/esp_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17438,724,"ESP","Spain","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ESP/BSGM/2006/DTE/esp_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17439,724,"ESP","Spain","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ESP/BSGM/2007/Binary/esp_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17440,724,"ESP","Spain","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ESP/BSGM/2007/DTE/esp_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17441,724,"ESP","Spain","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ESP/BSGM/2008/Binary/esp_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17442,724,"ESP","Spain","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ESP/BSGM/2008/DTE/esp_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17443,724,"ESP","Spain","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ESP/BSGM/2009/Binary/esp_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17444,724,"ESP","Spain","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ESP/BSGM/2009/DTE/esp_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17445,724,"ESP","Spain","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ESP/BSGM/2010/Binary/esp_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17446,724,"ESP","Spain","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ESP/BSGM/2010/DTE/esp_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17447,724,"ESP","Spain","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ESP/BSGM/2011/Binary/esp_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17448,724,"ESP","Spain","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ESP/BSGM/2011/DTE/esp_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17449,724,"ESP","Spain","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ESP/BSGM/2013/Binary/esp_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17450,724,"ESP","Spain","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ESP/BSGM/2013/DTE/esp_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17451,724,"ESP","Spain","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ESP/BSGM/2015/DTE/esp_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17452,724,"ESP","Spain","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ESP/BSGM/2016/DTE/esp_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17453,724,"ESP","Spain","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ESP/BSGM/2017/DTE/esp_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17454,724,"ESP","Spain","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ESP/BSGM/2018/DTE/esp_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17455,724,"ESP","Spain","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ESP/BSGM/2019/DTE/esp_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17456,724,"ESP","Spain","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ESP/BSGM/2020/DTE/esp_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17457,728,"SSD","South Sudan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SSD/BSGM/2001/Binary/ssd_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17458,728,"SSD","South Sudan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SSD/BSGM/2001/DTE/ssd_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17459,728,"SSD","South Sudan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SSD/BSGM/2002/Binary/ssd_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17460,728,"SSD","South Sudan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SSD/BSGM/2002/DTE/ssd_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17461,728,"SSD","South Sudan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SSD/BSGM/2003/Binary/ssd_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17462,728,"SSD","South Sudan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SSD/BSGM/2003/DTE/ssd_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17463,728,"SSD","South Sudan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SSD/BSGM/2004/Binary/ssd_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17464,728,"SSD","South Sudan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SSD/BSGM/2004/DTE/ssd_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17465,728,"SSD","South Sudan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SSD/BSGM/2005/Binary/ssd_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17466,728,"SSD","South Sudan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SSD/BSGM/2005/DTE/ssd_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17467,728,"SSD","South Sudan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SSD/BSGM/2006/Binary/ssd_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17468,728,"SSD","South Sudan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SSD/BSGM/2006/DTE/ssd_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17469,728,"SSD","South Sudan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SSD/BSGM/2007/Binary/ssd_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17470,728,"SSD","South Sudan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SSD/BSGM/2007/DTE/ssd_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17471,728,"SSD","South Sudan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SSD/BSGM/2008/Binary/ssd_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17472,728,"SSD","South Sudan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SSD/BSGM/2008/DTE/ssd_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17473,728,"SSD","South Sudan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SSD/BSGM/2009/Binary/ssd_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17474,728,"SSD","South Sudan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SSD/BSGM/2009/DTE/ssd_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17475,728,"SSD","South Sudan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SSD/BSGM/2010/Binary/ssd_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17476,728,"SSD","South Sudan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SSD/BSGM/2010/DTE/ssd_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17477,728,"SSD","South Sudan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SSD/BSGM/2011/Binary/ssd_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17478,728,"SSD","South Sudan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SSD/BSGM/2011/DTE/ssd_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17479,728,"SSD","South Sudan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SSD/BSGM/2013/Binary/ssd_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17480,728,"SSD","South Sudan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SSD/BSGM/2013/DTE/ssd_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17481,728,"SSD","South Sudan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SSD/BSGM/2015/DTE/ssd_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17482,728,"SSD","South Sudan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SSD/BSGM/2016/DTE/ssd_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17483,728,"SSD","South Sudan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SSD/BSGM/2017/DTE/ssd_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17484,728,"SSD","South Sudan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SSD/BSGM/2018/DTE/ssd_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17485,728,"SSD","South Sudan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SSD/BSGM/2019/DTE/ssd_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17486,728,"SSD","South Sudan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SSD/BSGM/2020/DTE/ssd_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17487,729,"SDN","Sudan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SDN/BSGM/2001/Binary/sdn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17488,729,"SDN","Sudan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SDN/BSGM/2001/DTE/sdn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17489,729,"SDN","Sudan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SDN/BSGM/2002/Binary/sdn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17490,729,"SDN","Sudan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SDN/BSGM/2002/DTE/sdn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17491,729,"SDN","Sudan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SDN/BSGM/2003/Binary/sdn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17492,729,"SDN","Sudan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SDN/BSGM/2003/DTE/sdn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17493,729,"SDN","Sudan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SDN/BSGM/2004/Binary/sdn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17494,729,"SDN","Sudan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SDN/BSGM/2004/DTE/sdn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17495,729,"SDN","Sudan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SDN/BSGM/2005/Binary/sdn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17496,729,"SDN","Sudan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SDN/BSGM/2005/DTE/sdn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17497,729,"SDN","Sudan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SDN/BSGM/2006/Binary/sdn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17498,729,"SDN","Sudan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SDN/BSGM/2006/DTE/sdn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17499,729,"SDN","Sudan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SDN/BSGM/2007/Binary/sdn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17500,729,"SDN","Sudan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SDN/BSGM/2007/DTE/sdn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17501,729,"SDN","Sudan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SDN/BSGM/2008/Binary/sdn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17502,729,"SDN","Sudan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SDN/BSGM/2008/DTE/sdn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17503,729,"SDN","Sudan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SDN/BSGM/2009/Binary/sdn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17504,729,"SDN","Sudan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SDN/BSGM/2009/DTE/sdn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17505,729,"SDN","Sudan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SDN/BSGM/2010/Binary/sdn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17506,729,"SDN","Sudan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SDN/BSGM/2010/DTE/sdn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17507,729,"SDN","Sudan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SDN/BSGM/2011/Binary/sdn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17508,729,"SDN","Sudan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SDN/BSGM/2011/DTE/sdn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17509,729,"SDN","Sudan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SDN/BSGM/2013/Binary/sdn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17510,729,"SDN","Sudan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SDN/BSGM/2013/DTE/sdn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17511,729,"SDN","Sudan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SDN/BSGM/2015/DTE/sdn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17512,729,"SDN","Sudan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SDN/BSGM/2016/DTE/sdn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17513,729,"SDN","Sudan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SDN/BSGM/2017/DTE/sdn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17514,729,"SDN","Sudan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SDN/BSGM/2018/DTE/sdn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17515,729,"SDN","Sudan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SDN/BSGM/2019/DTE/sdn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17516,729,"SDN","Sudan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SDN/BSGM/2020/DTE/sdn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17517,732,"ESH","Western Sahara","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ESH/BSGM/2001/Binary/esh_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17518,732,"ESH","Western Sahara","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ESH/BSGM/2001/DTE/esh_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17519,732,"ESH","Western Sahara","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ESH/BSGM/2002/Binary/esh_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17520,732,"ESH","Western Sahara","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ESH/BSGM/2002/DTE/esh_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17521,732,"ESH","Western Sahara","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ESH/BSGM/2003/Binary/esh_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17522,732,"ESH","Western Sahara","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ESH/BSGM/2003/DTE/esh_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17523,732,"ESH","Western Sahara","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ESH/BSGM/2004/Binary/esh_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17524,732,"ESH","Western Sahara","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ESH/BSGM/2004/DTE/esh_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17525,732,"ESH","Western Sahara","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ESH/BSGM/2005/Binary/esh_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17526,732,"ESH","Western Sahara","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ESH/BSGM/2005/DTE/esh_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17527,732,"ESH","Western Sahara","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ESH/BSGM/2006/Binary/esh_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17528,732,"ESH","Western Sahara","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ESH/BSGM/2006/DTE/esh_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17529,732,"ESH","Western Sahara","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ESH/BSGM/2007/Binary/esh_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17530,732,"ESH","Western Sahara","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ESH/BSGM/2007/DTE/esh_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17531,732,"ESH","Western Sahara","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ESH/BSGM/2008/Binary/esh_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17532,732,"ESH","Western Sahara","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ESH/BSGM/2008/DTE/esh_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17533,732,"ESH","Western Sahara","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ESH/BSGM/2009/Binary/esh_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17534,732,"ESH","Western Sahara","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ESH/BSGM/2009/DTE/esh_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17535,732,"ESH","Western Sahara","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ESH/BSGM/2010/Binary/esh_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17536,732,"ESH","Western Sahara","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ESH/BSGM/2010/DTE/esh_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17537,732,"ESH","Western Sahara","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ESH/BSGM/2011/Binary/esh_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17538,732,"ESH","Western Sahara","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ESH/BSGM/2011/DTE/esh_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17539,732,"ESH","Western Sahara","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ESH/BSGM/2013/Binary/esh_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17540,732,"ESH","Western Sahara","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ESH/BSGM/2013/DTE/esh_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17541,732,"ESH","Western Sahara","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ESH/BSGM/2015/DTE/esh_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17542,732,"ESH","Western Sahara","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ESH/BSGM/2016/DTE/esh_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17543,732,"ESH","Western Sahara","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ESH/BSGM/2017/DTE/esh_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17544,732,"ESH","Western Sahara","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ESH/BSGM/2018/DTE/esh_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17545,732,"ESH","Western Sahara","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ESH/BSGM/2019/DTE/esh_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17546,732,"ESH","Western Sahara","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ESH/BSGM/2020/DTE/esh_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17547,740,"SUR","Suriname","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SUR/BSGM/2001/Binary/sur_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17548,740,"SUR","Suriname","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SUR/BSGM/2001/DTE/sur_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17549,740,"SUR","Suriname","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SUR/BSGM/2002/Binary/sur_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17550,740,"SUR","Suriname","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SUR/BSGM/2002/DTE/sur_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17551,740,"SUR","Suriname","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SUR/BSGM/2003/Binary/sur_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17552,740,"SUR","Suriname","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SUR/BSGM/2003/DTE/sur_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17553,740,"SUR","Suriname","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SUR/BSGM/2004/Binary/sur_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17554,740,"SUR","Suriname","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SUR/BSGM/2004/DTE/sur_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17555,740,"SUR","Suriname","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SUR/BSGM/2005/Binary/sur_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17556,740,"SUR","Suriname","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SUR/BSGM/2005/DTE/sur_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17557,740,"SUR","Suriname","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SUR/BSGM/2006/Binary/sur_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17558,740,"SUR","Suriname","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SUR/BSGM/2006/DTE/sur_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17559,740,"SUR","Suriname","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SUR/BSGM/2007/Binary/sur_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17560,740,"SUR","Suriname","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SUR/BSGM/2007/DTE/sur_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17561,740,"SUR","Suriname","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SUR/BSGM/2008/Binary/sur_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17562,740,"SUR","Suriname","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SUR/BSGM/2008/DTE/sur_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17563,740,"SUR","Suriname","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SUR/BSGM/2009/Binary/sur_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17564,740,"SUR","Suriname","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SUR/BSGM/2009/DTE/sur_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17565,740,"SUR","Suriname","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SUR/BSGM/2010/Binary/sur_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17566,740,"SUR","Suriname","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SUR/BSGM/2010/DTE/sur_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17567,740,"SUR","Suriname","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SUR/BSGM/2011/Binary/sur_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17568,740,"SUR","Suriname","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SUR/BSGM/2011/DTE/sur_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17569,740,"SUR","Suriname","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SUR/BSGM/2013/Binary/sur_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17570,740,"SUR","Suriname","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SUR/BSGM/2013/DTE/sur_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17571,740,"SUR","Suriname","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SUR/BSGM/2015/DTE/sur_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17572,740,"SUR","Suriname","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SUR/BSGM/2016/DTE/sur_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17573,740,"SUR","Suriname","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SUR/BSGM/2017/DTE/sur_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17574,740,"SUR","Suriname","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SUR/BSGM/2018/DTE/sur_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17575,740,"SUR","Suriname","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SUR/BSGM/2019/DTE/sur_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17576,740,"SUR","Suriname","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SUR/BSGM/2020/DTE/sur_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17577,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SJM/BSGM/2001/Binary/sjm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17578,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SJM/BSGM/2001/DTE/sjm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17579,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SJM/BSGM/2002/Binary/sjm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17580,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SJM/BSGM/2002/DTE/sjm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17581,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SJM/BSGM/2003/Binary/sjm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17582,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SJM/BSGM/2003/DTE/sjm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17583,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SJM/BSGM/2004/Binary/sjm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17584,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SJM/BSGM/2004/DTE/sjm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17585,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SJM/BSGM/2005/Binary/sjm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17586,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SJM/BSGM/2005/DTE/sjm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17587,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SJM/BSGM/2006/Binary/sjm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17588,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SJM/BSGM/2006/DTE/sjm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17589,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SJM/BSGM/2007/Binary/sjm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17590,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SJM/BSGM/2007/DTE/sjm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17591,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SJM/BSGM/2008/Binary/sjm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17592,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SJM/BSGM/2008/DTE/sjm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17593,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SJM/BSGM/2009/Binary/sjm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17594,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SJM/BSGM/2009/DTE/sjm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17595,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SJM/BSGM/2010/Binary/sjm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17596,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SJM/BSGM/2010/DTE/sjm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17597,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SJM/BSGM/2011/Binary/sjm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17598,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SJM/BSGM/2011/DTE/sjm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17599,744,"SJM","Svalbard and Jan Mayen Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SJM/BSGM/2013/Binary/sjm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17600,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SJM/BSGM/2013/DTE/sjm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17601,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SJM/BSGM/2015/DTE/sjm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17602,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SJM/BSGM/2016/DTE/sjm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17603,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SJM/BSGM/2017/DTE/sjm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17604,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SJM/BSGM/2018/DTE/sjm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17605,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SJM/BSGM/2019/DTE/sjm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17606,744,"SJM","Svalbard and Jan Mayen Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SJM/BSGM/2020/DTE/sjm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17607,748,"SWZ","Swaziland","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2001/Binary/swz_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17608,748,"SWZ","Swaziland","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2001/DTE/swz_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17609,748,"SWZ","Swaziland","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2002/Binary/swz_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17610,748,"SWZ","Swaziland","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2002/DTE/swz_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17611,748,"SWZ","Swaziland","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2003/Binary/swz_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17612,748,"SWZ","Swaziland","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2003/DTE/swz_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17613,748,"SWZ","Swaziland","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2004/Binary/swz_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17614,748,"SWZ","Swaziland","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2004/DTE/swz_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17615,748,"SWZ","Swaziland","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2005/Binary/swz_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17616,748,"SWZ","Swaziland","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2005/DTE/swz_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17617,748,"SWZ","Swaziland","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2006/Binary/swz_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17618,748,"SWZ","Swaziland","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2006/DTE/swz_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17619,748,"SWZ","Swaziland","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2007/Binary/swz_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17620,748,"SWZ","Swaziland","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2007/DTE/swz_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17621,748,"SWZ","Swaziland","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2008/Binary/swz_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17622,748,"SWZ","Swaziland","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2008/DTE/swz_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17623,748,"SWZ","Swaziland","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2009/Binary/swz_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17624,748,"SWZ","Swaziland","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2009/DTE/swz_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17625,748,"SWZ","Swaziland","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2010/Binary/swz_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17626,748,"SWZ","Swaziland","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2010/DTE/swz_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17627,748,"SWZ","Swaziland","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2011/Binary/swz_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17628,748,"SWZ","Swaziland","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2011/DTE/swz_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17629,748,"SWZ","Swaziland","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2013/Binary/swz_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17630,748,"SWZ","Swaziland","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2013/DTE/swz_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17631,748,"SWZ","Swaziland","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2015/DTE/swz_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17632,748,"SWZ","Swaziland","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2016/DTE/swz_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17633,748,"SWZ","Swaziland","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2017/DTE/swz_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17634,748,"SWZ","Swaziland","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2018/DTE/swz_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17635,748,"SWZ","Swaziland","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2019/DTE/swz_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17636,748,"SWZ","Swaziland","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SWZ/BSGM/2020/DTE/swz_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17637,752,"SWE","Sweden","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SWE/BSGM/2001/Binary/swe_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17638,752,"SWE","Sweden","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SWE/BSGM/2001/DTE/swe_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17639,752,"SWE","Sweden","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SWE/BSGM/2002/Binary/swe_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17640,752,"SWE","Sweden","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SWE/BSGM/2002/DTE/swe_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17641,752,"SWE","Sweden","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SWE/BSGM/2003/Binary/swe_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17642,752,"SWE","Sweden","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SWE/BSGM/2003/DTE/swe_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17643,752,"SWE","Sweden","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SWE/BSGM/2004/Binary/swe_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17644,752,"SWE","Sweden","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SWE/BSGM/2004/DTE/swe_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17645,752,"SWE","Sweden","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SWE/BSGM/2005/Binary/swe_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17646,752,"SWE","Sweden","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SWE/BSGM/2005/DTE/swe_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17647,752,"SWE","Sweden","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SWE/BSGM/2006/Binary/swe_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17648,752,"SWE","Sweden","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SWE/BSGM/2006/DTE/swe_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17649,752,"SWE","Sweden","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SWE/BSGM/2007/Binary/swe_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17650,752,"SWE","Sweden","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SWE/BSGM/2007/DTE/swe_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17651,752,"SWE","Sweden","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SWE/BSGM/2008/Binary/swe_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17652,752,"SWE","Sweden","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SWE/BSGM/2008/DTE/swe_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17653,752,"SWE","Sweden","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SWE/BSGM/2009/Binary/swe_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17654,752,"SWE","Sweden","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SWE/BSGM/2009/DTE/swe_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17655,752,"SWE","Sweden","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SWE/BSGM/2010/Binary/swe_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17656,752,"SWE","Sweden","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SWE/BSGM/2010/DTE/swe_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17657,752,"SWE","Sweden","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SWE/BSGM/2011/Binary/swe_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17658,752,"SWE","Sweden","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SWE/BSGM/2011/DTE/swe_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17659,752,"SWE","Sweden","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SWE/BSGM/2013/Binary/swe_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17660,752,"SWE","Sweden","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SWE/BSGM/2013/DTE/swe_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17661,752,"SWE","Sweden","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SWE/BSGM/2015/DTE/swe_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17662,752,"SWE","Sweden","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SWE/BSGM/2016/DTE/swe_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17663,752,"SWE","Sweden","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SWE/BSGM/2017/DTE/swe_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17664,752,"SWE","Sweden","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SWE/BSGM/2018/DTE/swe_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17665,752,"SWE","Sweden","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SWE/BSGM/2019/DTE/swe_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17666,752,"SWE","Sweden","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SWE/BSGM/2020/DTE/swe_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17667,756,"CHE","Switzerland","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CHE/BSGM/2001/Binary/che_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17668,756,"CHE","Switzerland","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/CHE/BSGM/2001/DTE/che_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17669,756,"CHE","Switzerland","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CHE/BSGM/2002/Binary/che_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17670,756,"CHE","Switzerland","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/CHE/BSGM/2002/DTE/che_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17671,756,"CHE","Switzerland","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CHE/BSGM/2003/Binary/che_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17672,756,"CHE","Switzerland","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/CHE/BSGM/2003/DTE/che_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17673,756,"CHE","Switzerland","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CHE/BSGM/2004/Binary/che_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17674,756,"CHE","Switzerland","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/CHE/BSGM/2004/DTE/che_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17675,756,"CHE","Switzerland","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CHE/BSGM/2005/Binary/che_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17676,756,"CHE","Switzerland","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/CHE/BSGM/2005/DTE/che_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17677,756,"CHE","Switzerland","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CHE/BSGM/2006/Binary/che_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17678,756,"CHE","Switzerland","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/CHE/BSGM/2006/DTE/che_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17679,756,"CHE","Switzerland","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CHE/BSGM/2007/Binary/che_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17680,756,"CHE","Switzerland","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/CHE/BSGM/2007/DTE/che_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17681,756,"CHE","Switzerland","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CHE/BSGM/2008/Binary/che_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17682,756,"CHE","Switzerland","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/CHE/BSGM/2008/DTE/che_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17683,756,"CHE","Switzerland","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CHE/BSGM/2009/Binary/che_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17684,756,"CHE","Switzerland","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/CHE/BSGM/2009/DTE/che_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17685,756,"CHE","Switzerland","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CHE/BSGM/2010/Binary/che_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17686,756,"CHE","Switzerland","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/CHE/BSGM/2010/DTE/che_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17687,756,"CHE","Switzerland","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CHE/BSGM/2011/Binary/che_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17688,756,"CHE","Switzerland","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/CHE/BSGM/2011/DTE/che_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17689,756,"CHE","Switzerland","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CHE/BSGM/2013/Binary/che_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17690,756,"CHE","Switzerland","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/CHE/BSGM/2013/DTE/che_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17691,756,"CHE","Switzerland","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/CHE/BSGM/2015/DTE/che_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17692,756,"CHE","Switzerland","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/CHE/BSGM/2016/DTE/che_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17693,756,"CHE","Switzerland","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/CHE/BSGM/2017/DTE/che_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17694,756,"CHE","Switzerland","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/CHE/BSGM/2018/DTE/che_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17695,756,"CHE","Switzerland","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/CHE/BSGM/2019/DTE/che_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17696,756,"CHE","Switzerland","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/CHE/BSGM/2020/DTE/che_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17697,760,"SYR","Syria","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SYR/BSGM/2001/Binary/syr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17698,760,"SYR","Syria","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SYR/BSGM/2001/DTE/syr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17699,760,"SYR","Syria","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SYR/BSGM/2002/Binary/syr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17700,760,"SYR","Syria","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SYR/BSGM/2002/DTE/syr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17701,760,"SYR","Syria","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SYR/BSGM/2003/Binary/syr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17702,760,"SYR","Syria","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SYR/BSGM/2003/DTE/syr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17703,760,"SYR","Syria","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SYR/BSGM/2004/Binary/syr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17704,760,"SYR","Syria","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SYR/BSGM/2004/DTE/syr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17705,760,"SYR","Syria","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SYR/BSGM/2005/Binary/syr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17706,760,"SYR","Syria","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SYR/BSGM/2005/DTE/syr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17707,760,"SYR","Syria","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SYR/BSGM/2006/Binary/syr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17708,760,"SYR","Syria","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SYR/BSGM/2006/DTE/syr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17709,760,"SYR","Syria","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SYR/BSGM/2007/Binary/syr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17710,760,"SYR","Syria","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SYR/BSGM/2007/DTE/syr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17711,760,"SYR","Syria","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SYR/BSGM/2008/Binary/syr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17712,760,"SYR","Syria","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SYR/BSGM/2008/DTE/syr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17713,760,"SYR","Syria","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SYR/BSGM/2009/Binary/syr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17714,760,"SYR","Syria","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SYR/BSGM/2009/DTE/syr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17715,760,"SYR","Syria","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SYR/BSGM/2010/Binary/syr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17716,760,"SYR","Syria","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SYR/BSGM/2010/DTE/syr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17717,760,"SYR","Syria","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SYR/BSGM/2011/Binary/syr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17718,760,"SYR","Syria","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SYR/BSGM/2011/DTE/syr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17719,760,"SYR","Syria","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SYR/BSGM/2013/Binary/syr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17720,760,"SYR","Syria","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SYR/BSGM/2013/DTE/syr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17721,760,"SYR","Syria","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SYR/BSGM/2015/DTE/syr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17722,760,"SYR","Syria","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SYR/BSGM/2016/DTE/syr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17723,760,"SYR","Syria","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SYR/BSGM/2017/DTE/syr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17724,760,"SYR","Syria","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SYR/BSGM/2018/DTE/syr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17725,760,"SYR","Syria","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SYR/BSGM/2019/DTE/syr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17726,760,"SYR","Syria","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SYR/BSGM/2020/DTE/syr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17727,762,"TJK","Tajikistan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TJK/BSGM/2001/Binary/tjk_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17728,762,"TJK","Tajikistan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TJK/BSGM/2001/DTE/tjk_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17729,762,"TJK","Tajikistan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TJK/BSGM/2002/Binary/tjk_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17730,762,"TJK","Tajikistan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TJK/BSGM/2002/DTE/tjk_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17731,762,"TJK","Tajikistan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TJK/BSGM/2003/Binary/tjk_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17732,762,"TJK","Tajikistan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TJK/BSGM/2003/DTE/tjk_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17733,762,"TJK","Tajikistan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TJK/BSGM/2004/Binary/tjk_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17734,762,"TJK","Tajikistan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TJK/BSGM/2004/DTE/tjk_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17735,762,"TJK","Tajikistan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TJK/BSGM/2005/Binary/tjk_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17736,762,"TJK","Tajikistan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TJK/BSGM/2005/DTE/tjk_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17737,762,"TJK","Tajikistan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TJK/BSGM/2006/Binary/tjk_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17738,762,"TJK","Tajikistan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TJK/BSGM/2006/DTE/tjk_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17739,762,"TJK","Tajikistan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TJK/BSGM/2007/Binary/tjk_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17740,762,"TJK","Tajikistan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TJK/BSGM/2007/DTE/tjk_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17741,762,"TJK","Tajikistan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TJK/BSGM/2008/Binary/tjk_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17742,762,"TJK","Tajikistan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TJK/BSGM/2008/DTE/tjk_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17743,762,"TJK","Tajikistan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TJK/BSGM/2009/Binary/tjk_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17744,762,"TJK","Tajikistan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TJK/BSGM/2009/DTE/tjk_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17745,762,"TJK","Tajikistan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TJK/BSGM/2010/Binary/tjk_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17746,762,"TJK","Tajikistan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TJK/BSGM/2010/DTE/tjk_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17747,762,"TJK","Tajikistan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TJK/BSGM/2011/Binary/tjk_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17748,762,"TJK","Tajikistan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TJK/BSGM/2011/DTE/tjk_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17749,762,"TJK","Tajikistan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TJK/BSGM/2013/Binary/tjk_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17750,762,"TJK","Tajikistan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TJK/BSGM/2013/DTE/tjk_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17751,762,"TJK","Tajikistan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TJK/BSGM/2015/DTE/tjk_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17752,762,"TJK","Tajikistan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TJK/BSGM/2016/DTE/tjk_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17753,762,"TJK","Tajikistan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TJK/BSGM/2017/DTE/tjk_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17754,762,"TJK","Tajikistan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TJK/BSGM/2018/DTE/tjk_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17755,762,"TJK","Tajikistan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TJK/BSGM/2019/DTE/tjk_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17756,762,"TJK","Tajikistan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TJK/BSGM/2020/DTE/tjk_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17757,764,"THA","Thailand","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/THA/BSGM/2001/Binary/tha_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17758,764,"THA","Thailand","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/THA/BSGM/2001/DTE/tha_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17759,764,"THA","Thailand","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/THA/BSGM/2002/Binary/tha_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17760,764,"THA","Thailand","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/THA/BSGM/2002/DTE/tha_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17761,764,"THA","Thailand","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/THA/BSGM/2003/Binary/tha_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17762,764,"THA","Thailand","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/THA/BSGM/2003/DTE/tha_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17763,764,"THA","Thailand","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/THA/BSGM/2004/Binary/tha_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17764,764,"THA","Thailand","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/THA/BSGM/2004/DTE/tha_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17765,764,"THA","Thailand","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/THA/BSGM/2005/Binary/tha_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17766,764,"THA","Thailand","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/THA/BSGM/2005/DTE/tha_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17767,764,"THA","Thailand","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/THA/BSGM/2006/Binary/tha_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17768,764,"THA","Thailand","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/THA/BSGM/2006/DTE/tha_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17769,764,"THA","Thailand","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/THA/BSGM/2007/Binary/tha_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17770,764,"THA","Thailand","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/THA/BSGM/2007/DTE/tha_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17771,764,"THA","Thailand","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/THA/BSGM/2008/Binary/tha_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17772,764,"THA","Thailand","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/THA/BSGM/2008/DTE/tha_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17773,764,"THA","Thailand","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/THA/BSGM/2009/Binary/tha_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17774,764,"THA","Thailand","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/THA/BSGM/2009/DTE/tha_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17775,764,"THA","Thailand","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/THA/BSGM/2010/Binary/tha_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17776,764,"THA","Thailand","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/THA/BSGM/2010/DTE/tha_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17777,764,"THA","Thailand","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/THA/BSGM/2011/Binary/tha_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17778,764,"THA","Thailand","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/THA/BSGM/2011/DTE/tha_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17779,764,"THA","Thailand","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/THA/BSGM/2013/Binary/tha_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17780,764,"THA","Thailand","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/THA/BSGM/2013/DTE/tha_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17781,764,"THA","Thailand","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/THA/BSGM/2015/DTE/tha_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17782,764,"THA","Thailand","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/THA/BSGM/2016/DTE/tha_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17783,764,"THA","Thailand","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/THA/BSGM/2017/DTE/tha_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17784,764,"THA","Thailand","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/THA/BSGM/2018/DTE/tha_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17785,764,"THA","Thailand","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/THA/BSGM/2019/DTE/tha_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17786,764,"THA","Thailand","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/THA/BSGM/2020/DTE/tha_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17787,768,"TGO","Togo","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TGO/BSGM/2001/Binary/tgo_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17788,768,"TGO","Togo","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TGO/BSGM/2001/DTE/tgo_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17789,768,"TGO","Togo","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TGO/BSGM/2002/Binary/tgo_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17790,768,"TGO","Togo","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TGO/BSGM/2002/DTE/tgo_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17791,768,"TGO","Togo","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TGO/BSGM/2003/Binary/tgo_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17792,768,"TGO","Togo","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TGO/BSGM/2003/DTE/tgo_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17793,768,"TGO","Togo","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TGO/BSGM/2004/Binary/tgo_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17794,768,"TGO","Togo","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TGO/BSGM/2004/DTE/tgo_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17795,768,"TGO","Togo","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TGO/BSGM/2005/Binary/tgo_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17796,768,"TGO","Togo","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TGO/BSGM/2005/DTE/tgo_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17797,768,"TGO","Togo","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TGO/BSGM/2006/Binary/tgo_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17798,768,"TGO","Togo","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TGO/BSGM/2006/DTE/tgo_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17799,768,"TGO","Togo","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TGO/BSGM/2007/Binary/tgo_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17800,768,"TGO","Togo","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TGO/BSGM/2007/DTE/tgo_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17801,768,"TGO","Togo","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TGO/BSGM/2008/Binary/tgo_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17802,768,"TGO","Togo","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TGO/BSGM/2008/DTE/tgo_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17803,768,"TGO","Togo","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TGO/BSGM/2009/Binary/tgo_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17804,768,"TGO","Togo","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TGO/BSGM/2009/DTE/tgo_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17805,768,"TGO","Togo","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TGO/BSGM/2010/Binary/tgo_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17806,768,"TGO","Togo","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TGO/BSGM/2010/DTE/tgo_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17807,768,"TGO","Togo","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TGO/BSGM/2011/Binary/tgo_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17808,768,"TGO","Togo","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TGO/BSGM/2011/DTE/tgo_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17809,768,"TGO","Togo","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TGO/BSGM/2013/Binary/tgo_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17810,768,"TGO","Togo","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TGO/BSGM/2013/DTE/tgo_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17811,768,"TGO","Togo","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TGO/BSGM/2015/DTE/tgo_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17812,768,"TGO","Togo","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TGO/BSGM/2016/DTE/tgo_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17813,768,"TGO","Togo","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TGO/BSGM/2017/DTE/tgo_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17814,768,"TGO","Togo","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TGO/BSGM/2018/DTE/tgo_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17815,768,"TGO","Togo","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TGO/BSGM/2019/DTE/tgo_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17816,768,"TGO","Togo","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TGO/BSGM/2020/DTE/tgo_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17817,772,"TKL","Tokelau","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TKL/BSGM/2001/Binary/tkl_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17818,772,"TKL","Tokelau","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TKL/BSGM/2001/DTE/tkl_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17819,772,"TKL","Tokelau","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TKL/BSGM/2002/Binary/tkl_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17820,772,"TKL","Tokelau","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TKL/BSGM/2002/DTE/tkl_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17821,772,"TKL","Tokelau","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TKL/BSGM/2003/Binary/tkl_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17822,772,"TKL","Tokelau","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TKL/BSGM/2003/DTE/tkl_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17823,772,"TKL","Tokelau","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TKL/BSGM/2004/Binary/tkl_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17824,772,"TKL","Tokelau","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TKL/BSGM/2004/DTE/tkl_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17825,772,"TKL","Tokelau","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TKL/BSGM/2005/Binary/tkl_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17826,772,"TKL","Tokelau","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TKL/BSGM/2005/DTE/tkl_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17827,772,"TKL","Tokelau","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TKL/BSGM/2006/Binary/tkl_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17828,772,"TKL","Tokelau","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TKL/BSGM/2006/DTE/tkl_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17829,772,"TKL","Tokelau","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TKL/BSGM/2007/Binary/tkl_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17830,772,"TKL","Tokelau","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TKL/BSGM/2007/DTE/tkl_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17831,772,"TKL","Tokelau","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TKL/BSGM/2008/Binary/tkl_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17832,772,"TKL","Tokelau","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TKL/BSGM/2008/DTE/tkl_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17833,772,"TKL","Tokelau","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TKL/BSGM/2009/Binary/tkl_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17834,772,"TKL","Tokelau","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TKL/BSGM/2009/DTE/tkl_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17835,772,"TKL","Tokelau","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TKL/BSGM/2010/Binary/tkl_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17836,772,"TKL","Tokelau","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TKL/BSGM/2010/DTE/tkl_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17837,772,"TKL","Tokelau","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TKL/BSGM/2011/Binary/tkl_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17838,772,"TKL","Tokelau","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TKL/BSGM/2011/DTE/tkl_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17839,772,"TKL","Tokelau","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TKL/BSGM/2013/Binary/tkl_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17840,772,"TKL","Tokelau","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TKL/BSGM/2013/DTE/tkl_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17841,772,"TKL","Tokelau","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TKL/BSGM/2015/DTE/tkl_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17842,772,"TKL","Tokelau","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TKL/BSGM/2016/DTE/tkl_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17843,772,"TKL","Tokelau","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TKL/BSGM/2017/DTE/tkl_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17844,772,"TKL","Tokelau","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TKL/BSGM/2018/DTE/tkl_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17845,772,"TKL","Tokelau","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TKL/BSGM/2019/DTE/tkl_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17846,772,"TKL","Tokelau","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TKL/BSGM/2020/DTE/tkl_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17847,776,"TON","Tonga","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TON/BSGM/2001/Binary/ton_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17848,776,"TON","Tonga","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TON/BSGM/2001/DTE/ton_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17849,776,"TON","Tonga","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TON/BSGM/2002/Binary/ton_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17850,776,"TON","Tonga","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TON/BSGM/2002/DTE/ton_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17851,776,"TON","Tonga","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TON/BSGM/2003/Binary/ton_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17852,776,"TON","Tonga","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TON/BSGM/2003/DTE/ton_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17853,776,"TON","Tonga","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TON/BSGM/2004/Binary/ton_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17854,776,"TON","Tonga","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TON/BSGM/2004/DTE/ton_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17855,776,"TON","Tonga","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TON/BSGM/2005/Binary/ton_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17856,776,"TON","Tonga","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TON/BSGM/2005/DTE/ton_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17857,776,"TON","Tonga","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TON/BSGM/2006/Binary/ton_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17858,776,"TON","Tonga","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TON/BSGM/2006/DTE/ton_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17859,776,"TON","Tonga","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TON/BSGM/2007/Binary/ton_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17860,776,"TON","Tonga","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TON/BSGM/2007/DTE/ton_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17861,776,"TON","Tonga","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TON/BSGM/2008/Binary/ton_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17862,776,"TON","Tonga","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TON/BSGM/2008/DTE/ton_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17863,776,"TON","Tonga","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TON/BSGM/2009/Binary/ton_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17864,776,"TON","Tonga","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TON/BSGM/2009/DTE/ton_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17865,776,"TON","Tonga","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TON/BSGM/2010/Binary/ton_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17866,776,"TON","Tonga","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TON/BSGM/2010/DTE/ton_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17867,776,"TON","Tonga","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TON/BSGM/2011/Binary/ton_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17868,776,"TON","Tonga","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TON/BSGM/2011/DTE/ton_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17869,776,"TON","Tonga","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TON/BSGM/2013/Binary/ton_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17870,776,"TON","Tonga","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TON/BSGM/2013/DTE/ton_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17871,776,"TON","Tonga","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TON/BSGM/2015/DTE/ton_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17872,776,"TON","Tonga","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TON/BSGM/2016/DTE/ton_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17873,776,"TON","Tonga","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TON/BSGM/2017/DTE/ton_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17874,776,"TON","Tonga","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TON/BSGM/2018/DTE/ton_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17875,776,"TON","Tonga","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TON/BSGM/2019/DTE/ton_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17876,776,"TON","Tonga","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TON/BSGM/2020/DTE/ton_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17877,780,"TTO","Trinidad and Tobago","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TTO/BSGM/2001/Binary/tto_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17878,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TTO/BSGM/2001/DTE/tto_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17879,780,"TTO","Trinidad and Tobago","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TTO/BSGM/2002/Binary/tto_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17880,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TTO/BSGM/2002/DTE/tto_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17881,780,"TTO","Trinidad and Tobago","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TTO/BSGM/2003/Binary/tto_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17882,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TTO/BSGM/2003/DTE/tto_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17883,780,"TTO","Trinidad and Tobago","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TTO/BSGM/2004/Binary/tto_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17884,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TTO/BSGM/2004/DTE/tto_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17885,780,"TTO","Trinidad and Tobago","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TTO/BSGM/2005/Binary/tto_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17886,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TTO/BSGM/2005/DTE/tto_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17887,780,"TTO","Trinidad and Tobago","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TTO/BSGM/2006/Binary/tto_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17888,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TTO/BSGM/2006/DTE/tto_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17889,780,"TTO","Trinidad and Tobago","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TTO/BSGM/2007/Binary/tto_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17890,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TTO/BSGM/2007/DTE/tto_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17891,780,"TTO","Trinidad and Tobago","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TTO/BSGM/2008/Binary/tto_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17892,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TTO/BSGM/2008/DTE/tto_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17893,780,"TTO","Trinidad and Tobago","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TTO/BSGM/2009/Binary/tto_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17894,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TTO/BSGM/2009/DTE/tto_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17895,780,"TTO","Trinidad and Tobago","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TTO/BSGM/2010/Binary/tto_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17896,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TTO/BSGM/2010/DTE/tto_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17897,780,"TTO","Trinidad and Tobago","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TTO/BSGM/2011/Binary/tto_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17898,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TTO/BSGM/2011/DTE/tto_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17899,780,"TTO","Trinidad and Tobago","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TTO/BSGM/2013/Binary/tto_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17900,780,"TTO","Trinidad and Tobago","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TTO/BSGM/2013/DTE/tto_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17901,780,"TTO","Trinidad and Tobago","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TTO/BSGM/2015/DTE/tto_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17902,780,"TTO","Trinidad and Tobago","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TTO/BSGM/2016/DTE/tto_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17903,780,"TTO","Trinidad and Tobago","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TTO/BSGM/2017/DTE/tto_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17904,780,"TTO","Trinidad and Tobago","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TTO/BSGM/2018/DTE/tto_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17905,780,"TTO","Trinidad and Tobago","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TTO/BSGM/2019/DTE/tto_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17906,780,"TTO","Trinidad and Tobago","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TTO/BSGM/2020/DTE/tto_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17907,784,"ARE","United Arab Emirates","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ARE/BSGM/2001/Binary/are_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17908,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ARE/BSGM/2001/DTE/are_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17909,784,"ARE","United Arab Emirates","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ARE/BSGM/2002/Binary/are_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17910,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ARE/BSGM/2002/DTE/are_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17911,784,"ARE","United Arab Emirates","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ARE/BSGM/2003/Binary/are_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17912,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ARE/BSGM/2003/DTE/are_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17913,784,"ARE","United Arab Emirates","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ARE/BSGM/2004/Binary/are_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17914,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ARE/BSGM/2004/DTE/are_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17915,784,"ARE","United Arab Emirates","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ARE/BSGM/2005/Binary/are_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17916,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ARE/BSGM/2005/DTE/are_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17917,784,"ARE","United Arab Emirates","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ARE/BSGM/2006/Binary/are_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17918,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ARE/BSGM/2006/DTE/are_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17919,784,"ARE","United Arab Emirates","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ARE/BSGM/2007/Binary/are_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17920,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ARE/BSGM/2007/DTE/are_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17921,784,"ARE","United Arab Emirates","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ARE/BSGM/2008/Binary/are_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17922,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ARE/BSGM/2008/DTE/are_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17923,784,"ARE","United Arab Emirates","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ARE/BSGM/2009/Binary/are_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17924,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ARE/BSGM/2009/DTE/are_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17925,784,"ARE","United Arab Emirates","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ARE/BSGM/2010/Binary/are_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17926,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ARE/BSGM/2010/DTE/are_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17927,784,"ARE","United Arab Emirates","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ARE/BSGM/2011/Binary/are_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17928,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ARE/BSGM/2011/DTE/are_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17929,784,"ARE","United Arab Emirates","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ARE/BSGM/2013/Binary/are_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17930,784,"ARE","United Arab Emirates","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ARE/BSGM/2013/DTE/are_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17931,784,"ARE","United Arab Emirates","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ARE/BSGM/2015/DTE/are_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17932,784,"ARE","United Arab Emirates","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ARE/BSGM/2016/DTE/are_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17933,784,"ARE","United Arab Emirates","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ARE/BSGM/2017/DTE/are_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17934,784,"ARE","United Arab Emirates","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ARE/BSGM/2018/DTE/are_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17935,784,"ARE","United Arab Emirates","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ARE/BSGM/2019/DTE/are_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17936,784,"ARE","United Arab Emirates","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ARE/BSGM/2020/DTE/are_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17937,788,"TUN","Tunisia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TUN/BSGM/2001/Binary/tun_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17938,788,"TUN","Tunisia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TUN/BSGM/2001/DTE/tun_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17939,788,"TUN","Tunisia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TUN/BSGM/2002/Binary/tun_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17940,788,"TUN","Tunisia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TUN/BSGM/2002/DTE/tun_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17941,788,"TUN","Tunisia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TUN/BSGM/2003/Binary/tun_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17942,788,"TUN","Tunisia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TUN/BSGM/2003/DTE/tun_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17943,788,"TUN","Tunisia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TUN/BSGM/2004/Binary/tun_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17944,788,"TUN","Tunisia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TUN/BSGM/2004/DTE/tun_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17945,788,"TUN","Tunisia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TUN/BSGM/2005/Binary/tun_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17946,788,"TUN","Tunisia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TUN/BSGM/2005/DTE/tun_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17947,788,"TUN","Tunisia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TUN/BSGM/2006/Binary/tun_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17948,788,"TUN","Tunisia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TUN/BSGM/2006/DTE/tun_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17949,788,"TUN","Tunisia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TUN/BSGM/2007/Binary/tun_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17950,788,"TUN","Tunisia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TUN/BSGM/2007/DTE/tun_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17951,788,"TUN","Tunisia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TUN/BSGM/2008/Binary/tun_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17952,788,"TUN","Tunisia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TUN/BSGM/2008/DTE/tun_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17953,788,"TUN","Tunisia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TUN/BSGM/2009/Binary/tun_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17954,788,"TUN","Tunisia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TUN/BSGM/2009/DTE/tun_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17955,788,"TUN","Tunisia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TUN/BSGM/2010/Binary/tun_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17956,788,"TUN","Tunisia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TUN/BSGM/2010/DTE/tun_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17957,788,"TUN","Tunisia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TUN/BSGM/2011/Binary/tun_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17958,788,"TUN","Tunisia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TUN/BSGM/2011/DTE/tun_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17959,788,"TUN","Tunisia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TUN/BSGM/2013/Binary/tun_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17960,788,"TUN","Tunisia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TUN/BSGM/2013/DTE/tun_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17961,788,"TUN","Tunisia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TUN/BSGM/2015/DTE/tun_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17962,788,"TUN","Tunisia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TUN/BSGM/2016/DTE/tun_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17963,788,"TUN","Tunisia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TUN/BSGM/2017/DTE/tun_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17964,788,"TUN","Tunisia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TUN/BSGM/2018/DTE/tun_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17965,788,"TUN","Tunisia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TUN/BSGM/2019/DTE/tun_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17966,788,"TUN","Tunisia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TUN/BSGM/2020/DTE/tun_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17967,792,"TUR","Turkey","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TUR/BSGM/2001/Binary/tur_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17968,792,"TUR","Turkey","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TUR/BSGM/2001/DTE/tur_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17969,792,"TUR","Turkey","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TUR/BSGM/2002/Binary/tur_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
17970,792,"TUR","Turkey","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TUR/BSGM/2002/DTE/tur_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
17971,792,"TUR","Turkey","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TUR/BSGM/2003/Binary/tur_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
17972,792,"TUR","Turkey","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TUR/BSGM/2003/DTE/tur_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
17973,792,"TUR","Turkey","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TUR/BSGM/2004/Binary/tur_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
17974,792,"TUR","Turkey","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TUR/BSGM/2004/DTE/tur_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
17975,792,"TUR","Turkey","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TUR/BSGM/2005/Binary/tur_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
17976,792,"TUR","Turkey","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TUR/BSGM/2005/DTE/tur_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
17977,792,"TUR","Turkey","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TUR/BSGM/2006/Binary/tur_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
17978,792,"TUR","Turkey","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TUR/BSGM/2006/DTE/tur_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
17979,792,"TUR","Turkey","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TUR/BSGM/2007/Binary/tur_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
17980,792,"TUR","Turkey","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TUR/BSGM/2007/DTE/tur_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
17981,792,"TUR","Turkey","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TUR/BSGM/2008/Binary/tur_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
17982,792,"TUR","Turkey","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TUR/BSGM/2008/DTE/tur_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
17983,792,"TUR","Turkey","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TUR/BSGM/2009/Binary/tur_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
17984,792,"TUR","Turkey","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TUR/BSGM/2009/DTE/tur_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
17985,792,"TUR","Turkey","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TUR/BSGM/2010/Binary/tur_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
17986,792,"TUR","Turkey","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TUR/BSGM/2010/DTE/tur_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
17987,792,"TUR","Turkey","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TUR/BSGM/2011/Binary/tur_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
17988,792,"TUR","Turkey","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TUR/BSGM/2011/DTE/tur_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
17989,792,"TUR","Turkey","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TUR/BSGM/2013/Binary/tur_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
17990,792,"TUR","Turkey","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TUR/BSGM/2013/DTE/tur_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
17991,792,"TUR","Turkey","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TUR/BSGM/2015/DTE/tur_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
17992,792,"TUR","Turkey","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TUR/BSGM/2016/DTE/tur_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
17993,792,"TUR","Turkey","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TUR/BSGM/2017/DTE/tur_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
17994,792,"TUR","Turkey","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TUR/BSGM/2018/DTE/tur_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
17995,792,"TUR","Turkey","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TUR/BSGM/2019/DTE/tur_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
17996,792,"TUR","Turkey","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TUR/BSGM/2020/DTE/tur_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
17997,795,"TKM","Turkmenistan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TKM/BSGM/2001/Binary/tkm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
17998,795,"TKM","Turkmenistan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TKM/BSGM/2001/DTE/tkm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
17999,795,"TKM","Turkmenistan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TKM/BSGM/2002/Binary/tkm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18000,795,"TKM","Turkmenistan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TKM/BSGM/2002/DTE/tkm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18001,795,"TKM","Turkmenistan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TKM/BSGM/2003/Binary/tkm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18002,795,"TKM","Turkmenistan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TKM/BSGM/2003/DTE/tkm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18003,795,"TKM","Turkmenistan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TKM/BSGM/2004/Binary/tkm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18004,795,"TKM","Turkmenistan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TKM/BSGM/2004/DTE/tkm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18005,795,"TKM","Turkmenistan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TKM/BSGM/2005/Binary/tkm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18006,795,"TKM","Turkmenistan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TKM/BSGM/2005/DTE/tkm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18007,795,"TKM","Turkmenistan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TKM/BSGM/2006/Binary/tkm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18008,795,"TKM","Turkmenistan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TKM/BSGM/2006/DTE/tkm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18009,795,"TKM","Turkmenistan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TKM/BSGM/2007/Binary/tkm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18010,795,"TKM","Turkmenistan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TKM/BSGM/2007/DTE/tkm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18011,795,"TKM","Turkmenistan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TKM/BSGM/2008/Binary/tkm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18012,795,"TKM","Turkmenistan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TKM/BSGM/2008/DTE/tkm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18013,795,"TKM","Turkmenistan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TKM/BSGM/2009/Binary/tkm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18014,795,"TKM","Turkmenistan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TKM/BSGM/2009/DTE/tkm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18015,795,"TKM","Turkmenistan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TKM/BSGM/2010/Binary/tkm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18016,795,"TKM","Turkmenistan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TKM/BSGM/2010/DTE/tkm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18017,795,"TKM","Turkmenistan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TKM/BSGM/2011/Binary/tkm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18018,795,"TKM","Turkmenistan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TKM/BSGM/2011/DTE/tkm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18019,795,"TKM","Turkmenistan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TKM/BSGM/2013/Binary/tkm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18020,795,"TKM","Turkmenistan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TKM/BSGM/2013/DTE/tkm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18021,795,"TKM","Turkmenistan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TKM/BSGM/2015/DTE/tkm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18022,795,"TKM","Turkmenistan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TKM/BSGM/2016/DTE/tkm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18023,795,"TKM","Turkmenistan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TKM/BSGM/2017/DTE/tkm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18024,795,"TKM","Turkmenistan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TKM/BSGM/2018/DTE/tkm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18025,795,"TKM","Turkmenistan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TKM/BSGM/2019/DTE/tkm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18026,795,"TKM","Turkmenistan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TKM/BSGM/2020/DTE/tkm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18027,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TCA/BSGM/2001/Binary/tca_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18028,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TCA/BSGM/2001/DTE/tca_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18029,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TCA/BSGM/2002/Binary/tca_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18030,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TCA/BSGM/2002/DTE/tca_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18031,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TCA/BSGM/2003/Binary/tca_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18032,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TCA/BSGM/2003/DTE/tca_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18033,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TCA/BSGM/2004/Binary/tca_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18034,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TCA/BSGM/2004/DTE/tca_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18035,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TCA/BSGM/2005/Binary/tca_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18036,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TCA/BSGM/2005/DTE/tca_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18037,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TCA/BSGM/2006/Binary/tca_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18038,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TCA/BSGM/2006/DTE/tca_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18039,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TCA/BSGM/2007/Binary/tca_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18040,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TCA/BSGM/2007/DTE/tca_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18041,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TCA/BSGM/2008/Binary/tca_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18042,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TCA/BSGM/2008/DTE/tca_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18043,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TCA/BSGM/2009/Binary/tca_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18044,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TCA/BSGM/2009/DTE/tca_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18045,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TCA/BSGM/2010/Binary/tca_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18046,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TCA/BSGM/2010/DTE/tca_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18047,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TCA/BSGM/2011/Binary/tca_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18048,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TCA/BSGM/2011/DTE/tca_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18049,796,"TCA","Turks and Caicos Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TCA/BSGM/2013/Binary/tca_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18050,796,"TCA","Turks and Caicos Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TCA/BSGM/2013/DTE/tca_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18051,796,"TCA","Turks and Caicos Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TCA/BSGM/2015/DTE/tca_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18052,796,"TCA","Turks and Caicos Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TCA/BSGM/2016/DTE/tca_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18053,796,"TCA","Turks and Caicos Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TCA/BSGM/2017/DTE/tca_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18054,796,"TCA","Turks and Caicos Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TCA/BSGM/2018/DTE/tca_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18055,796,"TCA","Turks and Caicos Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TCA/BSGM/2019/DTE/tca_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18056,796,"TCA","Turks and Caicos Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TCA/BSGM/2020/DTE/tca_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18057,798,"TUV","Tuvalu","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TUV/BSGM/2001/Binary/tuv_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18058,798,"TUV","Tuvalu","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TUV/BSGM/2001/DTE/tuv_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18059,798,"TUV","Tuvalu","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TUV/BSGM/2002/Binary/tuv_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18060,798,"TUV","Tuvalu","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TUV/BSGM/2002/DTE/tuv_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18061,798,"TUV","Tuvalu","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TUV/BSGM/2003/Binary/tuv_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18062,798,"TUV","Tuvalu","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TUV/BSGM/2003/DTE/tuv_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18063,798,"TUV","Tuvalu","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TUV/BSGM/2004/Binary/tuv_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18064,798,"TUV","Tuvalu","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TUV/BSGM/2004/DTE/tuv_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18065,798,"TUV","Tuvalu","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TUV/BSGM/2005/Binary/tuv_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18066,798,"TUV","Tuvalu","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TUV/BSGM/2005/DTE/tuv_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18067,798,"TUV","Tuvalu","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TUV/BSGM/2006/Binary/tuv_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18068,798,"TUV","Tuvalu","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TUV/BSGM/2006/DTE/tuv_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18069,798,"TUV","Tuvalu","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TUV/BSGM/2007/Binary/tuv_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18070,798,"TUV","Tuvalu","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TUV/BSGM/2007/DTE/tuv_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18071,798,"TUV","Tuvalu","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TUV/BSGM/2008/Binary/tuv_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18072,798,"TUV","Tuvalu","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TUV/BSGM/2008/DTE/tuv_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18073,798,"TUV","Tuvalu","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TUV/BSGM/2009/Binary/tuv_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18074,798,"TUV","Tuvalu","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TUV/BSGM/2009/DTE/tuv_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18075,798,"TUV","Tuvalu","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TUV/BSGM/2010/Binary/tuv_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18076,798,"TUV","Tuvalu","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TUV/BSGM/2010/DTE/tuv_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18077,798,"TUV","Tuvalu","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TUV/BSGM/2011/Binary/tuv_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18078,798,"TUV","Tuvalu","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TUV/BSGM/2011/DTE/tuv_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18079,798,"TUV","Tuvalu","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TUV/BSGM/2013/Binary/tuv_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18080,798,"TUV","Tuvalu","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TUV/BSGM/2013/DTE/tuv_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18081,798,"TUV","Tuvalu","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TUV/BSGM/2015/DTE/tuv_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18082,798,"TUV","Tuvalu","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TUV/BSGM/2016/DTE/tuv_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18083,798,"TUV","Tuvalu","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TUV/BSGM/2017/DTE/tuv_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18084,798,"TUV","Tuvalu","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TUV/BSGM/2018/DTE/tuv_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18085,798,"TUV","Tuvalu","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TUV/BSGM/2019/DTE/tuv_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18086,798,"TUV","Tuvalu","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TUV/BSGM/2020/DTE/tuv_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18087,800,"UGA","Uganda","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/UGA/BSGM/2001/Binary/uga_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18088,800,"UGA","Uganda","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/UGA/BSGM/2001/DTE/uga_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18089,800,"UGA","Uganda","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/UGA/BSGM/2002/Binary/uga_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18090,800,"UGA","Uganda","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/UGA/BSGM/2002/DTE/uga_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18091,800,"UGA","Uganda","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/UGA/BSGM/2003/Binary/uga_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18092,800,"UGA","Uganda","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/UGA/BSGM/2003/DTE/uga_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18093,800,"UGA","Uganda","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/UGA/BSGM/2004/Binary/uga_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18094,800,"UGA","Uganda","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/UGA/BSGM/2004/DTE/uga_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18095,800,"UGA","Uganda","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/UGA/BSGM/2005/Binary/uga_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18096,800,"UGA","Uganda","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/UGA/BSGM/2005/DTE/uga_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18097,800,"UGA","Uganda","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/UGA/BSGM/2006/Binary/uga_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18098,800,"UGA","Uganda","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/UGA/BSGM/2006/DTE/uga_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18099,800,"UGA","Uganda","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/UGA/BSGM/2007/Binary/uga_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18100,800,"UGA","Uganda","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/UGA/BSGM/2007/DTE/uga_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18101,800,"UGA","Uganda","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/UGA/BSGM/2008/Binary/uga_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18102,800,"UGA","Uganda","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/UGA/BSGM/2008/DTE/uga_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18103,800,"UGA","Uganda","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/UGA/BSGM/2009/Binary/uga_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18104,800,"UGA","Uganda","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/UGA/BSGM/2009/DTE/uga_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18105,800,"UGA","Uganda","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/UGA/BSGM/2010/Binary/uga_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18106,800,"UGA","Uganda","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/UGA/BSGM/2010/DTE/uga_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18107,800,"UGA","Uganda","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/UGA/BSGM/2011/Binary/uga_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18108,800,"UGA","Uganda","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/UGA/BSGM/2011/DTE/uga_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18109,800,"UGA","Uganda","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/UGA/BSGM/2013/Binary/uga_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18110,800,"UGA","Uganda","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/UGA/BSGM/2013/DTE/uga_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18111,800,"UGA","Uganda","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/UGA/BSGM/2015/DTE/uga_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18112,800,"UGA","Uganda","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/UGA/BSGM/2016/DTE/uga_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18113,800,"UGA","Uganda","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/UGA/BSGM/2017/DTE/uga_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18114,800,"UGA","Uganda","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/UGA/BSGM/2018/DTE/uga_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18115,800,"UGA","Uganda","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/UGA/BSGM/2019/DTE/uga_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18116,800,"UGA","Uganda","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/UGA/BSGM/2020/DTE/uga_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18117,804,"UKR","Ukraine","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/UKR/BSGM/2001/Binary/ukr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18118,804,"UKR","Ukraine","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/UKR/BSGM/2001/DTE/ukr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18119,804,"UKR","Ukraine","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/UKR/BSGM/2002/Binary/ukr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18120,804,"UKR","Ukraine","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/UKR/BSGM/2002/DTE/ukr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18121,804,"UKR","Ukraine","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/UKR/BSGM/2003/Binary/ukr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18122,804,"UKR","Ukraine","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/UKR/BSGM/2003/DTE/ukr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18123,804,"UKR","Ukraine","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/UKR/BSGM/2004/Binary/ukr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18124,804,"UKR","Ukraine","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/UKR/BSGM/2004/DTE/ukr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18125,804,"UKR","Ukraine","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/UKR/BSGM/2005/Binary/ukr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18126,804,"UKR","Ukraine","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/UKR/BSGM/2005/DTE/ukr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18127,804,"UKR","Ukraine","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/UKR/BSGM/2006/Binary/ukr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18128,804,"UKR","Ukraine","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/UKR/BSGM/2006/DTE/ukr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18129,804,"UKR","Ukraine","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/UKR/BSGM/2007/Binary/ukr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18130,804,"UKR","Ukraine","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/UKR/BSGM/2007/DTE/ukr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18131,804,"UKR","Ukraine","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/UKR/BSGM/2008/Binary/ukr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18132,804,"UKR","Ukraine","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/UKR/BSGM/2008/DTE/ukr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18133,804,"UKR","Ukraine","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/UKR/BSGM/2009/Binary/ukr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18134,804,"UKR","Ukraine","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/UKR/BSGM/2009/DTE/ukr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18135,804,"UKR","Ukraine","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/UKR/BSGM/2010/Binary/ukr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18136,804,"UKR","Ukraine","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/UKR/BSGM/2010/DTE/ukr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18137,804,"UKR","Ukraine","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/UKR/BSGM/2011/Binary/ukr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18138,804,"UKR","Ukraine","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/UKR/BSGM/2011/DTE/ukr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18139,804,"UKR","Ukraine","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/UKR/BSGM/2013/Binary/ukr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18140,804,"UKR","Ukraine","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/UKR/BSGM/2013/DTE/ukr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18141,804,"UKR","Ukraine","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/UKR/BSGM/2015/DTE/ukr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18142,804,"UKR","Ukraine","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/UKR/BSGM/2016/DTE/ukr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18143,804,"UKR","Ukraine","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/UKR/BSGM/2017/DTE/ukr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18144,804,"UKR","Ukraine","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/UKR/BSGM/2018/DTE/ukr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18145,804,"UKR","Ukraine","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/UKR/BSGM/2019/DTE/ukr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18146,804,"UKR","Ukraine","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/UKR/BSGM/2020/DTE/ukr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18147,807,"MKD","Macedonia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MKD/BSGM/2001/Binary/mkd_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18148,807,"MKD","Macedonia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/MKD/BSGM/2001/DTE/mkd_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18149,807,"MKD","Macedonia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MKD/BSGM/2002/Binary/mkd_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18150,807,"MKD","Macedonia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/MKD/BSGM/2002/DTE/mkd_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18151,807,"MKD","Macedonia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MKD/BSGM/2003/Binary/mkd_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18152,807,"MKD","Macedonia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/MKD/BSGM/2003/DTE/mkd_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18153,807,"MKD","Macedonia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MKD/BSGM/2004/Binary/mkd_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18154,807,"MKD","Macedonia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/MKD/BSGM/2004/DTE/mkd_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18155,807,"MKD","Macedonia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MKD/BSGM/2005/Binary/mkd_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18156,807,"MKD","Macedonia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/MKD/BSGM/2005/DTE/mkd_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18157,807,"MKD","Macedonia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MKD/BSGM/2006/Binary/mkd_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18158,807,"MKD","Macedonia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/MKD/BSGM/2006/DTE/mkd_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18159,807,"MKD","Macedonia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MKD/BSGM/2007/Binary/mkd_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18160,807,"MKD","Macedonia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/MKD/BSGM/2007/DTE/mkd_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18161,807,"MKD","Macedonia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MKD/BSGM/2008/Binary/mkd_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18162,807,"MKD","Macedonia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/MKD/BSGM/2008/DTE/mkd_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18163,807,"MKD","Macedonia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MKD/BSGM/2009/Binary/mkd_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18164,807,"MKD","Macedonia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/MKD/BSGM/2009/DTE/mkd_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18165,807,"MKD","Macedonia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MKD/BSGM/2010/Binary/mkd_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18166,807,"MKD","Macedonia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/MKD/BSGM/2010/DTE/mkd_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18167,807,"MKD","Macedonia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MKD/BSGM/2011/Binary/mkd_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18168,807,"MKD","Macedonia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/MKD/BSGM/2011/DTE/mkd_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18169,807,"MKD","Macedonia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MKD/BSGM/2013/Binary/mkd_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18170,807,"MKD","Macedonia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/MKD/BSGM/2013/DTE/mkd_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18171,807,"MKD","Macedonia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/MKD/BSGM/2015/DTE/mkd_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18172,807,"MKD","Macedonia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/MKD/BSGM/2016/DTE/mkd_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18173,807,"MKD","Macedonia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/MKD/BSGM/2017/DTE/mkd_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18174,807,"MKD","Macedonia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/MKD/BSGM/2018/DTE/mkd_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18175,807,"MKD","Macedonia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/MKD/BSGM/2019/DTE/mkd_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18176,807,"MKD","Macedonia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/MKD/BSGM/2020/DTE/mkd_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18177,818,"EGY","Egypt","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/EGY/BSGM/2001/Binary/egy_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18178,818,"EGY","Egypt","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/EGY/BSGM/2001/DTE/egy_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18179,818,"EGY","Egypt","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/EGY/BSGM/2002/Binary/egy_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18180,818,"EGY","Egypt","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/EGY/BSGM/2002/DTE/egy_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18181,818,"EGY","Egypt","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/EGY/BSGM/2003/Binary/egy_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18182,818,"EGY","Egypt","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/EGY/BSGM/2003/DTE/egy_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18183,818,"EGY","Egypt","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/EGY/BSGM/2004/Binary/egy_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18184,818,"EGY","Egypt","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/EGY/BSGM/2004/DTE/egy_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18185,818,"EGY","Egypt","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/EGY/BSGM/2005/Binary/egy_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18186,818,"EGY","Egypt","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/EGY/BSGM/2005/DTE/egy_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18187,818,"EGY","Egypt","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/EGY/BSGM/2006/Binary/egy_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18188,818,"EGY","Egypt","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/EGY/BSGM/2006/DTE/egy_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18189,818,"EGY","Egypt","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/EGY/BSGM/2007/Binary/egy_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18190,818,"EGY","Egypt","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/EGY/BSGM/2007/DTE/egy_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18191,818,"EGY","Egypt","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/EGY/BSGM/2008/Binary/egy_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18192,818,"EGY","Egypt","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/EGY/BSGM/2008/DTE/egy_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18193,818,"EGY","Egypt","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/EGY/BSGM/2009/Binary/egy_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18194,818,"EGY","Egypt","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/EGY/BSGM/2009/DTE/egy_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18195,818,"EGY","Egypt","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/EGY/BSGM/2010/Binary/egy_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18196,818,"EGY","Egypt","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/EGY/BSGM/2010/DTE/egy_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18197,818,"EGY","Egypt","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/EGY/BSGM/2011/Binary/egy_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18198,818,"EGY","Egypt","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/EGY/BSGM/2011/DTE/egy_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18199,818,"EGY","Egypt","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/EGY/BSGM/2013/Binary/egy_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18200,818,"EGY","Egypt","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/EGY/BSGM/2013/DTE/egy_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18201,818,"EGY","Egypt","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/EGY/BSGM/2015/DTE/egy_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18202,818,"EGY","Egypt","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/EGY/BSGM/2016/DTE/egy_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18203,818,"EGY","Egypt","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/EGY/BSGM/2017/DTE/egy_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18204,818,"EGY","Egypt","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/EGY/BSGM/2018/DTE/egy_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18205,818,"EGY","Egypt","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/EGY/BSGM/2019/DTE/egy_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18206,818,"EGY","Egypt","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/EGY/BSGM/2020/DTE/egy_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18207,826,"GBR","United Kingdom","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GBR/BSGM/2001/Binary/gbr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18208,826,"GBR","United Kingdom","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GBR/BSGM/2001/DTE/gbr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18209,826,"GBR","United Kingdom","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GBR/BSGM/2002/Binary/gbr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18210,826,"GBR","United Kingdom","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GBR/BSGM/2002/DTE/gbr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18211,826,"GBR","United Kingdom","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GBR/BSGM/2003/Binary/gbr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18212,826,"GBR","United Kingdom","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GBR/BSGM/2003/DTE/gbr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18213,826,"GBR","United Kingdom","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GBR/BSGM/2004/Binary/gbr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18214,826,"GBR","United Kingdom","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GBR/BSGM/2004/DTE/gbr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18215,826,"GBR","United Kingdom","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GBR/BSGM/2005/Binary/gbr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18216,826,"GBR","United Kingdom","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GBR/BSGM/2005/DTE/gbr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18217,826,"GBR","United Kingdom","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GBR/BSGM/2006/Binary/gbr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18218,826,"GBR","United Kingdom","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GBR/BSGM/2006/DTE/gbr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18219,826,"GBR","United Kingdom","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GBR/BSGM/2007/Binary/gbr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18220,826,"GBR","United Kingdom","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GBR/BSGM/2007/DTE/gbr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18221,826,"GBR","United Kingdom","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GBR/BSGM/2008/Binary/gbr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18222,826,"GBR","United Kingdom","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GBR/BSGM/2008/DTE/gbr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18223,826,"GBR","United Kingdom","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GBR/BSGM/2009/Binary/gbr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18224,826,"GBR","United Kingdom","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GBR/BSGM/2009/DTE/gbr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18225,826,"GBR","United Kingdom","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GBR/BSGM/2010/Binary/gbr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18226,826,"GBR","United Kingdom","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GBR/BSGM/2010/DTE/gbr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18227,826,"GBR","United Kingdom","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GBR/BSGM/2011/Binary/gbr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18228,826,"GBR","United Kingdom","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GBR/BSGM/2011/DTE/gbr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18229,826,"GBR","United Kingdom","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GBR/BSGM/2013/Binary/gbr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18230,826,"GBR","United Kingdom","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GBR/BSGM/2013/DTE/gbr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18231,826,"GBR","United Kingdom","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GBR/BSGM/2015/DTE/gbr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18232,826,"GBR","United Kingdom","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GBR/BSGM/2016/DTE/gbr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18233,826,"GBR","United Kingdom","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GBR/BSGM/2017/DTE/gbr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18234,826,"GBR","United Kingdom","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GBR/BSGM/2018/DTE/gbr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18235,826,"GBR","United Kingdom","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GBR/BSGM/2019/DTE/gbr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18236,826,"GBR","United Kingdom","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GBR/BSGM/2020/DTE/gbr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18237,831,"GGY","Guernsey","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GGY/BSGM/2001/Binary/ggy_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18238,831,"GGY","Guernsey","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/GGY/BSGM/2001/DTE/ggy_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18239,831,"GGY","Guernsey","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GGY/BSGM/2002/Binary/ggy_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18240,831,"GGY","Guernsey","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/GGY/BSGM/2002/DTE/ggy_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18241,831,"GGY","Guernsey","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GGY/BSGM/2003/Binary/ggy_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18242,831,"GGY","Guernsey","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/GGY/BSGM/2003/DTE/ggy_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18243,831,"GGY","Guernsey","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GGY/BSGM/2004/Binary/ggy_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18244,831,"GGY","Guernsey","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/GGY/BSGM/2004/DTE/ggy_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18245,831,"GGY","Guernsey","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GGY/BSGM/2005/Binary/ggy_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18246,831,"GGY","Guernsey","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/GGY/BSGM/2005/DTE/ggy_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18247,831,"GGY","Guernsey","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GGY/BSGM/2006/Binary/ggy_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18248,831,"GGY","Guernsey","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/GGY/BSGM/2006/DTE/ggy_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18249,831,"GGY","Guernsey","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GGY/BSGM/2007/Binary/ggy_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18250,831,"GGY","Guernsey","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/GGY/BSGM/2007/DTE/ggy_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18251,831,"GGY","Guernsey","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GGY/BSGM/2008/Binary/ggy_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18252,831,"GGY","Guernsey","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/GGY/BSGM/2008/DTE/ggy_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18253,831,"GGY","Guernsey","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GGY/BSGM/2009/Binary/ggy_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18254,831,"GGY","Guernsey","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/GGY/BSGM/2009/DTE/ggy_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18255,831,"GGY","Guernsey","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GGY/BSGM/2010/Binary/ggy_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18256,831,"GGY","Guernsey","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/GGY/BSGM/2010/DTE/ggy_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18257,831,"GGY","Guernsey","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GGY/BSGM/2011/Binary/ggy_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18258,831,"GGY","Guernsey","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/GGY/BSGM/2011/DTE/ggy_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18259,831,"GGY","Guernsey","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GGY/BSGM/2013/Binary/ggy_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18260,831,"GGY","Guernsey","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/GGY/BSGM/2013/DTE/ggy_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18261,831,"GGY","Guernsey","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/GGY/BSGM/2015/DTE/ggy_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18262,831,"GGY","Guernsey","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/GGY/BSGM/2016/DTE/ggy_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18263,831,"GGY","Guernsey","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/GGY/BSGM/2017/DTE/ggy_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18264,831,"GGY","Guernsey","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/GGY/BSGM/2018/DTE/ggy_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18265,831,"GGY","Guernsey","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/GGY/BSGM/2019/DTE/ggy_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18266,831,"GGY","Guernsey","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/GGY/BSGM/2020/DTE/ggy_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18267,832,"JEY","Jersey","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/JEY/BSGM/2001/Binary/jey_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18268,832,"JEY","Jersey","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/JEY/BSGM/2001/DTE/jey_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18269,832,"JEY","Jersey","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/JEY/BSGM/2002/Binary/jey_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18270,832,"JEY","Jersey","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/JEY/BSGM/2002/DTE/jey_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18271,832,"JEY","Jersey","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/JEY/BSGM/2003/Binary/jey_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18272,832,"JEY","Jersey","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/JEY/BSGM/2003/DTE/jey_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18273,832,"JEY","Jersey","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/JEY/BSGM/2004/Binary/jey_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18274,832,"JEY","Jersey","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/JEY/BSGM/2004/DTE/jey_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18275,832,"JEY","Jersey","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/JEY/BSGM/2005/Binary/jey_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18276,832,"JEY","Jersey","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/JEY/BSGM/2005/DTE/jey_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18277,832,"JEY","Jersey","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/JEY/BSGM/2006/Binary/jey_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18278,832,"JEY","Jersey","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/JEY/BSGM/2006/DTE/jey_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18279,832,"JEY","Jersey","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/JEY/BSGM/2007/Binary/jey_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18280,832,"JEY","Jersey","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/JEY/BSGM/2007/DTE/jey_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18281,832,"JEY","Jersey","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/JEY/BSGM/2008/Binary/jey_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18282,832,"JEY","Jersey","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/JEY/BSGM/2008/DTE/jey_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18283,832,"JEY","Jersey","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/JEY/BSGM/2009/Binary/jey_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18284,832,"JEY","Jersey","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/JEY/BSGM/2009/DTE/jey_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18285,832,"JEY","Jersey","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/JEY/BSGM/2010/Binary/jey_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18286,832,"JEY","Jersey","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/JEY/BSGM/2010/DTE/jey_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18287,832,"JEY","Jersey","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/JEY/BSGM/2011/Binary/jey_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18288,832,"JEY","Jersey","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/JEY/BSGM/2011/DTE/jey_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18289,832,"JEY","Jersey","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/JEY/BSGM/2013/Binary/jey_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18290,832,"JEY","Jersey","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/JEY/BSGM/2013/DTE/jey_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18291,832,"JEY","Jersey","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/JEY/BSGM/2015/DTE/jey_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18292,832,"JEY","Jersey","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/JEY/BSGM/2016/DTE/jey_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18293,832,"JEY","Jersey","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/JEY/BSGM/2017/DTE/jey_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18294,832,"JEY","Jersey","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/JEY/BSGM/2018/DTE/jey_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18295,832,"JEY","Jersey","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/JEY/BSGM/2019/DTE/jey_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18296,832,"JEY","Jersey","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/JEY/BSGM/2020/DTE/jey_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18297,833,"IMN","Isle of Man","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IMN/BSGM/2001/Binary/imn_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18298,833,"IMN","Isle of Man","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/IMN/BSGM/2001/DTE/imn_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18299,833,"IMN","Isle of Man","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IMN/BSGM/2002/Binary/imn_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18300,833,"IMN","Isle of Man","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/IMN/BSGM/2002/DTE/imn_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18301,833,"IMN","Isle of Man","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IMN/BSGM/2003/Binary/imn_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18302,833,"IMN","Isle of Man","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/IMN/BSGM/2003/DTE/imn_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18303,833,"IMN","Isle of Man","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IMN/BSGM/2004/Binary/imn_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18304,833,"IMN","Isle of Man","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/IMN/BSGM/2004/DTE/imn_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18305,833,"IMN","Isle of Man","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IMN/BSGM/2005/Binary/imn_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18306,833,"IMN","Isle of Man","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/IMN/BSGM/2005/DTE/imn_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18307,833,"IMN","Isle of Man","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IMN/BSGM/2006/Binary/imn_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18308,833,"IMN","Isle of Man","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/IMN/BSGM/2006/DTE/imn_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18309,833,"IMN","Isle of Man","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IMN/BSGM/2007/Binary/imn_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18310,833,"IMN","Isle of Man","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/IMN/BSGM/2007/DTE/imn_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18311,833,"IMN","Isle of Man","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IMN/BSGM/2008/Binary/imn_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18312,833,"IMN","Isle of Man","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/IMN/BSGM/2008/DTE/imn_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18313,833,"IMN","Isle of Man","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IMN/BSGM/2009/Binary/imn_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18314,833,"IMN","Isle of Man","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/IMN/BSGM/2009/DTE/imn_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18315,833,"IMN","Isle of Man","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IMN/BSGM/2010/Binary/imn_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18316,833,"IMN","Isle of Man","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/IMN/BSGM/2010/DTE/imn_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18317,833,"IMN","Isle of Man","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IMN/BSGM/2011/Binary/imn_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18318,833,"IMN","Isle of Man","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/IMN/BSGM/2011/DTE/imn_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18319,833,"IMN","Isle of Man","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IMN/BSGM/2013/Binary/imn_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18320,833,"IMN","Isle of Man","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/IMN/BSGM/2013/DTE/imn_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18321,833,"IMN","Isle of Man","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/IMN/BSGM/2015/DTE/imn_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18322,833,"IMN","Isle of Man","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/IMN/BSGM/2016/DTE/imn_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18323,833,"IMN","Isle of Man","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/IMN/BSGM/2017/DTE/imn_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18324,833,"IMN","Isle of Man","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/IMN/BSGM/2018/DTE/imn_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18325,833,"IMN","Isle of Man","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/IMN/BSGM/2019/DTE/imn_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18326,833,"IMN","Isle of Man","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/IMN/BSGM/2020/DTE/imn_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18327,834,"TZA","Tanzania","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TZA/BSGM/2001/Binary/tza_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18328,834,"TZA","Tanzania","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/TZA/BSGM/2001/DTE/tza_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18329,834,"TZA","Tanzania","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TZA/BSGM/2002/Binary/tza_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18330,834,"TZA","Tanzania","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/TZA/BSGM/2002/DTE/tza_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18331,834,"TZA","Tanzania","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TZA/BSGM/2003/Binary/tza_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18332,834,"TZA","Tanzania","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/TZA/BSGM/2003/DTE/tza_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18333,834,"TZA","Tanzania","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TZA/BSGM/2004/Binary/tza_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18334,834,"TZA","Tanzania","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/TZA/BSGM/2004/DTE/tza_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18335,834,"TZA","Tanzania","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TZA/BSGM/2005/Binary/tza_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18336,834,"TZA","Tanzania","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/TZA/BSGM/2005/DTE/tza_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18337,834,"TZA","Tanzania","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TZA/BSGM/2006/Binary/tza_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18338,834,"TZA","Tanzania","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/TZA/BSGM/2006/DTE/tza_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18339,834,"TZA","Tanzania","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TZA/BSGM/2007/Binary/tza_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18340,834,"TZA","Tanzania","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/TZA/BSGM/2007/DTE/tza_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18341,834,"TZA","Tanzania","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TZA/BSGM/2008/Binary/tza_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18342,834,"TZA","Tanzania","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/TZA/BSGM/2008/DTE/tza_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18343,834,"TZA","Tanzania","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TZA/BSGM/2009/Binary/tza_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18344,834,"TZA","Tanzania","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/TZA/BSGM/2009/DTE/tza_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18345,834,"TZA","Tanzania","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TZA/BSGM/2010/Binary/tza_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18346,834,"TZA","Tanzania","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/TZA/BSGM/2010/DTE/tza_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18347,834,"TZA","Tanzania","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TZA/BSGM/2011/Binary/tza_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18348,834,"TZA","Tanzania","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/TZA/BSGM/2011/DTE/tza_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18349,834,"TZA","Tanzania","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TZA/BSGM/2013/Binary/tza_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18350,834,"TZA","Tanzania","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/TZA/BSGM/2013/DTE/tza_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18351,834,"TZA","Tanzania","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/TZA/BSGM/2015/DTE/tza_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18352,834,"TZA","Tanzania","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/TZA/BSGM/2016/DTE/tza_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18353,834,"TZA","Tanzania","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/TZA/BSGM/2017/DTE/tza_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18354,834,"TZA","Tanzania","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/TZA/BSGM/2018/DTE/tza_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18355,834,"TZA","Tanzania","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/TZA/BSGM/2019/DTE/tza_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18356,834,"TZA","Tanzania","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/TZA/BSGM/2020/DTE/tza_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18357,854,"BFA","Burkina Faso","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BFA/BSGM/2001/Binary/bfa_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18358,854,"BFA","Burkina Faso","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/BFA/BSGM/2001/DTE/bfa_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18359,854,"BFA","Burkina Faso","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BFA/BSGM/2002/Binary/bfa_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18360,854,"BFA","Burkina Faso","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/BFA/BSGM/2002/DTE/bfa_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18361,854,"BFA","Burkina Faso","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BFA/BSGM/2003/Binary/bfa_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18362,854,"BFA","Burkina Faso","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/BFA/BSGM/2003/DTE/bfa_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18363,854,"BFA","Burkina Faso","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BFA/BSGM/2004/Binary/bfa_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18364,854,"BFA","Burkina Faso","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/BFA/BSGM/2004/DTE/bfa_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18365,854,"BFA","Burkina Faso","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BFA/BSGM/2005/Binary/bfa_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18366,854,"BFA","Burkina Faso","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/BFA/BSGM/2005/DTE/bfa_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18367,854,"BFA","Burkina Faso","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BFA/BSGM/2006/Binary/bfa_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18368,854,"BFA","Burkina Faso","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/BFA/BSGM/2006/DTE/bfa_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18369,854,"BFA","Burkina Faso","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BFA/BSGM/2007/Binary/bfa_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18370,854,"BFA","Burkina Faso","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/BFA/BSGM/2007/DTE/bfa_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18371,854,"BFA","Burkina Faso","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BFA/BSGM/2008/Binary/bfa_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18372,854,"BFA","Burkina Faso","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/BFA/BSGM/2008/DTE/bfa_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18373,854,"BFA","Burkina Faso","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BFA/BSGM/2009/Binary/bfa_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18374,854,"BFA","Burkina Faso","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/BFA/BSGM/2009/DTE/bfa_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18375,854,"BFA","Burkina Faso","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BFA/BSGM/2010/Binary/bfa_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18376,854,"BFA","Burkina Faso","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/BFA/BSGM/2010/DTE/bfa_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18377,854,"BFA","Burkina Faso","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BFA/BSGM/2011/Binary/bfa_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18378,854,"BFA","Burkina Faso","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/BFA/BSGM/2011/DTE/bfa_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18379,854,"BFA","Burkina Faso","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BFA/BSGM/2013/Binary/bfa_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18380,854,"BFA","Burkina Faso","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/BFA/BSGM/2013/DTE/bfa_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18381,854,"BFA","Burkina Faso","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/BFA/BSGM/2015/DTE/bfa_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18382,854,"BFA","Burkina Faso","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/BFA/BSGM/2016/DTE/bfa_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18383,854,"BFA","Burkina Faso","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/BFA/BSGM/2017/DTE/bfa_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18384,854,"BFA","Burkina Faso","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/BFA/BSGM/2018/DTE/bfa_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18385,854,"BFA","Burkina Faso","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/BFA/BSGM/2019/DTE/bfa_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18386,854,"BFA","Burkina Faso","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/BFA/BSGM/2020/DTE/bfa_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18387,858,"URY","Uruguay","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/URY/BSGM/2001/Binary/ury_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18388,858,"URY","Uruguay","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/URY/BSGM/2001/DTE/ury_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18389,858,"URY","Uruguay","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/URY/BSGM/2002/Binary/ury_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18390,858,"URY","Uruguay","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/URY/BSGM/2002/DTE/ury_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18391,858,"URY","Uruguay","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/URY/BSGM/2003/Binary/ury_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18392,858,"URY","Uruguay","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/URY/BSGM/2003/DTE/ury_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18393,858,"URY","Uruguay","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/URY/BSGM/2004/Binary/ury_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18394,858,"URY","Uruguay","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/URY/BSGM/2004/DTE/ury_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18395,858,"URY","Uruguay","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/URY/BSGM/2005/Binary/ury_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18396,858,"URY","Uruguay","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/URY/BSGM/2005/DTE/ury_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18397,858,"URY","Uruguay","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/URY/BSGM/2006/Binary/ury_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18398,858,"URY","Uruguay","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/URY/BSGM/2006/DTE/ury_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18399,858,"URY","Uruguay","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/URY/BSGM/2007/Binary/ury_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18400,858,"URY","Uruguay","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/URY/BSGM/2007/DTE/ury_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18401,858,"URY","Uruguay","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/URY/BSGM/2008/Binary/ury_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18402,858,"URY","Uruguay","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/URY/BSGM/2008/DTE/ury_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18403,858,"URY","Uruguay","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/URY/BSGM/2009/Binary/ury_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18404,858,"URY","Uruguay","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/URY/BSGM/2009/DTE/ury_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18405,858,"URY","Uruguay","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/URY/BSGM/2010/Binary/ury_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18406,858,"URY","Uruguay","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/URY/BSGM/2010/DTE/ury_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18407,858,"URY","Uruguay","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/URY/BSGM/2011/Binary/ury_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18408,858,"URY","Uruguay","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/URY/BSGM/2011/DTE/ury_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18409,858,"URY","Uruguay","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/URY/BSGM/2013/Binary/ury_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18410,858,"URY","Uruguay","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/URY/BSGM/2013/DTE/ury_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18411,858,"URY","Uruguay","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/URY/BSGM/2015/DTE/ury_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18412,858,"URY","Uruguay","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/URY/BSGM/2016/DTE/ury_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18413,858,"URY","Uruguay","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/URY/BSGM/2017/DTE/ury_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18414,858,"URY","Uruguay","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/URY/BSGM/2018/DTE/ury_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18415,858,"URY","Uruguay","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/URY/BSGM/2019/DTE/ury_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18416,858,"URY","Uruguay","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/URY/BSGM/2020/DTE/ury_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18417,860,"UZB","Uzbekistan","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/UZB/BSGM/2001/Binary/uzb_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18418,860,"UZB","Uzbekistan","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/UZB/BSGM/2001/DTE/uzb_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18419,860,"UZB","Uzbekistan","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/UZB/BSGM/2002/Binary/uzb_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18420,860,"UZB","Uzbekistan","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/UZB/BSGM/2002/DTE/uzb_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18421,860,"UZB","Uzbekistan","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/UZB/BSGM/2003/Binary/uzb_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18422,860,"UZB","Uzbekistan","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/UZB/BSGM/2003/DTE/uzb_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18423,860,"UZB","Uzbekistan","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/UZB/BSGM/2004/Binary/uzb_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18424,860,"UZB","Uzbekistan","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/UZB/BSGM/2004/DTE/uzb_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18425,860,"UZB","Uzbekistan","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/UZB/BSGM/2005/Binary/uzb_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18426,860,"UZB","Uzbekistan","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/UZB/BSGM/2005/DTE/uzb_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18427,860,"UZB","Uzbekistan","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/UZB/BSGM/2006/Binary/uzb_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18428,860,"UZB","Uzbekistan","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/UZB/BSGM/2006/DTE/uzb_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18429,860,"UZB","Uzbekistan","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/UZB/BSGM/2007/Binary/uzb_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18430,860,"UZB","Uzbekistan","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/UZB/BSGM/2007/DTE/uzb_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18431,860,"UZB","Uzbekistan","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/UZB/BSGM/2008/Binary/uzb_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18432,860,"UZB","Uzbekistan","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/UZB/BSGM/2008/DTE/uzb_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18433,860,"UZB","Uzbekistan","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/UZB/BSGM/2009/Binary/uzb_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18434,860,"UZB","Uzbekistan","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/UZB/BSGM/2009/DTE/uzb_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18435,860,"UZB","Uzbekistan","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/UZB/BSGM/2010/Binary/uzb_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18436,860,"UZB","Uzbekistan","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/UZB/BSGM/2010/DTE/uzb_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18437,860,"UZB","Uzbekistan","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/UZB/BSGM/2011/Binary/uzb_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18438,860,"UZB","Uzbekistan","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/UZB/BSGM/2011/DTE/uzb_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18439,860,"UZB","Uzbekistan","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/UZB/BSGM/2013/Binary/uzb_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18440,860,"UZB","Uzbekistan","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/UZB/BSGM/2013/DTE/uzb_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18441,860,"UZB","Uzbekistan","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/UZB/BSGM/2015/DTE/uzb_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18442,860,"UZB","Uzbekistan","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/UZB/BSGM/2016/DTE/uzb_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18443,860,"UZB","Uzbekistan","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/UZB/BSGM/2017/DTE/uzb_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18444,860,"UZB","Uzbekistan","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/UZB/BSGM/2018/DTE/uzb_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18445,860,"UZB","Uzbekistan","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/UZB/BSGM/2019/DTE/uzb_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18446,860,"UZB","Uzbekistan","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/UZB/BSGM/2020/DTE/uzb_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18447,862,"VEN","Venezuela","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VEN/BSGM/2001/Binary/ven_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18448,862,"VEN","Venezuela","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/VEN/BSGM/2001/DTE/ven_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18449,862,"VEN","Venezuela","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VEN/BSGM/2002/Binary/ven_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18450,862,"VEN","Venezuela","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/VEN/BSGM/2002/DTE/ven_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18451,862,"VEN","Venezuela","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VEN/BSGM/2003/Binary/ven_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18452,862,"VEN","Venezuela","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/VEN/BSGM/2003/DTE/ven_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18453,862,"VEN","Venezuela","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VEN/BSGM/2004/Binary/ven_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18454,862,"VEN","Venezuela","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/VEN/BSGM/2004/DTE/ven_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18455,862,"VEN","Venezuela","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VEN/BSGM/2005/Binary/ven_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18456,862,"VEN","Venezuela","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/VEN/BSGM/2005/DTE/ven_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18457,862,"VEN","Venezuela","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VEN/BSGM/2006/Binary/ven_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18458,862,"VEN","Venezuela","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/VEN/BSGM/2006/DTE/ven_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18459,862,"VEN","Venezuela","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VEN/BSGM/2007/Binary/ven_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18460,862,"VEN","Venezuela","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/VEN/BSGM/2007/DTE/ven_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18461,862,"VEN","Venezuela","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VEN/BSGM/2008/Binary/ven_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18462,862,"VEN","Venezuela","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/VEN/BSGM/2008/DTE/ven_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18463,862,"VEN","Venezuela","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VEN/BSGM/2009/Binary/ven_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18464,862,"VEN","Venezuela","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/VEN/BSGM/2009/DTE/ven_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18465,862,"VEN","Venezuela","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VEN/BSGM/2010/Binary/ven_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18466,862,"VEN","Venezuela","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/VEN/BSGM/2010/DTE/ven_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18467,862,"VEN","Venezuela","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VEN/BSGM/2011/Binary/ven_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18468,862,"VEN","Venezuela","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/VEN/BSGM/2011/DTE/ven_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18469,862,"VEN","Venezuela","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VEN/BSGM/2013/Binary/ven_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18470,862,"VEN","Venezuela","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/VEN/BSGM/2013/DTE/ven_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18471,862,"VEN","Venezuela","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/VEN/BSGM/2015/DTE/ven_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18472,862,"VEN","Venezuela","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/VEN/BSGM/2016/DTE/ven_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18473,862,"VEN","Venezuela","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/VEN/BSGM/2017/DTE/ven_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18474,862,"VEN","Venezuela","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/VEN/BSGM/2018/DTE/ven_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18475,862,"VEN","Venezuela","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/VEN/BSGM/2019/DTE/ven_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18476,862,"VEN","Venezuela","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/VEN/BSGM/2020/DTE/ven_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18477,876,"WLF","Wallis and Futuna","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/WLF/BSGM/2001/Binary/wlf_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18478,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/WLF/BSGM/2001/DTE/wlf_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18479,876,"WLF","Wallis and Futuna","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/WLF/BSGM/2002/Binary/wlf_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18480,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/WLF/BSGM/2002/DTE/wlf_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18481,876,"WLF","Wallis and Futuna","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/WLF/BSGM/2003/Binary/wlf_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18482,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/WLF/BSGM/2003/DTE/wlf_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18483,876,"WLF","Wallis and Futuna","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/WLF/BSGM/2004/Binary/wlf_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18484,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/WLF/BSGM/2004/DTE/wlf_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18485,876,"WLF","Wallis and Futuna","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/WLF/BSGM/2005/Binary/wlf_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18486,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/WLF/BSGM/2005/DTE/wlf_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18487,876,"WLF","Wallis and Futuna","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/WLF/BSGM/2006/Binary/wlf_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18488,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/WLF/BSGM/2006/DTE/wlf_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18489,876,"WLF","Wallis and Futuna","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/WLF/BSGM/2007/Binary/wlf_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18490,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/WLF/BSGM/2007/DTE/wlf_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18491,876,"WLF","Wallis and Futuna","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/WLF/BSGM/2008/Binary/wlf_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18492,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/WLF/BSGM/2008/DTE/wlf_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18493,876,"WLF","Wallis and Futuna","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/WLF/BSGM/2009/Binary/wlf_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18494,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/WLF/BSGM/2009/DTE/wlf_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18495,876,"WLF","Wallis and Futuna","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/WLF/BSGM/2010/Binary/wlf_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18496,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/WLF/BSGM/2010/DTE/wlf_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18497,876,"WLF","Wallis and Futuna","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/WLF/BSGM/2011/Binary/wlf_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18498,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/WLF/BSGM/2011/DTE/wlf_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18499,876,"WLF","Wallis and Futuna","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/WLF/BSGM/2013/DTE/wlf_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18500,876,"WLF","Wallis and Futuna","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/WLF/BSGM/2015/DTE/wlf_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18501,876,"WLF","Wallis and Futuna","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/WLF/BSGM/2016/DTE/wlf_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18502,876,"WLF","Wallis and Futuna","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/WLF/BSGM/2017/DTE/wlf_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18503,876,"WLF","Wallis and Futuna","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/WLF/BSGM/2018/DTE/wlf_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18504,876,"WLF","Wallis and Futuna","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/WLF/BSGM/2019/DTE/wlf_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18505,876,"WLF","Wallis and Futuna","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/WLF/BSGM/2020/DTE/wlf_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18506,882,"WSM","Samoa","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/WSM/BSGM/2001/Binary/wsm_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18507,882,"WSM","Samoa","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/WSM/BSGM/2001/DTE/wsm_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18508,882,"WSM","Samoa","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/WSM/BSGM/2002/Binary/wsm_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18509,882,"WSM","Samoa","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/WSM/BSGM/2002/DTE/wsm_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18510,882,"WSM","Samoa","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/WSM/BSGM/2003/Binary/wsm_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18511,882,"WSM","Samoa","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/WSM/BSGM/2003/DTE/wsm_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18512,882,"WSM","Samoa","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/WSM/BSGM/2004/Binary/wsm_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18513,882,"WSM","Samoa","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/WSM/BSGM/2004/DTE/wsm_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18514,882,"WSM","Samoa","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/WSM/BSGM/2005/Binary/wsm_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18515,882,"WSM","Samoa","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/WSM/BSGM/2005/DTE/wsm_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18516,882,"WSM","Samoa","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/WSM/BSGM/2006/Binary/wsm_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18517,882,"WSM","Samoa","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/WSM/BSGM/2006/DTE/wsm_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18518,882,"WSM","Samoa","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/WSM/BSGM/2007/Binary/wsm_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18519,882,"WSM","Samoa","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/WSM/BSGM/2007/DTE/wsm_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18520,882,"WSM","Samoa","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/WSM/BSGM/2008/Binary/wsm_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18521,882,"WSM","Samoa","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/WSM/BSGM/2008/DTE/wsm_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18522,882,"WSM","Samoa","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/WSM/BSGM/2009/Binary/wsm_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18523,882,"WSM","Samoa","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/WSM/BSGM/2009/DTE/wsm_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18524,882,"WSM","Samoa","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/WSM/BSGM/2010/Binary/wsm_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18525,882,"WSM","Samoa","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/WSM/BSGM/2010/DTE/wsm_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18526,882,"WSM","Samoa","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/WSM/BSGM/2011/Binary/wsm_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18527,882,"WSM","Samoa","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/WSM/BSGM/2011/DTE/wsm_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18528,882,"WSM","Samoa","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/WSM/BSGM/2013/Binary/wsm_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18529,882,"WSM","Samoa","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/WSM/BSGM/2013/DTE/wsm_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18530,882,"WSM","Samoa","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/WSM/BSGM/2015/DTE/wsm_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18531,882,"WSM","Samoa","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/WSM/BSGM/2016/DTE/wsm_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18532,882,"WSM","Samoa","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/WSM/BSGM/2017/DTE/wsm_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18533,882,"WSM","Samoa","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/WSM/BSGM/2018/DTE/wsm_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18534,882,"WSM","Samoa","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/WSM/BSGM/2019/DTE/wsm_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18535,882,"WSM","Samoa","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/WSM/BSGM/2020/DTE/wsm_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18536,887,"YEM","Yemen","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/YEM/BSGM/2001/Binary/yem_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18537,887,"YEM","Yemen","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/YEM/BSGM/2001/DTE/yem_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18538,887,"YEM","Yemen","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/YEM/BSGM/2002/Binary/yem_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18539,887,"YEM","Yemen","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/YEM/BSGM/2002/DTE/yem_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18540,887,"YEM","Yemen","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/YEM/BSGM/2003/Binary/yem_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18541,887,"YEM","Yemen","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/YEM/BSGM/2003/DTE/yem_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18542,887,"YEM","Yemen","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/YEM/BSGM/2004/Binary/yem_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18543,887,"YEM","Yemen","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/YEM/BSGM/2004/DTE/yem_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18544,887,"YEM","Yemen","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/YEM/BSGM/2005/Binary/yem_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18545,887,"YEM","Yemen","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/YEM/BSGM/2005/DTE/yem_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18546,887,"YEM","Yemen","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/YEM/BSGM/2006/Binary/yem_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18547,887,"YEM","Yemen","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/YEM/BSGM/2006/DTE/yem_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18548,887,"YEM","Yemen","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/YEM/BSGM/2007/Binary/yem_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18549,887,"YEM","Yemen","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/YEM/BSGM/2007/DTE/yem_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18550,887,"YEM","Yemen","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/YEM/BSGM/2008/Binary/yem_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18551,887,"YEM","Yemen","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/YEM/BSGM/2008/DTE/yem_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18552,887,"YEM","Yemen","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/YEM/BSGM/2009/Binary/yem_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18553,887,"YEM","Yemen","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/YEM/BSGM/2009/DTE/yem_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18554,887,"YEM","Yemen","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/YEM/BSGM/2010/Binary/yem_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18555,887,"YEM","Yemen","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/YEM/BSGM/2010/DTE/yem_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18556,887,"YEM","Yemen","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/YEM/BSGM/2011/Binary/yem_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18557,887,"YEM","Yemen","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/YEM/BSGM/2011/DTE/yem_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18558,887,"YEM","Yemen","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/YEM/BSGM/2013/Binary/yem_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18559,887,"YEM","Yemen","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/YEM/BSGM/2013/DTE/yem_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18560,887,"YEM","Yemen","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/YEM/BSGM/2015/DTE/yem_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18561,887,"YEM","Yemen","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/YEM/BSGM/2016/DTE/yem_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18562,887,"YEM","Yemen","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/YEM/BSGM/2017/DTE/yem_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18563,887,"YEM","Yemen","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/YEM/BSGM/2018/DTE/yem_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18564,887,"YEM","Yemen","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/YEM/BSGM/2019/DTE/yem_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18565,887,"YEM","Yemen","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/YEM/BSGM/2020/DTE/yem_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18566,894,"ZMB","Zambia","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2001/Binary/zmb_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18567,894,"ZMB","Zambia","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2001/DTE/zmb_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18568,894,"ZMB","Zambia","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2002/Binary/zmb_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18569,894,"ZMB","Zambia","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2002/DTE/zmb_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18570,894,"ZMB","Zambia","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2003/Binary/zmb_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18571,894,"ZMB","Zambia","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2003/DTE/zmb_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18572,894,"ZMB","Zambia","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2004/Binary/zmb_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18573,894,"ZMB","Zambia","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2004/DTE/zmb_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18574,894,"ZMB","Zambia","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2005/Binary/zmb_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18575,894,"ZMB","Zambia","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2005/DTE/zmb_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18576,894,"ZMB","Zambia","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2006/Binary/zmb_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18577,894,"ZMB","Zambia","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2006/DTE/zmb_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18578,894,"ZMB","Zambia","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2007/Binary/zmb_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18579,894,"ZMB","Zambia","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2007/DTE/zmb_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18580,894,"ZMB","Zambia","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2008/Binary/zmb_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18581,894,"ZMB","Zambia","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2008/DTE/zmb_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18582,894,"ZMB","Zambia","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2009/Binary/zmb_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18583,894,"ZMB","Zambia","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2009/DTE/zmb_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18584,894,"ZMB","Zambia","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2010/Binary/zmb_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18585,894,"ZMB","Zambia","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2010/DTE/zmb_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18586,894,"ZMB","Zambia","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2011/Binary/zmb_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18587,894,"ZMB","Zambia","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2011/DTE/zmb_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18588,894,"ZMB","Zambia","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2013/Binary/zmb_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18589,894,"ZMB","Zambia","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2013/DTE/zmb_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18590,894,"ZMB","Zambia","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2015/DTE/zmb_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18591,894,"ZMB","Zambia","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2016/DTE/zmb_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18592,894,"ZMB","Zambia","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2017/DTE/zmb_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18593,894,"ZMB","Zambia","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2018/DTE/zmb_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18594,894,"ZMB","Zambia","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2019/DTE/zmb_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18595,894,"ZMB","Zambia","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/ZMB/BSGM/2020/DTE/zmb_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18596,900,"KOS","Kosovo","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KOS/BSGM/2001/Binary/kos_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18597,900,"KOS","Kosovo","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/KOS/BSGM/2001/DTE/kos_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18598,900,"KOS","Kosovo","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KOS/BSGM/2002/Binary/kos_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18599,900,"KOS","Kosovo","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/KOS/BSGM/2002/DTE/kos_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18600,900,"KOS","Kosovo","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KOS/BSGM/2003/Binary/kos_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18601,900,"KOS","Kosovo","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/KOS/BSGM/2003/DTE/kos_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18602,900,"KOS","Kosovo","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KOS/BSGM/2004/Binary/kos_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18603,900,"KOS","Kosovo","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/KOS/BSGM/2004/DTE/kos_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18604,900,"KOS","Kosovo","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KOS/BSGM/2005/Binary/kos_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18605,900,"KOS","Kosovo","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/KOS/BSGM/2005/DTE/kos_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18606,900,"KOS","Kosovo","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KOS/BSGM/2006/Binary/kos_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18607,900,"KOS","Kosovo","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/KOS/BSGM/2006/DTE/kos_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18608,900,"KOS","Kosovo","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KOS/BSGM/2007/Binary/kos_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18609,900,"KOS","Kosovo","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/KOS/BSGM/2007/DTE/kos_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18610,900,"KOS","Kosovo","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KOS/BSGM/2008/Binary/kos_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18611,900,"KOS","Kosovo","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/KOS/BSGM/2008/DTE/kos_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18612,900,"KOS","Kosovo","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KOS/BSGM/2009/Binary/kos_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18613,900,"KOS","Kosovo","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/KOS/BSGM/2009/DTE/kos_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18614,900,"KOS","Kosovo","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KOS/BSGM/2010/Binary/kos_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18615,900,"KOS","Kosovo","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/KOS/BSGM/2010/DTE/kos_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18616,900,"KOS","Kosovo","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KOS/BSGM/2011/Binary/kos_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18617,900,"KOS","Kosovo","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/KOS/BSGM/2011/DTE/kos_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18618,900,"KOS","Kosovo","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KOS/BSGM/2013/Binary/kos_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18619,900,"KOS","Kosovo","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/KOS/BSGM/2013/DTE/kos_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18620,900,"KOS","Kosovo","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/KOS/BSGM/2015/DTE/kos_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18621,900,"KOS","Kosovo","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/KOS/BSGM/2016/DTE/kos_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18622,900,"KOS","Kosovo","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/KOS/BSGM/2017/DTE/kos_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18623,900,"KOS","Kosovo","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/KOS/BSGM/2018/DTE/kos_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18624,900,"KOS","Kosovo","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/KOS/BSGM/2019/DTE/kos_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18625,900,"KOS","Kosovo","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/KOS/BSGM/2020/DTE/kos_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18626,901,"SPR","Spratly Islands","bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SPR/BSGM/2001/Binary/spr_bsgmi_100m_2001.tif","Interpolated built-settlement areas 2001"
18627,901,"SPR","Spratly Islands","dst_bsgmi_100m_2001","GIS/Covariates/Global_2000_2020/SPR/BSGM/2001/DTE/spr_dst_bsgmi_100m_2001.tif","Distance to interpolated built-settlement area edges 2001"
18628,901,"SPR","Spratly Islands","bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SPR/BSGM/2002/Binary/spr_bsgmi_100m_2002.tif","Interpolated built-settlement areas 2002"
18629,901,"SPR","Spratly Islands","dst_bsgmi_100m_2002","GIS/Covariates/Global_2000_2020/SPR/BSGM/2002/DTE/spr_dst_bsgmi_100m_2002.tif","Distance to interpolated built-settlement area edges 2002"
18630,901,"SPR","Spratly Islands","bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SPR/BSGM/2003/Binary/spr_bsgmi_100m_2003.tif","Interpolated built-settlement areas 2003"
18631,901,"SPR","Spratly Islands","dst_bsgmi_100m_2003","GIS/Covariates/Global_2000_2020/SPR/BSGM/2003/DTE/spr_dst_bsgmi_100m_2003.tif","Distance to interpolated built-settlement area edges 2003"
18632,901,"SPR","Spratly Islands","bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SPR/BSGM/2004/Binary/spr_bsgmi_100m_2004.tif","Interpolated built-settlement areas 2004"
18633,901,"SPR","Spratly Islands","dst_bsgmi_100m_2004","GIS/Covariates/Global_2000_2020/SPR/BSGM/2004/DTE/spr_dst_bsgmi_100m_2004.tif","Distance to interpolated built-settlement area edges 2004"
18634,901,"SPR","Spratly Islands","bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SPR/BSGM/2005/Binary/spr_bsgmi_100m_2005.tif","Interpolated built-settlement areas 2005"
18635,901,"SPR","Spratly Islands","dst_bsgmi_100m_2005","GIS/Covariates/Global_2000_2020/SPR/BSGM/2005/DTE/spr_dst_bsgmi_100m_2005.tif","Distance to interpolated built-settlement area edges 2005"
18636,901,"SPR","Spratly Islands","bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SPR/BSGM/2006/Binary/spr_bsgmi_100m_2006.tif","Interpolated built-settlement areas 2006"
18637,901,"SPR","Spratly Islands","dst_bsgmi_100m_2006","GIS/Covariates/Global_2000_2020/SPR/BSGM/2006/DTE/spr_dst_bsgmi_100m_2006.tif","Distance to interpolated built-settlement area edges 2006"
18638,901,"SPR","Spratly Islands","bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SPR/BSGM/2007/Binary/spr_bsgmi_100m_2007.tif","Interpolated built-settlement areas 2007"
18639,901,"SPR","Spratly Islands","dst_bsgmi_100m_2007","GIS/Covariates/Global_2000_2020/SPR/BSGM/2007/DTE/spr_dst_bsgmi_100m_2007.tif","Distance to interpolated built-settlement area edges 2007"
18640,901,"SPR","Spratly Islands","bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SPR/BSGM/2008/Binary/spr_bsgmi_100m_2008.tif","Interpolated built-settlement areas 2008"
18641,901,"SPR","Spratly Islands","dst_bsgmi_100m_2008","GIS/Covariates/Global_2000_2020/SPR/BSGM/2008/DTE/spr_dst_bsgmi_100m_2008.tif","Distance to interpolated built-settlement area edges 2008"
18642,901,"SPR","Spratly Islands","bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SPR/BSGM/2009/Binary/spr_bsgmi_100m_2009.tif","Interpolated built-settlement areas 2009"
18643,901,"SPR","Spratly Islands","dst_bsgmi_100m_2009","GIS/Covariates/Global_2000_2020/SPR/BSGM/2009/DTE/spr_dst_bsgmi_100m_2009.tif","Distance to interpolated built-settlement area edges 2009"
18644,901,"SPR","Spratly Islands","bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SPR/BSGM/2010/Binary/spr_bsgmi_100m_2010.tif","Interpolated built-settlement areas 2010"
18645,901,"SPR","Spratly Islands","dst_bsgmi_100m_2010","GIS/Covariates/Global_2000_2020/SPR/BSGM/2010/DTE/spr_dst_bsgmi_100m_2010.tif","Distance to interpolated built-settlement area edges 2010"
18646,901,"SPR","Spratly Islands","bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SPR/BSGM/2011/Binary/spr_bsgmi_100m_2011.tif","Interpolated built-settlement areas 2011"
18647,901,"SPR","Spratly Islands","dst_bsgmi_100m_2011","GIS/Covariates/Global_2000_2020/SPR/BSGM/2011/DTE/spr_dst_bsgmi_100m_2011.tif","Distance to interpolated built-settlement area edges 2011"
18648,901,"SPR","Spratly Islands","bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SPR/BSGM/2013/Binary/spr_bsgmi_100m_2013.tif","Interpolated built-settlement areas 2013"
18649,901,"SPR","Spratly Islands","dst_bsgmi_100m_2013","GIS/Covariates/Global_2000_2020/SPR/BSGM/2013/DTE/spr_dst_bsgmi_100m_2013.tif","Distance to interpolated built-settlement area edges 2013"
18650,901,"SPR","Spratly Islands","dst_bsgme_100m_2015","GIS/Covariates/Global_2000_2020/SPR/BSGM/2015/DTE/spr_dst_bsgme_100m_2015.tif","Distance to extrapolated built-settlement area edges 2015"
18651,901,"SPR","Spratly Islands","dst_bsgme_100m_2016","GIS/Covariates/Global_2000_2020/SPR/BSGM/2016/DTE/spr_dst_bsgme_100m_2016.tif","Distance to extrapolated built-settlement area edges 2016"
18652,901,"SPR","Spratly Islands","dst_bsgme_100m_2017","GIS/Covariates/Global_2000_2020/SPR/BSGM/2017/DTE/spr_dst_bsgme_100m_2017.tif","Distance to extrapolated built-settlement area edges 2017"
18653,901,"SPR","Spratly Islands","dst_bsgme_100m_2018","GIS/Covariates/Global_2000_2020/SPR/BSGM/2018/DTE/spr_dst_bsgme_100m_2018.tif","Distance to extrapolated built-settlement area edges 2018"
18654,901,"SPR","Spratly Islands","dst_bsgme_100m_2019","GIS/Covariates/Global_2000_2020/SPR/BSGM/2019/DTE/spr_dst_bsgme_100m_2019.tif","Distance to extrapolated built-settlement area edges 2019"
18655,901,"SPR","Spratly Islands","dst_bsgme_100m_2020","GIS/Covariates/Global_2000_2020/SPR/BSGM/2020/DTE/spr_dst_bsgme_100m_2020.tif","Distance to extrapolated built-settlement area edges 2020"
18656,643,"RUS","Russia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/RUS/Coastline/DST/rus_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18657,360,"IDN","Indonesia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/IDN/Coastline/DST/idn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18658,840,"USA","United States","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/USA/Coastline/DST/usa_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18659,850,"VIR","Virgin_Islands_U_S","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/VIR/Coastline/DST/vir_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18660,304,"GRL","Greenland","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GRL/Coastline/DST/grl_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18661,156,"CHN","China","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CHN/Coastline/DST/chn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18662,36,"AUS","Australia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/AUS/Coastline/DST/aus_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18663,76,"BRA","Brazil","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BRA/Coastline/DST/bra_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18664,124,"CAN","Canada","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CAN/Coastline/DST/can_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18665,152,"CHL","Chile","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CHL/Coastline/DST/chl_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18666,4,"AFG","Afghanistan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/AFG/Coastline/DST/afg_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18667,8,"ALB","Albania","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ALB/Coastline/DST/alb_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18668,10,"ATA","Antarctica","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ATA/Coastline/DST/ata_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18669,12,"DZA","Algeria","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/DZA/Coastline/DST/dza_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18670,16,"ASM","American Samoa","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ASM/Coastline/DST/asm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18671,20,"AND","Andorra","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/AND/Coastline/DST/and_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18672,24,"AGO","Angola","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/AGO/Coastline/DST/ago_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18673,28,"ATG","Antigua and Barbuda","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ATG/Coastline/DST/atg_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18674,31,"AZE","Azerbaijan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/AZE/Coastline/DST/aze_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18675,32,"ARG","Argentina","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ARG/Coastline/DST/arg_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18676,40,"AUT","Austria","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/AUT/Coastline/DST/aut_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18677,44,"BHS","Bahamas","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BHS/Coastline/DST/bhs_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18678,48,"BHR","Bahrain","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BHR/Coastline/DST/bhr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18679,50,"BGD","Bangladesh","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BGD/Coastline/DST/bgd_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18680,51,"ARM","Armenia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ARM/Coastline/DST/arm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18681,52,"BRB","Barbados","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BRB/Coastline/DST/brb_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18682,56,"BEL","Belgium","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BEL/Coastline/DST/bel_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18683,60,"BMU","Bermuda","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BMU/Coastline/DST/bmu_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18684,64,"BTN","Bhutan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BTN/Coastline/DST/btn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18685,68,"BOL","Bolivia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BOL/Coastline/DST/bol_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18686,70,"BIH","Bosnia and Herzegovina","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BIH/Coastline/DST/bih_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18687,72,"BWA","Botswana","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BWA/Coastline/DST/bwa_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18688,74,"BVT","Bouvet Island","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BVT/Coastline/DST/bvt_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18689,84,"BLZ","Belize","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BLZ/Coastline/DST/blz_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18690,86,"IOT","British Indian Ocean Territory","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/IOT/Coastline/DST/iot_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18691,90,"SLB","Solomon Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SLB/Coastline/DST/slb_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18692,92,"VGB","British Virgin Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/VGB/Coastline/DST/vgb_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18693,96,"BRN","Brunei","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BRN/Coastline/DST/brn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18694,100,"BGR","Bulgaria","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BGR/Coastline/DST/bgr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18695,104,"MMR","Myanmar","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MMR/Coastline/DST/mmr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18696,108,"BDI","Burundi","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BDI/Coastline/DST/bdi_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18697,112,"BLR","Belarus","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BLR/Coastline/DST/blr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18698,116,"KHM","Cambodia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/KHM/Coastline/DST/khm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18699,120,"CMR","Cameroon","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CMR/Coastline/DST/cmr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18700,132,"CPV","Cape Verde","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CPV/Coastline/DST/cpv_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18701,136,"CYM","Cayman Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CYM/Coastline/DST/cym_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18702,140,"CAF","Central African Republic","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CAF/Coastline/DST/caf_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18703,144,"LKA","Sri Lanka","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LKA/Coastline/DST/lka_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18704,148,"TCD","Chad","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TCD/Coastline/DST/tcd_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18705,158,"TWN","Taiwan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TWN/Coastline/DST/twn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18706,170,"COL","Colombia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/COL/Coastline/DST/col_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18707,174,"COM","Comoros","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/COM/Coastline/DST/com_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18708,175,"MYT","Mayotte","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MYT/Coastline/DST/myt_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18709,178,"COG","Republic of Congo","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/COG/Coastline/DST/cog_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18710,180,"COD","Democratic Republic of the Congo","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/COD/Coastline/DST/cod_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18711,184,"COK","Cook Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/COK/Coastline/DST/cok_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18712,188,"CRI","Costa Rica","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CRI/Coastline/DST/cri_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18713,191,"HRV","Croatia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/HRV/Coastline/DST/hrv_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18714,192,"CUB","Cuba","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CUB/Coastline/DST/cub_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18715,196,"CYP","Cyprus","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CYP/Coastline/DST/cyp_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18716,203,"CZE","Czech Republic","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CZE/Coastline/DST/cze_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18717,204,"BEN","Benin","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BEN/Coastline/DST/ben_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18718,208,"DNK","Denmark","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/DNK/Coastline/DST/dnk_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18719,212,"DMA","Dominica","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/DMA/Coastline/DST/dma_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18720,214,"DOM","Dominican Republic","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/DOM/Coastline/DST/dom_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18721,218,"ECU","Ecuador","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ECU/Coastline/DST/ecu_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18722,222,"SLV","El Salvador","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SLV/Coastline/DST/slv_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18723,226,"GNQ","Equatorial Guinea","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GNQ/Coastline/DST/gnq_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18724,231,"ETH","Ethiopia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ETH/Coastline/DST/eth_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18725,232,"ERI","Eritrea","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ERI/Coastline/DST/eri_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18726,233,"EST","Estonia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/EST/Coastline/DST/est_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18727,234,"FRO","Faroe Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/FRO/Coastline/DST/fro_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18728,238,"FLK","Falkland Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/FLK/Coastline/DST/flk_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18729,239,"SGS","South Georgia and the South Sandwich Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SGS/Coastline/DST/sgs_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18730,242,"FJI","Fiji","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/FJI/Coastline/DST/fji_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18731,246,"FIN","Finland","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/FIN/Coastline/DST/fin_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18732,248,"ALA","Aland Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ALA/Coastline/DST/ala_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18733,250,"FRA","France","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/FRA/Coastline/DST/fra_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18734,254,"GUF","French Guiana","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GUF/Coastline/DST/guf_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18735,258,"PYF","French Polynesia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PYF/Coastline/DST/pyf_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18736,260,"ATF","French Southern Territories","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ATF/Coastline/DST/atf_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18737,262,"DJI","Djibouti","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/DJI/Coastline/DST/dji_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18738,266,"GAB","Gabon","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GAB/Coastline/DST/gab_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18739,268,"GEO","Georgia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GEO/Coastline/DST/geo_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18740,270,"GMB","Gambia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GMB/Coastline/DST/gmb_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18741,275,"PSE","Palestina","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PSE/Coastline/DST/pse_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18742,276,"DEU","Germany","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/DEU/Coastline/DST/deu_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18743,288,"GHA","Ghana","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GHA/Coastline/DST/gha_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18744,292,"GIB","Gibraltar","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GIB/Coastline/DST/gib_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18745,296,"KIR","Kiribati","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/KIR/Coastline/DST/kir_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18746,300,"GRC","Greece","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GRC/Coastline/DST/grc_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18747,308,"GRD","Grenada","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GRD/Coastline/DST/grd_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18748,312,"GLP","Guadeloupe","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GLP/Coastline/DST/glp_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18749,316,"GUM","Guam","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GUM/Coastline/DST/gum_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18750,320,"GTM","Guatemala","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GTM/Coastline/DST/gtm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18751,324,"GIN","Guinea","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GIN/Coastline/DST/gin_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18752,328,"GUY","Guyana","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GUY/Coastline/DST/guy_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18753,332,"HTI","Haiti","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/HTI/Coastline/DST/hti_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18754,334,"HMD","Heard Island and McDonald Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/HMD/Coastline/DST/hmd_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18755,336,"VAT","Vatican City","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/VAT/Coastline/DST/vat_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18756,340,"HND","Honduras","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/HND/Coastline/DST/hnd_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18757,344,"HKG","Hong Kong","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/HKG/Coastline/DST/hkg_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18758,348,"HUN","Hungary","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/HUN/Coastline/DST/hun_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18759,352,"ISL","Iceland","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ISL/Coastline/DST/isl_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18760,356,"IND","India","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/IND/Coastline/DST/ind_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18761,364,"IRN","Iran","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/IRN/Coastline/DST/irn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18762,368,"IRQ","Iraq","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/IRQ/Coastline/DST/irq_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18763,372,"IRL","Ireland","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/IRL/Coastline/DST/irl_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18764,376,"ISR","Israel","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ISR/Coastline/DST/isr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18765,380,"ITA","Italy","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ITA/Coastline/DST/ita_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18766,384,"CIV","CIte dIvoire","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CIV/Coastline/DST/civ_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18767,388,"JAM","Jamaica","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/JAM/Coastline/DST/jam_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18768,392,"JPN","Japan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/JPN/Coastline/DST/jpn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18769,398,"KAZ","Kazakhstan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/KAZ/Coastline/DST/kaz_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18770,400,"JOR","Jordan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/JOR/Coastline/DST/jor_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18771,404,"KEN","Kenya","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/KEN/Coastline/DST/ken_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18772,408,"PRK","North Korea","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PRK/Coastline/DST/prk_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18773,410,"KOR","South Korea","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/KOR/Coastline/DST/kor_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18774,414,"KWT","Kuwait","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/KWT/Coastline/DST/kwt_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18775,417,"KGZ","Kyrgyzstan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/KGZ/Coastline/DST/kgz_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18776,418,"LAO","Laos","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LAO/Coastline/DST/lao_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18777,422,"LBN","Lebanon","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LBN/Coastline/DST/lbn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18778,426,"LSO","Lesotho","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LSO/Coastline/DST/lso_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18779,428,"LVA","Latvia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LVA/Coastline/DST/lva_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18780,430,"LBR","Liberia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LBR/Coastline/DST/lbr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18781,434,"LBY","Libya","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LBY/Coastline/DST/lby_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18782,438,"LIE","Liechtenstein","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LIE/Coastline/DST/lie_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18783,440,"LTU","Lithuania","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LTU/Coastline/DST/ltu_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18784,442,"LUX","Luxembourg","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LUX/Coastline/DST/lux_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18785,446,"MAC","Macao","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MAC/Coastline/DST/mac_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18786,450,"MDG","Madagascar","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MDG/Coastline/DST/mdg_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18787,454,"MWI","Malawi","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MWI/Coastline/DST/mwi_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18788,458,"MYS","Malaysia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MYS/Coastline/DST/mys_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18789,462,"MDV","Maldives","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MDV/Coastline/DST/mdv_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18790,466,"MLI","Mali","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MLI/Coastline/DST/mli_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18791,470,"MLT","Malta","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MLT/Coastline/DST/mlt_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18792,474,"MTQ","Martinique","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MTQ/Coastline/DST/mtq_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18793,478,"MRT","Mauritania","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MRT/Coastline/DST/mrt_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18794,480,"MUS","Mauritius","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MUS/Coastline/DST/mus_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18795,484,"MEX","Mexico","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MEX/Coastline/DST/mex_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18796,492,"MCO","Monaco","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MCO/Coastline/DST/mco_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18797,496,"MNG","Mongolia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MNG/Coastline/DST/mng_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18798,498,"MDA","Moldova","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MDA/Coastline/DST/mda_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18799,499,"MNE","Montenegro","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MNE/Coastline/DST/mne_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18800,500,"MSR","Montserrat","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MSR/Coastline/DST/msr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18801,504,"MAR","Morocco","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MAR/Coastline/DST/mar_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18802,508,"MOZ","Mozambique","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MOZ/Coastline/DST/moz_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18803,512,"OMN","Oman","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/OMN/Coastline/DST/omn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18804,516,"NAM","Namibia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NAM/Coastline/DST/nam_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18805,520,"NRU","Nauru","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NRU/Coastline/DST/nru_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18806,524,"NPL","Nepal","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NPL/Coastline/DST/npl_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18807,528,"NLD","Netherlands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NLD/Coastline/DST/nld_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18808,531,"CUW","Curacao","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CUW/Coastline/DST/cuw_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18809,533,"ABW","Aruba","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ABW/Coastline/DST/abw_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18810,534,"SXM","Sint Maarten (Dutch part)","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SXM/Coastline/DST/sxm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18811,535,"BES","Bonaire, Sint Eustatius and Saba","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BES/Coastline/DST/bes_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18812,540,"NCL","New Caledonia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NCL/Coastline/DST/ncl_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18813,548,"VUT","Vanuatu","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/VUT/Coastline/DST/vut_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18814,554,"NZL","New Zealand","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NZL/Coastline/DST/nzl_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18815,558,"NIC","Nicaragua","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NIC/Coastline/DST/nic_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18816,562,"NER","Niger","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NER/Coastline/DST/ner_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18817,566,"NGA","Nigeria","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NGA/Coastline/DST/nga_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18818,570,"NIU","Niue","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NIU/Coastline/DST/niu_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18819,574,"NFK","Norfolk Island","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NFK/Coastline/DST/nfk_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18820,578,"NOR","Norway","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/NOR/Coastline/DST/nor_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18821,580,"MNP","Northern Mariana Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MNP/Coastline/DST/mnp_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18822,581,"UMI","United States Minor Outlying Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/UMI/Coastline/DST/umi_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18823,583,"FSM","Micronesia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/FSM/Coastline/DST/fsm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18824,584,"MHL","Marshall Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MHL/Coastline/DST/mhl_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18825,585,"PLW","Palau","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PLW/Coastline/DST/plw_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18826,586,"PAK","Pakistan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PAK/Coastline/DST/pak_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18827,591,"PAN","Panama","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PAN/Coastline/DST/pan_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18828,598,"PNG","Papua New Guinea","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PNG/Coastline/DST/png_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18829,600,"PRY","Paraguay","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PRY/Coastline/DST/pry_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18830,604,"PER","Peru","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PER/Coastline/DST/per_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18831,608,"PHL","Philippines","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PHL/Coastline/DST/phl_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18832,612,"PCN","Pitcairn Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PCN/Coastline/DST/pcn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18833,616,"POL","Poland","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/POL/Coastline/DST/pol_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18834,620,"PRT","Portugal","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PRT/Coastline/DST/prt_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18835,624,"GNB","Guinea-Bissau","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GNB/Coastline/DST/gnb_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18836,626,"TLS","East Timor","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TLS/Coastline/DST/tls_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18837,630,"PRI","Puerto Rico","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/PRI/Coastline/DST/pri_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18838,634,"QAT","Qatar","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/QAT/Coastline/DST/qat_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18839,638,"REU","Reunion","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/REU/Coastline/DST/reu_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18840,642,"ROU","Romania","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ROU/Coastline/DST/rou_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18841,646,"RWA","Rwanda","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/RWA/Coastline/DST/rwa_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18842,652,"BLM","Saint Barthelemy","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BLM/Coastline/DST/blm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18843,654,"SHN","Saint Helena","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SHN/Coastline/DST/shn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18844,659,"KNA","Saint Kitts and Nevis","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/KNA/Coastline/DST/kna_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18845,660,"AIA","Anguilla","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/AIA/Coastline/DST/aia_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18846,662,"LCA","Saint Lucia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/LCA/Coastline/DST/lca_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18847,663,"MAF","Saint Martin (French part)","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MAF/Coastline/DST/maf_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18848,666,"SPM","Saint Pierre and Miquelon","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SPM/Coastline/DST/spm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18849,670,"VCT","Saint Vincent and the Grenadines","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/VCT/Coastline/DST/vct_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18850,674,"SMR","San Marino","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SMR/Coastline/DST/smr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18851,678,"STP","Sao Tome and Principe","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/STP/Coastline/DST/stp_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18852,682,"SAU","Saudi Arabia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SAU/Coastline/DST/sau_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18853,686,"SEN","Senegal","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SEN/Coastline/DST/sen_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18854,688,"SRB","Serbia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SRB/Coastline/DST/srb_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18855,690,"SYC","Seychelles","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SYC/Coastline/DST/syc_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18856,694,"SLE","Sierra Leone","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SLE/Coastline/DST/sle_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18857,702,"SGP","Singapore","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SGP/Coastline/DST/sgp_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18858,703,"SVK","Slovakia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SVK/Coastline/DST/svk_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18859,704,"VNM","Vietnam","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/VNM/Coastline/DST/vnm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18860,705,"SVN","Slovenia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SVN/Coastline/DST/svn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18861,706,"SOM","Somalia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SOM/Coastline/DST/som_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18862,710,"ZAF","South Africa","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ZAF/Coastline/DST/zaf_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18863,716,"ZWE","Zimbabwe","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ZWE/Coastline/DST/zwe_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18864,724,"ESP","Spain","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ESP/Coastline/DST/esp_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18865,728,"SSD","South Sudan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SSD/Coastline/DST/ssd_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18866,729,"SDN","Sudan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SDN/Coastline/DST/sdn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18867,732,"ESH","Western Sahara","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ESH/Coastline/DST/esh_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18868,740,"SUR","Suriname","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SUR/Coastline/DST/sur_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18869,744,"SJM","Svalbard and Jan Mayen Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SJM/Coastline/DST/sjm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18870,748,"SWZ","Swaziland","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SWZ/Coastline/DST/swz_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18871,752,"SWE","Sweden","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SWE/Coastline/DST/swe_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18872,756,"CHE","Switzerland","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/CHE/Coastline/DST/che_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18873,760,"SYR","Syria","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SYR/Coastline/DST/syr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18874,762,"TJK","Tajikistan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TJK/Coastline/DST/tjk_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18875,764,"THA","Thailand","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/THA/Coastline/DST/tha_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18876,768,"TGO","Togo","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TGO/Coastline/DST/tgo_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18877,772,"TKL","Tokelau","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TKL/Coastline/DST/tkl_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18878,776,"TON","Tonga","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TON/Coastline/DST/ton_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18879,780,"TTO","Trinidad and Tobago","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TTO/Coastline/DST/tto_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18880,784,"ARE","United Arab Emirates","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ARE/Coastline/DST/are_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18881,788,"TUN","Tunisia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TUN/Coastline/DST/tun_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18882,792,"TUR","Turkey","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TUR/Coastline/DST/tur_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18883,795,"TKM","Turkmenistan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TKM/Coastline/DST/tkm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18884,796,"TCA","Turks and Caicos Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TCA/Coastline/DST/tca_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18885,798,"TUV","Tuvalu","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TUV/Coastline/DST/tuv_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18886,800,"UGA","Uganda","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/UGA/Coastline/DST/uga_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18887,804,"UKR","Ukraine","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/UKR/Coastline/DST/ukr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18888,807,"MKD","Macedonia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/MKD/Coastline/DST/mkd_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18889,818,"EGY","Egypt","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/EGY/Coastline/DST/egy_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18890,826,"GBR","United Kingdom","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GBR/Coastline/DST/gbr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18891,831,"GGY","Guernsey","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/GGY/Coastline/DST/ggy_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18892,832,"JEY","Jersey","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/JEY/Coastline/DST/jey_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18893,833,"IMN","Isle of Man","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/IMN/Coastline/DST/imn_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18894,834,"TZA","Tanzania","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/TZA/Coastline/DST/tza_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18895,854,"BFA","Burkina Faso","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/BFA/Coastline/DST/bfa_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18896,858,"URY","Uruguay","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/URY/Coastline/DST/ury_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18897,860,"UZB","Uzbekistan","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/UZB/Coastline/DST/uzb_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18898,862,"VEN","Venezuela","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/VEN/Coastline/DST/ven_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18899,876,"WLF","Wallis and Futuna","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/WLF/Coastline/DST/wlf_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18900,882,"WSM","Samoa","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/WSM/Coastline/DST/wsm_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18901,887,"YEM","Yemen","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/YEM/Coastline/DST/yem_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18902,894,"ZMB","Zambia","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/ZMB/Coastline/DST/zmb_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18903,900,"KOS","Kosovo","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/KOS/Coastline/DST/kos_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18904,901,"SPR","Spratly Islands","dst_coastline_100m_2000_2020","GIS/Covariates/Global_2000_2020/SPR/Coastline/DST/spr_dst_coastline_100m_2000_2020.tif","Distance to coastline 2000-2020"
18905,643,"RUS","Russia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
18906,643,"RUS","Russia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
18907,643,"RUS","Russia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
18908,643,"RUS","Russia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
18909,643,"RUS","Russia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
18910,643,"RUS","Russia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
18911,643,"RUS","Russia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
18912,643,"RUS","Russia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
18913,643,"RUS","Russia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
18914,643,"RUS","Russia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
18915,643,"RUS","Russia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
18916,643,"RUS","Russia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/RUS/DMSP/rus_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
18917,360,"IDN","Indonesia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
18918,360,"IDN","Indonesia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
18919,360,"IDN","Indonesia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
18920,360,"IDN","Indonesia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
18921,360,"IDN","Indonesia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
18922,360,"IDN","Indonesia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
18923,360,"IDN","Indonesia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
18924,360,"IDN","Indonesia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
18925,360,"IDN","Indonesia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
18926,360,"IDN","Indonesia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
18927,360,"IDN","Indonesia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
18928,360,"IDN","Indonesia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/IDN/DMSP/idn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
18929,840,"USA","United States","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
18930,840,"USA","United States","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
18931,840,"USA","United States","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
18932,840,"USA","United States","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
18933,840,"USA","United States","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
18934,840,"USA","United States","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
18935,840,"USA","United States","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
18936,840,"USA","United States","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
18937,840,"USA","United States","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
18938,840,"USA","United States","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
18939,840,"USA","United States","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
18940,840,"USA","United States","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/USA/DMSP/usa_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
18941,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
18942,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
18943,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
18944,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
18945,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
18946,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
18947,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
18948,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
18949,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
18950,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
18951,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
18952,850,"VIR","Virgin_Islands_U_S","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/VIR/DMSP/vir_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
18953,304,"GRL","Greenland","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
18954,304,"GRL","Greenland","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
18955,304,"GRL","Greenland","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
18956,304,"GRL","Greenland","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
18957,304,"GRL","Greenland","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
18958,304,"GRL","Greenland","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
18959,304,"GRL","Greenland","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
18960,304,"GRL","Greenland","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
18961,304,"GRL","Greenland","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
18962,304,"GRL","Greenland","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
18963,304,"GRL","Greenland","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
18964,304,"GRL","Greenland","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GRL/DMSP/grl_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
18965,156,"CHN","China","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
18966,156,"CHN","China","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
18967,156,"CHN","China","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
18968,156,"CHN","China","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
18969,156,"CHN","China","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
18970,156,"CHN","China","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
18971,156,"CHN","China","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
18972,156,"CHN","China","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
18973,156,"CHN","China","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
18974,156,"CHN","China","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
18975,156,"CHN","China","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
18976,156,"CHN","China","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CHN/DMSP/chn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
18977,36,"AUS","Australia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
18978,36,"AUS","Australia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
18979,36,"AUS","Australia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
18980,36,"AUS","Australia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
18981,36,"AUS","Australia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
18982,36,"AUS","Australia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
18983,36,"AUS","Australia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
18984,36,"AUS","Australia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
18985,36,"AUS","Australia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
18986,36,"AUS","Australia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
18987,36,"AUS","Australia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
18988,36,"AUS","Australia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/AUS/DMSP/aus_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
18989,76,"BRA","Brazil","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
18990,76,"BRA","Brazil","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
18991,76,"BRA","Brazil","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
18992,76,"BRA","Brazil","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
18993,76,"BRA","Brazil","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
18994,76,"BRA","Brazil","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
18995,76,"BRA","Brazil","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
18996,76,"BRA","Brazil","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
18997,76,"BRA","Brazil","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
18998,76,"BRA","Brazil","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
18999,76,"BRA","Brazil","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19000,76,"BRA","Brazil","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BRA/DMSP/bra_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19001,124,"CAN","Canada","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19002,124,"CAN","Canada","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19003,124,"CAN","Canada","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19004,124,"CAN","Canada","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19005,124,"CAN","Canada","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19006,124,"CAN","Canada","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19007,124,"CAN","Canada","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19008,124,"CAN","Canada","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19009,124,"CAN","Canada","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19010,124,"CAN","Canada","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19011,124,"CAN","Canada","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19012,124,"CAN","Canada","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CAN/DMSP/can_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19013,152,"CHL","Chile","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19014,152,"CHL","Chile","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19015,152,"CHL","Chile","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19016,152,"CHL","Chile","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19017,152,"CHL","Chile","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19018,152,"CHL","Chile","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19019,152,"CHL","Chile","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19020,152,"CHL","Chile","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19021,152,"CHL","Chile","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19022,152,"CHL","Chile","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19023,152,"CHL","Chile","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19024,152,"CHL","Chile","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CHL/DMSP/chl_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19025,4,"AFG","Afghanistan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19026,4,"AFG","Afghanistan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19027,4,"AFG","Afghanistan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19028,4,"AFG","Afghanistan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19029,4,"AFG","Afghanistan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19030,4,"AFG","Afghanistan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19031,4,"AFG","Afghanistan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19032,4,"AFG","Afghanistan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19033,4,"AFG","Afghanistan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19034,4,"AFG","Afghanistan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19035,4,"AFG","Afghanistan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19036,4,"AFG","Afghanistan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/AFG/DMSP/afg_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19037,8,"ALB","Albania","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19038,8,"ALB","Albania","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19039,8,"ALB","Albania","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19040,8,"ALB","Albania","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19041,8,"ALB","Albania","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19042,8,"ALB","Albania","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19043,8,"ALB","Albania","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19044,8,"ALB","Albania","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19045,8,"ALB","Albania","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19046,8,"ALB","Albania","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19047,8,"ALB","Albania","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19048,8,"ALB","Albania","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ALB/DMSP/alb_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19049,10,"ATA","Antarctica","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19050,10,"ATA","Antarctica","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19051,10,"ATA","Antarctica","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19052,10,"ATA","Antarctica","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19053,10,"ATA","Antarctica","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19054,10,"ATA","Antarctica","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19055,10,"ATA","Antarctica","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19056,10,"ATA","Antarctica","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19057,10,"ATA","Antarctica","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19058,10,"ATA","Antarctica","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19059,10,"ATA","Antarctica","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19060,10,"ATA","Antarctica","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ATA/DMSP/ata_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19061,12,"DZA","Algeria","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19062,12,"DZA","Algeria","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19063,12,"DZA","Algeria","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19064,12,"DZA","Algeria","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19065,12,"DZA","Algeria","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19066,12,"DZA","Algeria","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19067,12,"DZA","Algeria","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19068,12,"DZA","Algeria","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19069,12,"DZA","Algeria","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19070,12,"DZA","Algeria","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19071,12,"DZA","Algeria","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19072,12,"DZA","Algeria","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/DZA/DMSP/dza_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19073,16,"ASM","American Samoa","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19074,16,"ASM","American Samoa","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19075,16,"ASM","American Samoa","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19076,16,"ASM","American Samoa","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19077,16,"ASM","American Samoa","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19078,16,"ASM","American Samoa","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19079,16,"ASM","American Samoa","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19080,16,"ASM","American Samoa","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19081,16,"ASM","American Samoa","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19082,16,"ASM","American Samoa","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19083,16,"ASM","American Samoa","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19084,16,"ASM","American Samoa","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ASM/DMSP/asm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19085,20,"AND","Andorra","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19086,20,"AND","Andorra","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19087,20,"AND","Andorra","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19088,20,"AND","Andorra","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19089,20,"AND","Andorra","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19090,20,"AND","Andorra","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19091,20,"AND","Andorra","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19092,20,"AND","Andorra","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19093,20,"AND","Andorra","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19094,20,"AND","Andorra","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19095,20,"AND","Andorra","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19096,20,"AND","Andorra","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/AND/DMSP/and_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19097,24,"AGO","Angola","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19098,24,"AGO","Angola","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19099,24,"AGO","Angola","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19100,24,"AGO","Angola","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19101,24,"AGO","Angola","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19102,24,"AGO","Angola","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19103,24,"AGO","Angola","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19104,24,"AGO","Angola","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19105,24,"AGO","Angola","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19106,24,"AGO","Angola","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19107,24,"AGO","Angola","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19108,24,"AGO","Angola","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/AGO/DMSP/ago_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19109,28,"ATG","Antigua and Barbuda","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19110,28,"ATG","Antigua and Barbuda","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19111,28,"ATG","Antigua and Barbuda","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19112,28,"ATG","Antigua and Barbuda","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19113,28,"ATG","Antigua and Barbuda","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19114,28,"ATG","Antigua and Barbuda","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19115,28,"ATG","Antigua and Barbuda","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19116,28,"ATG","Antigua and Barbuda","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19117,28,"ATG","Antigua and Barbuda","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19118,28,"ATG","Antigua and Barbuda","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19119,28,"ATG","Antigua and Barbuda","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19120,28,"ATG","Antigua and Barbuda","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ATG/DMSP/atg_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19121,31,"AZE","Azerbaijan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19122,31,"AZE","Azerbaijan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19123,31,"AZE","Azerbaijan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19124,31,"AZE","Azerbaijan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19125,31,"AZE","Azerbaijan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19126,31,"AZE","Azerbaijan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19127,31,"AZE","Azerbaijan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19128,31,"AZE","Azerbaijan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19129,31,"AZE","Azerbaijan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19130,31,"AZE","Azerbaijan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19131,31,"AZE","Azerbaijan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19132,31,"AZE","Azerbaijan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/AZE/DMSP/aze_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19133,32,"ARG","Argentina","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19134,32,"ARG","Argentina","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19135,32,"ARG","Argentina","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19136,32,"ARG","Argentina","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19137,32,"ARG","Argentina","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19138,32,"ARG","Argentina","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19139,32,"ARG","Argentina","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19140,32,"ARG","Argentina","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19141,32,"ARG","Argentina","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19142,32,"ARG","Argentina","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19143,32,"ARG","Argentina","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19144,32,"ARG","Argentina","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ARG/DMSP/arg_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19145,40,"AUT","Austria","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19146,40,"AUT","Austria","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19147,40,"AUT","Austria","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19148,40,"AUT","Austria","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19149,40,"AUT","Austria","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19150,40,"AUT","Austria","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19151,40,"AUT","Austria","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19152,40,"AUT","Austria","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19153,40,"AUT","Austria","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19154,40,"AUT","Austria","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19155,40,"AUT","Austria","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19156,40,"AUT","Austria","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/AUT/DMSP/aut_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19157,44,"BHS","Bahamas","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19158,44,"BHS","Bahamas","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19159,44,"BHS","Bahamas","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19160,44,"BHS","Bahamas","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19161,44,"BHS","Bahamas","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19162,44,"BHS","Bahamas","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19163,44,"BHS","Bahamas","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19164,44,"BHS","Bahamas","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19165,44,"BHS","Bahamas","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19166,44,"BHS","Bahamas","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19167,44,"BHS","Bahamas","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19168,44,"BHS","Bahamas","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BHS/DMSP/bhs_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19169,48,"BHR","Bahrain","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19170,48,"BHR","Bahrain","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19171,48,"BHR","Bahrain","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19172,48,"BHR","Bahrain","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19173,48,"BHR","Bahrain","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19174,48,"BHR","Bahrain","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19175,48,"BHR","Bahrain","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19176,48,"BHR","Bahrain","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19177,48,"BHR","Bahrain","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19178,48,"BHR","Bahrain","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19179,48,"BHR","Bahrain","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19180,48,"BHR","Bahrain","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BHR/DMSP/bhr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19181,50,"BGD","Bangladesh","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19182,50,"BGD","Bangladesh","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19183,50,"BGD","Bangladesh","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19184,50,"BGD","Bangladesh","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19185,50,"BGD","Bangladesh","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19186,50,"BGD","Bangladesh","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19187,50,"BGD","Bangladesh","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19188,50,"BGD","Bangladesh","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19189,50,"BGD","Bangladesh","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19190,50,"BGD","Bangladesh","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19191,50,"BGD","Bangladesh","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19192,50,"BGD","Bangladesh","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BGD/DMSP/bgd_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19193,51,"ARM","Armenia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19194,51,"ARM","Armenia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19195,51,"ARM","Armenia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19196,51,"ARM","Armenia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19197,51,"ARM","Armenia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19198,51,"ARM","Armenia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19199,51,"ARM","Armenia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19200,51,"ARM","Armenia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19201,51,"ARM","Armenia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19202,51,"ARM","Armenia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19203,51,"ARM","Armenia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19204,51,"ARM","Armenia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ARM/DMSP/arm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19205,52,"BRB","Barbados","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19206,52,"BRB","Barbados","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19207,52,"BRB","Barbados","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19208,52,"BRB","Barbados","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19209,52,"BRB","Barbados","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19210,52,"BRB","Barbados","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19211,52,"BRB","Barbados","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19212,52,"BRB","Barbados","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19213,52,"BRB","Barbados","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19214,52,"BRB","Barbados","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19215,52,"BRB","Barbados","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19216,52,"BRB","Barbados","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BRB/DMSP/brb_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19217,56,"BEL","Belgium","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19218,56,"BEL","Belgium","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19219,56,"BEL","Belgium","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19220,56,"BEL","Belgium","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19221,56,"BEL","Belgium","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19222,56,"BEL","Belgium","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19223,56,"BEL","Belgium","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19224,56,"BEL","Belgium","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19225,56,"BEL","Belgium","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19226,56,"BEL","Belgium","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19227,56,"BEL","Belgium","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19228,56,"BEL","Belgium","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BEL/DMSP/bel_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19229,60,"BMU","Bermuda","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19230,60,"BMU","Bermuda","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19231,60,"BMU","Bermuda","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19232,60,"BMU","Bermuda","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19233,60,"BMU","Bermuda","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19234,60,"BMU","Bermuda","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19235,60,"BMU","Bermuda","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19236,60,"BMU","Bermuda","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19237,60,"BMU","Bermuda","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19238,60,"BMU","Bermuda","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19239,60,"BMU","Bermuda","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19240,60,"BMU","Bermuda","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BMU/DMSP/bmu_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19241,64,"BTN","Bhutan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19242,64,"BTN","Bhutan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19243,64,"BTN","Bhutan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19244,64,"BTN","Bhutan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19245,64,"BTN","Bhutan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19246,64,"BTN","Bhutan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19247,64,"BTN","Bhutan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19248,64,"BTN","Bhutan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19249,64,"BTN","Bhutan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19250,64,"BTN","Bhutan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19251,64,"BTN","Bhutan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19252,64,"BTN","Bhutan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BTN/DMSP/btn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19253,68,"BOL","Bolivia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19254,68,"BOL","Bolivia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19255,68,"BOL","Bolivia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19256,68,"BOL","Bolivia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19257,68,"BOL","Bolivia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19258,68,"BOL","Bolivia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19259,68,"BOL","Bolivia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19260,68,"BOL","Bolivia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19261,68,"BOL","Bolivia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19262,68,"BOL","Bolivia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19263,68,"BOL","Bolivia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19264,68,"BOL","Bolivia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BOL/DMSP/bol_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19265,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19266,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19267,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19268,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19269,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19270,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19271,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19272,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19273,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19274,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19275,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19276,70,"BIH","Bosnia and Herzegovina","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BIH/DMSP/bih_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19277,72,"BWA","Botswana","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19278,72,"BWA","Botswana","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19279,72,"BWA","Botswana","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19280,72,"BWA","Botswana","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19281,72,"BWA","Botswana","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19282,72,"BWA","Botswana","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19283,72,"BWA","Botswana","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19284,72,"BWA","Botswana","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19285,72,"BWA","Botswana","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19286,72,"BWA","Botswana","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19287,72,"BWA","Botswana","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19288,72,"BWA","Botswana","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BWA/DMSP/bwa_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19289,74,"BVT","Bouvet Island","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19290,74,"BVT","Bouvet Island","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19291,74,"BVT","Bouvet Island","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19292,74,"BVT","Bouvet Island","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19293,74,"BVT","Bouvet Island","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19294,74,"BVT","Bouvet Island","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19295,74,"BVT","Bouvet Island","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19296,74,"BVT","Bouvet Island","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19297,74,"BVT","Bouvet Island","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19298,74,"BVT","Bouvet Island","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19299,74,"BVT","Bouvet Island","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19300,74,"BVT","Bouvet Island","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BVT/DMSP/bvt_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19301,84,"BLZ","Belize","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19302,84,"BLZ","Belize","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19303,84,"BLZ","Belize","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19304,84,"BLZ","Belize","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19305,84,"BLZ","Belize","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19306,84,"BLZ","Belize","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19307,84,"BLZ","Belize","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19308,84,"BLZ","Belize","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19309,84,"BLZ","Belize","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19310,84,"BLZ","Belize","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19311,84,"BLZ","Belize","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19312,84,"BLZ","Belize","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/DMSP/blz_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19313,86,"IOT","British Indian Ocean Territory","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19314,86,"IOT","British Indian Ocean Territory","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19315,86,"IOT","British Indian Ocean Territory","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19316,86,"IOT","British Indian Ocean Territory","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19317,86,"IOT","British Indian Ocean Territory","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19318,86,"IOT","British Indian Ocean Territory","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19319,86,"IOT","British Indian Ocean Territory","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19320,86,"IOT","British Indian Ocean Territory","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19321,86,"IOT","British Indian Ocean Territory","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19322,86,"IOT","British Indian Ocean Territory","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19323,86,"IOT","British Indian Ocean Territory","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19324,86,"IOT","British Indian Ocean Territory","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/IOT/DMSP/iot_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19325,90,"SLB","Solomon Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19326,90,"SLB","Solomon Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19327,90,"SLB","Solomon Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19328,90,"SLB","Solomon Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19329,90,"SLB","Solomon Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19330,90,"SLB","Solomon Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19331,90,"SLB","Solomon Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19332,90,"SLB","Solomon Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19333,90,"SLB","Solomon Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19334,90,"SLB","Solomon Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19335,90,"SLB","Solomon Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19336,90,"SLB","Solomon Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SLB/DMSP/slb_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19337,92,"VGB","British Virgin Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19338,92,"VGB","British Virgin Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19339,92,"VGB","British Virgin Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19340,92,"VGB","British Virgin Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19341,92,"VGB","British Virgin Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19342,92,"VGB","British Virgin Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19343,92,"VGB","British Virgin Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19344,92,"VGB","British Virgin Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19345,92,"VGB","British Virgin Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19346,92,"VGB","British Virgin Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19347,92,"VGB","British Virgin Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19348,92,"VGB","British Virgin Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/VGB/DMSP/vgb_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19349,96,"BRN","Brunei","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19350,96,"BRN","Brunei","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19351,96,"BRN","Brunei","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19352,96,"BRN","Brunei","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19353,96,"BRN","Brunei","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19354,96,"BRN","Brunei","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19355,96,"BRN","Brunei","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19356,96,"BRN","Brunei","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19357,96,"BRN","Brunei","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19358,96,"BRN","Brunei","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19359,96,"BRN","Brunei","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19360,96,"BRN","Brunei","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BRN/DMSP/brn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19361,100,"BGR","Bulgaria","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19362,100,"BGR","Bulgaria","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19363,100,"BGR","Bulgaria","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19364,100,"BGR","Bulgaria","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19365,100,"BGR","Bulgaria","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19366,100,"BGR","Bulgaria","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19367,100,"BGR","Bulgaria","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19368,100,"BGR","Bulgaria","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19369,100,"BGR","Bulgaria","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19370,100,"BGR","Bulgaria","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19371,100,"BGR","Bulgaria","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19372,100,"BGR","Bulgaria","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BGR/DMSP/bgr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19373,104,"MMR","Myanmar","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19374,104,"MMR","Myanmar","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19375,104,"MMR","Myanmar","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19376,104,"MMR","Myanmar","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19377,104,"MMR","Myanmar","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19378,104,"MMR","Myanmar","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19379,104,"MMR","Myanmar","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19380,104,"MMR","Myanmar","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19381,104,"MMR","Myanmar","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19382,104,"MMR","Myanmar","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19383,104,"MMR","Myanmar","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19384,104,"MMR","Myanmar","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MMR/DMSP/mmr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19385,108,"BDI","Burundi","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19386,108,"BDI","Burundi","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19387,108,"BDI","Burundi","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19388,108,"BDI","Burundi","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19389,108,"BDI","Burundi","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19390,108,"BDI","Burundi","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19391,108,"BDI","Burundi","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19392,108,"BDI","Burundi","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19393,108,"BDI","Burundi","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19394,108,"BDI","Burundi","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19395,108,"BDI","Burundi","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19396,108,"BDI","Burundi","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BDI/DMSP/bdi_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19397,112,"BLR","Belarus","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19398,112,"BLR","Belarus","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19399,112,"BLR","Belarus","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19400,112,"BLR","Belarus","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19401,112,"BLR","Belarus","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19402,112,"BLR","Belarus","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19403,112,"BLR","Belarus","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19404,112,"BLR","Belarus","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19405,112,"BLR","Belarus","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19406,112,"BLR","Belarus","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19407,112,"BLR","Belarus","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19408,112,"BLR","Belarus","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BLR/DMSP/blr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19409,116,"KHM","Cambodia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19410,116,"KHM","Cambodia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19411,116,"KHM","Cambodia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19412,116,"KHM","Cambodia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19413,116,"KHM","Cambodia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19414,116,"KHM","Cambodia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19415,116,"KHM","Cambodia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19416,116,"KHM","Cambodia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19417,116,"KHM","Cambodia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19418,116,"KHM","Cambodia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19419,116,"KHM","Cambodia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19420,116,"KHM","Cambodia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/KHM/DMSP/khm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19421,120,"CMR","Cameroon","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19422,120,"CMR","Cameroon","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19423,120,"CMR","Cameroon","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19424,120,"CMR","Cameroon","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19425,120,"CMR","Cameroon","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19426,120,"CMR","Cameroon","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19427,120,"CMR","Cameroon","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19428,120,"CMR","Cameroon","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19429,120,"CMR","Cameroon","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19430,120,"CMR","Cameroon","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19431,120,"CMR","Cameroon","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19432,120,"CMR","Cameroon","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CMR/DMSP/cmr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19433,132,"CPV","Cape Verde","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19434,132,"CPV","Cape Verde","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19435,132,"CPV","Cape Verde","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19436,132,"CPV","Cape Verde","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19437,132,"CPV","Cape Verde","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19438,132,"CPV","Cape Verde","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19439,132,"CPV","Cape Verde","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19440,132,"CPV","Cape Verde","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19441,132,"CPV","Cape Verde","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19442,132,"CPV","Cape Verde","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19443,132,"CPV","Cape Verde","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19444,132,"CPV","Cape Verde","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CPV/DMSP/cpv_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19445,136,"CYM","Cayman Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19446,136,"CYM","Cayman Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19447,136,"CYM","Cayman Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19448,136,"CYM","Cayman Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19449,136,"CYM","Cayman Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19450,136,"CYM","Cayman Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19451,136,"CYM","Cayman Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19452,136,"CYM","Cayman Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19453,136,"CYM","Cayman Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19454,136,"CYM","Cayman Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19455,136,"CYM","Cayman Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19456,136,"CYM","Cayman Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CYM/DMSP/cym_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19457,140,"CAF","Central African Republic","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19458,140,"CAF","Central African Republic","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19459,140,"CAF","Central African Republic","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19460,140,"CAF","Central African Republic","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19461,140,"CAF","Central African Republic","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19462,140,"CAF","Central African Republic","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19463,140,"CAF","Central African Republic","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19464,140,"CAF","Central African Republic","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19465,140,"CAF","Central African Republic","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19466,140,"CAF","Central African Republic","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19467,140,"CAF","Central African Republic","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19468,140,"CAF","Central African Republic","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CAF/DMSP/caf_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19469,144,"LKA","Sri Lanka","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19470,144,"LKA","Sri Lanka","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19471,144,"LKA","Sri Lanka","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19472,144,"LKA","Sri Lanka","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19473,144,"LKA","Sri Lanka","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19474,144,"LKA","Sri Lanka","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19475,144,"LKA","Sri Lanka","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19476,144,"LKA","Sri Lanka","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19477,144,"LKA","Sri Lanka","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19478,144,"LKA","Sri Lanka","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19479,144,"LKA","Sri Lanka","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19480,144,"LKA","Sri Lanka","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LKA/DMSP/lka_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19481,148,"TCD","Chad","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19482,148,"TCD","Chad","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19483,148,"TCD","Chad","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19484,148,"TCD","Chad","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19485,148,"TCD","Chad","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19486,148,"TCD","Chad","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19487,148,"TCD","Chad","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19488,148,"TCD","Chad","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19489,148,"TCD","Chad","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19490,148,"TCD","Chad","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19491,148,"TCD","Chad","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19492,148,"TCD","Chad","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TCD/DMSP/tcd_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19493,158,"TWN","Taiwan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19494,158,"TWN","Taiwan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19495,158,"TWN","Taiwan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19496,158,"TWN","Taiwan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19497,158,"TWN","Taiwan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19498,158,"TWN","Taiwan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19499,158,"TWN","Taiwan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19500,158,"TWN","Taiwan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19501,158,"TWN","Taiwan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19502,158,"TWN","Taiwan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19503,158,"TWN","Taiwan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19504,158,"TWN","Taiwan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TWN/DMSP/twn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19505,170,"COL","Colombia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19506,170,"COL","Colombia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19507,170,"COL","Colombia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19508,170,"COL","Colombia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19509,170,"COL","Colombia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19510,170,"COL","Colombia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19511,170,"COL","Colombia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19512,170,"COL","Colombia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19513,170,"COL","Colombia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19514,170,"COL","Colombia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19515,170,"COL","Colombia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19516,170,"COL","Colombia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/COL/DMSP/col_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19517,174,"COM","Comoros","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19518,174,"COM","Comoros","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19519,174,"COM","Comoros","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19520,174,"COM","Comoros","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19521,174,"COM","Comoros","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19522,174,"COM","Comoros","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19523,174,"COM","Comoros","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19524,174,"COM","Comoros","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19525,174,"COM","Comoros","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19526,174,"COM","Comoros","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19527,174,"COM","Comoros","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19528,174,"COM","Comoros","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/COM/DMSP/com_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19529,175,"MYT","Mayotte","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19530,175,"MYT","Mayotte","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19531,175,"MYT","Mayotte","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19532,175,"MYT","Mayotte","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19533,175,"MYT","Mayotte","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19534,175,"MYT","Mayotte","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19535,175,"MYT","Mayotte","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19536,175,"MYT","Mayotte","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19537,175,"MYT","Mayotte","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19538,175,"MYT","Mayotte","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19539,175,"MYT","Mayotte","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19540,175,"MYT","Mayotte","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MYT/DMSP/myt_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19541,178,"COG","Republic of Congo","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19542,178,"COG","Republic of Congo","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19543,178,"COG","Republic of Congo","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19544,178,"COG","Republic of Congo","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19545,178,"COG","Republic of Congo","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19546,178,"COG","Republic of Congo","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19547,178,"COG","Republic of Congo","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19548,178,"COG","Republic of Congo","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19549,178,"COG","Republic of Congo","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19550,178,"COG","Republic of Congo","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19551,178,"COG","Republic of Congo","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19552,178,"COG","Republic of Congo","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/COG/DMSP/cog_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19553,180,"COD","Democratic Republic of the Congo","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19554,180,"COD","Democratic Republic of the Congo","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19555,180,"COD","Democratic Republic of the Congo","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19556,180,"COD","Democratic Republic of the Congo","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19557,180,"COD","Democratic Republic of the Congo","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19558,180,"COD","Democratic Republic of the Congo","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19559,180,"COD","Democratic Republic of the Congo","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19560,180,"COD","Democratic Republic of the Congo","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19561,180,"COD","Democratic Republic of the Congo","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19562,180,"COD","Democratic Republic of the Congo","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19563,180,"COD","Democratic Republic of the Congo","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19564,180,"COD","Democratic Republic of the Congo","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/COD/DMSP/cod_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19565,184,"COK","Cook Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19566,184,"COK","Cook Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19567,184,"COK","Cook Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19568,184,"COK","Cook Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19569,184,"COK","Cook Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19570,184,"COK","Cook Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19571,184,"COK","Cook Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19572,184,"COK","Cook Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19573,184,"COK","Cook Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19574,184,"COK","Cook Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19575,184,"COK","Cook Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19576,184,"COK","Cook Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/COK/DMSP/cok_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19577,188,"CRI","Costa Rica","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19578,188,"CRI","Costa Rica","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19579,188,"CRI","Costa Rica","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19580,188,"CRI","Costa Rica","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19581,188,"CRI","Costa Rica","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19582,188,"CRI","Costa Rica","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19583,188,"CRI","Costa Rica","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19584,188,"CRI","Costa Rica","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19585,188,"CRI","Costa Rica","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19586,188,"CRI","Costa Rica","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19587,188,"CRI","Costa Rica","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19588,188,"CRI","Costa Rica","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CRI/DMSP/cri_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19589,191,"HRV","Croatia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19590,191,"HRV","Croatia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19591,191,"HRV","Croatia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19592,191,"HRV","Croatia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19593,191,"HRV","Croatia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19594,191,"HRV","Croatia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19595,191,"HRV","Croatia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19596,191,"HRV","Croatia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19597,191,"HRV","Croatia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19598,191,"HRV","Croatia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19599,191,"HRV","Croatia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19600,191,"HRV","Croatia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/HRV/DMSP/hrv_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19601,192,"CUB","Cuba","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19602,192,"CUB","Cuba","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19603,192,"CUB","Cuba","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19604,192,"CUB","Cuba","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19605,192,"CUB","Cuba","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19606,192,"CUB","Cuba","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19607,192,"CUB","Cuba","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19608,192,"CUB","Cuba","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19609,192,"CUB","Cuba","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19610,192,"CUB","Cuba","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19611,192,"CUB","Cuba","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19612,192,"CUB","Cuba","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CUB/DMSP/cub_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19613,196,"CYP","Cyprus","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19614,196,"CYP","Cyprus","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19615,196,"CYP","Cyprus","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19616,196,"CYP","Cyprus","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19617,196,"CYP","Cyprus","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19618,196,"CYP","Cyprus","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19619,196,"CYP","Cyprus","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19620,196,"CYP","Cyprus","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19621,196,"CYP","Cyprus","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19622,196,"CYP","Cyprus","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19623,196,"CYP","Cyprus","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19624,196,"CYP","Cyprus","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CYP/DMSP/cyp_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19625,203,"CZE","Czech Republic","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19626,203,"CZE","Czech Republic","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19627,203,"CZE","Czech Republic","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19628,203,"CZE","Czech Republic","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19629,203,"CZE","Czech Republic","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19630,203,"CZE","Czech Republic","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19631,203,"CZE","Czech Republic","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19632,203,"CZE","Czech Republic","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19633,203,"CZE","Czech Republic","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19634,203,"CZE","Czech Republic","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19635,203,"CZE","Czech Republic","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19636,203,"CZE","Czech Republic","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CZE/DMSP/cze_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19637,204,"BEN","Benin","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19638,204,"BEN","Benin","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19639,204,"BEN","Benin","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19640,204,"BEN","Benin","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19641,204,"BEN","Benin","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19642,204,"BEN","Benin","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19643,204,"BEN","Benin","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19644,204,"BEN","Benin","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19645,204,"BEN","Benin","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19646,204,"BEN","Benin","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19647,204,"BEN","Benin","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19648,204,"BEN","Benin","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BEN/DMSP/ben_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19649,208,"DNK","Denmark","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19650,208,"DNK","Denmark","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19651,208,"DNK","Denmark","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19652,208,"DNK","Denmark","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19653,208,"DNK","Denmark","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19654,208,"DNK","Denmark","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19655,208,"DNK","Denmark","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19656,208,"DNK","Denmark","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19657,208,"DNK","Denmark","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19658,208,"DNK","Denmark","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19659,208,"DNK","Denmark","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19660,208,"DNK","Denmark","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/DNK/DMSP/dnk_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19661,212,"DMA","Dominica","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19662,212,"DMA","Dominica","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19663,212,"DMA","Dominica","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19664,212,"DMA","Dominica","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19665,212,"DMA","Dominica","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19666,212,"DMA","Dominica","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19667,212,"DMA","Dominica","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19668,212,"DMA","Dominica","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19669,212,"DMA","Dominica","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19670,212,"DMA","Dominica","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19671,212,"DMA","Dominica","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19672,212,"DMA","Dominica","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/DMA/DMSP/dma_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19673,214,"DOM","Dominican Republic","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19674,214,"DOM","Dominican Republic","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19675,214,"DOM","Dominican Republic","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19676,214,"DOM","Dominican Republic","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19677,214,"DOM","Dominican Republic","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19678,214,"DOM","Dominican Republic","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19679,214,"DOM","Dominican Republic","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19680,214,"DOM","Dominican Republic","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19681,214,"DOM","Dominican Republic","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19682,214,"DOM","Dominican Republic","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19683,214,"DOM","Dominican Republic","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19684,214,"DOM","Dominican Republic","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/DOM/DMSP/dom_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19685,218,"ECU","Ecuador","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19686,218,"ECU","Ecuador","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19687,218,"ECU","Ecuador","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19688,218,"ECU","Ecuador","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19689,218,"ECU","Ecuador","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19690,218,"ECU","Ecuador","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19691,218,"ECU","Ecuador","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19692,218,"ECU","Ecuador","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19693,218,"ECU","Ecuador","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19694,218,"ECU","Ecuador","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19695,218,"ECU","Ecuador","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19696,218,"ECU","Ecuador","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ECU/DMSP/ecu_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19697,222,"SLV","El Salvador","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19698,222,"SLV","El Salvador","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19699,222,"SLV","El Salvador","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19700,222,"SLV","El Salvador","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19701,222,"SLV","El Salvador","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19702,222,"SLV","El Salvador","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19703,222,"SLV","El Salvador","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19704,222,"SLV","El Salvador","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19705,222,"SLV","El Salvador","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19706,222,"SLV","El Salvador","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19707,222,"SLV","El Salvador","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19708,222,"SLV","El Salvador","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SLV/DMSP/slv_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19709,226,"GNQ","Equatorial Guinea","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19710,226,"GNQ","Equatorial Guinea","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19711,226,"GNQ","Equatorial Guinea","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19712,226,"GNQ","Equatorial Guinea","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19713,226,"GNQ","Equatorial Guinea","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19714,226,"GNQ","Equatorial Guinea","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19715,226,"GNQ","Equatorial Guinea","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19716,226,"GNQ","Equatorial Guinea","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19717,226,"GNQ","Equatorial Guinea","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19718,226,"GNQ","Equatorial Guinea","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19719,226,"GNQ","Equatorial Guinea","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19720,226,"GNQ","Equatorial Guinea","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/DMSP/gnq_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19721,231,"ETH","Ethiopia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19722,231,"ETH","Ethiopia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19723,231,"ETH","Ethiopia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19724,231,"ETH","Ethiopia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19725,231,"ETH","Ethiopia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19726,231,"ETH","Ethiopia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19727,231,"ETH","Ethiopia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19728,231,"ETH","Ethiopia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19729,231,"ETH","Ethiopia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19730,231,"ETH","Ethiopia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19731,231,"ETH","Ethiopia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19732,231,"ETH","Ethiopia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ETH/DMSP/eth_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19733,232,"ERI","Eritrea","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19734,232,"ERI","Eritrea","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19735,232,"ERI","Eritrea","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19736,232,"ERI","Eritrea","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19737,232,"ERI","Eritrea","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19738,232,"ERI","Eritrea","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19739,232,"ERI","Eritrea","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19740,232,"ERI","Eritrea","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19741,232,"ERI","Eritrea","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19742,232,"ERI","Eritrea","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19743,232,"ERI","Eritrea","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19744,232,"ERI","Eritrea","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ERI/DMSP/eri_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19745,233,"EST","Estonia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19746,233,"EST","Estonia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19747,233,"EST","Estonia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19748,233,"EST","Estonia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19749,233,"EST","Estonia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19750,233,"EST","Estonia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19751,233,"EST","Estonia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19752,233,"EST","Estonia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19753,233,"EST","Estonia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19754,233,"EST","Estonia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19755,233,"EST","Estonia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19756,233,"EST","Estonia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/EST/DMSP/est_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19757,234,"FRO","Faroe Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19758,234,"FRO","Faroe Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19759,234,"FRO","Faroe Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19760,234,"FRO","Faroe Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19761,234,"FRO","Faroe Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19762,234,"FRO","Faroe Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19763,234,"FRO","Faroe Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19764,234,"FRO","Faroe Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19765,234,"FRO","Faroe Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19766,234,"FRO","Faroe Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19767,234,"FRO","Faroe Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19768,234,"FRO","Faroe Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/FRO/DMSP/fro_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19769,238,"FLK","Falkland Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19770,238,"FLK","Falkland Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19771,238,"FLK","Falkland Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19772,238,"FLK","Falkland Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19773,238,"FLK","Falkland Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19774,238,"FLK","Falkland Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19775,238,"FLK","Falkland Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19776,238,"FLK","Falkland Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19777,238,"FLK","Falkland Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19778,238,"FLK","Falkland Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19779,238,"FLK","Falkland Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19780,238,"FLK","Falkland Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/FLK/DMSP/flk_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19781,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19782,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19783,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19784,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19785,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19786,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19787,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19788,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19789,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19790,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19791,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19792,239,"SGS","South Georgia and the South Sandwich Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SGS/DMSP/sgs_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19793,242,"FJI","Fiji","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19794,242,"FJI","Fiji","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19795,242,"FJI","Fiji","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19796,242,"FJI","Fiji","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19797,242,"FJI","Fiji","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19798,242,"FJI","Fiji","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19799,242,"FJI","Fiji","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19800,242,"FJI","Fiji","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19801,242,"FJI","Fiji","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19802,242,"FJI","Fiji","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19803,242,"FJI","Fiji","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19804,242,"FJI","Fiji","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/FJI/DMSP/fji_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19805,246,"FIN","Finland","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19806,246,"FIN","Finland","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19807,246,"FIN","Finland","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19808,246,"FIN","Finland","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19809,246,"FIN","Finland","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19810,246,"FIN","Finland","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19811,246,"FIN","Finland","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19812,246,"FIN","Finland","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19813,246,"FIN","Finland","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19814,246,"FIN","Finland","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19815,246,"FIN","Finland","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19816,246,"FIN","Finland","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/FIN/DMSP/fin_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19817,248,"ALA","Aland Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19818,248,"ALA","Aland Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19819,248,"ALA","Aland Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19820,248,"ALA","Aland Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19821,248,"ALA","Aland Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19822,248,"ALA","Aland Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19823,248,"ALA","Aland Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19824,248,"ALA","Aland Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19825,248,"ALA","Aland Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19826,248,"ALA","Aland Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19827,248,"ALA","Aland Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19828,248,"ALA","Aland Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ALA/DMSP/ala_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19829,250,"FRA","France","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19830,250,"FRA","France","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19831,250,"FRA","France","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19832,250,"FRA","France","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19833,250,"FRA","France","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19834,250,"FRA","France","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19835,250,"FRA","France","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19836,250,"FRA","France","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19837,250,"FRA","France","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19838,250,"FRA","France","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19839,250,"FRA","France","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19840,250,"FRA","France","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/FRA/DMSP/fra_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19841,254,"GUF","French Guiana","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19842,254,"GUF","French Guiana","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19843,254,"GUF","French Guiana","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19844,254,"GUF","French Guiana","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19845,254,"GUF","French Guiana","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19846,254,"GUF","French Guiana","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19847,254,"GUF","French Guiana","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19848,254,"GUF","French Guiana","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19849,254,"GUF","French Guiana","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19850,254,"GUF","French Guiana","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19851,254,"GUF","French Guiana","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19852,254,"GUF","French Guiana","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GUF/DMSP/guf_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19853,258,"PYF","French Polynesia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19854,258,"PYF","French Polynesia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19855,258,"PYF","French Polynesia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19856,258,"PYF","French Polynesia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19857,258,"PYF","French Polynesia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19858,258,"PYF","French Polynesia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19859,258,"PYF","French Polynesia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19860,258,"PYF","French Polynesia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19861,258,"PYF","French Polynesia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19862,258,"PYF","French Polynesia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19863,258,"PYF","French Polynesia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19864,258,"PYF","French Polynesia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PYF/DMSP/pyf_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19865,260,"ATF","French Southern Territories","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19866,260,"ATF","French Southern Territories","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19867,260,"ATF","French Southern Territories","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19868,260,"ATF","French Southern Territories","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19869,260,"ATF","French Southern Territories","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19870,260,"ATF","French Southern Territories","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19871,260,"ATF","French Southern Territories","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19872,260,"ATF","French Southern Territories","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19873,260,"ATF","French Southern Territories","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19874,260,"ATF","French Southern Territories","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19875,260,"ATF","French Southern Territories","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19876,260,"ATF","French Southern Territories","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ATF/DMSP/atf_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19877,262,"DJI","Djibouti","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19878,262,"DJI","Djibouti","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19879,262,"DJI","Djibouti","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19880,262,"DJI","Djibouti","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19881,262,"DJI","Djibouti","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19882,262,"DJI","Djibouti","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19883,262,"DJI","Djibouti","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19884,262,"DJI","Djibouti","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19885,262,"DJI","Djibouti","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19886,262,"DJI","Djibouti","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19887,262,"DJI","Djibouti","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19888,262,"DJI","Djibouti","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/DJI/DMSP/dji_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19889,266,"GAB","Gabon","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19890,266,"GAB","Gabon","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19891,266,"GAB","Gabon","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19892,266,"GAB","Gabon","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19893,266,"GAB","Gabon","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19894,266,"GAB","Gabon","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19895,266,"GAB","Gabon","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19896,266,"GAB","Gabon","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19897,266,"GAB","Gabon","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19898,266,"GAB","Gabon","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19899,266,"GAB","Gabon","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19900,266,"GAB","Gabon","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GAB/DMSP/gab_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19901,268,"GEO","Georgia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19902,268,"GEO","Georgia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19903,268,"GEO","Georgia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19904,268,"GEO","Georgia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19905,268,"GEO","Georgia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19906,268,"GEO","Georgia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19907,268,"GEO","Georgia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19908,268,"GEO","Georgia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19909,268,"GEO","Georgia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19910,268,"GEO","Georgia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19911,268,"GEO","Georgia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19912,268,"GEO","Georgia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GEO/DMSP/geo_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19913,270,"GMB","Gambia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19914,270,"GMB","Gambia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19915,270,"GMB","Gambia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19916,270,"GMB","Gambia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19917,270,"GMB","Gambia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19918,270,"GMB","Gambia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19919,270,"GMB","Gambia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19920,270,"GMB","Gambia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19921,270,"GMB","Gambia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19922,270,"GMB","Gambia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19923,270,"GMB","Gambia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19924,270,"GMB","Gambia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GMB/DMSP/gmb_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19925,275,"PSE","Palestina","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19926,275,"PSE","Palestina","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19927,275,"PSE","Palestina","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19928,275,"PSE","Palestina","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19929,275,"PSE","Palestina","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19930,275,"PSE","Palestina","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19931,275,"PSE","Palestina","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19932,275,"PSE","Palestina","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19933,275,"PSE","Palestina","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19934,275,"PSE","Palestina","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19935,275,"PSE","Palestina","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19936,275,"PSE","Palestina","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PSE/DMSP/pse_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19937,276,"DEU","Germany","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19938,276,"DEU","Germany","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19939,276,"DEU","Germany","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19940,276,"DEU","Germany","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19941,276,"DEU","Germany","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19942,276,"DEU","Germany","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19943,276,"DEU","Germany","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19944,276,"DEU","Germany","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19945,276,"DEU","Germany","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19946,276,"DEU","Germany","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19947,276,"DEU","Germany","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19948,276,"DEU","Germany","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/DEU/DMSP/deu_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19949,288,"GHA","Ghana","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19950,288,"GHA","Ghana","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19951,288,"GHA","Ghana","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19952,288,"GHA","Ghana","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19953,288,"GHA","Ghana","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19954,288,"GHA","Ghana","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19955,288,"GHA","Ghana","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19956,288,"GHA","Ghana","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19957,288,"GHA","Ghana","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19958,288,"GHA","Ghana","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19959,288,"GHA","Ghana","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19960,288,"GHA","Ghana","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GHA/DMSP/gha_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19961,292,"GIB","Gibraltar","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19962,292,"GIB","Gibraltar","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19963,292,"GIB","Gibraltar","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19964,292,"GIB","Gibraltar","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19965,292,"GIB","Gibraltar","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19966,292,"GIB","Gibraltar","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19967,292,"GIB","Gibraltar","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19968,292,"GIB","Gibraltar","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19969,292,"GIB","Gibraltar","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19970,292,"GIB","Gibraltar","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19971,292,"GIB","Gibraltar","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19972,292,"GIB","Gibraltar","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GIB/DMSP/gib_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19973,296,"KIR","Kiribati","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19974,296,"KIR","Kiribati","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19975,296,"KIR","Kiribati","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19976,296,"KIR","Kiribati","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19977,296,"KIR","Kiribati","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19978,296,"KIR","Kiribati","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19979,296,"KIR","Kiribati","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19980,296,"KIR","Kiribati","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19981,296,"KIR","Kiribati","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19982,296,"KIR","Kiribati","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19983,296,"KIR","Kiribati","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19984,296,"KIR","Kiribati","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/KIR/DMSP/kir_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19985,300,"GRC","Greece","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19986,300,"GRC","Greece","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19987,300,"GRC","Greece","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
19988,300,"GRC","Greece","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
19989,300,"GRC","Greece","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
19990,300,"GRC","Greece","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
19991,300,"GRC","Greece","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
19992,300,"GRC","Greece","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
19993,300,"GRC","Greece","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
19994,300,"GRC","Greece","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
19995,300,"GRC","Greece","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
19996,300,"GRC","Greece","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GRC/DMSP/grc_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
19997,308,"GRD","Grenada","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
19998,308,"GRD","Grenada","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
19999,308,"GRD","Grenada","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20000,308,"GRD","Grenada","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20001,308,"GRD","Grenada","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20002,308,"GRD","Grenada","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20003,308,"GRD","Grenada","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20004,308,"GRD","Grenada","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20005,308,"GRD","Grenada","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20006,308,"GRD","Grenada","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20007,308,"GRD","Grenada","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20008,308,"GRD","Grenada","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GRD/DMSP/grd_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20009,312,"GLP","Guadeloupe","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20010,312,"GLP","Guadeloupe","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20011,312,"GLP","Guadeloupe","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20012,312,"GLP","Guadeloupe","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20013,312,"GLP","Guadeloupe","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20014,312,"GLP","Guadeloupe","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20015,312,"GLP","Guadeloupe","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20016,312,"GLP","Guadeloupe","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20017,312,"GLP","Guadeloupe","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20018,312,"GLP","Guadeloupe","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20019,312,"GLP","Guadeloupe","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20020,312,"GLP","Guadeloupe","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GLP/DMSP/glp_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20021,316,"GUM","Guam","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20022,316,"GUM","Guam","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20023,316,"GUM","Guam","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20024,316,"GUM","Guam","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20025,316,"GUM","Guam","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20026,316,"GUM","Guam","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20027,316,"GUM","Guam","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20028,316,"GUM","Guam","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20029,316,"GUM","Guam","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20030,316,"GUM","Guam","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20031,316,"GUM","Guam","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20032,316,"GUM","Guam","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GUM/DMSP/gum_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20033,320,"GTM","Guatemala","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20034,320,"GTM","Guatemala","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20035,320,"GTM","Guatemala","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20036,320,"GTM","Guatemala","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20037,320,"GTM","Guatemala","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20038,320,"GTM","Guatemala","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20039,320,"GTM","Guatemala","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20040,320,"GTM","Guatemala","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20041,320,"GTM","Guatemala","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20042,320,"GTM","Guatemala","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20043,320,"GTM","Guatemala","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20044,320,"GTM","Guatemala","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GTM/DMSP/gtm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20045,324,"GIN","Guinea","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20046,324,"GIN","Guinea","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20047,324,"GIN","Guinea","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20048,324,"GIN","Guinea","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20049,324,"GIN","Guinea","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20050,324,"GIN","Guinea","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20051,324,"GIN","Guinea","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20052,324,"GIN","Guinea","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20053,324,"GIN","Guinea","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20054,324,"GIN","Guinea","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20055,324,"GIN","Guinea","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20056,324,"GIN","Guinea","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GIN/DMSP/gin_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20057,328,"GUY","Guyana","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20058,328,"GUY","Guyana","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20059,328,"GUY","Guyana","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20060,328,"GUY","Guyana","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20061,328,"GUY","Guyana","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20062,328,"GUY","Guyana","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20063,328,"GUY","Guyana","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20064,328,"GUY","Guyana","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20065,328,"GUY","Guyana","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20066,328,"GUY","Guyana","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20067,328,"GUY","Guyana","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20068,328,"GUY","Guyana","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GUY/DMSP/guy_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20069,332,"HTI","Haiti","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20070,332,"HTI","Haiti","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20071,332,"HTI","Haiti","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20072,332,"HTI","Haiti","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20073,332,"HTI","Haiti","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20074,332,"HTI","Haiti","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20075,332,"HTI","Haiti","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20076,332,"HTI","Haiti","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20077,332,"HTI","Haiti","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20078,332,"HTI","Haiti","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20079,332,"HTI","Haiti","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20080,332,"HTI","Haiti","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/HTI/DMSP/hti_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20081,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20082,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20083,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20084,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20085,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20086,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20087,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20088,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20089,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20090,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20091,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20092,334,"HMD","Heard Island and McDonald Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/HMD/DMSP/hmd_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20093,336,"VAT","Vatican City","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20094,336,"VAT","Vatican City","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20095,336,"VAT","Vatican City","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20096,336,"VAT","Vatican City","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20097,336,"VAT","Vatican City","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20098,336,"VAT","Vatican City","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20099,336,"VAT","Vatican City","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20100,336,"VAT","Vatican City","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20101,336,"VAT","Vatican City","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20102,336,"VAT","Vatican City","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20103,336,"VAT","Vatican City","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20104,336,"VAT","Vatican City","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/VAT/DMSP/vat_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20105,340,"HND","Honduras","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20106,340,"HND","Honduras","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20107,340,"HND","Honduras","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20108,340,"HND","Honduras","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20109,340,"HND","Honduras","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20110,340,"HND","Honduras","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20111,340,"HND","Honduras","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20112,340,"HND","Honduras","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20113,340,"HND","Honduras","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20114,340,"HND","Honduras","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20115,340,"HND","Honduras","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20116,340,"HND","Honduras","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/HND/DMSP/hnd_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20117,344,"HKG","Hong Kong","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20118,344,"HKG","Hong Kong","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20119,344,"HKG","Hong Kong","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20120,344,"HKG","Hong Kong","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20121,344,"HKG","Hong Kong","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20122,344,"HKG","Hong Kong","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20123,344,"HKG","Hong Kong","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20124,344,"HKG","Hong Kong","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20125,344,"HKG","Hong Kong","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20126,344,"HKG","Hong Kong","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20127,344,"HKG","Hong Kong","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20128,344,"HKG","Hong Kong","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/HKG/DMSP/hkg_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20129,348,"HUN","Hungary","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20130,348,"HUN","Hungary","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20131,348,"HUN","Hungary","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20132,348,"HUN","Hungary","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20133,348,"HUN","Hungary","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20134,348,"HUN","Hungary","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20135,348,"HUN","Hungary","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20136,348,"HUN","Hungary","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20137,348,"HUN","Hungary","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20138,348,"HUN","Hungary","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20139,348,"HUN","Hungary","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20140,348,"HUN","Hungary","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/HUN/DMSP/hun_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20141,352,"ISL","Iceland","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20142,352,"ISL","Iceland","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20143,352,"ISL","Iceland","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20144,352,"ISL","Iceland","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20145,352,"ISL","Iceland","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20146,352,"ISL","Iceland","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20147,352,"ISL","Iceland","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20148,352,"ISL","Iceland","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20149,352,"ISL","Iceland","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20150,352,"ISL","Iceland","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20151,352,"ISL","Iceland","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20152,352,"ISL","Iceland","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ISL/DMSP/isl_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20153,356,"IND","India","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20154,356,"IND","India","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20155,356,"IND","India","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20156,356,"IND","India","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20157,356,"IND","India","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20158,356,"IND","India","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20159,356,"IND","India","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20160,356,"IND","India","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20161,356,"IND","India","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20162,356,"IND","India","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20163,356,"IND","India","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20164,356,"IND","India","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/IND/DMSP/ind_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20165,364,"IRN","Iran","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20166,364,"IRN","Iran","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20167,364,"IRN","Iran","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20168,364,"IRN","Iran","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20169,364,"IRN","Iran","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20170,364,"IRN","Iran","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20171,364,"IRN","Iran","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20172,364,"IRN","Iran","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20173,364,"IRN","Iran","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20174,364,"IRN","Iran","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20175,364,"IRN","Iran","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20176,364,"IRN","Iran","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/IRN/DMSP/irn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20177,368,"IRQ","Iraq","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20178,368,"IRQ","Iraq","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20179,368,"IRQ","Iraq","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20180,368,"IRQ","Iraq","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20181,368,"IRQ","Iraq","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20182,368,"IRQ","Iraq","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20183,368,"IRQ","Iraq","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20184,368,"IRQ","Iraq","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20185,368,"IRQ","Iraq","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20186,368,"IRQ","Iraq","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20187,368,"IRQ","Iraq","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20188,368,"IRQ","Iraq","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/DMSP/irq_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20189,372,"IRL","Ireland","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20190,372,"IRL","Ireland","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20191,372,"IRL","Ireland","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20192,372,"IRL","Ireland","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20193,372,"IRL","Ireland","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20194,372,"IRL","Ireland","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20195,372,"IRL","Ireland","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20196,372,"IRL","Ireland","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20197,372,"IRL","Ireland","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20198,372,"IRL","Ireland","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20199,372,"IRL","Ireland","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20200,372,"IRL","Ireland","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/IRL/DMSP/irl_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20201,376,"ISR","Israel","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20202,376,"ISR","Israel","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20203,376,"ISR","Israel","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20204,376,"ISR","Israel","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20205,376,"ISR","Israel","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20206,376,"ISR","Israel","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20207,376,"ISR","Israel","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20208,376,"ISR","Israel","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20209,376,"ISR","Israel","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20210,376,"ISR","Israel","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20211,376,"ISR","Israel","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20212,376,"ISR","Israel","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ISR/DMSP/isr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20213,380,"ITA","Italy","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20214,380,"ITA","Italy","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20215,380,"ITA","Italy","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20216,380,"ITA","Italy","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20217,380,"ITA","Italy","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20218,380,"ITA","Italy","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20219,380,"ITA","Italy","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20220,380,"ITA","Italy","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20221,380,"ITA","Italy","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20222,380,"ITA","Italy","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20223,380,"ITA","Italy","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20224,380,"ITA","Italy","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ITA/DMSP/ita_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20225,384,"CIV","CIte dIvoire","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20226,384,"CIV","CIte dIvoire","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20227,384,"CIV","CIte dIvoire","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20228,384,"CIV","CIte dIvoire","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20229,384,"CIV","CIte dIvoire","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20230,384,"CIV","CIte dIvoire","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20231,384,"CIV","CIte dIvoire","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20232,384,"CIV","CIte dIvoire","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20233,384,"CIV","CIte dIvoire","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20234,384,"CIV","CIte dIvoire","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20235,384,"CIV","CIte dIvoire","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20236,384,"CIV","CIte dIvoire","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CIV/DMSP/civ_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20237,388,"JAM","Jamaica","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20238,388,"JAM","Jamaica","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20239,388,"JAM","Jamaica","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20240,388,"JAM","Jamaica","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20241,388,"JAM","Jamaica","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20242,388,"JAM","Jamaica","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20243,388,"JAM","Jamaica","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20244,388,"JAM","Jamaica","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20245,388,"JAM","Jamaica","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20246,388,"JAM","Jamaica","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20247,388,"JAM","Jamaica","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20248,388,"JAM","Jamaica","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/JAM/DMSP/jam_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20249,392,"JPN","Japan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20250,392,"JPN","Japan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20251,392,"JPN","Japan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20252,392,"JPN","Japan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20253,392,"JPN","Japan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20254,392,"JPN","Japan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20255,392,"JPN","Japan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20256,392,"JPN","Japan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20257,392,"JPN","Japan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20258,392,"JPN","Japan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20259,392,"JPN","Japan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20260,392,"JPN","Japan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/JPN/DMSP/jpn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20261,398,"KAZ","Kazakhstan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20262,398,"KAZ","Kazakhstan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20263,398,"KAZ","Kazakhstan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20264,398,"KAZ","Kazakhstan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20265,398,"KAZ","Kazakhstan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20266,398,"KAZ","Kazakhstan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20267,398,"KAZ","Kazakhstan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20268,398,"KAZ","Kazakhstan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20269,398,"KAZ","Kazakhstan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20270,398,"KAZ","Kazakhstan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20271,398,"KAZ","Kazakhstan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20272,398,"KAZ","Kazakhstan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/DMSP/kaz_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20273,400,"JOR","Jordan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20274,400,"JOR","Jordan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20275,400,"JOR","Jordan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20276,400,"JOR","Jordan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20277,400,"JOR","Jordan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20278,400,"JOR","Jordan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20279,400,"JOR","Jordan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20280,400,"JOR","Jordan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20281,400,"JOR","Jordan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20282,400,"JOR","Jordan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20283,400,"JOR","Jordan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20284,400,"JOR","Jordan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/JOR/DMSP/jor_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20285,404,"KEN","Kenya","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20286,404,"KEN","Kenya","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20287,404,"KEN","Kenya","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20288,404,"KEN","Kenya","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20289,404,"KEN","Kenya","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20290,404,"KEN","Kenya","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20291,404,"KEN","Kenya","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20292,404,"KEN","Kenya","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20293,404,"KEN","Kenya","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20294,404,"KEN","Kenya","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20295,404,"KEN","Kenya","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20296,404,"KEN","Kenya","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/KEN/DMSP/ken_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20297,408,"PRK","North Korea","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20298,408,"PRK","North Korea","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20299,408,"PRK","North Korea","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20300,408,"PRK","North Korea","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20301,408,"PRK","North Korea","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20302,408,"PRK","North Korea","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20303,408,"PRK","North Korea","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20304,408,"PRK","North Korea","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20305,408,"PRK","North Korea","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20306,408,"PRK","North Korea","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20307,408,"PRK","North Korea","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20308,408,"PRK","North Korea","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PRK/DMSP/prk_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20309,410,"KOR","South Korea","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20310,410,"KOR","South Korea","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20311,410,"KOR","South Korea","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20312,410,"KOR","South Korea","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20313,410,"KOR","South Korea","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20314,410,"KOR","South Korea","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20315,410,"KOR","South Korea","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20316,410,"KOR","South Korea","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20317,410,"KOR","South Korea","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20318,410,"KOR","South Korea","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20319,410,"KOR","South Korea","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20320,410,"KOR","South Korea","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/KOR/DMSP/kor_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20321,414,"KWT","Kuwait","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20322,414,"KWT","Kuwait","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20323,414,"KWT","Kuwait","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20324,414,"KWT","Kuwait","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20325,414,"KWT","Kuwait","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20326,414,"KWT","Kuwait","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20327,414,"KWT","Kuwait","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20328,414,"KWT","Kuwait","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20329,414,"KWT","Kuwait","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20330,414,"KWT","Kuwait","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20331,414,"KWT","Kuwait","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20332,414,"KWT","Kuwait","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/KWT/DMSP/kwt_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20333,417,"KGZ","Kyrgyzstan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20334,417,"KGZ","Kyrgyzstan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20335,417,"KGZ","Kyrgyzstan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20336,417,"KGZ","Kyrgyzstan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20337,417,"KGZ","Kyrgyzstan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20338,417,"KGZ","Kyrgyzstan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20339,417,"KGZ","Kyrgyzstan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20340,417,"KGZ","Kyrgyzstan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20341,417,"KGZ","Kyrgyzstan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20342,417,"KGZ","Kyrgyzstan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20343,417,"KGZ","Kyrgyzstan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20344,417,"KGZ","Kyrgyzstan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/DMSP/kgz_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20345,418,"LAO","Laos","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20346,418,"LAO","Laos","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20347,418,"LAO","Laos","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20348,418,"LAO","Laos","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20349,418,"LAO","Laos","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20350,418,"LAO","Laos","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20351,418,"LAO","Laos","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20352,418,"LAO","Laos","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20353,418,"LAO","Laos","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20354,418,"LAO","Laos","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20355,418,"LAO","Laos","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20356,418,"LAO","Laos","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LAO/DMSP/lao_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20357,422,"LBN","Lebanon","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20358,422,"LBN","Lebanon","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20359,422,"LBN","Lebanon","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20360,422,"LBN","Lebanon","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20361,422,"LBN","Lebanon","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20362,422,"LBN","Lebanon","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20363,422,"LBN","Lebanon","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20364,422,"LBN","Lebanon","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20365,422,"LBN","Lebanon","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20366,422,"LBN","Lebanon","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20367,422,"LBN","Lebanon","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20368,422,"LBN","Lebanon","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LBN/DMSP/lbn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20369,426,"LSO","Lesotho","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20370,426,"LSO","Lesotho","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20371,426,"LSO","Lesotho","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20372,426,"LSO","Lesotho","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20373,426,"LSO","Lesotho","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20374,426,"LSO","Lesotho","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20375,426,"LSO","Lesotho","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20376,426,"LSO","Lesotho","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20377,426,"LSO","Lesotho","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20378,426,"LSO","Lesotho","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20379,426,"LSO","Lesotho","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20380,426,"LSO","Lesotho","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LSO/DMSP/lso_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20381,428,"LVA","Latvia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20382,428,"LVA","Latvia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20383,428,"LVA","Latvia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20384,428,"LVA","Latvia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20385,428,"LVA","Latvia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20386,428,"LVA","Latvia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20387,428,"LVA","Latvia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20388,428,"LVA","Latvia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20389,428,"LVA","Latvia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20390,428,"LVA","Latvia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20391,428,"LVA","Latvia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20392,428,"LVA","Latvia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LVA/DMSP/lva_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20393,430,"LBR","Liberia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20394,430,"LBR","Liberia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20395,430,"LBR","Liberia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20396,430,"LBR","Liberia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20397,430,"LBR","Liberia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20398,430,"LBR","Liberia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20399,430,"LBR","Liberia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20400,430,"LBR","Liberia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20401,430,"LBR","Liberia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20402,430,"LBR","Liberia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20403,430,"LBR","Liberia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20404,430,"LBR","Liberia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LBR/DMSP/lbr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20405,434,"LBY","Libya","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20406,434,"LBY","Libya","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20407,434,"LBY","Libya","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20408,434,"LBY","Libya","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20409,434,"LBY","Libya","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20410,434,"LBY","Libya","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20411,434,"LBY","Libya","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20412,434,"LBY","Libya","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20413,434,"LBY","Libya","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20414,434,"LBY","Libya","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20415,434,"LBY","Libya","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20416,434,"LBY","Libya","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LBY/DMSP/lby_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20417,438,"LIE","Liechtenstein","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20418,438,"LIE","Liechtenstein","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20419,438,"LIE","Liechtenstein","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20420,438,"LIE","Liechtenstein","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20421,438,"LIE","Liechtenstein","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20422,438,"LIE","Liechtenstein","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20423,438,"LIE","Liechtenstein","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20424,438,"LIE","Liechtenstein","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20425,438,"LIE","Liechtenstein","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20426,438,"LIE","Liechtenstein","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20427,438,"LIE","Liechtenstein","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20428,438,"LIE","Liechtenstein","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LIE/DMSP/lie_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20429,440,"LTU","Lithuania","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20430,440,"LTU","Lithuania","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20431,440,"LTU","Lithuania","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20432,440,"LTU","Lithuania","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20433,440,"LTU","Lithuania","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20434,440,"LTU","Lithuania","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20435,440,"LTU","Lithuania","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20436,440,"LTU","Lithuania","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20437,440,"LTU","Lithuania","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20438,440,"LTU","Lithuania","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20439,440,"LTU","Lithuania","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20440,440,"LTU","Lithuania","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LTU/DMSP/ltu_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20441,442,"LUX","Luxembourg","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20442,442,"LUX","Luxembourg","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20443,442,"LUX","Luxembourg","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20444,442,"LUX","Luxembourg","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20445,442,"LUX","Luxembourg","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20446,442,"LUX","Luxembourg","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20447,442,"LUX","Luxembourg","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20448,442,"LUX","Luxembourg","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20449,442,"LUX","Luxembourg","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20450,442,"LUX","Luxembourg","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20451,442,"LUX","Luxembourg","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20452,442,"LUX","Luxembourg","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LUX/DMSP/lux_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20453,446,"MAC","Macao","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20454,446,"MAC","Macao","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20455,446,"MAC","Macao","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20456,446,"MAC","Macao","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20457,446,"MAC","Macao","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20458,446,"MAC","Macao","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20459,446,"MAC","Macao","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20460,446,"MAC","Macao","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20461,446,"MAC","Macao","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20462,446,"MAC","Macao","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20463,446,"MAC","Macao","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20464,446,"MAC","Macao","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MAC/DMSP/mac_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20465,450,"MDG","Madagascar","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20466,450,"MDG","Madagascar","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20467,450,"MDG","Madagascar","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20468,450,"MDG","Madagascar","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20469,450,"MDG","Madagascar","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20470,450,"MDG","Madagascar","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20471,450,"MDG","Madagascar","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20472,450,"MDG","Madagascar","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20473,450,"MDG","Madagascar","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20474,450,"MDG","Madagascar","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20475,450,"MDG","Madagascar","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20476,450,"MDG","Madagascar","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MDG/DMSP/mdg_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20477,454,"MWI","Malawi","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20478,454,"MWI","Malawi","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20479,454,"MWI","Malawi","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20480,454,"MWI","Malawi","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20481,454,"MWI","Malawi","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20482,454,"MWI","Malawi","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20483,454,"MWI","Malawi","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20484,454,"MWI","Malawi","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20485,454,"MWI","Malawi","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20486,454,"MWI","Malawi","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20487,454,"MWI","Malawi","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20488,454,"MWI","Malawi","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MWI/DMSP/mwi_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20489,458,"MYS","Malaysia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20490,458,"MYS","Malaysia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20491,458,"MYS","Malaysia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20492,458,"MYS","Malaysia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20493,458,"MYS","Malaysia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20494,458,"MYS","Malaysia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20495,458,"MYS","Malaysia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20496,458,"MYS","Malaysia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20497,458,"MYS","Malaysia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20498,458,"MYS","Malaysia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20499,458,"MYS","Malaysia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20500,458,"MYS","Malaysia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MYS/DMSP/mys_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20501,462,"MDV","Maldives","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20502,462,"MDV","Maldives","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20503,462,"MDV","Maldives","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20504,462,"MDV","Maldives","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20505,462,"MDV","Maldives","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20506,462,"MDV","Maldives","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20507,462,"MDV","Maldives","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20508,462,"MDV","Maldives","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20509,462,"MDV","Maldives","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20510,462,"MDV","Maldives","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20511,462,"MDV","Maldives","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20512,462,"MDV","Maldives","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MDV/DMSP/mdv_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20513,466,"MLI","Mali","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20514,466,"MLI","Mali","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20515,466,"MLI","Mali","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20516,466,"MLI","Mali","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20517,466,"MLI","Mali","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20518,466,"MLI","Mali","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20519,466,"MLI","Mali","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20520,466,"MLI","Mali","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20521,466,"MLI","Mali","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20522,466,"MLI","Mali","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20523,466,"MLI","Mali","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20524,466,"MLI","Mali","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MLI/DMSP/mli_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20525,470,"MLT","Malta","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20526,470,"MLT","Malta","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20527,470,"MLT","Malta","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20528,470,"MLT","Malta","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20529,470,"MLT","Malta","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20530,470,"MLT","Malta","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20531,470,"MLT","Malta","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20532,470,"MLT","Malta","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20533,470,"MLT","Malta","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20534,470,"MLT","Malta","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20535,470,"MLT","Malta","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20536,470,"MLT","Malta","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MLT/DMSP/mlt_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20537,474,"MTQ","Martinique","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20538,474,"MTQ","Martinique","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20539,474,"MTQ","Martinique","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20540,474,"MTQ","Martinique","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20541,474,"MTQ","Martinique","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20542,474,"MTQ","Martinique","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20543,474,"MTQ","Martinique","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20544,474,"MTQ","Martinique","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20545,474,"MTQ","Martinique","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20546,474,"MTQ","Martinique","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20547,474,"MTQ","Martinique","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20548,474,"MTQ","Martinique","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/DMSP/mtq_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20549,478,"MRT","Mauritania","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20550,478,"MRT","Mauritania","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20551,478,"MRT","Mauritania","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20552,478,"MRT","Mauritania","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20553,478,"MRT","Mauritania","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20554,478,"MRT","Mauritania","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20555,478,"MRT","Mauritania","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20556,478,"MRT","Mauritania","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20557,478,"MRT","Mauritania","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20558,478,"MRT","Mauritania","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20559,478,"MRT","Mauritania","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20560,478,"MRT","Mauritania","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MRT/DMSP/mrt_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20561,480,"MUS","Mauritius","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20562,480,"MUS","Mauritius","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20563,480,"MUS","Mauritius","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20564,480,"MUS","Mauritius","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20565,480,"MUS","Mauritius","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20566,480,"MUS","Mauritius","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20567,480,"MUS","Mauritius","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20568,480,"MUS","Mauritius","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20569,480,"MUS","Mauritius","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20570,480,"MUS","Mauritius","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20571,480,"MUS","Mauritius","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20572,480,"MUS","Mauritius","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MUS/DMSP/mus_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20573,484,"MEX","Mexico","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20574,484,"MEX","Mexico","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20575,484,"MEX","Mexico","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20576,484,"MEX","Mexico","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20577,484,"MEX","Mexico","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20578,484,"MEX","Mexico","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20579,484,"MEX","Mexico","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20580,484,"MEX","Mexico","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20581,484,"MEX","Mexico","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20582,484,"MEX","Mexico","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20583,484,"MEX","Mexico","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20584,484,"MEX","Mexico","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MEX/DMSP/mex_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20585,492,"MCO","Monaco","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20586,492,"MCO","Monaco","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20587,492,"MCO","Monaco","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20588,492,"MCO","Monaco","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20589,492,"MCO","Monaco","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20590,492,"MCO","Monaco","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20591,492,"MCO","Monaco","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20592,492,"MCO","Monaco","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20593,492,"MCO","Monaco","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20594,492,"MCO","Monaco","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20595,492,"MCO","Monaco","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20596,492,"MCO","Monaco","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MCO/DMSP/mco_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20597,496,"MNG","Mongolia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20598,496,"MNG","Mongolia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20599,496,"MNG","Mongolia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20600,496,"MNG","Mongolia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20601,496,"MNG","Mongolia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20602,496,"MNG","Mongolia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20603,496,"MNG","Mongolia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20604,496,"MNG","Mongolia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20605,496,"MNG","Mongolia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20606,496,"MNG","Mongolia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20607,496,"MNG","Mongolia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20608,496,"MNG","Mongolia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MNG/DMSP/mng_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20609,498,"MDA","Moldova","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20610,498,"MDA","Moldova","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20611,498,"MDA","Moldova","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20612,498,"MDA","Moldova","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20613,498,"MDA","Moldova","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20614,498,"MDA","Moldova","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20615,498,"MDA","Moldova","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20616,498,"MDA","Moldova","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20617,498,"MDA","Moldova","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20618,498,"MDA","Moldova","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20619,498,"MDA","Moldova","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20620,498,"MDA","Moldova","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MDA/DMSP/mda_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20621,499,"MNE","Montenegro","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20622,499,"MNE","Montenegro","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20623,499,"MNE","Montenegro","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20624,499,"MNE","Montenegro","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20625,499,"MNE","Montenegro","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20626,499,"MNE","Montenegro","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20627,499,"MNE","Montenegro","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20628,499,"MNE","Montenegro","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20629,499,"MNE","Montenegro","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20630,499,"MNE","Montenegro","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20631,499,"MNE","Montenegro","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20632,499,"MNE","Montenegro","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MNE/DMSP/mne_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20633,500,"MSR","Montserrat","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20634,500,"MSR","Montserrat","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20635,500,"MSR","Montserrat","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20636,500,"MSR","Montserrat","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20637,500,"MSR","Montserrat","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20638,500,"MSR","Montserrat","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20639,500,"MSR","Montserrat","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20640,500,"MSR","Montserrat","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20641,500,"MSR","Montserrat","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20642,500,"MSR","Montserrat","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20643,500,"MSR","Montserrat","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20644,500,"MSR","Montserrat","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MSR/DMSP/msr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20645,504,"MAR","Morocco","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20646,504,"MAR","Morocco","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20647,504,"MAR","Morocco","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20648,504,"MAR","Morocco","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20649,504,"MAR","Morocco","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20650,504,"MAR","Morocco","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20651,504,"MAR","Morocco","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20652,504,"MAR","Morocco","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20653,504,"MAR","Morocco","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20654,504,"MAR","Morocco","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20655,504,"MAR","Morocco","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20656,504,"MAR","Morocco","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MAR/DMSP/mar_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20657,508,"MOZ","Mozambique","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20658,508,"MOZ","Mozambique","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20659,508,"MOZ","Mozambique","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20660,508,"MOZ","Mozambique","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20661,508,"MOZ","Mozambique","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20662,508,"MOZ","Mozambique","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20663,508,"MOZ","Mozambique","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20664,508,"MOZ","Mozambique","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20665,508,"MOZ","Mozambique","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20666,508,"MOZ","Mozambique","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20667,508,"MOZ","Mozambique","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20668,508,"MOZ","Mozambique","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/DMSP/moz_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20669,512,"OMN","Oman","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20670,512,"OMN","Oman","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20671,512,"OMN","Oman","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20672,512,"OMN","Oman","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20673,512,"OMN","Oman","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20674,512,"OMN","Oman","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20675,512,"OMN","Oman","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20676,512,"OMN","Oman","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20677,512,"OMN","Oman","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20678,512,"OMN","Oman","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20679,512,"OMN","Oman","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20680,512,"OMN","Oman","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/OMN/DMSP/omn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20681,516,"NAM","Namibia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20682,516,"NAM","Namibia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20683,516,"NAM","Namibia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20684,516,"NAM","Namibia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20685,516,"NAM","Namibia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20686,516,"NAM","Namibia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20687,516,"NAM","Namibia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20688,516,"NAM","Namibia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20689,516,"NAM","Namibia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20690,516,"NAM","Namibia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20691,516,"NAM","Namibia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20692,516,"NAM","Namibia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NAM/DMSP/nam_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20693,520,"NRU","Nauru","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20694,520,"NRU","Nauru","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20695,520,"NRU","Nauru","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20696,520,"NRU","Nauru","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20697,520,"NRU","Nauru","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20698,520,"NRU","Nauru","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20699,520,"NRU","Nauru","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20700,520,"NRU","Nauru","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20701,520,"NRU","Nauru","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20702,520,"NRU","Nauru","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20703,520,"NRU","Nauru","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20704,520,"NRU","Nauru","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NRU/DMSP/nru_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20705,524,"NPL","Nepal","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20706,524,"NPL","Nepal","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20707,524,"NPL","Nepal","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20708,524,"NPL","Nepal","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20709,524,"NPL","Nepal","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20710,524,"NPL","Nepal","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20711,524,"NPL","Nepal","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20712,524,"NPL","Nepal","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20713,524,"NPL","Nepal","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20714,524,"NPL","Nepal","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20715,524,"NPL","Nepal","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20716,524,"NPL","Nepal","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NPL/DMSP/npl_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20717,528,"NLD","Netherlands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20718,528,"NLD","Netherlands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20719,528,"NLD","Netherlands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20720,528,"NLD","Netherlands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20721,528,"NLD","Netherlands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20722,528,"NLD","Netherlands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20723,528,"NLD","Netherlands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20724,528,"NLD","Netherlands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20725,528,"NLD","Netherlands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20726,528,"NLD","Netherlands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20727,528,"NLD","Netherlands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20728,528,"NLD","Netherlands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NLD/DMSP/nld_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20729,531,"CUW","Curacao","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20730,531,"CUW","Curacao","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20731,531,"CUW","Curacao","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20732,531,"CUW","Curacao","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20733,531,"CUW","Curacao","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20734,531,"CUW","Curacao","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20735,531,"CUW","Curacao","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20736,531,"CUW","Curacao","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20737,531,"CUW","Curacao","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20738,531,"CUW","Curacao","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20739,531,"CUW","Curacao","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20740,531,"CUW","Curacao","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CUW/DMSP/cuw_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20741,533,"ABW","Aruba","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20742,533,"ABW","Aruba","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20743,533,"ABW","Aruba","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20744,533,"ABW","Aruba","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20745,533,"ABW","Aruba","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20746,533,"ABW","Aruba","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20747,533,"ABW","Aruba","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20748,533,"ABW","Aruba","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20749,533,"ABW","Aruba","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20750,533,"ABW","Aruba","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20751,533,"ABW","Aruba","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20752,533,"ABW","Aruba","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ABW/DMSP/abw_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20753,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20754,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20755,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20756,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20757,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20758,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20759,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20760,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20761,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20762,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20763,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20764,534,"SXM","Sint Maarten (Dutch part)","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SXM/DMSP/sxm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20765,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20766,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20767,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20768,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20769,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20770,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20771,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20772,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20773,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20774,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20775,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20776,535,"BES","Bonaire, Sint Eustatius and Saba","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BES/DMSP/bes_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20777,540,"NCL","New Caledonia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20778,540,"NCL","New Caledonia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20779,540,"NCL","New Caledonia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20780,540,"NCL","New Caledonia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20781,540,"NCL","New Caledonia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20782,540,"NCL","New Caledonia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20783,540,"NCL","New Caledonia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20784,540,"NCL","New Caledonia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20785,540,"NCL","New Caledonia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20786,540,"NCL","New Caledonia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20787,540,"NCL","New Caledonia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20788,540,"NCL","New Caledonia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NCL/DMSP/ncl_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20789,548,"VUT","Vanuatu","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20790,548,"VUT","Vanuatu","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20791,548,"VUT","Vanuatu","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20792,548,"VUT","Vanuatu","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20793,548,"VUT","Vanuatu","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20794,548,"VUT","Vanuatu","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20795,548,"VUT","Vanuatu","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20796,548,"VUT","Vanuatu","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20797,548,"VUT","Vanuatu","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20798,548,"VUT","Vanuatu","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20799,548,"VUT","Vanuatu","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20800,548,"VUT","Vanuatu","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/VUT/DMSP/vut_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20801,554,"NZL","New Zealand","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20802,554,"NZL","New Zealand","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20803,554,"NZL","New Zealand","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20804,554,"NZL","New Zealand","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20805,554,"NZL","New Zealand","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20806,554,"NZL","New Zealand","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20807,554,"NZL","New Zealand","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20808,554,"NZL","New Zealand","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20809,554,"NZL","New Zealand","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20810,554,"NZL","New Zealand","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20811,554,"NZL","New Zealand","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20812,554,"NZL","New Zealand","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NZL/DMSP/nzl_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20813,558,"NIC","Nicaragua","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20814,558,"NIC","Nicaragua","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20815,558,"NIC","Nicaragua","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20816,558,"NIC","Nicaragua","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20817,558,"NIC","Nicaragua","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20818,558,"NIC","Nicaragua","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20819,558,"NIC","Nicaragua","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20820,558,"NIC","Nicaragua","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20821,558,"NIC","Nicaragua","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20822,558,"NIC","Nicaragua","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20823,558,"NIC","Nicaragua","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20824,558,"NIC","Nicaragua","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NIC/DMSP/nic_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20825,562,"NER","Niger","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20826,562,"NER","Niger","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20827,562,"NER","Niger","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20828,562,"NER","Niger","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20829,562,"NER","Niger","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20830,562,"NER","Niger","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20831,562,"NER","Niger","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20832,562,"NER","Niger","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20833,562,"NER","Niger","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20834,562,"NER","Niger","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20835,562,"NER","Niger","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20836,562,"NER","Niger","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NER/DMSP/ner_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20837,566,"NGA","Nigeria","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20838,566,"NGA","Nigeria","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20839,566,"NGA","Nigeria","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20840,566,"NGA","Nigeria","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20841,566,"NGA","Nigeria","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20842,566,"NGA","Nigeria","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20843,566,"NGA","Nigeria","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20844,566,"NGA","Nigeria","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20845,566,"NGA","Nigeria","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20846,566,"NGA","Nigeria","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20847,566,"NGA","Nigeria","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20848,566,"NGA","Nigeria","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NGA/DMSP/nga_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20849,570,"NIU","Niue","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20850,570,"NIU","Niue","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20851,570,"NIU","Niue","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20852,570,"NIU","Niue","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20853,570,"NIU","Niue","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20854,570,"NIU","Niue","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20855,570,"NIU","Niue","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20856,570,"NIU","Niue","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20857,570,"NIU","Niue","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20858,570,"NIU","Niue","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20859,570,"NIU","Niue","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20860,570,"NIU","Niue","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NIU/DMSP/niu_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20861,574,"NFK","Norfolk Island","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20862,574,"NFK","Norfolk Island","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20863,574,"NFK","Norfolk Island","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20864,574,"NFK","Norfolk Island","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20865,574,"NFK","Norfolk Island","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20866,574,"NFK","Norfolk Island","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20867,574,"NFK","Norfolk Island","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20868,574,"NFK","Norfolk Island","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20869,574,"NFK","Norfolk Island","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20870,574,"NFK","Norfolk Island","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20871,574,"NFK","Norfolk Island","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20872,574,"NFK","Norfolk Island","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NFK/DMSP/nfk_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20873,578,"NOR","Norway","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20874,578,"NOR","Norway","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20875,578,"NOR","Norway","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20876,578,"NOR","Norway","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20877,578,"NOR","Norway","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20878,578,"NOR","Norway","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20879,578,"NOR","Norway","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20880,578,"NOR","Norway","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20881,578,"NOR","Norway","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20882,578,"NOR","Norway","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20883,578,"NOR","Norway","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20884,578,"NOR","Norway","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/NOR/DMSP/nor_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20885,580,"MNP","Northern Mariana Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20886,580,"MNP","Northern Mariana Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20887,580,"MNP","Northern Mariana Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20888,580,"MNP","Northern Mariana Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20889,580,"MNP","Northern Mariana Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20890,580,"MNP","Northern Mariana Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20891,580,"MNP","Northern Mariana Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20892,580,"MNP","Northern Mariana Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20893,580,"MNP","Northern Mariana Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20894,580,"MNP","Northern Mariana Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20895,580,"MNP","Northern Mariana Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20896,580,"MNP","Northern Mariana Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MNP/DMSP/mnp_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20897,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20898,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20899,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20900,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20901,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20902,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20903,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20904,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20905,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20906,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20907,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20908,581,"UMI","United States Minor Outlying Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/UMI/DMSP/umi_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20909,583,"FSM","Micronesia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20910,583,"FSM","Micronesia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20911,583,"FSM","Micronesia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20912,583,"FSM","Micronesia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20913,583,"FSM","Micronesia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20914,583,"FSM","Micronesia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20915,583,"FSM","Micronesia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20916,583,"FSM","Micronesia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20917,583,"FSM","Micronesia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20918,583,"FSM","Micronesia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20919,583,"FSM","Micronesia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20920,583,"FSM","Micronesia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/FSM/DMSP/fsm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20921,584,"MHL","Marshall Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20922,584,"MHL","Marshall Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20923,584,"MHL","Marshall Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20924,584,"MHL","Marshall Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20925,584,"MHL","Marshall Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20926,584,"MHL","Marshall Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20927,584,"MHL","Marshall Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20928,584,"MHL","Marshall Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20929,584,"MHL","Marshall Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20930,584,"MHL","Marshall Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20931,584,"MHL","Marshall Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20932,584,"MHL","Marshall Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MHL/DMSP/mhl_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20933,585,"PLW","Palau","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20934,585,"PLW","Palau","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20935,585,"PLW","Palau","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20936,585,"PLW","Palau","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20937,585,"PLW","Palau","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20938,585,"PLW","Palau","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20939,585,"PLW","Palau","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20940,585,"PLW","Palau","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20941,585,"PLW","Palau","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20942,585,"PLW","Palau","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20943,585,"PLW","Palau","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20944,585,"PLW","Palau","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PLW/DMSP/plw_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20945,586,"PAK","Pakistan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20946,586,"PAK","Pakistan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20947,586,"PAK","Pakistan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20948,586,"PAK","Pakistan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20949,586,"PAK","Pakistan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20950,586,"PAK","Pakistan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20951,586,"PAK","Pakistan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20952,586,"PAK","Pakistan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20953,586,"PAK","Pakistan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20954,586,"PAK","Pakistan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20955,586,"PAK","Pakistan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20956,586,"PAK","Pakistan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PAK/DMSP/pak_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20957,591,"PAN","Panama","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20958,591,"PAN","Panama","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20959,591,"PAN","Panama","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20960,591,"PAN","Panama","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20961,591,"PAN","Panama","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20962,591,"PAN","Panama","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20963,591,"PAN","Panama","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20964,591,"PAN","Panama","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20965,591,"PAN","Panama","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20966,591,"PAN","Panama","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20967,591,"PAN","Panama","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20968,591,"PAN","Panama","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PAN/DMSP/pan_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20969,598,"PNG","Papua New Guinea","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20970,598,"PNG","Papua New Guinea","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20971,598,"PNG","Papua New Guinea","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20972,598,"PNG","Papua New Guinea","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20973,598,"PNG","Papua New Guinea","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20974,598,"PNG","Papua New Guinea","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20975,598,"PNG","Papua New Guinea","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20976,598,"PNG","Papua New Guinea","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20977,598,"PNG","Papua New Guinea","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20978,598,"PNG","Papua New Guinea","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20979,598,"PNG","Papua New Guinea","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20980,598,"PNG","Papua New Guinea","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PNG/DMSP/png_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20981,600,"PRY","Paraguay","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20982,600,"PRY","Paraguay","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20983,600,"PRY","Paraguay","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20984,600,"PRY","Paraguay","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20985,600,"PRY","Paraguay","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20986,600,"PRY","Paraguay","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20987,600,"PRY","Paraguay","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
20988,600,"PRY","Paraguay","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
20989,600,"PRY","Paraguay","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
20990,600,"PRY","Paraguay","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
20991,600,"PRY","Paraguay","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
20992,600,"PRY","Paraguay","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PRY/DMSP/pry_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
20993,604,"PER","Peru","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
20994,604,"PER","Peru","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
20995,604,"PER","Peru","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
20996,604,"PER","Peru","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
20997,604,"PER","Peru","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
20998,604,"PER","Peru","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
20999,604,"PER","Peru","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21000,604,"PER","Peru","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21001,604,"PER","Peru","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21002,604,"PER","Peru","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21003,604,"PER","Peru","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21004,604,"PER","Peru","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PER/DMSP/per_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21005,608,"PHL","Philippines","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21006,608,"PHL","Philippines","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21007,608,"PHL","Philippines","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21008,608,"PHL","Philippines","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21009,608,"PHL","Philippines","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21010,608,"PHL","Philippines","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21011,608,"PHL","Philippines","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21012,608,"PHL","Philippines","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21013,608,"PHL","Philippines","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21014,608,"PHL","Philippines","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21015,608,"PHL","Philippines","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21016,608,"PHL","Philippines","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PHL/DMSP/phl_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21017,612,"PCN","Pitcairn Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21018,612,"PCN","Pitcairn Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21019,612,"PCN","Pitcairn Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21020,612,"PCN","Pitcairn Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21021,612,"PCN","Pitcairn Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21022,612,"PCN","Pitcairn Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21023,612,"PCN","Pitcairn Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21024,612,"PCN","Pitcairn Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21025,612,"PCN","Pitcairn Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21026,612,"PCN","Pitcairn Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21027,612,"PCN","Pitcairn Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21028,612,"PCN","Pitcairn Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PCN/DMSP/pcn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21029,616,"POL","Poland","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21030,616,"POL","Poland","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21031,616,"POL","Poland","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21032,616,"POL","Poland","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21033,616,"POL","Poland","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21034,616,"POL","Poland","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21035,616,"POL","Poland","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21036,616,"POL","Poland","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21037,616,"POL","Poland","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21038,616,"POL","Poland","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21039,616,"POL","Poland","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21040,616,"POL","Poland","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/POL/DMSP/pol_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21041,620,"PRT","Portugal","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21042,620,"PRT","Portugal","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21043,620,"PRT","Portugal","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21044,620,"PRT","Portugal","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21045,620,"PRT","Portugal","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21046,620,"PRT","Portugal","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21047,620,"PRT","Portugal","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21048,620,"PRT","Portugal","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21049,620,"PRT","Portugal","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21050,620,"PRT","Portugal","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21051,620,"PRT","Portugal","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21052,620,"PRT","Portugal","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PRT/DMSP/prt_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21053,624,"GNB","Guinea-Bissau","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21054,624,"GNB","Guinea-Bissau","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21055,624,"GNB","Guinea-Bissau","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21056,624,"GNB","Guinea-Bissau","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21057,624,"GNB","Guinea-Bissau","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21058,624,"GNB","Guinea-Bissau","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21059,624,"GNB","Guinea-Bissau","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21060,624,"GNB","Guinea-Bissau","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21061,624,"GNB","Guinea-Bissau","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21062,624,"GNB","Guinea-Bissau","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21063,624,"GNB","Guinea-Bissau","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21064,624,"GNB","Guinea-Bissau","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GNB/DMSP/gnb_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21065,626,"TLS","East Timor","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21066,626,"TLS","East Timor","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21067,626,"TLS","East Timor","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21068,626,"TLS","East Timor","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21069,626,"TLS","East Timor","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21070,626,"TLS","East Timor","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21071,626,"TLS","East Timor","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21072,626,"TLS","East Timor","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21073,626,"TLS","East Timor","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21074,626,"TLS","East Timor","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21075,626,"TLS","East Timor","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21076,626,"TLS","East Timor","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TLS/DMSP/tls_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21077,630,"PRI","Puerto Rico","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21078,630,"PRI","Puerto Rico","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21079,630,"PRI","Puerto Rico","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21080,630,"PRI","Puerto Rico","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21081,630,"PRI","Puerto Rico","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21082,630,"PRI","Puerto Rico","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21083,630,"PRI","Puerto Rico","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21084,630,"PRI","Puerto Rico","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21085,630,"PRI","Puerto Rico","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21086,630,"PRI","Puerto Rico","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21087,630,"PRI","Puerto Rico","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21088,630,"PRI","Puerto Rico","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/PRI/DMSP/pri_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21089,634,"QAT","Qatar","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21090,634,"QAT","Qatar","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21091,634,"QAT","Qatar","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21092,634,"QAT","Qatar","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21093,634,"QAT","Qatar","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21094,634,"QAT","Qatar","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21095,634,"QAT","Qatar","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21096,634,"QAT","Qatar","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21097,634,"QAT","Qatar","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21098,634,"QAT","Qatar","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21099,634,"QAT","Qatar","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21100,634,"QAT","Qatar","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/QAT/DMSP/qat_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21101,638,"REU","Reunion","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21102,638,"REU","Reunion","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21103,638,"REU","Reunion","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21104,638,"REU","Reunion","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21105,638,"REU","Reunion","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21106,638,"REU","Reunion","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21107,638,"REU","Reunion","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21108,638,"REU","Reunion","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21109,638,"REU","Reunion","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21110,638,"REU","Reunion","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21111,638,"REU","Reunion","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21112,638,"REU","Reunion","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/REU/DMSP/reu_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21113,642,"ROU","Romania","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21114,642,"ROU","Romania","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21115,642,"ROU","Romania","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21116,642,"ROU","Romania","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21117,642,"ROU","Romania","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21118,642,"ROU","Romania","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21119,642,"ROU","Romania","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21120,642,"ROU","Romania","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21121,642,"ROU","Romania","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21122,642,"ROU","Romania","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21123,642,"ROU","Romania","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21124,642,"ROU","Romania","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ROU/DMSP/rou_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21125,646,"RWA","Rwanda","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21126,646,"RWA","Rwanda","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21127,646,"RWA","Rwanda","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21128,646,"RWA","Rwanda","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21129,646,"RWA","Rwanda","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21130,646,"RWA","Rwanda","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21131,646,"RWA","Rwanda","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21132,646,"RWA","Rwanda","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21133,646,"RWA","Rwanda","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21134,646,"RWA","Rwanda","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21135,646,"RWA","Rwanda","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21136,646,"RWA","Rwanda","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/RWA/DMSP/rwa_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21137,652,"BLM","Saint Barthelemy","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21138,652,"BLM","Saint Barthelemy","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21139,652,"BLM","Saint Barthelemy","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21140,652,"BLM","Saint Barthelemy","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21141,652,"BLM","Saint Barthelemy","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21142,652,"BLM","Saint Barthelemy","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21143,652,"BLM","Saint Barthelemy","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21144,652,"BLM","Saint Barthelemy","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21145,652,"BLM","Saint Barthelemy","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21146,652,"BLM","Saint Barthelemy","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21147,652,"BLM","Saint Barthelemy","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21148,652,"BLM","Saint Barthelemy","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BLM/DMSP/blm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21149,654,"SHN","Saint Helena","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21150,654,"SHN","Saint Helena","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21151,654,"SHN","Saint Helena","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21152,654,"SHN","Saint Helena","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21153,654,"SHN","Saint Helena","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21154,654,"SHN","Saint Helena","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21155,654,"SHN","Saint Helena","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21156,654,"SHN","Saint Helena","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21157,654,"SHN","Saint Helena","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21158,654,"SHN","Saint Helena","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21159,654,"SHN","Saint Helena","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21160,654,"SHN","Saint Helena","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SHN/DMSP/shn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21161,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21162,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21163,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21164,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21165,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21166,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21167,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21168,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21169,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21170,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21171,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21172,659,"KNA","Saint Kitts and Nevis","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/KNA/DMSP/kna_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21173,660,"AIA","Anguilla","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21174,660,"AIA","Anguilla","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21175,660,"AIA","Anguilla","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21176,660,"AIA","Anguilla","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21177,660,"AIA","Anguilla","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21178,660,"AIA","Anguilla","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21179,660,"AIA","Anguilla","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21180,660,"AIA","Anguilla","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21181,660,"AIA","Anguilla","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21182,660,"AIA","Anguilla","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21183,660,"AIA","Anguilla","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21184,660,"AIA","Anguilla","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/AIA/DMSP/aia_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21185,662,"LCA","Saint Lucia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21186,662,"LCA","Saint Lucia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21187,662,"LCA","Saint Lucia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21188,662,"LCA","Saint Lucia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21189,662,"LCA","Saint Lucia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21190,662,"LCA","Saint Lucia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21191,662,"LCA","Saint Lucia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21192,662,"LCA","Saint Lucia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21193,662,"LCA","Saint Lucia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21194,662,"LCA","Saint Lucia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21195,662,"LCA","Saint Lucia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21196,662,"LCA","Saint Lucia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/LCA/DMSP/lca_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21197,663,"MAF","Saint Martin (French part)","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21198,663,"MAF","Saint Martin (French part)","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21199,663,"MAF","Saint Martin (French part)","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21200,663,"MAF","Saint Martin (French part)","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21201,663,"MAF","Saint Martin (French part)","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21202,663,"MAF","Saint Martin (French part)","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21203,663,"MAF","Saint Martin (French part)","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21204,663,"MAF","Saint Martin (French part)","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21205,663,"MAF","Saint Martin (French part)","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21206,663,"MAF","Saint Martin (French part)","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21207,663,"MAF","Saint Martin (French part)","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21208,663,"MAF","Saint Martin (French part)","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MAF/DMSP/maf_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21209,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21210,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21211,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21212,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21213,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21214,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21215,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21216,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21217,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21218,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21219,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21220,666,"SPM","Saint Pierre and Miquelon","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SPM/DMSP/spm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21221,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21222,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21223,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21224,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21225,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21226,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21227,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21228,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21229,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21230,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21231,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21232,670,"VCT","Saint Vincent and the Grenadines","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/VCT/DMSP/vct_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21233,674,"SMR","San Marino","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21234,674,"SMR","San Marino","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21235,674,"SMR","San Marino","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21236,674,"SMR","San Marino","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21237,674,"SMR","San Marino","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21238,674,"SMR","San Marino","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21239,674,"SMR","San Marino","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21240,674,"SMR","San Marino","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21241,674,"SMR","San Marino","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21242,674,"SMR","San Marino","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21243,674,"SMR","San Marino","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21244,674,"SMR","San Marino","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SMR/DMSP/smr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21245,678,"STP","Sao Tome and Principe","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21246,678,"STP","Sao Tome and Principe","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21247,678,"STP","Sao Tome and Principe","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21248,678,"STP","Sao Tome and Principe","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21249,678,"STP","Sao Tome and Principe","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21250,678,"STP","Sao Tome and Principe","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21251,678,"STP","Sao Tome and Principe","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21252,678,"STP","Sao Tome and Principe","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21253,678,"STP","Sao Tome and Principe","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21254,678,"STP","Sao Tome and Principe","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21255,678,"STP","Sao Tome and Principe","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21256,678,"STP","Sao Tome and Principe","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/STP/DMSP/stp_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21257,682,"SAU","Saudi Arabia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21258,682,"SAU","Saudi Arabia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21259,682,"SAU","Saudi Arabia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21260,682,"SAU","Saudi Arabia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21261,682,"SAU","Saudi Arabia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21262,682,"SAU","Saudi Arabia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21263,682,"SAU","Saudi Arabia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21264,682,"SAU","Saudi Arabia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21265,682,"SAU","Saudi Arabia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21266,682,"SAU","Saudi Arabia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21267,682,"SAU","Saudi Arabia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21268,682,"SAU","Saudi Arabia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SAU/DMSP/sau_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21269,686,"SEN","Senegal","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21270,686,"SEN","Senegal","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21271,686,"SEN","Senegal","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21272,686,"SEN","Senegal","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21273,686,"SEN","Senegal","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21274,686,"SEN","Senegal","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21275,686,"SEN","Senegal","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21276,686,"SEN","Senegal","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21277,686,"SEN","Senegal","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21278,686,"SEN","Senegal","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21279,686,"SEN","Senegal","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21280,686,"SEN","Senegal","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SEN/DMSP/sen_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21281,688,"SRB","Serbia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21282,688,"SRB","Serbia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21283,688,"SRB","Serbia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21284,688,"SRB","Serbia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21285,688,"SRB","Serbia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21286,688,"SRB","Serbia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21287,688,"SRB","Serbia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21288,688,"SRB","Serbia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21289,688,"SRB","Serbia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21290,688,"SRB","Serbia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21291,688,"SRB","Serbia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21292,688,"SRB","Serbia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SRB/DMSP/srb_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21293,690,"SYC","Seychelles","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21294,690,"SYC","Seychelles","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21295,690,"SYC","Seychelles","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21296,690,"SYC","Seychelles","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21297,690,"SYC","Seychelles","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21298,690,"SYC","Seychelles","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21299,690,"SYC","Seychelles","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21300,690,"SYC","Seychelles","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21301,690,"SYC","Seychelles","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21302,690,"SYC","Seychelles","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21303,690,"SYC","Seychelles","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21304,690,"SYC","Seychelles","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SYC/DMSP/syc_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21305,694,"SLE","Sierra Leone","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21306,694,"SLE","Sierra Leone","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21307,694,"SLE","Sierra Leone","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21308,694,"SLE","Sierra Leone","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21309,694,"SLE","Sierra Leone","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21310,694,"SLE","Sierra Leone","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21311,694,"SLE","Sierra Leone","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21312,694,"SLE","Sierra Leone","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21313,694,"SLE","Sierra Leone","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21314,694,"SLE","Sierra Leone","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21315,694,"SLE","Sierra Leone","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21316,694,"SLE","Sierra Leone","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SLE/DMSP/sle_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21317,702,"SGP","Singapore","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21318,702,"SGP","Singapore","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21319,702,"SGP","Singapore","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21320,702,"SGP","Singapore","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21321,702,"SGP","Singapore","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21322,702,"SGP","Singapore","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21323,702,"SGP","Singapore","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21324,702,"SGP","Singapore","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21325,702,"SGP","Singapore","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21326,702,"SGP","Singapore","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21327,702,"SGP","Singapore","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21328,702,"SGP","Singapore","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SGP/DMSP/sgp_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21329,703,"SVK","Slovakia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21330,703,"SVK","Slovakia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21331,703,"SVK","Slovakia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21332,703,"SVK","Slovakia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21333,703,"SVK","Slovakia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21334,703,"SVK","Slovakia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21335,703,"SVK","Slovakia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21336,703,"SVK","Slovakia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21337,703,"SVK","Slovakia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21338,703,"SVK","Slovakia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21339,703,"SVK","Slovakia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21340,703,"SVK","Slovakia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SVK/DMSP/svk_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21341,704,"VNM","Vietnam","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21342,704,"VNM","Vietnam","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21343,704,"VNM","Vietnam","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21344,704,"VNM","Vietnam","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21345,704,"VNM","Vietnam","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21346,704,"VNM","Vietnam","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21347,704,"VNM","Vietnam","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21348,704,"VNM","Vietnam","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21349,704,"VNM","Vietnam","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21350,704,"VNM","Vietnam","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21351,704,"VNM","Vietnam","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21352,704,"VNM","Vietnam","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/VNM/DMSP/vnm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21353,705,"SVN","Slovenia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21354,705,"SVN","Slovenia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21355,705,"SVN","Slovenia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21356,705,"SVN","Slovenia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21357,705,"SVN","Slovenia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21358,705,"SVN","Slovenia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21359,705,"SVN","Slovenia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21360,705,"SVN","Slovenia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21361,705,"SVN","Slovenia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21362,705,"SVN","Slovenia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21363,705,"SVN","Slovenia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21364,705,"SVN","Slovenia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SVN/DMSP/svn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21365,706,"SOM","Somalia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21366,706,"SOM","Somalia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21367,706,"SOM","Somalia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21368,706,"SOM","Somalia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21369,706,"SOM","Somalia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21370,706,"SOM","Somalia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21371,706,"SOM","Somalia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21372,706,"SOM","Somalia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21373,706,"SOM","Somalia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21374,706,"SOM","Somalia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21375,706,"SOM","Somalia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21376,706,"SOM","Somalia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SOM/DMSP/som_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21377,710,"ZAF","South Africa","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21378,710,"ZAF","South Africa","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21379,710,"ZAF","South Africa","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21380,710,"ZAF","South Africa","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21381,710,"ZAF","South Africa","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21382,710,"ZAF","South Africa","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21383,710,"ZAF","South Africa","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21384,710,"ZAF","South Africa","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21385,710,"ZAF","South Africa","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21386,710,"ZAF","South Africa","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21387,710,"ZAF","South Africa","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21388,710,"ZAF","South Africa","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/DMSP/zaf_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21389,716,"ZWE","Zimbabwe","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21390,716,"ZWE","Zimbabwe","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21391,716,"ZWE","Zimbabwe","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21392,716,"ZWE","Zimbabwe","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21393,716,"ZWE","Zimbabwe","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21394,716,"ZWE","Zimbabwe","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21395,716,"ZWE","Zimbabwe","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21396,716,"ZWE","Zimbabwe","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21397,716,"ZWE","Zimbabwe","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21398,716,"ZWE","Zimbabwe","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21399,716,"ZWE","Zimbabwe","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21400,716,"ZWE","Zimbabwe","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/DMSP/zwe_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21401,724,"ESP","Spain","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21402,724,"ESP","Spain","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21403,724,"ESP","Spain","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21404,724,"ESP","Spain","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21405,724,"ESP","Spain","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21406,724,"ESP","Spain","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21407,724,"ESP","Spain","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21408,724,"ESP","Spain","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21409,724,"ESP","Spain","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21410,724,"ESP","Spain","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21411,724,"ESP","Spain","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21412,724,"ESP","Spain","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ESP/DMSP/esp_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21413,728,"SSD","South Sudan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21414,728,"SSD","South Sudan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21415,728,"SSD","South Sudan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21416,728,"SSD","South Sudan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21417,728,"SSD","South Sudan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21418,728,"SSD","South Sudan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21419,728,"SSD","South Sudan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21420,728,"SSD","South Sudan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21421,728,"SSD","South Sudan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21422,728,"SSD","South Sudan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21423,728,"SSD","South Sudan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21424,728,"SSD","South Sudan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SSD/DMSP/ssd_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21425,729,"SDN","Sudan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21426,729,"SDN","Sudan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21427,729,"SDN","Sudan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21428,729,"SDN","Sudan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21429,729,"SDN","Sudan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21430,729,"SDN","Sudan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21431,729,"SDN","Sudan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21432,729,"SDN","Sudan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21433,729,"SDN","Sudan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21434,729,"SDN","Sudan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21435,729,"SDN","Sudan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21436,729,"SDN","Sudan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SDN/DMSP/sdn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21437,732,"ESH","Western Sahara","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21438,732,"ESH","Western Sahara","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21439,732,"ESH","Western Sahara","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21440,732,"ESH","Western Sahara","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21441,732,"ESH","Western Sahara","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21442,732,"ESH","Western Sahara","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21443,732,"ESH","Western Sahara","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21444,732,"ESH","Western Sahara","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21445,732,"ESH","Western Sahara","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21446,732,"ESH","Western Sahara","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21447,732,"ESH","Western Sahara","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21448,732,"ESH","Western Sahara","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ESH/DMSP/esh_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21449,740,"SUR","Suriname","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21450,740,"SUR","Suriname","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21451,740,"SUR","Suriname","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21452,740,"SUR","Suriname","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21453,740,"SUR","Suriname","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21454,740,"SUR","Suriname","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21455,740,"SUR","Suriname","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21456,740,"SUR","Suriname","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21457,740,"SUR","Suriname","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21458,740,"SUR","Suriname","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21459,740,"SUR","Suriname","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21460,740,"SUR","Suriname","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SUR/DMSP/sur_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21461,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21462,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21463,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21464,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21465,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21466,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21467,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21468,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21469,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21470,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21471,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21472,744,"SJM","Svalbard and Jan Mayen Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SJM/DMSP/sjm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21473,748,"SWZ","Swaziland","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21474,748,"SWZ","Swaziland","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21475,748,"SWZ","Swaziland","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21476,748,"SWZ","Swaziland","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21477,748,"SWZ","Swaziland","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21478,748,"SWZ","Swaziland","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21479,748,"SWZ","Swaziland","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21480,748,"SWZ","Swaziland","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21481,748,"SWZ","Swaziland","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21482,748,"SWZ","Swaziland","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21483,748,"SWZ","Swaziland","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21484,748,"SWZ","Swaziland","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/DMSP/swz_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21485,752,"SWE","Sweden","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21486,752,"SWE","Sweden","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21487,752,"SWE","Sweden","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21488,752,"SWE","Sweden","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21489,752,"SWE","Sweden","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21490,752,"SWE","Sweden","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21491,752,"SWE","Sweden","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21492,752,"SWE","Sweden","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21493,752,"SWE","Sweden","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21494,752,"SWE","Sweden","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21495,752,"SWE","Sweden","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21496,752,"SWE","Sweden","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SWE/DMSP/swe_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21497,756,"CHE","Switzerland","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21498,756,"CHE","Switzerland","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21499,756,"CHE","Switzerland","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21500,756,"CHE","Switzerland","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21501,756,"CHE","Switzerland","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21502,756,"CHE","Switzerland","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21503,756,"CHE","Switzerland","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21504,756,"CHE","Switzerland","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21505,756,"CHE","Switzerland","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21506,756,"CHE","Switzerland","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21507,756,"CHE","Switzerland","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21508,756,"CHE","Switzerland","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/CHE/DMSP/che_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21509,760,"SYR","Syria","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21510,760,"SYR","Syria","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21511,760,"SYR","Syria","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21512,760,"SYR","Syria","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21513,760,"SYR","Syria","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21514,760,"SYR","Syria","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21515,760,"SYR","Syria","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21516,760,"SYR","Syria","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21517,760,"SYR","Syria","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21518,760,"SYR","Syria","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21519,760,"SYR","Syria","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21520,760,"SYR","Syria","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SYR/DMSP/syr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21521,762,"TJK","Tajikistan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21522,762,"TJK","Tajikistan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21523,762,"TJK","Tajikistan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21524,762,"TJK","Tajikistan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21525,762,"TJK","Tajikistan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21526,762,"TJK","Tajikistan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21527,762,"TJK","Tajikistan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21528,762,"TJK","Tajikistan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21529,762,"TJK","Tajikistan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21530,762,"TJK","Tajikistan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21531,762,"TJK","Tajikistan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21532,762,"TJK","Tajikistan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TJK/DMSP/tjk_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21533,764,"THA","Thailand","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21534,764,"THA","Thailand","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21535,764,"THA","Thailand","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21536,764,"THA","Thailand","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21537,764,"THA","Thailand","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21538,764,"THA","Thailand","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21539,764,"THA","Thailand","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21540,764,"THA","Thailand","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21541,764,"THA","Thailand","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21542,764,"THA","Thailand","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21543,764,"THA","Thailand","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21544,764,"THA","Thailand","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/THA/DMSP/tha_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21545,768,"TGO","Togo","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21546,768,"TGO","Togo","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21547,768,"TGO","Togo","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21548,768,"TGO","Togo","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21549,768,"TGO","Togo","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21550,768,"TGO","Togo","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21551,768,"TGO","Togo","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21552,768,"TGO","Togo","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21553,768,"TGO","Togo","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21554,768,"TGO","Togo","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21555,768,"TGO","Togo","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21556,768,"TGO","Togo","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TGO/DMSP/tgo_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21557,772,"TKL","Tokelau","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21558,772,"TKL","Tokelau","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21559,772,"TKL","Tokelau","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21560,772,"TKL","Tokelau","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21561,772,"TKL","Tokelau","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21562,772,"TKL","Tokelau","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21563,772,"TKL","Tokelau","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21564,772,"TKL","Tokelau","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21565,772,"TKL","Tokelau","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21566,772,"TKL","Tokelau","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21567,772,"TKL","Tokelau","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21568,772,"TKL","Tokelau","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TKL/DMSP/tkl_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21569,776,"TON","Tonga","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21570,776,"TON","Tonga","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21571,776,"TON","Tonga","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21572,776,"TON","Tonga","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21573,776,"TON","Tonga","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21574,776,"TON","Tonga","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21575,776,"TON","Tonga","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21576,776,"TON","Tonga","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21577,776,"TON","Tonga","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21578,776,"TON","Tonga","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21579,776,"TON","Tonga","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21580,776,"TON","Tonga","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TON/DMSP/ton_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21581,780,"TTO","Trinidad and Tobago","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21582,780,"TTO","Trinidad and Tobago","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21583,780,"TTO","Trinidad and Tobago","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21584,780,"TTO","Trinidad and Tobago","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21585,780,"TTO","Trinidad and Tobago","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21586,780,"TTO","Trinidad and Tobago","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21587,780,"TTO","Trinidad and Tobago","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21588,780,"TTO","Trinidad and Tobago","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21589,780,"TTO","Trinidad and Tobago","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21590,780,"TTO","Trinidad and Tobago","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21591,780,"TTO","Trinidad and Tobago","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21592,780,"TTO","Trinidad and Tobago","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TTO/DMSP/tto_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21593,784,"ARE","United Arab Emirates","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21594,784,"ARE","United Arab Emirates","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21595,784,"ARE","United Arab Emirates","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21596,784,"ARE","United Arab Emirates","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21597,784,"ARE","United Arab Emirates","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21598,784,"ARE","United Arab Emirates","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21599,784,"ARE","United Arab Emirates","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21600,784,"ARE","United Arab Emirates","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21601,784,"ARE","United Arab Emirates","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21602,784,"ARE","United Arab Emirates","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21603,784,"ARE","United Arab Emirates","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21604,784,"ARE","United Arab Emirates","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ARE/DMSP/are_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21605,788,"TUN","Tunisia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21606,788,"TUN","Tunisia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21607,788,"TUN","Tunisia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21608,788,"TUN","Tunisia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21609,788,"TUN","Tunisia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21610,788,"TUN","Tunisia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21611,788,"TUN","Tunisia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21612,788,"TUN","Tunisia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21613,788,"TUN","Tunisia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21614,788,"TUN","Tunisia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21615,788,"TUN","Tunisia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21616,788,"TUN","Tunisia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TUN/DMSP/tun_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21617,792,"TUR","Turkey","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21618,792,"TUR","Turkey","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21619,792,"TUR","Turkey","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21620,792,"TUR","Turkey","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21621,792,"TUR","Turkey","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21622,792,"TUR","Turkey","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21623,792,"TUR","Turkey","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21624,792,"TUR","Turkey","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21625,792,"TUR","Turkey","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21626,792,"TUR","Turkey","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21627,792,"TUR","Turkey","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21628,792,"TUR","Turkey","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TUR/DMSP/tur_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21629,795,"TKM","Turkmenistan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21630,795,"TKM","Turkmenistan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21631,795,"TKM","Turkmenistan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21632,795,"TKM","Turkmenistan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21633,795,"TKM","Turkmenistan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21634,795,"TKM","Turkmenistan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21635,795,"TKM","Turkmenistan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21636,795,"TKM","Turkmenistan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21637,795,"TKM","Turkmenistan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21638,795,"TKM","Turkmenistan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21639,795,"TKM","Turkmenistan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21640,795,"TKM","Turkmenistan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TKM/DMSP/tkm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21641,796,"TCA","Turks and Caicos Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21642,796,"TCA","Turks and Caicos Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21643,796,"TCA","Turks and Caicos Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21644,796,"TCA","Turks and Caicos Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21645,796,"TCA","Turks and Caicos Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21646,796,"TCA","Turks and Caicos Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21647,796,"TCA","Turks and Caicos Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21648,796,"TCA","Turks and Caicos Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21649,796,"TCA","Turks and Caicos Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21650,796,"TCA","Turks and Caicos Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21651,796,"TCA","Turks and Caicos Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21652,796,"TCA","Turks and Caicos Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TCA/DMSP/tca_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21653,798,"TUV","Tuvalu","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21654,798,"TUV","Tuvalu","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21655,798,"TUV","Tuvalu","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21656,798,"TUV","Tuvalu","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21657,798,"TUV","Tuvalu","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21658,798,"TUV","Tuvalu","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21659,798,"TUV","Tuvalu","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21660,798,"TUV","Tuvalu","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21661,798,"TUV","Tuvalu","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21662,798,"TUV","Tuvalu","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21663,798,"TUV","Tuvalu","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21664,798,"TUV","Tuvalu","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TUV/DMSP/tuv_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21665,800,"UGA","Uganda","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21666,800,"UGA","Uganda","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21667,800,"UGA","Uganda","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21668,800,"UGA","Uganda","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21669,800,"UGA","Uganda","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21670,800,"UGA","Uganda","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21671,800,"UGA","Uganda","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21672,800,"UGA","Uganda","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21673,800,"UGA","Uganda","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21674,800,"UGA","Uganda","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21675,800,"UGA","Uganda","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21676,800,"UGA","Uganda","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/UGA/DMSP/uga_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21677,804,"UKR","Ukraine","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21678,804,"UKR","Ukraine","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21679,804,"UKR","Ukraine","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21680,804,"UKR","Ukraine","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21681,804,"UKR","Ukraine","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21682,804,"UKR","Ukraine","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21683,804,"UKR","Ukraine","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21684,804,"UKR","Ukraine","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21685,804,"UKR","Ukraine","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21686,804,"UKR","Ukraine","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21687,804,"UKR","Ukraine","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21688,804,"UKR","Ukraine","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/UKR/DMSP/ukr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21689,807,"MKD","Macedonia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21690,807,"MKD","Macedonia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21691,807,"MKD","Macedonia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21692,807,"MKD","Macedonia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21693,807,"MKD","Macedonia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21694,807,"MKD","Macedonia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21695,807,"MKD","Macedonia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21696,807,"MKD","Macedonia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21697,807,"MKD","Macedonia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21698,807,"MKD","Macedonia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21699,807,"MKD","Macedonia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21700,807,"MKD","Macedonia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/MKD/DMSP/mkd_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21701,818,"EGY","Egypt","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21702,818,"EGY","Egypt","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21703,818,"EGY","Egypt","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21704,818,"EGY","Egypt","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21705,818,"EGY","Egypt","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21706,818,"EGY","Egypt","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21707,818,"EGY","Egypt","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21708,818,"EGY","Egypt","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21709,818,"EGY","Egypt","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21710,818,"EGY","Egypt","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21711,818,"EGY","Egypt","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21712,818,"EGY","Egypt","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/EGY/DMSP/egy_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21713,826,"GBR","United Kingdom","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21714,826,"GBR","United Kingdom","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21715,826,"GBR","United Kingdom","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21716,826,"GBR","United Kingdom","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21717,826,"GBR","United Kingdom","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21718,826,"GBR","United Kingdom","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21719,826,"GBR","United Kingdom","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21720,826,"GBR","United Kingdom","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21721,826,"GBR","United Kingdom","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21722,826,"GBR","United Kingdom","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21723,826,"GBR","United Kingdom","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21724,826,"GBR","United Kingdom","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GBR/DMSP/gbr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21725,831,"GGY","Guernsey","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21726,831,"GGY","Guernsey","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21727,831,"GGY","Guernsey","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21728,831,"GGY","Guernsey","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21729,831,"GGY","Guernsey","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21730,831,"GGY","Guernsey","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21731,831,"GGY","Guernsey","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21732,831,"GGY","Guernsey","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21733,831,"GGY","Guernsey","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21734,831,"GGY","Guernsey","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21735,831,"GGY","Guernsey","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21736,831,"GGY","Guernsey","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/GGY/DMSP/ggy_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21737,832,"JEY","Jersey","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21738,832,"JEY","Jersey","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21739,832,"JEY","Jersey","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21740,832,"JEY","Jersey","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21741,832,"JEY","Jersey","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21742,832,"JEY","Jersey","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21743,832,"JEY","Jersey","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21744,832,"JEY","Jersey","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21745,832,"JEY","Jersey","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21746,832,"JEY","Jersey","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21747,832,"JEY","Jersey","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21748,832,"JEY","Jersey","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/JEY/DMSP/jey_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21749,833,"IMN","Isle of Man","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21750,833,"IMN","Isle of Man","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21751,833,"IMN","Isle of Man","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21752,833,"IMN","Isle of Man","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21753,833,"IMN","Isle of Man","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21754,833,"IMN","Isle of Man","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21755,833,"IMN","Isle of Man","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21756,833,"IMN","Isle of Man","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21757,833,"IMN","Isle of Man","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21758,833,"IMN","Isle of Man","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21759,833,"IMN","Isle of Man","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21760,833,"IMN","Isle of Man","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/IMN/DMSP/imn_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21761,834,"TZA","Tanzania","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21762,834,"TZA","Tanzania","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21763,834,"TZA","Tanzania","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21764,834,"TZA","Tanzania","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21765,834,"TZA","Tanzania","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21766,834,"TZA","Tanzania","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21767,834,"TZA","Tanzania","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21768,834,"TZA","Tanzania","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21769,834,"TZA","Tanzania","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21770,834,"TZA","Tanzania","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21771,834,"TZA","Tanzania","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21772,834,"TZA","Tanzania","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/TZA/DMSP/tza_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21773,854,"BFA","Burkina Faso","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21774,854,"BFA","Burkina Faso","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21775,854,"BFA","Burkina Faso","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21776,854,"BFA","Burkina Faso","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21777,854,"BFA","Burkina Faso","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21778,854,"BFA","Burkina Faso","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21779,854,"BFA","Burkina Faso","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21780,854,"BFA","Burkina Faso","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21781,854,"BFA","Burkina Faso","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21782,854,"BFA","Burkina Faso","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21783,854,"BFA","Burkina Faso","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21784,854,"BFA","Burkina Faso","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/BFA/DMSP/bfa_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21785,858,"URY","Uruguay","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21786,858,"URY","Uruguay","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21787,858,"URY","Uruguay","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21788,858,"URY","Uruguay","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21789,858,"URY","Uruguay","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21790,858,"URY","Uruguay","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21791,858,"URY","Uruguay","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21792,858,"URY","Uruguay","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21793,858,"URY","Uruguay","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21794,858,"URY","Uruguay","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21795,858,"URY","Uruguay","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21796,858,"URY","Uruguay","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/URY/DMSP/ury_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21797,860,"UZB","Uzbekistan","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21798,860,"UZB","Uzbekistan","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21799,860,"UZB","Uzbekistan","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21800,860,"UZB","Uzbekistan","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21801,860,"UZB","Uzbekistan","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21802,860,"UZB","Uzbekistan","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21803,860,"UZB","Uzbekistan","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21804,860,"UZB","Uzbekistan","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21805,860,"UZB","Uzbekistan","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21806,860,"UZB","Uzbekistan","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21807,860,"UZB","Uzbekistan","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21808,860,"UZB","Uzbekistan","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/UZB/DMSP/uzb_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21809,862,"VEN","Venezuela","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21810,862,"VEN","Venezuela","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21811,862,"VEN","Venezuela","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21812,862,"VEN","Venezuela","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21813,862,"VEN","Venezuela","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21814,862,"VEN","Venezuela","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21815,862,"VEN","Venezuela","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21816,862,"VEN","Venezuela","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21817,862,"VEN","Venezuela","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21818,862,"VEN","Venezuela","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21819,862,"VEN","Venezuela","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21820,862,"VEN","Venezuela","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/VEN/DMSP/ven_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21821,876,"WLF","Wallis and Futuna","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21822,876,"WLF","Wallis and Futuna","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21823,876,"WLF","Wallis and Futuna","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21824,876,"WLF","Wallis and Futuna","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21825,876,"WLF","Wallis and Futuna","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21826,876,"WLF","Wallis and Futuna","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21827,876,"WLF","Wallis and Futuna","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21828,876,"WLF","Wallis and Futuna","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21829,876,"WLF","Wallis and Futuna","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21830,876,"WLF","Wallis and Futuna","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21831,876,"WLF","Wallis and Futuna","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21832,876,"WLF","Wallis and Futuna","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/WLF/DMSP/wlf_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21833,882,"WSM","Samoa","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21834,882,"WSM","Samoa","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21835,882,"WSM","Samoa","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21836,882,"WSM","Samoa","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21837,882,"WSM","Samoa","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21838,882,"WSM","Samoa","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21839,882,"WSM","Samoa","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21840,882,"WSM","Samoa","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21841,882,"WSM","Samoa","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21842,882,"WSM","Samoa","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21843,882,"WSM","Samoa","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21844,882,"WSM","Samoa","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/WSM/DMSP/wsm_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21845,887,"YEM","Yemen","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21846,887,"YEM","Yemen","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21847,887,"YEM","Yemen","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21848,887,"YEM","Yemen","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21849,887,"YEM","Yemen","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21850,887,"YEM","Yemen","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21851,887,"YEM","Yemen","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21852,887,"YEM","Yemen","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21853,887,"YEM","Yemen","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21854,887,"YEM","Yemen","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21855,887,"YEM","Yemen","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21856,887,"YEM","Yemen","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/YEM/DMSP/yem_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21857,894,"ZMB","Zambia","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21858,894,"ZMB","Zambia","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21859,894,"ZMB","Zambia","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21860,894,"ZMB","Zambia","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21861,894,"ZMB","Zambia","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21862,894,"ZMB","Zambia","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21863,894,"ZMB","Zambia","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21864,894,"ZMB","Zambia","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21865,894,"ZMB","Zambia","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21866,894,"ZMB","Zambia","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21867,894,"ZMB","Zambia","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21868,894,"ZMB","Zambia","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/DMSP/zmb_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21869,900,"KOS","Kosovo","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21870,900,"KOS","Kosovo","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21871,900,"KOS","Kosovo","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21872,900,"KOS","Kosovo","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21873,900,"KOS","Kosovo","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21874,900,"KOS","Kosovo","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21875,900,"KOS","Kosovo","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21876,900,"KOS","Kosovo","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21877,900,"KOS","Kosovo","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21878,900,"KOS","Kosovo","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21879,900,"KOS","Kosovo","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21880,900,"KOS","Kosovo","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/KOS/DMSP/kos_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21881,901,"SPR","Spratly Islands","dmsp_100m_2000","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2000.tif","DMSP-OLS night-time lights 2000"
21882,901,"SPR","Spratly Islands","dmsp_100m_2001","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2001.tif","DMSP-OLS night-time lights 2001"
21883,901,"SPR","Spratly Islands","dmsp_100m_2002","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2002.tif","DMSP-OLS night-time lights 2002"
21884,901,"SPR","Spratly Islands","dmsp_100m_2003","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2003.tif","DMSP-OLS night-time lights 2003"
21885,901,"SPR","Spratly Islands","dmsp_100m_2004","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2004.tif","DMSP-OLS night-time lights 2004"
21886,901,"SPR","Spratly Islands","dmsp_100m_2005","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2005.tif","DMSP-OLS night-time lights 2005"
21887,901,"SPR","Spratly Islands","dmsp_100m_2006","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2006.tif","DMSP-OLS night-time lights 2006"
21888,901,"SPR","Spratly Islands","dmsp_100m_2007","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2007.tif","DMSP-OLS night-time lights 2007"
21889,901,"SPR","Spratly Islands","dmsp_100m_2008","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2008.tif","DMSP-OLS night-time lights 2008"
21890,901,"SPR","Spratly Islands","dmsp_100m_2009","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2009.tif","DMSP-OLS night-time lights 2009"
21891,901,"SPR","Spratly Islands","dmsp_100m_2010","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2010.tif","DMSP-OLS night-time lights 2010"
21892,901,"SPR","Spratly Islands","dmsp_100m_2011","GIS/Covariates/Global_2000_2020/SPR/DMSP/spr_dmsp_100m_2011.tif","DMSP-OLS night-time lights 2011"
21893,643,"RUS","Russia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2000/rus_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
21894,643,"RUS","Russia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2000/rus_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
21895,643,"RUS","Russia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2000/rus_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
21896,643,"RUS","Russia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2000/rus_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
21897,643,"RUS","Russia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2000/rus_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
21898,643,"RUS","Russia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2000/rus_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
21899,643,"RUS","Russia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2000/rus_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
21900,643,"RUS","Russia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2000/rus_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
21901,643,"RUS","Russia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2001/rus_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
21902,643,"RUS","Russia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2001/rus_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
21903,643,"RUS","Russia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2001/rus_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
21904,643,"RUS","Russia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2001/rus_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
21905,643,"RUS","Russia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2001/rus_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
21906,643,"RUS","Russia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2001/rus_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
21907,643,"RUS","Russia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2001/rus_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
21908,643,"RUS","Russia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2001/rus_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
21909,643,"RUS","Russia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2002/rus_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
21910,643,"RUS","Russia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2002/rus_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
21911,643,"RUS","Russia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2002/rus_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
21912,643,"RUS","Russia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2002/rus_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
21913,643,"RUS","Russia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2002/rus_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
21914,643,"RUS","Russia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2002/rus_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
21915,643,"RUS","Russia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2002/rus_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
21916,643,"RUS","Russia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2002/rus_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
21917,643,"RUS","Russia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2003/rus_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
21918,643,"RUS","Russia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2003/rus_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
21919,643,"RUS","Russia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2003/rus_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
21920,643,"RUS","Russia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2003/rus_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
21921,643,"RUS","Russia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2003/rus_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
21922,643,"RUS","Russia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2003/rus_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
21923,643,"RUS","Russia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2003/rus_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
21924,643,"RUS","Russia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2003/rus_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
21925,643,"RUS","Russia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2004/rus_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
21926,643,"RUS","Russia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2004/rus_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
21927,643,"RUS","Russia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2004/rus_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
21928,643,"RUS","Russia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2004/rus_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
21929,643,"RUS","Russia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2004/rus_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
21930,643,"RUS","Russia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2004/rus_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
21931,643,"RUS","Russia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2004/rus_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
21932,643,"RUS","Russia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2004/rus_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
21933,643,"RUS","Russia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2005/rus_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
21934,643,"RUS","Russia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2005/rus_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
21935,643,"RUS","Russia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2005/rus_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
21936,643,"RUS","Russia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2005/rus_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
21937,643,"RUS","Russia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2005/rus_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
21938,643,"RUS","Russia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2005/rus_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
21939,643,"RUS","Russia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2005/rus_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
21940,643,"RUS","Russia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2005/rus_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
21941,643,"RUS","Russia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2006/rus_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
21942,643,"RUS","Russia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2006/rus_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
21943,643,"RUS","Russia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2006/rus_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
21944,643,"RUS","Russia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2006/rus_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
21945,643,"RUS","Russia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2006/rus_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
21946,643,"RUS","Russia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2006/rus_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
21947,643,"RUS","Russia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2006/rus_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
21948,643,"RUS","Russia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2006/rus_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
21949,643,"RUS","Russia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2007/rus_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
21950,643,"RUS","Russia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2007/rus_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
21951,643,"RUS","Russia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2007/rus_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
21952,643,"RUS","Russia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2007/rus_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
21953,643,"RUS","Russia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2007/rus_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
21954,643,"RUS","Russia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2007/rus_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
21955,643,"RUS","Russia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2007/rus_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
21956,643,"RUS","Russia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2007/rus_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
21957,643,"RUS","Russia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2008/rus_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
21958,643,"RUS","Russia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2008/rus_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
21959,643,"RUS","Russia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2008/rus_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
21960,643,"RUS","Russia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2008/rus_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
21961,643,"RUS","Russia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2008/rus_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
21962,643,"RUS","Russia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2008/rus_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
21963,643,"RUS","Russia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2008/rus_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
21964,643,"RUS","Russia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2008/rus_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
21965,643,"RUS","Russia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2009/rus_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
21966,643,"RUS","Russia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2009/rus_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
21967,643,"RUS","Russia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2009/rus_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
21968,643,"RUS","Russia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2009/rus_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
21969,643,"RUS","Russia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2009/rus_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
21970,643,"RUS","Russia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2009/rus_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
21971,643,"RUS","Russia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2009/rus_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
21972,643,"RUS","Russia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2009/rus_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
21973,643,"RUS","Russia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2010/rus_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
21974,643,"RUS","Russia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2010/rus_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
21975,643,"RUS","Russia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2010/rus_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
21976,643,"RUS","Russia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2010/rus_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
21977,643,"RUS","Russia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2010/rus_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
21978,643,"RUS","Russia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2010/rus_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
21979,643,"RUS","Russia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2010/rus_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
21980,643,"RUS","Russia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2010/rus_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
21981,643,"RUS","Russia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2011/rus_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
21982,643,"RUS","Russia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2011/rus_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
21983,643,"RUS","Russia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2011/rus_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
21984,643,"RUS","Russia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2011/rus_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
21985,643,"RUS","Russia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2011/rus_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
21986,643,"RUS","Russia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2011/rus_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
21987,643,"RUS","Russia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2011/rus_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
21988,643,"RUS","Russia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2011/rus_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
21989,643,"RUS","Russia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2012/rus_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
21990,643,"RUS","Russia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2012/rus_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
21991,643,"RUS","Russia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2012/rus_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
21992,643,"RUS","Russia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2012/rus_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
21993,643,"RUS","Russia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2012/rus_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
21994,643,"RUS","Russia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2012/rus_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
21995,643,"RUS","Russia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2012/rus_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
21996,643,"RUS","Russia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2012/rus_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
21997,643,"RUS","Russia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2013/rus_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
21998,643,"RUS","Russia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2013/rus_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
21999,643,"RUS","Russia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2013/rus_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
22000,643,"RUS","Russia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2013/rus_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
22001,643,"RUS","Russia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2013/rus_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
22002,643,"RUS","Russia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2013/rus_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
22003,643,"RUS","Russia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2013/rus_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
22004,643,"RUS","Russia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2013/rus_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
22005,643,"RUS","Russia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2014/rus_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
22006,643,"RUS","Russia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2014/rus_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
22007,643,"RUS","Russia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2014/rus_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
22008,643,"RUS","Russia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2014/rus_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
22009,643,"RUS","Russia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2014/rus_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
22010,643,"RUS","Russia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2014/rus_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
22011,643,"RUS","Russia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2014/rus_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
22012,643,"RUS","Russia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2014/rus_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
22013,643,"RUS","Russia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2015/rus_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
22014,643,"RUS","Russia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2015/rus_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
22015,643,"RUS","Russia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2015/rus_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
22016,643,"RUS","Russia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2015/rus_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
22017,643,"RUS","Russia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2015/rus_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
22018,643,"RUS","Russia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2015/rus_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
22019,643,"RUS","Russia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2015/rus_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
22020,643,"RUS","Russia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Annual/2015/rus_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
22021,360,"IDN","Indonesia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2000/idn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
22022,360,"IDN","Indonesia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2000/idn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
22023,360,"IDN","Indonesia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2000/idn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
22024,360,"IDN","Indonesia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2000/idn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
22025,360,"IDN","Indonesia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2000/idn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
22026,360,"IDN","Indonesia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2000/idn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
22027,360,"IDN","Indonesia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2000/idn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
22028,360,"IDN","Indonesia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2000/idn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
22029,360,"IDN","Indonesia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2001/idn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
22030,360,"IDN","Indonesia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2001/idn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
22031,360,"IDN","Indonesia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2001/idn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
22032,360,"IDN","Indonesia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2001/idn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
22033,360,"IDN","Indonesia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2001/idn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
22034,360,"IDN","Indonesia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2001/idn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
22035,360,"IDN","Indonesia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2001/idn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
22036,360,"IDN","Indonesia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2001/idn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
22037,360,"IDN","Indonesia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2002/idn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
22038,360,"IDN","Indonesia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2002/idn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
22039,360,"IDN","Indonesia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2002/idn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
22040,360,"IDN","Indonesia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2002/idn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
22041,360,"IDN","Indonesia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2002/idn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
22042,360,"IDN","Indonesia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2002/idn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
22043,360,"IDN","Indonesia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2002/idn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
22044,360,"IDN","Indonesia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2002/idn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
22045,360,"IDN","Indonesia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2003/idn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
22046,360,"IDN","Indonesia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2003/idn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
22047,360,"IDN","Indonesia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2003/idn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
22048,360,"IDN","Indonesia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2003/idn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
22049,360,"IDN","Indonesia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2003/idn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
22050,360,"IDN","Indonesia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2003/idn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
22051,360,"IDN","Indonesia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2003/idn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
22052,360,"IDN","Indonesia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2003/idn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
22053,360,"IDN","Indonesia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2004/idn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
22054,360,"IDN","Indonesia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2004/idn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
22055,360,"IDN","Indonesia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2004/idn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
22056,360,"IDN","Indonesia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2004/idn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
22057,360,"IDN","Indonesia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2004/idn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
22058,360,"IDN","Indonesia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2004/idn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
22059,360,"IDN","Indonesia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2004/idn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
22060,360,"IDN","Indonesia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2004/idn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
22061,360,"IDN","Indonesia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2005/idn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
22062,360,"IDN","Indonesia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2005/idn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
22063,360,"IDN","Indonesia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2005/idn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
22064,360,"IDN","Indonesia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2005/idn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
22065,360,"IDN","Indonesia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2005/idn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
22066,360,"IDN","Indonesia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2005/idn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
22067,360,"IDN","Indonesia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2005/idn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
22068,360,"IDN","Indonesia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2005/idn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
22069,360,"IDN","Indonesia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2006/idn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
22070,360,"IDN","Indonesia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2006/idn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
22071,360,"IDN","Indonesia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2006/idn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
22072,360,"IDN","Indonesia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2006/idn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
22073,360,"IDN","Indonesia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2006/idn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
22074,360,"IDN","Indonesia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2006/idn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
22075,360,"IDN","Indonesia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2006/idn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
22076,360,"IDN","Indonesia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2006/idn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
22077,360,"IDN","Indonesia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2007/idn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
22078,360,"IDN","Indonesia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2007/idn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
22079,360,"IDN","Indonesia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2007/idn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
22080,360,"IDN","Indonesia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2007/idn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
22081,360,"IDN","Indonesia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2007/idn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
22082,360,"IDN","Indonesia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2007/idn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
22083,360,"IDN","Indonesia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2007/idn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
22084,360,"IDN","Indonesia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2007/idn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
22085,360,"IDN","Indonesia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2008/idn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
22086,360,"IDN","Indonesia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2008/idn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
22087,360,"IDN","Indonesia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2008/idn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
22088,360,"IDN","Indonesia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2008/idn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
22089,360,"IDN","Indonesia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2008/idn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
22090,360,"IDN","Indonesia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2008/idn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
22091,360,"IDN","Indonesia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2008/idn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
22092,360,"IDN","Indonesia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2008/idn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
22093,360,"IDN","Indonesia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2009/idn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
22094,360,"IDN","Indonesia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2009/idn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
22095,360,"IDN","Indonesia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2009/idn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
22096,360,"IDN","Indonesia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2009/idn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
22097,360,"IDN","Indonesia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2009/idn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
22098,360,"IDN","Indonesia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2009/idn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
22099,360,"IDN","Indonesia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2009/idn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
22100,360,"IDN","Indonesia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2009/idn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
22101,360,"IDN","Indonesia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2010/idn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
22102,360,"IDN","Indonesia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2010/idn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
22103,360,"IDN","Indonesia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2010/idn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
22104,360,"IDN","Indonesia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2010/idn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
22105,360,"IDN","Indonesia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2010/idn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
22106,360,"IDN","Indonesia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2010/idn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
22107,360,"IDN","Indonesia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2010/idn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
22108,360,"IDN","Indonesia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2010/idn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
22109,360,"IDN","Indonesia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2011/idn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
22110,360,"IDN","Indonesia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2011/idn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
22111,360,"IDN","Indonesia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2011/idn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
22112,360,"IDN","Indonesia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2011/idn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
22113,360,"IDN","Indonesia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2011/idn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
22114,360,"IDN","Indonesia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2011/idn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
22115,360,"IDN","Indonesia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2011/idn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
22116,360,"IDN","Indonesia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2011/idn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
22117,360,"IDN","Indonesia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2012/idn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
22118,360,"IDN","Indonesia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2012/idn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
22119,360,"IDN","Indonesia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2012/idn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
22120,360,"IDN","Indonesia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2012/idn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
22121,360,"IDN","Indonesia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2012/idn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
22122,360,"IDN","Indonesia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2012/idn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
22123,360,"IDN","Indonesia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2012/idn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
22124,360,"IDN","Indonesia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2012/idn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
22125,360,"IDN","Indonesia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2013/idn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
22126,360,"IDN","Indonesia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2013/idn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
22127,360,"IDN","Indonesia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2013/idn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
22128,360,"IDN","Indonesia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2013/idn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
22129,360,"IDN","Indonesia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2013/idn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
22130,360,"IDN","Indonesia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2013/idn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
22131,360,"IDN","Indonesia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2013/idn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
22132,360,"IDN","Indonesia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2013/idn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
22133,360,"IDN","Indonesia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2014/idn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
22134,360,"IDN","Indonesia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2014/idn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
22135,360,"IDN","Indonesia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2014/idn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
22136,360,"IDN","Indonesia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2014/idn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
22137,360,"IDN","Indonesia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2014/idn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
22138,360,"IDN","Indonesia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2014/idn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
22139,360,"IDN","Indonesia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2014/idn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
22140,360,"IDN","Indonesia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2014/idn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
22141,360,"IDN","Indonesia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2015/idn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
22142,360,"IDN","Indonesia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2015/idn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
22143,360,"IDN","Indonesia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2015/idn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
22144,360,"IDN","Indonesia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2015/idn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
22145,360,"IDN","Indonesia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2015/idn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
22146,360,"IDN","Indonesia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2015/idn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
22147,360,"IDN","Indonesia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2015/idn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
22148,360,"IDN","Indonesia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Annual/2015/idn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
22149,840,"USA","United States","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2000/usa_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
22150,840,"USA","United States","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2000/usa_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
22151,840,"USA","United States","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2000/usa_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
22152,840,"USA","United States","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2000/usa_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
22153,840,"USA","United States","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2000/usa_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
22154,840,"USA","United States","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2000/usa_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
22155,840,"USA","United States","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2000/usa_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
22156,840,"USA","United States","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2000/usa_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
22157,840,"USA","United States","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2001/usa_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
22158,840,"USA","United States","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2001/usa_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
22159,840,"USA","United States","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2001/usa_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
22160,840,"USA","United States","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2001/usa_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
22161,840,"USA","United States","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2001/usa_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
22162,840,"USA","United States","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2001/usa_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
22163,840,"USA","United States","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2001/usa_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
22164,840,"USA","United States","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2001/usa_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
22165,840,"USA","United States","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2002/usa_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
22166,840,"USA","United States","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2002/usa_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
22167,840,"USA","United States","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2002/usa_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
22168,840,"USA","United States","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2002/usa_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
22169,840,"USA","United States","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2002/usa_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
22170,840,"USA","United States","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2002/usa_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
22171,840,"USA","United States","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2002/usa_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
22172,840,"USA","United States","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2002/usa_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
22173,840,"USA","United States","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2003/usa_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
22174,840,"USA","United States","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2003/usa_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
22175,840,"USA","United States","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2003/usa_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
22176,840,"USA","United States","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2003/usa_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
22177,840,"USA","United States","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2003/usa_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
22178,840,"USA","United States","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2003/usa_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
22179,840,"USA","United States","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2003/usa_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
22180,840,"USA","United States","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2003/usa_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
22181,840,"USA","United States","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2004/usa_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
22182,840,"USA","United States","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2004/usa_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
22183,840,"USA","United States","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2004/usa_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
22184,840,"USA","United States","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2004/usa_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
22185,840,"USA","United States","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2004/usa_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
22186,840,"USA","United States","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2004/usa_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
22187,840,"USA","United States","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2004/usa_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
22188,840,"USA","United States","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2004/usa_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
22189,840,"USA","United States","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2005/usa_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
22190,840,"USA","United States","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2005/usa_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
22191,840,"USA","United States","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2005/usa_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
22192,840,"USA","United States","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2005/usa_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
22193,840,"USA","United States","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2005/usa_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
22194,840,"USA","United States","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2005/usa_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
22195,840,"USA","United States","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2005/usa_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
22196,840,"USA","United States","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2005/usa_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
22197,840,"USA","United States","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2006/usa_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
22198,840,"USA","United States","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2006/usa_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
22199,840,"USA","United States","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2006/usa_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
22200,840,"USA","United States","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2006/usa_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
22201,840,"USA","United States","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2006/usa_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
22202,840,"USA","United States","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2006/usa_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
22203,840,"USA","United States","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2006/usa_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
22204,840,"USA","United States","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2006/usa_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
22205,840,"USA","United States","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2007/usa_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
22206,840,"USA","United States","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2007/usa_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
22207,840,"USA","United States","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2007/usa_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
22208,840,"USA","United States","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2007/usa_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
22209,840,"USA","United States","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2007/usa_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
22210,840,"USA","United States","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2007/usa_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
22211,840,"USA","United States","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2007/usa_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
22212,840,"USA","United States","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2007/usa_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
22213,840,"USA","United States","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2008/usa_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
22214,840,"USA","United States","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2008/usa_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
22215,840,"USA","United States","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2008/usa_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
22216,840,"USA","United States","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2008/usa_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
22217,840,"USA","United States","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2008/usa_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
22218,840,"USA","United States","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2008/usa_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
22219,840,"USA","United States","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2008/usa_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
22220,840,"USA","United States","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2008/usa_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
22221,840,"USA","United States","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2009/usa_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
22222,840,"USA","United States","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2009/usa_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
22223,840,"USA","United States","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2009/usa_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
22224,840,"USA","United States","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2009/usa_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
22225,840,"USA","United States","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2009/usa_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
22226,840,"USA","United States","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2009/usa_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
22227,840,"USA","United States","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2009/usa_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
22228,840,"USA","United States","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2009/usa_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
22229,840,"USA","United States","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2010/usa_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
22230,840,"USA","United States","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2010/usa_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
22231,840,"USA","United States","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2010/usa_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
22232,840,"USA","United States","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2010/usa_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
22233,840,"USA","United States","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2010/usa_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
22234,840,"USA","United States","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2010/usa_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
22235,840,"USA","United States","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2010/usa_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
22236,840,"USA","United States","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2010/usa_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
22237,840,"USA","United States","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2011/usa_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
22238,840,"USA","United States","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2011/usa_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
22239,840,"USA","United States","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2011/usa_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
22240,840,"USA","United States","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2011/usa_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
22241,840,"USA","United States","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2011/usa_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
22242,840,"USA","United States","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2011/usa_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
22243,840,"USA","United States","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2011/usa_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
22244,840,"USA","United States","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2011/usa_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
22245,840,"USA","United States","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2012/usa_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
22246,840,"USA","United States","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2012/usa_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
22247,840,"USA","United States","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2012/usa_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
22248,840,"USA","United States","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2012/usa_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
22249,840,"USA","United States","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2012/usa_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
22250,840,"USA","United States","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2012/usa_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
22251,840,"USA","United States","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2012/usa_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
22252,840,"USA","United States","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2012/usa_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
22253,840,"USA","United States","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2013/usa_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
22254,840,"USA","United States","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2013/usa_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
22255,840,"USA","United States","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2013/usa_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
22256,840,"USA","United States","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2013/usa_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
22257,840,"USA","United States","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2013/usa_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
22258,840,"USA","United States","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2013/usa_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
22259,840,"USA","United States","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2013/usa_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
22260,840,"USA","United States","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2013/usa_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
22261,840,"USA","United States","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2014/usa_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
22262,840,"USA","United States","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2014/usa_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
22263,840,"USA","United States","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2014/usa_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
22264,840,"USA","United States","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2014/usa_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
22265,840,"USA","United States","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2014/usa_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
22266,840,"USA","United States","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2014/usa_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
22267,840,"USA","United States","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2014/usa_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
22268,840,"USA","United States","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2014/usa_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
22269,840,"USA","United States","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2015/usa_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
22270,840,"USA","United States","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2015/usa_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
22271,840,"USA","United States","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2015/usa_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
22272,840,"USA","United States","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2015/usa_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
22273,840,"USA","United States","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2015/usa_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
22274,840,"USA","United States","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2015/usa_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
22275,840,"USA","United States","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2015/usa_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
22276,840,"USA","United States","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Annual/2015/usa_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
22277,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2000/vir_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
22278,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2000/vir_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
22279,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2000/vir_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
22280,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2000/vir_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
22281,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2000/vir_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
22282,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2000/vir_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
22283,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2000/vir_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
22284,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2000/vir_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
22285,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2001/vir_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
22286,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2001/vir_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
22287,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2001/vir_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
22288,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2001/vir_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
22289,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2001/vir_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
22290,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2001/vir_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
22291,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2001/vir_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
22292,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2001/vir_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
22293,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2002/vir_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
22294,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2002/vir_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
22295,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2002/vir_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
22296,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2002/vir_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
22297,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2002/vir_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
22298,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2002/vir_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
22299,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2002/vir_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
22300,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2002/vir_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
22301,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2003/vir_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
22302,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2003/vir_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
22303,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2003/vir_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
22304,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2003/vir_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
22305,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2003/vir_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
22306,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2003/vir_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
22307,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2003/vir_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
22308,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2003/vir_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
22309,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2004/vir_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
22310,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2004/vir_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
22311,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2004/vir_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
22312,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2004/vir_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
22313,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2004/vir_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
22314,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2004/vir_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
22315,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2004/vir_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
22316,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2004/vir_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
22317,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2005/vir_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
22318,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2005/vir_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
22319,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2005/vir_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
22320,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2005/vir_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
22321,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2005/vir_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
22322,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2005/vir_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
22323,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2005/vir_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
22324,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2005/vir_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
22325,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2006/vir_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
22326,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2006/vir_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
22327,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2006/vir_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
22328,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2006/vir_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
22329,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2006/vir_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
22330,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2006/vir_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
22331,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2006/vir_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
22332,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2006/vir_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
22333,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2007/vir_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
22334,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2007/vir_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
22335,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2007/vir_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
22336,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2007/vir_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
22337,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2007/vir_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
22338,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2007/vir_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
22339,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2007/vir_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
22340,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2007/vir_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
22341,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2008/vir_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
22342,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2008/vir_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
22343,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2008/vir_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
22344,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2008/vir_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
22345,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2008/vir_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
22346,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2008/vir_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
22347,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2008/vir_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
22348,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2008/vir_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
22349,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2009/vir_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
22350,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2009/vir_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
22351,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2009/vir_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
22352,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2009/vir_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
22353,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2009/vir_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
22354,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2009/vir_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
22355,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2009/vir_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
22356,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2009/vir_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
22357,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2010/vir_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
22358,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2010/vir_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
22359,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2010/vir_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
22360,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2010/vir_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
22361,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2010/vir_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
22362,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2010/vir_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
22363,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2010/vir_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
22364,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2010/vir_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
22365,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2011/vir_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
22366,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2011/vir_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
22367,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2011/vir_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
22368,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2011/vir_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
22369,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2011/vir_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
22370,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2011/vir_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
22371,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2011/vir_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
22372,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2011/vir_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
22373,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2012/vir_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
22374,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2012/vir_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
22375,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2012/vir_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
22376,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2012/vir_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
22377,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2012/vir_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
22378,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2012/vir_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
22379,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2012/vir_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
22380,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2012/vir_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
22381,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2013/vir_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
22382,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2013/vir_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
22383,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2013/vir_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
22384,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2013/vir_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
22385,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2013/vir_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
22386,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2013/vir_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
22387,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2013/vir_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
22388,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2013/vir_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
22389,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2014/vir_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
22390,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2014/vir_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
22391,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2014/vir_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
22392,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2014/vir_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
22393,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2014/vir_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
22394,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2014/vir_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
22395,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2014/vir_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
22396,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2014/vir_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
22397,850,"VIR","Virgin_Islands_U_S","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2015/vir_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
22398,850,"VIR","Virgin_Islands_U_S","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2015/vir_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
22399,850,"VIR","Virgin_Islands_U_S","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2015/vir_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
22400,850,"VIR","Virgin_Islands_U_S","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2015/vir_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
22401,850,"VIR","Virgin_Islands_U_S","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2015/vir_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
22402,850,"VIR","Virgin_Islands_U_S","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2015/vir_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
22403,850,"VIR","Virgin_Islands_U_S","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2015/vir_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
22404,850,"VIR","Virgin_Islands_U_S","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Annual/2015/vir_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
22405,304,"GRL","Greenland","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2000/grl_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
22406,304,"GRL","Greenland","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2000/grl_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
22407,304,"GRL","Greenland","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2000/grl_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
22408,304,"GRL","Greenland","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2000/grl_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
22409,304,"GRL","Greenland","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2000/grl_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
22410,304,"GRL","Greenland","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2000/grl_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
22411,304,"GRL","Greenland","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2000/grl_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
22412,304,"GRL","Greenland","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2000/grl_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
22413,304,"GRL","Greenland","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2001/grl_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
22414,304,"GRL","Greenland","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2001/grl_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
22415,304,"GRL","Greenland","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2001/grl_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
22416,304,"GRL","Greenland","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2001/grl_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
22417,304,"GRL","Greenland","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2001/grl_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
22418,304,"GRL","Greenland","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2001/grl_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
22419,304,"GRL","Greenland","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2001/grl_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
22420,304,"GRL","Greenland","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2001/grl_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
22421,304,"GRL","Greenland","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2002/grl_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
22422,304,"GRL","Greenland","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2002/grl_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
22423,304,"GRL","Greenland","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2002/grl_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
22424,304,"GRL","Greenland","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2002/grl_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
22425,304,"GRL","Greenland","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2002/grl_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
22426,304,"GRL","Greenland","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2002/grl_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
22427,304,"GRL","Greenland","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2002/grl_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
22428,304,"GRL","Greenland","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2002/grl_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
22429,304,"GRL","Greenland","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2003/grl_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
22430,304,"GRL","Greenland","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2003/grl_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
22431,304,"GRL","Greenland","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2003/grl_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
22432,304,"GRL","Greenland","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2003/grl_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
22433,304,"GRL","Greenland","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2003/grl_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
22434,304,"GRL","Greenland","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2003/grl_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
22435,304,"GRL","Greenland","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2003/grl_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
22436,304,"GRL","Greenland","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2003/grl_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
22437,304,"GRL","Greenland","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2004/grl_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
22438,304,"GRL","Greenland","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2004/grl_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
22439,304,"GRL","Greenland","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2004/grl_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
22440,304,"GRL","Greenland","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2004/grl_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
22441,304,"GRL","Greenland","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2004/grl_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
22442,304,"GRL","Greenland","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2004/grl_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
22443,304,"GRL","Greenland","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2004/grl_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
22444,304,"GRL","Greenland","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2004/grl_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
22445,304,"GRL","Greenland","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2005/grl_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
22446,304,"GRL","Greenland","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2005/grl_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
22447,304,"GRL","Greenland","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2005/grl_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
22448,304,"GRL","Greenland","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2005/grl_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
22449,304,"GRL","Greenland","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2005/grl_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
22450,304,"GRL","Greenland","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2005/grl_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
22451,304,"GRL","Greenland","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2005/grl_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
22452,304,"GRL","Greenland","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2005/grl_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
22453,304,"GRL","Greenland","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2006/grl_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
22454,304,"GRL","Greenland","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2006/grl_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
22455,304,"GRL","Greenland","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2006/grl_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
22456,304,"GRL","Greenland","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2006/grl_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
22457,304,"GRL","Greenland","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2006/grl_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
22458,304,"GRL","Greenland","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2006/grl_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
22459,304,"GRL","Greenland","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2006/grl_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
22460,304,"GRL","Greenland","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2006/grl_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
22461,304,"GRL","Greenland","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2007/grl_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
22462,304,"GRL","Greenland","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2007/grl_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
22463,304,"GRL","Greenland","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2007/grl_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
22464,304,"GRL","Greenland","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2007/grl_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
22465,304,"GRL","Greenland","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2007/grl_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
22466,304,"GRL","Greenland","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2007/grl_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
22467,304,"GRL","Greenland","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2007/grl_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
22468,304,"GRL","Greenland","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2007/grl_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
22469,304,"GRL","Greenland","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2008/grl_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
22470,304,"GRL","Greenland","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2008/grl_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
22471,304,"GRL","Greenland","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2008/grl_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
22472,304,"GRL","Greenland","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2008/grl_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
22473,304,"GRL","Greenland","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2008/grl_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
22474,304,"GRL","Greenland","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2008/grl_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
22475,304,"GRL","Greenland","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2008/grl_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
22476,304,"GRL","Greenland","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2008/grl_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
22477,304,"GRL","Greenland","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2009/grl_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
22478,304,"GRL","Greenland","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2009/grl_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
22479,304,"GRL","Greenland","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2009/grl_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
22480,304,"GRL","Greenland","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2009/grl_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
22481,304,"GRL","Greenland","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2009/grl_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
22482,304,"GRL","Greenland","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2009/grl_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
22483,304,"GRL","Greenland","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2009/grl_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
22484,304,"GRL","Greenland","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2009/grl_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
22485,304,"GRL","Greenland","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2010/grl_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
22486,304,"GRL","Greenland","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2010/grl_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
22487,304,"GRL","Greenland","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2010/grl_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
22488,304,"GRL","Greenland","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2010/grl_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
22489,304,"GRL","Greenland","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2010/grl_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
22490,304,"GRL","Greenland","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2010/grl_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
22491,304,"GRL","Greenland","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2010/grl_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
22492,304,"GRL","Greenland","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2010/grl_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
22493,304,"GRL","Greenland","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2011/grl_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
22494,304,"GRL","Greenland","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2011/grl_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
22495,304,"GRL","Greenland","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2011/grl_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
22496,304,"GRL","Greenland","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2011/grl_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
22497,304,"GRL","Greenland","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2011/grl_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
22498,304,"GRL","Greenland","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2011/grl_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
22499,304,"GRL","Greenland","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2011/grl_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
22500,304,"GRL","Greenland","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2011/grl_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
22501,304,"GRL","Greenland","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2012/grl_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
22502,304,"GRL","Greenland","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2012/grl_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
22503,304,"GRL","Greenland","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2012/grl_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
22504,304,"GRL","Greenland","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2012/grl_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
22505,304,"GRL","Greenland","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2012/grl_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
22506,304,"GRL","Greenland","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2012/grl_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
22507,304,"GRL","Greenland","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2012/grl_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
22508,304,"GRL","Greenland","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2012/grl_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
22509,304,"GRL","Greenland","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2013/grl_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
22510,304,"GRL","Greenland","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2013/grl_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
22511,304,"GRL","Greenland","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2013/grl_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
22512,304,"GRL","Greenland","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2013/grl_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
22513,304,"GRL","Greenland","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2013/grl_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
22514,304,"GRL","Greenland","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2013/grl_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
22515,304,"GRL","Greenland","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2013/grl_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
22516,304,"GRL","Greenland","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2013/grl_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
22517,304,"GRL","Greenland","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2014/grl_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
22518,304,"GRL","Greenland","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2014/grl_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
22519,304,"GRL","Greenland","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2014/grl_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
22520,304,"GRL","Greenland","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2014/grl_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
22521,304,"GRL","Greenland","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2014/grl_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
22522,304,"GRL","Greenland","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2014/grl_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
22523,304,"GRL","Greenland","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2014/grl_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
22524,304,"GRL","Greenland","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2014/grl_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
22525,304,"GRL","Greenland","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2015/grl_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
22526,304,"GRL","Greenland","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2015/grl_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
22527,304,"GRL","Greenland","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2015/grl_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
22528,304,"GRL","Greenland","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2015/grl_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
22529,304,"GRL","Greenland","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2015/grl_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
22530,304,"GRL","Greenland","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2015/grl_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
22531,304,"GRL","Greenland","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2015/grl_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
22532,304,"GRL","Greenland","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Annual/2015/grl_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
22533,156,"CHN","China","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2000/chn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
22534,156,"CHN","China","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2000/chn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
22535,156,"CHN","China","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2000/chn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
22536,156,"CHN","China","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2000/chn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
22537,156,"CHN","China","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2000/chn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
22538,156,"CHN","China","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2000/chn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
22539,156,"CHN","China","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2000/chn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
22540,156,"CHN","China","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2000/chn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
22541,156,"CHN","China","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2001/chn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
22542,156,"CHN","China","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2001/chn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
22543,156,"CHN","China","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2001/chn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
22544,156,"CHN","China","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2001/chn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
22545,156,"CHN","China","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2001/chn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
22546,156,"CHN","China","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2001/chn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
22547,156,"CHN","China","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2001/chn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
22548,156,"CHN","China","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2001/chn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
22549,156,"CHN","China","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2002/chn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
22550,156,"CHN","China","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2002/chn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
22551,156,"CHN","China","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2002/chn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
22552,156,"CHN","China","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2002/chn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
22553,156,"CHN","China","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2002/chn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
22554,156,"CHN","China","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2002/chn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
22555,156,"CHN","China","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2002/chn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
22556,156,"CHN","China","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2002/chn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
22557,156,"CHN","China","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2003/chn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
22558,156,"CHN","China","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2003/chn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
22559,156,"CHN","China","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2003/chn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
22560,156,"CHN","China","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2003/chn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
22561,156,"CHN","China","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2003/chn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
22562,156,"CHN","China","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2003/chn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
22563,156,"CHN","China","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2003/chn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
22564,156,"CHN","China","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2003/chn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
22565,156,"CHN","China","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2004/chn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
22566,156,"CHN","China","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2004/chn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
22567,156,"CHN","China","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2004/chn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
22568,156,"CHN","China","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2004/chn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
22569,156,"CHN","China","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2004/chn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
22570,156,"CHN","China","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2004/chn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
22571,156,"CHN","China","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2004/chn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
22572,156,"CHN","China","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2004/chn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
22573,156,"CHN","China","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2005/chn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
22574,156,"CHN","China","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2005/chn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
22575,156,"CHN","China","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2005/chn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
22576,156,"CHN","China","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2005/chn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
22577,156,"CHN","China","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2005/chn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
22578,156,"CHN","China","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2005/chn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
22579,156,"CHN","China","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2005/chn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
22580,156,"CHN","China","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2005/chn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
22581,156,"CHN","China","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2006/chn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
22582,156,"CHN","China","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2006/chn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
22583,156,"CHN","China","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2006/chn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
22584,156,"CHN","China","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2006/chn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
22585,156,"CHN","China","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2006/chn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
22586,156,"CHN","China","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2006/chn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
22587,156,"CHN","China","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2006/chn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
22588,156,"CHN","China","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2006/chn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
22589,156,"CHN","China","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2007/chn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
22590,156,"CHN","China","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2007/chn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
22591,156,"CHN","China","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2007/chn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
22592,156,"CHN","China","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2007/chn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
22593,156,"CHN","China","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2007/chn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
22594,156,"CHN","China","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2007/chn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
22595,156,"CHN","China","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2007/chn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
22596,156,"CHN","China","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2007/chn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
22597,156,"CHN","China","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2008/chn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
22598,156,"CHN","China","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2008/chn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
22599,156,"CHN","China","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2008/chn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
22600,156,"CHN","China","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2008/chn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
22601,156,"CHN","China","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2008/chn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
22602,156,"CHN","China","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2008/chn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
22603,156,"CHN","China","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2008/chn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
22604,156,"CHN","China","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2008/chn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
22605,156,"CHN","China","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2009/chn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
22606,156,"CHN","China","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2009/chn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
22607,156,"CHN","China","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2009/chn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
22608,156,"CHN","China","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2009/chn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
22609,156,"CHN","China","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2009/chn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
22610,156,"CHN","China","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2009/chn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
22611,156,"CHN","China","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2009/chn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
22612,156,"CHN","China","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2009/chn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
22613,156,"CHN","China","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2010/chn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
22614,156,"CHN","China","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2010/chn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
22615,156,"CHN","China","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2010/chn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
22616,156,"CHN","China","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2010/chn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
22617,156,"CHN","China","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2010/chn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
22618,156,"CHN","China","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2010/chn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
22619,156,"CHN","China","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2010/chn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
22620,156,"CHN","China","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2010/chn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
22621,156,"CHN","China","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2011/chn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
22622,156,"CHN","China","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2011/chn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
22623,156,"CHN","China","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2011/chn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
22624,156,"CHN","China","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2011/chn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
22625,156,"CHN","China","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2011/chn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
22626,156,"CHN","China","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2011/chn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
22627,156,"CHN","China","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2011/chn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
22628,156,"CHN","China","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2011/chn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
22629,156,"CHN","China","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2012/chn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
22630,156,"CHN","China","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2012/chn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
22631,156,"CHN","China","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2012/chn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
22632,156,"CHN","China","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2012/chn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
22633,156,"CHN","China","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2012/chn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
22634,156,"CHN","China","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2012/chn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
22635,156,"CHN","China","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2012/chn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
22636,156,"CHN","China","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2012/chn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
22637,156,"CHN","China","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2013/chn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
22638,156,"CHN","China","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2013/chn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
22639,156,"CHN","China","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2013/chn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
22640,156,"CHN","China","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2013/chn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
22641,156,"CHN","China","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2013/chn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
22642,156,"CHN","China","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2013/chn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
22643,156,"CHN","China","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2013/chn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
22644,156,"CHN","China","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2013/chn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
22645,156,"CHN","China","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2014/chn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
22646,156,"CHN","China","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2014/chn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
22647,156,"CHN","China","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2014/chn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
22648,156,"CHN","China","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2014/chn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
22649,156,"CHN","China","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2014/chn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
22650,156,"CHN","China","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2014/chn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
22651,156,"CHN","China","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2014/chn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
22652,156,"CHN","China","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2014/chn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
22653,156,"CHN","China","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2015/chn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
22654,156,"CHN","China","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2015/chn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
22655,156,"CHN","China","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2015/chn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
22656,156,"CHN","China","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2015/chn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
22657,156,"CHN","China","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2015/chn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
22658,156,"CHN","China","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2015/chn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
22659,156,"CHN","China","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2015/chn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
22660,156,"CHN","China","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Annual/2015/chn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
22661,36,"AUS","Australia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2000/aus_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
22662,36,"AUS","Australia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2000/aus_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
22663,36,"AUS","Australia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2000/aus_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
22664,36,"AUS","Australia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2000/aus_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
22665,36,"AUS","Australia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2000/aus_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
22666,36,"AUS","Australia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2000/aus_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
22667,36,"AUS","Australia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2000/aus_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
22668,36,"AUS","Australia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2000/aus_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
22669,36,"AUS","Australia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2001/aus_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
22670,36,"AUS","Australia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2001/aus_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
22671,36,"AUS","Australia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2001/aus_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
22672,36,"AUS","Australia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2001/aus_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
22673,36,"AUS","Australia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2001/aus_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
22674,36,"AUS","Australia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2001/aus_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
22675,36,"AUS","Australia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2001/aus_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
22676,36,"AUS","Australia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2001/aus_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
22677,36,"AUS","Australia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2002/aus_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
22678,36,"AUS","Australia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2002/aus_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
22679,36,"AUS","Australia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2002/aus_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
22680,36,"AUS","Australia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2002/aus_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
22681,36,"AUS","Australia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2002/aus_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
22682,36,"AUS","Australia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2002/aus_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
22683,36,"AUS","Australia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2002/aus_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
22684,36,"AUS","Australia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2002/aus_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
22685,36,"AUS","Australia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2003/aus_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
22686,36,"AUS","Australia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2003/aus_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
22687,36,"AUS","Australia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2003/aus_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
22688,36,"AUS","Australia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2003/aus_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
22689,36,"AUS","Australia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2003/aus_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
22690,36,"AUS","Australia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2003/aus_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
22691,36,"AUS","Australia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2003/aus_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
22692,36,"AUS","Australia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2003/aus_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
22693,36,"AUS","Australia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2004/aus_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
22694,36,"AUS","Australia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2004/aus_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
22695,36,"AUS","Australia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2004/aus_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
22696,36,"AUS","Australia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2004/aus_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
22697,36,"AUS","Australia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2004/aus_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
22698,36,"AUS","Australia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2004/aus_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
22699,36,"AUS","Australia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2004/aus_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
22700,36,"AUS","Australia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2004/aus_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
22701,36,"AUS","Australia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2005/aus_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
22702,36,"AUS","Australia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2005/aus_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
22703,36,"AUS","Australia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2005/aus_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
22704,36,"AUS","Australia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2005/aus_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
22705,36,"AUS","Australia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2005/aus_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
22706,36,"AUS","Australia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2005/aus_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
22707,36,"AUS","Australia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2005/aus_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
22708,36,"AUS","Australia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2005/aus_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
22709,36,"AUS","Australia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2006/aus_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
22710,36,"AUS","Australia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2006/aus_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
22711,36,"AUS","Australia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2006/aus_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
22712,36,"AUS","Australia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2006/aus_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
22713,36,"AUS","Australia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2006/aus_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
22714,36,"AUS","Australia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2006/aus_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
22715,36,"AUS","Australia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2006/aus_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
22716,36,"AUS","Australia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2006/aus_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
22717,36,"AUS","Australia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2007/aus_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
22718,36,"AUS","Australia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2007/aus_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
22719,36,"AUS","Australia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2007/aus_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
22720,36,"AUS","Australia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2007/aus_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
22721,36,"AUS","Australia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2007/aus_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
22722,36,"AUS","Australia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2007/aus_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
22723,36,"AUS","Australia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2007/aus_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
22724,36,"AUS","Australia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2007/aus_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
22725,36,"AUS","Australia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2008/aus_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
22726,36,"AUS","Australia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2008/aus_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
22727,36,"AUS","Australia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2008/aus_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
22728,36,"AUS","Australia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2008/aus_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
22729,36,"AUS","Australia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2008/aus_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
22730,36,"AUS","Australia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2008/aus_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
22731,36,"AUS","Australia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2008/aus_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
22732,36,"AUS","Australia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2008/aus_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
22733,36,"AUS","Australia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2009/aus_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
22734,36,"AUS","Australia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2009/aus_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
22735,36,"AUS","Australia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2009/aus_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
22736,36,"AUS","Australia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2009/aus_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
22737,36,"AUS","Australia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2009/aus_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
22738,36,"AUS","Australia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2009/aus_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
22739,36,"AUS","Australia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2009/aus_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
22740,36,"AUS","Australia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2009/aus_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
22741,36,"AUS","Australia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2010/aus_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
22742,36,"AUS","Australia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2010/aus_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
22743,36,"AUS","Australia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2010/aus_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
22744,36,"AUS","Australia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2010/aus_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
22745,36,"AUS","Australia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2010/aus_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
22746,36,"AUS","Australia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2010/aus_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
22747,36,"AUS","Australia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2010/aus_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
22748,36,"AUS","Australia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2010/aus_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
22749,36,"AUS","Australia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2011/aus_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
22750,36,"AUS","Australia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2011/aus_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
22751,36,"AUS","Australia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2011/aus_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
22752,36,"AUS","Australia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2011/aus_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
22753,36,"AUS","Australia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2011/aus_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
22754,36,"AUS","Australia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2011/aus_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
22755,36,"AUS","Australia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2011/aus_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
22756,36,"AUS","Australia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2011/aus_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
22757,36,"AUS","Australia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2012/aus_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
22758,36,"AUS","Australia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2012/aus_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
22759,36,"AUS","Australia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2012/aus_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
22760,36,"AUS","Australia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2012/aus_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
22761,36,"AUS","Australia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2012/aus_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
22762,36,"AUS","Australia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2012/aus_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
22763,36,"AUS","Australia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2012/aus_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
22764,36,"AUS","Australia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2012/aus_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
22765,36,"AUS","Australia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2013/aus_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
22766,36,"AUS","Australia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2013/aus_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
22767,36,"AUS","Australia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2013/aus_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
22768,36,"AUS","Australia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2013/aus_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
22769,36,"AUS","Australia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2013/aus_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
22770,36,"AUS","Australia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2013/aus_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
22771,36,"AUS","Australia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2013/aus_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
22772,36,"AUS","Australia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2013/aus_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
22773,36,"AUS","Australia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2014/aus_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
22774,36,"AUS","Australia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2014/aus_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
22775,36,"AUS","Australia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2014/aus_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
22776,36,"AUS","Australia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2014/aus_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
22777,36,"AUS","Australia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2014/aus_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
22778,36,"AUS","Australia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2014/aus_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
22779,36,"AUS","Australia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2014/aus_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
22780,36,"AUS","Australia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2014/aus_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
22781,36,"AUS","Australia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2015/aus_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
22782,36,"AUS","Australia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2015/aus_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
22783,36,"AUS","Australia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2015/aus_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
22784,36,"AUS","Australia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2015/aus_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
22785,36,"AUS","Australia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2015/aus_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
22786,36,"AUS","Australia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2015/aus_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
22787,36,"AUS","Australia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2015/aus_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
22788,36,"AUS","Australia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Annual/2015/aus_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
22789,76,"BRA","Brazil","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2000/bra_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
22790,76,"BRA","Brazil","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2000/bra_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
22791,76,"BRA","Brazil","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2000/bra_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
22792,76,"BRA","Brazil","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2000/bra_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
22793,76,"BRA","Brazil","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2000/bra_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
22794,76,"BRA","Brazil","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2000/bra_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
22795,76,"BRA","Brazil","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2000/bra_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
22796,76,"BRA","Brazil","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2000/bra_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
22797,76,"BRA","Brazil","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2001/bra_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
22798,76,"BRA","Brazil","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2001/bra_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
22799,76,"BRA","Brazil","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2001/bra_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
22800,76,"BRA","Brazil","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2001/bra_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
22801,76,"BRA","Brazil","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2001/bra_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
22802,76,"BRA","Brazil","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2001/bra_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
22803,76,"BRA","Brazil","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2001/bra_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
22804,76,"BRA","Brazil","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2001/bra_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
22805,76,"BRA","Brazil","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2002/bra_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
22806,76,"BRA","Brazil","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2002/bra_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
22807,76,"BRA","Brazil","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2002/bra_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
22808,76,"BRA","Brazil","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2002/bra_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
22809,76,"BRA","Brazil","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2002/bra_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
22810,76,"BRA","Brazil","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2002/bra_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
22811,76,"BRA","Brazil","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2002/bra_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
22812,76,"BRA","Brazil","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2002/bra_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
22813,76,"BRA","Brazil","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2003/bra_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
22814,76,"BRA","Brazil","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2003/bra_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
22815,76,"BRA","Brazil","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2003/bra_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
22816,76,"BRA","Brazil","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2003/bra_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
22817,76,"BRA","Brazil","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2003/bra_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
22818,76,"BRA","Brazil","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2003/bra_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
22819,76,"BRA","Brazil","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2003/bra_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
22820,76,"BRA","Brazil","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2003/bra_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
22821,76,"BRA","Brazil","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2004/bra_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
22822,76,"BRA","Brazil","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2004/bra_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
22823,76,"BRA","Brazil","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2004/bra_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
22824,76,"BRA","Brazil","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2004/bra_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
22825,76,"BRA","Brazil","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2004/bra_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
22826,76,"BRA","Brazil","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2004/bra_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
22827,76,"BRA","Brazil","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2004/bra_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
22828,76,"BRA","Brazil","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2004/bra_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
22829,76,"BRA","Brazil","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2005/bra_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
22830,76,"BRA","Brazil","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2005/bra_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
22831,76,"BRA","Brazil","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2005/bra_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
22832,76,"BRA","Brazil","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2005/bra_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
22833,76,"BRA","Brazil","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2005/bra_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
22834,76,"BRA","Brazil","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2005/bra_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
22835,76,"BRA","Brazil","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2005/bra_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
22836,76,"BRA","Brazil","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2005/bra_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
22837,76,"BRA","Brazil","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2006/bra_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
22838,76,"BRA","Brazil","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2006/bra_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
22839,76,"BRA","Brazil","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2006/bra_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
22840,76,"BRA","Brazil","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2006/bra_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
22841,76,"BRA","Brazil","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2006/bra_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
22842,76,"BRA","Brazil","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2006/bra_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
22843,76,"BRA","Brazil","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2006/bra_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
22844,76,"BRA","Brazil","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2006/bra_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
22845,76,"BRA","Brazil","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2007/bra_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
22846,76,"BRA","Brazil","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2007/bra_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
22847,76,"BRA","Brazil","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2007/bra_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
22848,76,"BRA","Brazil","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2007/bra_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
22849,76,"BRA","Brazil","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2007/bra_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
22850,76,"BRA","Brazil","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2007/bra_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
22851,76,"BRA","Brazil","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2007/bra_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
22852,76,"BRA","Brazil","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2007/bra_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
22853,76,"BRA","Brazil","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2008/bra_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
22854,76,"BRA","Brazil","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2008/bra_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
22855,76,"BRA","Brazil","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2008/bra_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
22856,76,"BRA","Brazil","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2008/bra_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
22857,76,"BRA","Brazil","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2008/bra_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
22858,76,"BRA","Brazil","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2008/bra_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
22859,76,"BRA","Brazil","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2008/bra_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
22860,76,"BRA","Brazil","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2008/bra_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
22861,76,"BRA","Brazil","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2009/bra_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
22862,76,"BRA","Brazil","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2009/bra_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
22863,76,"BRA","Brazil","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2009/bra_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
22864,76,"BRA","Brazil","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2009/bra_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
22865,76,"BRA","Brazil","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2009/bra_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
22866,76,"BRA","Brazil","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2009/bra_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
22867,76,"BRA","Brazil","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2009/bra_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
22868,76,"BRA","Brazil","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2009/bra_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
22869,76,"BRA","Brazil","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2010/bra_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
22870,76,"BRA","Brazil","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2010/bra_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
22871,76,"BRA","Brazil","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2010/bra_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
22872,76,"BRA","Brazil","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2010/bra_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
22873,76,"BRA","Brazil","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2010/bra_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
22874,76,"BRA","Brazil","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2010/bra_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
22875,76,"BRA","Brazil","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2010/bra_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
22876,76,"BRA","Brazil","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2010/bra_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
22877,76,"BRA","Brazil","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2011/bra_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
22878,76,"BRA","Brazil","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2011/bra_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
22879,76,"BRA","Brazil","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2011/bra_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
22880,76,"BRA","Brazil","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2011/bra_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
22881,76,"BRA","Brazil","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2011/bra_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
22882,76,"BRA","Brazil","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2011/bra_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
22883,76,"BRA","Brazil","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2011/bra_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
22884,76,"BRA","Brazil","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2011/bra_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
22885,76,"BRA","Brazil","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2012/bra_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
22886,76,"BRA","Brazil","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2012/bra_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
22887,76,"BRA","Brazil","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2012/bra_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
22888,76,"BRA","Brazil","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2012/bra_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
22889,76,"BRA","Brazil","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2012/bra_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
22890,76,"BRA","Brazil","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2012/bra_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
22891,76,"BRA","Brazil","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2012/bra_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
22892,76,"BRA","Brazil","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2012/bra_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
22893,76,"BRA","Brazil","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2013/bra_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
22894,76,"BRA","Brazil","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2013/bra_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
22895,76,"BRA","Brazil","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2013/bra_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
22896,76,"BRA","Brazil","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2013/bra_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
22897,76,"BRA","Brazil","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2013/bra_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
22898,76,"BRA","Brazil","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2013/bra_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
22899,76,"BRA","Brazil","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2013/bra_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
22900,76,"BRA","Brazil","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2013/bra_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
22901,76,"BRA","Brazil","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2014/bra_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
22902,76,"BRA","Brazil","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2014/bra_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
22903,76,"BRA","Brazil","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2014/bra_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
22904,76,"BRA","Brazil","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2014/bra_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
22905,76,"BRA","Brazil","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2014/bra_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
22906,76,"BRA","Brazil","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2014/bra_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
22907,76,"BRA","Brazil","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2014/bra_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
22908,76,"BRA","Brazil","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2014/bra_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
22909,76,"BRA","Brazil","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2015/bra_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
22910,76,"BRA","Brazil","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2015/bra_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
22911,76,"BRA","Brazil","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2015/bra_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
22912,76,"BRA","Brazil","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2015/bra_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
22913,76,"BRA","Brazil","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2015/bra_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
22914,76,"BRA","Brazil","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2015/bra_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
22915,76,"BRA","Brazil","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2015/bra_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
22916,76,"BRA","Brazil","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Annual/2015/bra_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
22917,124,"CAN","Canada","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2000/can_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
22918,124,"CAN","Canada","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2000/can_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
22919,124,"CAN","Canada","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2000/can_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
22920,124,"CAN","Canada","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2000/can_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
22921,124,"CAN","Canada","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2000/can_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
22922,124,"CAN","Canada","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2000/can_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
22923,124,"CAN","Canada","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2000/can_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
22924,124,"CAN","Canada","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2000/can_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
22925,124,"CAN","Canada","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2001/can_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
22926,124,"CAN","Canada","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2001/can_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
22927,124,"CAN","Canada","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2001/can_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
22928,124,"CAN","Canada","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2001/can_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
22929,124,"CAN","Canada","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2001/can_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
22930,124,"CAN","Canada","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2001/can_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
22931,124,"CAN","Canada","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2001/can_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
22932,124,"CAN","Canada","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2001/can_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
22933,124,"CAN","Canada","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2002/can_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
22934,124,"CAN","Canada","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2002/can_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
22935,124,"CAN","Canada","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2002/can_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
22936,124,"CAN","Canada","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2002/can_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
22937,124,"CAN","Canada","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2002/can_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
22938,124,"CAN","Canada","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2002/can_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
22939,124,"CAN","Canada","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2002/can_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
22940,124,"CAN","Canada","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2002/can_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
22941,124,"CAN","Canada","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2003/can_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
22942,124,"CAN","Canada","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2003/can_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
22943,124,"CAN","Canada","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2003/can_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
22944,124,"CAN","Canada","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2003/can_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
22945,124,"CAN","Canada","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2003/can_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
22946,124,"CAN","Canada","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2003/can_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
22947,124,"CAN","Canada","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2003/can_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
22948,124,"CAN","Canada","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2003/can_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
22949,124,"CAN","Canada","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2004/can_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
22950,124,"CAN","Canada","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2004/can_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
22951,124,"CAN","Canada","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2004/can_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
22952,124,"CAN","Canada","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2004/can_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
22953,124,"CAN","Canada","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2004/can_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
22954,124,"CAN","Canada","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2004/can_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
22955,124,"CAN","Canada","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2004/can_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
22956,124,"CAN","Canada","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2004/can_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
22957,124,"CAN","Canada","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2005/can_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
22958,124,"CAN","Canada","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2005/can_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
22959,124,"CAN","Canada","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2005/can_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
22960,124,"CAN","Canada","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2005/can_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
22961,124,"CAN","Canada","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2005/can_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
22962,124,"CAN","Canada","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2005/can_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
22963,124,"CAN","Canada","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2005/can_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
22964,124,"CAN","Canada","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2005/can_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
22965,124,"CAN","Canada","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2006/can_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
22966,124,"CAN","Canada","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2006/can_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
22967,124,"CAN","Canada","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2006/can_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
22968,124,"CAN","Canada","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2006/can_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
22969,124,"CAN","Canada","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2006/can_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
22970,124,"CAN","Canada","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2006/can_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
22971,124,"CAN","Canada","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2006/can_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
22972,124,"CAN","Canada","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2006/can_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
22973,124,"CAN","Canada","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2007/can_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
22974,124,"CAN","Canada","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2007/can_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
22975,124,"CAN","Canada","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2007/can_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
22976,124,"CAN","Canada","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2007/can_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
22977,124,"CAN","Canada","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2007/can_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
22978,124,"CAN","Canada","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2007/can_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
22979,124,"CAN","Canada","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2007/can_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
22980,124,"CAN","Canada","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2007/can_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
22981,124,"CAN","Canada","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2008/can_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
22982,124,"CAN","Canada","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2008/can_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
22983,124,"CAN","Canada","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2008/can_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
22984,124,"CAN","Canada","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2008/can_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
22985,124,"CAN","Canada","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2008/can_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
22986,124,"CAN","Canada","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2008/can_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
22987,124,"CAN","Canada","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2008/can_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
22988,124,"CAN","Canada","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2008/can_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
22989,124,"CAN","Canada","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2009/can_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
22990,124,"CAN","Canada","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2009/can_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
22991,124,"CAN","Canada","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2009/can_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
22992,124,"CAN","Canada","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2009/can_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
22993,124,"CAN","Canada","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2009/can_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
22994,124,"CAN","Canada","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2009/can_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
22995,124,"CAN","Canada","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2009/can_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
22996,124,"CAN","Canada","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2009/can_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
22997,124,"CAN","Canada","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2010/can_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
22998,124,"CAN","Canada","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2010/can_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
22999,124,"CAN","Canada","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2010/can_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
23000,124,"CAN","Canada","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2010/can_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
23001,124,"CAN","Canada","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2010/can_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
23002,124,"CAN","Canada","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2010/can_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
23003,124,"CAN","Canada","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2010/can_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
23004,124,"CAN","Canada","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2010/can_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
23005,124,"CAN","Canada","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2011/can_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
23006,124,"CAN","Canada","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2011/can_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
23007,124,"CAN","Canada","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2011/can_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
23008,124,"CAN","Canada","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2011/can_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
23009,124,"CAN","Canada","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2011/can_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
23010,124,"CAN","Canada","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2011/can_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
23011,124,"CAN","Canada","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2011/can_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
23012,124,"CAN","Canada","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2011/can_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
23013,124,"CAN","Canada","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2012/can_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
23014,124,"CAN","Canada","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2012/can_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
23015,124,"CAN","Canada","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2012/can_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
23016,124,"CAN","Canada","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2012/can_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
23017,124,"CAN","Canada","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2012/can_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
23018,124,"CAN","Canada","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2012/can_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
23019,124,"CAN","Canada","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2012/can_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
23020,124,"CAN","Canada","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2012/can_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
23021,124,"CAN","Canada","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2013/can_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
23022,124,"CAN","Canada","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2013/can_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
23023,124,"CAN","Canada","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2013/can_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
23024,124,"CAN","Canada","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2013/can_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
23025,124,"CAN","Canada","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2013/can_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
23026,124,"CAN","Canada","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2013/can_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
23027,124,"CAN","Canada","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2013/can_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
23028,124,"CAN","Canada","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2013/can_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
23029,124,"CAN","Canada","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2014/can_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
23030,124,"CAN","Canada","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2014/can_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
23031,124,"CAN","Canada","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2014/can_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
23032,124,"CAN","Canada","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2014/can_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
23033,124,"CAN","Canada","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2014/can_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
23034,124,"CAN","Canada","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2014/can_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
23035,124,"CAN","Canada","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2014/can_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
23036,124,"CAN","Canada","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2014/can_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
23037,124,"CAN","Canada","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2015/can_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
23038,124,"CAN","Canada","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2015/can_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
23039,124,"CAN","Canada","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2015/can_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
23040,124,"CAN","Canada","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2015/can_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
23041,124,"CAN","Canada","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2015/can_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
23042,124,"CAN","Canada","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2015/can_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
23043,124,"CAN","Canada","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2015/can_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
23044,124,"CAN","Canada","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Annual/2015/can_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
23045,152,"CHL","Chile","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2000/chl_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
23046,152,"CHL","Chile","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2000/chl_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
23047,152,"CHL","Chile","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2000/chl_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
23048,152,"CHL","Chile","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2000/chl_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
23049,152,"CHL","Chile","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2000/chl_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
23050,152,"CHL","Chile","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2000/chl_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
23051,152,"CHL","Chile","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2000/chl_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
23052,152,"CHL","Chile","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2000/chl_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
23053,152,"CHL","Chile","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2001/chl_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
23054,152,"CHL","Chile","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2001/chl_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
23055,152,"CHL","Chile","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2001/chl_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
23056,152,"CHL","Chile","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2001/chl_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
23057,152,"CHL","Chile","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2001/chl_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
23058,152,"CHL","Chile","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2001/chl_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
23059,152,"CHL","Chile","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2001/chl_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
23060,152,"CHL","Chile","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2001/chl_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
23061,152,"CHL","Chile","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2002/chl_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
23062,152,"CHL","Chile","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2002/chl_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
23063,152,"CHL","Chile","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2002/chl_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
23064,152,"CHL","Chile","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2002/chl_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
23065,152,"CHL","Chile","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2002/chl_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
23066,152,"CHL","Chile","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2002/chl_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
23067,152,"CHL","Chile","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2002/chl_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
23068,152,"CHL","Chile","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2002/chl_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
23069,152,"CHL","Chile","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2003/chl_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
23070,152,"CHL","Chile","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2003/chl_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
23071,152,"CHL","Chile","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2003/chl_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
23072,152,"CHL","Chile","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2003/chl_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
23073,152,"CHL","Chile","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2003/chl_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
23074,152,"CHL","Chile","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2003/chl_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
23075,152,"CHL","Chile","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2003/chl_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
23076,152,"CHL","Chile","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2003/chl_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
23077,152,"CHL","Chile","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2004/chl_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
23078,152,"CHL","Chile","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2004/chl_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
23079,152,"CHL","Chile","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2004/chl_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
23080,152,"CHL","Chile","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2004/chl_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
23081,152,"CHL","Chile","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2004/chl_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
23082,152,"CHL","Chile","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2004/chl_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
23083,152,"CHL","Chile","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2004/chl_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
23084,152,"CHL","Chile","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2004/chl_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
23085,152,"CHL","Chile","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2005/chl_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
23086,152,"CHL","Chile","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2005/chl_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
23087,152,"CHL","Chile","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2005/chl_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
23088,152,"CHL","Chile","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2005/chl_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
23089,152,"CHL","Chile","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2005/chl_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
23090,152,"CHL","Chile","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2005/chl_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
23091,152,"CHL","Chile","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2005/chl_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
23092,152,"CHL","Chile","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2005/chl_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
23093,152,"CHL","Chile","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2006/chl_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
23094,152,"CHL","Chile","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2006/chl_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
23095,152,"CHL","Chile","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2006/chl_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
23096,152,"CHL","Chile","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2006/chl_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
23097,152,"CHL","Chile","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2006/chl_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
23098,152,"CHL","Chile","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2006/chl_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
23099,152,"CHL","Chile","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2006/chl_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
23100,152,"CHL","Chile","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2006/chl_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
23101,152,"CHL","Chile","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2007/chl_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
23102,152,"CHL","Chile","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2007/chl_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
23103,152,"CHL","Chile","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2007/chl_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
23104,152,"CHL","Chile","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2007/chl_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
23105,152,"CHL","Chile","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2007/chl_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
23106,152,"CHL","Chile","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2007/chl_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
23107,152,"CHL","Chile","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2007/chl_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
23108,152,"CHL","Chile","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2007/chl_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
23109,152,"CHL","Chile","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2008/chl_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
23110,152,"CHL","Chile","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2008/chl_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
23111,152,"CHL","Chile","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2008/chl_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
23112,152,"CHL","Chile","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2008/chl_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
23113,152,"CHL","Chile","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2008/chl_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
23114,152,"CHL","Chile","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2008/chl_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
23115,152,"CHL","Chile","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2008/chl_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
23116,152,"CHL","Chile","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2008/chl_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
23117,152,"CHL","Chile","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2009/chl_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
23118,152,"CHL","Chile","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2009/chl_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
23119,152,"CHL","Chile","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2009/chl_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
23120,152,"CHL","Chile","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2009/chl_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
23121,152,"CHL","Chile","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2009/chl_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
23122,152,"CHL","Chile","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2009/chl_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
23123,152,"CHL","Chile","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2009/chl_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
23124,152,"CHL","Chile","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2009/chl_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
23125,152,"CHL","Chile","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2010/chl_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
23126,152,"CHL","Chile","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2010/chl_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
23127,152,"CHL","Chile","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2010/chl_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
23128,152,"CHL","Chile","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2010/chl_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
23129,152,"CHL","Chile","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2010/chl_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
23130,152,"CHL","Chile","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2010/chl_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
23131,152,"CHL","Chile","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2010/chl_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
23132,152,"CHL","Chile","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2010/chl_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
23133,152,"CHL","Chile","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2011/chl_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
23134,152,"CHL","Chile","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2011/chl_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
23135,152,"CHL","Chile","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2011/chl_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
23136,152,"CHL","Chile","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2011/chl_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
23137,152,"CHL","Chile","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2011/chl_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
23138,152,"CHL","Chile","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2011/chl_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
23139,152,"CHL","Chile","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2011/chl_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
23140,152,"CHL","Chile","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2011/chl_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
23141,152,"CHL","Chile","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2012/chl_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
23142,152,"CHL","Chile","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2012/chl_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
23143,152,"CHL","Chile","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2012/chl_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
23144,152,"CHL","Chile","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2012/chl_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
23145,152,"CHL","Chile","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2012/chl_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
23146,152,"CHL","Chile","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2012/chl_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
23147,152,"CHL","Chile","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2012/chl_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
23148,152,"CHL","Chile","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2012/chl_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
23149,152,"CHL","Chile","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2013/chl_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
23150,152,"CHL","Chile","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2013/chl_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
23151,152,"CHL","Chile","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2013/chl_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
23152,152,"CHL","Chile","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2013/chl_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
23153,152,"CHL","Chile","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2013/chl_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
23154,152,"CHL","Chile","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2013/chl_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
23155,152,"CHL","Chile","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2013/chl_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
23156,152,"CHL","Chile","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2013/chl_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
23157,152,"CHL","Chile","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2014/chl_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
23158,152,"CHL","Chile","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2014/chl_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
23159,152,"CHL","Chile","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2014/chl_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
23160,152,"CHL","Chile","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2014/chl_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
23161,152,"CHL","Chile","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2014/chl_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
23162,152,"CHL","Chile","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2014/chl_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
23163,152,"CHL","Chile","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2014/chl_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
23164,152,"CHL","Chile","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2014/chl_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
23165,152,"CHL","Chile","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2015/chl_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
23166,152,"CHL","Chile","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2015/chl_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
23167,152,"CHL","Chile","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2015/chl_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
23168,152,"CHL","Chile","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2015/chl_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
23169,152,"CHL","Chile","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2015/chl_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
23170,152,"CHL","Chile","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2015/chl_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
23171,152,"CHL","Chile","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2015/chl_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
23172,152,"CHL","Chile","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Annual/2015/chl_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
23173,4,"AFG","Afghanistan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2000/afg_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
23174,4,"AFG","Afghanistan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2000/afg_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
23175,4,"AFG","Afghanistan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2000/afg_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
23176,4,"AFG","Afghanistan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2000/afg_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
23177,4,"AFG","Afghanistan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2000/afg_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
23178,4,"AFG","Afghanistan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2000/afg_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
23179,4,"AFG","Afghanistan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2000/afg_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
23180,4,"AFG","Afghanistan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2000/afg_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
23181,4,"AFG","Afghanistan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2001/afg_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
23182,4,"AFG","Afghanistan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2001/afg_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
23183,4,"AFG","Afghanistan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2001/afg_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
23184,4,"AFG","Afghanistan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2001/afg_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
23185,4,"AFG","Afghanistan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2001/afg_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
23186,4,"AFG","Afghanistan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2001/afg_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
23187,4,"AFG","Afghanistan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2001/afg_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
23188,4,"AFG","Afghanistan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2001/afg_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
23189,4,"AFG","Afghanistan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2002/afg_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
23190,4,"AFG","Afghanistan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2002/afg_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
23191,4,"AFG","Afghanistan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2002/afg_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
23192,4,"AFG","Afghanistan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2002/afg_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
23193,4,"AFG","Afghanistan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2002/afg_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
23194,4,"AFG","Afghanistan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2002/afg_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
23195,4,"AFG","Afghanistan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2002/afg_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
23196,4,"AFG","Afghanistan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2002/afg_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
23197,4,"AFG","Afghanistan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2003/afg_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
23198,4,"AFG","Afghanistan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2003/afg_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
23199,4,"AFG","Afghanistan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2003/afg_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
23200,4,"AFG","Afghanistan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2003/afg_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
23201,4,"AFG","Afghanistan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2003/afg_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
23202,4,"AFG","Afghanistan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2003/afg_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
23203,4,"AFG","Afghanistan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2003/afg_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
23204,4,"AFG","Afghanistan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2003/afg_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
23205,4,"AFG","Afghanistan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2004/afg_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
23206,4,"AFG","Afghanistan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2004/afg_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
23207,4,"AFG","Afghanistan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2004/afg_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
23208,4,"AFG","Afghanistan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2004/afg_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
23209,4,"AFG","Afghanistan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2004/afg_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
23210,4,"AFG","Afghanistan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2004/afg_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
23211,4,"AFG","Afghanistan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2004/afg_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
23212,4,"AFG","Afghanistan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2004/afg_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
23213,4,"AFG","Afghanistan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2005/afg_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
23214,4,"AFG","Afghanistan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2005/afg_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
23215,4,"AFG","Afghanistan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2005/afg_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
23216,4,"AFG","Afghanistan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2005/afg_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
23217,4,"AFG","Afghanistan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2005/afg_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
23218,4,"AFG","Afghanistan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2005/afg_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
23219,4,"AFG","Afghanistan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2005/afg_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
23220,4,"AFG","Afghanistan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2005/afg_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
23221,4,"AFG","Afghanistan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2006/afg_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
23222,4,"AFG","Afghanistan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2006/afg_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
23223,4,"AFG","Afghanistan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2006/afg_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
23224,4,"AFG","Afghanistan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2006/afg_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
23225,4,"AFG","Afghanistan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2006/afg_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
23226,4,"AFG","Afghanistan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2006/afg_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
23227,4,"AFG","Afghanistan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2006/afg_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
23228,4,"AFG","Afghanistan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2006/afg_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
23229,4,"AFG","Afghanistan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2007/afg_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
23230,4,"AFG","Afghanistan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2007/afg_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
23231,4,"AFG","Afghanistan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2007/afg_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
23232,4,"AFG","Afghanistan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2007/afg_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
23233,4,"AFG","Afghanistan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2007/afg_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
23234,4,"AFG","Afghanistan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2007/afg_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
23235,4,"AFG","Afghanistan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2007/afg_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
23236,4,"AFG","Afghanistan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2007/afg_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
23237,4,"AFG","Afghanistan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2008/afg_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
23238,4,"AFG","Afghanistan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2008/afg_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
23239,4,"AFG","Afghanistan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2008/afg_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
23240,4,"AFG","Afghanistan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2008/afg_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
23241,4,"AFG","Afghanistan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2008/afg_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
23242,4,"AFG","Afghanistan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2008/afg_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
23243,4,"AFG","Afghanistan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2008/afg_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
23244,4,"AFG","Afghanistan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2008/afg_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
23245,4,"AFG","Afghanistan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2009/afg_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
23246,4,"AFG","Afghanistan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2009/afg_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
23247,4,"AFG","Afghanistan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2009/afg_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
23248,4,"AFG","Afghanistan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2009/afg_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
23249,4,"AFG","Afghanistan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2009/afg_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
23250,4,"AFG","Afghanistan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2009/afg_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
23251,4,"AFG","Afghanistan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2009/afg_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
23252,4,"AFG","Afghanistan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2009/afg_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
23253,4,"AFG","Afghanistan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2010/afg_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
23254,4,"AFG","Afghanistan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2010/afg_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
23255,4,"AFG","Afghanistan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2010/afg_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
23256,4,"AFG","Afghanistan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2010/afg_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
23257,4,"AFG","Afghanistan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2010/afg_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
23258,4,"AFG","Afghanistan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2010/afg_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
23259,4,"AFG","Afghanistan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2010/afg_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
23260,4,"AFG","Afghanistan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2010/afg_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
23261,4,"AFG","Afghanistan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2011/afg_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
23262,4,"AFG","Afghanistan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2011/afg_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
23263,4,"AFG","Afghanistan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2011/afg_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
23264,4,"AFG","Afghanistan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2011/afg_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
23265,4,"AFG","Afghanistan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2011/afg_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
23266,4,"AFG","Afghanistan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2011/afg_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
23267,4,"AFG","Afghanistan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2011/afg_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
23268,4,"AFG","Afghanistan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2011/afg_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
23269,4,"AFG","Afghanistan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2012/afg_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
23270,4,"AFG","Afghanistan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2012/afg_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
23271,4,"AFG","Afghanistan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2012/afg_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
23272,4,"AFG","Afghanistan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2012/afg_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
23273,4,"AFG","Afghanistan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2012/afg_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
23274,4,"AFG","Afghanistan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2012/afg_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
23275,4,"AFG","Afghanistan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2012/afg_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
23276,4,"AFG","Afghanistan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2012/afg_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
23277,4,"AFG","Afghanistan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2013/afg_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
23278,4,"AFG","Afghanistan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2013/afg_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
23279,4,"AFG","Afghanistan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2013/afg_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
23280,4,"AFG","Afghanistan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2013/afg_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
23281,4,"AFG","Afghanistan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2013/afg_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
23282,4,"AFG","Afghanistan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2013/afg_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
23283,4,"AFG","Afghanistan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2013/afg_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
23284,4,"AFG","Afghanistan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2013/afg_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
23285,4,"AFG","Afghanistan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2014/afg_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
23286,4,"AFG","Afghanistan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2014/afg_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
23287,4,"AFG","Afghanistan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2014/afg_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
23288,4,"AFG","Afghanistan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2014/afg_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
23289,4,"AFG","Afghanistan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2014/afg_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
23290,4,"AFG","Afghanistan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2014/afg_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
23291,4,"AFG","Afghanistan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2014/afg_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
23292,4,"AFG","Afghanistan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2014/afg_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
23293,4,"AFG","Afghanistan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2015/afg_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
23294,4,"AFG","Afghanistan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2015/afg_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
23295,4,"AFG","Afghanistan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2015/afg_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
23296,4,"AFG","Afghanistan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2015/afg_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
23297,4,"AFG","Afghanistan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2015/afg_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
23298,4,"AFG","Afghanistan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2015/afg_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
23299,4,"AFG","Afghanistan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2015/afg_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
23300,4,"AFG","Afghanistan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Annual/2015/afg_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
23301,8,"ALB","Albania","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2000/alb_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
23302,8,"ALB","Albania","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2000/alb_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
23303,8,"ALB","Albania","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2000/alb_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
23304,8,"ALB","Albania","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2000/alb_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
23305,8,"ALB","Albania","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2000/alb_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
23306,8,"ALB","Albania","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2000/alb_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
23307,8,"ALB","Albania","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2000/alb_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
23308,8,"ALB","Albania","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2000/alb_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
23309,8,"ALB","Albania","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2001/alb_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
23310,8,"ALB","Albania","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2001/alb_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
23311,8,"ALB","Albania","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2001/alb_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
23312,8,"ALB","Albania","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2001/alb_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
23313,8,"ALB","Albania","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2001/alb_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
23314,8,"ALB","Albania","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2001/alb_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
23315,8,"ALB","Albania","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2001/alb_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
23316,8,"ALB","Albania","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2001/alb_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
23317,8,"ALB","Albania","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2002/alb_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
23318,8,"ALB","Albania","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2002/alb_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
23319,8,"ALB","Albania","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2002/alb_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
23320,8,"ALB","Albania","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2002/alb_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
23321,8,"ALB","Albania","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2002/alb_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
23322,8,"ALB","Albania","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2002/alb_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
23323,8,"ALB","Albania","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2002/alb_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
23324,8,"ALB","Albania","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2002/alb_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
23325,8,"ALB","Albania","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2003/alb_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
23326,8,"ALB","Albania","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2003/alb_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
23327,8,"ALB","Albania","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2003/alb_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
23328,8,"ALB","Albania","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2003/alb_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
23329,8,"ALB","Albania","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2003/alb_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
23330,8,"ALB","Albania","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2003/alb_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
23331,8,"ALB","Albania","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2003/alb_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
23332,8,"ALB","Albania","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2003/alb_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
23333,8,"ALB","Albania","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2004/alb_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
23334,8,"ALB","Albania","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2004/alb_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
23335,8,"ALB","Albania","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2004/alb_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
23336,8,"ALB","Albania","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2004/alb_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
23337,8,"ALB","Albania","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2004/alb_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
23338,8,"ALB","Albania","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2004/alb_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
23339,8,"ALB","Albania","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2004/alb_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
23340,8,"ALB","Albania","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2004/alb_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
23341,8,"ALB","Albania","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2005/alb_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
23342,8,"ALB","Albania","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2005/alb_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
23343,8,"ALB","Albania","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2005/alb_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
23344,8,"ALB","Albania","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2005/alb_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
23345,8,"ALB","Albania","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2005/alb_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
23346,8,"ALB","Albania","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2005/alb_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
23347,8,"ALB","Albania","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2005/alb_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
23348,8,"ALB","Albania","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2005/alb_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
23349,8,"ALB","Albania","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2006/alb_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
23350,8,"ALB","Albania","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2006/alb_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
23351,8,"ALB","Albania","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2006/alb_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
23352,8,"ALB","Albania","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2006/alb_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
23353,8,"ALB","Albania","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2006/alb_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
23354,8,"ALB","Albania","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2006/alb_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
23355,8,"ALB","Albania","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2006/alb_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
23356,8,"ALB","Albania","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2006/alb_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
23357,8,"ALB","Albania","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2007/alb_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
23358,8,"ALB","Albania","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2007/alb_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
23359,8,"ALB","Albania","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2007/alb_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
23360,8,"ALB","Albania","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2007/alb_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
23361,8,"ALB","Albania","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2007/alb_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
23362,8,"ALB","Albania","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2007/alb_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
23363,8,"ALB","Albania","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2007/alb_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
23364,8,"ALB","Albania","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2007/alb_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
23365,8,"ALB","Albania","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2008/alb_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
23366,8,"ALB","Albania","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2008/alb_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
23367,8,"ALB","Albania","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2008/alb_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
23368,8,"ALB","Albania","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2008/alb_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
23369,8,"ALB","Albania","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2008/alb_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
23370,8,"ALB","Albania","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2008/alb_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
23371,8,"ALB","Albania","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2008/alb_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
23372,8,"ALB","Albania","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2008/alb_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
23373,8,"ALB","Albania","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2009/alb_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
23374,8,"ALB","Albania","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2009/alb_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
23375,8,"ALB","Albania","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2009/alb_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
23376,8,"ALB","Albania","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2009/alb_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
23377,8,"ALB","Albania","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2009/alb_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
23378,8,"ALB","Albania","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2009/alb_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
23379,8,"ALB","Albania","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2009/alb_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
23380,8,"ALB","Albania","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2009/alb_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
23381,8,"ALB","Albania","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2010/alb_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
23382,8,"ALB","Albania","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2010/alb_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
23383,8,"ALB","Albania","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2010/alb_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
23384,8,"ALB","Albania","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2010/alb_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
23385,8,"ALB","Albania","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2010/alb_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
23386,8,"ALB","Albania","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2010/alb_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
23387,8,"ALB","Albania","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2010/alb_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
23388,8,"ALB","Albania","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2010/alb_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
23389,8,"ALB","Albania","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2011/alb_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
23390,8,"ALB","Albania","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2011/alb_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
23391,8,"ALB","Albania","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2011/alb_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
23392,8,"ALB","Albania","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2011/alb_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
23393,8,"ALB","Albania","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2011/alb_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
23394,8,"ALB","Albania","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2011/alb_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
23395,8,"ALB","Albania","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2011/alb_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
23396,8,"ALB","Albania","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2011/alb_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
23397,8,"ALB","Albania","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2012/alb_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
23398,8,"ALB","Albania","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2012/alb_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
23399,8,"ALB","Albania","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2012/alb_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
23400,8,"ALB","Albania","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2012/alb_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
23401,8,"ALB","Albania","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2012/alb_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
23402,8,"ALB","Albania","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2012/alb_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
23403,8,"ALB","Albania","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2012/alb_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
23404,8,"ALB","Albania","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2012/alb_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
23405,8,"ALB","Albania","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2013/alb_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
23406,8,"ALB","Albania","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2013/alb_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
23407,8,"ALB","Albania","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2013/alb_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
23408,8,"ALB","Albania","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2013/alb_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
23409,8,"ALB","Albania","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2013/alb_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
23410,8,"ALB","Albania","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2013/alb_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
23411,8,"ALB","Albania","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2013/alb_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
23412,8,"ALB","Albania","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2013/alb_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
23413,8,"ALB","Albania","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2014/alb_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
23414,8,"ALB","Albania","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2014/alb_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
23415,8,"ALB","Albania","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2014/alb_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
23416,8,"ALB","Albania","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2014/alb_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
23417,8,"ALB","Albania","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2014/alb_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
23418,8,"ALB","Albania","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2014/alb_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
23419,8,"ALB","Albania","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2014/alb_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
23420,8,"ALB","Albania","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2014/alb_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
23421,8,"ALB","Albania","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2015/alb_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
23422,8,"ALB","Albania","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2015/alb_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
23423,8,"ALB","Albania","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2015/alb_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
23424,8,"ALB","Albania","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2015/alb_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
23425,8,"ALB","Albania","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2015/alb_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
23426,8,"ALB","Albania","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2015/alb_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
23427,8,"ALB","Albania","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2015/alb_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
23428,8,"ALB","Albania","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Annual/2015/alb_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
23429,10,"ATA","Antarctica","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2000/ata_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
23430,10,"ATA","Antarctica","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2000/ata_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
23431,10,"ATA","Antarctica","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2000/ata_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
23432,10,"ATA","Antarctica","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2000/ata_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
23433,10,"ATA","Antarctica","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2000/ata_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
23434,10,"ATA","Antarctica","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2000/ata_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
23435,10,"ATA","Antarctica","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2000/ata_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
23436,10,"ATA","Antarctica","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2000/ata_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
23437,10,"ATA","Antarctica","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2001/ata_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
23438,10,"ATA","Antarctica","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2001/ata_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
23439,10,"ATA","Antarctica","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2001/ata_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
23440,10,"ATA","Antarctica","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2001/ata_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
23441,10,"ATA","Antarctica","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2001/ata_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
23442,10,"ATA","Antarctica","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2001/ata_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
23443,10,"ATA","Antarctica","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2001/ata_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
23444,10,"ATA","Antarctica","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2001/ata_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
23445,10,"ATA","Antarctica","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2002/ata_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
23446,10,"ATA","Antarctica","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2002/ata_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
23447,10,"ATA","Antarctica","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2002/ata_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
23448,10,"ATA","Antarctica","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2002/ata_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
23449,10,"ATA","Antarctica","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2002/ata_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
23450,10,"ATA","Antarctica","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2002/ata_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
23451,10,"ATA","Antarctica","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2002/ata_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
23452,10,"ATA","Antarctica","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2002/ata_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
23453,10,"ATA","Antarctica","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2003/ata_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
23454,10,"ATA","Antarctica","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2003/ata_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
23455,10,"ATA","Antarctica","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2003/ata_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
23456,10,"ATA","Antarctica","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2003/ata_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
23457,10,"ATA","Antarctica","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2003/ata_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
23458,10,"ATA","Antarctica","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2003/ata_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
23459,10,"ATA","Antarctica","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2003/ata_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
23460,10,"ATA","Antarctica","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2003/ata_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
23461,10,"ATA","Antarctica","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2004/ata_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
23462,10,"ATA","Antarctica","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2004/ata_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
23463,10,"ATA","Antarctica","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2004/ata_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
23464,10,"ATA","Antarctica","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2004/ata_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
23465,10,"ATA","Antarctica","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2004/ata_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
23466,10,"ATA","Antarctica","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2004/ata_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
23467,10,"ATA","Antarctica","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2004/ata_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
23468,10,"ATA","Antarctica","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2004/ata_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
23469,10,"ATA","Antarctica","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2005/ata_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
23470,10,"ATA","Antarctica","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2005/ata_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
23471,10,"ATA","Antarctica","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2005/ata_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
23472,10,"ATA","Antarctica","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2005/ata_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
23473,10,"ATA","Antarctica","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2005/ata_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
23474,10,"ATA","Antarctica","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2005/ata_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
23475,10,"ATA","Antarctica","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2005/ata_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
23476,10,"ATA","Antarctica","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2005/ata_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
23477,10,"ATA","Antarctica","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2006/ata_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
23478,10,"ATA","Antarctica","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2006/ata_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
23479,10,"ATA","Antarctica","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2006/ata_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
23480,10,"ATA","Antarctica","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2006/ata_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
23481,10,"ATA","Antarctica","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2006/ata_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
23482,10,"ATA","Antarctica","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2006/ata_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
23483,10,"ATA","Antarctica","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2006/ata_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
23484,10,"ATA","Antarctica","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2006/ata_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
23485,10,"ATA","Antarctica","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2007/ata_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
23486,10,"ATA","Antarctica","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2007/ata_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
23487,10,"ATA","Antarctica","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2007/ata_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
23488,10,"ATA","Antarctica","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2007/ata_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
23489,10,"ATA","Antarctica","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2007/ata_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
23490,10,"ATA","Antarctica","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2007/ata_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
23491,10,"ATA","Antarctica","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2007/ata_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
23492,10,"ATA","Antarctica","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2007/ata_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
23493,10,"ATA","Antarctica","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2008/ata_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
23494,10,"ATA","Antarctica","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2008/ata_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
23495,10,"ATA","Antarctica","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2008/ata_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
23496,10,"ATA","Antarctica","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2008/ata_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
23497,10,"ATA","Antarctica","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2008/ata_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
23498,10,"ATA","Antarctica","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2008/ata_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
23499,10,"ATA","Antarctica","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2008/ata_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
23500,10,"ATA","Antarctica","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2008/ata_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
23501,10,"ATA","Antarctica","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2009/ata_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
23502,10,"ATA","Antarctica","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2009/ata_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
23503,10,"ATA","Antarctica","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2009/ata_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
23504,10,"ATA","Antarctica","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2009/ata_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
23505,10,"ATA","Antarctica","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2009/ata_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
23506,10,"ATA","Antarctica","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2009/ata_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
23507,10,"ATA","Antarctica","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2009/ata_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
23508,10,"ATA","Antarctica","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2009/ata_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
23509,10,"ATA","Antarctica","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2010/ata_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
23510,10,"ATA","Antarctica","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2010/ata_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
23511,10,"ATA","Antarctica","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2010/ata_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
23512,10,"ATA","Antarctica","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2010/ata_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
23513,10,"ATA","Antarctica","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2010/ata_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
23514,10,"ATA","Antarctica","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2010/ata_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
23515,10,"ATA","Antarctica","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2010/ata_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
23516,10,"ATA","Antarctica","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2010/ata_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
23517,10,"ATA","Antarctica","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2011/ata_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
23518,10,"ATA","Antarctica","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2011/ata_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
23519,10,"ATA","Antarctica","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2011/ata_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
23520,10,"ATA","Antarctica","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2011/ata_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
23521,10,"ATA","Antarctica","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2011/ata_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
23522,10,"ATA","Antarctica","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2011/ata_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
23523,10,"ATA","Antarctica","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2011/ata_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
23524,10,"ATA","Antarctica","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2011/ata_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
23525,10,"ATA","Antarctica","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2012/ata_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
23526,10,"ATA","Antarctica","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2012/ata_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
23527,10,"ATA","Antarctica","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2012/ata_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
23528,10,"ATA","Antarctica","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2012/ata_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
23529,10,"ATA","Antarctica","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2012/ata_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
23530,10,"ATA","Antarctica","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2012/ata_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
23531,10,"ATA","Antarctica","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2012/ata_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
23532,10,"ATA","Antarctica","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2012/ata_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
23533,10,"ATA","Antarctica","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2013/ata_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
23534,10,"ATA","Antarctica","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2013/ata_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
23535,10,"ATA","Antarctica","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2013/ata_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
23536,10,"ATA","Antarctica","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2013/ata_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
23537,10,"ATA","Antarctica","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2013/ata_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
23538,10,"ATA","Antarctica","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2013/ata_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
23539,10,"ATA","Antarctica","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2013/ata_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
23540,10,"ATA","Antarctica","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2013/ata_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
23541,10,"ATA","Antarctica","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2014/ata_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
23542,10,"ATA","Antarctica","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2014/ata_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
23543,10,"ATA","Antarctica","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2014/ata_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
23544,10,"ATA","Antarctica","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2014/ata_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
23545,10,"ATA","Antarctica","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2014/ata_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
23546,10,"ATA","Antarctica","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2014/ata_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
23547,10,"ATA","Antarctica","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2014/ata_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
23548,10,"ATA","Antarctica","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2014/ata_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
23549,10,"ATA","Antarctica","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2015/ata_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
23550,10,"ATA","Antarctica","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2015/ata_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
23551,10,"ATA","Antarctica","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2015/ata_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
23552,10,"ATA","Antarctica","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2015/ata_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
23553,10,"ATA","Antarctica","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2015/ata_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
23554,10,"ATA","Antarctica","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2015/ata_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
23555,10,"ATA","Antarctica","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2015/ata_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
23556,10,"ATA","Antarctica","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Annual/2015/ata_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
23557,12,"DZA","Algeria","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2000/dza_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
23558,12,"DZA","Algeria","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2000/dza_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
23559,12,"DZA","Algeria","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2000/dza_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
23560,12,"DZA","Algeria","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2000/dza_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
23561,12,"DZA","Algeria","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2000/dza_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
23562,12,"DZA","Algeria","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2000/dza_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
23563,12,"DZA","Algeria","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2000/dza_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
23564,12,"DZA","Algeria","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2000/dza_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
23565,12,"DZA","Algeria","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2001/dza_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
23566,12,"DZA","Algeria","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2001/dza_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
23567,12,"DZA","Algeria","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2001/dza_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
23568,12,"DZA","Algeria","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2001/dza_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
23569,12,"DZA","Algeria","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2001/dza_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
23570,12,"DZA","Algeria","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2001/dza_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
23571,12,"DZA","Algeria","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2001/dza_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
23572,12,"DZA","Algeria","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2001/dza_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
23573,12,"DZA","Algeria","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2002/dza_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
23574,12,"DZA","Algeria","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2002/dza_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
23575,12,"DZA","Algeria","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2002/dza_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
23576,12,"DZA","Algeria","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2002/dza_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
23577,12,"DZA","Algeria","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2002/dza_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
23578,12,"DZA","Algeria","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2002/dza_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
23579,12,"DZA","Algeria","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2002/dza_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
23580,12,"DZA","Algeria","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2002/dza_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
23581,12,"DZA","Algeria","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2003/dza_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
23582,12,"DZA","Algeria","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2003/dza_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
23583,12,"DZA","Algeria","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2003/dza_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
23584,12,"DZA","Algeria","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2003/dza_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
23585,12,"DZA","Algeria","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2003/dza_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
23586,12,"DZA","Algeria","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2003/dza_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
23587,12,"DZA","Algeria","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2003/dza_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
23588,12,"DZA","Algeria","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2003/dza_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
23589,12,"DZA","Algeria","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2004/dza_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
23590,12,"DZA","Algeria","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2004/dza_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
23591,12,"DZA","Algeria","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2004/dza_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
23592,12,"DZA","Algeria","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2004/dza_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
23593,12,"DZA","Algeria","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2004/dza_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
23594,12,"DZA","Algeria","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2004/dza_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
23595,12,"DZA","Algeria","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2004/dza_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
23596,12,"DZA","Algeria","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2004/dza_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
23597,12,"DZA","Algeria","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2005/dza_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
23598,12,"DZA","Algeria","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2005/dza_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
23599,12,"DZA","Algeria","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2005/dza_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
23600,12,"DZA","Algeria","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2005/dza_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
23601,12,"DZA","Algeria","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2005/dza_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
23602,12,"DZA","Algeria","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2005/dza_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
23603,12,"DZA","Algeria","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2005/dza_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
23604,12,"DZA","Algeria","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2005/dza_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
23605,12,"DZA","Algeria","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2006/dza_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
23606,12,"DZA","Algeria","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2006/dza_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
23607,12,"DZA","Algeria","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2006/dza_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
23608,12,"DZA","Algeria","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2006/dza_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
23609,12,"DZA","Algeria","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2006/dza_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
23610,12,"DZA","Algeria","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2006/dza_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
23611,12,"DZA","Algeria","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2006/dza_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
23612,12,"DZA","Algeria","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2006/dza_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
23613,12,"DZA","Algeria","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2007/dza_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
23614,12,"DZA","Algeria","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2007/dza_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
23615,12,"DZA","Algeria","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2007/dza_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
23616,12,"DZA","Algeria","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2007/dza_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
23617,12,"DZA","Algeria","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2007/dza_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
23618,12,"DZA","Algeria","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2007/dza_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
23619,12,"DZA","Algeria","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2007/dza_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
23620,12,"DZA","Algeria","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2007/dza_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
23621,12,"DZA","Algeria","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2008/dza_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
23622,12,"DZA","Algeria","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2008/dza_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
23623,12,"DZA","Algeria","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2008/dza_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
23624,12,"DZA","Algeria","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2008/dza_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
23625,12,"DZA","Algeria","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2008/dza_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
23626,12,"DZA","Algeria","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2008/dza_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
23627,12,"DZA","Algeria","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2008/dza_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
23628,12,"DZA","Algeria","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2008/dza_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
23629,12,"DZA","Algeria","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2009/dza_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
23630,12,"DZA","Algeria","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2009/dza_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
23631,12,"DZA","Algeria","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2009/dza_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
23632,12,"DZA","Algeria","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2009/dza_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
23633,12,"DZA","Algeria","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2009/dza_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
23634,12,"DZA","Algeria","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2009/dza_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
23635,12,"DZA","Algeria","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2009/dza_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
23636,12,"DZA","Algeria","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2009/dza_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
23637,12,"DZA","Algeria","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2010/dza_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
23638,12,"DZA","Algeria","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2010/dza_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
23639,12,"DZA","Algeria","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2010/dza_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
23640,12,"DZA","Algeria","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2010/dza_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
23641,12,"DZA","Algeria","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2010/dza_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
23642,12,"DZA","Algeria","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2010/dza_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
23643,12,"DZA","Algeria","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2010/dza_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
23644,12,"DZA","Algeria","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2010/dza_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
23645,12,"DZA","Algeria","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2011/dza_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
23646,12,"DZA","Algeria","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2011/dza_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
23647,12,"DZA","Algeria","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2011/dza_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
23648,12,"DZA","Algeria","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2011/dza_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
23649,12,"DZA","Algeria","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2011/dza_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
23650,12,"DZA","Algeria","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2011/dza_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
23651,12,"DZA","Algeria","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2011/dza_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
23652,12,"DZA","Algeria","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2011/dza_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
23653,12,"DZA","Algeria","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2012/dza_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
23654,12,"DZA","Algeria","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2012/dza_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
23655,12,"DZA","Algeria","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2012/dza_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
23656,12,"DZA","Algeria","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2012/dza_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
23657,12,"DZA","Algeria","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2012/dza_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
23658,12,"DZA","Algeria","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2012/dza_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
23659,12,"DZA","Algeria","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2012/dza_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
23660,12,"DZA","Algeria","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2012/dza_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
23661,12,"DZA","Algeria","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2013/dza_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
23662,12,"DZA","Algeria","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2013/dza_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
23663,12,"DZA","Algeria","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2013/dza_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
23664,12,"DZA","Algeria","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2013/dza_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
23665,12,"DZA","Algeria","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2013/dza_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
23666,12,"DZA","Algeria","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2013/dza_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
23667,12,"DZA","Algeria","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2013/dza_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
23668,12,"DZA","Algeria","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2013/dza_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
23669,12,"DZA","Algeria","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2014/dza_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
23670,12,"DZA","Algeria","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2014/dza_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
23671,12,"DZA","Algeria","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2014/dza_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
23672,12,"DZA","Algeria","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2014/dza_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
23673,12,"DZA","Algeria","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2014/dza_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
23674,12,"DZA","Algeria","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2014/dza_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
23675,12,"DZA","Algeria","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2014/dza_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
23676,12,"DZA","Algeria","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2014/dza_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
23677,12,"DZA","Algeria","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2015/dza_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
23678,12,"DZA","Algeria","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2015/dza_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
23679,12,"DZA","Algeria","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2015/dza_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
23680,12,"DZA","Algeria","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2015/dza_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
23681,12,"DZA","Algeria","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2015/dza_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
23682,12,"DZA","Algeria","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2015/dza_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
23683,12,"DZA","Algeria","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2015/dza_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
23684,12,"DZA","Algeria","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Annual/2015/dza_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
23685,16,"ASM","American Samoa","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2000/asm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
23686,16,"ASM","American Samoa","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2000/asm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
23687,16,"ASM","American Samoa","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2000/asm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
23688,16,"ASM","American Samoa","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2000/asm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
23689,16,"ASM","American Samoa","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2000/asm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
23690,16,"ASM","American Samoa","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2000/asm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
23691,16,"ASM","American Samoa","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2000/asm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
23692,16,"ASM","American Samoa","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2000/asm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
23693,16,"ASM","American Samoa","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2001/asm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
23694,16,"ASM","American Samoa","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2001/asm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
23695,16,"ASM","American Samoa","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2001/asm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
23696,16,"ASM","American Samoa","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2001/asm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
23697,16,"ASM","American Samoa","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2001/asm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
23698,16,"ASM","American Samoa","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2001/asm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
23699,16,"ASM","American Samoa","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2001/asm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
23700,16,"ASM","American Samoa","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2001/asm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
23701,16,"ASM","American Samoa","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2002/asm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
23702,16,"ASM","American Samoa","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2002/asm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
23703,16,"ASM","American Samoa","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2002/asm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
23704,16,"ASM","American Samoa","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2002/asm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
23705,16,"ASM","American Samoa","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2002/asm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
23706,16,"ASM","American Samoa","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2002/asm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
23707,16,"ASM","American Samoa","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2002/asm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
23708,16,"ASM","American Samoa","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2002/asm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
23709,16,"ASM","American Samoa","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2003/asm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
23710,16,"ASM","American Samoa","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2003/asm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
23711,16,"ASM","American Samoa","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2003/asm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
23712,16,"ASM","American Samoa","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2003/asm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
23713,16,"ASM","American Samoa","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2003/asm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
23714,16,"ASM","American Samoa","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2003/asm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
23715,16,"ASM","American Samoa","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2003/asm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
23716,16,"ASM","American Samoa","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2003/asm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
23717,16,"ASM","American Samoa","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2004/asm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
23718,16,"ASM","American Samoa","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2004/asm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
23719,16,"ASM","American Samoa","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2004/asm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
23720,16,"ASM","American Samoa","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2004/asm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
23721,16,"ASM","American Samoa","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2004/asm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
23722,16,"ASM","American Samoa","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2004/asm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
23723,16,"ASM","American Samoa","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2004/asm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
23724,16,"ASM","American Samoa","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2004/asm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
23725,16,"ASM","American Samoa","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2005/asm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
23726,16,"ASM","American Samoa","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2005/asm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
23727,16,"ASM","American Samoa","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2005/asm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
23728,16,"ASM","American Samoa","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2005/asm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
23729,16,"ASM","American Samoa","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2005/asm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
23730,16,"ASM","American Samoa","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2005/asm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
23731,16,"ASM","American Samoa","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2005/asm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
23732,16,"ASM","American Samoa","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2005/asm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
23733,16,"ASM","American Samoa","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2006/asm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
23734,16,"ASM","American Samoa","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2006/asm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
23735,16,"ASM","American Samoa","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2006/asm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
23736,16,"ASM","American Samoa","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2006/asm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
23737,16,"ASM","American Samoa","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2006/asm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
23738,16,"ASM","American Samoa","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2006/asm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
23739,16,"ASM","American Samoa","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2006/asm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
23740,16,"ASM","American Samoa","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2006/asm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
23741,16,"ASM","American Samoa","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2007/asm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
23742,16,"ASM","American Samoa","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2007/asm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
23743,16,"ASM","American Samoa","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2007/asm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
23744,16,"ASM","American Samoa","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2007/asm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
23745,16,"ASM","American Samoa","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2007/asm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
23746,16,"ASM","American Samoa","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2007/asm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
23747,16,"ASM","American Samoa","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2007/asm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
23748,16,"ASM","American Samoa","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2007/asm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
23749,16,"ASM","American Samoa","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2008/asm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
23750,16,"ASM","American Samoa","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2008/asm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
23751,16,"ASM","American Samoa","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2008/asm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
23752,16,"ASM","American Samoa","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2008/asm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
23753,16,"ASM","American Samoa","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2008/asm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
23754,16,"ASM","American Samoa","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2008/asm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
23755,16,"ASM","American Samoa","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2008/asm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
23756,16,"ASM","American Samoa","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2008/asm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
23757,16,"ASM","American Samoa","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2009/asm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
23758,16,"ASM","American Samoa","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2009/asm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
23759,16,"ASM","American Samoa","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2009/asm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
23760,16,"ASM","American Samoa","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2009/asm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
23761,16,"ASM","American Samoa","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2009/asm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
23762,16,"ASM","American Samoa","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2009/asm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
23763,16,"ASM","American Samoa","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2009/asm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
23764,16,"ASM","American Samoa","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2009/asm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
23765,16,"ASM","American Samoa","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2010/asm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
23766,16,"ASM","American Samoa","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2010/asm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
23767,16,"ASM","American Samoa","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2010/asm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
23768,16,"ASM","American Samoa","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2010/asm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
23769,16,"ASM","American Samoa","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2010/asm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
23770,16,"ASM","American Samoa","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2010/asm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
23771,16,"ASM","American Samoa","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2010/asm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
23772,16,"ASM","American Samoa","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2010/asm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
23773,16,"ASM","American Samoa","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2011/asm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
23774,16,"ASM","American Samoa","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2011/asm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
23775,16,"ASM","American Samoa","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2011/asm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
23776,16,"ASM","American Samoa","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2011/asm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
23777,16,"ASM","American Samoa","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2011/asm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
23778,16,"ASM","American Samoa","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2011/asm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
23779,16,"ASM","American Samoa","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2011/asm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
23780,16,"ASM","American Samoa","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2011/asm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
23781,16,"ASM","American Samoa","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2012/asm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
23782,16,"ASM","American Samoa","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2012/asm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
23783,16,"ASM","American Samoa","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2012/asm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
23784,16,"ASM","American Samoa","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2012/asm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
23785,16,"ASM","American Samoa","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2012/asm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
23786,16,"ASM","American Samoa","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2012/asm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
23787,16,"ASM","American Samoa","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2012/asm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
23788,16,"ASM","American Samoa","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2012/asm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
23789,16,"ASM","American Samoa","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2013/asm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
23790,16,"ASM","American Samoa","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2013/asm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
23791,16,"ASM","American Samoa","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2013/asm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
23792,16,"ASM","American Samoa","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2013/asm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
23793,16,"ASM","American Samoa","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2013/asm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
23794,16,"ASM","American Samoa","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2013/asm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
23795,16,"ASM","American Samoa","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2013/asm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
23796,16,"ASM","American Samoa","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2013/asm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
23797,16,"ASM","American Samoa","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2014/asm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
23798,16,"ASM","American Samoa","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2014/asm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
23799,16,"ASM","American Samoa","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2014/asm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
23800,16,"ASM","American Samoa","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2014/asm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
23801,16,"ASM","American Samoa","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2014/asm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
23802,16,"ASM","American Samoa","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2014/asm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
23803,16,"ASM","American Samoa","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2014/asm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
23804,16,"ASM","American Samoa","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2014/asm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
23805,16,"ASM","American Samoa","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2015/asm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
23806,16,"ASM","American Samoa","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2015/asm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
23807,16,"ASM","American Samoa","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2015/asm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
23808,16,"ASM","American Samoa","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2015/asm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
23809,16,"ASM","American Samoa","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2015/asm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
23810,16,"ASM","American Samoa","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2015/asm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
23811,16,"ASM","American Samoa","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2015/asm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
23812,16,"ASM","American Samoa","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Annual/2015/asm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
23813,20,"AND","Andorra","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2000/and_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
23814,20,"AND","Andorra","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2000/and_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
23815,20,"AND","Andorra","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2000/and_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
23816,20,"AND","Andorra","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2000/and_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
23817,20,"AND","Andorra","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2000/and_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
23818,20,"AND","Andorra","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2000/and_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
23819,20,"AND","Andorra","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2000/and_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
23820,20,"AND","Andorra","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2000/and_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
23821,20,"AND","Andorra","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2001/and_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
23822,20,"AND","Andorra","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2001/and_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
23823,20,"AND","Andorra","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2001/and_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
23824,20,"AND","Andorra","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2001/and_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
23825,20,"AND","Andorra","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2001/and_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
23826,20,"AND","Andorra","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2001/and_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
23827,20,"AND","Andorra","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2001/and_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
23828,20,"AND","Andorra","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2001/and_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
23829,20,"AND","Andorra","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2002/and_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
23830,20,"AND","Andorra","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2002/and_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
23831,20,"AND","Andorra","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2002/and_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
23832,20,"AND","Andorra","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2002/and_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
23833,20,"AND","Andorra","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2002/and_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
23834,20,"AND","Andorra","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2002/and_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
23835,20,"AND","Andorra","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2002/and_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
23836,20,"AND","Andorra","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2002/and_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
23837,20,"AND","Andorra","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2003/and_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
23838,20,"AND","Andorra","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2003/and_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
23839,20,"AND","Andorra","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2003/and_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
23840,20,"AND","Andorra","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2003/and_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
23841,20,"AND","Andorra","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2003/and_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
23842,20,"AND","Andorra","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2003/and_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
23843,20,"AND","Andorra","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2003/and_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
23844,20,"AND","Andorra","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2003/and_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
23845,20,"AND","Andorra","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2004/and_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
23846,20,"AND","Andorra","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2004/and_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
23847,20,"AND","Andorra","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2004/and_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
23848,20,"AND","Andorra","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2004/and_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
23849,20,"AND","Andorra","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2004/and_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
23850,20,"AND","Andorra","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2004/and_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
23851,20,"AND","Andorra","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2004/and_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
23852,20,"AND","Andorra","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2004/and_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
23853,20,"AND","Andorra","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2005/and_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
23854,20,"AND","Andorra","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2005/and_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
23855,20,"AND","Andorra","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2005/and_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
23856,20,"AND","Andorra","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2005/and_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
23857,20,"AND","Andorra","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2005/and_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
23858,20,"AND","Andorra","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2005/and_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
23859,20,"AND","Andorra","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2005/and_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
23860,20,"AND","Andorra","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2005/and_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
23861,20,"AND","Andorra","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2006/and_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
23862,20,"AND","Andorra","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2006/and_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
23863,20,"AND","Andorra","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2006/and_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
23864,20,"AND","Andorra","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2006/and_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
23865,20,"AND","Andorra","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2006/and_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
23866,20,"AND","Andorra","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2006/and_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
23867,20,"AND","Andorra","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2006/and_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
23868,20,"AND","Andorra","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2006/and_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
23869,20,"AND","Andorra","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2007/and_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
23870,20,"AND","Andorra","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2007/and_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
23871,20,"AND","Andorra","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2007/and_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
23872,20,"AND","Andorra","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2007/and_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
23873,20,"AND","Andorra","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2007/and_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
23874,20,"AND","Andorra","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2007/and_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
23875,20,"AND","Andorra","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2007/and_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
23876,20,"AND","Andorra","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2007/and_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
23877,20,"AND","Andorra","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2008/and_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
23878,20,"AND","Andorra","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2008/and_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
23879,20,"AND","Andorra","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2008/and_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
23880,20,"AND","Andorra","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2008/and_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
23881,20,"AND","Andorra","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2008/and_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
23882,20,"AND","Andorra","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2008/and_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
23883,20,"AND","Andorra","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2008/and_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
23884,20,"AND","Andorra","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2008/and_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
23885,20,"AND","Andorra","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2009/and_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
23886,20,"AND","Andorra","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2009/and_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
23887,20,"AND","Andorra","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2009/and_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
23888,20,"AND","Andorra","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2009/and_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
23889,20,"AND","Andorra","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2009/and_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
23890,20,"AND","Andorra","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2009/and_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
23891,20,"AND","Andorra","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2009/and_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
23892,20,"AND","Andorra","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2009/and_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
23893,20,"AND","Andorra","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2010/and_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
23894,20,"AND","Andorra","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2010/and_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
23895,20,"AND","Andorra","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2010/and_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
23896,20,"AND","Andorra","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2010/and_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
23897,20,"AND","Andorra","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2010/and_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
23898,20,"AND","Andorra","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2010/and_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
23899,20,"AND","Andorra","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2010/and_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
23900,20,"AND","Andorra","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2010/and_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
23901,20,"AND","Andorra","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2011/and_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
23902,20,"AND","Andorra","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2011/and_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
23903,20,"AND","Andorra","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2011/and_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
23904,20,"AND","Andorra","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2011/and_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
23905,20,"AND","Andorra","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2011/and_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
23906,20,"AND","Andorra","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2011/and_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
23907,20,"AND","Andorra","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2011/and_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
23908,20,"AND","Andorra","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2011/and_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
23909,20,"AND","Andorra","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2012/and_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
23910,20,"AND","Andorra","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2012/and_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
23911,20,"AND","Andorra","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2012/and_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
23912,20,"AND","Andorra","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2012/and_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
23913,20,"AND","Andorra","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2012/and_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
23914,20,"AND","Andorra","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2012/and_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
23915,20,"AND","Andorra","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2012/and_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
23916,20,"AND","Andorra","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2012/and_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
23917,20,"AND","Andorra","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2013/and_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
23918,20,"AND","Andorra","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2013/and_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
23919,20,"AND","Andorra","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2013/and_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
23920,20,"AND","Andorra","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2013/and_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
23921,20,"AND","Andorra","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2013/and_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
23922,20,"AND","Andorra","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2013/and_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
23923,20,"AND","Andorra","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2013/and_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
23924,20,"AND","Andorra","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2013/and_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
23925,20,"AND","Andorra","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2014/and_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
23926,20,"AND","Andorra","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2014/and_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
23927,20,"AND","Andorra","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2014/and_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
23928,20,"AND","Andorra","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2014/and_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
23929,20,"AND","Andorra","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2014/and_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
23930,20,"AND","Andorra","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2014/and_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
23931,20,"AND","Andorra","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2014/and_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
23932,20,"AND","Andorra","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2014/and_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
23933,20,"AND","Andorra","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2015/and_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
23934,20,"AND","Andorra","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2015/and_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
23935,20,"AND","Andorra","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2015/and_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
23936,20,"AND","Andorra","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2015/and_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
23937,20,"AND","Andorra","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2015/and_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
23938,20,"AND","Andorra","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2015/and_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
23939,20,"AND","Andorra","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2015/and_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
23940,20,"AND","Andorra","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Annual/2015/and_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
23941,24,"AGO","Angola","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2000/ago_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
23942,24,"AGO","Angola","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2000/ago_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
23943,24,"AGO","Angola","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2000/ago_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
23944,24,"AGO","Angola","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2000/ago_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
23945,24,"AGO","Angola","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2000/ago_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
23946,24,"AGO","Angola","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2000/ago_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
23947,24,"AGO","Angola","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2000/ago_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
23948,24,"AGO","Angola","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2000/ago_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
23949,24,"AGO","Angola","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2001/ago_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
23950,24,"AGO","Angola","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2001/ago_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
23951,24,"AGO","Angola","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2001/ago_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
23952,24,"AGO","Angola","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2001/ago_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
23953,24,"AGO","Angola","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2001/ago_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
23954,24,"AGO","Angola","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2001/ago_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
23955,24,"AGO","Angola","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2001/ago_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
23956,24,"AGO","Angola","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2001/ago_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
23957,24,"AGO","Angola","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2002/ago_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
23958,24,"AGO","Angola","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2002/ago_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
23959,24,"AGO","Angola","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2002/ago_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
23960,24,"AGO","Angola","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2002/ago_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
23961,24,"AGO","Angola","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2002/ago_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
23962,24,"AGO","Angola","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2002/ago_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
23963,24,"AGO","Angola","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2002/ago_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
23964,24,"AGO","Angola","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2002/ago_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
23965,24,"AGO","Angola","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2003/ago_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
23966,24,"AGO","Angola","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2003/ago_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
23967,24,"AGO","Angola","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2003/ago_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
23968,24,"AGO","Angola","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2003/ago_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
23969,24,"AGO","Angola","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2003/ago_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
23970,24,"AGO","Angola","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2003/ago_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
23971,24,"AGO","Angola","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2003/ago_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
23972,24,"AGO","Angola","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2003/ago_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
23973,24,"AGO","Angola","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2004/ago_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
23974,24,"AGO","Angola","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2004/ago_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
23975,24,"AGO","Angola","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2004/ago_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
23976,24,"AGO","Angola","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2004/ago_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
23977,24,"AGO","Angola","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2004/ago_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
23978,24,"AGO","Angola","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2004/ago_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
23979,24,"AGO","Angola","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2004/ago_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
23980,24,"AGO","Angola","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2004/ago_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
23981,24,"AGO","Angola","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2005/ago_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
23982,24,"AGO","Angola","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2005/ago_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
23983,24,"AGO","Angola","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2005/ago_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
23984,24,"AGO","Angola","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2005/ago_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
23985,24,"AGO","Angola","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2005/ago_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
23986,24,"AGO","Angola","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2005/ago_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
23987,24,"AGO","Angola","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2005/ago_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
23988,24,"AGO","Angola","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2005/ago_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
23989,24,"AGO","Angola","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2006/ago_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
23990,24,"AGO","Angola","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2006/ago_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
23991,24,"AGO","Angola","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2006/ago_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
23992,24,"AGO","Angola","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2006/ago_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
23993,24,"AGO","Angola","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2006/ago_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
23994,24,"AGO","Angola","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2006/ago_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
23995,24,"AGO","Angola","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2006/ago_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
23996,24,"AGO","Angola","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2006/ago_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
23997,24,"AGO","Angola","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2007/ago_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
23998,24,"AGO","Angola","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2007/ago_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
23999,24,"AGO","Angola","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2007/ago_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
24000,24,"AGO","Angola","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2007/ago_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
24001,24,"AGO","Angola","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2007/ago_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
24002,24,"AGO","Angola","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2007/ago_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
24003,24,"AGO","Angola","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2007/ago_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
24004,24,"AGO","Angola","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2007/ago_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
24005,24,"AGO","Angola","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2008/ago_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
24006,24,"AGO","Angola","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2008/ago_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
24007,24,"AGO","Angola","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2008/ago_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
24008,24,"AGO","Angola","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2008/ago_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
24009,24,"AGO","Angola","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2008/ago_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
24010,24,"AGO","Angola","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2008/ago_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
24011,24,"AGO","Angola","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2008/ago_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
24012,24,"AGO","Angola","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2008/ago_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
24013,24,"AGO","Angola","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2009/ago_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
24014,24,"AGO","Angola","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2009/ago_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
24015,24,"AGO","Angola","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2009/ago_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
24016,24,"AGO","Angola","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2009/ago_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
24017,24,"AGO","Angola","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2009/ago_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
24018,24,"AGO","Angola","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2009/ago_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
24019,24,"AGO","Angola","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2009/ago_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
24020,24,"AGO","Angola","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2009/ago_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
24021,24,"AGO","Angola","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2010/ago_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
24022,24,"AGO","Angola","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2010/ago_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
24023,24,"AGO","Angola","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2010/ago_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
24024,24,"AGO","Angola","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2010/ago_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
24025,24,"AGO","Angola","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2010/ago_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
24026,24,"AGO","Angola","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2010/ago_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
24027,24,"AGO","Angola","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2010/ago_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
24028,24,"AGO","Angola","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2010/ago_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
24029,24,"AGO","Angola","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2011/ago_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
24030,24,"AGO","Angola","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2011/ago_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
24031,24,"AGO","Angola","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2011/ago_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
24032,24,"AGO","Angola","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2011/ago_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
24033,24,"AGO","Angola","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2011/ago_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
24034,24,"AGO","Angola","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2011/ago_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
24035,24,"AGO","Angola","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2011/ago_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
24036,24,"AGO","Angola","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2011/ago_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
24037,24,"AGO","Angola","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2012/ago_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
24038,24,"AGO","Angola","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2012/ago_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
24039,24,"AGO","Angola","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2012/ago_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
24040,24,"AGO","Angola","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2012/ago_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
24041,24,"AGO","Angola","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2012/ago_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
24042,24,"AGO","Angola","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2012/ago_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
24043,24,"AGO","Angola","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2012/ago_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
24044,24,"AGO","Angola","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2012/ago_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
24045,24,"AGO","Angola","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2013/ago_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
24046,24,"AGO","Angola","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2013/ago_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
24047,24,"AGO","Angola","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2013/ago_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
24048,24,"AGO","Angola","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2013/ago_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
24049,24,"AGO","Angola","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2013/ago_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
24050,24,"AGO","Angola","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2013/ago_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
24051,24,"AGO","Angola","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2013/ago_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
24052,24,"AGO","Angola","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2013/ago_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
24053,24,"AGO","Angola","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2014/ago_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
24054,24,"AGO","Angola","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2014/ago_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
24055,24,"AGO","Angola","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2014/ago_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
24056,24,"AGO","Angola","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2014/ago_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
24057,24,"AGO","Angola","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2014/ago_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
24058,24,"AGO","Angola","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2014/ago_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
24059,24,"AGO","Angola","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2014/ago_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
24060,24,"AGO","Angola","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2014/ago_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
24061,24,"AGO","Angola","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2015/ago_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
24062,24,"AGO","Angola","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2015/ago_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
24063,24,"AGO","Angola","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2015/ago_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
24064,24,"AGO","Angola","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2015/ago_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
24065,24,"AGO","Angola","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2015/ago_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
24066,24,"AGO","Angola","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2015/ago_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
24067,24,"AGO","Angola","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2015/ago_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
24068,24,"AGO","Angola","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Annual/2015/ago_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
24069,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2000/atg_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
24070,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2000/atg_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
24071,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2000/atg_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
24072,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2000/atg_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
24073,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2000/atg_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
24074,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2000/atg_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
24075,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2000/atg_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
24076,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2000/atg_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
24077,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2001/atg_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
24078,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2001/atg_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
24079,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2001/atg_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
24080,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2001/atg_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
24081,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2001/atg_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
24082,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2001/atg_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
24083,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2001/atg_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
24084,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2001/atg_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
24085,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2002/atg_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
24086,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2002/atg_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
24087,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2002/atg_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
24088,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2002/atg_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
24089,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2002/atg_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
24090,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2002/atg_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
24091,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2002/atg_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
24092,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2002/atg_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
24093,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2003/atg_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
24094,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2003/atg_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
24095,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2003/atg_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
24096,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2003/atg_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
24097,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2003/atg_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
24098,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2003/atg_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
24099,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2003/atg_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
24100,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2003/atg_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
24101,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2004/atg_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
24102,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2004/atg_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
24103,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2004/atg_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
24104,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2004/atg_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
24105,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2004/atg_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
24106,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2004/atg_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
24107,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2004/atg_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
24108,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2004/atg_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
24109,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2005/atg_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
24110,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2005/atg_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
24111,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2005/atg_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
24112,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2005/atg_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
24113,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2005/atg_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
24114,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2005/atg_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
24115,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2005/atg_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
24116,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2005/atg_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
24117,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2006/atg_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
24118,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2006/atg_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
24119,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2006/atg_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
24120,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2006/atg_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
24121,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2006/atg_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
24122,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2006/atg_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
24123,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2006/atg_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
24124,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2006/atg_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
24125,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2007/atg_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
24126,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2007/atg_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
24127,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2007/atg_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
24128,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2007/atg_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
24129,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2007/atg_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
24130,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2007/atg_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
24131,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2007/atg_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
24132,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2007/atg_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
24133,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2008/atg_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
24134,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2008/atg_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
24135,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2008/atg_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
24136,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2008/atg_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
24137,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2008/atg_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
24138,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2008/atg_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
24139,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2008/atg_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
24140,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2008/atg_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
24141,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2009/atg_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
24142,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2009/atg_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
24143,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2009/atg_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
24144,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2009/atg_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
24145,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2009/atg_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
24146,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2009/atg_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
24147,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2009/atg_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
24148,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2009/atg_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
24149,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2010/atg_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
24150,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2010/atg_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
24151,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2010/atg_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
24152,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2010/atg_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
24153,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2010/atg_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
24154,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2010/atg_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
24155,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2010/atg_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
24156,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2010/atg_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
24157,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2011/atg_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
24158,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2011/atg_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
24159,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2011/atg_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
24160,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2011/atg_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
24161,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2011/atg_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
24162,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2011/atg_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
24163,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2011/atg_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
24164,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2011/atg_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
24165,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2012/atg_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
24166,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2012/atg_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
24167,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2012/atg_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
24168,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2012/atg_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
24169,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2012/atg_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
24170,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2012/atg_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
24171,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2012/atg_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
24172,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2012/atg_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
24173,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2013/atg_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
24174,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2013/atg_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
24175,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2013/atg_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
24176,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2013/atg_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
24177,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2013/atg_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
24178,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2013/atg_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
24179,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2013/atg_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
24180,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2013/atg_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
24181,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2014/atg_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
24182,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2014/atg_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
24183,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2014/atg_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
24184,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2014/atg_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
24185,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2014/atg_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
24186,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2014/atg_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
24187,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2014/atg_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
24188,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2014/atg_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
24189,28,"ATG","Antigua and Barbuda","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2015/atg_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
24190,28,"ATG","Antigua and Barbuda","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2015/atg_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
24191,28,"ATG","Antigua and Barbuda","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2015/atg_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
24192,28,"ATG","Antigua and Barbuda","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2015/atg_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
24193,28,"ATG","Antigua and Barbuda","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2015/atg_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
24194,28,"ATG","Antigua and Barbuda","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2015/atg_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
24195,28,"ATG","Antigua and Barbuda","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2015/atg_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
24196,28,"ATG","Antigua and Barbuda","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Annual/2015/atg_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
24197,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2000/aze_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
24198,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2000/aze_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
24199,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2000/aze_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
24200,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2000/aze_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
24201,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2000/aze_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
24202,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2000/aze_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
24203,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2000/aze_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
24204,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2000/aze_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
24205,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2001/aze_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
24206,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2001/aze_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
24207,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2001/aze_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
24208,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2001/aze_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
24209,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2001/aze_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
24210,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2001/aze_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
24211,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2001/aze_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
24212,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2001/aze_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
24213,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2002/aze_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
24214,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2002/aze_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
24215,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2002/aze_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
24216,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2002/aze_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
24217,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2002/aze_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
24218,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2002/aze_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
24219,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2002/aze_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
24220,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2002/aze_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
24221,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2003/aze_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
24222,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2003/aze_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
24223,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2003/aze_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
24224,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2003/aze_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
24225,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2003/aze_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
24226,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2003/aze_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
24227,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2003/aze_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
24228,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2003/aze_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
24229,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2004/aze_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
24230,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2004/aze_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
24231,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2004/aze_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
24232,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2004/aze_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
24233,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2004/aze_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
24234,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2004/aze_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
24235,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2004/aze_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
24236,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2004/aze_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
24237,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2005/aze_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
24238,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2005/aze_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
24239,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2005/aze_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
24240,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2005/aze_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
24241,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2005/aze_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
24242,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2005/aze_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
24243,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2005/aze_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
24244,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2005/aze_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
24245,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2006/aze_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
24246,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2006/aze_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
24247,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2006/aze_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
24248,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2006/aze_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
24249,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2006/aze_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
24250,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2006/aze_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
24251,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2006/aze_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
24252,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2006/aze_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
24253,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2007/aze_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
24254,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2007/aze_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
24255,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2007/aze_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
24256,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2007/aze_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
24257,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2007/aze_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
24258,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2007/aze_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
24259,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2007/aze_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
24260,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2007/aze_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
24261,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2008/aze_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
24262,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2008/aze_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
24263,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2008/aze_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
24264,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2008/aze_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
24265,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2008/aze_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
24266,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2008/aze_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
24267,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2008/aze_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
24268,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2008/aze_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
24269,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2009/aze_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
24270,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2009/aze_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
24271,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2009/aze_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
24272,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2009/aze_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
24273,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2009/aze_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
24274,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2009/aze_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
24275,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2009/aze_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
24276,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2009/aze_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
24277,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2010/aze_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
24278,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2010/aze_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
24279,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2010/aze_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
24280,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2010/aze_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
24281,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2010/aze_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
24282,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2010/aze_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
24283,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2010/aze_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
24284,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2010/aze_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
24285,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2011/aze_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
24286,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2011/aze_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
24287,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2011/aze_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
24288,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2011/aze_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
24289,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2011/aze_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
24290,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2011/aze_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
24291,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2011/aze_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
24292,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2011/aze_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
24293,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2012/aze_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
24294,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2012/aze_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
24295,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2012/aze_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
24296,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2012/aze_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
24297,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2012/aze_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
24298,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2012/aze_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
24299,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2012/aze_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
24300,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2012/aze_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
24301,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2013/aze_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
24302,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2013/aze_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
24303,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2013/aze_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
24304,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2013/aze_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
24305,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2013/aze_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
24306,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2013/aze_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
24307,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2013/aze_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
24308,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2013/aze_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
24309,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2014/aze_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
24310,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2014/aze_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
24311,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2014/aze_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
24312,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2014/aze_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
24313,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2014/aze_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
24314,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2014/aze_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
24315,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2014/aze_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
24316,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2014/aze_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
24317,31,"AZE","Azerbaijan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2015/aze_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
24318,31,"AZE","Azerbaijan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2015/aze_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
24319,31,"AZE","Azerbaijan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2015/aze_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
24320,31,"AZE","Azerbaijan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2015/aze_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
24321,31,"AZE","Azerbaijan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2015/aze_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
24322,31,"AZE","Azerbaijan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2015/aze_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
24323,31,"AZE","Azerbaijan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2015/aze_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
24324,31,"AZE","Azerbaijan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Annual/2015/aze_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
24325,32,"ARG","Argentina","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2000/arg_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
24326,32,"ARG","Argentina","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2000/arg_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
24327,32,"ARG","Argentina","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2000/arg_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
24328,32,"ARG","Argentina","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2000/arg_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
24329,32,"ARG","Argentina","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2000/arg_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
24330,32,"ARG","Argentina","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2000/arg_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
24331,32,"ARG","Argentina","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2000/arg_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
24332,32,"ARG","Argentina","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2000/arg_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
24333,32,"ARG","Argentina","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2001/arg_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
24334,32,"ARG","Argentina","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2001/arg_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
24335,32,"ARG","Argentina","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2001/arg_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
24336,32,"ARG","Argentina","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2001/arg_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
24337,32,"ARG","Argentina","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2001/arg_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
24338,32,"ARG","Argentina","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2001/arg_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
24339,32,"ARG","Argentina","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2001/arg_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
24340,32,"ARG","Argentina","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2001/arg_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
24341,32,"ARG","Argentina","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2002/arg_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
24342,32,"ARG","Argentina","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2002/arg_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
24343,32,"ARG","Argentina","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2002/arg_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
24344,32,"ARG","Argentina","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2002/arg_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
24345,32,"ARG","Argentina","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2002/arg_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
24346,32,"ARG","Argentina","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2002/arg_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
24347,32,"ARG","Argentina","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2002/arg_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
24348,32,"ARG","Argentina","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2002/arg_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
24349,32,"ARG","Argentina","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2003/arg_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
24350,32,"ARG","Argentina","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2003/arg_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
24351,32,"ARG","Argentina","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2003/arg_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
24352,32,"ARG","Argentina","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2003/arg_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
24353,32,"ARG","Argentina","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2003/arg_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
24354,32,"ARG","Argentina","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2003/arg_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
24355,32,"ARG","Argentina","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2003/arg_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
24356,32,"ARG","Argentina","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2003/arg_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
24357,32,"ARG","Argentina","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2004/arg_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
24358,32,"ARG","Argentina","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2004/arg_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
24359,32,"ARG","Argentina","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2004/arg_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
24360,32,"ARG","Argentina","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2004/arg_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
24361,32,"ARG","Argentina","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2004/arg_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
24362,32,"ARG","Argentina","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2004/arg_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
24363,32,"ARG","Argentina","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2004/arg_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
24364,32,"ARG","Argentina","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2004/arg_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
24365,32,"ARG","Argentina","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2005/arg_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
24366,32,"ARG","Argentina","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2005/arg_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
24367,32,"ARG","Argentina","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2005/arg_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
24368,32,"ARG","Argentina","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2005/arg_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
24369,32,"ARG","Argentina","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2005/arg_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
24370,32,"ARG","Argentina","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2005/arg_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
24371,32,"ARG","Argentina","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2005/arg_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
24372,32,"ARG","Argentina","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2005/arg_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
24373,32,"ARG","Argentina","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2006/arg_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
24374,32,"ARG","Argentina","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2006/arg_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
24375,32,"ARG","Argentina","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2006/arg_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
24376,32,"ARG","Argentina","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2006/arg_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
24377,32,"ARG","Argentina","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2006/arg_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
24378,32,"ARG","Argentina","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2006/arg_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
24379,32,"ARG","Argentina","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2006/arg_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
24380,32,"ARG","Argentina","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2006/arg_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
24381,32,"ARG","Argentina","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2007/arg_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
24382,32,"ARG","Argentina","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2007/arg_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
24383,32,"ARG","Argentina","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2007/arg_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
24384,32,"ARG","Argentina","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2007/arg_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
24385,32,"ARG","Argentina","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2007/arg_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
24386,32,"ARG","Argentina","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2007/arg_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
24387,32,"ARG","Argentina","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2007/arg_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
24388,32,"ARG","Argentina","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2007/arg_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
24389,32,"ARG","Argentina","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2008/arg_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
24390,32,"ARG","Argentina","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2008/arg_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
24391,32,"ARG","Argentina","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2008/arg_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
24392,32,"ARG","Argentina","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2008/arg_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
24393,32,"ARG","Argentina","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2008/arg_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
24394,32,"ARG","Argentina","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2008/arg_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
24395,32,"ARG","Argentina","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2008/arg_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
24396,32,"ARG","Argentina","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2008/arg_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
24397,32,"ARG","Argentina","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2009/arg_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
24398,32,"ARG","Argentina","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2009/arg_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
24399,32,"ARG","Argentina","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2009/arg_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
24400,32,"ARG","Argentina","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2009/arg_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
24401,32,"ARG","Argentina","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2009/arg_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
24402,32,"ARG","Argentina","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2009/arg_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
24403,32,"ARG","Argentina","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2009/arg_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
24404,32,"ARG","Argentina","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2009/arg_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
24405,32,"ARG","Argentina","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2010/arg_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
24406,32,"ARG","Argentina","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2010/arg_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
24407,32,"ARG","Argentina","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2010/arg_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
24408,32,"ARG","Argentina","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2010/arg_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
24409,32,"ARG","Argentina","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2010/arg_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
24410,32,"ARG","Argentina","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2010/arg_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
24411,32,"ARG","Argentina","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2010/arg_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
24412,32,"ARG","Argentina","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2010/arg_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
24413,32,"ARG","Argentina","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2011/arg_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
24414,32,"ARG","Argentina","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2011/arg_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
24415,32,"ARG","Argentina","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2011/arg_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
24416,32,"ARG","Argentina","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2011/arg_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
24417,32,"ARG","Argentina","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2011/arg_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
24418,32,"ARG","Argentina","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2011/arg_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
24419,32,"ARG","Argentina","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2011/arg_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
24420,32,"ARG","Argentina","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2011/arg_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
24421,32,"ARG","Argentina","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2012/arg_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
24422,32,"ARG","Argentina","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2012/arg_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
24423,32,"ARG","Argentina","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2012/arg_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
24424,32,"ARG","Argentina","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2012/arg_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
24425,32,"ARG","Argentina","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2012/arg_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
24426,32,"ARG","Argentina","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2012/arg_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
24427,32,"ARG","Argentina","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2012/arg_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
24428,32,"ARG","Argentina","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2012/arg_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
24429,32,"ARG","Argentina","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2013/arg_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
24430,32,"ARG","Argentina","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2013/arg_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
24431,32,"ARG","Argentina","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2013/arg_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
24432,32,"ARG","Argentina","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2013/arg_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
24433,32,"ARG","Argentina","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2013/arg_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
24434,32,"ARG","Argentina","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2013/arg_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
24435,32,"ARG","Argentina","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2013/arg_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
24436,32,"ARG","Argentina","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2013/arg_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
24437,32,"ARG","Argentina","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2014/arg_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
24438,32,"ARG","Argentina","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2014/arg_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
24439,32,"ARG","Argentina","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2014/arg_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
24440,32,"ARG","Argentina","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2014/arg_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
24441,32,"ARG","Argentina","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2014/arg_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
24442,32,"ARG","Argentina","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2014/arg_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
24443,32,"ARG","Argentina","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2014/arg_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
24444,32,"ARG","Argentina","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2014/arg_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
24445,32,"ARG","Argentina","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2015/arg_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
24446,32,"ARG","Argentina","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2015/arg_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
24447,32,"ARG","Argentina","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2015/arg_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
24448,32,"ARG","Argentina","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2015/arg_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
24449,32,"ARG","Argentina","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2015/arg_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
24450,32,"ARG","Argentina","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2015/arg_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
24451,32,"ARG","Argentina","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2015/arg_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
24452,32,"ARG","Argentina","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Annual/2015/arg_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
24453,40,"AUT","Austria","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2000/aut_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
24454,40,"AUT","Austria","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2000/aut_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
24455,40,"AUT","Austria","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2000/aut_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
24456,40,"AUT","Austria","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2000/aut_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
24457,40,"AUT","Austria","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2000/aut_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
24458,40,"AUT","Austria","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2000/aut_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
24459,40,"AUT","Austria","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2000/aut_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
24460,40,"AUT","Austria","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2000/aut_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
24461,40,"AUT","Austria","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2001/aut_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
24462,40,"AUT","Austria","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2001/aut_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
24463,40,"AUT","Austria","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2001/aut_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
24464,40,"AUT","Austria","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2001/aut_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
24465,40,"AUT","Austria","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2001/aut_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
24466,40,"AUT","Austria","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2001/aut_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
24467,40,"AUT","Austria","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2001/aut_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
24468,40,"AUT","Austria","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2001/aut_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
24469,40,"AUT","Austria","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2002/aut_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
24470,40,"AUT","Austria","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2002/aut_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
24471,40,"AUT","Austria","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2002/aut_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
24472,40,"AUT","Austria","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2002/aut_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
24473,40,"AUT","Austria","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2002/aut_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
24474,40,"AUT","Austria","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2002/aut_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
24475,40,"AUT","Austria","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2002/aut_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
24476,40,"AUT","Austria","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2002/aut_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
24477,40,"AUT","Austria","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2003/aut_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
24478,40,"AUT","Austria","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2003/aut_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
24479,40,"AUT","Austria","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2003/aut_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
24480,40,"AUT","Austria","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2003/aut_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
24481,40,"AUT","Austria","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2003/aut_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
24482,40,"AUT","Austria","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2003/aut_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
24483,40,"AUT","Austria","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2003/aut_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
24484,40,"AUT","Austria","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2003/aut_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
24485,40,"AUT","Austria","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2004/aut_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
24486,40,"AUT","Austria","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2004/aut_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
24487,40,"AUT","Austria","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2004/aut_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
24488,40,"AUT","Austria","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2004/aut_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
24489,40,"AUT","Austria","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2004/aut_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
24490,40,"AUT","Austria","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2004/aut_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
24491,40,"AUT","Austria","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2004/aut_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
24492,40,"AUT","Austria","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2004/aut_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
24493,40,"AUT","Austria","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2005/aut_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
24494,40,"AUT","Austria","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2005/aut_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
24495,40,"AUT","Austria","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2005/aut_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
24496,40,"AUT","Austria","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2005/aut_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
24497,40,"AUT","Austria","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2005/aut_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
24498,40,"AUT","Austria","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2005/aut_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
24499,40,"AUT","Austria","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2005/aut_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
24500,40,"AUT","Austria","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2005/aut_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
24501,40,"AUT","Austria","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2006/aut_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
24502,40,"AUT","Austria","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2006/aut_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
24503,40,"AUT","Austria","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2006/aut_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
24504,40,"AUT","Austria","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2006/aut_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
24505,40,"AUT","Austria","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2006/aut_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
24506,40,"AUT","Austria","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2006/aut_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
24507,40,"AUT","Austria","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2006/aut_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
24508,40,"AUT","Austria","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2006/aut_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
24509,40,"AUT","Austria","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2007/aut_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
24510,40,"AUT","Austria","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2007/aut_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
24511,40,"AUT","Austria","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2007/aut_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
24512,40,"AUT","Austria","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2007/aut_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
24513,40,"AUT","Austria","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2007/aut_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
24514,40,"AUT","Austria","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2007/aut_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
24515,40,"AUT","Austria","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2007/aut_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
24516,40,"AUT","Austria","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2007/aut_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
24517,40,"AUT","Austria","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2008/aut_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
24518,40,"AUT","Austria","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2008/aut_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
24519,40,"AUT","Austria","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2008/aut_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
24520,40,"AUT","Austria","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2008/aut_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
24521,40,"AUT","Austria","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2008/aut_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
24522,40,"AUT","Austria","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2008/aut_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
24523,40,"AUT","Austria","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2008/aut_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
24524,40,"AUT","Austria","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2008/aut_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
24525,40,"AUT","Austria","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2009/aut_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
24526,40,"AUT","Austria","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2009/aut_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
24527,40,"AUT","Austria","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2009/aut_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
24528,40,"AUT","Austria","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2009/aut_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
24529,40,"AUT","Austria","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2009/aut_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
24530,40,"AUT","Austria","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2009/aut_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
24531,40,"AUT","Austria","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2009/aut_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
24532,40,"AUT","Austria","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2009/aut_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
24533,40,"AUT","Austria","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2010/aut_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
24534,40,"AUT","Austria","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2010/aut_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
24535,40,"AUT","Austria","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2010/aut_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
24536,40,"AUT","Austria","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2010/aut_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
24537,40,"AUT","Austria","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2010/aut_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
24538,40,"AUT","Austria","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2010/aut_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
24539,40,"AUT","Austria","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2010/aut_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
24540,40,"AUT","Austria","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2010/aut_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
24541,40,"AUT","Austria","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2011/aut_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
24542,40,"AUT","Austria","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2011/aut_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
24543,40,"AUT","Austria","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2011/aut_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
24544,40,"AUT","Austria","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2011/aut_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
24545,40,"AUT","Austria","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2011/aut_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
24546,40,"AUT","Austria","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2011/aut_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
24547,40,"AUT","Austria","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2011/aut_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
24548,40,"AUT","Austria","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2011/aut_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
24549,40,"AUT","Austria","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2012/aut_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
24550,40,"AUT","Austria","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2012/aut_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
24551,40,"AUT","Austria","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2012/aut_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
24552,40,"AUT","Austria","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2012/aut_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
24553,40,"AUT","Austria","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2012/aut_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
24554,40,"AUT","Austria","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2012/aut_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
24555,40,"AUT","Austria","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2012/aut_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
24556,40,"AUT","Austria","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2012/aut_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
24557,40,"AUT","Austria","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2013/aut_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
24558,40,"AUT","Austria","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2013/aut_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
24559,40,"AUT","Austria","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2013/aut_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
24560,40,"AUT","Austria","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2013/aut_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
24561,40,"AUT","Austria","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2013/aut_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
24562,40,"AUT","Austria","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2013/aut_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
24563,40,"AUT","Austria","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2013/aut_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
24564,40,"AUT","Austria","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2013/aut_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
24565,40,"AUT","Austria","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2014/aut_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
24566,40,"AUT","Austria","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2014/aut_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
24567,40,"AUT","Austria","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2014/aut_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
24568,40,"AUT","Austria","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2014/aut_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
24569,40,"AUT","Austria","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2014/aut_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
24570,40,"AUT","Austria","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2014/aut_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
24571,40,"AUT","Austria","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2014/aut_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
24572,40,"AUT","Austria","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2014/aut_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
24573,40,"AUT","Austria","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2015/aut_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
24574,40,"AUT","Austria","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2015/aut_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
24575,40,"AUT","Austria","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2015/aut_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
24576,40,"AUT","Austria","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2015/aut_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
24577,40,"AUT","Austria","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2015/aut_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
24578,40,"AUT","Austria","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2015/aut_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
24579,40,"AUT","Austria","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2015/aut_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
24580,40,"AUT","Austria","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Annual/2015/aut_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
24581,44,"BHS","Bahamas","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2000/bhs_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
24582,44,"BHS","Bahamas","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2000/bhs_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
24583,44,"BHS","Bahamas","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2000/bhs_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
24584,44,"BHS","Bahamas","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2000/bhs_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
24585,44,"BHS","Bahamas","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2000/bhs_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
24586,44,"BHS","Bahamas","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2000/bhs_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
24587,44,"BHS","Bahamas","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2000/bhs_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
24588,44,"BHS","Bahamas","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2000/bhs_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
24589,44,"BHS","Bahamas","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2001/bhs_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
24590,44,"BHS","Bahamas","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2001/bhs_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
24591,44,"BHS","Bahamas","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2001/bhs_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
24592,44,"BHS","Bahamas","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2001/bhs_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
24593,44,"BHS","Bahamas","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2001/bhs_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
24594,44,"BHS","Bahamas","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2001/bhs_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
24595,44,"BHS","Bahamas","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2001/bhs_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
24596,44,"BHS","Bahamas","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2001/bhs_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
24597,44,"BHS","Bahamas","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2002/bhs_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
24598,44,"BHS","Bahamas","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2002/bhs_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
24599,44,"BHS","Bahamas","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2002/bhs_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
24600,44,"BHS","Bahamas","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2002/bhs_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
24601,44,"BHS","Bahamas","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2002/bhs_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
24602,44,"BHS","Bahamas","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2002/bhs_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
24603,44,"BHS","Bahamas","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2002/bhs_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
24604,44,"BHS","Bahamas","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2002/bhs_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
24605,44,"BHS","Bahamas","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2003/bhs_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
24606,44,"BHS","Bahamas","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2003/bhs_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
24607,44,"BHS","Bahamas","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2003/bhs_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
24608,44,"BHS","Bahamas","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2003/bhs_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
24609,44,"BHS","Bahamas","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2003/bhs_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
24610,44,"BHS","Bahamas","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2003/bhs_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
24611,44,"BHS","Bahamas","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2003/bhs_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
24612,44,"BHS","Bahamas","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2003/bhs_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
24613,44,"BHS","Bahamas","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2004/bhs_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
24614,44,"BHS","Bahamas","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2004/bhs_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
24615,44,"BHS","Bahamas","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2004/bhs_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
24616,44,"BHS","Bahamas","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2004/bhs_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
24617,44,"BHS","Bahamas","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2004/bhs_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
24618,44,"BHS","Bahamas","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2004/bhs_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
24619,44,"BHS","Bahamas","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2004/bhs_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
24620,44,"BHS","Bahamas","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2004/bhs_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
24621,44,"BHS","Bahamas","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2005/bhs_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
24622,44,"BHS","Bahamas","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2005/bhs_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
24623,44,"BHS","Bahamas","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2005/bhs_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
24624,44,"BHS","Bahamas","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2005/bhs_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
24625,44,"BHS","Bahamas","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2005/bhs_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
24626,44,"BHS","Bahamas","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2005/bhs_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
24627,44,"BHS","Bahamas","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2005/bhs_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
24628,44,"BHS","Bahamas","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2005/bhs_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
24629,44,"BHS","Bahamas","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2006/bhs_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
24630,44,"BHS","Bahamas","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2006/bhs_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
24631,44,"BHS","Bahamas","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2006/bhs_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
24632,44,"BHS","Bahamas","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2006/bhs_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
24633,44,"BHS","Bahamas","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2006/bhs_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
24634,44,"BHS","Bahamas","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2006/bhs_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
24635,44,"BHS","Bahamas","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2006/bhs_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
24636,44,"BHS","Bahamas","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2006/bhs_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
24637,44,"BHS","Bahamas","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2007/bhs_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
24638,44,"BHS","Bahamas","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2007/bhs_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
24639,44,"BHS","Bahamas","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2007/bhs_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
24640,44,"BHS","Bahamas","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2007/bhs_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
24641,44,"BHS","Bahamas","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2007/bhs_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
24642,44,"BHS","Bahamas","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2007/bhs_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
24643,44,"BHS","Bahamas","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2007/bhs_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
24644,44,"BHS","Bahamas","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2007/bhs_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
24645,44,"BHS","Bahamas","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2008/bhs_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
24646,44,"BHS","Bahamas","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2008/bhs_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
24647,44,"BHS","Bahamas","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2008/bhs_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
24648,44,"BHS","Bahamas","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2008/bhs_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
24649,44,"BHS","Bahamas","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2008/bhs_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
24650,44,"BHS","Bahamas","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2008/bhs_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
24651,44,"BHS","Bahamas","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2008/bhs_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
24652,44,"BHS","Bahamas","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2008/bhs_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
24653,44,"BHS","Bahamas","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2009/bhs_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
24654,44,"BHS","Bahamas","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2009/bhs_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
24655,44,"BHS","Bahamas","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2009/bhs_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
24656,44,"BHS","Bahamas","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2009/bhs_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
24657,44,"BHS","Bahamas","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2009/bhs_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
24658,44,"BHS","Bahamas","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2009/bhs_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
24659,44,"BHS","Bahamas","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2009/bhs_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
24660,44,"BHS","Bahamas","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2009/bhs_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
24661,44,"BHS","Bahamas","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2010/bhs_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
24662,44,"BHS","Bahamas","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2010/bhs_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
24663,44,"BHS","Bahamas","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2010/bhs_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
24664,44,"BHS","Bahamas","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2010/bhs_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
24665,44,"BHS","Bahamas","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2010/bhs_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
24666,44,"BHS","Bahamas","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2010/bhs_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
24667,44,"BHS","Bahamas","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2010/bhs_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
24668,44,"BHS","Bahamas","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2010/bhs_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
24669,44,"BHS","Bahamas","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2011/bhs_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
24670,44,"BHS","Bahamas","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2011/bhs_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
24671,44,"BHS","Bahamas","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2011/bhs_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
24672,44,"BHS","Bahamas","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2011/bhs_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
24673,44,"BHS","Bahamas","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2011/bhs_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
24674,44,"BHS","Bahamas","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2011/bhs_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
24675,44,"BHS","Bahamas","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2011/bhs_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
24676,44,"BHS","Bahamas","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2011/bhs_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
24677,44,"BHS","Bahamas","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2012/bhs_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
24678,44,"BHS","Bahamas","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2012/bhs_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
24679,44,"BHS","Bahamas","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2012/bhs_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
24680,44,"BHS","Bahamas","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2012/bhs_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
24681,44,"BHS","Bahamas","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2012/bhs_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
24682,44,"BHS","Bahamas","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2012/bhs_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
24683,44,"BHS","Bahamas","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2012/bhs_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
24684,44,"BHS","Bahamas","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2012/bhs_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
24685,44,"BHS","Bahamas","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2013/bhs_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
24686,44,"BHS","Bahamas","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2013/bhs_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
24687,44,"BHS","Bahamas","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2013/bhs_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
24688,44,"BHS","Bahamas","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2013/bhs_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
24689,44,"BHS","Bahamas","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2013/bhs_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
24690,44,"BHS","Bahamas","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2013/bhs_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
24691,44,"BHS","Bahamas","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2013/bhs_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
24692,44,"BHS","Bahamas","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2013/bhs_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
24693,44,"BHS","Bahamas","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2014/bhs_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
24694,44,"BHS","Bahamas","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2014/bhs_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
24695,44,"BHS","Bahamas","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2014/bhs_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
24696,44,"BHS","Bahamas","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2014/bhs_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
24697,44,"BHS","Bahamas","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2014/bhs_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
24698,44,"BHS","Bahamas","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2014/bhs_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
24699,44,"BHS","Bahamas","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2014/bhs_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
24700,44,"BHS","Bahamas","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2014/bhs_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
24701,44,"BHS","Bahamas","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2015/bhs_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
24702,44,"BHS","Bahamas","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2015/bhs_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
24703,44,"BHS","Bahamas","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2015/bhs_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
24704,44,"BHS","Bahamas","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2015/bhs_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
24705,44,"BHS","Bahamas","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2015/bhs_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
24706,44,"BHS","Bahamas","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2015/bhs_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
24707,44,"BHS","Bahamas","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2015/bhs_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
24708,44,"BHS","Bahamas","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Annual/2015/bhs_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
24709,48,"BHR","Bahrain","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2000/bhr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
24710,48,"BHR","Bahrain","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2000/bhr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
24711,48,"BHR","Bahrain","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2000/bhr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
24712,48,"BHR","Bahrain","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2000/bhr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
24713,48,"BHR","Bahrain","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2000/bhr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
24714,48,"BHR","Bahrain","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2000/bhr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
24715,48,"BHR","Bahrain","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2000/bhr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
24716,48,"BHR","Bahrain","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2000/bhr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
24717,48,"BHR","Bahrain","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2001/bhr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
24718,48,"BHR","Bahrain","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2001/bhr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
24719,48,"BHR","Bahrain","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2001/bhr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
24720,48,"BHR","Bahrain","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2001/bhr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
24721,48,"BHR","Bahrain","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2001/bhr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
24722,48,"BHR","Bahrain","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2001/bhr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
24723,48,"BHR","Bahrain","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2001/bhr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
24724,48,"BHR","Bahrain","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2001/bhr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
24725,48,"BHR","Bahrain","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2002/bhr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
24726,48,"BHR","Bahrain","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2002/bhr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
24727,48,"BHR","Bahrain","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2002/bhr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
24728,48,"BHR","Bahrain","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2002/bhr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
24729,48,"BHR","Bahrain","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2002/bhr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
24730,48,"BHR","Bahrain","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2002/bhr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
24731,48,"BHR","Bahrain","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2002/bhr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
24732,48,"BHR","Bahrain","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2002/bhr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
24733,48,"BHR","Bahrain","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2003/bhr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
24734,48,"BHR","Bahrain","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2003/bhr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
24735,48,"BHR","Bahrain","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2003/bhr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
24736,48,"BHR","Bahrain","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2003/bhr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
24737,48,"BHR","Bahrain","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2003/bhr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
24738,48,"BHR","Bahrain","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2003/bhr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
24739,48,"BHR","Bahrain","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2003/bhr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
24740,48,"BHR","Bahrain","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2003/bhr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
24741,48,"BHR","Bahrain","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2004/bhr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
24742,48,"BHR","Bahrain","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2004/bhr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
24743,48,"BHR","Bahrain","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2004/bhr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
24744,48,"BHR","Bahrain","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2004/bhr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
24745,48,"BHR","Bahrain","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2004/bhr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
24746,48,"BHR","Bahrain","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2004/bhr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
24747,48,"BHR","Bahrain","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2004/bhr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
24748,48,"BHR","Bahrain","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2004/bhr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
24749,48,"BHR","Bahrain","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2005/bhr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
24750,48,"BHR","Bahrain","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2005/bhr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
24751,48,"BHR","Bahrain","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2005/bhr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
24752,48,"BHR","Bahrain","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2005/bhr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
24753,48,"BHR","Bahrain","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2005/bhr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
24754,48,"BHR","Bahrain","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2005/bhr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
24755,48,"BHR","Bahrain","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2005/bhr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
24756,48,"BHR","Bahrain","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2005/bhr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
24757,48,"BHR","Bahrain","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2006/bhr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
24758,48,"BHR","Bahrain","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2006/bhr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
24759,48,"BHR","Bahrain","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2006/bhr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
24760,48,"BHR","Bahrain","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2006/bhr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
24761,48,"BHR","Bahrain","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2006/bhr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
24762,48,"BHR","Bahrain","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2006/bhr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
24763,48,"BHR","Bahrain","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2006/bhr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
24764,48,"BHR","Bahrain","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2006/bhr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
24765,48,"BHR","Bahrain","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2007/bhr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
24766,48,"BHR","Bahrain","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2007/bhr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
24767,48,"BHR","Bahrain","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2007/bhr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
24768,48,"BHR","Bahrain","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2007/bhr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
24769,48,"BHR","Bahrain","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2007/bhr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
24770,48,"BHR","Bahrain","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2007/bhr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
24771,48,"BHR","Bahrain","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2007/bhr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
24772,48,"BHR","Bahrain","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2007/bhr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
24773,48,"BHR","Bahrain","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2008/bhr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
24774,48,"BHR","Bahrain","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2008/bhr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
24775,48,"BHR","Bahrain","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2008/bhr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
24776,48,"BHR","Bahrain","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2008/bhr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
24777,48,"BHR","Bahrain","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2008/bhr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
24778,48,"BHR","Bahrain","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2008/bhr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
24779,48,"BHR","Bahrain","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2008/bhr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
24780,48,"BHR","Bahrain","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2008/bhr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
24781,48,"BHR","Bahrain","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2009/bhr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
24782,48,"BHR","Bahrain","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2009/bhr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
24783,48,"BHR","Bahrain","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2009/bhr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
24784,48,"BHR","Bahrain","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2009/bhr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
24785,48,"BHR","Bahrain","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2009/bhr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
24786,48,"BHR","Bahrain","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2009/bhr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
24787,48,"BHR","Bahrain","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2009/bhr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
24788,48,"BHR","Bahrain","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2009/bhr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
24789,48,"BHR","Bahrain","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2010/bhr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
24790,48,"BHR","Bahrain","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2010/bhr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
24791,48,"BHR","Bahrain","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2010/bhr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
24792,48,"BHR","Bahrain","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2010/bhr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
24793,48,"BHR","Bahrain","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2010/bhr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
24794,48,"BHR","Bahrain","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2010/bhr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
24795,48,"BHR","Bahrain","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2010/bhr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
24796,48,"BHR","Bahrain","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2010/bhr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
24797,48,"BHR","Bahrain","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2011/bhr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
24798,48,"BHR","Bahrain","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2011/bhr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
24799,48,"BHR","Bahrain","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2011/bhr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
24800,48,"BHR","Bahrain","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2011/bhr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
24801,48,"BHR","Bahrain","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2011/bhr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
24802,48,"BHR","Bahrain","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2011/bhr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
24803,48,"BHR","Bahrain","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2011/bhr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
24804,48,"BHR","Bahrain","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2011/bhr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
24805,48,"BHR","Bahrain","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2012/bhr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
24806,48,"BHR","Bahrain","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2012/bhr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
24807,48,"BHR","Bahrain","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2012/bhr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
24808,48,"BHR","Bahrain","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2012/bhr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
24809,48,"BHR","Bahrain","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2012/bhr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
24810,48,"BHR","Bahrain","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2012/bhr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
24811,48,"BHR","Bahrain","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2012/bhr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
24812,48,"BHR","Bahrain","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2012/bhr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
24813,48,"BHR","Bahrain","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2013/bhr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
24814,48,"BHR","Bahrain","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2013/bhr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
24815,48,"BHR","Bahrain","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2013/bhr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
24816,48,"BHR","Bahrain","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2013/bhr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
24817,48,"BHR","Bahrain","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2013/bhr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
24818,48,"BHR","Bahrain","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2013/bhr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
24819,48,"BHR","Bahrain","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2013/bhr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
24820,48,"BHR","Bahrain","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2013/bhr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
24821,48,"BHR","Bahrain","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2014/bhr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
24822,48,"BHR","Bahrain","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2014/bhr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
24823,48,"BHR","Bahrain","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2014/bhr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
24824,48,"BHR","Bahrain","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2014/bhr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
24825,48,"BHR","Bahrain","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2014/bhr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
24826,48,"BHR","Bahrain","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2014/bhr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
24827,48,"BHR","Bahrain","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2014/bhr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
24828,48,"BHR","Bahrain","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2014/bhr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
24829,48,"BHR","Bahrain","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2015/bhr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
24830,48,"BHR","Bahrain","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2015/bhr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
24831,48,"BHR","Bahrain","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2015/bhr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
24832,48,"BHR","Bahrain","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2015/bhr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
24833,48,"BHR","Bahrain","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2015/bhr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
24834,48,"BHR","Bahrain","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2015/bhr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
24835,48,"BHR","Bahrain","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2015/bhr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
24836,48,"BHR","Bahrain","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Annual/2015/bhr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
24837,50,"BGD","Bangladesh","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2000/bgd_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
24838,50,"BGD","Bangladesh","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2000/bgd_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
24839,50,"BGD","Bangladesh","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2000/bgd_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
24840,50,"BGD","Bangladesh","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2000/bgd_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
24841,50,"BGD","Bangladesh","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2000/bgd_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
24842,50,"BGD","Bangladesh","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2000/bgd_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
24843,50,"BGD","Bangladesh","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2000/bgd_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
24844,50,"BGD","Bangladesh","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2000/bgd_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
24845,50,"BGD","Bangladesh","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2001/bgd_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
24846,50,"BGD","Bangladesh","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2001/bgd_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
24847,50,"BGD","Bangladesh","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2001/bgd_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
24848,50,"BGD","Bangladesh","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2001/bgd_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
24849,50,"BGD","Bangladesh","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2001/bgd_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
24850,50,"BGD","Bangladesh","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2001/bgd_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
24851,50,"BGD","Bangladesh","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2001/bgd_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
24852,50,"BGD","Bangladesh","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2001/bgd_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
24853,50,"BGD","Bangladesh","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2002/bgd_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
24854,50,"BGD","Bangladesh","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2002/bgd_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
24855,50,"BGD","Bangladesh","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2002/bgd_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
24856,50,"BGD","Bangladesh","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2002/bgd_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
24857,50,"BGD","Bangladesh","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2002/bgd_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
24858,50,"BGD","Bangladesh","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2002/bgd_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
24859,50,"BGD","Bangladesh","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2002/bgd_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
24860,50,"BGD","Bangladesh","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2002/bgd_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
24861,50,"BGD","Bangladesh","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2003/bgd_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
24862,50,"BGD","Bangladesh","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2003/bgd_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
24863,50,"BGD","Bangladesh","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2003/bgd_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
24864,50,"BGD","Bangladesh","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2003/bgd_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
24865,50,"BGD","Bangladesh","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2003/bgd_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
24866,50,"BGD","Bangladesh","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2003/bgd_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
24867,50,"BGD","Bangladesh","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2003/bgd_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
24868,50,"BGD","Bangladesh","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2003/bgd_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
24869,50,"BGD","Bangladesh","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2004/bgd_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
24870,50,"BGD","Bangladesh","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2004/bgd_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
24871,50,"BGD","Bangladesh","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2004/bgd_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
24872,50,"BGD","Bangladesh","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2004/bgd_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
24873,50,"BGD","Bangladesh","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2004/bgd_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
24874,50,"BGD","Bangladesh","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2004/bgd_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
24875,50,"BGD","Bangladesh","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2004/bgd_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
24876,50,"BGD","Bangladesh","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2004/bgd_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
24877,50,"BGD","Bangladesh","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2005/bgd_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
24878,50,"BGD","Bangladesh","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2005/bgd_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
24879,50,"BGD","Bangladesh","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2005/bgd_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
24880,50,"BGD","Bangladesh","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2005/bgd_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
24881,50,"BGD","Bangladesh","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2005/bgd_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
24882,50,"BGD","Bangladesh","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2005/bgd_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
24883,50,"BGD","Bangladesh","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2005/bgd_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
24884,50,"BGD","Bangladesh","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2005/bgd_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
24885,50,"BGD","Bangladesh","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2006/bgd_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
24886,50,"BGD","Bangladesh","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2006/bgd_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
24887,50,"BGD","Bangladesh","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2006/bgd_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
24888,50,"BGD","Bangladesh","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2006/bgd_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
24889,50,"BGD","Bangladesh","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2006/bgd_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
24890,50,"BGD","Bangladesh","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2006/bgd_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
24891,50,"BGD","Bangladesh","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2006/bgd_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
24892,50,"BGD","Bangladesh","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2006/bgd_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
24893,50,"BGD","Bangladesh","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2007/bgd_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
24894,50,"BGD","Bangladesh","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2007/bgd_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
24895,50,"BGD","Bangladesh","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2007/bgd_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
24896,50,"BGD","Bangladesh","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2007/bgd_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
24897,50,"BGD","Bangladesh","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2007/bgd_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
24898,50,"BGD","Bangladesh","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2007/bgd_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
24899,50,"BGD","Bangladesh","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2007/bgd_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
24900,50,"BGD","Bangladesh","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2007/bgd_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
24901,50,"BGD","Bangladesh","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2008/bgd_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
24902,50,"BGD","Bangladesh","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2008/bgd_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
24903,50,"BGD","Bangladesh","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2008/bgd_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
24904,50,"BGD","Bangladesh","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2008/bgd_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
24905,50,"BGD","Bangladesh","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2008/bgd_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
24906,50,"BGD","Bangladesh","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2008/bgd_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
24907,50,"BGD","Bangladesh","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2008/bgd_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
24908,50,"BGD","Bangladesh","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2008/bgd_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
24909,50,"BGD","Bangladesh","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2009/bgd_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
24910,50,"BGD","Bangladesh","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2009/bgd_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
24911,50,"BGD","Bangladesh","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2009/bgd_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
24912,50,"BGD","Bangladesh","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2009/bgd_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
24913,50,"BGD","Bangladesh","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2009/bgd_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
24914,50,"BGD","Bangladesh","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2009/bgd_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
24915,50,"BGD","Bangladesh","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2009/bgd_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
24916,50,"BGD","Bangladesh","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2009/bgd_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
24917,50,"BGD","Bangladesh","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2010/bgd_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
24918,50,"BGD","Bangladesh","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2010/bgd_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
24919,50,"BGD","Bangladesh","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2010/bgd_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
24920,50,"BGD","Bangladesh","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2010/bgd_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
24921,50,"BGD","Bangladesh","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2010/bgd_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
24922,50,"BGD","Bangladesh","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2010/bgd_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
24923,50,"BGD","Bangladesh","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2010/bgd_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
24924,50,"BGD","Bangladesh","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2010/bgd_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
24925,50,"BGD","Bangladesh","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2011/bgd_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
24926,50,"BGD","Bangladesh","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2011/bgd_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
24927,50,"BGD","Bangladesh","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2011/bgd_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
24928,50,"BGD","Bangladesh","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2011/bgd_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
24929,50,"BGD","Bangladesh","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2011/bgd_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
24930,50,"BGD","Bangladesh","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2011/bgd_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
24931,50,"BGD","Bangladesh","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2011/bgd_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
24932,50,"BGD","Bangladesh","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2011/bgd_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
24933,50,"BGD","Bangladesh","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2012/bgd_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
24934,50,"BGD","Bangladesh","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2012/bgd_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
24935,50,"BGD","Bangladesh","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2012/bgd_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
24936,50,"BGD","Bangladesh","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2012/bgd_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
24937,50,"BGD","Bangladesh","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2012/bgd_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
24938,50,"BGD","Bangladesh","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2012/bgd_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
24939,50,"BGD","Bangladesh","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2012/bgd_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
24940,50,"BGD","Bangladesh","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2012/bgd_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
24941,50,"BGD","Bangladesh","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2013/bgd_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
24942,50,"BGD","Bangladesh","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2013/bgd_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
24943,50,"BGD","Bangladesh","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2013/bgd_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
24944,50,"BGD","Bangladesh","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2013/bgd_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
24945,50,"BGD","Bangladesh","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2013/bgd_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
24946,50,"BGD","Bangladesh","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2013/bgd_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
24947,50,"BGD","Bangladesh","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2013/bgd_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
24948,50,"BGD","Bangladesh","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2013/bgd_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
24949,50,"BGD","Bangladesh","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2014/bgd_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
24950,50,"BGD","Bangladesh","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2014/bgd_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
24951,50,"BGD","Bangladesh","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2014/bgd_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
24952,50,"BGD","Bangladesh","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2014/bgd_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
24953,50,"BGD","Bangladesh","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2014/bgd_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
24954,50,"BGD","Bangladesh","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2014/bgd_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
24955,50,"BGD","Bangladesh","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2014/bgd_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
24956,50,"BGD","Bangladesh","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2014/bgd_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
24957,50,"BGD","Bangladesh","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2015/bgd_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
24958,50,"BGD","Bangladesh","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2015/bgd_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
24959,50,"BGD","Bangladesh","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2015/bgd_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
24960,50,"BGD","Bangladesh","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2015/bgd_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
24961,50,"BGD","Bangladesh","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2015/bgd_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
24962,50,"BGD","Bangladesh","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2015/bgd_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
24963,50,"BGD","Bangladesh","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2015/bgd_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
24964,50,"BGD","Bangladesh","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Annual/2015/bgd_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
24965,51,"ARM","Armenia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2000/arm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
24966,51,"ARM","Armenia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2000/arm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
24967,51,"ARM","Armenia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2000/arm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
24968,51,"ARM","Armenia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2000/arm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
24969,51,"ARM","Armenia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2000/arm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
24970,51,"ARM","Armenia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2000/arm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
24971,51,"ARM","Armenia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2000/arm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
24972,51,"ARM","Armenia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2000/arm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
24973,51,"ARM","Armenia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2001/arm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
24974,51,"ARM","Armenia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2001/arm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
24975,51,"ARM","Armenia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2001/arm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
24976,51,"ARM","Armenia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2001/arm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
24977,51,"ARM","Armenia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2001/arm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
24978,51,"ARM","Armenia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2001/arm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
24979,51,"ARM","Armenia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2001/arm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
24980,51,"ARM","Armenia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2001/arm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
24981,51,"ARM","Armenia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2002/arm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
24982,51,"ARM","Armenia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2002/arm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
24983,51,"ARM","Armenia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2002/arm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
24984,51,"ARM","Armenia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2002/arm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
24985,51,"ARM","Armenia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2002/arm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
24986,51,"ARM","Armenia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2002/arm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
24987,51,"ARM","Armenia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2002/arm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
24988,51,"ARM","Armenia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2002/arm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
24989,51,"ARM","Armenia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2003/arm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
24990,51,"ARM","Armenia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2003/arm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
24991,51,"ARM","Armenia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2003/arm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
24992,51,"ARM","Armenia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2003/arm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
24993,51,"ARM","Armenia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2003/arm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
24994,51,"ARM","Armenia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2003/arm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
24995,51,"ARM","Armenia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2003/arm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
24996,51,"ARM","Armenia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2003/arm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
24997,51,"ARM","Armenia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2004/arm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
24998,51,"ARM","Armenia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2004/arm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
24999,51,"ARM","Armenia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2004/arm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
25000,51,"ARM","Armenia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2004/arm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
25001,51,"ARM","Armenia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2004/arm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
25002,51,"ARM","Armenia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2004/arm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
25003,51,"ARM","Armenia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2004/arm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
25004,51,"ARM","Armenia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2004/arm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
25005,51,"ARM","Armenia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2005/arm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
25006,51,"ARM","Armenia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2005/arm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
25007,51,"ARM","Armenia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2005/arm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
25008,51,"ARM","Armenia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2005/arm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
25009,51,"ARM","Armenia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2005/arm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
25010,51,"ARM","Armenia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2005/arm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
25011,51,"ARM","Armenia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2005/arm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
25012,51,"ARM","Armenia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2005/arm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
25013,51,"ARM","Armenia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2006/arm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
25014,51,"ARM","Armenia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2006/arm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
25015,51,"ARM","Armenia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2006/arm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
25016,51,"ARM","Armenia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2006/arm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
25017,51,"ARM","Armenia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2006/arm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
25018,51,"ARM","Armenia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2006/arm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
25019,51,"ARM","Armenia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2006/arm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
25020,51,"ARM","Armenia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2006/arm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
25021,51,"ARM","Armenia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2007/arm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
25022,51,"ARM","Armenia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2007/arm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
25023,51,"ARM","Armenia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2007/arm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
25024,51,"ARM","Armenia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2007/arm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
25025,51,"ARM","Armenia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2007/arm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
25026,51,"ARM","Armenia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2007/arm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
25027,51,"ARM","Armenia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2007/arm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
25028,51,"ARM","Armenia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2007/arm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
25029,51,"ARM","Armenia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2008/arm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
25030,51,"ARM","Armenia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2008/arm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
25031,51,"ARM","Armenia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2008/arm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
25032,51,"ARM","Armenia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2008/arm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
25033,51,"ARM","Armenia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2008/arm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
25034,51,"ARM","Armenia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2008/arm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
25035,51,"ARM","Armenia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2008/arm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
25036,51,"ARM","Armenia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2008/arm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
25037,51,"ARM","Armenia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2009/arm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
25038,51,"ARM","Armenia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2009/arm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
25039,51,"ARM","Armenia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2009/arm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
25040,51,"ARM","Armenia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2009/arm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
25041,51,"ARM","Armenia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2009/arm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
25042,51,"ARM","Armenia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2009/arm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
25043,51,"ARM","Armenia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2009/arm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
25044,51,"ARM","Armenia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2009/arm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
25045,51,"ARM","Armenia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2010/arm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
25046,51,"ARM","Armenia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2010/arm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
25047,51,"ARM","Armenia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2010/arm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
25048,51,"ARM","Armenia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2010/arm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
25049,51,"ARM","Armenia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2010/arm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
25050,51,"ARM","Armenia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2010/arm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
25051,51,"ARM","Armenia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2010/arm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
25052,51,"ARM","Armenia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2010/arm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
25053,51,"ARM","Armenia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2011/arm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
25054,51,"ARM","Armenia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2011/arm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
25055,51,"ARM","Armenia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2011/arm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
25056,51,"ARM","Armenia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2011/arm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
25057,51,"ARM","Armenia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2011/arm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
25058,51,"ARM","Armenia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2011/arm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
25059,51,"ARM","Armenia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2011/arm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
25060,51,"ARM","Armenia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2011/arm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
25061,51,"ARM","Armenia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2012/arm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
25062,51,"ARM","Armenia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2012/arm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
25063,51,"ARM","Armenia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2012/arm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
25064,51,"ARM","Armenia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2012/arm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
25065,51,"ARM","Armenia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2012/arm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
25066,51,"ARM","Armenia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2012/arm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
25067,51,"ARM","Armenia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2012/arm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
25068,51,"ARM","Armenia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2012/arm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
25069,51,"ARM","Armenia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2013/arm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
25070,51,"ARM","Armenia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2013/arm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
25071,51,"ARM","Armenia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2013/arm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
25072,51,"ARM","Armenia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2013/arm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
25073,51,"ARM","Armenia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2013/arm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
25074,51,"ARM","Armenia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2013/arm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
25075,51,"ARM","Armenia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2013/arm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
25076,51,"ARM","Armenia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2013/arm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
25077,51,"ARM","Armenia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2014/arm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
25078,51,"ARM","Armenia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2014/arm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
25079,51,"ARM","Armenia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2014/arm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
25080,51,"ARM","Armenia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2014/arm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
25081,51,"ARM","Armenia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2014/arm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
25082,51,"ARM","Armenia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2014/arm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
25083,51,"ARM","Armenia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2014/arm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
25084,51,"ARM","Armenia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2014/arm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
25085,51,"ARM","Armenia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2015/arm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
25086,51,"ARM","Armenia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2015/arm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
25087,51,"ARM","Armenia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2015/arm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
25088,51,"ARM","Armenia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2015/arm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
25089,51,"ARM","Armenia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2015/arm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
25090,51,"ARM","Armenia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2015/arm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
25091,51,"ARM","Armenia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2015/arm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
25092,51,"ARM","Armenia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Annual/2015/arm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
25093,52,"BRB","Barbados","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2000/brb_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
25094,52,"BRB","Barbados","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2000/brb_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
25095,52,"BRB","Barbados","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2000/brb_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
25096,52,"BRB","Barbados","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2000/brb_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
25097,52,"BRB","Barbados","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2000/brb_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
25098,52,"BRB","Barbados","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2000/brb_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
25099,52,"BRB","Barbados","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2000/brb_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
25100,52,"BRB","Barbados","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2000/brb_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
25101,52,"BRB","Barbados","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2001/brb_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
25102,52,"BRB","Barbados","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2001/brb_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
25103,52,"BRB","Barbados","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2001/brb_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
25104,52,"BRB","Barbados","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2001/brb_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
25105,52,"BRB","Barbados","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2001/brb_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
25106,52,"BRB","Barbados","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2001/brb_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
25107,52,"BRB","Barbados","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2001/brb_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
25108,52,"BRB","Barbados","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2001/brb_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
25109,52,"BRB","Barbados","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2002/brb_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
25110,52,"BRB","Barbados","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2002/brb_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
25111,52,"BRB","Barbados","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2002/brb_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
25112,52,"BRB","Barbados","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2002/brb_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
25113,52,"BRB","Barbados","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2002/brb_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
25114,52,"BRB","Barbados","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2002/brb_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
25115,52,"BRB","Barbados","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2002/brb_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
25116,52,"BRB","Barbados","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2002/brb_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
25117,52,"BRB","Barbados","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2003/brb_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
25118,52,"BRB","Barbados","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2003/brb_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
25119,52,"BRB","Barbados","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2003/brb_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
25120,52,"BRB","Barbados","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2003/brb_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
25121,52,"BRB","Barbados","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2003/brb_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
25122,52,"BRB","Barbados","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2003/brb_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
25123,52,"BRB","Barbados","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2003/brb_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
25124,52,"BRB","Barbados","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2003/brb_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
25125,52,"BRB","Barbados","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2004/brb_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
25126,52,"BRB","Barbados","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2004/brb_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
25127,52,"BRB","Barbados","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2004/brb_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
25128,52,"BRB","Barbados","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2004/brb_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
25129,52,"BRB","Barbados","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2004/brb_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
25130,52,"BRB","Barbados","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2004/brb_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
25131,52,"BRB","Barbados","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2004/brb_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
25132,52,"BRB","Barbados","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2004/brb_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
25133,52,"BRB","Barbados","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2005/brb_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
25134,52,"BRB","Barbados","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2005/brb_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
25135,52,"BRB","Barbados","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2005/brb_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
25136,52,"BRB","Barbados","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2005/brb_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
25137,52,"BRB","Barbados","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2005/brb_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
25138,52,"BRB","Barbados","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2005/brb_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
25139,52,"BRB","Barbados","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2005/brb_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
25140,52,"BRB","Barbados","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2005/brb_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
25141,52,"BRB","Barbados","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2006/brb_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
25142,52,"BRB","Barbados","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2006/brb_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
25143,52,"BRB","Barbados","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2006/brb_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
25144,52,"BRB","Barbados","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2006/brb_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
25145,52,"BRB","Barbados","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2006/brb_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
25146,52,"BRB","Barbados","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2006/brb_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
25147,52,"BRB","Barbados","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2006/brb_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
25148,52,"BRB","Barbados","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2006/brb_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
25149,52,"BRB","Barbados","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2007/brb_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
25150,52,"BRB","Barbados","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2007/brb_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
25151,52,"BRB","Barbados","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2007/brb_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
25152,52,"BRB","Barbados","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2007/brb_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
25153,52,"BRB","Barbados","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2007/brb_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
25154,52,"BRB","Barbados","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2007/brb_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
25155,52,"BRB","Barbados","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2007/brb_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
25156,52,"BRB","Barbados","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2007/brb_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
25157,52,"BRB","Barbados","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2008/brb_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
25158,52,"BRB","Barbados","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2008/brb_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
25159,52,"BRB","Barbados","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2008/brb_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
25160,52,"BRB","Barbados","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2008/brb_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
25161,52,"BRB","Barbados","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2008/brb_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
25162,52,"BRB","Barbados","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2008/brb_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
25163,52,"BRB","Barbados","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2008/brb_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
25164,52,"BRB","Barbados","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2008/brb_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
25165,52,"BRB","Barbados","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2009/brb_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
25166,52,"BRB","Barbados","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2009/brb_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
25167,52,"BRB","Barbados","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2009/brb_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
25168,52,"BRB","Barbados","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2009/brb_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
25169,52,"BRB","Barbados","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2009/brb_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
25170,52,"BRB","Barbados","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2009/brb_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
25171,52,"BRB","Barbados","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2009/brb_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
25172,52,"BRB","Barbados","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2009/brb_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
25173,52,"BRB","Barbados","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2010/brb_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
25174,52,"BRB","Barbados","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2010/brb_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
25175,52,"BRB","Barbados","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2010/brb_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
25176,52,"BRB","Barbados","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2010/brb_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
25177,52,"BRB","Barbados","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2010/brb_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
25178,52,"BRB","Barbados","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2010/brb_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
25179,52,"BRB","Barbados","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2010/brb_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
25180,52,"BRB","Barbados","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2010/brb_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
25181,52,"BRB","Barbados","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2011/brb_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
25182,52,"BRB","Barbados","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2011/brb_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
25183,52,"BRB","Barbados","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2011/brb_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
25184,52,"BRB","Barbados","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2011/brb_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
25185,52,"BRB","Barbados","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2011/brb_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
25186,52,"BRB","Barbados","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2011/brb_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
25187,52,"BRB","Barbados","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2011/brb_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
25188,52,"BRB","Barbados","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2011/brb_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
25189,52,"BRB","Barbados","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2012/brb_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
25190,52,"BRB","Barbados","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2012/brb_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
25191,52,"BRB","Barbados","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2012/brb_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
25192,52,"BRB","Barbados","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2012/brb_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
25193,52,"BRB","Barbados","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2012/brb_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
25194,52,"BRB","Barbados","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2012/brb_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
25195,52,"BRB","Barbados","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2012/brb_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
25196,52,"BRB","Barbados","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2012/brb_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
25197,52,"BRB","Barbados","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2013/brb_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
25198,52,"BRB","Barbados","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2013/brb_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
25199,52,"BRB","Barbados","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2013/brb_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
25200,52,"BRB","Barbados","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2013/brb_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
25201,52,"BRB","Barbados","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2013/brb_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
25202,52,"BRB","Barbados","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2013/brb_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
25203,52,"BRB","Barbados","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2013/brb_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
25204,52,"BRB","Barbados","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2013/brb_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
25205,52,"BRB","Barbados","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2014/brb_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
25206,52,"BRB","Barbados","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2014/brb_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
25207,52,"BRB","Barbados","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2014/brb_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
25208,52,"BRB","Barbados","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2014/brb_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
25209,52,"BRB","Barbados","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2014/brb_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
25210,52,"BRB","Barbados","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2014/brb_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
25211,52,"BRB","Barbados","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2014/brb_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
25212,52,"BRB","Barbados","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2014/brb_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
25213,52,"BRB","Barbados","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2015/brb_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
25214,52,"BRB","Barbados","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2015/brb_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
25215,52,"BRB","Barbados","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2015/brb_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
25216,52,"BRB","Barbados","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2015/brb_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
25217,52,"BRB","Barbados","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2015/brb_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
25218,52,"BRB","Barbados","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2015/brb_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
25219,52,"BRB","Barbados","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2015/brb_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
25220,52,"BRB","Barbados","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Annual/2015/brb_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
25221,56,"BEL","Belgium","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2000/bel_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
25222,56,"BEL","Belgium","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2000/bel_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
25223,56,"BEL","Belgium","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2000/bel_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
25224,56,"BEL","Belgium","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2000/bel_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
25225,56,"BEL","Belgium","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2000/bel_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
25226,56,"BEL","Belgium","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2000/bel_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
25227,56,"BEL","Belgium","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2000/bel_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
25228,56,"BEL","Belgium","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2000/bel_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
25229,56,"BEL","Belgium","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2001/bel_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
25230,56,"BEL","Belgium","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2001/bel_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
25231,56,"BEL","Belgium","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2001/bel_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
25232,56,"BEL","Belgium","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2001/bel_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
25233,56,"BEL","Belgium","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2001/bel_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
25234,56,"BEL","Belgium","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2001/bel_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
25235,56,"BEL","Belgium","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2001/bel_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
25236,56,"BEL","Belgium","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2001/bel_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
25237,56,"BEL","Belgium","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2002/bel_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
25238,56,"BEL","Belgium","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2002/bel_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
25239,56,"BEL","Belgium","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2002/bel_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
25240,56,"BEL","Belgium","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2002/bel_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
25241,56,"BEL","Belgium","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2002/bel_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
25242,56,"BEL","Belgium","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2002/bel_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
25243,56,"BEL","Belgium","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2002/bel_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
25244,56,"BEL","Belgium","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2002/bel_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
25245,56,"BEL","Belgium","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2003/bel_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
25246,56,"BEL","Belgium","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2003/bel_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
25247,56,"BEL","Belgium","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2003/bel_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
25248,56,"BEL","Belgium","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2003/bel_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
25249,56,"BEL","Belgium","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2003/bel_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
25250,56,"BEL","Belgium","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2003/bel_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
25251,56,"BEL","Belgium","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2003/bel_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
25252,56,"BEL","Belgium","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2003/bel_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
25253,56,"BEL","Belgium","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2004/bel_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
25254,56,"BEL","Belgium","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2004/bel_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
25255,56,"BEL","Belgium","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2004/bel_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
25256,56,"BEL","Belgium","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2004/bel_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
25257,56,"BEL","Belgium","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2004/bel_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
25258,56,"BEL","Belgium","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2004/bel_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
25259,56,"BEL","Belgium","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2004/bel_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
25260,56,"BEL","Belgium","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2004/bel_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
25261,56,"BEL","Belgium","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2005/bel_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
25262,56,"BEL","Belgium","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2005/bel_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
25263,56,"BEL","Belgium","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2005/bel_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
25264,56,"BEL","Belgium","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2005/bel_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
25265,56,"BEL","Belgium","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2005/bel_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
25266,56,"BEL","Belgium","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2005/bel_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
25267,56,"BEL","Belgium","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2005/bel_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
25268,56,"BEL","Belgium","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2005/bel_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
25269,56,"BEL","Belgium","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2006/bel_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
25270,56,"BEL","Belgium","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2006/bel_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
25271,56,"BEL","Belgium","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2006/bel_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
25272,56,"BEL","Belgium","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2006/bel_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
25273,56,"BEL","Belgium","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2006/bel_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
25274,56,"BEL","Belgium","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2006/bel_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
25275,56,"BEL","Belgium","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2006/bel_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
25276,56,"BEL","Belgium","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2006/bel_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
25277,56,"BEL","Belgium","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2007/bel_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
25278,56,"BEL","Belgium","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2007/bel_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
25279,56,"BEL","Belgium","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2007/bel_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
25280,56,"BEL","Belgium","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2007/bel_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
25281,56,"BEL","Belgium","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2007/bel_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
25282,56,"BEL","Belgium","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2007/bel_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
25283,56,"BEL","Belgium","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2007/bel_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
25284,56,"BEL","Belgium","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2007/bel_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
25285,56,"BEL","Belgium","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2008/bel_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
25286,56,"BEL","Belgium","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2008/bel_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
25287,56,"BEL","Belgium","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2008/bel_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
25288,56,"BEL","Belgium","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2008/bel_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
25289,56,"BEL","Belgium","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2008/bel_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
25290,56,"BEL","Belgium","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2008/bel_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
25291,56,"BEL","Belgium","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2008/bel_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
25292,56,"BEL","Belgium","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2008/bel_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
25293,56,"BEL","Belgium","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2009/bel_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
25294,56,"BEL","Belgium","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2009/bel_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
25295,56,"BEL","Belgium","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2009/bel_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
25296,56,"BEL","Belgium","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2009/bel_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
25297,56,"BEL","Belgium","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2009/bel_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
25298,56,"BEL","Belgium","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2009/bel_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
25299,56,"BEL","Belgium","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2009/bel_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
25300,56,"BEL","Belgium","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2009/bel_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
25301,56,"BEL","Belgium","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2010/bel_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
25302,56,"BEL","Belgium","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2010/bel_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
25303,56,"BEL","Belgium","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2010/bel_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
25304,56,"BEL","Belgium","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2010/bel_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
25305,56,"BEL","Belgium","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2010/bel_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
25306,56,"BEL","Belgium","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2010/bel_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
25307,56,"BEL","Belgium","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2010/bel_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
25308,56,"BEL","Belgium","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2010/bel_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
25309,56,"BEL","Belgium","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2011/bel_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
25310,56,"BEL","Belgium","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2011/bel_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
25311,56,"BEL","Belgium","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2011/bel_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
25312,56,"BEL","Belgium","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2011/bel_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
25313,56,"BEL","Belgium","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2011/bel_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
25314,56,"BEL","Belgium","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2011/bel_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
25315,56,"BEL","Belgium","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2011/bel_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
25316,56,"BEL","Belgium","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2011/bel_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
25317,56,"BEL","Belgium","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2012/bel_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
25318,56,"BEL","Belgium","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2012/bel_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
25319,56,"BEL","Belgium","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2012/bel_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
25320,56,"BEL","Belgium","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2012/bel_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
25321,56,"BEL","Belgium","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2012/bel_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
25322,56,"BEL","Belgium","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2012/bel_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
25323,56,"BEL","Belgium","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2012/bel_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
25324,56,"BEL","Belgium","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2012/bel_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
25325,56,"BEL","Belgium","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2013/bel_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
25326,56,"BEL","Belgium","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2013/bel_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
25327,56,"BEL","Belgium","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2013/bel_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
25328,56,"BEL","Belgium","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2013/bel_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
25329,56,"BEL","Belgium","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2013/bel_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
25330,56,"BEL","Belgium","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2013/bel_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
25331,56,"BEL","Belgium","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2013/bel_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
25332,56,"BEL","Belgium","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2013/bel_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
25333,56,"BEL","Belgium","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2014/bel_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
25334,56,"BEL","Belgium","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2014/bel_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
25335,56,"BEL","Belgium","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2014/bel_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
25336,56,"BEL","Belgium","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2014/bel_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
25337,56,"BEL","Belgium","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2014/bel_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
25338,56,"BEL","Belgium","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2014/bel_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
25339,56,"BEL","Belgium","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2014/bel_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
25340,56,"BEL","Belgium","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2014/bel_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
25341,56,"BEL","Belgium","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2015/bel_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
25342,56,"BEL","Belgium","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2015/bel_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
25343,56,"BEL","Belgium","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2015/bel_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
25344,56,"BEL","Belgium","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2015/bel_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
25345,56,"BEL","Belgium","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2015/bel_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
25346,56,"BEL","Belgium","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2015/bel_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
25347,56,"BEL","Belgium","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2015/bel_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
25348,56,"BEL","Belgium","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Annual/2015/bel_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
25349,60,"BMU","Bermuda","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2000/bmu_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
25350,60,"BMU","Bermuda","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2000/bmu_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
25351,60,"BMU","Bermuda","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2000/bmu_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
25352,60,"BMU","Bermuda","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2000/bmu_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
25353,60,"BMU","Bermuda","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2000/bmu_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
25354,60,"BMU","Bermuda","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2000/bmu_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
25355,60,"BMU","Bermuda","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2000/bmu_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
25356,60,"BMU","Bermuda","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2000/bmu_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
25357,60,"BMU","Bermuda","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2001/bmu_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
25358,60,"BMU","Bermuda","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2001/bmu_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
25359,60,"BMU","Bermuda","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2001/bmu_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
25360,60,"BMU","Bermuda","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2001/bmu_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
25361,60,"BMU","Bermuda","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2001/bmu_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
25362,60,"BMU","Bermuda","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2001/bmu_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
25363,60,"BMU","Bermuda","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2001/bmu_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
25364,60,"BMU","Bermuda","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2001/bmu_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
25365,60,"BMU","Bermuda","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2002/bmu_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
25366,60,"BMU","Bermuda","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2002/bmu_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
25367,60,"BMU","Bermuda","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2002/bmu_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
25368,60,"BMU","Bermuda","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2002/bmu_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
25369,60,"BMU","Bermuda","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2002/bmu_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
25370,60,"BMU","Bermuda","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2002/bmu_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
25371,60,"BMU","Bermuda","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2002/bmu_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
25372,60,"BMU","Bermuda","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2002/bmu_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
25373,60,"BMU","Bermuda","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2003/bmu_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
25374,60,"BMU","Bermuda","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2003/bmu_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
25375,60,"BMU","Bermuda","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2003/bmu_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
25376,60,"BMU","Bermuda","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2003/bmu_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
25377,60,"BMU","Bermuda","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2003/bmu_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
25378,60,"BMU","Bermuda","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2003/bmu_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
25379,60,"BMU","Bermuda","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2003/bmu_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
25380,60,"BMU","Bermuda","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2003/bmu_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
25381,60,"BMU","Bermuda","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2004/bmu_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
25382,60,"BMU","Bermuda","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2004/bmu_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
25383,60,"BMU","Bermuda","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2004/bmu_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
25384,60,"BMU","Bermuda","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2004/bmu_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
25385,60,"BMU","Bermuda","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2004/bmu_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
25386,60,"BMU","Bermuda","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2004/bmu_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
25387,60,"BMU","Bermuda","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2004/bmu_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
25388,60,"BMU","Bermuda","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2004/bmu_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
25389,60,"BMU","Bermuda","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2005/bmu_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
25390,60,"BMU","Bermuda","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2005/bmu_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
25391,60,"BMU","Bermuda","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2005/bmu_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
25392,60,"BMU","Bermuda","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2005/bmu_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
25393,60,"BMU","Bermuda","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2005/bmu_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
25394,60,"BMU","Bermuda","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2005/bmu_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
25395,60,"BMU","Bermuda","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2005/bmu_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
25396,60,"BMU","Bermuda","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2005/bmu_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
25397,60,"BMU","Bermuda","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2006/bmu_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
25398,60,"BMU","Bermuda","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2006/bmu_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
25399,60,"BMU","Bermuda","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2006/bmu_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
25400,60,"BMU","Bermuda","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2006/bmu_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
25401,60,"BMU","Bermuda","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2006/bmu_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
25402,60,"BMU","Bermuda","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2006/bmu_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
25403,60,"BMU","Bermuda","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2006/bmu_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
25404,60,"BMU","Bermuda","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2006/bmu_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
25405,60,"BMU","Bermuda","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2007/bmu_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
25406,60,"BMU","Bermuda","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2007/bmu_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
25407,60,"BMU","Bermuda","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2007/bmu_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
25408,60,"BMU","Bermuda","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2007/bmu_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
25409,60,"BMU","Bermuda","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2007/bmu_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
25410,60,"BMU","Bermuda","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2007/bmu_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
25411,60,"BMU","Bermuda","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2007/bmu_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
25412,60,"BMU","Bermuda","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2007/bmu_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
25413,60,"BMU","Bermuda","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2008/bmu_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
25414,60,"BMU","Bermuda","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2008/bmu_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
25415,60,"BMU","Bermuda","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2008/bmu_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
25416,60,"BMU","Bermuda","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2008/bmu_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
25417,60,"BMU","Bermuda","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2008/bmu_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
25418,60,"BMU","Bermuda","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2008/bmu_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
25419,60,"BMU","Bermuda","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2008/bmu_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
25420,60,"BMU","Bermuda","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2008/bmu_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
25421,60,"BMU","Bermuda","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2009/bmu_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
25422,60,"BMU","Bermuda","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2009/bmu_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
25423,60,"BMU","Bermuda","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2009/bmu_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
25424,60,"BMU","Bermuda","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2009/bmu_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
25425,60,"BMU","Bermuda","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2009/bmu_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
25426,60,"BMU","Bermuda","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2009/bmu_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
25427,60,"BMU","Bermuda","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2009/bmu_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
25428,60,"BMU","Bermuda","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2009/bmu_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
25429,60,"BMU","Bermuda","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2010/bmu_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
25430,60,"BMU","Bermuda","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2010/bmu_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
25431,60,"BMU","Bermuda","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2010/bmu_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
25432,60,"BMU","Bermuda","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2010/bmu_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
25433,60,"BMU","Bermuda","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2010/bmu_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
25434,60,"BMU","Bermuda","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2010/bmu_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
25435,60,"BMU","Bermuda","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2010/bmu_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
25436,60,"BMU","Bermuda","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2010/bmu_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
25437,60,"BMU","Bermuda","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2011/bmu_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
25438,60,"BMU","Bermuda","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2011/bmu_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
25439,60,"BMU","Bermuda","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2011/bmu_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
25440,60,"BMU","Bermuda","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2011/bmu_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
25441,60,"BMU","Bermuda","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2011/bmu_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
25442,60,"BMU","Bermuda","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2011/bmu_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
25443,60,"BMU","Bermuda","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2011/bmu_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
25444,60,"BMU","Bermuda","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2011/bmu_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
25445,60,"BMU","Bermuda","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2012/bmu_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
25446,60,"BMU","Bermuda","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2012/bmu_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
25447,60,"BMU","Bermuda","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2012/bmu_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
25448,60,"BMU","Bermuda","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2012/bmu_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
25449,60,"BMU","Bermuda","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2012/bmu_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
25450,60,"BMU","Bermuda","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2012/bmu_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
25451,60,"BMU","Bermuda","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2012/bmu_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
25452,60,"BMU","Bermuda","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2012/bmu_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
25453,60,"BMU","Bermuda","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2013/bmu_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
25454,60,"BMU","Bermuda","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2013/bmu_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
25455,60,"BMU","Bermuda","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2013/bmu_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
25456,60,"BMU","Bermuda","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2013/bmu_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
25457,60,"BMU","Bermuda","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2013/bmu_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
25458,60,"BMU","Bermuda","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2013/bmu_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
25459,60,"BMU","Bermuda","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2013/bmu_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
25460,60,"BMU","Bermuda","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2013/bmu_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
25461,60,"BMU","Bermuda","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2014/bmu_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
25462,60,"BMU","Bermuda","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2014/bmu_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
25463,60,"BMU","Bermuda","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2014/bmu_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
25464,60,"BMU","Bermuda","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2014/bmu_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
25465,60,"BMU","Bermuda","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2014/bmu_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
25466,60,"BMU","Bermuda","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2014/bmu_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
25467,60,"BMU","Bermuda","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2014/bmu_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
25468,60,"BMU","Bermuda","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2014/bmu_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
25469,60,"BMU","Bermuda","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2015/bmu_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
25470,60,"BMU","Bermuda","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2015/bmu_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
25471,60,"BMU","Bermuda","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2015/bmu_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
25472,60,"BMU","Bermuda","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2015/bmu_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
25473,60,"BMU","Bermuda","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2015/bmu_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
25474,60,"BMU","Bermuda","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2015/bmu_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
25475,60,"BMU","Bermuda","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2015/bmu_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
25476,60,"BMU","Bermuda","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Annual/2015/bmu_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
25477,64,"BTN","Bhutan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2000/btn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
25478,64,"BTN","Bhutan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2000/btn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
25479,64,"BTN","Bhutan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2000/btn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
25480,64,"BTN","Bhutan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2000/btn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
25481,64,"BTN","Bhutan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2000/btn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
25482,64,"BTN","Bhutan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2000/btn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
25483,64,"BTN","Bhutan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2000/btn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
25484,64,"BTN","Bhutan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2000/btn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
25485,64,"BTN","Bhutan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2001/btn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
25486,64,"BTN","Bhutan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2001/btn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
25487,64,"BTN","Bhutan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2001/btn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
25488,64,"BTN","Bhutan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2001/btn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
25489,64,"BTN","Bhutan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2001/btn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
25490,64,"BTN","Bhutan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2001/btn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
25491,64,"BTN","Bhutan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2001/btn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
25492,64,"BTN","Bhutan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2001/btn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
25493,64,"BTN","Bhutan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2002/btn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
25494,64,"BTN","Bhutan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2002/btn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
25495,64,"BTN","Bhutan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2002/btn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
25496,64,"BTN","Bhutan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2002/btn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
25497,64,"BTN","Bhutan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2002/btn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
25498,64,"BTN","Bhutan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2002/btn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
25499,64,"BTN","Bhutan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2002/btn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
25500,64,"BTN","Bhutan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2002/btn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
25501,64,"BTN","Bhutan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2003/btn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
25502,64,"BTN","Bhutan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2003/btn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
25503,64,"BTN","Bhutan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2003/btn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
25504,64,"BTN","Bhutan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2003/btn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
25505,64,"BTN","Bhutan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2003/btn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
25506,64,"BTN","Bhutan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2003/btn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
25507,64,"BTN","Bhutan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2003/btn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
25508,64,"BTN","Bhutan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2003/btn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
25509,64,"BTN","Bhutan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2004/btn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
25510,64,"BTN","Bhutan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2004/btn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
25511,64,"BTN","Bhutan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2004/btn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
25512,64,"BTN","Bhutan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2004/btn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
25513,64,"BTN","Bhutan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2004/btn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
25514,64,"BTN","Bhutan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2004/btn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
25515,64,"BTN","Bhutan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2004/btn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
25516,64,"BTN","Bhutan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2004/btn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
25517,64,"BTN","Bhutan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2005/btn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
25518,64,"BTN","Bhutan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2005/btn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
25519,64,"BTN","Bhutan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2005/btn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
25520,64,"BTN","Bhutan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2005/btn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
25521,64,"BTN","Bhutan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2005/btn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
25522,64,"BTN","Bhutan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2005/btn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
25523,64,"BTN","Bhutan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2005/btn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
25524,64,"BTN","Bhutan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2005/btn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
25525,64,"BTN","Bhutan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2006/btn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
25526,64,"BTN","Bhutan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2006/btn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
25527,64,"BTN","Bhutan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2006/btn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
25528,64,"BTN","Bhutan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2006/btn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
25529,64,"BTN","Bhutan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2006/btn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
25530,64,"BTN","Bhutan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2006/btn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
25531,64,"BTN","Bhutan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2006/btn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
25532,64,"BTN","Bhutan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2006/btn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
25533,64,"BTN","Bhutan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2007/btn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
25534,64,"BTN","Bhutan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2007/btn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
25535,64,"BTN","Bhutan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2007/btn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
25536,64,"BTN","Bhutan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2007/btn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
25537,64,"BTN","Bhutan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2007/btn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
25538,64,"BTN","Bhutan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2007/btn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
25539,64,"BTN","Bhutan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2007/btn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
25540,64,"BTN","Bhutan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2007/btn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
25541,64,"BTN","Bhutan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2008/btn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
25542,64,"BTN","Bhutan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2008/btn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
25543,64,"BTN","Bhutan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2008/btn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
25544,64,"BTN","Bhutan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2008/btn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
25545,64,"BTN","Bhutan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2008/btn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
25546,64,"BTN","Bhutan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2008/btn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
25547,64,"BTN","Bhutan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2008/btn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
25548,64,"BTN","Bhutan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2008/btn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
25549,64,"BTN","Bhutan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2009/btn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
25550,64,"BTN","Bhutan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2009/btn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
25551,64,"BTN","Bhutan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2009/btn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
25552,64,"BTN","Bhutan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2009/btn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
25553,64,"BTN","Bhutan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2009/btn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
25554,64,"BTN","Bhutan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2009/btn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
25555,64,"BTN","Bhutan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2009/btn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
25556,64,"BTN","Bhutan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2009/btn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
25557,64,"BTN","Bhutan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2010/btn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
25558,64,"BTN","Bhutan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2010/btn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
25559,64,"BTN","Bhutan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2010/btn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
25560,64,"BTN","Bhutan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2010/btn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
25561,64,"BTN","Bhutan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2010/btn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
25562,64,"BTN","Bhutan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2010/btn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
25563,64,"BTN","Bhutan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2010/btn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
25564,64,"BTN","Bhutan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2010/btn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
25565,64,"BTN","Bhutan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2011/btn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
25566,64,"BTN","Bhutan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2011/btn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
25567,64,"BTN","Bhutan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2011/btn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
25568,64,"BTN","Bhutan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2011/btn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
25569,64,"BTN","Bhutan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2011/btn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
25570,64,"BTN","Bhutan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2011/btn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
25571,64,"BTN","Bhutan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2011/btn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
25572,64,"BTN","Bhutan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2011/btn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
25573,64,"BTN","Bhutan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2012/btn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
25574,64,"BTN","Bhutan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2012/btn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
25575,64,"BTN","Bhutan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2012/btn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
25576,64,"BTN","Bhutan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2012/btn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
25577,64,"BTN","Bhutan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2012/btn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
25578,64,"BTN","Bhutan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2012/btn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
25579,64,"BTN","Bhutan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2012/btn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
25580,64,"BTN","Bhutan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2012/btn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
25581,64,"BTN","Bhutan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2013/btn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
25582,64,"BTN","Bhutan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2013/btn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
25583,64,"BTN","Bhutan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2013/btn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
25584,64,"BTN","Bhutan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2013/btn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
25585,64,"BTN","Bhutan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2013/btn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
25586,64,"BTN","Bhutan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2013/btn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
25587,64,"BTN","Bhutan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2013/btn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
25588,64,"BTN","Bhutan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2013/btn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
25589,64,"BTN","Bhutan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2014/btn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
25590,64,"BTN","Bhutan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2014/btn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
25591,64,"BTN","Bhutan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2014/btn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
25592,64,"BTN","Bhutan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2014/btn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
25593,64,"BTN","Bhutan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2014/btn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
25594,64,"BTN","Bhutan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2014/btn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
25595,64,"BTN","Bhutan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2014/btn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
25596,64,"BTN","Bhutan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2014/btn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
25597,64,"BTN","Bhutan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2015/btn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
25598,64,"BTN","Bhutan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2015/btn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
25599,64,"BTN","Bhutan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2015/btn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
25600,64,"BTN","Bhutan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2015/btn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
25601,64,"BTN","Bhutan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2015/btn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
25602,64,"BTN","Bhutan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2015/btn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
25603,64,"BTN","Bhutan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2015/btn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
25604,64,"BTN","Bhutan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Annual/2015/btn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
25605,68,"BOL","Bolivia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2000/bol_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
25606,68,"BOL","Bolivia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2000/bol_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
25607,68,"BOL","Bolivia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2000/bol_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
25608,68,"BOL","Bolivia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2000/bol_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
25609,68,"BOL","Bolivia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2000/bol_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
25610,68,"BOL","Bolivia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2000/bol_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
25611,68,"BOL","Bolivia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2000/bol_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
25612,68,"BOL","Bolivia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2000/bol_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
25613,68,"BOL","Bolivia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2001/bol_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
25614,68,"BOL","Bolivia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2001/bol_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
25615,68,"BOL","Bolivia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2001/bol_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
25616,68,"BOL","Bolivia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2001/bol_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
25617,68,"BOL","Bolivia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2001/bol_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
25618,68,"BOL","Bolivia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2001/bol_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
25619,68,"BOL","Bolivia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2001/bol_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
25620,68,"BOL","Bolivia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2001/bol_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
25621,68,"BOL","Bolivia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2002/bol_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
25622,68,"BOL","Bolivia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2002/bol_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
25623,68,"BOL","Bolivia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2002/bol_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
25624,68,"BOL","Bolivia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2002/bol_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
25625,68,"BOL","Bolivia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2002/bol_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
25626,68,"BOL","Bolivia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2002/bol_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
25627,68,"BOL","Bolivia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2002/bol_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
25628,68,"BOL","Bolivia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2002/bol_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
25629,68,"BOL","Bolivia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2003/bol_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
25630,68,"BOL","Bolivia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2003/bol_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
25631,68,"BOL","Bolivia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2003/bol_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
25632,68,"BOL","Bolivia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2003/bol_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
25633,68,"BOL","Bolivia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2003/bol_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
25634,68,"BOL","Bolivia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2003/bol_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
25635,68,"BOL","Bolivia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2003/bol_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
25636,68,"BOL","Bolivia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2003/bol_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
25637,68,"BOL","Bolivia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2004/bol_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
25638,68,"BOL","Bolivia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2004/bol_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
25639,68,"BOL","Bolivia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2004/bol_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
25640,68,"BOL","Bolivia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2004/bol_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
25641,68,"BOL","Bolivia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2004/bol_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
25642,68,"BOL","Bolivia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2004/bol_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
25643,68,"BOL","Bolivia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2004/bol_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
25644,68,"BOL","Bolivia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2004/bol_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
25645,68,"BOL","Bolivia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2005/bol_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
25646,68,"BOL","Bolivia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2005/bol_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
25647,68,"BOL","Bolivia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2005/bol_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
25648,68,"BOL","Bolivia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2005/bol_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
25649,68,"BOL","Bolivia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2005/bol_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
25650,68,"BOL","Bolivia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2005/bol_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
25651,68,"BOL","Bolivia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2005/bol_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
25652,68,"BOL","Bolivia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2005/bol_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
25653,68,"BOL","Bolivia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2006/bol_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
25654,68,"BOL","Bolivia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2006/bol_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
25655,68,"BOL","Bolivia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2006/bol_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
25656,68,"BOL","Bolivia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2006/bol_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
25657,68,"BOL","Bolivia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2006/bol_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
25658,68,"BOL","Bolivia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2006/bol_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
25659,68,"BOL","Bolivia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2006/bol_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
25660,68,"BOL","Bolivia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2006/bol_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
25661,68,"BOL","Bolivia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2007/bol_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
25662,68,"BOL","Bolivia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2007/bol_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
25663,68,"BOL","Bolivia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2007/bol_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
25664,68,"BOL","Bolivia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2007/bol_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
25665,68,"BOL","Bolivia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2007/bol_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
25666,68,"BOL","Bolivia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2007/bol_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
25667,68,"BOL","Bolivia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2007/bol_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
25668,68,"BOL","Bolivia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2007/bol_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
25669,68,"BOL","Bolivia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2008/bol_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
25670,68,"BOL","Bolivia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2008/bol_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
25671,68,"BOL","Bolivia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2008/bol_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
25672,68,"BOL","Bolivia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2008/bol_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
25673,68,"BOL","Bolivia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2008/bol_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
25674,68,"BOL","Bolivia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2008/bol_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
25675,68,"BOL","Bolivia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2008/bol_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
25676,68,"BOL","Bolivia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2008/bol_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
25677,68,"BOL","Bolivia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2009/bol_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
25678,68,"BOL","Bolivia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2009/bol_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
25679,68,"BOL","Bolivia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2009/bol_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
25680,68,"BOL","Bolivia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2009/bol_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
25681,68,"BOL","Bolivia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2009/bol_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
25682,68,"BOL","Bolivia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2009/bol_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
25683,68,"BOL","Bolivia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2009/bol_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
25684,68,"BOL","Bolivia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2009/bol_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
25685,68,"BOL","Bolivia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2010/bol_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
25686,68,"BOL","Bolivia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2010/bol_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
25687,68,"BOL","Bolivia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2010/bol_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
25688,68,"BOL","Bolivia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2010/bol_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
25689,68,"BOL","Bolivia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2010/bol_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
25690,68,"BOL","Bolivia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2010/bol_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
25691,68,"BOL","Bolivia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2010/bol_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
25692,68,"BOL","Bolivia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2010/bol_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
25693,68,"BOL","Bolivia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2011/bol_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
25694,68,"BOL","Bolivia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2011/bol_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
25695,68,"BOL","Bolivia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2011/bol_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
25696,68,"BOL","Bolivia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2011/bol_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
25697,68,"BOL","Bolivia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2011/bol_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
25698,68,"BOL","Bolivia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2011/bol_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
25699,68,"BOL","Bolivia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2011/bol_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
25700,68,"BOL","Bolivia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2011/bol_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
25701,68,"BOL","Bolivia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2012/bol_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
25702,68,"BOL","Bolivia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2012/bol_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
25703,68,"BOL","Bolivia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2012/bol_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
25704,68,"BOL","Bolivia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2012/bol_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
25705,68,"BOL","Bolivia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2012/bol_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
25706,68,"BOL","Bolivia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2012/bol_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
25707,68,"BOL","Bolivia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2012/bol_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
25708,68,"BOL","Bolivia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2012/bol_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
25709,68,"BOL","Bolivia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2013/bol_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
25710,68,"BOL","Bolivia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2013/bol_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
25711,68,"BOL","Bolivia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2013/bol_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
25712,68,"BOL","Bolivia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2013/bol_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
25713,68,"BOL","Bolivia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2013/bol_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
25714,68,"BOL","Bolivia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2013/bol_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
25715,68,"BOL","Bolivia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2013/bol_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
25716,68,"BOL","Bolivia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2013/bol_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
25717,68,"BOL","Bolivia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2014/bol_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
25718,68,"BOL","Bolivia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2014/bol_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
25719,68,"BOL","Bolivia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2014/bol_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
25720,68,"BOL","Bolivia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2014/bol_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
25721,68,"BOL","Bolivia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2014/bol_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
25722,68,"BOL","Bolivia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2014/bol_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
25723,68,"BOL","Bolivia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2014/bol_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
25724,68,"BOL","Bolivia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2014/bol_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
25725,68,"BOL","Bolivia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2015/bol_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
25726,68,"BOL","Bolivia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2015/bol_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
25727,68,"BOL","Bolivia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2015/bol_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
25728,68,"BOL","Bolivia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2015/bol_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
25729,68,"BOL","Bolivia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2015/bol_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
25730,68,"BOL","Bolivia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2015/bol_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
25731,68,"BOL","Bolivia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2015/bol_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
25732,68,"BOL","Bolivia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Annual/2015/bol_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
25733,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2000/bih_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
25734,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2000/bih_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
25735,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2000/bih_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
25736,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2000/bih_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
25737,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2000/bih_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
25738,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2000/bih_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
25739,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2000/bih_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
25740,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2000/bih_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
25741,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2001/bih_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
25742,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2001/bih_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
25743,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2001/bih_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
25744,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2001/bih_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
25745,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2001/bih_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
25746,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2001/bih_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
25747,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2001/bih_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
25748,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2001/bih_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
25749,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2002/bih_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
25750,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2002/bih_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
25751,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2002/bih_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
25752,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2002/bih_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
25753,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2002/bih_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
25754,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2002/bih_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
25755,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2002/bih_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
25756,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2002/bih_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
25757,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2003/bih_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
25758,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2003/bih_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
25759,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2003/bih_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
25760,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2003/bih_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
25761,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2003/bih_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
25762,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2003/bih_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
25763,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2003/bih_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
25764,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2003/bih_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
25765,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2004/bih_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
25766,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2004/bih_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
25767,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2004/bih_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
25768,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2004/bih_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
25769,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2004/bih_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
25770,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2004/bih_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
25771,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2004/bih_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
25772,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2004/bih_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
25773,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2005/bih_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
25774,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2005/bih_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
25775,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2005/bih_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
25776,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2005/bih_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
25777,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2005/bih_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
25778,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2005/bih_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
25779,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2005/bih_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
25780,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2005/bih_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
25781,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2006/bih_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
25782,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2006/bih_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
25783,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2006/bih_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
25784,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2006/bih_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
25785,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2006/bih_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
25786,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2006/bih_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
25787,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2006/bih_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
25788,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2006/bih_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
25789,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2007/bih_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
25790,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2007/bih_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
25791,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2007/bih_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
25792,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2007/bih_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
25793,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2007/bih_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
25794,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2007/bih_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
25795,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2007/bih_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
25796,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2007/bih_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
25797,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2008/bih_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
25798,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2008/bih_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
25799,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2008/bih_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
25800,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2008/bih_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
25801,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2008/bih_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
25802,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2008/bih_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
25803,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2008/bih_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
25804,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2008/bih_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
25805,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2009/bih_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
25806,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2009/bih_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
25807,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2009/bih_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
25808,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2009/bih_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
25809,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2009/bih_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
25810,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2009/bih_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
25811,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2009/bih_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
25812,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2009/bih_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
25813,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2010/bih_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
25814,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2010/bih_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
25815,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2010/bih_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
25816,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2010/bih_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
25817,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2010/bih_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
25818,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2010/bih_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
25819,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2010/bih_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
25820,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2010/bih_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
25821,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2011/bih_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
25822,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2011/bih_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
25823,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2011/bih_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
25824,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2011/bih_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
25825,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2011/bih_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
25826,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2011/bih_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
25827,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2011/bih_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
25828,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2011/bih_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
25829,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2012/bih_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
25830,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2012/bih_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
25831,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2012/bih_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
25832,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2012/bih_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
25833,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2012/bih_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
25834,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2012/bih_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
25835,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2012/bih_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
25836,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2012/bih_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
25837,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2013/bih_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
25838,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2013/bih_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
25839,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2013/bih_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
25840,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2013/bih_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
25841,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2013/bih_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
25842,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2013/bih_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
25843,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2013/bih_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
25844,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2013/bih_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
25845,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2014/bih_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
25846,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2014/bih_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
25847,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2014/bih_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
25848,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2014/bih_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
25849,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2014/bih_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
25850,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2014/bih_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
25851,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2014/bih_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
25852,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2014/bih_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
25853,70,"BIH","Bosnia and Herzegovina","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2015/bih_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
25854,70,"BIH","Bosnia and Herzegovina","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2015/bih_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
25855,70,"BIH","Bosnia and Herzegovina","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2015/bih_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
25856,70,"BIH","Bosnia and Herzegovina","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2015/bih_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
25857,70,"BIH","Bosnia and Herzegovina","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2015/bih_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
25858,70,"BIH","Bosnia and Herzegovina","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2015/bih_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
25859,70,"BIH","Bosnia and Herzegovina","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2015/bih_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
25860,70,"BIH","Bosnia and Herzegovina","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Annual/2015/bih_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
25861,72,"BWA","Botswana","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2000/bwa_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
25862,72,"BWA","Botswana","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2000/bwa_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
25863,72,"BWA","Botswana","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2000/bwa_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
25864,72,"BWA","Botswana","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2000/bwa_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
25865,72,"BWA","Botswana","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2000/bwa_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
25866,72,"BWA","Botswana","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2000/bwa_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
25867,72,"BWA","Botswana","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2000/bwa_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
25868,72,"BWA","Botswana","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2000/bwa_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
25869,72,"BWA","Botswana","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2001/bwa_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
25870,72,"BWA","Botswana","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2001/bwa_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
25871,72,"BWA","Botswana","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2001/bwa_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
25872,72,"BWA","Botswana","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2001/bwa_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
25873,72,"BWA","Botswana","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2001/bwa_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
25874,72,"BWA","Botswana","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2001/bwa_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
25875,72,"BWA","Botswana","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2001/bwa_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
25876,72,"BWA","Botswana","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2001/bwa_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
25877,72,"BWA","Botswana","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2002/bwa_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
25878,72,"BWA","Botswana","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2002/bwa_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
25879,72,"BWA","Botswana","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2002/bwa_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
25880,72,"BWA","Botswana","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2002/bwa_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
25881,72,"BWA","Botswana","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2002/bwa_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
25882,72,"BWA","Botswana","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2002/bwa_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
25883,72,"BWA","Botswana","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2002/bwa_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
25884,72,"BWA","Botswana","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2002/bwa_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
25885,72,"BWA","Botswana","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2003/bwa_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
25886,72,"BWA","Botswana","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2003/bwa_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
25887,72,"BWA","Botswana","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2003/bwa_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
25888,72,"BWA","Botswana","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2003/bwa_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
25889,72,"BWA","Botswana","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2003/bwa_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
25890,72,"BWA","Botswana","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2003/bwa_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
25891,72,"BWA","Botswana","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2003/bwa_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
25892,72,"BWA","Botswana","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2003/bwa_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
25893,72,"BWA","Botswana","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2004/bwa_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
25894,72,"BWA","Botswana","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2004/bwa_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
25895,72,"BWA","Botswana","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2004/bwa_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
25896,72,"BWA","Botswana","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2004/bwa_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
25897,72,"BWA","Botswana","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2004/bwa_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
25898,72,"BWA","Botswana","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2004/bwa_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
25899,72,"BWA","Botswana","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2004/bwa_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
25900,72,"BWA","Botswana","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2004/bwa_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
25901,72,"BWA","Botswana","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2005/bwa_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
25902,72,"BWA","Botswana","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2005/bwa_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
25903,72,"BWA","Botswana","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2005/bwa_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
25904,72,"BWA","Botswana","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2005/bwa_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
25905,72,"BWA","Botswana","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2005/bwa_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
25906,72,"BWA","Botswana","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2005/bwa_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
25907,72,"BWA","Botswana","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2005/bwa_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
25908,72,"BWA","Botswana","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2005/bwa_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
25909,72,"BWA","Botswana","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2006/bwa_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
25910,72,"BWA","Botswana","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2006/bwa_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
25911,72,"BWA","Botswana","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2006/bwa_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
25912,72,"BWA","Botswana","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2006/bwa_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
25913,72,"BWA","Botswana","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2006/bwa_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
25914,72,"BWA","Botswana","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2006/bwa_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
25915,72,"BWA","Botswana","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2006/bwa_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
25916,72,"BWA","Botswana","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2006/bwa_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
25917,72,"BWA","Botswana","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2007/bwa_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
25918,72,"BWA","Botswana","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2007/bwa_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
25919,72,"BWA","Botswana","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2007/bwa_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
25920,72,"BWA","Botswana","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2007/bwa_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
25921,72,"BWA","Botswana","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2007/bwa_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
25922,72,"BWA","Botswana","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2007/bwa_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
25923,72,"BWA","Botswana","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2007/bwa_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
25924,72,"BWA","Botswana","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2007/bwa_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
25925,72,"BWA","Botswana","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2008/bwa_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
25926,72,"BWA","Botswana","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2008/bwa_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
25927,72,"BWA","Botswana","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2008/bwa_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
25928,72,"BWA","Botswana","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2008/bwa_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
25929,72,"BWA","Botswana","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2008/bwa_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
25930,72,"BWA","Botswana","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2008/bwa_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
25931,72,"BWA","Botswana","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2008/bwa_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
25932,72,"BWA","Botswana","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2008/bwa_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
25933,72,"BWA","Botswana","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2009/bwa_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
25934,72,"BWA","Botswana","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2009/bwa_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
25935,72,"BWA","Botswana","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2009/bwa_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
25936,72,"BWA","Botswana","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2009/bwa_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
25937,72,"BWA","Botswana","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2009/bwa_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
25938,72,"BWA","Botswana","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2009/bwa_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
25939,72,"BWA","Botswana","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2009/bwa_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
25940,72,"BWA","Botswana","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2009/bwa_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
25941,72,"BWA","Botswana","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2010/bwa_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
25942,72,"BWA","Botswana","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2010/bwa_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
25943,72,"BWA","Botswana","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2010/bwa_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
25944,72,"BWA","Botswana","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2010/bwa_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
25945,72,"BWA","Botswana","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2010/bwa_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
25946,72,"BWA","Botswana","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2010/bwa_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
25947,72,"BWA","Botswana","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2010/bwa_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
25948,72,"BWA","Botswana","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2010/bwa_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
25949,72,"BWA","Botswana","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2011/bwa_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
25950,72,"BWA","Botswana","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2011/bwa_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
25951,72,"BWA","Botswana","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2011/bwa_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
25952,72,"BWA","Botswana","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2011/bwa_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
25953,72,"BWA","Botswana","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2011/bwa_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
25954,72,"BWA","Botswana","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2011/bwa_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
25955,72,"BWA","Botswana","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2011/bwa_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
25956,72,"BWA","Botswana","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2011/bwa_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
25957,72,"BWA","Botswana","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2012/bwa_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
25958,72,"BWA","Botswana","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2012/bwa_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
25959,72,"BWA","Botswana","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2012/bwa_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
25960,72,"BWA","Botswana","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2012/bwa_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
25961,72,"BWA","Botswana","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2012/bwa_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
25962,72,"BWA","Botswana","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2012/bwa_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
25963,72,"BWA","Botswana","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2012/bwa_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
25964,72,"BWA","Botswana","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2012/bwa_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
25965,72,"BWA","Botswana","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2013/bwa_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
25966,72,"BWA","Botswana","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2013/bwa_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
25967,72,"BWA","Botswana","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2013/bwa_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
25968,72,"BWA","Botswana","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2013/bwa_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
25969,72,"BWA","Botswana","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2013/bwa_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
25970,72,"BWA","Botswana","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2013/bwa_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
25971,72,"BWA","Botswana","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2013/bwa_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
25972,72,"BWA","Botswana","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2013/bwa_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
25973,72,"BWA","Botswana","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2014/bwa_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
25974,72,"BWA","Botswana","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2014/bwa_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
25975,72,"BWA","Botswana","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2014/bwa_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
25976,72,"BWA","Botswana","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2014/bwa_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
25977,72,"BWA","Botswana","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2014/bwa_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
25978,72,"BWA","Botswana","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2014/bwa_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
25979,72,"BWA","Botswana","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2014/bwa_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
25980,72,"BWA","Botswana","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2014/bwa_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
25981,72,"BWA","Botswana","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2015/bwa_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
25982,72,"BWA","Botswana","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2015/bwa_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
25983,72,"BWA","Botswana","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2015/bwa_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
25984,72,"BWA","Botswana","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2015/bwa_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
25985,72,"BWA","Botswana","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2015/bwa_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
25986,72,"BWA","Botswana","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2015/bwa_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
25987,72,"BWA","Botswana","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2015/bwa_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
25988,72,"BWA","Botswana","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Annual/2015/bwa_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
25989,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2000/bvt_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
25990,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2000/bvt_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
25991,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2000/bvt_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
25992,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2000/bvt_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
25993,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2000/bvt_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
25994,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2000/bvt_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
25995,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2000/bvt_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
25996,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2000/bvt_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
25997,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2001/bvt_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
25998,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2001/bvt_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
25999,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2001/bvt_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
26000,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2001/bvt_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
26001,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2001/bvt_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
26002,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2001/bvt_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
26003,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2001/bvt_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
26004,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2001/bvt_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
26005,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2002/bvt_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
26006,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2002/bvt_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
26007,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2002/bvt_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
26008,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2002/bvt_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
26009,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2002/bvt_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
26010,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2002/bvt_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
26011,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2002/bvt_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
26012,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2002/bvt_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
26013,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2003/bvt_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
26014,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2003/bvt_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
26015,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2003/bvt_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
26016,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2003/bvt_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
26017,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2003/bvt_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
26018,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2003/bvt_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
26019,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2003/bvt_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
26020,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2003/bvt_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
26021,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2004/bvt_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
26022,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2004/bvt_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
26023,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2004/bvt_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
26024,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2004/bvt_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
26025,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2004/bvt_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
26026,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2004/bvt_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
26027,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2004/bvt_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
26028,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2004/bvt_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
26029,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2005/bvt_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
26030,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2005/bvt_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
26031,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2005/bvt_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
26032,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2005/bvt_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
26033,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2005/bvt_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
26034,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2005/bvt_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
26035,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2005/bvt_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
26036,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2005/bvt_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
26037,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2006/bvt_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
26038,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2006/bvt_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
26039,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2006/bvt_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
26040,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2006/bvt_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
26041,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2006/bvt_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
26042,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2006/bvt_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
26043,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2006/bvt_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
26044,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2006/bvt_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
26045,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2007/bvt_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
26046,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2007/bvt_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
26047,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2007/bvt_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
26048,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2007/bvt_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
26049,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2007/bvt_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
26050,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2007/bvt_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
26051,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2007/bvt_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
26052,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2007/bvt_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
26053,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2008/bvt_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
26054,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2008/bvt_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
26055,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2008/bvt_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
26056,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2008/bvt_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
26057,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2008/bvt_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
26058,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2008/bvt_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
26059,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2008/bvt_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
26060,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2008/bvt_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
26061,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2009/bvt_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
26062,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2009/bvt_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
26063,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2009/bvt_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
26064,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2009/bvt_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
26065,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2009/bvt_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
26066,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2009/bvt_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
26067,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2009/bvt_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
26068,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2009/bvt_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
26069,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2010/bvt_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
26070,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2010/bvt_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
26071,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2010/bvt_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
26072,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2010/bvt_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
26073,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2010/bvt_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
26074,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2010/bvt_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
26075,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2010/bvt_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
26076,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2010/bvt_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
26077,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2011/bvt_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
26078,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2011/bvt_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
26079,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2011/bvt_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
26080,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2011/bvt_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
26081,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2011/bvt_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
26082,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2011/bvt_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
26083,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2011/bvt_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
26084,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2011/bvt_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
26085,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2012/bvt_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
26086,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2012/bvt_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
26087,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2012/bvt_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
26088,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2012/bvt_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
26089,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2012/bvt_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
26090,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2012/bvt_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
26091,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2012/bvt_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
26092,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2012/bvt_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
26093,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2013/bvt_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
26094,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2013/bvt_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
26095,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2013/bvt_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
26096,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2013/bvt_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
26097,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2013/bvt_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
26098,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2013/bvt_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
26099,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2013/bvt_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
26100,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2013/bvt_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
26101,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2014/bvt_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
26102,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2014/bvt_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
26103,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2014/bvt_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
26104,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2014/bvt_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
26105,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2014/bvt_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
26106,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2014/bvt_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
26107,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2014/bvt_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
26108,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2014/bvt_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
26109,74,"BVT","Bouvet Island","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2015/bvt_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
26110,74,"BVT","Bouvet Island","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2015/bvt_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
26111,74,"BVT","Bouvet Island","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2015/bvt_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
26112,74,"BVT","Bouvet Island","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2015/bvt_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
26113,74,"BVT","Bouvet Island","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2015/bvt_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
26114,74,"BVT","Bouvet Island","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2015/bvt_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
26115,74,"BVT","Bouvet Island","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2015/bvt_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
26116,74,"BVT","Bouvet Island","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Annual/2015/bvt_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
26117,84,"BLZ","Belize","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2000/blz_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
26118,84,"BLZ","Belize","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2000/blz_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
26119,84,"BLZ","Belize","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2000/blz_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
26120,84,"BLZ","Belize","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2000/blz_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
26121,84,"BLZ","Belize","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2000/blz_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
26122,84,"BLZ","Belize","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2000/blz_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
26123,84,"BLZ","Belize","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2000/blz_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
26124,84,"BLZ","Belize","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2000/blz_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
26125,84,"BLZ","Belize","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2001/blz_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
26126,84,"BLZ","Belize","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2001/blz_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
26127,84,"BLZ","Belize","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2001/blz_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
26128,84,"BLZ","Belize","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2001/blz_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
26129,84,"BLZ","Belize","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2001/blz_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
26130,84,"BLZ","Belize","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2001/blz_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
26131,84,"BLZ","Belize","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2001/blz_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
26132,84,"BLZ","Belize","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2001/blz_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
26133,84,"BLZ","Belize","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2002/blz_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
26134,84,"BLZ","Belize","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2002/blz_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
26135,84,"BLZ","Belize","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2002/blz_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
26136,84,"BLZ","Belize","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2002/blz_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
26137,84,"BLZ","Belize","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2002/blz_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
26138,84,"BLZ","Belize","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2002/blz_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
26139,84,"BLZ","Belize","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2002/blz_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
26140,84,"BLZ","Belize","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2002/blz_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
26141,84,"BLZ","Belize","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2003/blz_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
26142,84,"BLZ","Belize","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2003/blz_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
26143,84,"BLZ","Belize","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2003/blz_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
26144,84,"BLZ","Belize","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2003/blz_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
26145,84,"BLZ","Belize","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2003/blz_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
26146,84,"BLZ","Belize","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2003/blz_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
26147,84,"BLZ","Belize","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2003/blz_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
26148,84,"BLZ","Belize","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2003/blz_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
26149,84,"BLZ","Belize","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2004/blz_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
26150,84,"BLZ","Belize","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2004/blz_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
26151,84,"BLZ","Belize","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2004/blz_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
26152,84,"BLZ","Belize","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2004/blz_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
26153,84,"BLZ","Belize","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2004/blz_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
26154,84,"BLZ","Belize","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2004/blz_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
26155,84,"BLZ","Belize","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2004/blz_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
26156,84,"BLZ","Belize","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2004/blz_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
26157,84,"BLZ","Belize","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2005/blz_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
26158,84,"BLZ","Belize","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2005/blz_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
26159,84,"BLZ","Belize","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2005/blz_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
26160,84,"BLZ","Belize","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2005/blz_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
26161,84,"BLZ","Belize","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2005/blz_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
26162,84,"BLZ","Belize","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2005/blz_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
26163,84,"BLZ","Belize","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2005/blz_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
26164,84,"BLZ","Belize","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2005/blz_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
26165,84,"BLZ","Belize","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2006/blz_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
26166,84,"BLZ","Belize","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2006/blz_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
26167,84,"BLZ","Belize","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2006/blz_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
26168,84,"BLZ","Belize","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2006/blz_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
26169,84,"BLZ","Belize","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2006/blz_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
26170,84,"BLZ","Belize","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2006/blz_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
26171,84,"BLZ","Belize","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2006/blz_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
26172,84,"BLZ","Belize","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2006/blz_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
26173,84,"BLZ","Belize","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2007/blz_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
26174,84,"BLZ","Belize","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2007/blz_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
26175,84,"BLZ","Belize","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2007/blz_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
26176,84,"BLZ","Belize","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2007/blz_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
26177,84,"BLZ","Belize","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2007/blz_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
26178,84,"BLZ","Belize","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2007/blz_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
26179,84,"BLZ","Belize","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2007/blz_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
26180,84,"BLZ","Belize","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2007/blz_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
26181,84,"BLZ","Belize","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2008/blz_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
26182,84,"BLZ","Belize","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2008/blz_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
26183,84,"BLZ","Belize","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2008/blz_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
26184,84,"BLZ","Belize","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2008/blz_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
26185,84,"BLZ","Belize","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2008/blz_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
26186,84,"BLZ","Belize","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2008/blz_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
26187,84,"BLZ","Belize","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2008/blz_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
26188,84,"BLZ","Belize","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2008/blz_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
26189,84,"BLZ","Belize","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2009/blz_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
26190,84,"BLZ","Belize","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2009/blz_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
26191,84,"BLZ","Belize","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2009/blz_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
26192,84,"BLZ","Belize","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2009/blz_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
26193,84,"BLZ","Belize","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2009/blz_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
26194,84,"BLZ","Belize","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2009/blz_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
26195,84,"BLZ","Belize","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2009/blz_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
26196,84,"BLZ","Belize","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2009/blz_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
26197,84,"BLZ","Belize","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2010/blz_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
26198,84,"BLZ","Belize","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2010/blz_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
26199,84,"BLZ","Belize","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2010/blz_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
26200,84,"BLZ","Belize","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2010/blz_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
26201,84,"BLZ","Belize","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2010/blz_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
26202,84,"BLZ","Belize","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2010/blz_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
26203,84,"BLZ","Belize","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2010/blz_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
26204,84,"BLZ","Belize","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2010/blz_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
26205,84,"BLZ","Belize","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2011/blz_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
26206,84,"BLZ","Belize","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2011/blz_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
26207,84,"BLZ","Belize","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2011/blz_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
26208,84,"BLZ","Belize","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2011/blz_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
26209,84,"BLZ","Belize","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2011/blz_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
26210,84,"BLZ","Belize","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2011/blz_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
26211,84,"BLZ","Belize","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2011/blz_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
26212,84,"BLZ","Belize","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2011/blz_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
26213,84,"BLZ","Belize","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2012/blz_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
26214,84,"BLZ","Belize","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2012/blz_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
26215,84,"BLZ","Belize","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2012/blz_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
26216,84,"BLZ","Belize","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2012/blz_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
26217,84,"BLZ","Belize","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2012/blz_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
26218,84,"BLZ","Belize","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2012/blz_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
26219,84,"BLZ","Belize","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2012/blz_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
26220,84,"BLZ","Belize","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2012/blz_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
26221,84,"BLZ","Belize","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2013/blz_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
26222,84,"BLZ","Belize","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2013/blz_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
26223,84,"BLZ","Belize","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2013/blz_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
26224,84,"BLZ","Belize","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2013/blz_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
26225,84,"BLZ","Belize","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2013/blz_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
26226,84,"BLZ","Belize","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2013/blz_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
26227,84,"BLZ","Belize","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2013/blz_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
26228,84,"BLZ","Belize","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2013/blz_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
26229,84,"BLZ","Belize","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2014/blz_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
26230,84,"BLZ","Belize","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2014/blz_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
26231,84,"BLZ","Belize","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2014/blz_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
26232,84,"BLZ","Belize","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2014/blz_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
26233,84,"BLZ","Belize","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2014/blz_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
26234,84,"BLZ","Belize","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2014/blz_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
26235,84,"BLZ","Belize","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2014/blz_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
26236,84,"BLZ","Belize","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2014/blz_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
26237,84,"BLZ","Belize","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2015/blz_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
26238,84,"BLZ","Belize","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2015/blz_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
26239,84,"BLZ","Belize","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2015/blz_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
26240,84,"BLZ","Belize","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2015/blz_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
26241,84,"BLZ","Belize","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2015/blz_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
26242,84,"BLZ","Belize","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2015/blz_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
26243,84,"BLZ","Belize","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2015/blz_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
26244,84,"BLZ","Belize","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Annual/2015/blz_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
26245,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2000/iot_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
26246,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2000/iot_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
26247,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2000/iot_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
26248,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2000/iot_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
26249,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2000/iot_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
26250,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2000/iot_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
26251,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2000/iot_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
26252,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2000/iot_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
26253,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2001/iot_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
26254,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2001/iot_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
26255,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2001/iot_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
26256,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2001/iot_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
26257,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2001/iot_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
26258,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2001/iot_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
26259,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2001/iot_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
26260,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2001/iot_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
26261,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2002/iot_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
26262,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2002/iot_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
26263,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2002/iot_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
26264,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2002/iot_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
26265,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2002/iot_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
26266,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2002/iot_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
26267,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2002/iot_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
26268,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2002/iot_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
26269,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2003/iot_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
26270,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2003/iot_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
26271,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2003/iot_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
26272,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2003/iot_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
26273,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2003/iot_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
26274,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2003/iot_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
26275,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2003/iot_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
26276,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2003/iot_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
26277,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2004/iot_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
26278,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2004/iot_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
26279,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2004/iot_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
26280,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2004/iot_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
26281,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2004/iot_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
26282,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2004/iot_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
26283,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2004/iot_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
26284,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2004/iot_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
26285,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2005/iot_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
26286,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2005/iot_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
26287,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2005/iot_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
26288,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2005/iot_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
26289,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2005/iot_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
26290,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2005/iot_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
26291,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2005/iot_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
26292,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2005/iot_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
26293,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2006/iot_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
26294,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2006/iot_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
26295,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2006/iot_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
26296,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2006/iot_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
26297,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2006/iot_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
26298,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2006/iot_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
26299,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2006/iot_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
26300,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2006/iot_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
26301,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2007/iot_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
26302,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2007/iot_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
26303,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2007/iot_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
26304,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2007/iot_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
26305,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2007/iot_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
26306,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2007/iot_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
26307,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2007/iot_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
26308,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2007/iot_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
26309,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2008/iot_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
26310,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2008/iot_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
26311,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2008/iot_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
26312,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2008/iot_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
26313,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2008/iot_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
26314,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2008/iot_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
26315,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2008/iot_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
26316,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2008/iot_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
26317,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2009/iot_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
26318,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2009/iot_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
26319,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2009/iot_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
26320,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2009/iot_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
26321,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2009/iot_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
26322,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2009/iot_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
26323,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2009/iot_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
26324,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2009/iot_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
26325,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2010/iot_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
26326,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2010/iot_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
26327,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2010/iot_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
26328,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2010/iot_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
26329,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2010/iot_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
26330,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2010/iot_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
26331,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2010/iot_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
26332,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2010/iot_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
26333,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2011/iot_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
26334,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2011/iot_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
26335,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2011/iot_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
26336,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2011/iot_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
26337,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2011/iot_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
26338,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2011/iot_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
26339,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2011/iot_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
26340,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2011/iot_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
26341,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2012/iot_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
26342,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2012/iot_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
26343,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2012/iot_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
26344,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2012/iot_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
26345,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2012/iot_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
26346,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2012/iot_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
26347,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2012/iot_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
26348,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2012/iot_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
26349,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2013/iot_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
26350,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2013/iot_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
26351,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2013/iot_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
26352,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2013/iot_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
26353,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2013/iot_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
26354,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2013/iot_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
26355,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2013/iot_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
26356,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2013/iot_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
26357,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2014/iot_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
26358,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2014/iot_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
26359,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2014/iot_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
26360,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2014/iot_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
26361,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2014/iot_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
26362,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2014/iot_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
26363,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2014/iot_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
26364,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2014/iot_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
26365,86,"IOT","British Indian Ocean Territory","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2015/iot_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
26366,86,"IOT","British Indian Ocean Territory","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2015/iot_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
26367,86,"IOT","British Indian Ocean Territory","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2015/iot_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
26368,86,"IOT","British Indian Ocean Territory","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2015/iot_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
26369,86,"IOT","British Indian Ocean Territory","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2015/iot_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
26370,86,"IOT","British Indian Ocean Territory","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2015/iot_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
26371,86,"IOT","British Indian Ocean Territory","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2015/iot_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
26372,86,"IOT","British Indian Ocean Territory","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Annual/2015/iot_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
26373,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2000/slb_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
26374,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2000/slb_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
26375,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2000/slb_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
26376,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2000/slb_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
26377,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2000/slb_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
26378,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2000/slb_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
26379,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2000/slb_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
26380,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2000/slb_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
26381,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2001/slb_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
26382,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2001/slb_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
26383,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2001/slb_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
26384,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2001/slb_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
26385,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2001/slb_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
26386,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2001/slb_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
26387,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2001/slb_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
26388,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2001/slb_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
26389,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2002/slb_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
26390,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2002/slb_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
26391,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2002/slb_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
26392,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2002/slb_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
26393,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2002/slb_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
26394,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2002/slb_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
26395,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2002/slb_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
26396,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2002/slb_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
26397,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2003/slb_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
26398,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2003/slb_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
26399,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2003/slb_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
26400,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2003/slb_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
26401,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2003/slb_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
26402,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2003/slb_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
26403,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2003/slb_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
26404,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2003/slb_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
26405,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2004/slb_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
26406,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2004/slb_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
26407,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2004/slb_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
26408,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2004/slb_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
26409,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2004/slb_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
26410,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2004/slb_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
26411,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2004/slb_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
26412,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2004/slb_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
26413,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2005/slb_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
26414,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2005/slb_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
26415,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2005/slb_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
26416,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2005/slb_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
26417,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2005/slb_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
26418,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2005/slb_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
26419,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2005/slb_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
26420,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2005/slb_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
26421,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2006/slb_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
26422,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2006/slb_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
26423,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2006/slb_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
26424,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2006/slb_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
26425,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2006/slb_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
26426,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2006/slb_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
26427,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2006/slb_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
26428,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2006/slb_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
26429,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2007/slb_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
26430,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2007/slb_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
26431,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2007/slb_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
26432,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2007/slb_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
26433,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2007/slb_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
26434,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2007/slb_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
26435,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2007/slb_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
26436,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2007/slb_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
26437,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2008/slb_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
26438,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2008/slb_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
26439,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2008/slb_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
26440,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2008/slb_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
26441,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2008/slb_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
26442,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2008/slb_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
26443,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2008/slb_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
26444,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2008/slb_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
26445,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2009/slb_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
26446,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2009/slb_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
26447,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2009/slb_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
26448,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2009/slb_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
26449,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2009/slb_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
26450,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2009/slb_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
26451,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2009/slb_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
26452,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2009/slb_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
26453,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2010/slb_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
26454,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2010/slb_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
26455,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2010/slb_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
26456,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2010/slb_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
26457,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2010/slb_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
26458,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2010/slb_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
26459,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2010/slb_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
26460,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2010/slb_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
26461,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2011/slb_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
26462,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2011/slb_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
26463,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2011/slb_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
26464,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2011/slb_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
26465,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2011/slb_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
26466,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2011/slb_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
26467,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2011/slb_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
26468,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2011/slb_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
26469,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2012/slb_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
26470,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2012/slb_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
26471,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2012/slb_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
26472,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2012/slb_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
26473,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2012/slb_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
26474,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2012/slb_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
26475,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2012/slb_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
26476,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2012/slb_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
26477,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2013/slb_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
26478,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2013/slb_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
26479,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2013/slb_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
26480,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2013/slb_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
26481,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2013/slb_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
26482,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2013/slb_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
26483,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2013/slb_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
26484,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2013/slb_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
26485,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2014/slb_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
26486,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2014/slb_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
26487,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2014/slb_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
26488,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2014/slb_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
26489,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2014/slb_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
26490,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2014/slb_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
26491,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2014/slb_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
26492,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2014/slb_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
26493,90,"SLB","Solomon Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2015/slb_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
26494,90,"SLB","Solomon Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2015/slb_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
26495,90,"SLB","Solomon Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2015/slb_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
26496,90,"SLB","Solomon Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2015/slb_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
26497,90,"SLB","Solomon Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2015/slb_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
26498,90,"SLB","Solomon Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2015/slb_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
26499,90,"SLB","Solomon Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2015/slb_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
26500,90,"SLB","Solomon Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Annual/2015/slb_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
26501,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2000/vgb_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
26502,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2000/vgb_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
26503,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2000/vgb_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
26504,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2000/vgb_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
26505,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2000/vgb_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
26506,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2000/vgb_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
26507,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2000/vgb_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
26508,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2000/vgb_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
26509,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2001/vgb_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
26510,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2001/vgb_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
26511,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2001/vgb_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
26512,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2001/vgb_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
26513,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2001/vgb_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
26514,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2001/vgb_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
26515,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2001/vgb_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
26516,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2001/vgb_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
26517,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2002/vgb_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
26518,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2002/vgb_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
26519,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2002/vgb_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
26520,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2002/vgb_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
26521,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2002/vgb_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
26522,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2002/vgb_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
26523,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2002/vgb_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
26524,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2002/vgb_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
26525,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2003/vgb_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
26526,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2003/vgb_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
26527,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2003/vgb_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
26528,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2003/vgb_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
26529,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2003/vgb_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
26530,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2003/vgb_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
26531,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2003/vgb_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
26532,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2003/vgb_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
26533,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2004/vgb_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
26534,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2004/vgb_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
26535,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2004/vgb_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
26536,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2004/vgb_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
26537,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2004/vgb_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
26538,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2004/vgb_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
26539,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2004/vgb_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
26540,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2004/vgb_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
26541,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2005/vgb_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
26542,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2005/vgb_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
26543,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2005/vgb_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
26544,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2005/vgb_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
26545,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2005/vgb_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
26546,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2005/vgb_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
26547,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2005/vgb_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
26548,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2005/vgb_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
26549,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2006/vgb_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
26550,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2006/vgb_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
26551,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2006/vgb_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
26552,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2006/vgb_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
26553,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2006/vgb_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
26554,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2006/vgb_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
26555,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2006/vgb_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
26556,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2006/vgb_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
26557,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2007/vgb_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
26558,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2007/vgb_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
26559,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2007/vgb_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
26560,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2007/vgb_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
26561,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2007/vgb_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
26562,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2007/vgb_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
26563,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2007/vgb_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
26564,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2007/vgb_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
26565,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2008/vgb_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
26566,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2008/vgb_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
26567,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2008/vgb_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
26568,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2008/vgb_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
26569,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2008/vgb_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
26570,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2008/vgb_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
26571,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2008/vgb_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
26572,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2008/vgb_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
26573,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2009/vgb_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
26574,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2009/vgb_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
26575,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2009/vgb_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
26576,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2009/vgb_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
26577,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2009/vgb_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
26578,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2009/vgb_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
26579,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2009/vgb_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
26580,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2009/vgb_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
26581,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2010/vgb_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
26582,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2010/vgb_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
26583,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2010/vgb_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
26584,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2010/vgb_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
26585,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2010/vgb_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
26586,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2010/vgb_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
26587,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2010/vgb_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
26588,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2010/vgb_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
26589,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2011/vgb_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
26590,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2011/vgb_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
26591,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2011/vgb_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
26592,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2011/vgb_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
26593,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2011/vgb_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
26594,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2011/vgb_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
26595,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2011/vgb_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
26596,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2011/vgb_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
26597,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2012/vgb_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
26598,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2012/vgb_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
26599,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2012/vgb_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
26600,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2012/vgb_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
26601,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2012/vgb_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
26602,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2012/vgb_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
26603,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2012/vgb_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
26604,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2012/vgb_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
26605,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2013/vgb_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
26606,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2013/vgb_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
26607,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2013/vgb_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
26608,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2013/vgb_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
26609,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2013/vgb_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
26610,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2013/vgb_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
26611,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2013/vgb_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
26612,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2013/vgb_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
26613,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2014/vgb_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
26614,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2014/vgb_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
26615,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2014/vgb_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
26616,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2014/vgb_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
26617,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2014/vgb_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
26618,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2014/vgb_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
26619,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2014/vgb_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
26620,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2014/vgb_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
26621,92,"VGB","British Virgin Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2015/vgb_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
26622,92,"VGB","British Virgin Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2015/vgb_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
26623,92,"VGB","British Virgin Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2015/vgb_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
26624,92,"VGB","British Virgin Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2015/vgb_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
26625,92,"VGB","British Virgin Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2015/vgb_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
26626,92,"VGB","British Virgin Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2015/vgb_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
26627,92,"VGB","British Virgin Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2015/vgb_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
26628,92,"VGB","British Virgin Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Annual/2015/vgb_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
26629,96,"BRN","Brunei","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2000/brn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
26630,96,"BRN","Brunei","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2000/brn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
26631,96,"BRN","Brunei","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2000/brn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
26632,96,"BRN","Brunei","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2000/brn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
26633,96,"BRN","Brunei","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2000/brn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
26634,96,"BRN","Brunei","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2000/brn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
26635,96,"BRN","Brunei","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2000/brn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
26636,96,"BRN","Brunei","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2000/brn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
26637,96,"BRN","Brunei","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2001/brn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
26638,96,"BRN","Brunei","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2001/brn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
26639,96,"BRN","Brunei","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2001/brn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
26640,96,"BRN","Brunei","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2001/brn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
26641,96,"BRN","Brunei","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2001/brn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
26642,96,"BRN","Brunei","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2001/brn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
26643,96,"BRN","Brunei","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2001/brn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
26644,96,"BRN","Brunei","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2001/brn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
26645,96,"BRN","Brunei","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2002/brn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
26646,96,"BRN","Brunei","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2002/brn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
26647,96,"BRN","Brunei","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2002/brn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
26648,96,"BRN","Brunei","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2002/brn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
26649,96,"BRN","Brunei","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2002/brn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
26650,96,"BRN","Brunei","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2002/brn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
26651,96,"BRN","Brunei","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2002/brn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
26652,96,"BRN","Brunei","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2002/brn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
26653,96,"BRN","Brunei","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2003/brn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
26654,96,"BRN","Brunei","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2003/brn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
26655,96,"BRN","Brunei","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2003/brn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
26656,96,"BRN","Brunei","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2003/brn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
26657,96,"BRN","Brunei","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2003/brn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
26658,96,"BRN","Brunei","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2003/brn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
26659,96,"BRN","Brunei","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2003/brn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
26660,96,"BRN","Brunei","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2003/brn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
26661,96,"BRN","Brunei","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2004/brn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
26662,96,"BRN","Brunei","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2004/brn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
26663,96,"BRN","Brunei","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2004/brn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
26664,96,"BRN","Brunei","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2004/brn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
26665,96,"BRN","Brunei","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2004/brn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
26666,96,"BRN","Brunei","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2004/brn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
26667,96,"BRN","Brunei","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2004/brn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
26668,96,"BRN","Brunei","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2004/brn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
26669,96,"BRN","Brunei","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2005/brn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
26670,96,"BRN","Brunei","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2005/brn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
26671,96,"BRN","Brunei","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2005/brn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
26672,96,"BRN","Brunei","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2005/brn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
26673,96,"BRN","Brunei","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2005/brn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
26674,96,"BRN","Brunei","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2005/brn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
26675,96,"BRN","Brunei","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2005/brn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
26676,96,"BRN","Brunei","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2005/brn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
26677,96,"BRN","Brunei","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2006/brn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
26678,96,"BRN","Brunei","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2006/brn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
26679,96,"BRN","Brunei","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2006/brn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
26680,96,"BRN","Brunei","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2006/brn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
26681,96,"BRN","Brunei","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2006/brn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
26682,96,"BRN","Brunei","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2006/brn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
26683,96,"BRN","Brunei","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2006/brn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
26684,96,"BRN","Brunei","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2006/brn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
26685,96,"BRN","Brunei","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2007/brn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
26686,96,"BRN","Brunei","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2007/brn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
26687,96,"BRN","Brunei","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2007/brn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
26688,96,"BRN","Brunei","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2007/brn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
26689,96,"BRN","Brunei","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2007/brn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
26690,96,"BRN","Brunei","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2007/brn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
26691,96,"BRN","Brunei","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2007/brn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
26692,96,"BRN","Brunei","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2007/brn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
26693,96,"BRN","Brunei","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2008/brn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
26694,96,"BRN","Brunei","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2008/brn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
26695,96,"BRN","Brunei","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2008/brn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
26696,96,"BRN","Brunei","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2008/brn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
26697,96,"BRN","Brunei","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2008/brn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
26698,96,"BRN","Brunei","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2008/brn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
26699,96,"BRN","Brunei","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2008/brn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
26700,96,"BRN","Brunei","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2008/brn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
26701,96,"BRN","Brunei","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2009/brn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
26702,96,"BRN","Brunei","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2009/brn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
26703,96,"BRN","Brunei","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2009/brn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
26704,96,"BRN","Brunei","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2009/brn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
26705,96,"BRN","Brunei","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2009/brn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
26706,96,"BRN","Brunei","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2009/brn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
26707,96,"BRN","Brunei","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2009/brn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
26708,96,"BRN","Brunei","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2009/brn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
26709,96,"BRN","Brunei","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2010/brn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
26710,96,"BRN","Brunei","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2010/brn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
26711,96,"BRN","Brunei","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2010/brn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
26712,96,"BRN","Brunei","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2010/brn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
26713,96,"BRN","Brunei","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2010/brn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
26714,96,"BRN","Brunei","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2010/brn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
26715,96,"BRN","Brunei","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2010/brn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
26716,96,"BRN","Brunei","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2010/brn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
26717,96,"BRN","Brunei","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2011/brn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
26718,96,"BRN","Brunei","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2011/brn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
26719,96,"BRN","Brunei","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2011/brn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
26720,96,"BRN","Brunei","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2011/brn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
26721,96,"BRN","Brunei","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2011/brn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
26722,96,"BRN","Brunei","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2011/brn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
26723,96,"BRN","Brunei","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2011/brn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
26724,96,"BRN","Brunei","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2011/brn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
26725,96,"BRN","Brunei","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2012/brn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
26726,96,"BRN","Brunei","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2012/brn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
26727,96,"BRN","Brunei","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2012/brn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
26728,96,"BRN","Brunei","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2012/brn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
26729,96,"BRN","Brunei","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2012/brn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
26730,96,"BRN","Brunei","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2012/brn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
26731,96,"BRN","Brunei","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2012/brn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
26732,96,"BRN","Brunei","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2012/brn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
26733,96,"BRN","Brunei","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2013/brn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
26734,96,"BRN","Brunei","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2013/brn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
26735,96,"BRN","Brunei","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2013/brn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
26736,96,"BRN","Brunei","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2013/brn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
26737,96,"BRN","Brunei","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2013/brn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
26738,96,"BRN","Brunei","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2013/brn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
26739,96,"BRN","Brunei","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2013/brn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
26740,96,"BRN","Brunei","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2013/brn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
26741,96,"BRN","Brunei","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2014/brn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
26742,96,"BRN","Brunei","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2014/brn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
26743,96,"BRN","Brunei","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2014/brn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
26744,96,"BRN","Brunei","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2014/brn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
26745,96,"BRN","Brunei","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2014/brn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
26746,96,"BRN","Brunei","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2014/brn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
26747,96,"BRN","Brunei","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2014/brn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
26748,96,"BRN","Brunei","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2014/brn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
26749,96,"BRN","Brunei","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2015/brn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
26750,96,"BRN","Brunei","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2015/brn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
26751,96,"BRN","Brunei","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2015/brn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
26752,96,"BRN","Brunei","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2015/brn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
26753,96,"BRN","Brunei","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2015/brn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
26754,96,"BRN","Brunei","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2015/brn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
26755,96,"BRN","Brunei","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2015/brn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
26756,96,"BRN","Brunei","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Annual/2015/brn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
26757,100,"BGR","Bulgaria","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2000/bgr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
26758,100,"BGR","Bulgaria","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2000/bgr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
26759,100,"BGR","Bulgaria","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2000/bgr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
26760,100,"BGR","Bulgaria","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2000/bgr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
26761,100,"BGR","Bulgaria","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2000/bgr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
26762,100,"BGR","Bulgaria","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2000/bgr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
26763,100,"BGR","Bulgaria","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2000/bgr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
26764,100,"BGR","Bulgaria","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2000/bgr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
26765,100,"BGR","Bulgaria","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2001/bgr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
26766,100,"BGR","Bulgaria","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2001/bgr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
26767,100,"BGR","Bulgaria","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2001/bgr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
26768,100,"BGR","Bulgaria","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2001/bgr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
26769,100,"BGR","Bulgaria","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2001/bgr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
26770,100,"BGR","Bulgaria","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2001/bgr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
26771,100,"BGR","Bulgaria","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2001/bgr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
26772,100,"BGR","Bulgaria","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2001/bgr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
26773,100,"BGR","Bulgaria","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2002/bgr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
26774,100,"BGR","Bulgaria","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2002/bgr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
26775,100,"BGR","Bulgaria","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2002/bgr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
26776,100,"BGR","Bulgaria","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2002/bgr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
26777,100,"BGR","Bulgaria","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2002/bgr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
26778,100,"BGR","Bulgaria","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2002/bgr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
26779,100,"BGR","Bulgaria","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2002/bgr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
26780,100,"BGR","Bulgaria","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2002/bgr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
26781,100,"BGR","Bulgaria","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2003/bgr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
26782,100,"BGR","Bulgaria","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2003/bgr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
26783,100,"BGR","Bulgaria","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2003/bgr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
26784,100,"BGR","Bulgaria","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2003/bgr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
26785,100,"BGR","Bulgaria","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2003/bgr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
26786,100,"BGR","Bulgaria","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2003/bgr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
26787,100,"BGR","Bulgaria","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2003/bgr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
26788,100,"BGR","Bulgaria","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2003/bgr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
26789,100,"BGR","Bulgaria","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2004/bgr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
26790,100,"BGR","Bulgaria","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2004/bgr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
26791,100,"BGR","Bulgaria","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2004/bgr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
26792,100,"BGR","Bulgaria","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2004/bgr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
26793,100,"BGR","Bulgaria","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2004/bgr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
26794,100,"BGR","Bulgaria","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2004/bgr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
26795,100,"BGR","Bulgaria","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2004/bgr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
26796,100,"BGR","Bulgaria","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2004/bgr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
26797,100,"BGR","Bulgaria","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2005/bgr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
26798,100,"BGR","Bulgaria","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2005/bgr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
26799,100,"BGR","Bulgaria","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2005/bgr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
26800,100,"BGR","Bulgaria","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2005/bgr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
26801,100,"BGR","Bulgaria","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2005/bgr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
26802,100,"BGR","Bulgaria","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2005/bgr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
26803,100,"BGR","Bulgaria","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2005/bgr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
26804,100,"BGR","Bulgaria","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2005/bgr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
26805,100,"BGR","Bulgaria","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2006/bgr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
26806,100,"BGR","Bulgaria","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2006/bgr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
26807,100,"BGR","Bulgaria","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2006/bgr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
26808,100,"BGR","Bulgaria","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2006/bgr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
26809,100,"BGR","Bulgaria","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2006/bgr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
26810,100,"BGR","Bulgaria","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2006/bgr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
26811,100,"BGR","Bulgaria","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2006/bgr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
26812,100,"BGR","Bulgaria","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2006/bgr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
26813,100,"BGR","Bulgaria","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2007/bgr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
26814,100,"BGR","Bulgaria","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2007/bgr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
26815,100,"BGR","Bulgaria","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2007/bgr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
26816,100,"BGR","Bulgaria","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2007/bgr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
26817,100,"BGR","Bulgaria","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2007/bgr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
26818,100,"BGR","Bulgaria","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2007/bgr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
26819,100,"BGR","Bulgaria","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2007/bgr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
26820,100,"BGR","Bulgaria","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2007/bgr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
26821,100,"BGR","Bulgaria","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2008/bgr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
26822,100,"BGR","Bulgaria","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2008/bgr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
26823,100,"BGR","Bulgaria","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2008/bgr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
26824,100,"BGR","Bulgaria","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2008/bgr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
26825,100,"BGR","Bulgaria","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2008/bgr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
26826,100,"BGR","Bulgaria","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2008/bgr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
26827,100,"BGR","Bulgaria","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2008/bgr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
26828,100,"BGR","Bulgaria","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2008/bgr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
26829,100,"BGR","Bulgaria","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2009/bgr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
26830,100,"BGR","Bulgaria","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2009/bgr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
26831,100,"BGR","Bulgaria","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2009/bgr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
26832,100,"BGR","Bulgaria","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2009/bgr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
26833,100,"BGR","Bulgaria","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2009/bgr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
26834,100,"BGR","Bulgaria","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2009/bgr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
26835,100,"BGR","Bulgaria","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2009/bgr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
26836,100,"BGR","Bulgaria","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2009/bgr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
26837,100,"BGR","Bulgaria","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2010/bgr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
26838,100,"BGR","Bulgaria","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2010/bgr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
26839,100,"BGR","Bulgaria","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2010/bgr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
26840,100,"BGR","Bulgaria","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2010/bgr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
26841,100,"BGR","Bulgaria","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2010/bgr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
26842,100,"BGR","Bulgaria","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2010/bgr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
26843,100,"BGR","Bulgaria","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2010/bgr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
26844,100,"BGR","Bulgaria","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2010/bgr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
26845,100,"BGR","Bulgaria","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2011/bgr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
26846,100,"BGR","Bulgaria","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2011/bgr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
26847,100,"BGR","Bulgaria","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2011/bgr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
26848,100,"BGR","Bulgaria","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2011/bgr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
26849,100,"BGR","Bulgaria","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2011/bgr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
26850,100,"BGR","Bulgaria","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2011/bgr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
26851,100,"BGR","Bulgaria","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2011/bgr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
26852,100,"BGR","Bulgaria","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2011/bgr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
26853,100,"BGR","Bulgaria","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2012/bgr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
26854,100,"BGR","Bulgaria","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2012/bgr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
26855,100,"BGR","Bulgaria","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2012/bgr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
26856,100,"BGR","Bulgaria","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2012/bgr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
26857,100,"BGR","Bulgaria","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2012/bgr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
26858,100,"BGR","Bulgaria","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2012/bgr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
26859,100,"BGR","Bulgaria","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2012/bgr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
26860,100,"BGR","Bulgaria","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2012/bgr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
26861,100,"BGR","Bulgaria","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2013/bgr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
26862,100,"BGR","Bulgaria","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2013/bgr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
26863,100,"BGR","Bulgaria","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2013/bgr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
26864,100,"BGR","Bulgaria","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2013/bgr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
26865,100,"BGR","Bulgaria","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2013/bgr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
26866,100,"BGR","Bulgaria","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2013/bgr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
26867,100,"BGR","Bulgaria","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2013/bgr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
26868,100,"BGR","Bulgaria","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2013/bgr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
26869,100,"BGR","Bulgaria","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2014/bgr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
26870,100,"BGR","Bulgaria","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2014/bgr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
26871,100,"BGR","Bulgaria","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2014/bgr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
26872,100,"BGR","Bulgaria","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2014/bgr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
26873,100,"BGR","Bulgaria","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2014/bgr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
26874,100,"BGR","Bulgaria","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2014/bgr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
26875,100,"BGR","Bulgaria","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2014/bgr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
26876,100,"BGR","Bulgaria","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2014/bgr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
26877,100,"BGR","Bulgaria","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2015/bgr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
26878,100,"BGR","Bulgaria","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2015/bgr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
26879,100,"BGR","Bulgaria","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2015/bgr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
26880,100,"BGR","Bulgaria","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2015/bgr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
26881,100,"BGR","Bulgaria","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2015/bgr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
26882,100,"BGR","Bulgaria","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2015/bgr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
26883,100,"BGR","Bulgaria","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2015/bgr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
26884,100,"BGR","Bulgaria","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Annual/2015/bgr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
26885,104,"MMR","Myanmar","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2000/mmr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
26886,104,"MMR","Myanmar","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2000/mmr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
26887,104,"MMR","Myanmar","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2000/mmr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
26888,104,"MMR","Myanmar","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2000/mmr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
26889,104,"MMR","Myanmar","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2000/mmr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
26890,104,"MMR","Myanmar","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2000/mmr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
26891,104,"MMR","Myanmar","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2000/mmr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
26892,104,"MMR","Myanmar","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2000/mmr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
26893,104,"MMR","Myanmar","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2001/mmr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
26894,104,"MMR","Myanmar","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2001/mmr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
26895,104,"MMR","Myanmar","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2001/mmr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
26896,104,"MMR","Myanmar","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2001/mmr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
26897,104,"MMR","Myanmar","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2001/mmr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
26898,104,"MMR","Myanmar","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2001/mmr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
26899,104,"MMR","Myanmar","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2001/mmr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
26900,104,"MMR","Myanmar","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2001/mmr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
26901,104,"MMR","Myanmar","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2002/mmr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
26902,104,"MMR","Myanmar","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2002/mmr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
26903,104,"MMR","Myanmar","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2002/mmr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
26904,104,"MMR","Myanmar","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2002/mmr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
26905,104,"MMR","Myanmar","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2002/mmr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
26906,104,"MMR","Myanmar","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2002/mmr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
26907,104,"MMR","Myanmar","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2002/mmr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
26908,104,"MMR","Myanmar","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2002/mmr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
26909,104,"MMR","Myanmar","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2003/mmr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
26910,104,"MMR","Myanmar","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2003/mmr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
26911,104,"MMR","Myanmar","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2003/mmr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
26912,104,"MMR","Myanmar","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2003/mmr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
26913,104,"MMR","Myanmar","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2003/mmr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
26914,104,"MMR","Myanmar","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2003/mmr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
26915,104,"MMR","Myanmar","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2003/mmr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
26916,104,"MMR","Myanmar","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2003/mmr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
26917,104,"MMR","Myanmar","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2004/mmr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
26918,104,"MMR","Myanmar","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2004/mmr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
26919,104,"MMR","Myanmar","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2004/mmr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
26920,104,"MMR","Myanmar","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2004/mmr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
26921,104,"MMR","Myanmar","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2004/mmr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
26922,104,"MMR","Myanmar","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2004/mmr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
26923,104,"MMR","Myanmar","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2004/mmr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
26924,104,"MMR","Myanmar","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2004/mmr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
26925,104,"MMR","Myanmar","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2005/mmr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
26926,104,"MMR","Myanmar","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2005/mmr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
26927,104,"MMR","Myanmar","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2005/mmr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
26928,104,"MMR","Myanmar","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2005/mmr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
26929,104,"MMR","Myanmar","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2005/mmr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
26930,104,"MMR","Myanmar","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2005/mmr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
26931,104,"MMR","Myanmar","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2005/mmr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
26932,104,"MMR","Myanmar","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2005/mmr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
26933,104,"MMR","Myanmar","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2006/mmr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
26934,104,"MMR","Myanmar","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2006/mmr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
26935,104,"MMR","Myanmar","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2006/mmr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
26936,104,"MMR","Myanmar","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2006/mmr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
26937,104,"MMR","Myanmar","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2006/mmr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
26938,104,"MMR","Myanmar","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2006/mmr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
26939,104,"MMR","Myanmar","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2006/mmr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
26940,104,"MMR","Myanmar","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2006/mmr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
26941,104,"MMR","Myanmar","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2007/mmr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
26942,104,"MMR","Myanmar","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2007/mmr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
26943,104,"MMR","Myanmar","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2007/mmr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
26944,104,"MMR","Myanmar","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2007/mmr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
26945,104,"MMR","Myanmar","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2007/mmr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
26946,104,"MMR","Myanmar","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2007/mmr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
26947,104,"MMR","Myanmar","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2007/mmr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
26948,104,"MMR","Myanmar","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2007/mmr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
26949,104,"MMR","Myanmar","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2008/mmr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
26950,104,"MMR","Myanmar","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2008/mmr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
26951,104,"MMR","Myanmar","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2008/mmr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
26952,104,"MMR","Myanmar","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2008/mmr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
26953,104,"MMR","Myanmar","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2008/mmr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
26954,104,"MMR","Myanmar","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2008/mmr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
26955,104,"MMR","Myanmar","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2008/mmr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
26956,104,"MMR","Myanmar","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2008/mmr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
26957,104,"MMR","Myanmar","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2009/mmr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
26958,104,"MMR","Myanmar","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2009/mmr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
26959,104,"MMR","Myanmar","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2009/mmr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
26960,104,"MMR","Myanmar","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2009/mmr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
26961,104,"MMR","Myanmar","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2009/mmr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
26962,104,"MMR","Myanmar","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2009/mmr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
26963,104,"MMR","Myanmar","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2009/mmr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
26964,104,"MMR","Myanmar","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2009/mmr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
26965,104,"MMR","Myanmar","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2010/mmr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
26966,104,"MMR","Myanmar","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2010/mmr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
26967,104,"MMR","Myanmar","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2010/mmr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
26968,104,"MMR","Myanmar","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2010/mmr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
26969,104,"MMR","Myanmar","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2010/mmr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
26970,104,"MMR","Myanmar","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2010/mmr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
26971,104,"MMR","Myanmar","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2010/mmr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
26972,104,"MMR","Myanmar","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2010/mmr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
26973,104,"MMR","Myanmar","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2011/mmr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
26974,104,"MMR","Myanmar","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2011/mmr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
26975,104,"MMR","Myanmar","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2011/mmr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
26976,104,"MMR","Myanmar","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2011/mmr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
26977,104,"MMR","Myanmar","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2011/mmr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
26978,104,"MMR","Myanmar","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2011/mmr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
26979,104,"MMR","Myanmar","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2011/mmr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
26980,104,"MMR","Myanmar","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2011/mmr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
26981,104,"MMR","Myanmar","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2012/mmr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
26982,104,"MMR","Myanmar","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2012/mmr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
26983,104,"MMR","Myanmar","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2012/mmr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
26984,104,"MMR","Myanmar","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2012/mmr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
26985,104,"MMR","Myanmar","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2012/mmr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
26986,104,"MMR","Myanmar","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2012/mmr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
26987,104,"MMR","Myanmar","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2012/mmr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
26988,104,"MMR","Myanmar","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2012/mmr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
26989,104,"MMR","Myanmar","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2013/mmr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
26990,104,"MMR","Myanmar","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2013/mmr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
26991,104,"MMR","Myanmar","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2013/mmr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
26992,104,"MMR","Myanmar","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2013/mmr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
26993,104,"MMR","Myanmar","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2013/mmr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
26994,104,"MMR","Myanmar","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2013/mmr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
26995,104,"MMR","Myanmar","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2013/mmr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
26996,104,"MMR","Myanmar","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2013/mmr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
26997,104,"MMR","Myanmar","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2014/mmr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
26998,104,"MMR","Myanmar","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2014/mmr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
26999,104,"MMR","Myanmar","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2014/mmr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
27000,104,"MMR","Myanmar","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2014/mmr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
27001,104,"MMR","Myanmar","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2014/mmr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
27002,104,"MMR","Myanmar","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2014/mmr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
27003,104,"MMR","Myanmar","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2014/mmr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
27004,104,"MMR","Myanmar","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2014/mmr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
27005,104,"MMR","Myanmar","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2015/mmr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
27006,104,"MMR","Myanmar","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2015/mmr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
27007,104,"MMR","Myanmar","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2015/mmr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
27008,104,"MMR","Myanmar","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2015/mmr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
27009,104,"MMR","Myanmar","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2015/mmr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
27010,104,"MMR","Myanmar","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2015/mmr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
27011,104,"MMR","Myanmar","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2015/mmr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
27012,104,"MMR","Myanmar","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Annual/2015/mmr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
27013,108,"BDI","Burundi","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2000/bdi_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
27014,108,"BDI","Burundi","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2000/bdi_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
27015,108,"BDI","Burundi","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2000/bdi_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
27016,108,"BDI","Burundi","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2000/bdi_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
27017,108,"BDI","Burundi","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2000/bdi_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
27018,108,"BDI","Burundi","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2000/bdi_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
27019,108,"BDI","Burundi","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2000/bdi_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
27020,108,"BDI","Burundi","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2000/bdi_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
27021,108,"BDI","Burundi","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2001/bdi_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
27022,108,"BDI","Burundi","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2001/bdi_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
27023,108,"BDI","Burundi","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2001/bdi_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
27024,108,"BDI","Burundi","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2001/bdi_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
27025,108,"BDI","Burundi","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2001/bdi_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
27026,108,"BDI","Burundi","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2001/bdi_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
27027,108,"BDI","Burundi","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2001/bdi_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
27028,108,"BDI","Burundi","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2001/bdi_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
27029,108,"BDI","Burundi","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2002/bdi_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
27030,108,"BDI","Burundi","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2002/bdi_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
27031,108,"BDI","Burundi","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2002/bdi_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
27032,108,"BDI","Burundi","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2002/bdi_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
27033,108,"BDI","Burundi","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2002/bdi_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
27034,108,"BDI","Burundi","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2002/bdi_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
27035,108,"BDI","Burundi","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2002/bdi_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
27036,108,"BDI","Burundi","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2002/bdi_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
27037,108,"BDI","Burundi","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2003/bdi_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
27038,108,"BDI","Burundi","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2003/bdi_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
27039,108,"BDI","Burundi","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2003/bdi_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
27040,108,"BDI","Burundi","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2003/bdi_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
27041,108,"BDI","Burundi","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2003/bdi_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
27042,108,"BDI","Burundi","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2003/bdi_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
27043,108,"BDI","Burundi","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2003/bdi_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
27044,108,"BDI","Burundi","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2003/bdi_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
27045,108,"BDI","Burundi","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2004/bdi_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
27046,108,"BDI","Burundi","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2004/bdi_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
27047,108,"BDI","Burundi","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2004/bdi_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
27048,108,"BDI","Burundi","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2004/bdi_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
27049,108,"BDI","Burundi","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2004/bdi_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
27050,108,"BDI","Burundi","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2004/bdi_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
27051,108,"BDI","Burundi","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2004/bdi_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
27052,108,"BDI","Burundi","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2004/bdi_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
27053,108,"BDI","Burundi","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2005/bdi_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
27054,108,"BDI","Burundi","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2005/bdi_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
27055,108,"BDI","Burundi","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2005/bdi_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
27056,108,"BDI","Burundi","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2005/bdi_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
27057,108,"BDI","Burundi","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2005/bdi_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
27058,108,"BDI","Burundi","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2005/bdi_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
27059,108,"BDI","Burundi","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2005/bdi_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
27060,108,"BDI","Burundi","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2005/bdi_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
27061,108,"BDI","Burundi","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2006/bdi_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
27062,108,"BDI","Burundi","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2006/bdi_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
27063,108,"BDI","Burundi","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2006/bdi_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
27064,108,"BDI","Burundi","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2006/bdi_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
27065,108,"BDI","Burundi","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2006/bdi_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
27066,108,"BDI","Burundi","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2006/bdi_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
27067,108,"BDI","Burundi","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2006/bdi_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
27068,108,"BDI","Burundi","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2006/bdi_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
27069,108,"BDI","Burundi","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2007/bdi_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
27070,108,"BDI","Burundi","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2007/bdi_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
27071,108,"BDI","Burundi","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2007/bdi_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
27072,108,"BDI","Burundi","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2007/bdi_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
27073,108,"BDI","Burundi","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2007/bdi_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
27074,108,"BDI","Burundi","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2007/bdi_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
27075,108,"BDI","Burundi","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2007/bdi_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
27076,108,"BDI","Burundi","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2007/bdi_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
27077,108,"BDI","Burundi","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2008/bdi_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
27078,108,"BDI","Burundi","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2008/bdi_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
27079,108,"BDI","Burundi","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2008/bdi_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
27080,108,"BDI","Burundi","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2008/bdi_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
27081,108,"BDI","Burundi","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2008/bdi_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
27082,108,"BDI","Burundi","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2008/bdi_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
27083,108,"BDI","Burundi","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2008/bdi_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
27084,108,"BDI","Burundi","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2008/bdi_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
27085,108,"BDI","Burundi","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2009/bdi_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
27086,108,"BDI","Burundi","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2009/bdi_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
27087,108,"BDI","Burundi","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2009/bdi_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
27088,108,"BDI","Burundi","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2009/bdi_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
27089,108,"BDI","Burundi","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2009/bdi_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
27090,108,"BDI","Burundi","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2009/bdi_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
27091,108,"BDI","Burundi","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2009/bdi_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
27092,108,"BDI","Burundi","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2009/bdi_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
27093,108,"BDI","Burundi","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2010/bdi_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
27094,108,"BDI","Burundi","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2010/bdi_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
27095,108,"BDI","Burundi","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2010/bdi_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
27096,108,"BDI","Burundi","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2010/bdi_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
27097,108,"BDI","Burundi","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2010/bdi_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
27098,108,"BDI","Burundi","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2010/bdi_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
27099,108,"BDI","Burundi","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2010/bdi_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
27100,108,"BDI","Burundi","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2010/bdi_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
27101,108,"BDI","Burundi","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2011/bdi_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
27102,108,"BDI","Burundi","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2011/bdi_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
27103,108,"BDI","Burundi","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2011/bdi_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
27104,108,"BDI","Burundi","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2011/bdi_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
27105,108,"BDI","Burundi","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2011/bdi_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
27106,108,"BDI","Burundi","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2011/bdi_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
27107,108,"BDI","Burundi","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2011/bdi_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
27108,108,"BDI","Burundi","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2011/bdi_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
27109,108,"BDI","Burundi","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2012/bdi_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
27110,108,"BDI","Burundi","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2012/bdi_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
27111,108,"BDI","Burundi","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2012/bdi_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
27112,108,"BDI","Burundi","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2012/bdi_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
27113,108,"BDI","Burundi","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2012/bdi_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
27114,108,"BDI","Burundi","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2012/bdi_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
27115,108,"BDI","Burundi","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2012/bdi_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
27116,108,"BDI","Burundi","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2012/bdi_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
27117,108,"BDI","Burundi","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2013/bdi_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
27118,108,"BDI","Burundi","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2013/bdi_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
27119,108,"BDI","Burundi","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2013/bdi_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
27120,108,"BDI","Burundi","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2013/bdi_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
27121,108,"BDI","Burundi","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2013/bdi_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
27122,108,"BDI","Burundi","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2013/bdi_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
27123,108,"BDI","Burundi","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2013/bdi_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
27124,108,"BDI","Burundi","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2013/bdi_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
27125,108,"BDI","Burundi","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2014/bdi_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
27126,108,"BDI","Burundi","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2014/bdi_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
27127,108,"BDI","Burundi","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2014/bdi_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
27128,108,"BDI","Burundi","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2014/bdi_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
27129,108,"BDI","Burundi","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2014/bdi_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
27130,108,"BDI","Burundi","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2014/bdi_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
27131,108,"BDI","Burundi","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2014/bdi_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
27132,108,"BDI","Burundi","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2014/bdi_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
27133,108,"BDI","Burundi","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2015/bdi_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
27134,108,"BDI","Burundi","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2015/bdi_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
27135,108,"BDI","Burundi","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2015/bdi_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
27136,108,"BDI","Burundi","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2015/bdi_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
27137,108,"BDI","Burundi","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2015/bdi_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
27138,108,"BDI","Burundi","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2015/bdi_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
27139,108,"BDI","Burundi","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2015/bdi_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
27140,108,"BDI","Burundi","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Annual/2015/bdi_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
27141,112,"BLR","Belarus","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2000/blr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
27142,112,"BLR","Belarus","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2000/blr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
27143,112,"BLR","Belarus","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2000/blr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
27144,112,"BLR","Belarus","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2000/blr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
27145,112,"BLR","Belarus","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2000/blr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
27146,112,"BLR","Belarus","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2000/blr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
27147,112,"BLR","Belarus","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2000/blr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
27148,112,"BLR","Belarus","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2000/blr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
27149,112,"BLR","Belarus","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2001/blr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
27150,112,"BLR","Belarus","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2001/blr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
27151,112,"BLR","Belarus","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2001/blr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
27152,112,"BLR","Belarus","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2001/blr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
27153,112,"BLR","Belarus","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2001/blr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
27154,112,"BLR","Belarus","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2001/blr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
27155,112,"BLR","Belarus","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2001/blr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
27156,112,"BLR","Belarus","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2001/blr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
27157,112,"BLR","Belarus","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2002/blr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
27158,112,"BLR","Belarus","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2002/blr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
27159,112,"BLR","Belarus","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2002/blr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
27160,112,"BLR","Belarus","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2002/blr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
27161,112,"BLR","Belarus","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2002/blr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
27162,112,"BLR","Belarus","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2002/blr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
27163,112,"BLR","Belarus","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2002/blr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
27164,112,"BLR","Belarus","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2002/blr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
27165,112,"BLR","Belarus","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2003/blr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
27166,112,"BLR","Belarus","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2003/blr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
27167,112,"BLR","Belarus","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2003/blr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
27168,112,"BLR","Belarus","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2003/blr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
27169,112,"BLR","Belarus","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2003/blr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
27170,112,"BLR","Belarus","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2003/blr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
27171,112,"BLR","Belarus","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2003/blr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
27172,112,"BLR","Belarus","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2003/blr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
27173,112,"BLR","Belarus","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2004/blr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
27174,112,"BLR","Belarus","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2004/blr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
27175,112,"BLR","Belarus","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2004/blr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
27176,112,"BLR","Belarus","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2004/blr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
27177,112,"BLR","Belarus","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2004/blr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
27178,112,"BLR","Belarus","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2004/blr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
27179,112,"BLR","Belarus","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2004/blr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
27180,112,"BLR","Belarus","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2004/blr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
27181,112,"BLR","Belarus","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2005/blr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
27182,112,"BLR","Belarus","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2005/blr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
27183,112,"BLR","Belarus","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2005/blr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
27184,112,"BLR","Belarus","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2005/blr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
27185,112,"BLR","Belarus","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2005/blr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
27186,112,"BLR","Belarus","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2005/blr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
27187,112,"BLR","Belarus","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2005/blr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
27188,112,"BLR","Belarus","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2005/blr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
27189,112,"BLR","Belarus","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2006/blr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
27190,112,"BLR","Belarus","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2006/blr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
27191,112,"BLR","Belarus","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2006/blr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
27192,112,"BLR","Belarus","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2006/blr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
27193,112,"BLR","Belarus","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2006/blr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
27194,112,"BLR","Belarus","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2006/blr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
27195,112,"BLR","Belarus","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2006/blr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
27196,112,"BLR","Belarus","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2006/blr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
27197,112,"BLR","Belarus","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2007/blr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
27198,112,"BLR","Belarus","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2007/blr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
27199,112,"BLR","Belarus","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2007/blr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
27200,112,"BLR","Belarus","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2007/blr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
27201,112,"BLR","Belarus","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2007/blr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
27202,112,"BLR","Belarus","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2007/blr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
27203,112,"BLR","Belarus","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2007/blr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
27204,112,"BLR","Belarus","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2007/blr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
27205,112,"BLR","Belarus","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2008/blr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
27206,112,"BLR","Belarus","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2008/blr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
27207,112,"BLR","Belarus","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2008/blr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
27208,112,"BLR","Belarus","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2008/blr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
27209,112,"BLR","Belarus","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2008/blr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
27210,112,"BLR","Belarus","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2008/blr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
27211,112,"BLR","Belarus","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2008/blr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
27212,112,"BLR","Belarus","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2008/blr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
27213,112,"BLR","Belarus","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2009/blr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
27214,112,"BLR","Belarus","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2009/blr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
27215,112,"BLR","Belarus","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2009/blr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
27216,112,"BLR","Belarus","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2009/blr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
27217,112,"BLR","Belarus","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2009/blr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
27218,112,"BLR","Belarus","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2009/blr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
27219,112,"BLR","Belarus","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2009/blr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
27220,112,"BLR","Belarus","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2009/blr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
27221,112,"BLR","Belarus","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2010/blr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
27222,112,"BLR","Belarus","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2010/blr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
27223,112,"BLR","Belarus","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2010/blr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
27224,112,"BLR","Belarus","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2010/blr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
27225,112,"BLR","Belarus","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2010/blr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
27226,112,"BLR","Belarus","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2010/blr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
27227,112,"BLR","Belarus","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2010/blr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
27228,112,"BLR","Belarus","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2010/blr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
27229,112,"BLR","Belarus","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2011/blr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
27230,112,"BLR","Belarus","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2011/blr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
27231,112,"BLR","Belarus","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2011/blr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
27232,112,"BLR","Belarus","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2011/blr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
27233,112,"BLR","Belarus","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2011/blr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
27234,112,"BLR","Belarus","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2011/blr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
27235,112,"BLR","Belarus","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2011/blr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
27236,112,"BLR","Belarus","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2011/blr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
27237,112,"BLR","Belarus","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2012/blr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
27238,112,"BLR","Belarus","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2012/blr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
27239,112,"BLR","Belarus","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2012/blr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
27240,112,"BLR","Belarus","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2012/blr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
27241,112,"BLR","Belarus","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2012/blr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
27242,112,"BLR","Belarus","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2012/blr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
27243,112,"BLR","Belarus","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2012/blr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
27244,112,"BLR","Belarus","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2012/blr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
27245,112,"BLR","Belarus","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2013/blr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
27246,112,"BLR","Belarus","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2013/blr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
27247,112,"BLR","Belarus","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2013/blr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
27248,112,"BLR","Belarus","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2013/blr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
27249,112,"BLR","Belarus","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2013/blr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
27250,112,"BLR","Belarus","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2013/blr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
27251,112,"BLR","Belarus","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2013/blr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
27252,112,"BLR","Belarus","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2013/blr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
27253,112,"BLR","Belarus","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2014/blr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
27254,112,"BLR","Belarus","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2014/blr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
27255,112,"BLR","Belarus","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2014/blr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
27256,112,"BLR","Belarus","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2014/blr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
27257,112,"BLR","Belarus","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2014/blr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
27258,112,"BLR","Belarus","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2014/blr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
27259,112,"BLR","Belarus","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2014/blr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
27260,112,"BLR","Belarus","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2014/blr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
27261,112,"BLR","Belarus","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2015/blr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
27262,112,"BLR","Belarus","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2015/blr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
27263,112,"BLR","Belarus","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2015/blr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
27264,112,"BLR","Belarus","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2015/blr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
27265,112,"BLR","Belarus","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2015/blr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
27266,112,"BLR","Belarus","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2015/blr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
27267,112,"BLR","Belarus","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2015/blr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
27268,112,"BLR","Belarus","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Annual/2015/blr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
27269,116,"KHM","Cambodia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2000/khm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
27270,116,"KHM","Cambodia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2000/khm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
27271,116,"KHM","Cambodia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2000/khm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
27272,116,"KHM","Cambodia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2000/khm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
27273,116,"KHM","Cambodia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2000/khm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
27274,116,"KHM","Cambodia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2000/khm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
27275,116,"KHM","Cambodia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2000/khm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
27276,116,"KHM","Cambodia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2000/khm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
27277,116,"KHM","Cambodia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2001/khm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
27278,116,"KHM","Cambodia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2001/khm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
27279,116,"KHM","Cambodia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2001/khm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
27280,116,"KHM","Cambodia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2001/khm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
27281,116,"KHM","Cambodia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2001/khm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
27282,116,"KHM","Cambodia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2001/khm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
27283,116,"KHM","Cambodia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2001/khm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
27284,116,"KHM","Cambodia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2001/khm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
27285,116,"KHM","Cambodia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2002/khm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
27286,116,"KHM","Cambodia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2002/khm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
27287,116,"KHM","Cambodia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2002/khm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
27288,116,"KHM","Cambodia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2002/khm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
27289,116,"KHM","Cambodia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2002/khm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
27290,116,"KHM","Cambodia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2002/khm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
27291,116,"KHM","Cambodia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2002/khm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
27292,116,"KHM","Cambodia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2002/khm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
27293,116,"KHM","Cambodia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2003/khm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
27294,116,"KHM","Cambodia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2003/khm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
27295,116,"KHM","Cambodia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2003/khm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
27296,116,"KHM","Cambodia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2003/khm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
27297,116,"KHM","Cambodia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2003/khm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
27298,116,"KHM","Cambodia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2003/khm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
27299,116,"KHM","Cambodia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2003/khm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
27300,116,"KHM","Cambodia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2003/khm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
27301,116,"KHM","Cambodia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2004/khm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
27302,116,"KHM","Cambodia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2004/khm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
27303,116,"KHM","Cambodia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2004/khm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
27304,116,"KHM","Cambodia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2004/khm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
27305,116,"KHM","Cambodia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2004/khm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
27306,116,"KHM","Cambodia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2004/khm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
27307,116,"KHM","Cambodia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2004/khm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
27308,116,"KHM","Cambodia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2004/khm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
27309,116,"KHM","Cambodia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2005/khm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
27310,116,"KHM","Cambodia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2005/khm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
27311,116,"KHM","Cambodia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2005/khm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
27312,116,"KHM","Cambodia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2005/khm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
27313,116,"KHM","Cambodia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2005/khm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
27314,116,"KHM","Cambodia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2005/khm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
27315,116,"KHM","Cambodia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2005/khm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
27316,116,"KHM","Cambodia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2005/khm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
27317,116,"KHM","Cambodia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2006/khm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
27318,116,"KHM","Cambodia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2006/khm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
27319,116,"KHM","Cambodia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2006/khm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
27320,116,"KHM","Cambodia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2006/khm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
27321,116,"KHM","Cambodia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2006/khm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
27322,116,"KHM","Cambodia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2006/khm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
27323,116,"KHM","Cambodia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2006/khm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
27324,116,"KHM","Cambodia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2006/khm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
27325,116,"KHM","Cambodia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2007/khm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
27326,116,"KHM","Cambodia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2007/khm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
27327,116,"KHM","Cambodia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2007/khm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
27328,116,"KHM","Cambodia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2007/khm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
27329,116,"KHM","Cambodia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2007/khm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
27330,116,"KHM","Cambodia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2007/khm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
27331,116,"KHM","Cambodia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2007/khm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
27332,116,"KHM","Cambodia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2007/khm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
27333,116,"KHM","Cambodia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2008/khm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
27334,116,"KHM","Cambodia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2008/khm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
27335,116,"KHM","Cambodia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2008/khm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
27336,116,"KHM","Cambodia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2008/khm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
27337,116,"KHM","Cambodia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2008/khm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
27338,116,"KHM","Cambodia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2008/khm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
27339,116,"KHM","Cambodia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2008/khm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
27340,116,"KHM","Cambodia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2008/khm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
27341,116,"KHM","Cambodia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2009/khm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
27342,116,"KHM","Cambodia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2009/khm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
27343,116,"KHM","Cambodia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2009/khm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
27344,116,"KHM","Cambodia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2009/khm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
27345,116,"KHM","Cambodia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2009/khm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
27346,116,"KHM","Cambodia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2009/khm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
27347,116,"KHM","Cambodia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2009/khm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
27348,116,"KHM","Cambodia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2009/khm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
27349,116,"KHM","Cambodia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2010/khm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
27350,116,"KHM","Cambodia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2010/khm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
27351,116,"KHM","Cambodia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2010/khm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
27352,116,"KHM","Cambodia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2010/khm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
27353,116,"KHM","Cambodia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2010/khm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
27354,116,"KHM","Cambodia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2010/khm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
27355,116,"KHM","Cambodia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2010/khm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
27356,116,"KHM","Cambodia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2010/khm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
27357,116,"KHM","Cambodia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2011/khm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
27358,116,"KHM","Cambodia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2011/khm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
27359,116,"KHM","Cambodia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2011/khm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
27360,116,"KHM","Cambodia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2011/khm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
27361,116,"KHM","Cambodia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2011/khm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
27362,116,"KHM","Cambodia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2011/khm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
27363,116,"KHM","Cambodia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2011/khm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
27364,116,"KHM","Cambodia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2011/khm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
27365,116,"KHM","Cambodia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2012/khm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
27366,116,"KHM","Cambodia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2012/khm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
27367,116,"KHM","Cambodia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2012/khm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
27368,116,"KHM","Cambodia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2012/khm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
27369,116,"KHM","Cambodia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2012/khm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
27370,116,"KHM","Cambodia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2012/khm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
27371,116,"KHM","Cambodia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2012/khm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
27372,116,"KHM","Cambodia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2012/khm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
27373,116,"KHM","Cambodia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2013/khm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
27374,116,"KHM","Cambodia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2013/khm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
27375,116,"KHM","Cambodia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2013/khm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
27376,116,"KHM","Cambodia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2013/khm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
27377,116,"KHM","Cambodia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2013/khm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
27378,116,"KHM","Cambodia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2013/khm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
27379,116,"KHM","Cambodia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2013/khm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
27380,116,"KHM","Cambodia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2013/khm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
27381,116,"KHM","Cambodia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2014/khm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
27382,116,"KHM","Cambodia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2014/khm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
27383,116,"KHM","Cambodia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2014/khm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
27384,116,"KHM","Cambodia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2014/khm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
27385,116,"KHM","Cambodia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2014/khm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
27386,116,"KHM","Cambodia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2014/khm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
27387,116,"KHM","Cambodia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2014/khm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
27388,116,"KHM","Cambodia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2014/khm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
27389,116,"KHM","Cambodia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2015/khm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
27390,116,"KHM","Cambodia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2015/khm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
27391,116,"KHM","Cambodia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2015/khm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
27392,116,"KHM","Cambodia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2015/khm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
27393,116,"KHM","Cambodia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2015/khm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
27394,116,"KHM","Cambodia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2015/khm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
27395,116,"KHM","Cambodia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2015/khm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
27396,116,"KHM","Cambodia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Annual/2015/khm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
27397,120,"CMR","Cameroon","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2000/cmr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
27398,120,"CMR","Cameroon","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2000/cmr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
27399,120,"CMR","Cameroon","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2000/cmr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
27400,120,"CMR","Cameroon","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2000/cmr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
27401,120,"CMR","Cameroon","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2000/cmr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
27402,120,"CMR","Cameroon","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2000/cmr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
27403,120,"CMR","Cameroon","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2000/cmr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
27404,120,"CMR","Cameroon","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2000/cmr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
27405,120,"CMR","Cameroon","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2001/cmr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
27406,120,"CMR","Cameroon","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2001/cmr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
27407,120,"CMR","Cameroon","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2001/cmr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
27408,120,"CMR","Cameroon","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2001/cmr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
27409,120,"CMR","Cameroon","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2001/cmr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
27410,120,"CMR","Cameroon","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2001/cmr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
27411,120,"CMR","Cameroon","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2001/cmr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
27412,120,"CMR","Cameroon","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2001/cmr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
27413,120,"CMR","Cameroon","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2002/cmr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
27414,120,"CMR","Cameroon","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2002/cmr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
27415,120,"CMR","Cameroon","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2002/cmr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
27416,120,"CMR","Cameroon","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2002/cmr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
27417,120,"CMR","Cameroon","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2002/cmr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
27418,120,"CMR","Cameroon","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2002/cmr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
27419,120,"CMR","Cameroon","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2002/cmr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
27420,120,"CMR","Cameroon","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2002/cmr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
27421,120,"CMR","Cameroon","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2003/cmr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
27422,120,"CMR","Cameroon","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2003/cmr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
27423,120,"CMR","Cameroon","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2003/cmr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
27424,120,"CMR","Cameroon","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2003/cmr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
27425,120,"CMR","Cameroon","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2003/cmr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
27426,120,"CMR","Cameroon","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2003/cmr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
27427,120,"CMR","Cameroon","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2003/cmr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
27428,120,"CMR","Cameroon","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2003/cmr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
27429,120,"CMR","Cameroon","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2004/cmr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
27430,120,"CMR","Cameroon","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2004/cmr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
27431,120,"CMR","Cameroon","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2004/cmr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
27432,120,"CMR","Cameroon","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2004/cmr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
27433,120,"CMR","Cameroon","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2004/cmr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
27434,120,"CMR","Cameroon","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2004/cmr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
27435,120,"CMR","Cameroon","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2004/cmr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
27436,120,"CMR","Cameroon","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2004/cmr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
27437,120,"CMR","Cameroon","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2005/cmr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
27438,120,"CMR","Cameroon","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2005/cmr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
27439,120,"CMR","Cameroon","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2005/cmr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
27440,120,"CMR","Cameroon","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2005/cmr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
27441,120,"CMR","Cameroon","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2005/cmr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
27442,120,"CMR","Cameroon","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2005/cmr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
27443,120,"CMR","Cameroon","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2005/cmr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
27444,120,"CMR","Cameroon","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2005/cmr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
27445,120,"CMR","Cameroon","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2006/cmr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
27446,120,"CMR","Cameroon","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2006/cmr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
27447,120,"CMR","Cameroon","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2006/cmr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
27448,120,"CMR","Cameroon","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2006/cmr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
27449,120,"CMR","Cameroon","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2006/cmr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
27450,120,"CMR","Cameroon","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2006/cmr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
27451,120,"CMR","Cameroon","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2006/cmr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
27452,120,"CMR","Cameroon","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2006/cmr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
27453,120,"CMR","Cameroon","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2007/cmr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
27454,120,"CMR","Cameroon","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2007/cmr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
27455,120,"CMR","Cameroon","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2007/cmr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
27456,120,"CMR","Cameroon","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2007/cmr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
27457,120,"CMR","Cameroon","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2007/cmr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
27458,120,"CMR","Cameroon","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2007/cmr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
27459,120,"CMR","Cameroon","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2007/cmr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
27460,120,"CMR","Cameroon","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2007/cmr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
27461,120,"CMR","Cameroon","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2008/cmr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
27462,120,"CMR","Cameroon","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2008/cmr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
27463,120,"CMR","Cameroon","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2008/cmr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
27464,120,"CMR","Cameroon","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2008/cmr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
27465,120,"CMR","Cameroon","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2008/cmr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
27466,120,"CMR","Cameroon","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2008/cmr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
27467,120,"CMR","Cameroon","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2008/cmr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
27468,120,"CMR","Cameroon","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2008/cmr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
27469,120,"CMR","Cameroon","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2009/cmr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
27470,120,"CMR","Cameroon","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2009/cmr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
27471,120,"CMR","Cameroon","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2009/cmr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
27472,120,"CMR","Cameroon","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2009/cmr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
27473,120,"CMR","Cameroon","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2009/cmr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
27474,120,"CMR","Cameroon","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2009/cmr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
27475,120,"CMR","Cameroon","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2009/cmr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
27476,120,"CMR","Cameroon","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2009/cmr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
27477,120,"CMR","Cameroon","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2010/cmr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
27478,120,"CMR","Cameroon","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2010/cmr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
27479,120,"CMR","Cameroon","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2010/cmr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
27480,120,"CMR","Cameroon","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2010/cmr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
27481,120,"CMR","Cameroon","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2010/cmr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
27482,120,"CMR","Cameroon","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2010/cmr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
27483,120,"CMR","Cameroon","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2010/cmr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
27484,120,"CMR","Cameroon","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2010/cmr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
27485,120,"CMR","Cameroon","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2011/cmr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
27486,120,"CMR","Cameroon","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2011/cmr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
27487,120,"CMR","Cameroon","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2011/cmr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
27488,120,"CMR","Cameroon","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2011/cmr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
27489,120,"CMR","Cameroon","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2011/cmr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
27490,120,"CMR","Cameroon","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2011/cmr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
27491,120,"CMR","Cameroon","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2011/cmr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
27492,120,"CMR","Cameroon","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2011/cmr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
27493,120,"CMR","Cameroon","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2012/cmr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
27494,120,"CMR","Cameroon","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2012/cmr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
27495,120,"CMR","Cameroon","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2012/cmr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
27496,120,"CMR","Cameroon","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2012/cmr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
27497,120,"CMR","Cameroon","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2012/cmr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
27498,120,"CMR","Cameroon","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2012/cmr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
27499,120,"CMR","Cameroon","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2012/cmr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
27500,120,"CMR","Cameroon","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2012/cmr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
27501,120,"CMR","Cameroon","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2013/cmr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
27502,120,"CMR","Cameroon","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2013/cmr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
27503,120,"CMR","Cameroon","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2013/cmr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
27504,120,"CMR","Cameroon","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2013/cmr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
27505,120,"CMR","Cameroon","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2013/cmr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
27506,120,"CMR","Cameroon","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2013/cmr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
27507,120,"CMR","Cameroon","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2013/cmr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
27508,120,"CMR","Cameroon","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2013/cmr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
27509,120,"CMR","Cameroon","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2014/cmr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
27510,120,"CMR","Cameroon","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2014/cmr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
27511,120,"CMR","Cameroon","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2014/cmr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
27512,120,"CMR","Cameroon","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2014/cmr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
27513,120,"CMR","Cameroon","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2014/cmr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
27514,120,"CMR","Cameroon","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2014/cmr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
27515,120,"CMR","Cameroon","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2014/cmr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
27516,120,"CMR","Cameroon","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2014/cmr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
27517,120,"CMR","Cameroon","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2015/cmr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
27518,120,"CMR","Cameroon","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2015/cmr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
27519,120,"CMR","Cameroon","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2015/cmr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
27520,120,"CMR","Cameroon","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2015/cmr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
27521,120,"CMR","Cameroon","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2015/cmr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
27522,120,"CMR","Cameroon","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2015/cmr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
27523,120,"CMR","Cameroon","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2015/cmr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
27524,120,"CMR","Cameroon","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Annual/2015/cmr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
27525,132,"CPV","Cape Verde","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2000/cpv_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
27526,132,"CPV","Cape Verde","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2000/cpv_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
27527,132,"CPV","Cape Verde","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2000/cpv_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
27528,132,"CPV","Cape Verde","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2000/cpv_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
27529,132,"CPV","Cape Verde","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2000/cpv_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
27530,132,"CPV","Cape Verde","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2000/cpv_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
27531,132,"CPV","Cape Verde","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2000/cpv_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
27532,132,"CPV","Cape Verde","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2000/cpv_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
27533,132,"CPV","Cape Verde","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2001/cpv_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
27534,132,"CPV","Cape Verde","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2001/cpv_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
27535,132,"CPV","Cape Verde","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2001/cpv_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
27536,132,"CPV","Cape Verde","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2001/cpv_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
27537,132,"CPV","Cape Verde","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2001/cpv_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
27538,132,"CPV","Cape Verde","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2001/cpv_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
27539,132,"CPV","Cape Verde","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2001/cpv_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
27540,132,"CPV","Cape Verde","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2001/cpv_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
27541,132,"CPV","Cape Verde","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2002/cpv_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
27542,132,"CPV","Cape Verde","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2002/cpv_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
27543,132,"CPV","Cape Verde","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2002/cpv_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
27544,132,"CPV","Cape Verde","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2002/cpv_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
27545,132,"CPV","Cape Verde","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2002/cpv_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
27546,132,"CPV","Cape Verde","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2002/cpv_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
27547,132,"CPV","Cape Verde","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2002/cpv_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
27548,132,"CPV","Cape Verde","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2002/cpv_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
27549,132,"CPV","Cape Verde","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2003/cpv_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
27550,132,"CPV","Cape Verde","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2003/cpv_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
27551,132,"CPV","Cape Verde","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2003/cpv_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
27552,132,"CPV","Cape Verde","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2003/cpv_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
27553,132,"CPV","Cape Verde","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2003/cpv_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
27554,132,"CPV","Cape Verde","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2003/cpv_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
27555,132,"CPV","Cape Verde","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2003/cpv_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
27556,132,"CPV","Cape Verde","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2003/cpv_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
27557,132,"CPV","Cape Verde","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2004/cpv_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
27558,132,"CPV","Cape Verde","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2004/cpv_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
27559,132,"CPV","Cape Verde","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2004/cpv_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
27560,132,"CPV","Cape Verde","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2004/cpv_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
27561,132,"CPV","Cape Verde","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2004/cpv_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
27562,132,"CPV","Cape Verde","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2004/cpv_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
27563,132,"CPV","Cape Verde","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2004/cpv_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
27564,132,"CPV","Cape Verde","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2004/cpv_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
27565,132,"CPV","Cape Verde","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2005/cpv_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
27566,132,"CPV","Cape Verde","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2005/cpv_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
27567,132,"CPV","Cape Verde","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2005/cpv_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
27568,132,"CPV","Cape Verde","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2005/cpv_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
27569,132,"CPV","Cape Verde","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2005/cpv_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
27570,132,"CPV","Cape Verde","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2005/cpv_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
27571,132,"CPV","Cape Verde","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2005/cpv_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
27572,132,"CPV","Cape Verde","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2005/cpv_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
27573,132,"CPV","Cape Verde","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2006/cpv_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
27574,132,"CPV","Cape Verde","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2006/cpv_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
27575,132,"CPV","Cape Verde","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2006/cpv_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
27576,132,"CPV","Cape Verde","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2006/cpv_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
27577,132,"CPV","Cape Verde","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2006/cpv_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
27578,132,"CPV","Cape Verde","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2006/cpv_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
27579,132,"CPV","Cape Verde","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2006/cpv_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
27580,132,"CPV","Cape Verde","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2006/cpv_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
27581,132,"CPV","Cape Verde","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2007/cpv_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
27582,132,"CPV","Cape Verde","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2007/cpv_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
27583,132,"CPV","Cape Verde","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2007/cpv_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
27584,132,"CPV","Cape Verde","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2007/cpv_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
27585,132,"CPV","Cape Verde","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2007/cpv_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
27586,132,"CPV","Cape Verde","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2007/cpv_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
27587,132,"CPV","Cape Verde","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2007/cpv_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
27588,132,"CPV","Cape Verde","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2007/cpv_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
27589,132,"CPV","Cape Verde","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2008/cpv_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
27590,132,"CPV","Cape Verde","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2008/cpv_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
27591,132,"CPV","Cape Verde","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2008/cpv_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
27592,132,"CPV","Cape Verde","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2008/cpv_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
27593,132,"CPV","Cape Verde","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2008/cpv_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
27594,132,"CPV","Cape Verde","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2008/cpv_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
27595,132,"CPV","Cape Verde","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2008/cpv_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
27596,132,"CPV","Cape Verde","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2008/cpv_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
27597,132,"CPV","Cape Verde","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2009/cpv_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
27598,132,"CPV","Cape Verde","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2009/cpv_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
27599,132,"CPV","Cape Verde","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2009/cpv_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
27600,132,"CPV","Cape Verde","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2009/cpv_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
27601,132,"CPV","Cape Verde","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2009/cpv_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
27602,132,"CPV","Cape Verde","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2009/cpv_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
27603,132,"CPV","Cape Verde","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2009/cpv_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
27604,132,"CPV","Cape Verde","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2009/cpv_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
27605,132,"CPV","Cape Verde","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2010/cpv_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
27606,132,"CPV","Cape Verde","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2010/cpv_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
27607,132,"CPV","Cape Verde","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2010/cpv_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
27608,132,"CPV","Cape Verde","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2010/cpv_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
27609,132,"CPV","Cape Verde","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2010/cpv_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
27610,132,"CPV","Cape Verde","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2010/cpv_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
27611,132,"CPV","Cape Verde","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2010/cpv_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
27612,132,"CPV","Cape Verde","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2010/cpv_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
27613,132,"CPV","Cape Verde","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2011/cpv_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
27614,132,"CPV","Cape Verde","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2011/cpv_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
27615,132,"CPV","Cape Verde","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2011/cpv_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
27616,132,"CPV","Cape Verde","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2011/cpv_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
27617,132,"CPV","Cape Verde","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2011/cpv_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
27618,132,"CPV","Cape Verde","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2011/cpv_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
27619,132,"CPV","Cape Verde","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2011/cpv_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
27620,132,"CPV","Cape Verde","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2011/cpv_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
27621,132,"CPV","Cape Verde","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2012/cpv_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
27622,132,"CPV","Cape Verde","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2012/cpv_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
27623,132,"CPV","Cape Verde","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2012/cpv_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
27624,132,"CPV","Cape Verde","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2012/cpv_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
27625,132,"CPV","Cape Verde","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2012/cpv_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
27626,132,"CPV","Cape Verde","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2012/cpv_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
27627,132,"CPV","Cape Verde","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2012/cpv_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
27628,132,"CPV","Cape Verde","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2012/cpv_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
27629,132,"CPV","Cape Verde","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2013/cpv_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
27630,132,"CPV","Cape Verde","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2013/cpv_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
27631,132,"CPV","Cape Verde","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2013/cpv_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
27632,132,"CPV","Cape Verde","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2013/cpv_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
27633,132,"CPV","Cape Verde","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2013/cpv_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
27634,132,"CPV","Cape Verde","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2013/cpv_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
27635,132,"CPV","Cape Verde","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2013/cpv_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
27636,132,"CPV","Cape Verde","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2013/cpv_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
27637,132,"CPV","Cape Verde","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2014/cpv_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
27638,132,"CPV","Cape Verde","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2014/cpv_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
27639,132,"CPV","Cape Verde","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2014/cpv_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
27640,132,"CPV","Cape Verde","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2014/cpv_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
27641,132,"CPV","Cape Verde","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2014/cpv_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
27642,132,"CPV","Cape Verde","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2014/cpv_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
27643,132,"CPV","Cape Verde","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2014/cpv_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
27644,132,"CPV","Cape Verde","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2014/cpv_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
27645,132,"CPV","Cape Verde","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2015/cpv_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
27646,132,"CPV","Cape Verde","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2015/cpv_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
27647,132,"CPV","Cape Verde","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2015/cpv_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
27648,132,"CPV","Cape Verde","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2015/cpv_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
27649,132,"CPV","Cape Verde","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2015/cpv_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
27650,132,"CPV","Cape Verde","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2015/cpv_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
27651,132,"CPV","Cape Verde","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2015/cpv_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
27652,132,"CPV","Cape Verde","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Annual/2015/cpv_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
27653,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2000/cym_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
27654,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2000/cym_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
27655,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2000/cym_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
27656,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2000/cym_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
27657,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2000/cym_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
27658,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2000/cym_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
27659,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2000/cym_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
27660,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2000/cym_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
27661,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2001/cym_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
27662,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2001/cym_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
27663,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2001/cym_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
27664,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2001/cym_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
27665,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2001/cym_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
27666,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2001/cym_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
27667,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2001/cym_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
27668,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2001/cym_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
27669,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2002/cym_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
27670,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2002/cym_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
27671,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2002/cym_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
27672,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2002/cym_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
27673,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2002/cym_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
27674,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2002/cym_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
27675,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2002/cym_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
27676,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2002/cym_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
27677,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2003/cym_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
27678,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2003/cym_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
27679,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2003/cym_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
27680,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2003/cym_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
27681,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2003/cym_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
27682,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2003/cym_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
27683,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2003/cym_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
27684,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2003/cym_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
27685,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2004/cym_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
27686,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2004/cym_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
27687,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2004/cym_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
27688,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2004/cym_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
27689,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2004/cym_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
27690,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2004/cym_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
27691,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2004/cym_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
27692,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2004/cym_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
27693,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2005/cym_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
27694,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2005/cym_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
27695,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2005/cym_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
27696,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2005/cym_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
27697,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2005/cym_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
27698,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2005/cym_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
27699,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2005/cym_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
27700,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2005/cym_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
27701,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2006/cym_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
27702,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2006/cym_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
27703,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2006/cym_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
27704,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2006/cym_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
27705,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2006/cym_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
27706,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2006/cym_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
27707,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2006/cym_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
27708,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2006/cym_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
27709,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2007/cym_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
27710,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2007/cym_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
27711,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2007/cym_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
27712,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2007/cym_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
27713,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2007/cym_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
27714,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2007/cym_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
27715,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2007/cym_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
27716,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2007/cym_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
27717,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2008/cym_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
27718,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2008/cym_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
27719,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2008/cym_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
27720,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2008/cym_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
27721,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2008/cym_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
27722,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2008/cym_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
27723,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2008/cym_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
27724,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2008/cym_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
27725,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2009/cym_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
27726,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2009/cym_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
27727,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2009/cym_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
27728,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2009/cym_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
27729,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2009/cym_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
27730,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2009/cym_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
27731,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2009/cym_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
27732,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2009/cym_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
27733,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2010/cym_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
27734,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2010/cym_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
27735,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2010/cym_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
27736,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2010/cym_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
27737,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2010/cym_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
27738,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2010/cym_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
27739,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2010/cym_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
27740,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2010/cym_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
27741,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2011/cym_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
27742,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2011/cym_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
27743,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2011/cym_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
27744,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2011/cym_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
27745,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2011/cym_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
27746,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2011/cym_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
27747,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2011/cym_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
27748,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2011/cym_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
27749,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2012/cym_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
27750,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2012/cym_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
27751,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2012/cym_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
27752,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2012/cym_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
27753,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2012/cym_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
27754,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2012/cym_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
27755,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2012/cym_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
27756,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2012/cym_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
27757,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2013/cym_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
27758,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2013/cym_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
27759,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2013/cym_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
27760,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2013/cym_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
27761,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2013/cym_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
27762,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2013/cym_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
27763,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2013/cym_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
27764,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2013/cym_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
27765,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2014/cym_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
27766,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2014/cym_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
27767,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2014/cym_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
27768,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2014/cym_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
27769,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2014/cym_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
27770,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2014/cym_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
27771,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2014/cym_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
27772,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2014/cym_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
27773,136,"CYM","Cayman Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2015/cym_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
27774,136,"CYM","Cayman Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2015/cym_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
27775,136,"CYM","Cayman Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2015/cym_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
27776,136,"CYM","Cayman Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2015/cym_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
27777,136,"CYM","Cayman Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2015/cym_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
27778,136,"CYM","Cayman Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2015/cym_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
27779,136,"CYM","Cayman Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2015/cym_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
27780,136,"CYM","Cayman Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Annual/2015/cym_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
27781,140,"CAF","Central African Republic","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2000/caf_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
27782,140,"CAF","Central African Republic","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2000/caf_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
27783,140,"CAF","Central African Republic","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2000/caf_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
27784,140,"CAF","Central African Republic","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2000/caf_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
27785,140,"CAF","Central African Republic","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2000/caf_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
27786,140,"CAF","Central African Republic","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2000/caf_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
27787,140,"CAF","Central African Republic","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2000/caf_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
27788,140,"CAF","Central African Republic","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2000/caf_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
27789,140,"CAF","Central African Republic","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2001/caf_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
27790,140,"CAF","Central African Republic","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2001/caf_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
27791,140,"CAF","Central African Republic","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2001/caf_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
27792,140,"CAF","Central African Republic","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2001/caf_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
27793,140,"CAF","Central African Republic","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2001/caf_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
27794,140,"CAF","Central African Republic","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2001/caf_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
27795,140,"CAF","Central African Republic","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2001/caf_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
27796,140,"CAF","Central African Republic","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2001/caf_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
27797,140,"CAF","Central African Republic","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2002/caf_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
27798,140,"CAF","Central African Republic","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2002/caf_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
27799,140,"CAF","Central African Republic","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2002/caf_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
27800,140,"CAF","Central African Republic","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2002/caf_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
27801,140,"CAF","Central African Republic","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2002/caf_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
27802,140,"CAF","Central African Republic","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2002/caf_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
27803,140,"CAF","Central African Republic","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2002/caf_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
27804,140,"CAF","Central African Republic","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2002/caf_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
27805,140,"CAF","Central African Republic","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2003/caf_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
27806,140,"CAF","Central African Republic","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2003/caf_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
27807,140,"CAF","Central African Republic","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2003/caf_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
27808,140,"CAF","Central African Republic","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2003/caf_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
27809,140,"CAF","Central African Republic","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2003/caf_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
27810,140,"CAF","Central African Republic","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2003/caf_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
27811,140,"CAF","Central African Republic","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2003/caf_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
27812,140,"CAF","Central African Republic","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2003/caf_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
27813,140,"CAF","Central African Republic","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2004/caf_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
27814,140,"CAF","Central African Republic","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2004/caf_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
27815,140,"CAF","Central African Republic","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2004/caf_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
27816,140,"CAF","Central African Republic","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2004/caf_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
27817,140,"CAF","Central African Republic","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2004/caf_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
27818,140,"CAF","Central African Republic","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2004/caf_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
27819,140,"CAF","Central African Republic","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2004/caf_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
27820,140,"CAF","Central African Republic","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2004/caf_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
27821,140,"CAF","Central African Republic","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2005/caf_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
27822,140,"CAF","Central African Republic","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2005/caf_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
27823,140,"CAF","Central African Republic","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2005/caf_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
27824,140,"CAF","Central African Republic","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2005/caf_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
27825,140,"CAF","Central African Republic","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2005/caf_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
27826,140,"CAF","Central African Republic","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2005/caf_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
27827,140,"CAF","Central African Republic","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2005/caf_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
27828,140,"CAF","Central African Republic","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2005/caf_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
27829,140,"CAF","Central African Republic","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2006/caf_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
27830,140,"CAF","Central African Republic","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2006/caf_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
27831,140,"CAF","Central African Republic","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2006/caf_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
27832,140,"CAF","Central African Republic","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2006/caf_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
27833,140,"CAF","Central African Republic","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2006/caf_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
27834,140,"CAF","Central African Republic","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2006/caf_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
27835,140,"CAF","Central African Republic","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2006/caf_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
27836,140,"CAF","Central African Republic","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2006/caf_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
27837,140,"CAF","Central African Republic","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2007/caf_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
27838,140,"CAF","Central African Republic","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2007/caf_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
27839,140,"CAF","Central African Republic","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2007/caf_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
27840,140,"CAF","Central African Republic","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2007/caf_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
27841,140,"CAF","Central African Republic","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2007/caf_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
27842,140,"CAF","Central African Republic","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2007/caf_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
27843,140,"CAF","Central African Republic","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2007/caf_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
27844,140,"CAF","Central African Republic","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2007/caf_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
27845,140,"CAF","Central African Republic","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2008/caf_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
27846,140,"CAF","Central African Republic","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2008/caf_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
27847,140,"CAF","Central African Republic","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2008/caf_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
27848,140,"CAF","Central African Republic","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2008/caf_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
27849,140,"CAF","Central African Republic","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2008/caf_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
27850,140,"CAF","Central African Republic","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2008/caf_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
27851,140,"CAF","Central African Republic","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2008/caf_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
27852,140,"CAF","Central African Republic","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2008/caf_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
27853,140,"CAF","Central African Republic","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2009/caf_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
27854,140,"CAF","Central African Republic","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2009/caf_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
27855,140,"CAF","Central African Republic","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2009/caf_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
27856,140,"CAF","Central African Republic","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2009/caf_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
27857,140,"CAF","Central African Republic","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2009/caf_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
27858,140,"CAF","Central African Republic","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2009/caf_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
27859,140,"CAF","Central African Republic","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2009/caf_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
27860,140,"CAF","Central African Republic","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2009/caf_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
27861,140,"CAF","Central African Republic","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2010/caf_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
27862,140,"CAF","Central African Republic","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2010/caf_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
27863,140,"CAF","Central African Republic","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2010/caf_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
27864,140,"CAF","Central African Republic","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2010/caf_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
27865,140,"CAF","Central African Republic","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2010/caf_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
27866,140,"CAF","Central African Republic","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2010/caf_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
27867,140,"CAF","Central African Republic","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2010/caf_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
27868,140,"CAF","Central African Republic","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2010/caf_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
27869,140,"CAF","Central African Republic","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2011/caf_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
27870,140,"CAF","Central African Republic","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2011/caf_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
27871,140,"CAF","Central African Republic","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2011/caf_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
27872,140,"CAF","Central African Republic","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2011/caf_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
27873,140,"CAF","Central African Republic","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2011/caf_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
27874,140,"CAF","Central African Republic","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2011/caf_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
27875,140,"CAF","Central African Republic","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2011/caf_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
27876,140,"CAF","Central African Republic","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2011/caf_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
27877,140,"CAF","Central African Republic","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2012/caf_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
27878,140,"CAF","Central African Republic","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2012/caf_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
27879,140,"CAF","Central African Republic","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2012/caf_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
27880,140,"CAF","Central African Republic","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2012/caf_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
27881,140,"CAF","Central African Republic","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2012/caf_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
27882,140,"CAF","Central African Republic","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2012/caf_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
27883,140,"CAF","Central African Republic","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2012/caf_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
27884,140,"CAF","Central African Republic","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2012/caf_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
27885,140,"CAF","Central African Republic","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2013/caf_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
27886,140,"CAF","Central African Republic","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2013/caf_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
27887,140,"CAF","Central African Republic","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2013/caf_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
27888,140,"CAF","Central African Republic","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2013/caf_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
27889,140,"CAF","Central African Republic","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2013/caf_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
27890,140,"CAF","Central African Republic","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2013/caf_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
27891,140,"CAF","Central African Republic","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2013/caf_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
27892,140,"CAF","Central African Republic","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2013/caf_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
27893,140,"CAF","Central African Republic","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2014/caf_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
27894,140,"CAF","Central African Republic","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2014/caf_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
27895,140,"CAF","Central African Republic","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2014/caf_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
27896,140,"CAF","Central African Republic","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2014/caf_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
27897,140,"CAF","Central African Republic","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2014/caf_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
27898,140,"CAF","Central African Republic","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2014/caf_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
27899,140,"CAF","Central African Republic","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2014/caf_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
27900,140,"CAF","Central African Republic","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2014/caf_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
27901,140,"CAF","Central African Republic","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2015/caf_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
27902,140,"CAF","Central African Republic","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2015/caf_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
27903,140,"CAF","Central African Republic","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2015/caf_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
27904,140,"CAF","Central African Republic","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2015/caf_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
27905,140,"CAF","Central African Republic","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2015/caf_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
27906,140,"CAF","Central African Republic","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2015/caf_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
27907,140,"CAF","Central African Republic","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2015/caf_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
27908,140,"CAF","Central African Republic","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Annual/2015/caf_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
27909,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2000/lka_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
27910,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2000/lka_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
27911,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2000/lka_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
27912,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2000/lka_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
27913,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2000/lka_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
27914,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2000/lka_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
27915,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2000/lka_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
27916,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2000/lka_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
27917,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2001/lka_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
27918,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2001/lka_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
27919,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2001/lka_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
27920,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2001/lka_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
27921,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2001/lka_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
27922,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2001/lka_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
27923,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2001/lka_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
27924,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2001/lka_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
27925,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2002/lka_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
27926,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2002/lka_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
27927,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2002/lka_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
27928,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2002/lka_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
27929,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2002/lka_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
27930,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2002/lka_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
27931,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2002/lka_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
27932,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2002/lka_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
27933,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2003/lka_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
27934,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2003/lka_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
27935,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2003/lka_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
27936,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2003/lka_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
27937,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2003/lka_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
27938,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2003/lka_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
27939,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2003/lka_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
27940,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2003/lka_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
27941,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2004/lka_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
27942,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2004/lka_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
27943,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2004/lka_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
27944,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2004/lka_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
27945,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2004/lka_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
27946,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2004/lka_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
27947,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2004/lka_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
27948,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2004/lka_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
27949,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2005/lka_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
27950,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2005/lka_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
27951,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2005/lka_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
27952,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2005/lka_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
27953,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2005/lka_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
27954,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2005/lka_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
27955,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2005/lka_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
27956,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2005/lka_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
27957,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2006/lka_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
27958,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2006/lka_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
27959,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2006/lka_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
27960,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2006/lka_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
27961,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2006/lka_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
27962,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2006/lka_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
27963,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2006/lka_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
27964,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2006/lka_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
27965,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2007/lka_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
27966,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2007/lka_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
27967,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2007/lka_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
27968,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2007/lka_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
27969,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2007/lka_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
27970,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2007/lka_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
27971,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2007/lka_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
27972,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2007/lka_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
27973,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2008/lka_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
27974,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2008/lka_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
27975,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2008/lka_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
27976,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2008/lka_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
27977,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2008/lka_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
27978,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2008/lka_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
27979,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2008/lka_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
27980,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2008/lka_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
27981,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2009/lka_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
27982,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2009/lka_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
27983,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2009/lka_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
27984,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2009/lka_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
27985,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2009/lka_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
27986,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2009/lka_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
27987,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2009/lka_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
27988,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2009/lka_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
27989,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2010/lka_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
27990,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2010/lka_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
27991,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2010/lka_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
27992,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2010/lka_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
27993,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2010/lka_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
27994,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2010/lka_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
27995,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2010/lka_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
27996,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2010/lka_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
27997,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2011/lka_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
27998,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2011/lka_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
27999,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2011/lka_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
28000,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2011/lka_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
28001,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2011/lka_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
28002,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2011/lka_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
28003,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2011/lka_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
28004,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2011/lka_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
28005,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2012/lka_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
28006,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2012/lka_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
28007,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2012/lka_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
28008,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2012/lka_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
28009,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2012/lka_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
28010,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2012/lka_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
28011,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2012/lka_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
28012,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2012/lka_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
28013,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2013/lka_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
28014,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2013/lka_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
28015,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2013/lka_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
28016,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2013/lka_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
28017,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2013/lka_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
28018,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2013/lka_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
28019,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2013/lka_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
28020,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2013/lka_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
28021,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2014/lka_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
28022,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2014/lka_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
28023,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2014/lka_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
28024,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2014/lka_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
28025,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2014/lka_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
28026,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2014/lka_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
28027,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2014/lka_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
28028,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2014/lka_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
28029,144,"LKA","Sri Lanka","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2015/lka_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
28030,144,"LKA","Sri Lanka","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2015/lka_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
28031,144,"LKA","Sri Lanka","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2015/lka_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
28032,144,"LKA","Sri Lanka","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2015/lka_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
28033,144,"LKA","Sri Lanka","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2015/lka_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
28034,144,"LKA","Sri Lanka","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2015/lka_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
28035,144,"LKA","Sri Lanka","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2015/lka_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
28036,144,"LKA","Sri Lanka","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Annual/2015/lka_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
28037,148,"TCD","Chad","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2000/tcd_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
28038,148,"TCD","Chad","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2000/tcd_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
28039,148,"TCD","Chad","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2000/tcd_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
28040,148,"TCD","Chad","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2000/tcd_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
28041,148,"TCD","Chad","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2000/tcd_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
28042,148,"TCD","Chad","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2000/tcd_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
28043,148,"TCD","Chad","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2000/tcd_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
28044,148,"TCD","Chad","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2000/tcd_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
28045,148,"TCD","Chad","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2001/tcd_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
28046,148,"TCD","Chad","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2001/tcd_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
28047,148,"TCD","Chad","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2001/tcd_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
28048,148,"TCD","Chad","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2001/tcd_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
28049,148,"TCD","Chad","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2001/tcd_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
28050,148,"TCD","Chad","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2001/tcd_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
28051,148,"TCD","Chad","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2001/tcd_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
28052,148,"TCD","Chad","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2001/tcd_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
28053,148,"TCD","Chad","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2002/tcd_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
28054,148,"TCD","Chad","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2002/tcd_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
28055,148,"TCD","Chad","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2002/tcd_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
28056,148,"TCD","Chad","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2002/tcd_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
28057,148,"TCD","Chad","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2002/tcd_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
28058,148,"TCD","Chad","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2002/tcd_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
28059,148,"TCD","Chad","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2002/tcd_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
28060,148,"TCD","Chad","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2002/tcd_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
28061,148,"TCD","Chad","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2003/tcd_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
28062,148,"TCD","Chad","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2003/tcd_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
28063,148,"TCD","Chad","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2003/tcd_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
28064,148,"TCD","Chad","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2003/tcd_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
28065,148,"TCD","Chad","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2003/tcd_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
28066,148,"TCD","Chad","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2003/tcd_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
28067,148,"TCD","Chad","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2003/tcd_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
28068,148,"TCD","Chad","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2003/tcd_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
28069,148,"TCD","Chad","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2004/tcd_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
28070,148,"TCD","Chad","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2004/tcd_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
28071,148,"TCD","Chad","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2004/tcd_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
28072,148,"TCD","Chad","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2004/tcd_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
28073,148,"TCD","Chad","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2004/tcd_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
28074,148,"TCD","Chad","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2004/tcd_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
28075,148,"TCD","Chad","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2004/tcd_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
28076,148,"TCD","Chad","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2004/tcd_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
28077,148,"TCD","Chad","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2005/tcd_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
28078,148,"TCD","Chad","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2005/tcd_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
28079,148,"TCD","Chad","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2005/tcd_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
28080,148,"TCD","Chad","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2005/tcd_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
28081,148,"TCD","Chad","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2005/tcd_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
28082,148,"TCD","Chad","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2005/tcd_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
28083,148,"TCD","Chad","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2005/tcd_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
28084,148,"TCD","Chad","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2005/tcd_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
28085,148,"TCD","Chad","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2006/tcd_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
28086,148,"TCD","Chad","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2006/tcd_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
28087,148,"TCD","Chad","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2006/tcd_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
28088,148,"TCD","Chad","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2006/tcd_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
28089,148,"TCD","Chad","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2006/tcd_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
28090,148,"TCD","Chad","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2006/tcd_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
28091,148,"TCD","Chad","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2006/tcd_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
28092,148,"TCD","Chad","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2006/tcd_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
28093,148,"TCD","Chad","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2007/tcd_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
28094,148,"TCD","Chad","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2007/tcd_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
28095,148,"TCD","Chad","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2007/tcd_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
28096,148,"TCD","Chad","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2007/tcd_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
28097,148,"TCD","Chad","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2007/tcd_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
28098,148,"TCD","Chad","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2007/tcd_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
28099,148,"TCD","Chad","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2007/tcd_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
28100,148,"TCD","Chad","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2007/tcd_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
28101,148,"TCD","Chad","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2008/tcd_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
28102,148,"TCD","Chad","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2008/tcd_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
28103,148,"TCD","Chad","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2008/tcd_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
28104,148,"TCD","Chad","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2008/tcd_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
28105,148,"TCD","Chad","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2008/tcd_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
28106,148,"TCD","Chad","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2008/tcd_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
28107,148,"TCD","Chad","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2008/tcd_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
28108,148,"TCD","Chad","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2008/tcd_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
28109,148,"TCD","Chad","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2009/tcd_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
28110,148,"TCD","Chad","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2009/tcd_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
28111,148,"TCD","Chad","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2009/tcd_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
28112,148,"TCD","Chad","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2009/tcd_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
28113,148,"TCD","Chad","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2009/tcd_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
28114,148,"TCD","Chad","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2009/tcd_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
28115,148,"TCD","Chad","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2009/tcd_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
28116,148,"TCD","Chad","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2009/tcd_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
28117,148,"TCD","Chad","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2010/tcd_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
28118,148,"TCD","Chad","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2010/tcd_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
28119,148,"TCD","Chad","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2010/tcd_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
28120,148,"TCD","Chad","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2010/tcd_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
28121,148,"TCD","Chad","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2010/tcd_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
28122,148,"TCD","Chad","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2010/tcd_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
28123,148,"TCD","Chad","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2010/tcd_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
28124,148,"TCD","Chad","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2010/tcd_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
28125,148,"TCD","Chad","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2011/tcd_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
28126,148,"TCD","Chad","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2011/tcd_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
28127,148,"TCD","Chad","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2011/tcd_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
28128,148,"TCD","Chad","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2011/tcd_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
28129,148,"TCD","Chad","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2011/tcd_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
28130,148,"TCD","Chad","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2011/tcd_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
28131,148,"TCD","Chad","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2011/tcd_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
28132,148,"TCD","Chad","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2011/tcd_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
28133,148,"TCD","Chad","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2012/tcd_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
28134,148,"TCD","Chad","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2012/tcd_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
28135,148,"TCD","Chad","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2012/tcd_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
28136,148,"TCD","Chad","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2012/tcd_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
28137,148,"TCD","Chad","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2012/tcd_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
28138,148,"TCD","Chad","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2012/tcd_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
28139,148,"TCD","Chad","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2012/tcd_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
28140,148,"TCD","Chad","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2012/tcd_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
28141,148,"TCD","Chad","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2013/tcd_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
28142,148,"TCD","Chad","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2013/tcd_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
28143,148,"TCD","Chad","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2013/tcd_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
28144,148,"TCD","Chad","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2013/tcd_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
28145,148,"TCD","Chad","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2013/tcd_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
28146,148,"TCD","Chad","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2013/tcd_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
28147,148,"TCD","Chad","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2013/tcd_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
28148,148,"TCD","Chad","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2013/tcd_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
28149,148,"TCD","Chad","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2014/tcd_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
28150,148,"TCD","Chad","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2014/tcd_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
28151,148,"TCD","Chad","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2014/tcd_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
28152,148,"TCD","Chad","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2014/tcd_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
28153,148,"TCD","Chad","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2014/tcd_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
28154,148,"TCD","Chad","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2014/tcd_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
28155,148,"TCD","Chad","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2014/tcd_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
28156,148,"TCD","Chad","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2014/tcd_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
28157,148,"TCD","Chad","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2015/tcd_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
28158,148,"TCD","Chad","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2015/tcd_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
28159,148,"TCD","Chad","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2015/tcd_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
28160,148,"TCD","Chad","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2015/tcd_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
28161,148,"TCD","Chad","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2015/tcd_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
28162,148,"TCD","Chad","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2015/tcd_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
28163,148,"TCD","Chad","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2015/tcd_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
28164,148,"TCD","Chad","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Annual/2015/tcd_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
28165,158,"TWN","Taiwan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2000/twn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
28166,158,"TWN","Taiwan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2000/twn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
28167,158,"TWN","Taiwan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2000/twn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
28168,158,"TWN","Taiwan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2000/twn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
28169,158,"TWN","Taiwan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2000/twn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
28170,158,"TWN","Taiwan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2000/twn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
28171,158,"TWN","Taiwan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2000/twn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
28172,158,"TWN","Taiwan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2000/twn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
28173,158,"TWN","Taiwan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2001/twn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
28174,158,"TWN","Taiwan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2001/twn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
28175,158,"TWN","Taiwan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2001/twn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
28176,158,"TWN","Taiwan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2001/twn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
28177,158,"TWN","Taiwan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2001/twn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
28178,158,"TWN","Taiwan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2001/twn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
28179,158,"TWN","Taiwan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2001/twn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
28180,158,"TWN","Taiwan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2001/twn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
28181,158,"TWN","Taiwan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2002/twn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
28182,158,"TWN","Taiwan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2002/twn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
28183,158,"TWN","Taiwan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2002/twn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
28184,158,"TWN","Taiwan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2002/twn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
28185,158,"TWN","Taiwan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2002/twn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
28186,158,"TWN","Taiwan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2002/twn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
28187,158,"TWN","Taiwan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2002/twn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
28188,158,"TWN","Taiwan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2002/twn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
28189,158,"TWN","Taiwan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2003/twn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
28190,158,"TWN","Taiwan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2003/twn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
28191,158,"TWN","Taiwan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2003/twn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
28192,158,"TWN","Taiwan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2003/twn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
28193,158,"TWN","Taiwan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2003/twn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
28194,158,"TWN","Taiwan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2003/twn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
28195,158,"TWN","Taiwan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2003/twn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
28196,158,"TWN","Taiwan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2003/twn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
28197,158,"TWN","Taiwan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2004/twn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
28198,158,"TWN","Taiwan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2004/twn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
28199,158,"TWN","Taiwan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2004/twn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
28200,158,"TWN","Taiwan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2004/twn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
28201,158,"TWN","Taiwan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2004/twn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
28202,158,"TWN","Taiwan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2004/twn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
28203,158,"TWN","Taiwan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2004/twn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
28204,158,"TWN","Taiwan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2004/twn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
28205,158,"TWN","Taiwan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2005/twn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
28206,158,"TWN","Taiwan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2005/twn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
28207,158,"TWN","Taiwan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2005/twn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
28208,158,"TWN","Taiwan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2005/twn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
28209,158,"TWN","Taiwan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2005/twn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
28210,158,"TWN","Taiwan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2005/twn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
28211,158,"TWN","Taiwan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2005/twn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
28212,158,"TWN","Taiwan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2005/twn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
28213,158,"TWN","Taiwan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2006/twn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
28214,158,"TWN","Taiwan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2006/twn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
28215,158,"TWN","Taiwan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2006/twn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
28216,158,"TWN","Taiwan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2006/twn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
28217,158,"TWN","Taiwan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2006/twn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
28218,158,"TWN","Taiwan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2006/twn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
28219,158,"TWN","Taiwan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2006/twn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
28220,158,"TWN","Taiwan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2006/twn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
28221,158,"TWN","Taiwan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2007/twn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
28222,158,"TWN","Taiwan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2007/twn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
28223,158,"TWN","Taiwan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2007/twn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
28224,158,"TWN","Taiwan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2007/twn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
28225,158,"TWN","Taiwan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2007/twn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
28226,158,"TWN","Taiwan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2007/twn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
28227,158,"TWN","Taiwan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2007/twn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
28228,158,"TWN","Taiwan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2007/twn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
28229,158,"TWN","Taiwan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2008/twn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
28230,158,"TWN","Taiwan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2008/twn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
28231,158,"TWN","Taiwan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2008/twn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
28232,158,"TWN","Taiwan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2008/twn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
28233,158,"TWN","Taiwan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2008/twn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
28234,158,"TWN","Taiwan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2008/twn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
28235,158,"TWN","Taiwan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2008/twn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
28236,158,"TWN","Taiwan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2008/twn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
28237,158,"TWN","Taiwan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2009/twn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
28238,158,"TWN","Taiwan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2009/twn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
28239,158,"TWN","Taiwan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2009/twn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
28240,158,"TWN","Taiwan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2009/twn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
28241,158,"TWN","Taiwan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2009/twn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
28242,158,"TWN","Taiwan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2009/twn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
28243,158,"TWN","Taiwan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2009/twn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
28244,158,"TWN","Taiwan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2009/twn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
28245,158,"TWN","Taiwan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2010/twn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
28246,158,"TWN","Taiwan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2010/twn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
28247,158,"TWN","Taiwan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2010/twn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
28248,158,"TWN","Taiwan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2010/twn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
28249,158,"TWN","Taiwan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2010/twn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
28250,158,"TWN","Taiwan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2010/twn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
28251,158,"TWN","Taiwan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2010/twn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
28252,158,"TWN","Taiwan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2010/twn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
28253,158,"TWN","Taiwan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2011/twn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
28254,158,"TWN","Taiwan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2011/twn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
28255,158,"TWN","Taiwan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2011/twn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
28256,158,"TWN","Taiwan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2011/twn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
28257,158,"TWN","Taiwan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2011/twn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
28258,158,"TWN","Taiwan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2011/twn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
28259,158,"TWN","Taiwan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2011/twn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
28260,158,"TWN","Taiwan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2011/twn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
28261,158,"TWN","Taiwan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2012/twn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
28262,158,"TWN","Taiwan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2012/twn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
28263,158,"TWN","Taiwan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2012/twn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
28264,158,"TWN","Taiwan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2012/twn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
28265,158,"TWN","Taiwan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2012/twn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
28266,158,"TWN","Taiwan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2012/twn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
28267,158,"TWN","Taiwan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2012/twn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
28268,158,"TWN","Taiwan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2012/twn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
28269,158,"TWN","Taiwan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2013/twn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
28270,158,"TWN","Taiwan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2013/twn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
28271,158,"TWN","Taiwan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2013/twn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
28272,158,"TWN","Taiwan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2013/twn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
28273,158,"TWN","Taiwan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2013/twn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
28274,158,"TWN","Taiwan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2013/twn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
28275,158,"TWN","Taiwan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2013/twn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
28276,158,"TWN","Taiwan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2013/twn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
28277,158,"TWN","Taiwan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2014/twn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
28278,158,"TWN","Taiwan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2014/twn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
28279,158,"TWN","Taiwan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2014/twn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
28280,158,"TWN","Taiwan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2014/twn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
28281,158,"TWN","Taiwan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2014/twn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
28282,158,"TWN","Taiwan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2014/twn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
28283,158,"TWN","Taiwan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2014/twn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
28284,158,"TWN","Taiwan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2014/twn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
28285,158,"TWN","Taiwan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2015/twn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
28286,158,"TWN","Taiwan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2015/twn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
28287,158,"TWN","Taiwan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2015/twn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
28288,158,"TWN","Taiwan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2015/twn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
28289,158,"TWN","Taiwan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2015/twn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
28290,158,"TWN","Taiwan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2015/twn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
28291,158,"TWN","Taiwan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2015/twn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
28292,158,"TWN","Taiwan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Annual/2015/twn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
28293,170,"COL","Colombia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2000/col_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
28294,170,"COL","Colombia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2000/col_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
28295,170,"COL","Colombia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2000/col_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
28296,170,"COL","Colombia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2000/col_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
28297,170,"COL","Colombia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2000/col_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
28298,170,"COL","Colombia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2000/col_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
28299,170,"COL","Colombia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2000/col_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
28300,170,"COL","Colombia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2000/col_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
28301,170,"COL","Colombia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2001/col_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
28302,170,"COL","Colombia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2001/col_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
28303,170,"COL","Colombia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2001/col_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
28304,170,"COL","Colombia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2001/col_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
28305,170,"COL","Colombia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2001/col_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
28306,170,"COL","Colombia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2001/col_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
28307,170,"COL","Colombia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2001/col_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
28308,170,"COL","Colombia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2001/col_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
28309,170,"COL","Colombia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2002/col_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
28310,170,"COL","Colombia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2002/col_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
28311,170,"COL","Colombia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2002/col_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
28312,170,"COL","Colombia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2002/col_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
28313,170,"COL","Colombia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2002/col_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
28314,170,"COL","Colombia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2002/col_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
28315,170,"COL","Colombia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2002/col_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
28316,170,"COL","Colombia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2002/col_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
28317,170,"COL","Colombia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2003/col_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
28318,170,"COL","Colombia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2003/col_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
28319,170,"COL","Colombia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2003/col_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
28320,170,"COL","Colombia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2003/col_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
28321,170,"COL","Colombia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2003/col_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
28322,170,"COL","Colombia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2003/col_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
28323,170,"COL","Colombia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2003/col_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
28324,170,"COL","Colombia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2003/col_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
28325,170,"COL","Colombia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2004/col_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
28326,170,"COL","Colombia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2004/col_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
28327,170,"COL","Colombia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2004/col_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
28328,170,"COL","Colombia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2004/col_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
28329,170,"COL","Colombia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2004/col_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
28330,170,"COL","Colombia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2004/col_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
28331,170,"COL","Colombia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2004/col_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
28332,170,"COL","Colombia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2004/col_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
28333,170,"COL","Colombia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2005/col_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
28334,170,"COL","Colombia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2005/col_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
28335,170,"COL","Colombia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2005/col_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
28336,170,"COL","Colombia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2005/col_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
28337,170,"COL","Colombia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2005/col_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
28338,170,"COL","Colombia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2005/col_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
28339,170,"COL","Colombia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2005/col_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
28340,170,"COL","Colombia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2005/col_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
28341,170,"COL","Colombia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2006/col_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
28342,170,"COL","Colombia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2006/col_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
28343,170,"COL","Colombia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2006/col_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
28344,170,"COL","Colombia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2006/col_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
28345,170,"COL","Colombia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2006/col_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
28346,170,"COL","Colombia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2006/col_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
28347,170,"COL","Colombia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2006/col_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
28348,170,"COL","Colombia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2006/col_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
28349,170,"COL","Colombia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2007/col_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
28350,170,"COL","Colombia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2007/col_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
28351,170,"COL","Colombia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2007/col_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
28352,170,"COL","Colombia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2007/col_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
28353,170,"COL","Colombia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2007/col_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
28354,170,"COL","Colombia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2007/col_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
28355,170,"COL","Colombia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2007/col_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
28356,170,"COL","Colombia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2007/col_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
28357,170,"COL","Colombia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2008/col_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
28358,170,"COL","Colombia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2008/col_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
28359,170,"COL","Colombia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2008/col_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
28360,170,"COL","Colombia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2008/col_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
28361,170,"COL","Colombia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2008/col_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
28362,170,"COL","Colombia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2008/col_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
28363,170,"COL","Colombia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2008/col_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
28364,170,"COL","Colombia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2008/col_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
28365,170,"COL","Colombia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2009/col_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
28366,170,"COL","Colombia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2009/col_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
28367,170,"COL","Colombia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2009/col_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
28368,170,"COL","Colombia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2009/col_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
28369,170,"COL","Colombia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2009/col_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
28370,170,"COL","Colombia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2009/col_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
28371,170,"COL","Colombia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2009/col_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
28372,170,"COL","Colombia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2009/col_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
28373,170,"COL","Colombia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2010/col_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
28374,170,"COL","Colombia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2010/col_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
28375,170,"COL","Colombia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2010/col_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
28376,170,"COL","Colombia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2010/col_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
28377,170,"COL","Colombia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2010/col_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
28378,170,"COL","Colombia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2010/col_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
28379,170,"COL","Colombia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2010/col_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
28380,170,"COL","Colombia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2010/col_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
28381,170,"COL","Colombia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2011/col_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
28382,170,"COL","Colombia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2011/col_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
28383,170,"COL","Colombia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2011/col_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
28384,170,"COL","Colombia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2011/col_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
28385,170,"COL","Colombia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2011/col_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
28386,170,"COL","Colombia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2011/col_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
28387,170,"COL","Colombia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2011/col_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
28388,170,"COL","Colombia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2011/col_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
28389,170,"COL","Colombia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2012/col_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
28390,170,"COL","Colombia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2012/col_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
28391,170,"COL","Colombia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2012/col_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
28392,170,"COL","Colombia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2012/col_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
28393,170,"COL","Colombia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2012/col_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
28394,170,"COL","Colombia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2012/col_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
28395,170,"COL","Colombia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2012/col_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
28396,170,"COL","Colombia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2012/col_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
28397,170,"COL","Colombia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2013/col_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
28398,170,"COL","Colombia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2013/col_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
28399,170,"COL","Colombia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2013/col_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
28400,170,"COL","Colombia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2013/col_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
28401,170,"COL","Colombia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2013/col_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
28402,170,"COL","Colombia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2013/col_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
28403,170,"COL","Colombia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2013/col_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
28404,170,"COL","Colombia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2013/col_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
28405,170,"COL","Colombia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2014/col_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
28406,170,"COL","Colombia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2014/col_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
28407,170,"COL","Colombia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2014/col_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
28408,170,"COL","Colombia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2014/col_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
28409,170,"COL","Colombia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2014/col_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
28410,170,"COL","Colombia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2014/col_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
28411,170,"COL","Colombia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2014/col_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
28412,170,"COL","Colombia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2014/col_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
28413,170,"COL","Colombia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2015/col_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
28414,170,"COL","Colombia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2015/col_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
28415,170,"COL","Colombia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2015/col_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
28416,170,"COL","Colombia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2015/col_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
28417,170,"COL","Colombia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2015/col_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
28418,170,"COL","Colombia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2015/col_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
28419,170,"COL","Colombia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2015/col_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
28420,170,"COL","Colombia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Annual/2015/col_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
28421,174,"COM","Comoros","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2000/com_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
28422,174,"COM","Comoros","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2000/com_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
28423,174,"COM","Comoros","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2000/com_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
28424,174,"COM","Comoros","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2000/com_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
28425,174,"COM","Comoros","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2000/com_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
28426,174,"COM","Comoros","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2000/com_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
28427,174,"COM","Comoros","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2000/com_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
28428,174,"COM","Comoros","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2000/com_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
28429,174,"COM","Comoros","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2001/com_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
28430,174,"COM","Comoros","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2001/com_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
28431,174,"COM","Comoros","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2001/com_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
28432,174,"COM","Comoros","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2001/com_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
28433,174,"COM","Comoros","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2001/com_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
28434,174,"COM","Comoros","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2001/com_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
28435,174,"COM","Comoros","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2001/com_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
28436,174,"COM","Comoros","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2001/com_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
28437,174,"COM","Comoros","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2002/com_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
28438,174,"COM","Comoros","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2002/com_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
28439,174,"COM","Comoros","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2002/com_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
28440,174,"COM","Comoros","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2002/com_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
28441,174,"COM","Comoros","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2002/com_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
28442,174,"COM","Comoros","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2002/com_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
28443,174,"COM","Comoros","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2002/com_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
28444,174,"COM","Comoros","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2002/com_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
28445,174,"COM","Comoros","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2003/com_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
28446,174,"COM","Comoros","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2003/com_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
28447,174,"COM","Comoros","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2003/com_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
28448,174,"COM","Comoros","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2003/com_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
28449,174,"COM","Comoros","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2003/com_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
28450,174,"COM","Comoros","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2003/com_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
28451,174,"COM","Comoros","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2003/com_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
28452,174,"COM","Comoros","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2003/com_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
28453,174,"COM","Comoros","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2004/com_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
28454,174,"COM","Comoros","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2004/com_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
28455,174,"COM","Comoros","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2004/com_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
28456,174,"COM","Comoros","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2004/com_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
28457,174,"COM","Comoros","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2004/com_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
28458,174,"COM","Comoros","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2004/com_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
28459,174,"COM","Comoros","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2004/com_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
28460,174,"COM","Comoros","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2004/com_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
28461,174,"COM","Comoros","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2005/com_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
28462,174,"COM","Comoros","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2005/com_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
28463,174,"COM","Comoros","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2005/com_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
28464,174,"COM","Comoros","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2005/com_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
28465,174,"COM","Comoros","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2005/com_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
28466,174,"COM","Comoros","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2005/com_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
28467,174,"COM","Comoros","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2005/com_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
28468,174,"COM","Comoros","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2005/com_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
28469,174,"COM","Comoros","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2006/com_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
28470,174,"COM","Comoros","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2006/com_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
28471,174,"COM","Comoros","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2006/com_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
28472,174,"COM","Comoros","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2006/com_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
28473,174,"COM","Comoros","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2006/com_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
28474,174,"COM","Comoros","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2006/com_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
28475,174,"COM","Comoros","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2006/com_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
28476,174,"COM","Comoros","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2006/com_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
28477,174,"COM","Comoros","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2007/com_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
28478,174,"COM","Comoros","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2007/com_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
28479,174,"COM","Comoros","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2007/com_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
28480,174,"COM","Comoros","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2007/com_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
28481,174,"COM","Comoros","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2007/com_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
28482,174,"COM","Comoros","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2007/com_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
28483,174,"COM","Comoros","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2007/com_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
28484,174,"COM","Comoros","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2007/com_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
28485,174,"COM","Comoros","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2008/com_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
28486,174,"COM","Comoros","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2008/com_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
28487,174,"COM","Comoros","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2008/com_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
28488,174,"COM","Comoros","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2008/com_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
28489,174,"COM","Comoros","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2008/com_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
28490,174,"COM","Comoros","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2008/com_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
28491,174,"COM","Comoros","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2008/com_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
28492,174,"COM","Comoros","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2008/com_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
28493,174,"COM","Comoros","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2009/com_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
28494,174,"COM","Comoros","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2009/com_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
28495,174,"COM","Comoros","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2009/com_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
28496,174,"COM","Comoros","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2009/com_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
28497,174,"COM","Comoros","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2009/com_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
28498,174,"COM","Comoros","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2009/com_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
28499,174,"COM","Comoros","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2009/com_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
28500,174,"COM","Comoros","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2009/com_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
28501,174,"COM","Comoros","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2010/com_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
28502,174,"COM","Comoros","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2010/com_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
28503,174,"COM","Comoros","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2010/com_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
28504,174,"COM","Comoros","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2010/com_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
28505,174,"COM","Comoros","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2010/com_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
28506,174,"COM","Comoros","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2010/com_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
28507,174,"COM","Comoros","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2010/com_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
28508,174,"COM","Comoros","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2010/com_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
28509,174,"COM","Comoros","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2011/com_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
28510,174,"COM","Comoros","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2011/com_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
28511,174,"COM","Comoros","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2011/com_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
28512,174,"COM","Comoros","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2011/com_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
28513,174,"COM","Comoros","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2011/com_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
28514,174,"COM","Comoros","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2011/com_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
28515,174,"COM","Comoros","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2011/com_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
28516,174,"COM","Comoros","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2011/com_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
28517,174,"COM","Comoros","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2012/com_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
28518,174,"COM","Comoros","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2012/com_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
28519,174,"COM","Comoros","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2012/com_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
28520,174,"COM","Comoros","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2012/com_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
28521,174,"COM","Comoros","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2012/com_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
28522,174,"COM","Comoros","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2012/com_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
28523,174,"COM","Comoros","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2012/com_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
28524,174,"COM","Comoros","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2012/com_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
28525,174,"COM","Comoros","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2013/com_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
28526,174,"COM","Comoros","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2013/com_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
28527,174,"COM","Comoros","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2013/com_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
28528,174,"COM","Comoros","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2013/com_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
28529,174,"COM","Comoros","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2013/com_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
28530,174,"COM","Comoros","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2013/com_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
28531,174,"COM","Comoros","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2013/com_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
28532,174,"COM","Comoros","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2013/com_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
28533,174,"COM","Comoros","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2014/com_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
28534,174,"COM","Comoros","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2014/com_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
28535,174,"COM","Comoros","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2014/com_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
28536,174,"COM","Comoros","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2014/com_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
28537,174,"COM","Comoros","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2014/com_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
28538,174,"COM","Comoros","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2014/com_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
28539,174,"COM","Comoros","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2014/com_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
28540,174,"COM","Comoros","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2014/com_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
28541,174,"COM","Comoros","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2015/com_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
28542,174,"COM","Comoros","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2015/com_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
28543,174,"COM","Comoros","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2015/com_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
28544,174,"COM","Comoros","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2015/com_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
28545,174,"COM","Comoros","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2015/com_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
28546,174,"COM","Comoros","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2015/com_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
28547,174,"COM","Comoros","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2015/com_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
28548,174,"COM","Comoros","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Annual/2015/com_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
28549,175,"MYT","Mayotte","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2000/myt_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
28550,175,"MYT","Mayotte","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2000/myt_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
28551,175,"MYT","Mayotte","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2000/myt_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
28552,175,"MYT","Mayotte","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2000/myt_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
28553,175,"MYT","Mayotte","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2000/myt_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
28554,175,"MYT","Mayotte","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2000/myt_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
28555,175,"MYT","Mayotte","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2000/myt_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
28556,175,"MYT","Mayotte","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2000/myt_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
28557,175,"MYT","Mayotte","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2001/myt_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
28558,175,"MYT","Mayotte","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2001/myt_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
28559,175,"MYT","Mayotte","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2001/myt_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
28560,175,"MYT","Mayotte","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2001/myt_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
28561,175,"MYT","Mayotte","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2001/myt_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
28562,175,"MYT","Mayotte","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2001/myt_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
28563,175,"MYT","Mayotte","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2001/myt_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
28564,175,"MYT","Mayotte","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2001/myt_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
28565,175,"MYT","Mayotte","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2002/myt_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
28566,175,"MYT","Mayotte","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2002/myt_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
28567,175,"MYT","Mayotte","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2002/myt_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
28568,175,"MYT","Mayotte","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2002/myt_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
28569,175,"MYT","Mayotte","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2002/myt_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
28570,175,"MYT","Mayotte","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2002/myt_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
28571,175,"MYT","Mayotte","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2002/myt_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
28572,175,"MYT","Mayotte","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2002/myt_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
28573,175,"MYT","Mayotte","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2003/myt_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
28574,175,"MYT","Mayotte","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2003/myt_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
28575,175,"MYT","Mayotte","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2003/myt_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
28576,175,"MYT","Mayotte","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2003/myt_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
28577,175,"MYT","Mayotte","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2003/myt_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
28578,175,"MYT","Mayotte","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2003/myt_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
28579,175,"MYT","Mayotte","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2003/myt_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
28580,175,"MYT","Mayotte","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2003/myt_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
28581,175,"MYT","Mayotte","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2004/myt_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
28582,175,"MYT","Mayotte","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2004/myt_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
28583,175,"MYT","Mayotte","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2004/myt_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
28584,175,"MYT","Mayotte","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2004/myt_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
28585,175,"MYT","Mayotte","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2004/myt_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
28586,175,"MYT","Mayotte","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2004/myt_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
28587,175,"MYT","Mayotte","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2004/myt_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
28588,175,"MYT","Mayotte","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2004/myt_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
28589,175,"MYT","Mayotte","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2005/myt_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
28590,175,"MYT","Mayotte","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2005/myt_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
28591,175,"MYT","Mayotte","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2005/myt_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
28592,175,"MYT","Mayotte","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2005/myt_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
28593,175,"MYT","Mayotte","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2005/myt_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
28594,175,"MYT","Mayotte","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2005/myt_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
28595,175,"MYT","Mayotte","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2005/myt_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
28596,175,"MYT","Mayotte","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2005/myt_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
28597,175,"MYT","Mayotte","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2006/myt_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
28598,175,"MYT","Mayotte","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2006/myt_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
28599,175,"MYT","Mayotte","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2006/myt_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
28600,175,"MYT","Mayotte","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2006/myt_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
28601,175,"MYT","Mayotte","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2006/myt_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
28602,175,"MYT","Mayotte","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2006/myt_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
28603,175,"MYT","Mayotte","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2006/myt_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
28604,175,"MYT","Mayotte","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2006/myt_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
28605,175,"MYT","Mayotte","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2007/myt_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
28606,175,"MYT","Mayotte","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2007/myt_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
28607,175,"MYT","Mayotte","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2007/myt_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
28608,175,"MYT","Mayotte","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2007/myt_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
28609,175,"MYT","Mayotte","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2007/myt_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
28610,175,"MYT","Mayotte","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2007/myt_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
28611,175,"MYT","Mayotte","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2007/myt_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
28612,175,"MYT","Mayotte","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2007/myt_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
28613,175,"MYT","Mayotte","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2008/myt_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
28614,175,"MYT","Mayotte","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2008/myt_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
28615,175,"MYT","Mayotte","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2008/myt_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
28616,175,"MYT","Mayotte","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2008/myt_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
28617,175,"MYT","Mayotte","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2008/myt_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
28618,175,"MYT","Mayotte","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2008/myt_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
28619,175,"MYT","Mayotte","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2008/myt_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
28620,175,"MYT","Mayotte","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2008/myt_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
28621,175,"MYT","Mayotte","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2009/myt_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
28622,175,"MYT","Mayotte","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2009/myt_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
28623,175,"MYT","Mayotte","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2009/myt_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
28624,175,"MYT","Mayotte","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2009/myt_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
28625,175,"MYT","Mayotte","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2009/myt_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
28626,175,"MYT","Mayotte","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2009/myt_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
28627,175,"MYT","Mayotte","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2009/myt_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
28628,175,"MYT","Mayotte","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2009/myt_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
28629,175,"MYT","Mayotte","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2010/myt_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
28630,175,"MYT","Mayotte","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2010/myt_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
28631,175,"MYT","Mayotte","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2010/myt_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
28632,175,"MYT","Mayotte","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2010/myt_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
28633,175,"MYT","Mayotte","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2010/myt_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
28634,175,"MYT","Mayotte","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2010/myt_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
28635,175,"MYT","Mayotte","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2010/myt_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
28636,175,"MYT","Mayotte","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2010/myt_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
28637,175,"MYT","Mayotte","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2011/myt_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
28638,175,"MYT","Mayotte","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2011/myt_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
28639,175,"MYT","Mayotte","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2011/myt_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
28640,175,"MYT","Mayotte","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2011/myt_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
28641,175,"MYT","Mayotte","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2011/myt_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
28642,175,"MYT","Mayotte","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2011/myt_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
28643,175,"MYT","Mayotte","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2011/myt_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
28644,175,"MYT","Mayotte","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2011/myt_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
28645,175,"MYT","Mayotte","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2012/myt_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
28646,175,"MYT","Mayotte","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2012/myt_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
28647,175,"MYT","Mayotte","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2012/myt_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
28648,175,"MYT","Mayotte","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2012/myt_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
28649,175,"MYT","Mayotte","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2012/myt_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
28650,175,"MYT","Mayotte","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2012/myt_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
28651,175,"MYT","Mayotte","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2012/myt_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
28652,175,"MYT","Mayotte","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2012/myt_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
28653,175,"MYT","Mayotte","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2013/myt_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
28654,175,"MYT","Mayotte","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2013/myt_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
28655,175,"MYT","Mayotte","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2013/myt_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
28656,175,"MYT","Mayotte","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2013/myt_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
28657,175,"MYT","Mayotte","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2013/myt_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
28658,175,"MYT","Mayotte","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2013/myt_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
28659,175,"MYT","Mayotte","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2013/myt_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
28660,175,"MYT","Mayotte","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2013/myt_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
28661,175,"MYT","Mayotte","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2014/myt_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
28662,175,"MYT","Mayotte","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2014/myt_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
28663,175,"MYT","Mayotte","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2014/myt_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
28664,175,"MYT","Mayotte","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2014/myt_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
28665,175,"MYT","Mayotte","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2014/myt_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
28666,175,"MYT","Mayotte","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2014/myt_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
28667,175,"MYT","Mayotte","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2014/myt_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
28668,175,"MYT","Mayotte","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2014/myt_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
28669,175,"MYT","Mayotte","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2015/myt_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
28670,175,"MYT","Mayotte","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2015/myt_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
28671,175,"MYT","Mayotte","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2015/myt_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
28672,175,"MYT","Mayotte","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2015/myt_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
28673,175,"MYT","Mayotte","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2015/myt_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
28674,175,"MYT","Mayotte","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2015/myt_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
28675,175,"MYT","Mayotte","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2015/myt_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
28676,175,"MYT","Mayotte","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Annual/2015/myt_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
28677,178,"COG","Republic of Congo","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2000/cog_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
28678,178,"COG","Republic of Congo","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2000/cog_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
28679,178,"COG","Republic of Congo","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2000/cog_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
28680,178,"COG","Republic of Congo","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2000/cog_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
28681,178,"COG","Republic of Congo","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2000/cog_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
28682,178,"COG","Republic of Congo","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2000/cog_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
28683,178,"COG","Republic of Congo","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2000/cog_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
28684,178,"COG","Republic of Congo","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2000/cog_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
28685,178,"COG","Republic of Congo","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2001/cog_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
28686,178,"COG","Republic of Congo","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2001/cog_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
28687,178,"COG","Republic of Congo","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2001/cog_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
28688,178,"COG","Republic of Congo","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2001/cog_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
28689,178,"COG","Republic of Congo","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2001/cog_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
28690,178,"COG","Republic of Congo","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2001/cog_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
28691,178,"COG","Republic of Congo","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2001/cog_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
28692,178,"COG","Republic of Congo","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2001/cog_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
28693,178,"COG","Republic of Congo","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2002/cog_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
28694,178,"COG","Republic of Congo","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2002/cog_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
28695,178,"COG","Republic of Congo","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2002/cog_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
28696,178,"COG","Republic of Congo","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2002/cog_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
28697,178,"COG","Republic of Congo","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2002/cog_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
28698,178,"COG","Republic of Congo","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2002/cog_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
28699,178,"COG","Republic of Congo","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2002/cog_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
28700,178,"COG","Republic of Congo","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2002/cog_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
28701,178,"COG","Republic of Congo","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2003/cog_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
28702,178,"COG","Republic of Congo","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2003/cog_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
28703,178,"COG","Republic of Congo","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2003/cog_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
28704,178,"COG","Republic of Congo","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2003/cog_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
28705,178,"COG","Republic of Congo","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2003/cog_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
28706,178,"COG","Republic of Congo","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2003/cog_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
28707,178,"COG","Republic of Congo","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2003/cog_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
28708,178,"COG","Republic of Congo","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2003/cog_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
28709,178,"COG","Republic of Congo","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2004/cog_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
28710,178,"COG","Republic of Congo","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2004/cog_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
28711,178,"COG","Republic of Congo","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2004/cog_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
28712,178,"COG","Republic of Congo","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2004/cog_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
28713,178,"COG","Republic of Congo","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2004/cog_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
28714,178,"COG","Republic of Congo","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2004/cog_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
28715,178,"COG","Republic of Congo","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2004/cog_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
28716,178,"COG","Republic of Congo","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2004/cog_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
28717,178,"COG","Republic of Congo","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2005/cog_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
28718,178,"COG","Republic of Congo","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2005/cog_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
28719,178,"COG","Republic of Congo","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2005/cog_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
28720,178,"COG","Republic of Congo","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2005/cog_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
28721,178,"COG","Republic of Congo","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2005/cog_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
28722,178,"COG","Republic of Congo","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2005/cog_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
28723,178,"COG","Republic of Congo","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2005/cog_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
28724,178,"COG","Republic of Congo","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2005/cog_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
28725,178,"COG","Republic of Congo","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2006/cog_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
28726,178,"COG","Republic of Congo","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2006/cog_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
28727,178,"COG","Republic of Congo","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2006/cog_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
28728,178,"COG","Republic of Congo","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2006/cog_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
28729,178,"COG","Republic of Congo","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2006/cog_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
28730,178,"COG","Republic of Congo","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2006/cog_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
28731,178,"COG","Republic of Congo","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2006/cog_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
28732,178,"COG","Republic of Congo","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2006/cog_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
28733,178,"COG","Republic of Congo","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2007/cog_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
28734,178,"COG","Republic of Congo","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2007/cog_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
28735,178,"COG","Republic of Congo","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2007/cog_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
28736,178,"COG","Republic of Congo","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2007/cog_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
28737,178,"COG","Republic of Congo","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2007/cog_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
28738,178,"COG","Republic of Congo","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2007/cog_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
28739,178,"COG","Republic of Congo","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2007/cog_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
28740,178,"COG","Republic of Congo","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2007/cog_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
28741,178,"COG","Republic of Congo","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2008/cog_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
28742,178,"COG","Republic of Congo","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2008/cog_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
28743,178,"COG","Republic of Congo","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2008/cog_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
28744,178,"COG","Republic of Congo","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2008/cog_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
28745,178,"COG","Republic of Congo","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2008/cog_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
28746,178,"COG","Republic of Congo","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2008/cog_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
28747,178,"COG","Republic of Congo","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2008/cog_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
28748,178,"COG","Republic of Congo","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2008/cog_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
28749,178,"COG","Republic of Congo","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2009/cog_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
28750,178,"COG","Republic of Congo","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2009/cog_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
28751,178,"COG","Republic of Congo","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2009/cog_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
28752,178,"COG","Republic of Congo","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2009/cog_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
28753,178,"COG","Republic of Congo","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2009/cog_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
28754,178,"COG","Republic of Congo","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2009/cog_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
28755,178,"COG","Republic of Congo","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2009/cog_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
28756,178,"COG","Republic of Congo","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2009/cog_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
28757,178,"COG","Republic of Congo","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2010/cog_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
28758,178,"COG","Republic of Congo","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2010/cog_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
28759,178,"COG","Republic of Congo","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2010/cog_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
28760,178,"COG","Republic of Congo","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2010/cog_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
28761,178,"COG","Republic of Congo","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2010/cog_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
28762,178,"COG","Republic of Congo","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2010/cog_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
28763,178,"COG","Republic of Congo","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2010/cog_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
28764,178,"COG","Republic of Congo","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2010/cog_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
28765,178,"COG","Republic of Congo","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2011/cog_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
28766,178,"COG","Republic of Congo","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2011/cog_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
28767,178,"COG","Republic of Congo","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2011/cog_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
28768,178,"COG","Republic of Congo","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2011/cog_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
28769,178,"COG","Republic of Congo","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2011/cog_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
28770,178,"COG","Republic of Congo","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2011/cog_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
28771,178,"COG","Republic of Congo","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2011/cog_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
28772,178,"COG","Republic of Congo","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2011/cog_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
28773,178,"COG","Republic of Congo","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2012/cog_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
28774,178,"COG","Republic of Congo","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2012/cog_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
28775,178,"COG","Republic of Congo","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2012/cog_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
28776,178,"COG","Republic of Congo","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2012/cog_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
28777,178,"COG","Republic of Congo","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2012/cog_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
28778,178,"COG","Republic of Congo","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2012/cog_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
28779,178,"COG","Republic of Congo","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2012/cog_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
28780,178,"COG","Republic of Congo","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2012/cog_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
28781,178,"COG","Republic of Congo","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2013/cog_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
28782,178,"COG","Republic of Congo","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2013/cog_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
28783,178,"COG","Republic of Congo","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2013/cog_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
28784,178,"COG","Republic of Congo","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2013/cog_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
28785,178,"COG","Republic of Congo","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2013/cog_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
28786,178,"COG","Republic of Congo","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2013/cog_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
28787,178,"COG","Republic of Congo","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2013/cog_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
28788,178,"COG","Republic of Congo","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2013/cog_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
28789,178,"COG","Republic of Congo","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2014/cog_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
28790,178,"COG","Republic of Congo","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2014/cog_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
28791,178,"COG","Republic of Congo","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2014/cog_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
28792,178,"COG","Republic of Congo","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2014/cog_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
28793,178,"COG","Republic of Congo","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2014/cog_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
28794,178,"COG","Republic of Congo","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2014/cog_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
28795,178,"COG","Republic of Congo","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2014/cog_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
28796,178,"COG","Republic of Congo","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2014/cog_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
28797,178,"COG","Republic of Congo","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2015/cog_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
28798,178,"COG","Republic of Congo","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2015/cog_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
28799,178,"COG","Republic of Congo","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2015/cog_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
28800,178,"COG","Republic of Congo","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2015/cog_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
28801,178,"COG","Republic of Congo","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2015/cog_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
28802,178,"COG","Republic of Congo","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2015/cog_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
28803,178,"COG","Republic of Congo","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2015/cog_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
28804,178,"COG","Republic of Congo","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Annual/2015/cog_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
28805,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2000/cod_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
28806,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2000/cod_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
28807,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2000/cod_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
28808,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2000/cod_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
28809,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2000/cod_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
28810,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2000/cod_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
28811,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2000/cod_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
28812,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2000/cod_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
28813,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2001/cod_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
28814,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2001/cod_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
28815,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2001/cod_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
28816,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2001/cod_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
28817,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2001/cod_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
28818,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2001/cod_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
28819,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2001/cod_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
28820,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2001/cod_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
28821,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2002/cod_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
28822,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2002/cod_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
28823,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2002/cod_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
28824,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2002/cod_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
28825,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2002/cod_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
28826,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2002/cod_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
28827,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2002/cod_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
28828,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2002/cod_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
28829,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2003/cod_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
28830,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2003/cod_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
28831,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2003/cod_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
28832,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2003/cod_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
28833,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2003/cod_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
28834,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2003/cod_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
28835,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2003/cod_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
28836,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2003/cod_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
28837,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2004/cod_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
28838,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2004/cod_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
28839,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2004/cod_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
28840,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2004/cod_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
28841,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2004/cod_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
28842,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2004/cod_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
28843,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2004/cod_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
28844,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2004/cod_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
28845,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2005/cod_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
28846,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2005/cod_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
28847,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2005/cod_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
28848,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2005/cod_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
28849,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2005/cod_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
28850,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2005/cod_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
28851,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2005/cod_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
28852,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2005/cod_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
28853,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2006/cod_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
28854,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2006/cod_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
28855,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2006/cod_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
28856,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2006/cod_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
28857,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2006/cod_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
28858,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2006/cod_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
28859,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2006/cod_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
28860,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2006/cod_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
28861,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2007/cod_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
28862,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2007/cod_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
28863,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2007/cod_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
28864,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2007/cod_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
28865,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2007/cod_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
28866,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2007/cod_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
28867,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2007/cod_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
28868,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2007/cod_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
28869,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2008/cod_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
28870,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2008/cod_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
28871,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2008/cod_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
28872,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2008/cod_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
28873,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2008/cod_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
28874,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2008/cod_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
28875,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2008/cod_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
28876,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2008/cod_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
28877,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2009/cod_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
28878,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2009/cod_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
28879,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2009/cod_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
28880,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2009/cod_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
28881,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2009/cod_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
28882,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2009/cod_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
28883,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2009/cod_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
28884,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2009/cod_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
28885,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2010/cod_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
28886,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2010/cod_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
28887,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2010/cod_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
28888,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2010/cod_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
28889,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2010/cod_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
28890,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2010/cod_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
28891,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2010/cod_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
28892,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2010/cod_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
28893,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2011/cod_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
28894,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2011/cod_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
28895,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2011/cod_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
28896,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2011/cod_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
28897,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2011/cod_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
28898,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2011/cod_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
28899,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2011/cod_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
28900,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2011/cod_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
28901,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2012/cod_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
28902,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2012/cod_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
28903,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2012/cod_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
28904,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2012/cod_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
28905,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2012/cod_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
28906,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2012/cod_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
28907,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2012/cod_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
28908,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2012/cod_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
28909,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2013/cod_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
28910,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2013/cod_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
28911,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2013/cod_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
28912,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2013/cod_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
28913,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2013/cod_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
28914,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2013/cod_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
28915,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2013/cod_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
28916,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2013/cod_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
28917,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2014/cod_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
28918,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2014/cod_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
28919,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2014/cod_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
28920,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2014/cod_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
28921,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2014/cod_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
28922,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2014/cod_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
28923,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2014/cod_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
28924,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2014/cod_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
28925,180,"COD","Democratic Republic of the Congo","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2015/cod_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
28926,180,"COD","Democratic Republic of the Congo","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2015/cod_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
28927,180,"COD","Democratic Republic of the Congo","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2015/cod_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
28928,180,"COD","Democratic Republic of the Congo","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2015/cod_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
28929,180,"COD","Democratic Republic of the Congo","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2015/cod_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
28930,180,"COD","Democratic Republic of the Congo","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2015/cod_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
28931,180,"COD","Democratic Republic of the Congo","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2015/cod_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
28932,180,"COD","Democratic Republic of the Congo","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Annual/2015/cod_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
28933,184,"COK","Cook Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2000/cok_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
28934,184,"COK","Cook Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2000/cok_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
28935,184,"COK","Cook Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2000/cok_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
28936,184,"COK","Cook Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2000/cok_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
28937,184,"COK","Cook Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2000/cok_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
28938,184,"COK","Cook Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2000/cok_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
28939,184,"COK","Cook Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2000/cok_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
28940,184,"COK","Cook Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2000/cok_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
28941,184,"COK","Cook Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2001/cok_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
28942,184,"COK","Cook Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2001/cok_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
28943,184,"COK","Cook Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2001/cok_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
28944,184,"COK","Cook Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2001/cok_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
28945,184,"COK","Cook Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2001/cok_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
28946,184,"COK","Cook Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2001/cok_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
28947,184,"COK","Cook Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2001/cok_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
28948,184,"COK","Cook Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2001/cok_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
28949,184,"COK","Cook Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2002/cok_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
28950,184,"COK","Cook Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2002/cok_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
28951,184,"COK","Cook Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2002/cok_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
28952,184,"COK","Cook Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2002/cok_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
28953,184,"COK","Cook Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2002/cok_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
28954,184,"COK","Cook Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2002/cok_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
28955,184,"COK","Cook Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2002/cok_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
28956,184,"COK","Cook Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2002/cok_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
28957,184,"COK","Cook Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2003/cok_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
28958,184,"COK","Cook Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2003/cok_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
28959,184,"COK","Cook Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2003/cok_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
28960,184,"COK","Cook Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2003/cok_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
28961,184,"COK","Cook Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2003/cok_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
28962,184,"COK","Cook Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2003/cok_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
28963,184,"COK","Cook Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2003/cok_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
28964,184,"COK","Cook Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2003/cok_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
28965,184,"COK","Cook Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2004/cok_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
28966,184,"COK","Cook Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2004/cok_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
28967,184,"COK","Cook Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2004/cok_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
28968,184,"COK","Cook Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2004/cok_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
28969,184,"COK","Cook Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2004/cok_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
28970,184,"COK","Cook Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2004/cok_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
28971,184,"COK","Cook Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2004/cok_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
28972,184,"COK","Cook Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2004/cok_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
28973,184,"COK","Cook Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2005/cok_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
28974,184,"COK","Cook Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2005/cok_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
28975,184,"COK","Cook Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2005/cok_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
28976,184,"COK","Cook Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2005/cok_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
28977,184,"COK","Cook Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2005/cok_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
28978,184,"COK","Cook Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2005/cok_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
28979,184,"COK","Cook Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2005/cok_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
28980,184,"COK","Cook Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2005/cok_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
28981,184,"COK","Cook Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2006/cok_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
28982,184,"COK","Cook Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2006/cok_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
28983,184,"COK","Cook Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2006/cok_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
28984,184,"COK","Cook Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2006/cok_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
28985,184,"COK","Cook Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2006/cok_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
28986,184,"COK","Cook Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2006/cok_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
28987,184,"COK","Cook Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2006/cok_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
28988,184,"COK","Cook Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2006/cok_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
28989,184,"COK","Cook Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2007/cok_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
28990,184,"COK","Cook Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2007/cok_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
28991,184,"COK","Cook Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2007/cok_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
28992,184,"COK","Cook Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2007/cok_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
28993,184,"COK","Cook Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2007/cok_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
28994,184,"COK","Cook Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2007/cok_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
28995,184,"COK","Cook Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2007/cok_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
28996,184,"COK","Cook Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2007/cok_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
28997,184,"COK","Cook Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2008/cok_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
28998,184,"COK","Cook Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2008/cok_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
28999,184,"COK","Cook Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2008/cok_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
29000,184,"COK","Cook Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2008/cok_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
29001,184,"COK","Cook Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2008/cok_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
29002,184,"COK","Cook Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2008/cok_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
29003,184,"COK","Cook Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2008/cok_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
29004,184,"COK","Cook Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2008/cok_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
29005,184,"COK","Cook Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2009/cok_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
29006,184,"COK","Cook Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2009/cok_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
29007,184,"COK","Cook Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2009/cok_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
29008,184,"COK","Cook Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2009/cok_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
29009,184,"COK","Cook Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2009/cok_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
29010,184,"COK","Cook Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2009/cok_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
29011,184,"COK","Cook Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2009/cok_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
29012,184,"COK","Cook Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2009/cok_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
29013,184,"COK","Cook Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2010/cok_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
29014,184,"COK","Cook Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2010/cok_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
29015,184,"COK","Cook Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2010/cok_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
29016,184,"COK","Cook Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2010/cok_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
29017,184,"COK","Cook Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2010/cok_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
29018,184,"COK","Cook Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2010/cok_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
29019,184,"COK","Cook Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2010/cok_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
29020,184,"COK","Cook Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2010/cok_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
29021,184,"COK","Cook Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2011/cok_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
29022,184,"COK","Cook Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2011/cok_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
29023,184,"COK","Cook Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2011/cok_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
29024,184,"COK","Cook Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2011/cok_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
29025,184,"COK","Cook Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2011/cok_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
29026,184,"COK","Cook Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2011/cok_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
29027,184,"COK","Cook Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2011/cok_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
29028,184,"COK","Cook Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2011/cok_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
29029,184,"COK","Cook Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2012/cok_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
29030,184,"COK","Cook Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2012/cok_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
29031,184,"COK","Cook Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2012/cok_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
29032,184,"COK","Cook Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2012/cok_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
29033,184,"COK","Cook Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2012/cok_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
29034,184,"COK","Cook Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2012/cok_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
29035,184,"COK","Cook Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2012/cok_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
29036,184,"COK","Cook Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2012/cok_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
29037,184,"COK","Cook Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2013/cok_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
29038,184,"COK","Cook Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2013/cok_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
29039,184,"COK","Cook Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2013/cok_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
29040,184,"COK","Cook Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2013/cok_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
29041,184,"COK","Cook Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2013/cok_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
29042,184,"COK","Cook Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2013/cok_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
29043,184,"COK","Cook Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2013/cok_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
29044,184,"COK","Cook Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2013/cok_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
29045,184,"COK","Cook Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2014/cok_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
29046,184,"COK","Cook Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2014/cok_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
29047,184,"COK","Cook Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2014/cok_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
29048,184,"COK","Cook Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2014/cok_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
29049,184,"COK","Cook Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2014/cok_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
29050,184,"COK","Cook Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2014/cok_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
29051,184,"COK","Cook Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2014/cok_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
29052,184,"COK","Cook Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2014/cok_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
29053,184,"COK","Cook Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2015/cok_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
29054,184,"COK","Cook Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2015/cok_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
29055,184,"COK","Cook Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2015/cok_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
29056,184,"COK","Cook Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2015/cok_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
29057,184,"COK","Cook Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2015/cok_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
29058,184,"COK","Cook Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2015/cok_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
29059,184,"COK","Cook Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2015/cok_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
29060,184,"COK","Cook Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Annual/2015/cok_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
29061,188,"CRI","Costa Rica","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2000/cri_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
29062,188,"CRI","Costa Rica","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2000/cri_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
29063,188,"CRI","Costa Rica","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2000/cri_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
29064,188,"CRI","Costa Rica","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2000/cri_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
29065,188,"CRI","Costa Rica","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2000/cri_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
29066,188,"CRI","Costa Rica","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2000/cri_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
29067,188,"CRI","Costa Rica","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2000/cri_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
29068,188,"CRI","Costa Rica","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2000/cri_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
29069,188,"CRI","Costa Rica","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2001/cri_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
29070,188,"CRI","Costa Rica","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2001/cri_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
29071,188,"CRI","Costa Rica","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2001/cri_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
29072,188,"CRI","Costa Rica","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2001/cri_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
29073,188,"CRI","Costa Rica","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2001/cri_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
29074,188,"CRI","Costa Rica","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2001/cri_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
29075,188,"CRI","Costa Rica","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2001/cri_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
29076,188,"CRI","Costa Rica","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2001/cri_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
29077,188,"CRI","Costa Rica","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2002/cri_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
29078,188,"CRI","Costa Rica","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2002/cri_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
29079,188,"CRI","Costa Rica","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2002/cri_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
29080,188,"CRI","Costa Rica","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2002/cri_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
29081,188,"CRI","Costa Rica","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2002/cri_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
29082,188,"CRI","Costa Rica","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2002/cri_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
29083,188,"CRI","Costa Rica","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2002/cri_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
29084,188,"CRI","Costa Rica","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2002/cri_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
29085,188,"CRI","Costa Rica","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2003/cri_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
29086,188,"CRI","Costa Rica","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2003/cri_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
29087,188,"CRI","Costa Rica","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2003/cri_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
29088,188,"CRI","Costa Rica","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2003/cri_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
29089,188,"CRI","Costa Rica","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2003/cri_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
29090,188,"CRI","Costa Rica","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2003/cri_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
29091,188,"CRI","Costa Rica","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2003/cri_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
29092,188,"CRI","Costa Rica","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2003/cri_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
29093,188,"CRI","Costa Rica","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2004/cri_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
29094,188,"CRI","Costa Rica","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2004/cri_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
29095,188,"CRI","Costa Rica","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2004/cri_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
29096,188,"CRI","Costa Rica","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2004/cri_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
29097,188,"CRI","Costa Rica","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2004/cri_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
29098,188,"CRI","Costa Rica","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2004/cri_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
29099,188,"CRI","Costa Rica","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2004/cri_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
29100,188,"CRI","Costa Rica","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2004/cri_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
29101,188,"CRI","Costa Rica","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2005/cri_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
29102,188,"CRI","Costa Rica","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2005/cri_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
29103,188,"CRI","Costa Rica","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2005/cri_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
29104,188,"CRI","Costa Rica","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2005/cri_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
29105,188,"CRI","Costa Rica","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2005/cri_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
29106,188,"CRI","Costa Rica","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2005/cri_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
29107,188,"CRI","Costa Rica","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2005/cri_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
29108,188,"CRI","Costa Rica","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2005/cri_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
29109,188,"CRI","Costa Rica","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2006/cri_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
29110,188,"CRI","Costa Rica","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2006/cri_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
29111,188,"CRI","Costa Rica","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2006/cri_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
29112,188,"CRI","Costa Rica","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2006/cri_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
29113,188,"CRI","Costa Rica","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2006/cri_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
29114,188,"CRI","Costa Rica","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2006/cri_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
29115,188,"CRI","Costa Rica","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2006/cri_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
29116,188,"CRI","Costa Rica","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2006/cri_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
29117,188,"CRI","Costa Rica","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2007/cri_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
29118,188,"CRI","Costa Rica","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2007/cri_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
29119,188,"CRI","Costa Rica","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2007/cri_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
29120,188,"CRI","Costa Rica","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2007/cri_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
29121,188,"CRI","Costa Rica","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2007/cri_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
29122,188,"CRI","Costa Rica","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2007/cri_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
29123,188,"CRI","Costa Rica","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2007/cri_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
29124,188,"CRI","Costa Rica","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2007/cri_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
29125,188,"CRI","Costa Rica","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2008/cri_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
29126,188,"CRI","Costa Rica","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2008/cri_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
29127,188,"CRI","Costa Rica","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2008/cri_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
29128,188,"CRI","Costa Rica","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2008/cri_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
29129,188,"CRI","Costa Rica","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2008/cri_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
29130,188,"CRI","Costa Rica","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2008/cri_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
29131,188,"CRI","Costa Rica","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2008/cri_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
29132,188,"CRI","Costa Rica","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2008/cri_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
29133,188,"CRI","Costa Rica","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2009/cri_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
29134,188,"CRI","Costa Rica","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2009/cri_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
29135,188,"CRI","Costa Rica","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2009/cri_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
29136,188,"CRI","Costa Rica","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2009/cri_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
29137,188,"CRI","Costa Rica","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2009/cri_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
29138,188,"CRI","Costa Rica","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2009/cri_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
29139,188,"CRI","Costa Rica","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2009/cri_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
29140,188,"CRI","Costa Rica","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2009/cri_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
29141,188,"CRI","Costa Rica","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2010/cri_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
29142,188,"CRI","Costa Rica","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2010/cri_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
29143,188,"CRI","Costa Rica","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2010/cri_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
29144,188,"CRI","Costa Rica","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2010/cri_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
29145,188,"CRI","Costa Rica","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2010/cri_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
29146,188,"CRI","Costa Rica","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2010/cri_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
29147,188,"CRI","Costa Rica","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2010/cri_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
29148,188,"CRI","Costa Rica","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2010/cri_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
29149,188,"CRI","Costa Rica","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2011/cri_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
29150,188,"CRI","Costa Rica","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2011/cri_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
29151,188,"CRI","Costa Rica","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2011/cri_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
29152,188,"CRI","Costa Rica","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2011/cri_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
29153,188,"CRI","Costa Rica","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2011/cri_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
29154,188,"CRI","Costa Rica","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2011/cri_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
29155,188,"CRI","Costa Rica","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2011/cri_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
29156,188,"CRI","Costa Rica","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2011/cri_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
29157,188,"CRI","Costa Rica","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2012/cri_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
29158,188,"CRI","Costa Rica","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2012/cri_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
29159,188,"CRI","Costa Rica","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2012/cri_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
29160,188,"CRI","Costa Rica","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2012/cri_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
29161,188,"CRI","Costa Rica","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2012/cri_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
29162,188,"CRI","Costa Rica","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2012/cri_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
29163,188,"CRI","Costa Rica","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2012/cri_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
29164,188,"CRI","Costa Rica","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2012/cri_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
29165,188,"CRI","Costa Rica","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2013/cri_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
29166,188,"CRI","Costa Rica","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2013/cri_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
29167,188,"CRI","Costa Rica","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2013/cri_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
29168,188,"CRI","Costa Rica","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2013/cri_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
29169,188,"CRI","Costa Rica","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2013/cri_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
29170,188,"CRI","Costa Rica","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2013/cri_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
29171,188,"CRI","Costa Rica","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2013/cri_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
29172,188,"CRI","Costa Rica","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2013/cri_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
29173,188,"CRI","Costa Rica","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2014/cri_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
29174,188,"CRI","Costa Rica","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2014/cri_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
29175,188,"CRI","Costa Rica","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2014/cri_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
29176,188,"CRI","Costa Rica","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2014/cri_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
29177,188,"CRI","Costa Rica","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2014/cri_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
29178,188,"CRI","Costa Rica","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2014/cri_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
29179,188,"CRI","Costa Rica","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2014/cri_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
29180,188,"CRI","Costa Rica","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2014/cri_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
29181,188,"CRI","Costa Rica","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2015/cri_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
29182,188,"CRI","Costa Rica","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2015/cri_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
29183,188,"CRI","Costa Rica","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2015/cri_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
29184,188,"CRI","Costa Rica","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2015/cri_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
29185,188,"CRI","Costa Rica","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2015/cri_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
29186,188,"CRI","Costa Rica","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2015/cri_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
29187,188,"CRI","Costa Rica","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2015/cri_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
29188,188,"CRI","Costa Rica","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Annual/2015/cri_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
29189,191,"HRV","Croatia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2000/hrv_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
29190,191,"HRV","Croatia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2000/hrv_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
29191,191,"HRV","Croatia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2000/hrv_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
29192,191,"HRV","Croatia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2000/hrv_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
29193,191,"HRV","Croatia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2000/hrv_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
29194,191,"HRV","Croatia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2000/hrv_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
29195,191,"HRV","Croatia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2000/hrv_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
29196,191,"HRV","Croatia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2000/hrv_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
29197,191,"HRV","Croatia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2001/hrv_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
29198,191,"HRV","Croatia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2001/hrv_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
29199,191,"HRV","Croatia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2001/hrv_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
29200,191,"HRV","Croatia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2001/hrv_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
29201,191,"HRV","Croatia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2001/hrv_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
29202,191,"HRV","Croatia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2001/hrv_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
29203,191,"HRV","Croatia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2001/hrv_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
29204,191,"HRV","Croatia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2001/hrv_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
29205,191,"HRV","Croatia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2002/hrv_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
29206,191,"HRV","Croatia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2002/hrv_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
29207,191,"HRV","Croatia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2002/hrv_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
29208,191,"HRV","Croatia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2002/hrv_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
29209,191,"HRV","Croatia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2002/hrv_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
29210,191,"HRV","Croatia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2002/hrv_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
29211,191,"HRV","Croatia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2002/hrv_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
29212,191,"HRV","Croatia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2002/hrv_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
29213,191,"HRV","Croatia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2003/hrv_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
29214,191,"HRV","Croatia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2003/hrv_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
29215,191,"HRV","Croatia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2003/hrv_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
29216,191,"HRV","Croatia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2003/hrv_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
29217,191,"HRV","Croatia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2003/hrv_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
29218,191,"HRV","Croatia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2003/hrv_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
29219,191,"HRV","Croatia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2003/hrv_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
29220,191,"HRV","Croatia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2003/hrv_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
29221,191,"HRV","Croatia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2004/hrv_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
29222,191,"HRV","Croatia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2004/hrv_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
29223,191,"HRV","Croatia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2004/hrv_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
29224,191,"HRV","Croatia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2004/hrv_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
29225,191,"HRV","Croatia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2004/hrv_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
29226,191,"HRV","Croatia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2004/hrv_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
29227,191,"HRV","Croatia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2004/hrv_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
29228,191,"HRV","Croatia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2004/hrv_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
29229,191,"HRV","Croatia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2005/hrv_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
29230,191,"HRV","Croatia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2005/hrv_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
29231,191,"HRV","Croatia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2005/hrv_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
29232,191,"HRV","Croatia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2005/hrv_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
29233,191,"HRV","Croatia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2005/hrv_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
29234,191,"HRV","Croatia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2005/hrv_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
29235,191,"HRV","Croatia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2005/hrv_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
29236,191,"HRV","Croatia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2005/hrv_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
29237,191,"HRV","Croatia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2006/hrv_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
29238,191,"HRV","Croatia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2006/hrv_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
29239,191,"HRV","Croatia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2006/hrv_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
29240,191,"HRV","Croatia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2006/hrv_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
29241,191,"HRV","Croatia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2006/hrv_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
29242,191,"HRV","Croatia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2006/hrv_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
29243,191,"HRV","Croatia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2006/hrv_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
29244,191,"HRV","Croatia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2006/hrv_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
29245,191,"HRV","Croatia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2007/hrv_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
29246,191,"HRV","Croatia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2007/hrv_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
29247,191,"HRV","Croatia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2007/hrv_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
29248,191,"HRV","Croatia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2007/hrv_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
29249,191,"HRV","Croatia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2007/hrv_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
29250,191,"HRV","Croatia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2007/hrv_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
29251,191,"HRV","Croatia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2007/hrv_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
29252,191,"HRV","Croatia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2007/hrv_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
29253,191,"HRV","Croatia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2008/hrv_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
29254,191,"HRV","Croatia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2008/hrv_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
29255,191,"HRV","Croatia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2008/hrv_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
29256,191,"HRV","Croatia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2008/hrv_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
29257,191,"HRV","Croatia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2008/hrv_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
29258,191,"HRV","Croatia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2008/hrv_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
29259,191,"HRV","Croatia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2008/hrv_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
29260,191,"HRV","Croatia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2008/hrv_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
29261,191,"HRV","Croatia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2009/hrv_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
29262,191,"HRV","Croatia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2009/hrv_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
29263,191,"HRV","Croatia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2009/hrv_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
29264,191,"HRV","Croatia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2009/hrv_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
29265,191,"HRV","Croatia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2009/hrv_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
29266,191,"HRV","Croatia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2009/hrv_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
29267,191,"HRV","Croatia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2009/hrv_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
29268,191,"HRV","Croatia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2009/hrv_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
29269,191,"HRV","Croatia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2010/hrv_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
29270,191,"HRV","Croatia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2010/hrv_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
29271,191,"HRV","Croatia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2010/hrv_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
29272,191,"HRV","Croatia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2010/hrv_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
29273,191,"HRV","Croatia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2010/hrv_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
29274,191,"HRV","Croatia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2010/hrv_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
29275,191,"HRV","Croatia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2010/hrv_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
29276,191,"HRV","Croatia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2010/hrv_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
29277,191,"HRV","Croatia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2011/hrv_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
29278,191,"HRV","Croatia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2011/hrv_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
29279,191,"HRV","Croatia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2011/hrv_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
29280,191,"HRV","Croatia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2011/hrv_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
29281,191,"HRV","Croatia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2011/hrv_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
29282,191,"HRV","Croatia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2011/hrv_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
29283,191,"HRV","Croatia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2011/hrv_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
29284,191,"HRV","Croatia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2011/hrv_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
29285,191,"HRV","Croatia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2012/hrv_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
29286,191,"HRV","Croatia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2012/hrv_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
29287,191,"HRV","Croatia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2012/hrv_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
29288,191,"HRV","Croatia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2012/hrv_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
29289,191,"HRV","Croatia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2012/hrv_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
29290,191,"HRV","Croatia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2012/hrv_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
29291,191,"HRV","Croatia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2012/hrv_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
29292,191,"HRV","Croatia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2012/hrv_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
29293,191,"HRV","Croatia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2013/hrv_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
29294,191,"HRV","Croatia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2013/hrv_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
29295,191,"HRV","Croatia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2013/hrv_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
29296,191,"HRV","Croatia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2013/hrv_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
29297,191,"HRV","Croatia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2013/hrv_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
29298,191,"HRV","Croatia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2013/hrv_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
29299,191,"HRV","Croatia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2013/hrv_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
29300,191,"HRV","Croatia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2013/hrv_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
29301,191,"HRV","Croatia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2014/hrv_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
29302,191,"HRV","Croatia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2014/hrv_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
29303,191,"HRV","Croatia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2014/hrv_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
29304,191,"HRV","Croatia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2014/hrv_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
29305,191,"HRV","Croatia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2014/hrv_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
29306,191,"HRV","Croatia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2014/hrv_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
29307,191,"HRV","Croatia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2014/hrv_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
29308,191,"HRV","Croatia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2014/hrv_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
29309,191,"HRV","Croatia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2015/hrv_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
29310,191,"HRV","Croatia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2015/hrv_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
29311,191,"HRV","Croatia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2015/hrv_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
29312,191,"HRV","Croatia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2015/hrv_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
29313,191,"HRV","Croatia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2015/hrv_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
29314,191,"HRV","Croatia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2015/hrv_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
29315,191,"HRV","Croatia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2015/hrv_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
29316,191,"HRV","Croatia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Annual/2015/hrv_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
29317,192,"CUB","Cuba","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2000/cub_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
29318,192,"CUB","Cuba","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2000/cub_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
29319,192,"CUB","Cuba","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2000/cub_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
29320,192,"CUB","Cuba","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2000/cub_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
29321,192,"CUB","Cuba","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2000/cub_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
29322,192,"CUB","Cuba","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2000/cub_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
29323,192,"CUB","Cuba","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2000/cub_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
29324,192,"CUB","Cuba","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2000/cub_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
29325,192,"CUB","Cuba","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2001/cub_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
29326,192,"CUB","Cuba","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2001/cub_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
29327,192,"CUB","Cuba","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2001/cub_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
29328,192,"CUB","Cuba","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2001/cub_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
29329,192,"CUB","Cuba","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2001/cub_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
29330,192,"CUB","Cuba","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2001/cub_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
29331,192,"CUB","Cuba","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2001/cub_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
29332,192,"CUB","Cuba","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2001/cub_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
29333,192,"CUB","Cuba","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2002/cub_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
29334,192,"CUB","Cuba","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2002/cub_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
29335,192,"CUB","Cuba","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2002/cub_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
29336,192,"CUB","Cuba","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2002/cub_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
29337,192,"CUB","Cuba","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2002/cub_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
29338,192,"CUB","Cuba","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2002/cub_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
29339,192,"CUB","Cuba","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2002/cub_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
29340,192,"CUB","Cuba","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2002/cub_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
29341,192,"CUB","Cuba","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2003/cub_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
29342,192,"CUB","Cuba","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2003/cub_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
29343,192,"CUB","Cuba","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2003/cub_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
29344,192,"CUB","Cuba","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2003/cub_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
29345,192,"CUB","Cuba","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2003/cub_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
29346,192,"CUB","Cuba","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2003/cub_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
29347,192,"CUB","Cuba","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2003/cub_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
29348,192,"CUB","Cuba","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2003/cub_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
29349,192,"CUB","Cuba","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2004/cub_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
29350,192,"CUB","Cuba","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2004/cub_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
29351,192,"CUB","Cuba","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2004/cub_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
29352,192,"CUB","Cuba","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2004/cub_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
29353,192,"CUB","Cuba","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2004/cub_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
29354,192,"CUB","Cuba","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2004/cub_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
29355,192,"CUB","Cuba","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2004/cub_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
29356,192,"CUB","Cuba","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2004/cub_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
29357,192,"CUB","Cuba","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2005/cub_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
29358,192,"CUB","Cuba","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2005/cub_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
29359,192,"CUB","Cuba","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2005/cub_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
29360,192,"CUB","Cuba","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2005/cub_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
29361,192,"CUB","Cuba","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2005/cub_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
29362,192,"CUB","Cuba","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2005/cub_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
29363,192,"CUB","Cuba","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2005/cub_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
29364,192,"CUB","Cuba","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2005/cub_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
29365,192,"CUB","Cuba","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2006/cub_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
29366,192,"CUB","Cuba","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2006/cub_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
29367,192,"CUB","Cuba","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2006/cub_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
29368,192,"CUB","Cuba","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2006/cub_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
29369,192,"CUB","Cuba","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2006/cub_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
29370,192,"CUB","Cuba","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2006/cub_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
29371,192,"CUB","Cuba","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2006/cub_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
29372,192,"CUB","Cuba","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2006/cub_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
29373,192,"CUB","Cuba","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2007/cub_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
29374,192,"CUB","Cuba","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2007/cub_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
29375,192,"CUB","Cuba","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2007/cub_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
29376,192,"CUB","Cuba","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2007/cub_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
29377,192,"CUB","Cuba","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2007/cub_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
29378,192,"CUB","Cuba","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2007/cub_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
29379,192,"CUB","Cuba","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2007/cub_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
29380,192,"CUB","Cuba","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2007/cub_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
29381,192,"CUB","Cuba","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2008/cub_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
29382,192,"CUB","Cuba","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2008/cub_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
29383,192,"CUB","Cuba","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2008/cub_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
29384,192,"CUB","Cuba","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2008/cub_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
29385,192,"CUB","Cuba","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2008/cub_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
29386,192,"CUB","Cuba","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2008/cub_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
29387,192,"CUB","Cuba","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2008/cub_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
29388,192,"CUB","Cuba","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2008/cub_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
29389,192,"CUB","Cuba","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2009/cub_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
29390,192,"CUB","Cuba","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2009/cub_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
29391,192,"CUB","Cuba","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2009/cub_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
29392,192,"CUB","Cuba","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2009/cub_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
29393,192,"CUB","Cuba","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2009/cub_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
29394,192,"CUB","Cuba","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2009/cub_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
29395,192,"CUB","Cuba","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2009/cub_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
29396,192,"CUB","Cuba","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2009/cub_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
29397,192,"CUB","Cuba","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2010/cub_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
29398,192,"CUB","Cuba","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2010/cub_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
29399,192,"CUB","Cuba","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2010/cub_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
29400,192,"CUB","Cuba","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2010/cub_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
29401,192,"CUB","Cuba","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2010/cub_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
29402,192,"CUB","Cuba","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2010/cub_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
29403,192,"CUB","Cuba","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2010/cub_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
29404,192,"CUB","Cuba","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2010/cub_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
29405,192,"CUB","Cuba","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2011/cub_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
29406,192,"CUB","Cuba","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2011/cub_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
29407,192,"CUB","Cuba","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2011/cub_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
29408,192,"CUB","Cuba","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2011/cub_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
29409,192,"CUB","Cuba","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2011/cub_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
29410,192,"CUB","Cuba","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2011/cub_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
29411,192,"CUB","Cuba","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2011/cub_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
29412,192,"CUB","Cuba","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2011/cub_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
29413,192,"CUB","Cuba","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2012/cub_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
29414,192,"CUB","Cuba","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2012/cub_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
29415,192,"CUB","Cuba","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2012/cub_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
29416,192,"CUB","Cuba","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2012/cub_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
29417,192,"CUB","Cuba","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2012/cub_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
29418,192,"CUB","Cuba","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2012/cub_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
29419,192,"CUB","Cuba","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2012/cub_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
29420,192,"CUB","Cuba","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2012/cub_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
29421,192,"CUB","Cuba","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2013/cub_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
29422,192,"CUB","Cuba","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2013/cub_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
29423,192,"CUB","Cuba","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2013/cub_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
29424,192,"CUB","Cuba","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2013/cub_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
29425,192,"CUB","Cuba","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2013/cub_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
29426,192,"CUB","Cuba","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2013/cub_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
29427,192,"CUB","Cuba","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2013/cub_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
29428,192,"CUB","Cuba","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2013/cub_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
29429,192,"CUB","Cuba","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2014/cub_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
29430,192,"CUB","Cuba","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2014/cub_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
29431,192,"CUB","Cuba","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2014/cub_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
29432,192,"CUB","Cuba","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2014/cub_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
29433,192,"CUB","Cuba","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2014/cub_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
29434,192,"CUB","Cuba","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2014/cub_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
29435,192,"CUB","Cuba","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2014/cub_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
29436,192,"CUB","Cuba","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2014/cub_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
29437,192,"CUB","Cuba","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2015/cub_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
29438,192,"CUB","Cuba","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2015/cub_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
29439,192,"CUB","Cuba","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2015/cub_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
29440,192,"CUB","Cuba","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2015/cub_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
29441,192,"CUB","Cuba","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2015/cub_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
29442,192,"CUB","Cuba","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2015/cub_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
29443,192,"CUB","Cuba","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2015/cub_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
29444,192,"CUB","Cuba","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Annual/2015/cub_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
29445,196,"CYP","Cyprus","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2000/cyp_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
29446,196,"CYP","Cyprus","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2000/cyp_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
29447,196,"CYP","Cyprus","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2000/cyp_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
29448,196,"CYP","Cyprus","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2000/cyp_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
29449,196,"CYP","Cyprus","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2000/cyp_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
29450,196,"CYP","Cyprus","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2000/cyp_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
29451,196,"CYP","Cyprus","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2000/cyp_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
29452,196,"CYP","Cyprus","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2000/cyp_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
29453,196,"CYP","Cyprus","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2001/cyp_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
29454,196,"CYP","Cyprus","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2001/cyp_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
29455,196,"CYP","Cyprus","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2001/cyp_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
29456,196,"CYP","Cyprus","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2001/cyp_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
29457,196,"CYP","Cyprus","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2001/cyp_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
29458,196,"CYP","Cyprus","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2001/cyp_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
29459,196,"CYP","Cyprus","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2001/cyp_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
29460,196,"CYP","Cyprus","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2001/cyp_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
29461,196,"CYP","Cyprus","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2002/cyp_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
29462,196,"CYP","Cyprus","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2002/cyp_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
29463,196,"CYP","Cyprus","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2002/cyp_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
29464,196,"CYP","Cyprus","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2002/cyp_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
29465,196,"CYP","Cyprus","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2002/cyp_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
29466,196,"CYP","Cyprus","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2002/cyp_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
29467,196,"CYP","Cyprus","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2002/cyp_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
29468,196,"CYP","Cyprus","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2002/cyp_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
29469,196,"CYP","Cyprus","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2003/cyp_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
29470,196,"CYP","Cyprus","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2003/cyp_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
29471,196,"CYP","Cyprus","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2003/cyp_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
29472,196,"CYP","Cyprus","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2003/cyp_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
29473,196,"CYP","Cyprus","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2003/cyp_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
29474,196,"CYP","Cyprus","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2003/cyp_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
29475,196,"CYP","Cyprus","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2003/cyp_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
29476,196,"CYP","Cyprus","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2003/cyp_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
29477,196,"CYP","Cyprus","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2004/cyp_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
29478,196,"CYP","Cyprus","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2004/cyp_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
29479,196,"CYP","Cyprus","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2004/cyp_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
29480,196,"CYP","Cyprus","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2004/cyp_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
29481,196,"CYP","Cyprus","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2004/cyp_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
29482,196,"CYP","Cyprus","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2004/cyp_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
29483,196,"CYP","Cyprus","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2004/cyp_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
29484,196,"CYP","Cyprus","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2004/cyp_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
29485,196,"CYP","Cyprus","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2005/cyp_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
29486,196,"CYP","Cyprus","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2005/cyp_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
29487,196,"CYP","Cyprus","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2005/cyp_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
29488,196,"CYP","Cyprus","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2005/cyp_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
29489,196,"CYP","Cyprus","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2005/cyp_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
29490,196,"CYP","Cyprus","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2005/cyp_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
29491,196,"CYP","Cyprus","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2005/cyp_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
29492,196,"CYP","Cyprus","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2005/cyp_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
29493,196,"CYP","Cyprus","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2006/cyp_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
29494,196,"CYP","Cyprus","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2006/cyp_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
29495,196,"CYP","Cyprus","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2006/cyp_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
29496,196,"CYP","Cyprus","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2006/cyp_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
29497,196,"CYP","Cyprus","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2006/cyp_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
29498,196,"CYP","Cyprus","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2006/cyp_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
29499,196,"CYP","Cyprus","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2006/cyp_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
29500,196,"CYP","Cyprus","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2006/cyp_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
29501,196,"CYP","Cyprus","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2007/cyp_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
29502,196,"CYP","Cyprus","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2007/cyp_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
29503,196,"CYP","Cyprus","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2007/cyp_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
29504,196,"CYP","Cyprus","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2007/cyp_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
29505,196,"CYP","Cyprus","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2007/cyp_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
29506,196,"CYP","Cyprus","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2007/cyp_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
29507,196,"CYP","Cyprus","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2007/cyp_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
29508,196,"CYP","Cyprus","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2007/cyp_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
29509,196,"CYP","Cyprus","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2008/cyp_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
29510,196,"CYP","Cyprus","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2008/cyp_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
29511,196,"CYP","Cyprus","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2008/cyp_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
29512,196,"CYP","Cyprus","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2008/cyp_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
29513,196,"CYP","Cyprus","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2008/cyp_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
29514,196,"CYP","Cyprus","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2008/cyp_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
29515,196,"CYP","Cyprus","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2008/cyp_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
29516,196,"CYP","Cyprus","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2008/cyp_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
29517,196,"CYP","Cyprus","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2009/cyp_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
29518,196,"CYP","Cyprus","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2009/cyp_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
29519,196,"CYP","Cyprus","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2009/cyp_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
29520,196,"CYP","Cyprus","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2009/cyp_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
29521,196,"CYP","Cyprus","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2009/cyp_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
29522,196,"CYP","Cyprus","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2009/cyp_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
29523,196,"CYP","Cyprus","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2009/cyp_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
29524,196,"CYP","Cyprus","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2009/cyp_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
29525,196,"CYP","Cyprus","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2010/cyp_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
29526,196,"CYP","Cyprus","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2010/cyp_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
29527,196,"CYP","Cyprus","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2010/cyp_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
29528,196,"CYP","Cyprus","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2010/cyp_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
29529,196,"CYP","Cyprus","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2010/cyp_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
29530,196,"CYP","Cyprus","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2010/cyp_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
29531,196,"CYP","Cyprus","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2010/cyp_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
29532,196,"CYP","Cyprus","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2010/cyp_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
29533,196,"CYP","Cyprus","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2011/cyp_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
29534,196,"CYP","Cyprus","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2011/cyp_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
29535,196,"CYP","Cyprus","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2011/cyp_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
29536,196,"CYP","Cyprus","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2011/cyp_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
29537,196,"CYP","Cyprus","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2011/cyp_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
29538,196,"CYP","Cyprus","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2011/cyp_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
29539,196,"CYP","Cyprus","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2011/cyp_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
29540,196,"CYP","Cyprus","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2011/cyp_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
29541,196,"CYP","Cyprus","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2012/cyp_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
29542,196,"CYP","Cyprus","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2012/cyp_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
29543,196,"CYP","Cyprus","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2012/cyp_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
29544,196,"CYP","Cyprus","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2012/cyp_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
29545,196,"CYP","Cyprus","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2012/cyp_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
29546,196,"CYP","Cyprus","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2012/cyp_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
29547,196,"CYP","Cyprus","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2012/cyp_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
29548,196,"CYP","Cyprus","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2012/cyp_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
29549,196,"CYP","Cyprus","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2013/cyp_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
29550,196,"CYP","Cyprus","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2013/cyp_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
29551,196,"CYP","Cyprus","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2013/cyp_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
29552,196,"CYP","Cyprus","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2013/cyp_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
29553,196,"CYP","Cyprus","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2013/cyp_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
29554,196,"CYP","Cyprus","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2013/cyp_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
29555,196,"CYP","Cyprus","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2013/cyp_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
29556,196,"CYP","Cyprus","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2013/cyp_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
29557,196,"CYP","Cyprus","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2014/cyp_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
29558,196,"CYP","Cyprus","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2014/cyp_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
29559,196,"CYP","Cyprus","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2014/cyp_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
29560,196,"CYP","Cyprus","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2014/cyp_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
29561,196,"CYP","Cyprus","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2014/cyp_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
29562,196,"CYP","Cyprus","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2014/cyp_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
29563,196,"CYP","Cyprus","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2014/cyp_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
29564,196,"CYP","Cyprus","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2014/cyp_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
29565,196,"CYP","Cyprus","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2015/cyp_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
29566,196,"CYP","Cyprus","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2015/cyp_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
29567,196,"CYP","Cyprus","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2015/cyp_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
29568,196,"CYP","Cyprus","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2015/cyp_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
29569,196,"CYP","Cyprus","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2015/cyp_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
29570,196,"CYP","Cyprus","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2015/cyp_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
29571,196,"CYP","Cyprus","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2015/cyp_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
29572,196,"CYP","Cyprus","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Annual/2015/cyp_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
29573,203,"CZE","Czech Republic","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2000/cze_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
29574,203,"CZE","Czech Republic","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2000/cze_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
29575,203,"CZE","Czech Republic","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2000/cze_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
29576,203,"CZE","Czech Republic","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2000/cze_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
29577,203,"CZE","Czech Republic","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2000/cze_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
29578,203,"CZE","Czech Republic","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2000/cze_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
29579,203,"CZE","Czech Republic","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2000/cze_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
29580,203,"CZE","Czech Republic","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2000/cze_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
29581,203,"CZE","Czech Republic","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2001/cze_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
29582,203,"CZE","Czech Republic","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2001/cze_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
29583,203,"CZE","Czech Republic","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2001/cze_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
29584,203,"CZE","Czech Republic","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2001/cze_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
29585,203,"CZE","Czech Republic","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2001/cze_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
29586,203,"CZE","Czech Republic","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2001/cze_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
29587,203,"CZE","Czech Republic","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2001/cze_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
29588,203,"CZE","Czech Republic","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2001/cze_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
29589,203,"CZE","Czech Republic","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2002/cze_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
29590,203,"CZE","Czech Republic","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2002/cze_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
29591,203,"CZE","Czech Republic","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2002/cze_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
29592,203,"CZE","Czech Republic","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2002/cze_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
29593,203,"CZE","Czech Republic","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2002/cze_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
29594,203,"CZE","Czech Republic","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2002/cze_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
29595,203,"CZE","Czech Republic","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2002/cze_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
29596,203,"CZE","Czech Republic","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2002/cze_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
29597,203,"CZE","Czech Republic","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2003/cze_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
29598,203,"CZE","Czech Republic","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2003/cze_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
29599,203,"CZE","Czech Republic","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2003/cze_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
29600,203,"CZE","Czech Republic","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2003/cze_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
29601,203,"CZE","Czech Republic","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2003/cze_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
29602,203,"CZE","Czech Republic","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2003/cze_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
29603,203,"CZE","Czech Republic","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2003/cze_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
29604,203,"CZE","Czech Republic","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2003/cze_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
29605,203,"CZE","Czech Republic","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2004/cze_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
29606,203,"CZE","Czech Republic","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2004/cze_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
29607,203,"CZE","Czech Republic","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2004/cze_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
29608,203,"CZE","Czech Republic","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2004/cze_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
29609,203,"CZE","Czech Republic","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2004/cze_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
29610,203,"CZE","Czech Republic","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2004/cze_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
29611,203,"CZE","Czech Republic","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2004/cze_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
29612,203,"CZE","Czech Republic","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2004/cze_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
29613,203,"CZE","Czech Republic","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2005/cze_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
29614,203,"CZE","Czech Republic","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2005/cze_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
29615,203,"CZE","Czech Republic","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2005/cze_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
29616,203,"CZE","Czech Republic","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2005/cze_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
29617,203,"CZE","Czech Republic","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2005/cze_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
29618,203,"CZE","Czech Republic","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2005/cze_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
29619,203,"CZE","Czech Republic","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2005/cze_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
29620,203,"CZE","Czech Republic","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2005/cze_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
29621,203,"CZE","Czech Republic","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2006/cze_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
29622,203,"CZE","Czech Republic","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2006/cze_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
29623,203,"CZE","Czech Republic","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2006/cze_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
29624,203,"CZE","Czech Republic","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2006/cze_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
29625,203,"CZE","Czech Republic","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2006/cze_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
29626,203,"CZE","Czech Republic","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2006/cze_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
29627,203,"CZE","Czech Republic","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2006/cze_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
29628,203,"CZE","Czech Republic","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2006/cze_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
29629,203,"CZE","Czech Republic","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2007/cze_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
29630,203,"CZE","Czech Republic","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2007/cze_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
29631,203,"CZE","Czech Republic","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2007/cze_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
29632,203,"CZE","Czech Republic","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2007/cze_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
29633,203,"CZE","Czech Republic","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2007/cze_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
29634,203,"CZE","Czech Republic","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2007/cze_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
29635,203,"CZE","Czech Republic","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2007/cze_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
29636,203,"CZE","Czech Republic","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2007/cze_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
29637,203,"CZE","Czech Republic","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2008/cze_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
29638,203,"CZE","Czech Republic","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2008/cze_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
29639,203,"CZE","Czech Republic","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2008/cze_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
29640,203,"CZE","Czech Republic","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2008/cze_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
29641,203,"CZE","Czech Republic","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2008/cze_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
29642,203,"CZE","Czech Republic","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2008/cze_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
29643,203,"CZE","Czech Republic","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2008/cze_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
29644,203,"CZE","Czech Republic","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2008/cze_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
29645,203,"CZE","Czech Republic","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2009/cze_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
29646,203,"CZE","Czech Republic","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2009/cze_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
29647,203,"CZE","Czech Republic","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2009/cze_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
29648,203,"CZE","Czech Republic","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2009/cze_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
29649,203,"CZE","Czech Republic","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2009/cze_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
29650,203,"CZE","Czech Republic","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2009/cze_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
29651,203,"CZE","Czech Republic","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2009/cze_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
29652,203,"CZE","Czech Republic","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2009/cze_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
29653,203,"CZE","Czech Republic","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2010/cze_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
29654,203,"CZE","Czech Republic","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2010/cze_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
29655,203,"CZE","Czech Republic","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2010/cze_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
29656,203,"CZE","Czech Republic","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2010/cze_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
29657,203,"CZE","Czech Republic","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2010/cze_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
29658,203,"CZE","Czech Republic","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2010/cze_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
29659,203,"CZE","Czech Republic","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2010/cze_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
29660,203,"CZE","Czech Republic","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2010/cze_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
29661,203,"CZE","Czech Republic","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2011/cze_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
29662,203,"CZE","Czech Republic","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2011/cze_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
29663,203,"CZE","Czech Republic","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2011/cze_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
29664,203,"CZE","Czech Republic","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2011/cze_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
29665,203,"CZE","Czech Republic","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2011/cze_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
29666,203,"CZE","Czech Republic","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2011/cze_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
29667,203,"CZE","Czech Republic","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2011/cze_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
29668,203,"CZE","Czech Republic","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2011/cze_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
29669,203,"CZE","Czech Republic","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2012/cze_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
29670,203,"CZE","Czech Republic","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2012/cze_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
29671,203,"CZE","Czech Republic","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2012/cze_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
29672,203,"CZE","Czech Republic","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2012/cze_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
29673,203,"CZE","Czech Republic","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2012/cze_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
29674,203,"CZE","Czech Republic","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2012/cze_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
29675,203,"CZE","Czech Republic","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2012/cze_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
29676,203,"CZE","Czech Republic","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2012/cze_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
29677,203,"CZE","Czech Republic","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2013/cze_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
29678,203,"CZE","Czech Republic","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2013/cze_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
29679,203,"CZE","Czech Republic","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2013/cze_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
29680,203,"CZE","Czech Republic","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2013/cze_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
29681,203,"CZE","Czech Republic","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2013/cze_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
29682,203,"CZE","Czech Republic","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2013/cze_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
29683,203,"CZE","Czech Republic","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2013/cze_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
29684,203,"CZE","Czech Republic","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2013/cze_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
29685,203,"CZE","Czech Republic","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2014/cze_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
29686,203,"CZE","Czech Republic","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2014/cze_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
29687,203,"CZE","Czech Republic","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2014/cze_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
29688,203,"CZE","Czech Republic","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2014/cze_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
29689,203,"CZE","Czech Republic","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2014/cze_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
29690,203,"CZE","Czech Republic","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2014/cze_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
29691,203,"CZE","Czech Republic","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2014/cze_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
29692,203,"CZE","Czech Republic","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2014/cze_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
29693,203,"CZE","Czech Republic","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2015/cze_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
29694,203,"CZE","Czech Republic","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2015/cze_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
29695,203,"CZE","Czech Republic","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2015/cze_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
29696,203,"CZE","Czech Republic","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2015/cze_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
29697,203,"CZE","Czech Republic","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2015/cze_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
29698,203,"CZE","Czech Republic","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2015/cze_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
29699,203,"CZE","Czech Republic","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2015/cze_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
29700,203,"CZE","Czech Republic","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Annual/2015/cze_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
29701,204,"BEN","Benin","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2000/ben_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
29702,204,"BEN","Benin","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2000/ben_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
29703,204,"BEN","Benin","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2000/ben_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
29704,204,"BEN","Benin","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2000/ben_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
29705,204,"BEN","Benin","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2000/ben_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
29706,204,"BEN","Benin","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2000/ben_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
29707,204,"BEN","Benin","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2000/ben_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
29708,204,"BEN","Benin","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2000/ben_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
29709,204,"BEN","Benin","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2001/ben_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
29710,204,"BEN","Benin","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2001/ben_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
29711,204,"BEN","Benin","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2001/ben_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
29712,204,"BEN","Benin","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2001/ben_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
29713,204,"BEN","Benin","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2001/ben_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
29714,204,"BEN","Benin","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2001/ben_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
29715,204,"BEN","Benin","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2001/ben_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
29716,204,"BEN","Benin","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2001/ben_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
29717,204,"BEN","Benin","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2002/ben_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
29718,204,"BEN","Benin","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2002/ben_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
29719,204,"BEN","Benin","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2002/ben_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
29720,204,"BEN","Benin","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2002/ben_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
29721,204,"BEN","Benin","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2002/ben_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
29722,204,"BEN","Benin","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2002/ben_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
29723,204,"BEN","Benin","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2002/ben_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
29724,204,"BEN","Benin","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2002/ben_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
29725,204,"BEN","Benin","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2003/ben_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
29726,204,"BEN","Benin","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2003/ben_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
29727,204,"BEN","Benin","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2003/ben_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
29728,204,"BEN","Benin","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2003/ben_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
29729,204,"BEN","Benin","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2003/ben_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
29730,204,"BEN","Benin","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2003/ben_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
29731,204,"BEN","Benin","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2003/ben_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
29732,204,"BEN","Benin","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2003/ben_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
29733,204,"BEN","Benin","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2004/ben_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
29734,204,"BEN","Benin","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2004/ben_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
29735,204,"BEN","Benin","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2004/ben_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
29736,204,"BEN","Benin","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2004/ben_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
29737,204,"BEN","Benin","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2004/ben_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
29738,204,"BEN","Benin","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2004/ben_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
29739,204,"BEN","Benin","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2004/ben_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
29740,204,"BEN","Benin","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2004/ben_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
29741,204,"BEN","Benin","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2005/ben_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
29742,204,"BEN","Benin","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2005/ben_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
29743,204,"BEN","Benin","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2005/ben_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
29744,204,"BEN","Benin","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2005/ben_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
29745,204,"BEN","Benin","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2005/ben_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
29746,204,"BEN","Benin","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2005/ben_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
29747,204,"BEN","Benin","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2005/ben_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
29748,204,"BEN","Benin","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2005/ben_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
29749,204,"BEN","Benin","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2006/ben_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
29750,204,"BEN","Benin","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2006/ben_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
29751,204,"BEN","Benin","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2006/ben_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
29752,204,"BEN","Benin","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2006/ben_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
29753,204,"BEN","Benin","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2006/ben_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
29754,204,"BEN","Benin","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2006/ben_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
29755,204,"BEN","Benin","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2006/ben_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
29756,204,"BEN","Benin","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2006/ben_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
29757,204,"BEN","Benin","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2007/ben_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
29758,204,"BEN","Benin","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2007/ben_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
29759,204,"BEN","Benin","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2007/ben_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
29760,204,"BEN","Benin","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2007/ben_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
29761,204,"BEN","Benin","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2007/ben_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
29762,204,"BEN","Benin","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2007/ben_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
29763,204,"BEN","Benin","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2007/ben_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
29764,204,"BEN","Benin","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2007/ben_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
29765,204,"BEN","Benin","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2008/ben_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
29766,204,"BEN","Benin","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2008/ben_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
29767,204,"BEN","Benin","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2008/ben_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
29768,204,"BEN","Benin","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2008/ben_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
29769,204,"BEN","Benin","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2008/ben_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
29770,204,"BEN","Benin","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2008/ben_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
29771,204,"BEN","Benin","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2008/ben_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
29772,204,"BEN","Benin","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2008/ben_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
29773,204,"BEN","Benin","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2009/ben_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
29774,204,"BEN","Benin","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2009/ben_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
29775,204,"BEN","Benin","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2009/ben_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
29776,204,"BEN","Benin","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2009/ben_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
29777,204,"BEN","Benin","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2009/ben_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
29778,204,"BEN","Benin","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2009/ben_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
29779,204,"BEN","Benin","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2009/ben_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
29780,204,"BEN","Benin","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2009/ben_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
29781,204,"BEN","Benin","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2010/ben_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
29782,204,"BEN","Benin","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2010/ben_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
29783,204,"BEN","Benin","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2010/ben_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
29784,204,"BEN","Benin","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2010/ben_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
29785,204,"BEN","Benin","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2010/ben_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
29786,204,"BEN","Benin","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2010/ben_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
29787,204,"BEN","Benin","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2010/ben_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
29788,204,"BEN","Benin","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2010/ben_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
29789,204,"BEN","Benin","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2011/ben_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
29790,204,"BEN","Benin","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2011/ben_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
29791,204,"BEN","Benin","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2011/ben_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
29792,204,"BEN","Benin","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2011/ben_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
29793,204,"BEN","Benin","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2011/ben_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
29794,204,"BEN","Benin","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2011/ben_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
29795,204,"BEN","Benin","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2011/ben_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
29796,204,"BEN","Benin","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2011/ben_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
29797,204,"BEN","Benin","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2012/ben_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
29798,204,"BEN","Benin","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2012/ben_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
29799,204,"BEN","Benin","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2012/ben_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
29800,204,"BEN","Benin","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2012/ben_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
29801,204,"BEN","Benin","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2012/ben_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
29802,204,"BEN","Benin","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2012/ben_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
29803,204,"BEN","Benin","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2012/ben_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
29804,204,"BEN","Benin","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2012/ben_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
29805,204,"BEN","Benin","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2013/ben_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
29806,204,"BEN","Benin","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2013/ben_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
29807,204,"BEN","Benin","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2013/ben_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
29808,204,"BEN","Benin","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2013/ben_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
29809,204,"BEN","Benin","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2013/ben_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
29810,204,"BEN","Benin","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2013/ben_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
29811,204,"BEN","Benin","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2013/ben_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
29812,204,"BEN","Benin","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2013/ben_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
29813,204,"BEN","Benin","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2014/ben_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
29814,204,"BEN","Benin","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2014/ben_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
29815,204,"BEN","Benin","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2014/ben_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
29816,204,"BEN","Benin","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2014/ben_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
29817,204,"BEN","Benin","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2014/ben_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
29818,204,"BEN","Benin","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2014/ben_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
29819,204,"BEN","Benin","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2014/ben_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
29820,204,"BEN","Benin","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2014/ben_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
29821,204,"BEN","Benin","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2015/ben_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
29822,204,"BEN","Benin","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2015/ben_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
29823,204,"BEN","Benin","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2015/ben_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
29824,204,"BEN","Benin","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2015/ben_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
29825,204,"BEN","Benin","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2015/ben_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
29826,204,"BEN","Benin","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2015/ben_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
29827,204,"BEN","Benin","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2015/ben_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
29828,204,"BEN","Benin","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Annual/2015/ben_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
29829,208,"DNK","Denmark","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2000/dnk_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
29830,208,"DNK","Denmark","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2000/dnk_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
29831,208,"DNK","Denmark","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2000/dnk_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
29832,208,"DNK","Denmark","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2000/dnk_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
29833,208,"DNK","Denmark","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2000/dnk_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
29834,208,"DNK","Denmark","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2000/dnk_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
29835,208,"DNK","Denmark","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2000/dnk_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
29836,208,"DNK","Denmark","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2000/dnk_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
29837,208,"DNK","Denmark","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2001/dnk_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
29838,208,"DNK","Denmark","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2001/dnk_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
29839,208,"DNK","Denmark","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2001/dnk_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
29840,208,"DNK","Denmark","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2001/dnk_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
29841,208,"DNK","Denmark","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2001/dnk_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
29842,208,"DNK","Denmark","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2001/dnk_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
29843,208,"DNK","Denmark","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2001/dnk_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
29844,208,"DNK","Denmark","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2001/dnk_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
29845,208,"DNK","Denmark","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2002/dnk_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
29846,208,"DNK","Denmark","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2002/dnk_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
29847,208,"DNK","Denmark","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2002/dnk_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
29848,208,"DNK","Denmark","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2002/dnk_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
29849,208,"DNK","Denmark","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2002/dnk_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
29850,208,"DNK","Denmark","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2002/dnk_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
29851,208,"DNK","Denmark","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2002/dnk_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
29852,208,"DNK","Denmark","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2002/dnk_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
29853,208,"DNK","Denmark","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2003/dnk_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
29854,208,"DNK","Denmark","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2003/dnk_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
29855,208,"DNK","Denmark","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2003/dnk_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
29856,208,"DNK","Denmark","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2003/dnk_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
29857,208,"DNK","Denmark","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2003/dnk_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
29858,208,"DNK","Denmark","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2003/dnk_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
29859,208,"DNK","Denmark","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2003/dnk_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
29860,208,"DNK","Denmark","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2003/dnk_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
29861,208,"DNK","Denmark","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2004/dnk_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
29862,208,"DNK","Denmark","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2004/dnk_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
29863,208,"DNK","Denmark","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2004/dnk_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
29864,208,"DNK","Denmark","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2004/dnk_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
29865,208,"DNK","Denmark","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2004/dnk_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
29866,208,"DNK","Denmark","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2004/dnk_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
29867,208,"DNK","Denmark","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2004/dnk_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
29868,208,"DNK","Denmark","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2004/dnk_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
29869,208,"DNK","Denmark","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2005/dnk_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
29870,208,"DNK","Denmark","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2005/dnk_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
29871,208,"DNK","Denmark","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2005/dnk_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
29872,208,"DNK","Denmark","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2005/dnk_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
29873,208,"DNK","Denmark","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2005/dnk_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
29874,208,"DNK","Denmark","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2005/dnk_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
29875,208,"DNK","Denmark","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2005/dnk_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
29876,208,"DNK","Denmark","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2005/dnk_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
29877,208,"DNK","Denmark","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2006/dnk_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
29878,208,"DNK","Denmark","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2006/dnk_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
29879,208,"DNK","Denmark","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2006/dnk_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
29880,208,"DNK","Denmark","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2006/dnk_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
29881,208,"DNK","Denmark","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2006/dnk_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
29882,208,"DNK","Denmark","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2006/dnk_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
29883,208,"DNK","Denmark","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2006/dnk_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
29884,208,"DNK","Denmark","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2006/dnk_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
29885,208,"DNK","Denmark","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2007/dnk_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
29886,208,"DNK","Denmark","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2007/dnk_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
29887,208,"DNK","Denmark","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2007/dnk_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
29888,208,"DNK","Denmark","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2007/dnk_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
29889,208,"DNK","Denmark","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2007/dnk_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
29890,208,"DNK","Denmark","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2007/dnk_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
29891,208,"DNK","Denmark","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2007/dnk_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
29892,208,"DNK","Denmark","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2007/dnk_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
29893,208,"DNK","Denmark","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2008/dnk_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
29894,208,"DNK","Denmark","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2008/dnk_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
29895,208,"DNK","Denmark","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2008/dnk_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
29896,208,"DNK","Denmark","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2008/dnk_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
29897,208,"DNK","Denmark","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2008/dnk_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
29898,208,"DNK","Denmark","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2008/dnk_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
29899,208,"DNK","Denmark","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2008/dnk_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
29900,208,"DNK","Denmark","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2008/dnk_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
29901,208,"DNK","Denmark","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2009/dnk_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
29902,208,"DNK","Denmark","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2009/dnk_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
29903,208,"DNK","Denmark","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2009/dnk_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
29904,208,"DNK","Denmark","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2009/dnk_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
29905,208,"DNK","Denmark","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2009/dnk_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
29906,208,"DNK","Denmark","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2009/dnk_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
29907,208,"DNK","Denmark","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2009/dnk_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
29908,208,"DNK","Denmark","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2009/dnk_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
29909,208,"DNK","Denmark","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2010/dnk_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
29910,208,"DNK","Denmark","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2010/dnk_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
29911,208,"DNK","Denmark","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2010/dnk_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
29912,208,"DNK","Denmark","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2010/dnk_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
29913,208,"DNK","Denmark","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2010/dnk_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
29914,208,"DNK","Denmark","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2010/dnk_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
29915,208,"DNK","Denmark","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2010/dnk_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
29916,208,"DNK","Denmark","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2010/dnk_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
29917,208,"DNK","Denmark","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2011/dnk_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
29918,208,"DNK","Denmark","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2011/dnk_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
29919,208,"DNK","Denmark","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2011/dnk_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
29920,208,"DNK","Denmark","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2011/dnk_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
29921,208,"DNK","Denmark","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2011/dnk_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
29922,208,"DNK","Denmark","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2011/dnk_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
29923,208,"DNK","Denmark","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2011/dnk_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
29924,208,"DNK","Denmark","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2011/dnk_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
29925,208,"DNK","Denmark","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2012/dnk_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
29926,208,"DNK","Denmark","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2012/dnk_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
29927,208,"DNK","Denmark","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2012/dnk_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
29928,208,"DNK","Denmark","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2012/dnk_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
29929,208,"DNK","Denmark","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2012/dnk_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
29930,208,"DNK","Denmark","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2012/dnk_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
29931,208,"DNK","Denmark","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2012/dnk_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
29932,208,"DNK","Denmark","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2012/dnk_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
29933,208,"DNK","Denmark","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2013/dnk_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
29934,208,"DNK","Denmark","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2013/dnk_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
29935,208,"DNK","Denmark","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2013/dnk_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
29936,208,"DNK","Denmark","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2013/dnk_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
29937,208,"DNK","Denmark","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2013/dnk_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
29938,208,"DNK","Denmark","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2013/dnk_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
29939,208,"DNK","Denmark","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2013/dnk_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
29940,208,"DNK","Denmark","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2013/dnk_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
29941,208,"DNK","Denmark","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2014/dnk_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
29942,208,"DNK","Denmark","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2014/dnk_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
29943,208,"DNK","Denmark","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2014/dnk_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
29944,208,"DNK","Denmark","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2014/dnk_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
29945,208,"DNK","Denmark","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2014/dnk_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
29946,208,"DNK","Denmark","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2014/dnk_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
29947,208,"DNK","Denmark","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2014/dnk_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
29948,208,"DNK","Denmark","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2014/dnk_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
29949,208,"DNK","Denmark","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2015/dnk_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
29950,208,"DNK","Denmark","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2015/dnk_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
29951,208,"DNK","Denmark","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2015/dnk_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
29952,208,"DNK","Denmark","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2015/dnk_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
29953,208,"DNK","Denmark","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2015/dnk_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
29954,208,"DNK","Denmark","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2015/dnk_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
29955,208,"DNK","Denmark","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2015/dnk_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
29956,208,"DNK","Denmark","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Annual/2015/dnk_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
29957,212,"DMA","Dominica","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2000/dma_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
29958,212,"DMA","Dominica","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2000/dma_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
29959,212,"DMA","Dominica","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2000/dma_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
29960,212,"DMA","Dominica","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2000/dma_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
29961,212,"DMA","Dominica","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2000/dma_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
29962,212,"DMA","Dominica","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2000/dma_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
29963,212,"DMA","Dominica","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2000/dma_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
29964,212,"DMA","Dominica","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2000/dma_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
29965,212,"DMA","Dominica","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2001/dma_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
29966,212,"DMA","Dominica","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2001/dma_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
29967,212,"DMA","Dominica","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2001/dma_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
29968,212,"DMA","Dominica","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2001/dma_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
29969,212,"DMA","Dominica","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2001/dma_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
29970,212,"DMA","Dominica","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2001/dma_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
29971,212,"DMA","Dominica","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2001/dma_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
29972,212,"DMA","Dominica","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2001/dma_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
29973,212,"DMA","Dominica","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2002/dma_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
29974,212,"DMA","Dominica","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2002/dma_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
29975,212,"DMA","Dominica","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2002/dma_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
29976,212,"DMA","Dominica","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2002/dma_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
29977,212,"DMA","Dominica","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2002/dma_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
29978,212,"DMA","Dominica","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2002/dma_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
29979,212,"DMA","Dominica","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2002/dma_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
29980,212,"DMA","Dominica","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2002/dma_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
29981,212,"DMA","Dominica","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2003/dma_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
29982,212,"DMA","Dominica","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2003/dma_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
29983,212,"DMA","Dominica","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2003/dma_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
29984,212,"DMA","Dominica","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2003/dma_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
29985,212,"DMA","Dominica","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2003/dma_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
29986,212,"DMA","Dominica","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2003/dma_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
29987,212,"DMA","Dominica","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2003/dma_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
29988,212,"DMA","Dominica","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2003/dma_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
29989,212,"DMA","Dominica","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2004/dma_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
29990,212,"DMA","Dominica","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2004/dma_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
29991,212,"DMA","Dominica","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2004/dma_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
29992,212,"DMA","Dominica","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2004/dma_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
29993,212,"DMA","Dominica","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2004/dma_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
29994,212,"DMA","Dominica","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2004/dma_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
29995,212,"DMA","Dominica","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2004/dma_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
29996,212,"DMA","Dominica","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2004/dma_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
29997,212,"DMA","Dominica","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2005/dma_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
29998,212,"DMA","Dominica","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2005/dma_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
29999,212,"DMA","Dominica","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2005/dma_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
30000,212,"DMA","Dominica","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2005/dma_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
30001,212,"DMA","Dominica","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2005/dma_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
30002,212,"DMA","Dominica","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2005/dma_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
30003,212,"DMA","Dominica","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2005/dma_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
30004,212,"DMA","Dominica","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2005/dma_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
30005,212,"DMA","Dominica","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2006/dma_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
30006,212,"DMA","Dominica","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2006/dma_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
30007,212,"DMA","Dominica","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2006/dma_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
30008,212,"DMA","Dominica","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2006/dma_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
30009,212,"DMA","Dominica","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2006/dma_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
30010,212,"DMA","Dominica","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2006/dma_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
30011,212,"DMA","Dominica","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2006/dma_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
30012,212,"DMA","Dominica","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2006/dma_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
30013,212,"DMA","Dominica","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2007/dma_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
30014,212,"DMA","Dominica","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2007/dma_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
30015,212,"DMA","Dominica","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2007/dma_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
30016,212,"DMA","Dominica","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2007/dma_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
30017,212,"DMA","Dominica","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2007/dma_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
30018,212,"DMA","Dominica","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2007/dma_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
30019,212,"DMA","Dominica","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2007/dma_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
30020,212,"DMA","Dominica","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2007/dma_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
30021,212,"DMA","Dominica","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2008/dma_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
30022,212,"DMA","Dominica","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2008/dma_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
30023,212,"DMA","Dominica","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2008/dma_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
30024,212,"DMA","Dominica","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2008/dma_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
30025,212,"DMA","Dominica","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2008/dma_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
30026,212,"DMA","Dominica","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2008/dma_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
30027,212,"DMA","Dominica","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2008/dma_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
30028,212,"DMA","Dominica","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2008/dma_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
30029,212,"DMA","Dominica","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2009/dma_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
30030,212,"DMA","Dominica","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2009/dma_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
30031,212,"DMA","Dominica","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2009/dma_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
30032,212,"DMA","Dominica","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2009/dma_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
30033,212,"DMA","Dominica","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2009/dma_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
30034,212,"DMA","Dominica","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2009/dma_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
30035,212,"DMA","Dominica","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2009/dma_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
30036,212,"DMA","Dominica","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2009/dma_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
30037,212,"DMA","Dominica","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2010/dma_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
30038,212,"DMA","Dominica","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2010/dma_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
30039,212,"DMA","Dominica","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2010/dma_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
30040,212,"DMA","Dominica","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2010/dma_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
30041,212,"DMA","Dominica","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2010/dma_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
30042,212,"DMA","Dominica","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2010/dma_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
30043,212,"DMA","Dominica","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2010/dma_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
30044,212,"DMA","Dominica","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2010/dma_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
30045,212,"DMA","Dominica","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2011/dma_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
30046,212,"DMA","Dominica","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2011/dma_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
30047,212,"DMA","Dominica","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2011/dma_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
30048,212,"DMA","Dominica","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2011/dma_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
30049,212,"DMA","Dominica","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2011/dma_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
30050,212,"DMA","Dominica","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2011/dma_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
30051,212,"DMA","Dominica","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2011/dma_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
30052,212,"DMA","Dominica","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2011/dma_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
30053,212,"DMA","Dominica","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2012/dma_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
30054,212,"DMA","Dominica","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2012/dma_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
30055,212,"DMA","Dominica","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2012/dma_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
30056,212,"DMA","Dominica","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2012/dma_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
30057,212,"DMA","Dominica","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2012/dma_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
30058,212,"DMA","Dominica","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2012/dma_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
30059,212,"DMA","Dominica","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2012/dma_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
30060,212,"DMA","Dominica","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2012/dma_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
30061,212,"DMA","Dominica","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2013/dma_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
30062,212,"DMA","Dominica","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2013/dma_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
30063,212,"DMA","Dominica","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2013/dma_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
30064,212,"DMA","Dominica","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2013/dma_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
30065,212,"DMA","Dominica","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2013/dma_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
30066,212,"DMA","Dominica","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2013/dma_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
30067,212,"DMA","Dominica","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2013/dma_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
30068,212,"DMA","Dominica","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2013/dma_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
30069,212,"DMA","Dominica","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2014/dma_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
30070,212,"DMA","Dominica","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2014/dma_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
30071,212,"DMA","Dominica","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2014/dma_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
30072,212,"DMA","Dominica","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2014/dma_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
30073,212,"DMA","Dominica","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2014/dma_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
30074,212,"DMA","Dominica","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2014/dma_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
30075,212,"DMA","Dominica","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2014/dma_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
30076,212,"DMA","Dominica","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2014/dma_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
30077,212,"DMA","Dominica","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2015/dma_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
30078,212,"DMA","Dominica","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2015/dma_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
30079,212,"DMA","Dominica","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2015/dma_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
30080,212,"DMA","Dominica","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2015/dma_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
30081,212,"DMA","Dominica","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2015/dma_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
30082,212,"DMA","Dominica","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2015/dma_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
30083,212,"DMA","Dominica","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2015/dma_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
30084,212,"DMA","Dominica","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Annual/2015/dma_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
30085,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2000/dom_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
30086,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2000/dom_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
30087,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2000/dom_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
30088,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2000/dom_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
30089,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2000/dom_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
30090,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2000/dom_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
30091,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2000/dom_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
30092,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2000/dom_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
30093,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2001/dom_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
30094,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2001/dom_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
30095,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2001/dom_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
30096,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2001/dom_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
30097,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2001/dom_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
30098,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2001/dom_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
30099,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2001/dom_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
30100,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2001/dom_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
30101,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2002/dom_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
30102,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2002/dom_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
30103,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2002/dom_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
30104,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2002/dom_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
30105,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2002/dom_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
30106,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2002/dom_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
30107,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2002/dom_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
30108,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2002/dom_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
30109,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2003/dom_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
30110,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2003/dom_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
30111,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2003/dom_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
30112,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2003/dom_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
30113,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2003/dom_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
30114,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2003/dom_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
30115,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2003/dom_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
30116,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2003/dom_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
30117,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2004/dom_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
30118,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2004/dom_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
30119,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2004/dom_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
30120,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2004/dom_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
30121,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2004/dom_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
30122,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2004/dom_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
30123,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2004/dom_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
30124,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2004/dom_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
30125,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2005/dom_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
30126,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2005/dom_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
30127,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2005/dom_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
30128,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2005/dom_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
30129,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2005/dom_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
30130,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2005/dom_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
30131,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2005/dom_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
30132,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2005/dom_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
30133,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2006/dom_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
30134,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2006/dom_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
30135,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2006/dom_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
30136,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2006/dom_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
30137,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2006/dom_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
30138,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2006/dom_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
30139,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2006/dom_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
30140,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2006/dom_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
30141,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2007/dom_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
30142,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2007/dom_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
30143,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2007/dom_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
30144,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2007/dom_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
30145,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2007/dom_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
30146,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2007/dom_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
30147,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2007/dom_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
30148,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2007/dom_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
30149,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2008/dom_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
30150,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2008/dom_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
30151,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2008/dom_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
30152,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2008/dom_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
30153,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2008/dom_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
30154,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2008/dom_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
30155,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2008/dom_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
30156,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2008/dom_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
30157,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2009/dom_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
30158,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2009/dom_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
30159,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2009/dom_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
30160,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2009/dom_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
30161,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2009/dom_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
30162,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2009/dom_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
30163,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2009/dom_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
30164,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2009/dom_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
30165,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2010/dom_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
30166,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2010/dom_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
30167,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2010/dom_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
30168,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2010/dom_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
30169,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2010/dom_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
30170,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2010/dom_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
30171,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2010/dom_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
30172,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2010/dom_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
30173,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2011/dom_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
30174,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2011/dom_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
30175,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2011/dom_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
30176,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2011/dom_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
30177,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2011/dom_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
30178,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2011/dom_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
30179,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2011/dom_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
30180,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2011/dom_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
30181,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2012/dom_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
30182,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2012/dom_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
30183,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2012/dom_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
30184,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2012/dom_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
30185,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2012/dom_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
30186,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2012/dom_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
30187,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2012/dom_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
30188,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2012/dom_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
30189,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2013/dom_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
30190,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2013/dom_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
30191,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2013/dom_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
30192,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2013/dom_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
30193,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2013/dom_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
30194,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2013/dom_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
30195,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2013/dom_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
30196,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2013/dom_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
30197,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2014/dom_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
30198,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2014/dom_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
30199,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2014/dom_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
30200,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2014/dom_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
30201,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2014/dom_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
30202,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2014/dom_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
30203,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2014/dom_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
30204,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2014/dom_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
30205,214,"DOM","Dominican Republic","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2015/dom_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
30206,214,"DOM","Dominican Republic","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2015/dom_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
30207,214,"DOM","Dominican Republic","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2015/dom_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
30208,214,"DOM","Dominican Republic","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2015/dom_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
30209,214,"DOM","Dominican Republic","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2015/dom_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
30210,214,"DOM","Dominican Republic","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2015/dom_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
30211,214,"DOM","Dominican Republic","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2015/dom_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
30212,214,"DOM","Dominican Republic","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Annual/2015/dom_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
30213,218,"ECU","Ecuador","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2000/ecu_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
30214,218,"ECU","Ecuador","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2000/ecu_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
30215,218,"ECU","Ecuador","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2000/ecu_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
30216,218,"ECU","Ecuador","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2000/ecu_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
30217,218,"ECU","Ecuador","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2000/ecu_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
30218,218,"ECU","Ecuador","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2000/ecu_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
30219,218,"ECU","Ecuador","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2000/ecu_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
30220,218,"ECU","Ecuador","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2000/ecu_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
30221,218,"ECU","Ecuador","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2001/ecu_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
30222,218,"ECU","Ecuador","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2001/ecu_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
30223,218,"ECU","Ecuador","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2001/ecu_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
30224,218,"ECU","Ecuador","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2001/ecu_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
30225,218,"ECU","Ecuador","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2001/ecu_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
30226,218,"ECU","Ecuador","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2001/ecu_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
30227,218,"ECU","Ecuador","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2001/ecu_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
30228,218,"ECU","Ecuador","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2001/ecu_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
30229,218,"ECU","Ecuador","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2002/ecu_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
30230,218,"ECU","Ecuador","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2002/ecu_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
30231,218,"ECU","Ecuador","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2002/ecu_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
30232,218,"ECU","Ecuador","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2002/ecu_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
30233,218,"ECU","Ecuador","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2002/ecu_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
30234,218,"ECU","Ecuador","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2002/ecu_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
30235,218,"ECU","Ecuador","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2002/ecu_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
30236,218,"ECU","Ecuador","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2002/ecu_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
30237,218,"ECU","Ecuador","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2003/ecu_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
30238,218,"ECU","Ecuador","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2003/ecu_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
30239,218,"ECU","Ecuador","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2003/ecu_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
30240,218,"ECU","Ecuador","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2003/ecu_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
30241,218,"ECU","Ecuador","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2003/ecu_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
30242,218,"ECU","Ecuador","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2003/ecu_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
30243,218,"ECU","Ecuador","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2003/ecu_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
30244,218,"ECU","Ecuador","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2003/ecu_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
30245,218,"ECU","Ecuador","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2004/ecu_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
30246,218,"ECU","Ecuador","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2004/ecu_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
30247,218,"ECU","Ecuador","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2004/ecu_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
30248,218,"ECU","Ecuador","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2004/ecu_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
30249,218,"ECU","Ecuador","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2004/ecu_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
30250,218,"ECU","Ecuador","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2004/ecu_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
30251,218,"ECU","Ecuador","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2004/ecu_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
30252,218,"ECU","Ecuador","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2004/ecu_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
30253,218,"ECU","Ecuador","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2005/ecu_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
30254,218,"ECU","Ecuador","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2005/ecu_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
30255,218,"ECU","Ecuador","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2005/ecu_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
30256,218,"ECU","Ecuador","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2005/ecu_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
30257,218,"ECU","Ecuador","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2005/ecu_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
30258,218,"ECU","Ecuador","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2005/ecu_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
30259,218,"ECU","Ecuador","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2005/ecu_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
30260,218,"ECU","Ecuador","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2005/ecu_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
30261,218,"ECU","Ecuador","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2006/ecu_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
30262,218,"ECU","Ecuador","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2006/ecu_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
30263,218,"ECU","Ecuador","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2006/ecu_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
30264,218,"ECU","Ecuador","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2006/ecu_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
30265,218,"ECU","Ecuador","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2006/ecu_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
30266,218,"ECU","Ecuador","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2006/ecu_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
30267,218,"ECU","Ecuador","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2006/ecu_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
30268,218,"ECU","Ecuador","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2006/ecu_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
30269,218,"ECU","Ecuador","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2007/ecu_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
30270,218,"ECU","Ecuador","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2007/ecu_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
30271,218,"ECU","Ecuador","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2007/ecu_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
30272,218,"ECU","Ecuador","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2007/ecu_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
30273,218,"ECU","Ecuador","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2007/ecu_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
30274,218,"ECU","Ecuador","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2007/ecu_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
30275,218,"ECU","Ecuador","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2007/ecu_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
30276,218,"ECU","Ecuador","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2007/ecu_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
30277,218,"ECU","Ecuador","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2008/ecu_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
30278,218,"ECU","Ecuador","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2008/ecu_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
30279,218,"ECU","Ecuador","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2008/ecu_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
30280,218,"ECU","Ecuador","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2008/ecu_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
30281,218,"ECU","Ecuador","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2008/ecu_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
30282,218,"ECU","Ecuador","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2008/ecu_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
30283,218,"ECU","Ecuador","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2008/ecu_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
30284,218,"ECU","Ecuador","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2008/ecu_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
30285,218,"ECU","Ecuador","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2009/ecu_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
30286,218,"ECU","Ecuador","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2009/ecu_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
30287,218,"ECU","Ecuador","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2009/ecu_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
30288,218,"ECU","Ecuador","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2009/ecu_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
30289,218,"ECU","Ecuador","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2009/ecu_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
30290,218,"ECU","Ecuador","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2009/ecu_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
30291,218,"ECU","Ecuador","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2009/ecu_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
30292,218,"ECU","Ecuador","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2009/ecu_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
30293,218,"ECU","Ecuador","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2010/ecu_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
30294,218,"ECU","Ecuador","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2010/ecu_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
30295,218,"ECU","Ecuador","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2010/ecu_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
30296,218,"ECU","Ecuador","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2010/ecu_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
30297,218,"ECU","Ecuador","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2010/ecu_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
30298,218,"ECU","Ecuador","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2010/ecu_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
30299,218,"ECU","Ecuador","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2010/ecu_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
30300,218,"ECU","Ecuador","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2010/ecu_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
30301,218,"ECU","Ecuador","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2011/ecu_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
30302,218,"ECU","Ecuador","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2011/ecu_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
30303,218,"ECU","Ecuador","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2011/ecu_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
30304,218,"ECU","Ecuador","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2011/ecu_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
30305,218,"ECU","Ecuador","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2011/ecu_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
30306,218,"ECU","Ecuador","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2011/ecu_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
30307,218,"ECU","Ecuador","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2011/ecu_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
30308,218,"ECU","Ecuador","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2011/ecu_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
30309,218,"ECU","Ecuador","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2012/ecu_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
30310,218,"ECU","Ecuador","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2012/ecu_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
30311,218,"ECU","Ecuador","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2012/ecu_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
30312,218,"ECU","Ecuador","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2012/ecu_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
30313,218,"ECU","Ecuador","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2012/ecu_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
30314,218,"ECU","Ecuador","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2012/ecu_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
30315,218,"ECU","Ecuador","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2012/ecu_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
30316,218,"ECU","Ecuador","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2012/ecu_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
30317,218,"ECU","Ecuador","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2013/ecu_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
30318,218,"ECU","Ecuador","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2013/ecu_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
30319,218,"ECU","Ecuador","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2013/ecu_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
30320,218,"ECU","Ecuador","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2013/ecu_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
30321,218,"ECU","Ecuador","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2013/ecu_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
30322,218,"ECU","Ecuador","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2013/ecu_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
30323,218,"ECU","Ecuador","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2013/ecu_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
30324,218,"ECU","Ecuador","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2013/ecu_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
30325,218,"ECU","Ecuador","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2014/ecu_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
30326,218,"ECU","Ecuador","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2014/ecu_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
30327,218,"ECU","Ecuador","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2014/ecu_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
30328,218,"ECU","Ecuador","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2014/ecu_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
30329,218,"ECU","Ecuador","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2014/ecu_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
30330,218,"ECU","Ecuador","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2014/ecu_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
30331,218,"ECU","Ecuador","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2014/ecu_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
30332,218,"ECU","Ecuador","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2014/ecu_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
30333,218,"ECU","Ecuador","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2015/ecu_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
30334,218,"ECU","Ecuador","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2015/ecu_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
30335,218,"ECU","Ecuador","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2015/ecu_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
30336,218,"ECU","Ecuador","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2015/ecu_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
30337,218,"ECU","Ecuador","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2015/ecu_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
30338,218,"ECU","Ecuador","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2015/ecu_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
30339,218,"ECU","Ecuador","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2015/ecu_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
30340,218,"ECU","Ecuador","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Annual/2015/ecu_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
30341,222,"SLV","El Salvador","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2000/slv_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
30342,222,"SLV","El Salvador","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2000/slv_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
30343,222,"SLV","El Salvador","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2000/slv_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
30344,222,"SLV","El Salvador","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2000/slv_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
30345,222,"SLV","El Salvador","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2000/slv_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
30346,222,"SLV","El Salvador","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2000/slv_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
30347,222,"SLV","El Salvador","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2000/slv_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
30348,222,"SLV","El Salvador","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2000/slv_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
30349,222,"SLV","El Salvador","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2001/slv_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
30350,222,"SLV","El Salvador","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2001/slv_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
30351,222,"SLV","El Salvador","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2001/slv_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
30352,222,"SLV","El Salvador","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2001/slv_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
30353,222,"SLV","El Salvador","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2001/slv_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
30354,222,"SLV","El Salvador","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2001/slv_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
30355,222,"SLV","El Salvador","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2001/slv_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
30356,222,"SLV","El Salvador","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2001/slv_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
30357,222,"SLV","El Salvador","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2002/slv_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
30358,222,"SLV","El Salvador","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2002/slv_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
30359,222,"SLV","El Salvador","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2002/slv_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
30360,222,"SLV","El Salvador","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2002/slv_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
30361,222,"SLV","El Salvador","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2002/slv_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
30362,222,"SLV","El Salvador","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2002/slv_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
30363,222,"SLV","El Salvador","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2002/slv_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
30364,222,"SLV","El Salvador","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2002/slv_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
30365,222,"SLV","El Salvador","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2003/slv_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
30366,222,"SLV","El Salvador","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2003/slv_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
30367,222,"SLV","El Salvador","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2003/slv_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
30368,222,"SLV","El Salvador","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2003/slv_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
30369,222,"SLV","El Salvador","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2003/slv_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
30370,222,"SLV","El Salvador","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2003/slv_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
30371,222,"SLV","El Salvador","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2003/slv_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
30372,222,"SLV","El Salvador","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2003/slv_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
30373,222,"SLV","El Salvador","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2004/slv_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
30374,222,"SLV","El Salvador","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2004/slv_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
30375,222,"SLV","El Salvador","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2004/slv_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
30376,222,"SLV","El Salvador","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2004/slv_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
30377,222,"SLV","El Salvador","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2004/slv_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
30378,222,"SLV","El Salvador","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2004/slv_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
30379,222,"SLV","El Salvador","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2004/slv_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
30380,222,"SLV","El Salvador","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2004/slv_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
30381,222,"SLV","El Salvador","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2005/slv_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
30382,222,"SLV","El Salvador","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2005/slv_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
30383,222,"SLV","El Salvador","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2005/slv_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
30384,222,"SLV","El Salvador","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2005/slv_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
30385,222,"SLV","El Salvador","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2005/slv_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
30386,222,"SLV","El Salvador","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2005/slv_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
30387,222,"SLV","El Salvador","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2005/slv_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
30388,222,"SLV","El Salvador","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2005/slv_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
30389,222,"SLV","El Salvador","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2006/slv_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
30390,222,"SLV","El Salvador","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2006/slv_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
30391,222,"SLV","El Salvador","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2006/slv_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
30392,222,"SLV","El Salvador","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2006/slv_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
30393,222,"SLV","El Salvador","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2006/slv_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
30394,222,"SLV","El Salvador","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2006/slv_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
30395,222,"SLV","El Salvador","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2006/slv_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
30396,222,"SLV","El Salvador","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2006/slv_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
30397,222,"SLV","El Salvador","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2007/slv_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
30398,222,"SLV","El Salvador","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2007/slv_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
30399,222,"SLV","El Salvador","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2007/slv_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
30400,222,"SLV","El Salvador","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2007/slv_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
30401,222,"SLV","El Salvador","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2007/slv_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
30402,222,"SLV","El Salvador","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2007/slv_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
30403,222,"SLV","El Salvador","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2007/slv_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
30404,222,"SLV","El Salvador","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2007/slv_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
30405,222,"SLV","El Salvador","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2008/slv_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
30406,222,"SLV","El Salvador","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2008/slv_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
30407,222,"SLV","El Salvador","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2008/slv_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
30408,222,"SLV","El Salvador","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2008/slv_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
30409,222,"SLV","El Salvador","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2008/slv_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
30410,222,"SLV","El Salvador","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2008/slv_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
30411,222,"SLV","El Salvador","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2008/slv_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
30412,222,"SLV","El Salvador","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2008/slv_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
30413,222,"SLV","El Salvador","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2009/slv_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
30414,222,"SLV","El Salvador","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2009/slv_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
30415,222,"SLV","El Salvador","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2009/slv_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
30416,222,"SLV","El Salvador","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2009/slv_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
30417,222,"SLV","El Salvador","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2009/slv_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
30418,222,"SLV","El Salvador","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2009/slv_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
30419,222,"SLV","El Salvador","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2009/slv_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
30420,222,"SLV","El Salvador","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2009/slv_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
30421,222,"SLV","El Salvador","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2010/slv_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
30422,222,"SLV","El Salvador","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2010/slv_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
30423,222,"SLV","El Salvador","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2010/slv_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
30424,222,"SLV","El Salvador","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2010/slv_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
30425,222,"SLV","El Salvador","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2010/slv_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
30426,222,"SLV","El Salvador","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2010/slv_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
30427,222,"SLV","El Salvador","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2010/slv_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
30428,222,"SLV","El Salvador","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2010/slv_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
30429,222,"SLV","El Salvador","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2011/slv_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
30430,222,"SLV","El Salvador","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2011/slv_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
30431,222,"SLV","El Salvador","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2011/slv_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
30432,222,"SLV","El Salvador","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2011/slv_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
30433,222,"SLV","El Salvador","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2011/slv_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
30434,222,"SLV","El Salvador","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2011/slv_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
30435,222,"SLV","El Salvador","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2011/slv_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
30436,222,"SLV","El Salvador","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2011/slv_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
30437,222,"SLV","El Salvador","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2012/slv_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
30438,222,"SLV","El Salvador","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2012/slv_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
30439,222,"SLV","El Salvador","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2012/slv_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
30440,222,"SLV","El Salvador","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2012/slv_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
30441,222,"SLV","El Salvador","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2012/slv_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
30442,222,"SLV","El Salvador","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2012/slv_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
30443,222,"SLV","El Salvador","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2012/slv_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
30444,222,"SLV","El Salvador","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2012/slv_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
30445,222,"SLV","El Salvador","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2013/slv_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
30446,222,"SLV","El Salvador","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2013/slv_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
30447,222,"SLV","El Salvador","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2013/slv_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
30448,222,"SLV","El Salvador","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2013/slv_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
30449,222,"SLV","El Salvador","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2013/slv_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
30450,222,"SLV","El Salvador","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2013/slv_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
30451,222,"SLV","El Salvador","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2013/slv_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
30452,222,"SLV","El Salvador","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2013/slv_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
30453,222,"SLV","El Salvador","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2014/slv_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
30454,222,"SLV","El Salvador","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2014/slv_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
30455,222,"SLV","El Salvador","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2014/slv_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
30456,222,"SLV","El Salvador","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2014/slv_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
30457,222,"SLV","El Salvador","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2014/slv_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
30458,222,"SLV","El Salvador","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2014/slv_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
30459,222,"SLV","El Salvador","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2014/slv_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
30460,222,"SLV","El Salvador","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2014/slv_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
30461,222,"SLV","El Salvador","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2015/slv_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
30462,222,"SLV","El Salvador","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2015/slv_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
30463,222,"SLV","El Salvador","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2015/slv_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
30464,222,"SLV","El Salvador","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2015/slv_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
30465,222,"SLV","El Salvador","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2015/slv_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
30466,222,"SLV","El Salvador","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2015/slv_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
30467,222,"SLV","El Salvador","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2015/slv_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
30468,222,"SLV","El Salvador","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Annual/2015/slv_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
30469,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2000/gnq_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
30470,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2000/gnq_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
30471,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2000/gnq_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
30472,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2000/gnq_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
30473,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2000/gnq_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
30474,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2000/gnq_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
30475,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2000/gnq_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
30476,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2000/gnq_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
30477,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2001/gnq_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
30478,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2001/gnq_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
30479,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2001/gnq_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
30480,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2001/gnq_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
30481,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2001/gnq_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
30482,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2001/gnq_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
30483,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2001/gnq_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
30484,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2001/gnq_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
30485,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2002/gnq_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
30486,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2002/gnq_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
30487,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2002/gnq_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
30488,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2002/gnq_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
30489,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2002/gnq_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
30490,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2002/gnq_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
30491,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2002/gnq_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
30492,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2002/gnq_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
30493,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2003/gnq_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
30494,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2003/gnq_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
30495,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2003/gnq_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
30496,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2003/gnq_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
30497,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2003/gnq_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
30498,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2003/gnq_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
30499,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2003/gnq_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
30500,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2003/gnq_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
30501,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2004/gnq_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
30502,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2004/gnq_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
30503,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2004/gnq_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
30504,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2004/gnq_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
30505,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2004/gnq_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
30506,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2004/gnq_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
30507,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2004/gnq_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
30508,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2004/gnq_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
30509,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2005/gnq_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
30510,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2005/gnq_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
30511,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2005/gnq_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
30512,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2005/gnq_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
30513,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2005/gnq_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
30514,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2005/gnq_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
30515,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2005/gnq_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
30516,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2005/gnq_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
30517,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2006/gnq_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
30518,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2006/gnq_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
30519,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2006/gnq_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
30520,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2006/gnq_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
30521,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2006/gnq_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
30522,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2006/gnq_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
30523,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2006/gnq_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
30524,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2006/gnq_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
30525,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2007/gnq_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
30526,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2007/gnq_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
30527,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2007/gnq_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
30528,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2007/gnq_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
30529,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2007/gnq_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
30530,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2007/gnq_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
30531,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2007/gnq_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
30532,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2007/gnq_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
30533,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2008/gnq_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
30534,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2008/gnq_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
30535,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2008/gnq_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
30536,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2008/gnq_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
30537,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2008/gnq_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
30538,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2008/gnq_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
30539,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2008/gnq_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
30540,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2008/gnq_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
30541,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2009/gnq_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
30542,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2009/gnq_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
30543,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2009/gnq_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
30544,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2009/gnq_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
30545,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2009/gnq_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
30546,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2009/gnq_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
30547,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2009/gnq_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
30548,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2009/gnq_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
30549,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2010/gnq_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
30550,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2010/gnq_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
30551,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2010/gnq_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
30552,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2010/gnq_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
30553,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2010/gnq_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
30554,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2010/gnq_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
30555,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2010/gnq_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
30556,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2010/gnq_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
30557,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2011/gnq_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
30558,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2011/gnq_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
30559,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2011/gnq_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
30560,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2011/gnq_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
30561,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2011/gnq_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
30562,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2011/gnq_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
30563,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2011/gnq_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
30564,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2011/gnq_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
30565,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2012/gnq_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
30566,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2012/gnq_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
30567,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2012/gnq_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
30568,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2012/gnq_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
30569,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2012/gnq_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
30570,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2012/gnq_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
30571,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2012/gnq_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
30572,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2012/gnq_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
30573,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2013/gnq_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
30574,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2013/gnq_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
30575,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2013/gnq_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
30576,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2013/gnq_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
30577,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2013/gnq_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
30578,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2013/gnq_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
30579,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2013/gnq_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
30580,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2013/gnq_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
30581,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2014/gnq_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
30582,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2014/gnq_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
30583,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2014/gnq_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
30584,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2014/gnq_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
30585,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2014/gnq_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
30586,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2014/gnq_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
30587,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2014/gnq_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
30588,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2014/gnq_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
30589,226,"GNQ","Equatorial Guinea","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2015/gnq_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
30590,226,"GNQ","Equatorial Guinea","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2015/gnq_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
30591,226,"GNQ","Equatorial Guinea","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2015/gnq_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
30592,226,"GNQ","Equatorial Guinea","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2015/gnq_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
30593,226,"GNQ","Equatorial Guinea","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2015/gnq_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
30594,226,"GNQ","Equatorial Guinea","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2015/gnq_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
30595,226,"GNQ","Equatorial Guinea","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2015/gnq_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
30596,226,"GNQ","Equatorial Guinea","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Annual/2015/gnq_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
30597,231,"ETH","Ethiopia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2000/eth_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
30598,231,"ETH","Ethiopia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2000/eth_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
30599,231,"ETH","Ethiopia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2000/eth_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
30600,231,"ETH","Ethiopia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2000/eth_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
30601,231,"ETH","Ethiopia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2000/eth_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
30602,231,"ETH","Ethiopia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2000/eth_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
30603,231,"ETH","Ethiopia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2000/eth_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
30604,231,"ETH","Ethiopia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2000/eth_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
30605,231,"ETH","Ethiopia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2001/eth_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
30606,231,"ETH","Ethiopia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2001/eth_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
30607,231,"ETH","Ethiopia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2001/eth_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
30608,231,"ETH","Ethiopia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2001/eth_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
30609,231,"ETH","Ethiopia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2001/eth_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
30610,231,"ETH","Ethiopia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2001/eth_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
30611,231,"ETH","Ethiopia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2001/eth_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
30612,231,"ETH","Ethiopia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2001/eth_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
30613,231,"ETH","Ethiopia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2002/eth_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
30614,231,"ETH","Ethiopia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2002/eth_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
30615,231,"ETH","Ethiopia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2002/eth_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
30616,231,"ETH","Ethiopia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2002/eth_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
30617,231,"ETH","Ethiopia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2002/eth_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
30618,231,"ETH","Ethiopia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2002/eth_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
30619,231,"ETH","Ethiopia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2002/eth_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
30620,231,"ETH","Ethiopia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2002/eth_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
30621,231,"ETH","Ethiopia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2003/eth_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
30622,231,"ETH","Ethiopia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2003/eth_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
30623,231,"ETH","Ethiopia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2003/eth_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
30624,231,"ETH","Ethiopia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2003/eth_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
30625,231,"ETH","Ethiopia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2003/eth_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
30626,231,"ETH","Ethiopia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2003/eth_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
30627,231,"ETH","Ethiopia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2003/eth_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
30628,231,"ETH","Ethiopia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2003/eth_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
30629,231,"ETH","Ethiopia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2004/eth_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
30630,231,"ETH","Ethiopia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2004/eth_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
30631,231,"ETH","Ethiopia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2004/eth_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
30632,231,"ETH","Ethiopia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2004/eth_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
30633,231,"ETH","Ethiopia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2004/eth_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
30634,231,"ETH","Ethiopia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2004/eth_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
30635,231,"ETH","Ethiopia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2004/eth_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
30636,231,"ETH","Ethiopia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2004/eth_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
30637,231,"ETH","Ethiopia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2005/eth_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
30638,231,"ETH","Ethiopia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2005/eth_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
30639,231,"ETH","Ethiopia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2005/eth_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
30640,231,"ETH","Ethiopia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2005/eth_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
30641,231,"ETH","Ethiopia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2005/eth_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
30642,231,"ETH","Ethiopia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2005/eth_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
30643,231,"ETH","Ethiopia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2005/eth_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
30644,231,"ETH","Ethiopia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2005/eth_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
30645,231,"ETH","Ethiopia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2006/eth_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
30646,231,"ETH","Ethiopia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2006/eth_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
30647,231,"ETH","Ethiopia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2006/eth_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
30648,231,"ETH","Ethiopia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2006/eth_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
30649,231,"ETH","Ethiopia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2006/eth_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
30650,231,"ETH","Ethiopia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2006/eth_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
30651,231,"ETH","Ethiopia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2006/eth_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
30652,231,"ETH","Ethiopia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2006/eth_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
30653,231,"ETH","Ethiopia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2007/eth_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
30654,231,"ETH","Ethiopia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2007/eth_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
30655,231,"ETH","Ethiopia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2007/eth_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
30656,231,"ETH","Ethiopia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2007/eth_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
30657,231,"ETH","Ethiopia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2007/eth_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
30658,231,"ETH","Ethiopia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2007/eth_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
30659,231,"ETH","Ethiopia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2007/eth_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
30660,231,"ETH","Ethiopia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2007/eth_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
30661,231,"ETH","Ethiopia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2008/eth_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
30662,231,"ETH","Ethiopia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2008/eth_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
30663,231,"ETH","Ethiopia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2008/eth_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
30664,231,"ETH","Ethiopia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2008/eth_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
30665,231,"ETH","Ethiopia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2008/eth_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
30666,231,"ETH","Ethiopia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2008/eth_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
30667,231,"ETH","Ethiopia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2008/eth_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
30668,231,"ETH","Ethiopia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2008/eth_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
30669,231,"ETH","Ethiopia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2009/eth_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
30670,231,"ETH","Ethiopia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2009/eth_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
30671,231,"ETH","Ethiopia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2009/eth_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
30672,231,"ETH","Ethiopia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2009/eth_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
30673,231,"ETH","Ethiopia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2009/eth_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
30674,231,"ETH","Ethiopia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2009/eth_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
30675,231,"ETH","Ethiopia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2009/eth_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
30676,231,"ETH","Ethiopia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2009/eth_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
30677,231,"ETH","Ethiopia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2010/eth_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
30678,231,"ETH","Ethiopia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2010/eth_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
30679,231,"ETH","Ethiopia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2010/eth_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
30680,231,"ETH","Ethiopia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2010/eth_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
30681,231,"ETH","Ethiopia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2010/eth_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
30682,231,"ETH","Ethiopia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2010/eth_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
30683,231,"ETH","Ethiopia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2010/eth_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
30684,231,"ETH","Ethiopia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2010/eth_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
30685,231,"ETH","Ethiopia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2011/eth_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
30686,231,"ETH","Ethiopia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2011/eth_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
30687,231,"ETH","Ethiopia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2011/eth_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
30688,231,"ETH","Ethiopia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2011/eth_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
30689,231,"ETH","Ethiopia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2011/eth_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
30690,231,"ETH","Ethiopia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2011/eth_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
30691,231,"ETH","Ethiopia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2011/eth_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
30692,231,"ETH","Ethiopia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2011/eth_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
30693,231,"ETH","Ethiopia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2012/eth_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
30694,231,"ETH","Ethiopia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2012/eth_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
30695,231,"ETH","Ethiopia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2012/eth_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
30696,231,"ETH","Ethiopia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2012/eth_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
30697,231,"ETH","Ethiopia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2012/eth_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
30698,231,"ETH","Ethiopia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2012/eth_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
30699,231,"ETH","Ethiopia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2012/eth_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
30700,231,"ETH","Ethiopia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2012/eth_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
30701,231,"ETH","Ethiopia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2013/eth_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
30702,231,"ETH","Ethiopia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2013/eth_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
30703,231,"ETH","Ethiopia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2013/eth_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
30704,231,"ETH","Ethiopia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2013/eth_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
30705,231,"ETH","Ethiopia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2013/eth_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
30706,231,"ETH","Ethiopia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2013/eth_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
30707,231,"ETH","Ethiopia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2013/eth_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
30708,231,"ETH","Ethiopia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2013/eth_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
30709,231,"ETH","Ethiopia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2014/eth_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
30710,231,"ETH","Ethiopia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2014/eth_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
30711,231,"ETH","Ethiopia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2014/eth_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
30712,231,"ETH","Ethiopia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2014/eth_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
30713,231,"ETH","Ethiopia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2014/eth_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
30714,231,"ETH","Ethiopia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2014/eth_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
30715,231,"ETH","Ethiopia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2014/eth_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
30716,231,"ETH","Ethiopia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2014/eth_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
30717,231,"ETH","Ethiopia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2015/eth_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
30718,231,"ETH","Ethiopia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2015/eth_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
30719,231,"ETH","Ethiopia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2015/eth_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
30720,231,"ETH","Ethiopia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2015/eth_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
30721,231,"ETH","Ethiopia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2015/eth_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
30722,231,"ETH","Ethiopia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2015/eth_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
30723,231,"ETH","Ethiopia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2015/eth_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
30724,231,"ETH","Ethiopia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Annual/2015/eth_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
30725,232,"ERI","Eritrea","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2000/eri_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
30726,232,"ERI","Eritrea","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2000/eri_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
30727,232,"ERI","Eritrea","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2000/eri_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
30728,232,"ERI","Eritrea","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2000/eri_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
30729,232,"ERI","Eritrea","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2000/eri_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
30730,232,"ERI","Eritrea","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2000/eri_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
30731,232,"ERI","Eritrea","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2000/eri_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
30732,232,"ERI","Eritrea","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2000/eri_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
30733,232,"ERI","Eritrea","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2001/eri_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
30734,232,"ERI","Eritrea","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2001/eri_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
30735,232,"ERI","Eritrea","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2001/eri_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
30736,232,"ERI","Eritrea","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2001/eri_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
30737,232,"ERI","Eritrea","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2001/eri_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
30738,232,"ERI","Eritrea","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2001/eri_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
30739,232,"ERI","Eritrea","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2001/eri_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
30740,232,"ERI","Eritrea","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2001/eri_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
30741,232,"ERI","Eritrea","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2002/eri_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
30742,232,"ERI","Eritrea","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2002/eri_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
30743,232,"ERI","Eritrea","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2002/eri_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
30744,232,"ERI","Eritrea","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2002/eri_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
30745,232,"ERI","Eritrea","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2002/eri_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
30746,232,"ERI","Eritrea","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2002/eri_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
30747,232,"ERI","Eritrea","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2002/eri_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
30748,232,"ERI","Eritrea","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2002/eri_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
30749,232,"ERI","Eritrea","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2003/eri_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
30750,232,"ERI","Eritrea","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2003/eri_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
30751,232,"ERI","Eritrea","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2003/eri_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
30752,232,"ERI","Eritrea","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2003/eri_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
30753,232,"ERI","Eritrea","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2003/eri_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
30754,232,"ERI","Eritrea","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2003/eri_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
30755,232,"ERI","Eritrea","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2003/eri_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
30756,232,"ERI","Eritrea","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2003/eri_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
30757,232,"ERI","Eritrea","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2004/eri_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
30758,232,"ERI","Eritrea","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2004/eri_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
30759,232,"ERI","Eritrea","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2004/eri_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
30760,232,"ERI","Eritrea","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2004/eri_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
30761,232,"ERI","Eritrea","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2004/eri_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
30762,232,"ERI","Eritrea","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2004/eri_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
30763,232,"ERI","Eritrea","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2004/eri_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
30764,232,"ERI","Eritrea","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2004/eri_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
30765,232,"ERI","Eritrea","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2005/eri_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
30766,232,"ERI","Eritrea","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2005/eri_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
30767,232,"ERI","Eritrea","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2005/eri_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
30768,232,"ERI","Eritrea","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2005/eri_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
30769,232,"ERI","Eritrea","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2005/eri_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
30770,232,"ERI","Eritrea","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2005/eri_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
30771,232,"ERI","Eritrea","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2005/eri_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
30772,232,"ERI","Eritrea","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2005/eri_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
30773,232,"ERI","Eritrea","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2006/eri_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
30774,232,"ERI","Eritrea","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2006/eri_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
30775,232,"ERI","Eritrea","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2006/eri_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
30776,232,"ERI","Eritrea","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2006/eri_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
30777,232,"ERI","Eritrea","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2006/eri_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
30778,232,"ERI","Eritrea","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2006/eri_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
30779,232,"ERI","Eritrea","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2006/eri_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
30780,232,"ERI","Eritrea","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2006/eri_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
30781,232,"ERI","Eritrea","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2007/eri_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
30782,232,"ERI","Eritrea","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2007/eri_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
30783,232,"ERI","Eritrea","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2007/eri_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
30784,232,"ERI","Eritrea","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2007/eri_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
30785,232,"ERI","Eritrea","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2007/eri_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
30786,232,"ERI","Eritrea","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2007/eri_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
30787,232,"ERI","Eritrea","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2007/eri_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
30788,232,"ERI","Eritrea","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2007/eri_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
30789,232,"ERI","Eritrea","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2008/eri_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
30790,232,"ERI","Eritrea","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2008/eri_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
30791,232,"ERI","Eritrea","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2008/eri_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
30792,232,"ERI","Eritrea","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2008/eri_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
30793,232,"ERI","Eritrea","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2008/eri_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
30794,232,"ERI","Eritrea","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2008/eri_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
30795,232,"ERI","Eritrea","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2008/eri_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
30796,232,"ERI","Eritrea","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2008/eri_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
30797,232,"ERI","Eritrea","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2009/eri_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
30798,232,"ERI","Eritrea","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2009/eri_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
30799,232,"ERI","Eritrea","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2009/eri_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
30800,232,"ERI","Eritrea","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2009/eri_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
30801,232,"ERI","Eritrea","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2009/eri_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
30802,232,"ERI","Eritrea","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2009/eri_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
30803,232,"ERI","Eritrea","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2009/eri_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
30804,232,"ERI","Eritrea","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2009/eri_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
30805,232,"ERI","Eritrea","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2010/eri_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
30806,232,"ERI","Eritrea","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2010/eri_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
30807,232,"ERI","Eritrea","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2010/eri_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
30808,232,"ERI","Eritrea","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2010/eri_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
30809,232,"ERI","Eritrea","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2010/eri_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
30810,232,"ERI","Eritrea","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2010/eri_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
30811,232,"ERI","Eritrea","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2010/eri_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
30812,232,"ERI","Eritrea","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2010/eri_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
30813,232,"ERI","Eritrea","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2011/eri_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
30814,232,"ERI","Eritrea","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2011/eri_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
30815,232,"ERI","Eritrea","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2011/eri_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
30816,232,"ERI","Eritrea","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2011/eri_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
30817,232,"ERI","Eritrea","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2011/eri_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
30818,232,"ERI","Eritrea","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2011/eri_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
30819,232,"ERI","Eritrea","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2011/eri_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
30820,232,"ERI","Eritrea","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2011/eri_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
30821,232,"ERI","Eritrea","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2012/eri_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
30822,232,"ERI","Eritrea","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2012/eri_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
30823,232,"ERI","Eritrea","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2012/eri_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
30824,232,"ERI","Eritrea","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2012/eri_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
30825,232,"ERI","Eritrea","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2012/eri_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
30826,232,"ERI","Eritrea","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2012/eri_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
30827,232,"ERI","Eritrea","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2012/eri_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
30828,232,"ERI","Eritrea","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2012/eri_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
30829,232,"ERI","Eritrea","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2013/eri_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
30830,232,"ERI","Eritrea","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2013/eri_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
30831,232,"ERI","Eritrea","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2013/eri_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
30832,232,"ERI","Eritrea","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2013/eri_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
30833,232,"ERI","Eritrea","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2013/eri_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
30834,232,"ERI","Eritrea","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2013/eri_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
30835,232,"ERI","Eritrea","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2013/eri_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
30836,232,"ERI","Eritrea","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2013/eri_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
30837,232,"ERI","Eritrea","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2014/eri_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
30838,232,"ERI","Eritrea","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2014/eri_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
30839,232,"ERI","Eritrea","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2014/eri_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
30840,232,"ERI","Eritrea","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2014/eri_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
30841,232,"ERI","Eritrea","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2014/eri_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
30842,232,"ERI","Eritrea","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2014/eri_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
30843,232,"ERI","Eritrea","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2014/eri_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
30844,232,"ERI","Eritrea","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2014/eri_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
30845,232,"ERI","Eritrea","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2015/eri_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
30846,232,"ERI","Eritrea","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2015/eri_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
30847,232,"ERI","Eritrea","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2015/eri_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
30848,232,"ERI","Eritrea","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2015/eri_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
30849,232,"ERI","Eritrea","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2015/eri_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
30850,232,"ERI","Eritrea","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2015/eri_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
30851,232,"ERI","Eritrea","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2015/eri_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
30852,232,"ERI","Eritrea","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Annual/2015/eri_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
30853,233,"EST","Estonia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2000/est_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
30854,233,"EST","Estonia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2000/est_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
30855,233,"EST","Estonia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2000/est_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
30856,233,"EST","Estonia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2000/est_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
30857,233,"EST","Estonia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2000/est_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
30858,233,"EST","Estonia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2000/est_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
30859,233,"EST","Estonia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2000/est_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
30860,233,"EST","Estonia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2000/est_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
30861,233,"EST","Estonia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2001/est_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
30862,233,"EST","Estonia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2001/est_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
30863,233,"EST","Estonia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2001/est_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
30864,233,"EST","Estonia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2001/est_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
30865,233,"EST","Estonia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2001/est_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
30866,233,"EST","Estonia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2001/est_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
30867,233,"EST","Estonia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2001/est_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
30868,233,"EST","Estonia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2001/est_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
30869,233,"EST","Estonia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2002/est_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
30870,233,"EST","Estonia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2002/est_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
30871,233,"EST","Estonia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2002/est_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
30872,233,"EST","Estonia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2002/est_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
30873,233,"EST","Estonia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2002/est_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
30874,233,"EST","Estonia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2002/est_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
30875,233,"EST","Estonia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2002/est_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
30876,233,"EST","Estonia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2002/est_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
30877,233,"EST","Estonia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2003/est_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
30878,233,"EST","Estonia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2003/est_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
30879,233,"EST","Estonia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2003/est_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
30880,233,"EST","Estonia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2003/est_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
30881,233,"EST","Estonia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2003/est_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
30882,233,"EST","Estonia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2003/est_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
30883,233,"EST","Estonia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2003/est_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
30884,233,"EST","Estonia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2003/est_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
30885,233,"EST","Estonia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2004/est_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
30886,233,"EST","Estonia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2004/est_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
30887,233,"EST","Estonia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2004/est_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
30888,233,"EST","Estonia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2004/est_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
30889,233,"EST","Estonia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2004/est_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
30890,233,"EST","Estonia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2004/est_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
30891,233,"EST","Estonia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2004/est_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
30892,233,"EST","Estonia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2004/est_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
30893,233,"EST","Estonia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2005/est_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
30894,233,"EST","Estonia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2005/est_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
30895,233,"EST","Estonia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2005/est_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
30896,233,"EST","Estonia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2005/est_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
30897,233,"EST","Estonia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2005/est_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
30898,233,"EST","Estonia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2005/est_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
30899,233,"EST","Estonia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2005/est_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
30900,233,"EST","Estonia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2005/est_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
30901,233,"EST","Estonia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2006/est_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
30902,233,"EST","Estonia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2006/est_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
30903,233,"EST","Estonia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2006/est_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
30904,233,"EST","Estonia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2006/est_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
30905,233,"EST","Estonia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2006/est_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
30906,233,"EST","Estonia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2006/est_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
30907,233,"EST","Estonia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2006/est_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
30908,233,"EST","Estonia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2006/est_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
30909,233,"EST","Estonia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2007/est_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
30910,233,"EST","Estonia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2007/est_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
30911,233,"EST","Estonia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2007/est_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
30912,233,"EST","Estonia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2007/est_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
30913,233,"EST","Estonia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2007/est_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
30914,233,"EST","Estonia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2007/est_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
30915,233,"EST","Estonia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2007/est_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
30916,233,"EST","Estonia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2007/est_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
30917,233,"EST","Estonia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2008/est_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
30918,233,"EST","Estonia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2008/est_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
30919,233,"EST","Estonia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2008/est_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
30920,233,"EST","Estonia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2008/est_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
30921,233,"EST","Estonia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2008/est_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
30922,233,"EST","Estonia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2008/est_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
30923,233,"EST","Estonia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2008/est_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
30924,233,"EST","Estonia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2008/est_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
30925,233,"EST","Estonia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2009/est_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
30926,233,"EST","Estonia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2009/est_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
30927,233,"EST","Estonia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2009/est_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
30928,233,"EST","Estonia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2009/est_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
30929,233,"EST","Estonia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2009/est_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
30930,233,"EST","Estonia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2009/est_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
30931,233,"EST","Estonia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2009/est_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
30932,233,"EST","Estonia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2009/est_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
30933,233,"EST","Estonia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2010/est_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
30934,233,"EST","Estonia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2010/est_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
30935,233,"EST","Estonia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2010/est_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
30936,233,"EST","Estonia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2010/est_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
30937,233,"EST","Estonia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2010/est_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
30938,233,"EST","Estonia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2010/est_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
30939,233,"EST","Estonia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2010/est_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
30940,233,"EST","Estonia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2010/est_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
30941,233,"EST","Estonia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2011/est_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
30942,233,"EST","Estonia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2011/est_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
30943,233,"EST","Estonia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2011/est_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
30944,233,"EST","Estonia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2011/est_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
30945,233,"EST","Estonia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2011/est_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
30946,233,"EST","Estonia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2011/est_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
30947,233,"EST","Estonia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2011/est_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
30948,233,"EST","Estonia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2011/est_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
30949,233,"EST","Estonia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2012/est_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
30950,233,"EST","Estonia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2012/est_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
30951,233,"EST","Estonia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2012/est_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
30952,233,"EST","Estonia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2012/est_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
30953,233,"EST","Estonia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2012/est_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
30954,233,"EST","Estonia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2012/est_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
30955,233,"EST","Estonia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2012/est_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
30956,233,"EST","Estonia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2012/est_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
30957,233,"EST","Estonia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2013/est_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
30958,233,"EST","Estonia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2013/est_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
30959,233,"EST","Estonia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2013/est_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
30960,233,"EST","Estonia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2013/est_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
30961,233,"EST","Estonia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2013/est_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
30962,233,"EST","Estonia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2013/est_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
30963,233,"EST","Estonia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2013/est_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
30964,233,"EST","Estonia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2013/est_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
30965,233,"EST","Estonia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2014/est_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
30966,233,"EST","Estonia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2014/est_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
30967,233,"EST","Estonia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2014/est_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
30968,233,"EST","Estonia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2014/est_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
30969,233,"EST","Estonia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2014/est_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
30970,233,"EST","Estonia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2014/est_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
30971,233,"EST","Estonia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2014/est_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
30972,233,"EST","Estonia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2014/est_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
30973,233,"EST","Estonia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2015/est_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
30974,233,"EST","Estonia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2015/est_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
30975,233,"EST","Estonia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2015/est_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
30976,233,"EST","Estonia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2015/est_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
30977,233,"EST","Estonia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2015/est_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
30978,233,"EST","Estonia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2015/est_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
30979,233,"EST","Estonia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2015/est_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
30980,233,"EST","Estonia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Annual/2015/est_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
30981,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2000/fro_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
30982,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2000/fro_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
30983,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2000/fro_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
30984,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2000/fro_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
30985,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2000/fro_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
30986,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2000/fro_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
30987,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2000/fro_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
30988,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2000/fro_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
30989,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2001/fro_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
30990,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2001/fro_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
30991,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2001/fro_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
30992,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2001/fro_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
30993,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2001/fro_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
30994,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2001/fro_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
30995,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2001/fro_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
30996,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2001/fro_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
30997,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2002/fro_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
30998,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2002/fro_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
30999,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2002/fro_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
31000,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2002/fro_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
31001,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2002/fro_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
31002,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2002/fro_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
31003,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2002/fro_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
31004,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2002/fro_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
31005,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2003/fro_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
31006,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2003/fro_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
31007,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2003/fro_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
31008,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2003/fro_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
31009,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2003/fro_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
31010,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2003/fro_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
31011,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2003/fro_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
31012,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2003/fro_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
31013,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2004/fro_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
31014,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2004/fro_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
31015,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2004/fro_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
31016,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2004/fro_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
31017,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2004/fro_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
31018,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2004/fro_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
31019,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2004/fro_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
31020,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2004/fro_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
31021,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2005/fro_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
31022,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2005/fro_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
31023,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2005/fro_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
31024,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2005/fro_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
31025,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2005/fro_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
31026,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2005/fro_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
31027,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2005/fro_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
31028,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2005/fro_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
31029,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2006/fro_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
31030,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2006/fro_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
31031,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2006/fro_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
31032,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2006/fro_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
31033,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2006/fro_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
31034,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2006/fro_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
31035,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2006/fro_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
31036,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2006/fro_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
31037,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2007/fro_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
31038,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2007/fro_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
31039,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2007/fro_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
31040,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2007/fro_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
31041,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2007/fro_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
31042,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2007/fro_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
31043,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2007/fro_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
31044,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2007/fro_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
31045,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2008/fro_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
31046,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2008/fro_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
31047,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2008/fro_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
31048,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2008/fro_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
31049,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2008/fro_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
31050,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2008/fro_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
31051,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2008/fro_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
31052,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2008/fro_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
31053,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2009/fro_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
31054,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2009/fro_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
31055,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2009/fro_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
31056,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2009/fro_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
31057,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2009/fro_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
31058,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2009/fro_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
31059,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2009/fro_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
31060,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2009/fro_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
31061,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2010/fro_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
31062,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2010/fro_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
31063,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2010/fro_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
31064,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2010/fro_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
31065,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2010/fro_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
31066,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2010/fro_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
31067,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2010/fro_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
31068,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2010/fro_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
31069,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2011/fro_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
31070,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2011/fro_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
31071,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2011/fro_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
31072,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2011/fro_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
31073,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2011/fro_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
31074,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2011/fro_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
31075,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2011/fro_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
31076,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2011/fro_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
31077,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2012/fro_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
31078,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2012/fro_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
31079,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2012/fro_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
31080,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2012/fro_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
31081,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2012/fro_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
31082,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2012/fro_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
31083,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2012/fro_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
31084,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2012/fro_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
31085,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2013/fro_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
31086,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2013/fro_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
31087,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2013/fro_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
31088,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2013/fro_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
31089,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2013/fro_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
31090,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2013/fro_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
31091,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2013/fro_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
31092,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2013/fro_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
31093,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2014/fro_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
31094,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2014/fro_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
31095,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2014/fro_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
31096,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2014/fro_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
31097,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2014/fro_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
31098,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2014/fro_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
31099,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2014/fro_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
31100,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2014/fro_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
31101,234,"FRO","Faroe Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2015/fro_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
31102,234,"FRO","Faroe Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2015/fro_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
31103,234,"FRO","Faroe Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2015/fro_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
31104,234,"FRO","Faroe Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2015/fro_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
31105,234,"FRO","Faroe Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2015/fro_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
31106,234,"FRO","Faroe Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2015/fro_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
31107,234,"FRO","Faroe Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2015/fro_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
31108,234,"FRO","Faroe Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Annual/2015/fro_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
31109,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2000/flk_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
31110,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2000/flk_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
31111,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2000/flk_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
31112,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2000/flk_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
31113,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2000/flk_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
31114,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2000/flk_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
31115,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2000/flk_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
31116,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2000/flk_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
31117,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2001/flk_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
31118,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2001/flk_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
31119,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2001/flk_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
31120,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2001/flk_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
31121,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2001/flk_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
31122,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2001/flk_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
31123,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2001/flk_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
31124,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2001/flk_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
31125,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2002/flk_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
31126,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2002/flk_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
31127,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2002/flk_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
31128,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2002/flk_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
31129,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2002/flk_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
31130,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2002/flk_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
31131,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2002/flk_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
31132,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2002/flk_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
31133,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2003/flk_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
31134,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2003/flk_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
31135,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2003/flk_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
31136,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2003/flk_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
31137,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2003/flk_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
31138,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2003/flk_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
31139,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2003/flk_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
31140,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2003/flk_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
31141,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2004/flk_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
31142,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2004/flk_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
31143,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2004/flk_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
31144,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2004/flk_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
31145,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2004/flk_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
31146,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2004/flk_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
31147,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2004/flk_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
31148,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2004/flk_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
31149,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2005/flk_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
31150,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2005/flk_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
31151,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2005/flk_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
31152,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2005/flk_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
31153,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2005/flk_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
31154,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2005/flk_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
31155,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2005/flk_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
31156,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2005/flk_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
31157,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2006/flk_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
31158,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2006/flk_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
31159,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2006/flk_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
31160,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2006/flk_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
31161,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2006/flk_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
31162,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2006/flk_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
31163,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2006/flk_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
31164,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2006/flk_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
31165,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2007/flk_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
31166,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2007/flk_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
31167,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2007/flk_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
31168,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2007/flk_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
31169,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2007/flk_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
31170,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2007/flk_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
31171,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2007/flk_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
31172,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2007/flk_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
31173,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2008/flk_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
31174,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2008/flk_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
31175,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2008/flk_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
31176,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2008/flk_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
31177,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2008/flk_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
31178,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2008/flk_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
31179,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2008/flk_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
31180,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2008/flk_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
31181,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2009/flk_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
31182,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2009/flk_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
31183,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2009/flk_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
31184,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2009/flk_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
31185,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2009/flk_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
31186,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2009/flk_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
31187,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2009/flk_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
31188,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2009/flk_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
31189,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2010/flk_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
31190,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2010/flk_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
31191,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2010/flk_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
31192,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2010/flk_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
31193,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2010/flk_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
31194,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2010/flk_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
31195,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2010/flk_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
31196,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2010/flk_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
31197,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2011/flk_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
31198,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2011/flk_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
31199,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2011/flk_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
31200,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2011/flk_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
31201,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2011/flk_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
31202,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2011/flk_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
31203,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2011/flk_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
31204,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2011/flk_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
31205,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2012/flk_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
31206,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2012/flk_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
31207,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2012/flk_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
31208,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2012/flk_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
31209,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2012/flk_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
31210,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2012/flk_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
31211,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2012/flk_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
31212,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2012/flk_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
31213,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2013/flk_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
31214,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2013/flk_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
31215,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2013/flk_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
31216,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2013/flk_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
31217,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2013/flk_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
31218,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2013/flk_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
31219,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2013/flk_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
31220,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2013/flk_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
31221,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2014/flk_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
31222,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2014/flk_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
31223,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2014/flk_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
31224,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2014/flk_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
31225,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2014/flk_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
31226,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2014/flk_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
31227,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2014/flk_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
31228,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2014/flk_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
31229,238,"FLK","Falkland Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2015/flk_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
31230,238,"FLK","Falkland Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2015/flk_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
31231,238,"FLK","Falkland Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2015/flk_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
31232,238,"FLK","Falkland Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2015/flk_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
31233,238,"FLK","Falkland Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2015/flk_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
31234,238,"FLK","Falkland Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2015/flk_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
31235,238,"FLK","Falkland Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2015/flk_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
31236,238,"FLK","Falkland Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Annual/2015/flk_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
31237,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2000/sgs_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
31238,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2000/sgs_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
31239,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2000/sgs_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
31240,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2000/sgs_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
31241,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2000/sgs_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
31242,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2000/sgs_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
31243,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2000/sgs_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
31244,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2000/sgs_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
31245,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2001/sgs_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
31246,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2001/sgs_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
31247,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2001/sgs_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
31248,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2001/sgs_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
31249,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2001/sgs_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
31250,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2001/sgs_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
31251,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2001/sgs_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
31252,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2001/sgs_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
31253,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2002/sgs_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
31254,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2002/sgs_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
31255,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2002/sgs_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
31256,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2002/sgs_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
31257,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2002/sgs_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
31258,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2002/sgs_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
31259,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2002/sgs_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
31260,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2002/sgs_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
31261,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2003/sgs_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
31262,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2003/sgs_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
31263,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2003/sgs_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
31264,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2003/sgs_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
31265,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2003/sgs_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
31266,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2003/sgs_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
31267,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2003/sgs_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
31268,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2003/sgs_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
31269,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2004/sgs_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
31270,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2004/sgs_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
31271,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2004/sgs_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
31272,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2004/sgs_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
31273,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2004/sgs_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
31274,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2004/sgs_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
31275,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2004/sgs_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
31276,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2004/sgs_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
31277,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2005/sgs_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
31278,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2005/sgs_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
31279,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2005/sgs_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
31280,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2005/sgs_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
31281,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2005/sgs_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
31282,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2005/sgs_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
31283,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2005/sgs_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
31284,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2005/sgs_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
31285,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2006/sgs_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
31286,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2006/sgs_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
31287,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2006/sgs_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
31288,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2006/sgs_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
31289,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2006/sgs_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
31290,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2006/sgs_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
31291,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2006/sgs_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
31292,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2006/sgs_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
31293,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2007/sgs_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
31294,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2007/sgs_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
31295,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2007/sgs_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
31296,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2007/sgs_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
31297,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2007/sgs_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
31298,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2007/sgs_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
31299,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2007/sgs_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
31300,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2007/sgs_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
31301,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2008/sgs_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
31302,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2008/sgs_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
31303,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2008/sgs_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
31304,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2008/sgs_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
31305,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2008/sgs_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
31306,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2008/sgs_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
31307,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2008/sgs_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
31308,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2008/sgs_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
31309,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2009/sgs_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
31310,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2009/sgs_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
31311,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2009/sgs_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
31312,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2009/sgs_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
31313,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2009/sgs_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
31314,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2009/sgs_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
31315,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2009/sgs_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
31316,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2009/sgs_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
31317,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2010/sgs_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
31318,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2010/sgs_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
31319,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2010/sgs_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
31320,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2010/sgs_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
31321,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2010/sgs_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
31322,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2010/sgs_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
31323,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2010/sgs_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
31324,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2010/sgs_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
31325,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2011/sgs_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
31326,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2011/sgs_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
31327,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2011/sgs_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
31328,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2011/sgs_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
31329,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2011/sgs_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
31330,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2011/sgs_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
31331,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2011/sgs_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
31332,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2011/sgs_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
31333,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2012/sgs_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
31334,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2012/sgs_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
31335,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2012/sgs_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
31336,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2012/sgs_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
31337,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2012/sgs_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
31338,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2012/sgs_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
31339,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2012/sgs_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
31340,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2012/sgs_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
31341,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2013/sgs_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
31342,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2013/sgs_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
31343,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2013/sgs_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
31344,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2013/sgs_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
31345,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2013/sgs_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
31346,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2013/sgs_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
31347,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2013/sgs_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
31348,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2013/sgs_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
31349,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2014/sgs_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
31350,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2014/sgs_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
31351,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2014/sgs_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
31352,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2014/sgs_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
31353,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2014/sgs_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
31354,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2014/sgs_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
31355,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2014/sgs_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
31356,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2014/sgs_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
31357,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2015/sgs_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
31358,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2015/sgs_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
31359,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2015/sgs_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
31360,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2015/sgs_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
31361,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2015/sgs_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
31362,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2015/sgs_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
31363,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2015/sgs_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
31364,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Annual/2015/sgs_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
31365,242,"FJI","Fiji","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2000/fji_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
31366,242,"FJI","Fiji","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2000/fji_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
31367,242,"FJI","Fiji","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2000/fji_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
31368,242,"FJI","Fiji","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2000/fji_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
31369,242,"FJI","Fiji","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2000/fji_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
31370,242,"FJI","Fiji","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2000/fji_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
31371,242,"FJI","Fiji","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2000/fji_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
31372,242,"FJI","Fiji","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2000/fji_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
31373,242,"FJI","Fiji","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2001/fji_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
31374,242,"FJI","Fiji","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2001/fji_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
31375,242,"FJI","Fiji","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2001/fji_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
31376,242,"FJI","Fiji","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2001/fji_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
31377,242,"FJI","Fiji","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2001/fji_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
31378,242,"FJI","Fiji","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2001/fji_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
31379,242,"FJI","Fiji","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2001/fji_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
31380,242,"FJI","Fiji","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2001/fji_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
31381,242,"FJI","Fiji","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2002/fji_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
31382,242,"FJI","Fiji","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2002/fji_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
31383,242,"FJI","Fiji","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2002/fji_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
31384,242,"FJI","Fiji","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2002/fji_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
31385,242,"FJI","Fiji","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2002/fji_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
31386,242,"FJI","Fiji","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2002/fji_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
31387,242,"FJI","Fiji","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2002/fji_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
31388,242,"FJI","Fiji","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2002/fji_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
31389,242,"FJI","Fiji","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2003/fji_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
31390,242,"FJI","Fiji","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2003/fji_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
31391,242,"FJI","Fiji","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2003/fji_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
31392,242,"FJI","Fiji","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2003/fji_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
31393,242,"FJI","Fiji","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2003/fji_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
31394,242,"FJI","Fiji","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2003/fji_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
31395,242,"FJI","Fiji","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2003/fji_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
31396,242,"FJI","Fiji","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2003/fji_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
31397,242,"FJI","Fiji","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2004/fji_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
31398,242,"FJI","Fiji","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2004/fji_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
31399,242,"FJI","Fiji","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2004/fji_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
31400,242,"FJI","Fiji","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2004/fji_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
31401,242,"FJI","Fiji","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2004/fji_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
31402,242,"FJI","Fiji","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2004/fji_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
31403,242,"FJI","Fiji","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2004/fji_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
31404,242,"FJI","Fiji","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2004/fji_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
31405,242,"FJI","Fiji","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2005/fji_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
31406,242,"FJI","Fiji","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2005/fji_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
31407,242,"FJI","Fiji","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2005/fji_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
31408,242,"FJI","Fiji","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2005/fji_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
31409,242,"FJI","Fiji","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2005/fji_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
31410,242,"FJI","Fiji","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2005/fji_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
31411,242,"FJI","Fiji","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2005/fji_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
31412,242,"FJI","Fiji","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2005/fji_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
31413,242,"FJI","Fiji","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2006/fji_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
31414,242,"FJI","Fiji","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2006/fji_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
31415,242,"FJI","Fiji","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2006/fji_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
31416,242,"FJI","Fiji","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2006/fji_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
31417,242,"FJI","Fiji","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2006/fji_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
31418,242,"FJI","Fiji","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2006/fji_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
31419,242,"FJI","Fiji","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2006/fji_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
31420,242,"FJI","Fiji","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2006/fji_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
31421,242,"FJI","Fiji","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2007/fji_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
31422,242,"FJI","Fiji","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2007/fji_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
31423,242,"FJI","Fiji","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2007/fji_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
31424,242,"FJI","Fiji","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2007/fji_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
31425,242,"FJI","Fiji","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2007/fji_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
31426,242,"FJI","Fiji","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2007/fji_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
31427,242,"FJI","Fiji","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2007/fji_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
31428,242,"FJI","Fiji","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2007/fji_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
31429,242,"FJI","Fiji","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2008/fji_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
31430,242,"FJI","Fiji","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2008/fji_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
31431,242,"FJI","Fiji","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2008/fji_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
31432,242,"FJI","Fiji","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2008/fji_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
31433,242,"FJI","Fiji","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2008/fji_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
31434,242,"FJI","Fiji","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2008/fji_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
31435,242,"FJI","Fiji","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2008/fji_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
31436,242,"FJI","Fiji","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2008/fji_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
31437,242,"FJI","Fiji","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2009/fji_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
31438,242,"FJI","Fiji","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2009/fji_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
31439,242,"FJI","Fiji","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2009/fji_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
31440,242,"FJI","Fiji","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2009/fji_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
31441,242,"FJI","Fiji","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2009/fji_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
31442,242,"FJI","Fiji","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2009/fji_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
31443,242,"FJI","Fiji","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2009/fji_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
31444,242,"FJI","Fiji","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2009/fji_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
31445,242,"FJI","Fiji","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2010/fji_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
31446,242,"FJI","Fiji","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2010/fji_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
31447,242,"FJI","Fiji","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2010/fji_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
31448,242,"FJI","Fiji","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2010/fji_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
31449,242,"FJI","Fiji","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2010/fji_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
31450,242,"FJI","Fiji","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2010/fji_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
31451,242,"FJI","Fiji","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2010/fji_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
31452,242,"FJI","Fiji","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2010/fji_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
31453,242,"FJI","Fiji","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2011/fji_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
31454,242,"FJI","Fiji","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2011/fji_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
31455,242,"FJI","Fiji","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2011/fji_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
31456,242,"FJI","Fiji","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2011/fji_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
31457,242,"FJI","Fiji","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2011/fji_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
31458,242,"FJI","Fiji","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2011/fji_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
31459,242,"FJI","Fiji","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2011/fji_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
31460,242,"FJI","Fiji","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2011/fji_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
31461,242,"FJI","Fiji","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2012/fji_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
31462,242,"FJI","Fiji","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2012/fji_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
31463,242,"FJI","Fiji","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2012/fji_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
31464,242,"FJI","Fiji","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2012/fji_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
31465,242,"FJI","Fiji","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2012/fji_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
31466,242,"FJI","Fiji","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2012/fji_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
31467,242,"FJI","Fiji","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2012/fji_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
31468,242,"FJI","Fiji","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2012/fji_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
31469,242,"FJI","Fiji","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2013/fji_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
31470,242,"FJI","Fiji","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2013/fji_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
31471,242,"FJI","Fiji","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2013/fji_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
31472,242,"FJI","Fiji","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2013/fji_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
31473,242,"FJI","Fiji","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2013/fji_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
31474,242,"FJI","Fiji","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2013/fji_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
31475,242,"FJI","Fiji","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2013/fji_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
31476,242,"FJI","Fiji","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2013/fji_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
31477,242,"FJI","Fiji","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2014/fji_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
31478,242,"FJI","Fiji","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2014/fji_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
31479,242,"FJI","Fiji","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2014/fji_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
31480,242,"FJI","Fiji","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2014/fji_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
31481,242,"FJI","Fiji","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2014/fji_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
31482,242,"FJI","Fiji","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2014/fji_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
31483,242,"FJI","Fiji","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2014/fji_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
31484,242,"FJI","Fiji","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2014/fji_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
31485,242,"FJI","Fiji","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2015/fji_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
31486,242,"FJI","Fiji","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2015/fji_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
31487,242,"FJI","Fiji","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2015/fji_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
31488,242,"FJI","Fiji","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2015/fji_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
31489,242,"FJI","Fiji","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2015/fji_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
31490,242,"FJI","Fiji","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2015/fji_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
31491,242,"FJI","Fiji","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2015/fji_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
31492,242,"FJI","Fiji","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Annual/2015/fji_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
31493,246,"FIN","Finland","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2000/fin_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
31494,246,"FIN","Finland","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2000/fin_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
31495,246,"FIN","Finland","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2000/fin_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
31496,246,"FIN","Finland","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2000/fin_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
31497,246,"FIN","Finland","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2000/fin_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
31498,246,"FIN","Finland","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2000/fin_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
31499,246,"FIN","Finland","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2000/fin_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
31500,246,"FIN","Finland","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2000/fin_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
31501,246,"FIN","Finland","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2001/fin_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
31502,246,"FIN","Finland","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2001/fin_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
31503,246,"FIN","Finland","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2001/fin_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
31504,246,"FIN","Finland","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2001/fin_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
31505,246,"FIN","Finland","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2001/fin_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
31506,246,"FIN","Finland","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2001/fin_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
31507,246,"FIN","Finland","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2001/fin_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
31508,246,"FIN","Finland","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2001/fin_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
31509,246,"FIN","Finland","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2002/fin_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
31510,246,"FIN","Finland","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2002/fin_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
31511,246,"FIN","Finland","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2002/fin_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
31512,246,"FIN","Finland","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2002/fin_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
31513,246,"FIN","Finland","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2002/fin_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
31514,246,"FIN","Finland","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2002/fin_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
31515,246,"FIN","Finland","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2002/fin_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
31516,246,"FIN","Finland","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2002/fin_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
31517,246,"FIN","Finland","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2003/fin_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
31518,246,"FIN","Finland","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2003/fin_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
31519,246,"FIN","Finland","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2003/fin_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
31520,246,"FIN","Finland","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2003/fin_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
31521,246,"FIN","Finland","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2003/fin_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
31522,246,"FIN","Finland","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2003/fin_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
31523,246,"FIN","Finland","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2003/fin_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
31524,246,"FIN","Finland","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2003/fin_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
31525,246,"FIN","Finland","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2004/fin_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
31526,246,"FIN","Finland","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2004/fin_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
31527,246,"FIN","Finland","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2004/fin_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
31528,246,"FIN","Finland","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2004/fin_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
31529,246,"FIN","Finland","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2004/fin_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
31530,246,"FIN","Finland","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2004/fin_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
31531,246,"FIN","Finland","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2004/fin_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
31532,246,"FIN","Finland","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2004/fin_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
31533,246,"FIN","Finland","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2005/fin_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
31534,246,"FIN","Finland","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2005/fin_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
31535,246,"FIN","Finland","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2005/fin_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
31536,246,"FIN","Finland","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2005/fin_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
31537,246,"FIN","Finland","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2005/fin_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
31538,246,"FIN","Finland","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2005/fin_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
31539,246,"FIN","Finland","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2005/fin_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
31540,246,"FIN","Finland","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2005/fin_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
31541,246,"FIN","Finland","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2006/fin_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
31542,246,"FIN","Finland","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2006/fin_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
31543,246,"FIN","Finland","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2006/fin_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
31544,246,"FIN","Finland","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2006/fin_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
31545,246,"FIN","Finland","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2006/fin_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
31546,246,"FIN","Finland","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2006/fin_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
31547,246,"FIN","Finland","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2006/fin_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
31548,246,"FIN","Finland","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2006/fin_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
31549,246,"FIN","Finland","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2007/fin_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
31550,246,"FIN","Finland","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2007/fin_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
31551,246,"FIN","Finland","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2007/fin_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
31552,246,"FIN","Finland","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2007/fin_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
31553,246,"FIN","Finland","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2007/fin_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
31554,246,"FIN","Finland","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2007/fin_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
31555,246,"FIN","Finland","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2007/fin_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
31556,246,"FIN","Finland","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2007/fin_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
31557,246,"FIN","Finland","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2008/fin_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
31558,246,"FIN","Finland","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2008/fin_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
31559,246,"FIN","Finland","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2008/fin_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
31560,246,"FIN","Finland","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2008/fin_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
31561,246,"FIN","Finland","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2008/fin_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
31562,246,"FIN","Finland","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2008/fin_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
31563,246,"FIN","Finland","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2008/fin_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
31564,246,"FIN","Finland","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2008/fin_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
31565,246,"FIN","Finland","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2009/fin_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
31566,246,"FIN","Finland","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2009/fin_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
31567,246,"FIN","Finland","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2009/fin_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
31568,246,"FIN","Finland","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2009/fin_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
31569,246,"FIN","Finland","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2009/fin_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
31570,246,"FIN","Finland","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2009/fin_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
31571,246,"FIN","Finland","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2009/fin_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
31572,246,"FIN","Finland","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2009/fin_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
31573,246,"FIN","Finland","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2010/fin_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
31574,246,"FIN","Finland","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2010/fin_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
31575,246,"FIN","Finland","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2010/fin_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
31576,246,"FIN","Finland","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2010/fin_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
31577,246,"FIN","Finland","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2010/fin_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
31578,246,"FIN","Finland","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2010/fin_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
31579,246,"FIN","Finland","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2010/fin_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
31580,246,"FIN","Finland","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2010/fin_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
31581,246,"FIN","Finland","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2011/fin_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
31582,246,"FIN","Finland","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2011/fin_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
31583,246,"FIN","Finland","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2011/fin_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
31584,246,"FIN","Finland","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2011/fin_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
31585,246,"FIN","Finland","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2011/fin_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
31586,246,"FIN","Finland","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2011/fin_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
31587,246,"FIN","Finland","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2011/fin_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
31588,246,"FIN","Finland","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2011/fin_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
31589,246,"FIN","Finland","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2012/fin_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
31590,246,"FIN","Finland","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2012/fin_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
31591,246,"FIN","Finland","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2012/fin_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
31592,246,"FIN","Finland","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2012/fin_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
31593,246,"FIN","Finland","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2012/fin_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
31594,246,"FIN","Finland","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2012/fin_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
31595,246,"FIN","Finland","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2012/fin_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
31596,246,"FIN","Finland","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2012/fin_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
31597,246,"FIN","Finland","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2013/fin_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
31598,246,"FIN","Finland","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2013/fin_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
31599,246,"FIN","Finland","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2013/fin_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
31600,246,"FIN","Finland","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2013/fin_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
31601,246,"FIN","Finland","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2013/fin_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
31602,246,"FIN","Finland","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2013/fin_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
31603,246,"FIN","Finland","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2013/fin_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
31604,246,"FIN","Finland","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2013/fin_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
31605,246,"FIN","Finland","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2014/fin_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
31606,246,"FIN","Finland","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2014/fin_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
31607,246,"FIN","Finland","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2014/fin_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
31608,246,"FIN","Finland","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2014/fin_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
31609,246,"FIN","Finland","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2014/fin_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
31610,246,"FIN","Finland","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2014/fin_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
31611,246,"FIN","Finland","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2014/fin_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
31612,246,"FIN","Finland","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2014/fin_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
31613,246,"FIN","Finland","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2015/fin_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
31614,246,"FIN","Finland","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2015/fin_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
31615,246,"FIN","Finland","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2015/fin_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
31616,246,"FIN","Finland","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2015/fin_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
31617,246,"FIN","Finland","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2015/fin_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
31618,246,"FIN","Finland","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2015/fin_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
31619,246,"FIN","Finland","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2015/fin_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
31620,246,"FIN","Finland","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Annual/2015/fin_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
31621,248,"ALA","Aland Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2000/ala_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
31622,248,"ALA","Aland Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2000/ala_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
31623,248,"ALA","Aland Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2000/ala_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
31624,248,"ALA","Aland Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2000/ala_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
31625,248,"ALA","Aland Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2000/ala_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
31626,248,"ALA","Aland Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2000/ala_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
31627,248,"ALA","Aland Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2000/ala_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
31628,248,"ALA","Aland Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2000/ala_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
31629,248,"ALA","Aland Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2001/ala_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
31630,248,"ALA","Aland Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2001/ala_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
31631,248,"ALA","Aland Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2001/ala_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
31632,248,"ALA","Aland Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2001/ala_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
31633,248,"ALA","Aland Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2001/ala_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
31634,248,"ALA","Aland Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2001/ala_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
31635,248,"ALA","Aland Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2001/ala_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
31636,248,"ALA","Aland Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2001/ala_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
31637,248,"ALA","Aland Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2002/ala_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
31638,248,"ALA","Aland Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2002/ala_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
31639,248,"ALA","Aland Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2002/ala_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
31640,248,"ALA","Aland Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2002/ala_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
31641,248,"ALA","Aland Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2002/ala_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
31642,248,"ALA","Aland Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2002/ala_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
31643,248,"ALA","Aland Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2002/ala_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
31644,248,"ALA","Aland Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2002/ala_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
31645,248,"ALA","Aland Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2003/ala_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
31646,248,"ALA","Aland Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2003/ala_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
31647,248,"ALA","Aland Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2003/ala_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
31648,248,"ALA","Aland Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2003/ala_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
31649,248,"ALA","Aland Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2003/ala_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
31650,248,"ALA","Aland Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2003/ala_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
31651,248,"ALA","Aland Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2003/ala_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
31652,248,"ALA","Aland Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2003/ala_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
31653,248,"ALA","Aland Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2004/ala_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
31654,248,"ALA","Aland Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2004/ala_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
31655,248,"ALA","Aland Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2004/ala_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
31656,248,"ALA","Aland Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2004/ala_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
31657,248,"ALA","Aland Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2004/ala_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
31658,248,"ALA","Aland Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2004/ala_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
31659,248,"ALA","Aland Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2004/ala_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
31660,248,"ALA","Aland Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2004/ala_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
31661,248,"ALA","Aland Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2005/ala_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
31662,248,"ALA","Aland Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2005/ala_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
31663,248,"ALA","Aland Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2005/ala_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
31664,248,"ALA","Aland Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2005/ala_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
31665,248,"ALA","Aland Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2005/ala_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
31666,248,"ALA","Aland Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2005/ala_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
31667,248,"ALA","Aland Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2005/ala_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
31668,248,"ALA","Aland Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2005/ala_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
31669,248,"ALA","Aland Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2006/ala_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
31670,248,"ALA","Aland Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2006/ala_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
31671,248,"ALA","Aland Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2006/ala_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
31672,248,"ALA","Aland Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2006/ala_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
31673,248,"ALA","Aland Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2006/ala_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
31674,248,"ALA","Aland Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2006/ala_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
31675,248,"ALA","Aland Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2006/ala_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
31676,248,"ALA","Aland Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2006/ala_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
31677,248,"ALA","Aland Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2007/ala_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
31678,248,"ALA","Aland Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2007/ala_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
31679,248,"ALA","Aland Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2007/ala_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
31680,248,"ALA","Aland Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2007/ala_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
31681,248,"ALA","Aland Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2007/ala_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
31682,248,"ALA","Aland Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2007/ala_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
31683,248,"ALA","Aland Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2007/ala_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
31684,248,"ALA","Aland Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2007/ala_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
31685,248,"ALA","Aland Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2008/ala_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
31686,248,"ALA","Aland Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2008/ala_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
31687,248,"ALA","Aland Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2008/ala_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
31688,248,"ALA","Aland Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2008/ala_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
31689,248,"ALA","Aland Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2008/ala_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
31690,248,"ALA","Aland Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2008/ala_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
31691,248,"ALA","Aland Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2008/ala_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
31692,248,"ALA","Aland Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2008/ala_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
31693,248,"ALA","Aland Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2009/ala_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
31694,248,"ALA","Aland Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2009/ala_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
31695,248,"ALA","Aland Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2009/ala_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
31696,248,"ALA","Aland Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2009/ala_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
31697,248,"ALA","Aland Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2009/ala_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
31698,248,"ALA","Aland Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2009/ala_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
31699,248,"ALA","Aland Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2009/ala_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
31700,248,"ALA","Aland Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2009/ala_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
31701,248,"ALA","Aland Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2010/ala_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
31702,248,"ALA","Aland Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2010/ala_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
31703,248,"ALA","Aland Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2010/ala_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
31704,248,"ALA","Aland Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2010/ala_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
31705,248,"ALA","Aland Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2010/ala_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
31706,248,"ALA","Aland Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2010/ala_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
31707,248,"ALA","Aland Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2010/ala_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
31708,248,"ALA","Aland Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2010/ala_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
31709,248,"ALA","Aland Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2011/ala_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
31710,248,"ALA","Aland Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2011/ala_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
31711,248,"ALA","Aland Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2011/ala_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
31712,248,"ALA","Aland Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2011/ala_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
31713,248,"ALA","Aland Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2011/ala_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
31714,248,"ALA","Aland Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2011/ala_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
31715,248,"ALA","Aland Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2011/ala_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
31716,248,"ALA","Aland Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2011/ala_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
31717,248,"ALA","Aland Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2012/ala_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
31718,248,"ALA","Aland Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2012/ala_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
31719,248,"ALA","Aland Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2012/ala_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
31720,248,"ALA","Aland Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2012/ala_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
31721,248,"ALA","Aland Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2012/ala_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
31722,248,"ALA","Aland Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2012/ala_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
31723,248,"ALA","Aland Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2012/ala_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
31724,248,"ALA","Aland Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2012/ala_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
31725,248,"ALA","Aland Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2013/ala_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
31726,248,"ALA","Aland Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2013/ala_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
31727,248,"ALA","Aland Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2013/ala_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
31728,248,"ALA","Aland Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2013/ala_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
31729,248,"ALA","Aland Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2013/ala_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
31730,248,"ALA","Aland Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2013/ala_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
31731,248,"ALA","Aland Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2013/ala_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
31732,248,"ALA","Aland Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2013/ala_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
31733,248,"ALA","Aland Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2014/ala_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
31734,248,"ALA","Aland Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2014/ala_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
31735,248,"ALA","Aland Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2014/ala_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
31736,248,"ALA","Aland Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2014/ala_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
31737,248,"ALA","Aland Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2014/ala_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
31738,248,"ALA","Aland Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2014/ala_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
31739,248,"ALA","Aland Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2014/ala_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
31740,248,"ALA","Aland Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2014/ala_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
31741,248,"ALA","Aland Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2015/ala_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
31742,248,"ALA","Aland Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2015/ala_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
31743,248,"ALA","Aland Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2015/ala_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
31744,248,"ALA","Aland Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2015/ala_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
31745,248,"ALA","Aland Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2015/ala_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
31746,248,"ALA","Aland Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2015/ala_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
31747,248,"ALA","Aland Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2015/ala_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
31748,248,"ALA","Aland Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Annual/2015/ala_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
31749,250,"FRA","France","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2000/fra_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
31750,250,"FRA","France","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2000/fra_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
31751,250,"FRA","France","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2000/fra_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
31752,250,"FRA","France","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2000/fra_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
31753,250,"FRA","France","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2000/fra_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
31754,250,"FRA","France","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2000/fra_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
31755,250,"FRA","France","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2000/fra_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
31756,250,"FRA","France","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2000/fra_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
31757,250,"FRA","France","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2001/fra_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
31758,250,"FRA","France","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2001/fra_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
31759,250,"FRA","France","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2001/fra_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
31760,250,"FRA","France","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2001/fra_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
31761,250,"FRA","France","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2001/fra_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
31762,250,"FRA","France","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2001/fra_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
31763,250,"FRA","France","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2001/fra_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
31764,250,"FRA","France","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2001/fra_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
31765,250,"FRA","France","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2002/fra_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
31766,250,"FRA","France","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2002/fra_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
31767,250,"FRA","France","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2002/fra_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
31768,250,"FRA","France","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2002/fra_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
31769,250,"FRA","France","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2002/fra_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
31770,250,"FRA","France","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2002/fra_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
31771,250,"FRA","France","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2002/fra_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
31772,250,"FRA","France","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2002/fra_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
31773,250,"FRA","France","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2003/fra_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
31774,250,"FRA","France","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2003/fra_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
31775,250,"FRA","France","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2003/fra_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
31776,250,"FRA","France","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2003/fra_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
31777,250,"FRA","France","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2003/fra_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
31778,250,"FRA","France","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2003/fra_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
31779,250,"FRA","France","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2003/fra_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
31780,250,"FRA","France","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2003/fra_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
31781,250,"FRA","France","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2004/fra_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
31782,250,"FRA","France","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2004/fra_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
31783,250,"FRA","France","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2004/fra_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
31784,250,"FRA","France","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2004/fra_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
31785,250,"FRA","France","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2004/fra_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
31786,250,"FRA","France","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2004/fra_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
31787,250,"FRA","France","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2004/fra_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
31788,250,"FRA","France","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2004/fra_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
31789,250,"FRA","France","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2005/fra_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
31790,250,"FRA","France","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2005/fra_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
31791,250,"FRA","France","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2005/fra_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
31792,250,"FRA","France","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2005/fra_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
31793,250,"FRA","France","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2005/fra_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
31794,250,"FRA","France","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2005/fra_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
31795,250,"FRA","France","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2005/fra_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
31796,250,"FRA","France","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2005/fra_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
31797,250,"FRA","France","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2006/fra_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
31798,250,"FRA","France","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2006/fra_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
31799,250,"FRA","France","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2006/fra_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
31800,250,"FRA","France","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2006/fra_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
31801,250,"FRA","France","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2006/fra_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
31802,250,"FRA","France","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2006/fra_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
31803,250,"FRA","France","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2006/fra_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
31804,250,"FRA","France","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2006/fra_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
31805,250,"FRA","France","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2007/fra_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
31806,250,"FRA","France","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2007/fra_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
31807,250,"FRA","France","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2007/fra_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
31808,250,"FRA","France","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2007/fra_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
31809,250,"FRA","France","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2007/fra_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
31810,250,"FRA","France","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2007/fra_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
31811,250,"FRA","France","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2007/fra_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
31812,250,"FRA","France","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2007/fra_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
31813,250,"FRA","France","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2008/fra_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
31814,250,"FRA","France","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2008/fra_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
31815,250,"FRA","France","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2008/fra_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
31816,250,"FRA","France","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2008/fra_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
31817,250,"FRA","France","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2008/fra_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
31818,250,"FRA","France","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2008/fra_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
31819,250,"FRA","France","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2008/fra_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
31820,250,"FRA","France","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2008/fra_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
31821,250,"FRA","France","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2009/fra_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
31822,250,"FRA","France","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2009/fra_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
31823,250,"FRA","France","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2009/fra_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
31824,250,"FRA","France","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2009/fra_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
31825,250,"FRA","France","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2009/fra_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
31826,250,"FRA","France","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2009/fra_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
31827,250,"FRA","France","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2009/fra_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
31828,250,"FRA","France","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2009/fra_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
31829,250,"FRA","France","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2010/fra_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
31830,250,"FRA","France","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2010/fra_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
31831,250,"FRA","France","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2010/fra_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
31832,250,"FRA","France","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2010/fra_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
31833,250,"FRA","France","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2010/fra_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
31834,250,"FRA","France","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2010/fra_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
31835,250,"FRA","France","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2010/fra_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
31836,250,"FRA","France","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2010/fra_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
31837,250,"FRA","France","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2011/fra_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
31838,250,"FRA","France","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2011/fra_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
31839,250,"FRA","France","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2011/fra_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
31840,250,"FRA","France","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2011/fra_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
31841,250,"FRA","France","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2011/fra_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
31842,250,"FRA","France","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2011/fra_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
31843,250,"FRA","France","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2011/fra_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
31844,250,"FRA","France","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2011/fra_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
31845,250,"FRA","France","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2012/fra_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
31846,250,"FRA","France","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2012/fra_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
31847,250,"FRA","France","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2012/fra_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
31848,250,"FRA","France","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2012/fra_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
31849,250,"FRA","France","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2012/fra_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
31850,250,"FRA","France","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2012/fra_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
31851,250,"FRA","France","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2012/fra_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
31852,250,"FRA","France","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2012/fra_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
31853,250,"FRA","France","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2013/fra_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
31854,250,"FRA","France","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2013/fra_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
31855,250,"FRA","France","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2013/fra_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
31856,250,"FRA","France","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2013/fra_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
31857,250,"FRA","France","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2013/fra_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
31858,250,"FRA","France","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2013/fra_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
31859,250,"FRA","France","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2013/fra_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
31860,250,"FRA","France","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2013/fra_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
31861,250,"FRA","France","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2014/fra_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
31862,250,"FRA","France","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2014/fra_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
31863,250,"FRA","France","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2014/fra_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
31864,250,"FRA","France","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2014/fra_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
31865,250,"FRA","France","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2014/fra_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
31866,250,"FRA","France","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2014/fra_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
31867,250,"FRA","France","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2014/fra_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
31868,250,"FRA","France","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2014/fra_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
31869,250,"FRA","France","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2015/fra_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
31870,250,"FRA","France","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2015/fra_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
31871,250,"FRA","France","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2015/fra_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
31872,250,"FRA","France","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2015/fra_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
31873,250,"FRA","France","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2015/fra_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
31874,250,"FRA","France","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2015/fra_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
31875,250,"FRA","France","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2015/fra_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
31876,250,"FRA","France","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Annual/2015/fra_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
31877,254,"GUF","French Guiana","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2000/guf_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
31878,254,"GUF","French Guiana","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2000/guf_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
31879,254,"GUF","French Guiana","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2000/guf_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
31880,254,"GUF","French Guiana","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2000/guf_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
31881,254,"GUF","French Guiana","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2000/guf_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
31882,254,"GUF","French Guiana","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2000/guf_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
31883,254,"GUF","French Guiana","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2000/guf_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
31884,254,"GUF","French Guiana","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2000/guf_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
31885,254,"GUF","French Guiana","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2001/guf_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
31886,254,"GUF","French Guiana","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2001/guf_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
31887,254,"GUF","French Guiana","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2001/guf_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
31888,254,"GUF","French Guiana","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2001/guf_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
31889,254,"GUF","French Guiana","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2001/guf_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
31890,254,"GUF","French Guiana","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2001/guf_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
31891,254,"GUF","French Guiana","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2001/guf_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
31892,254,"GUF","French Guiana","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2001/guf_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
31893,254,"GUF","French Guiana","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2002/guf_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
31894,254,"GUF","French Guiana","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2002/guf_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
31895,254,"GUF","French Guiana","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2002/guf_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
31896,254,"GUF","French Guiana","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2002/guf_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
31897,254,"GUF","French Guiana","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2002/guf_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
31898,254,"GUF","French Guiana","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2002/guf_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
31899,254,"GUF","French Guiana","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2002/guf_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
31900,254,"GUF","French Guiana","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2002/guf_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
31901,254,"GUF","French Guiana","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2003/guf_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
31902,254,"GUF","French Guiana","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2003/guf_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
31903,254,"GUF","French Guiana","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2003/guf_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
31904,254,"GUF","French Guiana","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2003/guf_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
31905,254,"GUF","French Guiana","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2003/guf_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
31906,254,"GUF","French Guiana","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2003/guf_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
31907,254,"GUF","French Guiana","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2003/guf_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
31908,254,"GUF","French Guiana","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2003/guf_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
31909,254,"GUF","French Guiana","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2004/guf_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
31910,254,"GUF","French Guiana","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2004/guf_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
31911,254,"GUF","French Guiana","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2004/guf_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
31912,254,"GUF","French Guiana","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2004/guf_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
31913,254,"GUF","French Guiana","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2004/guf_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
31914,254,"GUF","French Guiana","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2004/guf_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
31915,254,"GUF","French Guiana","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2004/guf_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
31916,254,"GUF","French Guiana","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2004/guf_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
31917,254,"GUF","French Guiana","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2005/guf_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
31918,254,"GUF","French Guiana","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2005/guf_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
31919,254,"GUF","French Guiana","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2005/guf_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
31920,254,"GUF","French Guiana","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2005/guf_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
31921,254,"GUF","French Guiana","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2005/guf_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
31922,254,"GUF","French Guiana","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2005/guf_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
31923,254,"GUF","French Guiana","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2005/guf_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
31924,254,"GUF","French Guiana","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2005/guf_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
31925,254,"GUF","French Guiana","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2006/guf_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
31926,254,"GUF","French Guiana","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2006/guf_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
31927,254,"GUF","French Guiana","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2006/guf_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
31928,254,"GUF","French Guiana","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2006/guf_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
31929,254,"GUF","French Guiana","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2006/guf_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
31930,254,"GUF","French Guiana","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2006/guf_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
31931,254,"GUF","French Guiana","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2006/guf_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
31932,254,"GUF","French Guiana","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2006/guf_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
31933,254,"GUF","French Guiana","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2007/guf_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
31934,254,"GUF","French Guiana","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2007/guf_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
31935,254,"GUF","French Guiana","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2007/guf_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
31936,254,"GUF","French Guiana","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2007/guf_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
31937,254,"GUF","French Guiana","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2007/guf_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
31938,254,"GUF","French Guiana","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2007/guf_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
31939,254,"GUF","French Guiana","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2007/guf_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
31940,254,"GUF","French Guiana","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2007/guf_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
31941,254,"GUF","French Guiana","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2008/guf_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
31942,254,"GUF","French Guiana","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2008/guf_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
31943,254,"GUF","French Guiana","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2008/guf_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
31944,254,"GUF","French Guiana","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2008/guf_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
31945,254,"GUF","French Guiana","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2008/guf_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
31946,254,"GUF","French Guiana","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2008/guf_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
31947,254,"GUF","French Guiana","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2008/guf_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
31948,254,"GUF","French Guiana","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2008/guf_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
31949,254,"GUF","French Guiana","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2009/guf_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
31950,254,"GUF","French Guiana","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2009/guf_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
31951,254,"GUF","French Guiana","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2009/guf_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
31952,254,"GUF","French Guiana","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2009/guf_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
31953,254,"GUF","French Guiana","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2009/guf_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
31954,254,"GUF","French Guiana","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2009/guf_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
31955,254,"GUF","French Guiana","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2009/guf_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
31956,254,"GUF","French Guiana","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2009/guf_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
31957,254,"GUF","French Guiana","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2010/guf_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
31958,254,"GUF","French Guiana","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2010/guf_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
31959,254,"GUF","French Guiana","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2010/guf_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
31960,254,"GUF","French Guiana","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2010/guf_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
31961,254,"GUF","French Guiana","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2010/guf_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
31962,254,"GUF","French Guiana","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2010/guf_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
31963,254,"GUF","French Guiana","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2010/guf_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
31964,254,"GUF","French Guiana","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2010/guf_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
31965,254,"GUF","French Guiana","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2011/guf_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
31966,254,"GUF","French Guiana","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2011/guf_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
31967,254,"GUF","French Guiana","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2011/guf_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
31968,254,"GUF","French Guiana","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2011/guf_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
31969,254,"GUF","French Guiana","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2011/guf_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
31970,254,"GUF","French Guiana","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2011/guf_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
31971,254,"GUF","French Guiana","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2011/guf_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
31972,254,"GUF","French Guiana","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2011/guf_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
31973,254,"GUF","French Guiana","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2012/guf_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
31974,254,"GUF","French Guiana","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2012/guf_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
31975,254,"GUF","French Guiana","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2012/guf_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
31976,254,"GUF","French Guiana","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2012/guf_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
31977,254,"GUF","French Guiana","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2012/guf_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
31978,254,"GUF","French Guiana","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2012/guf_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
31979,254,"GUF","French Guiana","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2012/guf_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
31980,254,"GUF","French Guiana","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2012/guf_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
31981,254,"GUF","French Guiana","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2013/guf_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
31982,254,"GUF","French Guiana","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2013/guf_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
31983,254,"GUF","French Guiana","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2013/guf_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
31984,254,"GUF","French Guiana","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2013/guf_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
31985,254,"GUF","French Guiana","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2013/guf_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
31986,254,"GUF","French Guiana","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2013/guf_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
31987,254,"GUF","French Guiana","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2013/guf_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
31988,254,"GUF","French Guiana","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2013/guf_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
31989,254,"GUF","French Guiana","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2014/guf_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
31990,254,"GUF","French Guiana","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2014/guf_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
31991,254,"GUF","French Guiana","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2014/guf_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
31992,254,"GUF","French Guiana","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2014/guf_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
31993,254,"GUF","French Guiana","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2014/guf_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
31994,254,"GUF","French Guiana","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2014/guf_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
31995,254,"GUF","French Guiana","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2014/guf_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
31996,254,"GUF","French Guiana","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2014/guf_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
31997,254,"GUF","French Guiana","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2015/guf_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
31998,254,"GUF","French Guiana","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2015/guf_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
31999,254,"GUF","French Guiana","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2015/guf_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
32000,254,"GUF","French Guiana","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2015/guf_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
32001,254,"GUF","French Guiana","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2015/guf_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
32002,254,"GUF","French Guiana","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2015/guf_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
32003,254,"GUF","French Guiana","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2015/guf_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
32004,254,"GUF","French Guiana","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Annual/2015/guf_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
32005,258,"PYF","French Polynesia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2000/pyf_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
32006,258,"PYF","French Polynesia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2000/pyf_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
32007,258,"PYF","French Polynesia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2000/pyf_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
32008,258,"PYF","French Polynesia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2000/pyf_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
32009,258,"PYF","French Polynesia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2000/pyf_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
32010,258,"PYF","French Polynesia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2000/pyf_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
32011,258,"PYF","French Polynesia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2000/pyf_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
32012,258,"PYF","French Polynesia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2000/pyf_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
32013,258,"PYF","French Polynesia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2001/pyf_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
32014,258,"PYF","French Polynesia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2001/pyf_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
32015,258,"PYF","French Polynesia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2001/pyf_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
32016,258,"PYF","French Polynesia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2001/pyf_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
32017,258,"PYF","French Polynesia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2001/pyf_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
32018,258,"PYF","French Polynesia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2001/pyf_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
32019,258,"PYF","French Polynesia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2001/pyf_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
32020,258,"PYF","French Polynesia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2001/pyf_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
32021,258,"PYF","French Polynesia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2002/pyf_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
32022,258,"PYF","French Polynesia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2002/pyf_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
32023,258,"PYF","French Polynesia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2002/pyf_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
32024,258,"PYF","French Polynesia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2002/pyf_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
32025,258,"PYF","French Polynesia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2002/pyf_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
32026,258,"PYF","French Polynesia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2002/pyf_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
32027,258,"PYF","French Polynesia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2002/pyf_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
32028,258,"PYF","French Polynesia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2002/pyf_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
32029,258,"PYF","French Polynesia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2003/pyf_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
32030,258,"PYF","French Polynesia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2003/pyf_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
32031,258,"PYF","French Polynesia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2003/pyf_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
32032,258,"PYF","French Polynesia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2003/pyf_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
32033,258,"PYF","French Polynesia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2003/pyf_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
32034,258,"PYF","French Polynesia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2003/pyf_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
32035,258,"PYF","French Polynesia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2003/pyf_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
32036,258,"PYF","French Polynesia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2003/pyf_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
32037,258,"PYF","French Polynesia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2004/pyf_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
32038,258,"PYF","French Polynesia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2004/pyf_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
32039,258,"PYF","French Polynesia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2004/pyf_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
32040,258,"PYF","French Polynesia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2004/pyf_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
32041,258,"PYF","French Polynesia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2004/pyf_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
32042,258,"PYF","French Polynesia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2004/pyf_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
32043,258,"PYF","French Polynesia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2004/pyf_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
32044,258,"PYF","French Polynesia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2004/pyf_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
32045,258,"PYF","French Polynesia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2005/pyf_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
32046,258,"PYF","French Polynesia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2005/pyf_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
32047,258,"PYF","French Polynesia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2005/pyf_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
32048,258,"PYF","French Polynesia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2005/pyf_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
32049,258,"PYF","French Polynesia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2005/pyf_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
32050,258,"PYF","French Polynesia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2005/pyf_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
32051,258,"PYF","French Polynesia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2005/pyf_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
32052,258,"PYF","French Polynesia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2005/pyf_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
32053,258,"PYF","French Polynesia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2006/pyf_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
32054,258,"PYF","French Polynesia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2006/pyf_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
32055,258,"PYF","French Polynesia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2006/pyf_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
32056,258,"PYF","French Polynesia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2006/pyf_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
32057,258,"PYF","French Polynesia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2006/pyf_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
32058,258,"PYF","French Polynesia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2006/pyf_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
32059,258,"PYF","French Polynesia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2006/pyf_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
32060,258,"PYF","French Polynesia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2006/pyf_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
32061,258,"PYF","French Polynesia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2007/pyf_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
32062,258,"PYF","French Polynesia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2007/pyf_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
32063,258,"PYF","French Polynesia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2007/pyf_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
32064,258,"PYF","French Polynesia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2007/pyf_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
32065,258,"PYF","French Polynesia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2007/pyf_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
32066,258,"PYF","French Polynesia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2007/pyf_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
32067,258,"PYF","French Polynesia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2007/pyf_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
32068,258,"PYF","French Polynesia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2007/pyf_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
32069,258,"PYF","French Polynesia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2008/pyf_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
32070,258,"PYF","French Polynesia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2008/pyf_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
32071,258,"PYF","French Polynesia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2008/pyf_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
32072,258,"PYF","French Polynesia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2008/pyf_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
32073,258,"PYF","French Polynesia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2008/pyf_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
32074,258,"PYF","French Polynesia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2008/pyf_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
32075,258,"PYF","French Polynesia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2008/pyf_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
32076,258,"PYF","French Polynesia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2008/pyf_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
32077,258,"PYF","French Polynesia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2009/pyf_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
32078,258,"PYF","French Polynesia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2009/pyf_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
32079,258,"PYF","French Polynesia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2009/pyf_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
32080,258,"PYF","French Polynesia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2009/pyf_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
32081,258,"PYF","French Polynesia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2009/pyf_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
32082,258,"PYF","French Polynesia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2009/pyf_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
32083,258,"PYF","French Polynesia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2009/pyf_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
32084,258,"PYF","French Polynesia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2009/pyf_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
32085,258,"PYF","French Polynesia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2010/pyf_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
32086,258,"PYF","French Polynesia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2010/pyf_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
32087,258,"PYF","French Polynesia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2010/pyf_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
32088,258,"PYF","French Polynesia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2010/pyf_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
32089,258,"PYF","French Polynesia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2010/pyf_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
32090,258,"PYF","French Polynesia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2010/pyf_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
32091,258,"PYF","French Polynesia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2010/pyf_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
32092,258,"PYF","French Polynesia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2010/pyf_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
32093,258,"PYF","French Polynesia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2011/pyf_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
32094,258,"PYF","French Polynesia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2011/pyf_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
32095,258,"PYF","French Polynesia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2011/pyf_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
32096,258,"PYF","French Polynesia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2011/pyf_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
32097,258,"PYF","French Polynesia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2011/pyf_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
32098,258,"PYF","French Polynesia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2011/pyf_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
32099,258,"PYF","French Polynesia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2011/pyf_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
32100,258,"PYF","French Polynesia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2011/pyf_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
32101,258,"PYF","French Polynesia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2012/pyf_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
32102,258,"PYF","French Polynesia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2012/pyf_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
32103,258,"PYF","French Polynesia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2012/pyf_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
32104,258,"PYF","French Polynesia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2012/pyf_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
32105,258,"PYF","French Polynesia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2012/pyf_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
32106,258,"PYF","French Polynesia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2012/pyf_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
32107,258,"PYF","French Polynesia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2012/pyf_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
32108,258,"PYF","French Polynesia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2012/pyf_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
32109,258,"PYF","French Polynesia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2013/pyf_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
32110,258,"PYF","French Polynesia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2013/pyf_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
32111,258,"PYF","French Polynesia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2013/pyf_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
32112,258,"PYF","French Polynesia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2013/pyf_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
32113,258,"PYF","French Polynesia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2013/pyf_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
32114,258,"PYF","French Polynesia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2013/pyf_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
32115,258,"PYF","French Polynesia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2013/pyf_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
32116,258,"PYF","French Polynesia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2013/pyf_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
32117,258,"PYF","French Polynesia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2014/pyf_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
32118,258,"PYF","French Polynesia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2014/pyf_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
32119,258,"PYF","French Polynesia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2014/pyf_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
32120,258,"PYF","French Polynesia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2014/pyf_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
32121,258,"PYF","French Polynesia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2014/pyf_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
32122,258,"PYF","French Polynesia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2014/pyf_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
32123,258,"PYF","French Polynesia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2014/pyf_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
32124,258,"PYF","French Polynesia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2014/pyf_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
32125,258,"PYF","French Polynesia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2015/pyf_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
32126,258,"PYF","French Polynesia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2015/pyf_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
32127,258,"PYF","French Polynesia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2015/pyf_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
32128,258,"PYF","French Polynesia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2015/pyf_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
32129,258,"PYF","French Polynesia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2015/pyf_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
32130,258,"PYF","French Polynesia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2015/pyf_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
32131,258,"PYF","French Polynesia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2015/pyf_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
32132,258,"PYF","French Polynesia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Annual/2015/pyf_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
32133,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2000/atf_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
32134,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2000/atf_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
32135,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2000/atf_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
32136,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2000/atf_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
32137,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2000/atf_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
32138,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2000/atf_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
32139,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2000/atf_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
32140,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2000/atf_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
32141,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2001/atf_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
32142,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2001/atf_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
32143,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2001/atf_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
32144,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2001/atf_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
32145,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2001/atf_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
32146,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2001/atf_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
32147,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2001/atf_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
32148,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2001/atf_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
32149,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2002/atf_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
32150,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2002/atf_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
32151,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2002/atf_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
32152,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2002/atf_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
32153,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2002/atf_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
32154,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2002/atf_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
32155,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2002/atf_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
32156,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2002/atf_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
32157,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2003/atf_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
32158,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2003/atf_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
32159,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2003/atf_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
32160,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2003/atf_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
32161,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2003/atf_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
32162,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2003/atf_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
32163,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2003/atf_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
32164,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2003/atf_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
32165,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2004/atf_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
32166,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2004/atf_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
32167,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2004/atf_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
32168,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2004/atf_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
32169,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2004/atf_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
32170,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2004/atf_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
32171,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2004/atf_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
32172,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2004/atf_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
32173,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2005/atf_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
32174,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2005/atf_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
32175,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2005/atf_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
32176,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2005/atf_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
32177,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2005/atf_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
32178,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2005/atf_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
32179,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2005/atf_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
32180,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2005/atf_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
32181,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2006/atf_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
32182,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2006/atf_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
32183,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2006/atf_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
32184,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2006/atf_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
32185,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2006/atf_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
32186,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2006/atf_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
32187,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2006/atf_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
32188,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2006/atf_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
32189,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2007/atf_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
32190,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2007/atf_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
32191,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2007/atf_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
32192,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2007/atf_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
32193,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2007/atf_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
32194,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2007/atf_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
32195,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2007/atf_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
32196,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2007/atf_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
32197,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2008/atf_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
32198,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2008/atf_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
32199,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2008/atf_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
32200,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2008/atf_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
32201,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2008/atf_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
32202,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2008/atf_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
32203,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2008/atf_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
32204,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2008/atf_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
32205,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2009/atf_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
32206,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2009/atf_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
32207,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2009/atf_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
32208,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2009/atf_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
32209,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2009/atf_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
32210,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2009/atf_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
32211,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2009/atf_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
32212,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2009/atf_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
32213,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2010/atf_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
32214,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2010/atf_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
32215,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2010/atf_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
32216,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2010/atf_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
32217,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2010/atf_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
32218,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2010/atf_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
32219,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2010/atf_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
32220,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2010/atf_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
32221,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2011/atf_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
32222,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2011/atf_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
32223,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2011/atf_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
32224,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2011/atf_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
32225,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2011/atf_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
32226,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2011/atf_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
32227,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2011/atf_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
32228,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2011/atf_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
32229,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2012/atf_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
32230,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2012/atf_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
32231,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2012/atf_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
32232,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2012/atf_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
32233,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2012/atf_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
32234,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2012/atf_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
32235,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2012/atf_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
32236,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2012/atf_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
32237,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2013/atf_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
32238,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2013/atf_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
32239,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2013/atf_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
32240,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2013/atf_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
32241,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2013/atf_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
32242,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2013/atf_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
32243,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2013/atf_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
32244,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2013/atf_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
32245,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2014/atf_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
32246,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2014/atf_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
32247,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2014/atf_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
32248,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2014/atf_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
32249,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2014/atf_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
32250,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2014/atf_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
32251,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2014/atf_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
32252,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2014/atf_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
32253,260,"ATF","French Southern Territories","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2015/atf_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
32254,260,"ATF","French Southern Territories","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2015/atf_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
32255,260,"ATF","French Southern Territories","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2015/atf_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
32256,260,"ATF","French Southern Territories","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2015/atf_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
32257,260,"ATF","French Southern Territories","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2015/atf_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
32258,260,"ATF","French Southern Territories","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2015/atf_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
32259,260,"ATF","French Southern Territories","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2015/atf_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
32260,260,"ATF","French Southern Territories","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Annual/2015/atf_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
32261,262,"DJI","Djibouti","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2000/dji_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
32262,262,"DJI","Djibouti","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2000/dji_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
32263,262,"DJI","Djibouti","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2000/dji_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
32264,262,"DJI","Djibouti","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2000/dji_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
32265,262,"DJI","Djibouti","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2000/dji_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
32266,262,"DJI","Djibouti","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2000/dji_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
32267,262,"DJI","Djibouti","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2000/dji_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
32268,262,"DJI","Djibouti","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2000/dji_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
32269,262,"DJI","Djibouti","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2001/dji_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
32270,262,"DJI","Djibouti","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2001/dji_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
32271,262,"DJI","Djibouti","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2001/dji_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
32272,262,"DJI","Djibouti","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2001/dji_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
32273,262,"DJI","Djibouti","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2001/dji_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
32274,262,"DJI","Djibouti","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2001/dji_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
32275,262,"DJI","Djibouti","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2001/dji_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
32276,262,"DJI","Djibouti","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2001/dji_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
32277,262,"DJI","Djibouti","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2002/dji_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
32278,262,"DJI","Djibouti","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2002/dji_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
32279,262,"DJI","Djibouti","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2002/dji_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
32280,262,"DJI","Djibouti","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2002/dji_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
32281,262,"DJI","Djibouti","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2002/dji_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
32282,262,"DJI","Djibouti","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2002/dji_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
32283,262,"DJI","Djibouti","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2002/dji_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
32284,262,"DJI","Djibouti","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2002/dji_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
32285,262,"DJI","Djibouti","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2003/dji_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
32286,262,"DJI","Djibouti","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2003/dji_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
32287,262,"DJI","Djibouti","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2003/dji_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
32288,262,"DJI","Djibouti","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2003/dji_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
32289,262,"DJI","Djibouti","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2003/dji_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
32290,262,"DJI","Djibouti","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2003/dji_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
32291,262,"DJI","Djibouti","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2003/dji_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
32292,262,"DJI","Djibouti","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2003/dji_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
32293,262,"DJI","Djibouti","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2004/dji_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
32294,262,"DJI","Djibouti","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2004/dji_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
32295,262,"DJI","Djibouti","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2004/dji_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
32296,262,"DJI","Djibouti","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2004/dji_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
32297,262,"DJI","Djibouti","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2004/dji_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
32298,262,"DJI","Djibouti","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2004/dji_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
32299,262,"DJI","Djibouti","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2004/dji_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
32300,262,"DJI","Djibouti","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2004/dji_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
32301,262,"DJI","Djibouti","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2005/dji_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
32302,262,"DJI","Djibouti","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2005/dji_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
32303,262,"DJI","Djibouti","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2005/dji_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
32304,262,"DJI","Djibouti","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2005/dji_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
32305,262,"DJI","Djibouti","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2005/dji_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
32306,262,"DJI","Djibouti","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2005/dji_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
32307,262,"DJI","Djibouti","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2005/dji_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
32308,262,"DJI","Djibouti","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2005/dji_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
32309,262,"DJI","Djibouti","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2006/dji_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
32310,262,"DJI","Djibouti","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2006/dji_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
32311,262,"DJI","Djibouti","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2006/dji_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
32312,262,"DJI","Djibouti","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2006/dji_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
32313,262,"DJI","Djibouti","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2006/dji_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
32314,262,"DJI","Djibouti","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2006/dji_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
32315,262,"DJI","Djibouti","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2006/dji_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
32316,262,"DJI","Djibouti","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2006/dji_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
32317,262,"DJI","Djibouti","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2007/dji_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
32318,262,"DJI","Djibouti","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2007/dji_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
32319,262,"DJI","Djibouti","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2007/dji_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
32320,262,"DJI","Djibouti","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2007/dji_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
32321,262,"DJI","Djibouti","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2007/dji_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
32322,262,"DJI","Djibouti","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2007/dji_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
32323,262,"DJI","Djibouti","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2007/dji_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
32324,262,"DJI","Djibouti","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2007/dji_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
32325,262,"DJI","Djibouti","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2008/dji_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
32326,262,"DJI","Djibouti","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2008/dji_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
32327,262,"DJI","Djibouti","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2008/dji_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
32328,262,"DJI","Djibouti","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2008/dji_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
32329,262,"DJI","Djibouti","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2008/dji_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
32330,262,"DJI","Djibouti","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2008/dji_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
32331,262,"DJI","Djibouti","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2008/dji_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
32332,262,"DJI","Djibouti","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2008/dji_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
32333,262,"DJI","Djibouti","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2009/dji_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
32334,262,"DJI","Djibouti","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2009/dji_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
32335,262,"DJI","Djibouti","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2009/dji_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
32336,262,"DJI","Djibouti","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2009/dji_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
32337,262,"DJI","Djibouti","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2009/dji_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
32338,262,"DJI","Djibouti","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2009/dji_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
32339,262,"DJI","Djibouti","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2009/dji_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
32340,262,"DJI","Djibouti","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2009/dji_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
32341,262,"DJI","Djibouti","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2010/dji_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
32342,262,"DJI","Djibouti","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2010/dji_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
32343,262,"DJI","Djibouti","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2010/dji_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
32344,262,"DJI","Djibouti","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2010/dji_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
32345,262,"DJI","Djibouti","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2010/dji_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
32346,262,"DJI","Djibouti","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2010/dji_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
32347,262,"DJI","Djibouti","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2010/dji_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
32348,262,"DJI","Djibouti","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2010/dji_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
32349,262,"DJI","Djibouti","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2011/dji_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
32350,262,"DJI","Djibouti","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2011/dji_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
32351,262,"DJI","Djibouti","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2011/dji_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
32352,262,"DJI","Djibouti","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2011/dji_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
32353,262,"DJI","Djibouti","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2011/dji_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
32354,262,"DJI","Djibouti","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2011/dji_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
32355,262,"DJI","Djibouti","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2011/dji_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
32356,262,"DJI","Djibouti","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2011/dji_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
32357,262,"DJI","Djibouti","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2012/dji_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
32358,262,"DJI","Djibouti","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2012/dji_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
32359,262,"DJI","Djibouti","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2012/dji_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
32360,262,"DJI","Djibouti","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2012/dji_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
32361,262,"DJI","Djibouti","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2012/dji_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
32362,262,"DJI","Djibouti","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2012/dji_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
32363,262,"DJI","Djibouti","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2012/dji_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
32364,262,"DJI","Djibouti","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2012/dji_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
32365,262,"DJI","Djibouti","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2013/dji_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
32366,262,"DJI","Djibouti","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2013/dji_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
32367,262,"DJI","Djibouti","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2013/dji_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
32368,262,"DJI","Djibouti","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2013/dji_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
32369,262,"DJI","Djibouti","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2013/dji_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
32370,262,"DJI","Djibouti","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2013/dji_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
32371,262,"DJI","Djibouti","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2013/dji_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
32372,262,"DJI","Djibouti","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2013/dji_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
32373,262,"DJI","Djibouti","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2014/dji_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
32374,262,"DJI","Djibouti","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2014/dji_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
32375,262,"DJI","Djibouti","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2014/dji_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
32376,262,"DJI","Djibouti","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2014/dji_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
32377,262,"DJI","Djibouti","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2014/dji_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
32378,262,"DJI","Djibouti","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2014/dji_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
32379,262,"DJI","Djibouti","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2014/dji_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
32380,262,"DJI","Djibouti","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2014/dji_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
32381,262,"DJI","Djibouti","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2015/dji_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
32382,262,"DJI","Djibouti","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2015/dji_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
32383,262,"DJI","Djibouti","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2015/dji_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
32384,262,"DJI","Djibouti","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2015/dji_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
32385,262,"DJI","Djibouti","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2015/dji_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
32386,262,"DJI","Djibouti","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2015/dji_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
32387,262,"DJI","Djibouti","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2015/dji_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
32388,262,"DJI","Djibouti","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Annual/2015/dji_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
32389,266,"GAB","Gabon","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2000/gab_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
32390,266,"GAB","Gabon","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2000/gab_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
32391,266,"GAB","Gabon","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2000/gab_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
32392,266,"GAB","Gabon","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2000/gab_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
32393,266,"GAB","Gabon","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2000/gab_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
32394,266,"GAB","Gabon","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2000/gab_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
32395,266,"GAB","Gabon","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2000/gab_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
32396,266,"GAB","Gabon","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2000/gab_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
32397,266,"GAB","Gabon","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2001/gab_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
32398,266,"GAB","Gabon","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2001/gab_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
32399,266,"GAB","Gabon","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2001/gab_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
32400,266,"GAB","Gabon","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2001/gab_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
32401,266,"GAB","Gabon","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2001/gab_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
32402,266,"GAB","Gabon","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2001/gab_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
32403,266,"GAB","Gabon","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2001/gab_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
32404,266,"GAB","Gabon","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2001/gab_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
32405,266,"GAB","Gabon","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2002/gab_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
32406,266,"GAB","Gabon","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2002/gab_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
32407,266,"GAB","Gabon","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2002/gab_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
32408,266,"GAB","Gabon","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2002/gab_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
32409,266,"GAB","Gabon","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2002/gab_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
32410,266,"GAB","Gabon","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2002/gab_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
32411,266,"GAB","Gabon","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2002/gab_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
32412,266,"GAB","Gabon","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2002/gab_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
32413,266,"GAB","Gabon","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2003/gab_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
32414,266,"GAB","Gabon","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2003/gab_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
32415,266,"GAB","Gabon","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2003/gab_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
32416,266,"GAB","Gabon","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2003/gab_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
32417,266,"GAB","Gabon","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2003/gab_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
32418,266,"GAB","Gabon","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2003/gab_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
32419,266,"GAB","Gabon","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2003/gab_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
32420,266,"GAB","Gabon","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2003/gab_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
32421,266,"GAB","Gabon","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2004/gab_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
32422,266,"GAB","Gabon","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2004/gab_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
32423,266,"GAB","Gabon","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2004/gab_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
32424,266,"GAB","Gabon","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2004/gab_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
32425,266,"GAB","Gabon","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2004/gab_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
32426,266,"GAB","Gabon","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2004/gab_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
32427,266,"GAB","Gabon","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2004/gab_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
32428,266,"GAB","Gabon","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2004/gab_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
32429,266,"GAB","Gabon","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2005/gab_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
32430,266,"GAB","Gabon","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2005/gab_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
32431,266,"GAB","Gabon","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2005/gab_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
32432,266,"GAB","Gabon","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2005/gab_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
32433,266,"GAB","Gabon","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2005/gab_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
32434,266,"GAB","Gabon","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2005/gab_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
32435,266,"GAB","Gabon","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2005/gab_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
32436,266,"GAB","Gabon","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2005/gab_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
32437,266,"GAB","Gabon","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2006/gab_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
32438,266,"GAB","Gabon","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2006/gab_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
32439,266,"GAB","Gabon","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2006/gab_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
32440,266,"GAB","Gabon","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2006/gab_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
32441,266,"GAB","Gabon","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2006/gab_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
32442,266,"GAB","Gabon","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2006/gab_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
32443,266,"GAB","Gabon","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2006/gab_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
32444,266,"GAB","Gabon","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2006/gab_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
32445,266,"GAB","Gabon","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2007/gab_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
32446,266,"GAB","Gabon","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2007/gab_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
32447,266,"GAB","Gabon","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2007/gab_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
32448,266,"GAB","Gabon","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2007/gab_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
32449,266,"GAB","Gabon","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2007/gab_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
32450,266,"GAB","Gabon","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2007/gab_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
32451,266,"GAB","Gabon","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2007/gab_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
32452,266,"GAB","Gabon","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2007/gab_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
32453,266,"GAB","Gabon","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2008/gab_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
32454,266,"GAB","Gabon","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2008/gab_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
32455,266,"GAB","Gabon","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2008/gab_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
32456,266,"GAB","Gabon","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2008/gab_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
32457,266,"GAB","Gabon","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2008/gab_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
32458,266,"GAB","Gabon","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2008/gab_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
32459,266,"GAB","Gabon","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2008/gab_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
32460,266,"GAB","Gabon","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2008/gab_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
32461,266,"GAB","Gabon","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2009/gab_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
32462,266,"GAB","Gabon","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2009/gab_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
32463,266,"GAB","Gabon","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2009/gab_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
32464,266,"GAB","Gabon","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2009/gab_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
32465,266,"GAB","Gabon","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2009/gab_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
32466,266,"GAB","Gabon","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2009/gab_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
32467,266,"GAB","Gabon","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2009/gab_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
32468,266,"GAB","Gabon","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2009/gab_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
32469,266,"GAB","Gabon","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2010/gab_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
32470,266,"GAB","Gabon","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2010/gab_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
32471,266,"GAB","Gabon","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2010/gab_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
32472,266,"GAB","Gabon","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2010/gab_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
32473,266,"GAB","Gabon","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2010/gab_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
32474,266,"GAB","Gabon","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2010/gab_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
32475,266,"GAB","Gabon","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2010/gab_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
32476,266,"GAB","Gabon","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2010/gab_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
32477,266,"GAB","Gabon","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2011/gab_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
32478,266,"GAB","Gabon","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2011/gab_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
32479,266,"GAB","Gabon","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2011/gab_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
32480,266,"GAB","Gabon","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2011/gab_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
32481,266,"GAB","Gabon","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2011/gab_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
32482,266,"GAB","Gabon","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2011/gab_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
32483,266,"GAB","Gabon","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2011/gab_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
32484,266,"GAB","Gabon","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2011/gab_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
32485,266,"GAB","Gabon","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2012/gab_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
32486,266,"GAB","Gabon","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2012/gab_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
32487,266,"GAB","Gabon","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2012/gab_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
32488,266,"GAB","Gabon","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2012/gab_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
32489,266,"GAB","Gabon","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2012/gab_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
32490,266,"GAB","Gabon","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2012/gab_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
32491,266,"GAB","Gabon","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2012/gab_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
32492,266,"GAB","Gabon","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2012/gab_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
32493,266,"GAB","Gabon","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2013/gab_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
32494,266,"GAB","Gabon","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2013/gab_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
32495,266,"GAB","Gabon","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2013/gab_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
32496,266,"GAB","Gabon","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2013/gab_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
32497,266,"GAB","Gabon","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2013/gab_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
32498,266,"GAB","Gabon","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2013/gab_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
32499,266,"GAB","Gabon","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2013/gab_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
32500,266,"GAB","Gabon","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2013/gab_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
32501,266,"GAB","Gabon","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2014/gab_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
32502,266,"GAB","Gabon","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2014/gab_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
32503,266,"GAB","Gabon","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2014/gab_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
32504,266,"GAB","Gabon","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2014/gab_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
32505,266,"GAB","Gabon","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2014/gab_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
32506,266,"GAB","Gabon","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2014/gab_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
32507,266,"GAB","Gabon","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2014/gab_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
32508,266,"GAB","Gabon","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2014/gab_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
32509,266,"GAB","Gabon","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2015/gab_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
32510,266,"GAB","Gabon","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2015/gab_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
32511,266,"GAB","Gabon","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2015/gab_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
32512,266,"GAB","Gabon","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2015/gab_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
32513,266,"GAB","Gabon","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2015/gab_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
32514,266,"GAB","Gabon","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2015/gab_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
32515,266,"GAB","Gabon","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2015/gab_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
32516,266,"GAB","Gabon","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Annual/2015/gab_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
32517,268,"GEO","Georgia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2000/geo_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
32518,268,"GEO","Georgia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2000/geo_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
32519,268,"GEO","Georgia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2000/geo_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
32520,268,"GEO","Georgia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2000/geo_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
32521,268,"GEO","Georgia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2000/geo_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
32522,268,"GEO","Georgia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2000/geo_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
32523,268,"GEO","Georgia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2000/geo_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
32524,268,"GEO","Georgia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2000/geo_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
32525,268,"GEO","Georgia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2001/geo_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
32526,268,"GEO","Georgia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2001/geo_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
32527,268,"GEO","Georgia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2001/geo_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
32528,268,"GEO","Georgia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2001/geo_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
32529,268,"GEO","Georgia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2001/geo_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
32530,268,"GEO","Georgia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2001/geo_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
32531,268,"GEO","Georgia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2001/geo_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
32532,268,"GEO","Georgia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2001/geo_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
32533,268,"GEO","Georgia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2002/geo_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
32534,268,"GEO","Georgia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2002/geo_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
32535,268,"GEO","Georgia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2002/geo_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
32536,268,"GEO","Georgia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2002/geo_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
32537,268,"GEO","Georgia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2002/geo_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
32538,268,"GEO","Georgia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2002/geo_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
32539,268,"GEO","Georgia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2002/geo_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
32540,268,"GEO","Georgia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2002/geo_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
32541,268,"GEO","Georgia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2003/geo_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
32542,268,"GEO","Georgia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2003/geo_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
32543,268,"GEO","Georgia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2003/geo_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
32544,268,"GEO","Georgia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2003/geo_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
32545,268,"GEO","Georgia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2003/geo_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
32546,268,"GEO","Georgia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2003/geo_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
32547,268,"GEO","Georgia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2003/geo_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
32548,268,"GEO","Georgia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2003/geo_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
32549,268,"GEO","Georgia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2004/geo_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
32550,268,"GEO","Georgia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2004/geo_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
32551,268,"GEO","Georgia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2004/geo_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
32552,268,"GEO","Georgia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2004/geo_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
32553,268,"GEO","Georgia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2004/geo_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
32554,268,"GEO","Georgia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2004/geo_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
32555,268,"GEO","Georgia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2004/geo_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
32556,268,"GEO","Georgia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2004/geo_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
32557,268,"GEO","Georgia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2005/geo_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
32558,268,"GEO","Georgia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2005/geo_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
32559,268,"GEO","Georgia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2005/geo_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
32560,268,"GEO","Georgia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2005/geo_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
32561,268,"GEO","Georgia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2005/geo_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
32562,268,"GEO","Georgia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2005/geo_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
32563,268,"GEO","Georgia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2005/geo_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
32564,268,"GEO","Georgia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2005/geo_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
32565,268,"GEO","Georgia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2006/geo_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
32566,268,"GEO","Georgia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2006/geo_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
32567,268,"GEO","Georgia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2006/geo_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
32568,268,"GEO","Georgia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2006/geo_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
32569,268,"GEO","Georgia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2006/geo_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
32570,268,"GEO","Georgia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2006/geo_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
32571,268,"GEO","Georgia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2006/geo_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
32572,268,"GEO","Georgia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2006/geo_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
32573,268,"GEO","Georgia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2007/geo_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
32574,268,"GEO","Georgia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2007/geo_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
32575,268,"GEO","Georgia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2007/geo_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
32576,268,"GEO","Georgia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2007/geo_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
32577,268,"GEO","Georgia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2007/geo_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
32578,268,"GEO","Georgia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2007/geo_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
32579,268,"GEO","Georgia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2007/geo_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
32580,268,"GEO","Georgia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2007/geo_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
32581,268,"GEO","Georgia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2008/geo_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
32582,268,"GEO","Georgia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2008/geo_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
32583,268,"GEO","Georgia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2008/geo_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
32584,268,"GEO","Georgia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2008/geo_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
32585,268,"GEO","Georgia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2008/geo_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
32586,268,"GEO","Georgia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2008/geo_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
32587,268,"GEO","Georgia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2008/geo_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
32588,268,"GEO","Georgia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2008/geo_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
32589,268,"GEO","Georgia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2009/geo_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
32590,268,"GEO","Georgia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2009/geo_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
32591,268,"GEO","Georgia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2009/geo_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
32592,268,"GEO","Georgia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2009/geo_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
32593,268,"GEO","Georgia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2009/geo_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
32594,268,"GEO","Georgia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2009/geo_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
32595,268,"GEO","Georgia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2009/geo_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
32596,268,"GEO","Georgia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2009/geo_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
32597,268,"GEO","Georgia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2010/geo_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
32598,268,"GEO","Georgia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2010/geo_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
32599,268,"GEO","Georgia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2010/geo_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
32600,268,"GEO","Georgia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2010/geo_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
32601,268,"GEO","Georgia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2010/geo_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
32602,268,"GEO","Georgia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2010/geo_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
32603,268,"GEO","Georgia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2010/geo_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
32604,268,"GEO","Georgia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2010/geo_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
32605,268,"GEO","Georgia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2011/geo_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
32606,268,"GEO","Georgia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2011/geo_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
32607,268,"GEO","Georgia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2011/geo_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
32608,268,"GEO","Georgia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2011/geo_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
32609,268,"GEO","Georgia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2011/geo_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
32610,268,"GEO","Georgia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2011/geo_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
32611,268,"GEO","Georgia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2011/geo_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
32612,268,"GEO","Georgia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2011/geo_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
32613,268,"GEO","Georgia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2012/geo_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
32614,268,"GEO","Georgia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2012/geo_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
32615,268,"GEO","Georgia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2012/geo_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
32616,268,"GEO","Georgia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2012/geo_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
32617,268,"GEO","Georgia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2012/geo_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
32618,268,"GEO","Georgia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2012/geo_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
32619,268,"GEO","Georgia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2012/geo_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
32620,268,"GEO","Georgia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2012/geo_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
32621,268,"GEO","Georgia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2013/geo_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
32622,268,"GEO","Georgia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2013/geo_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
32623,268,"GEO","Georgia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2013/geo_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
32624,268,"GEO","Georgia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2013/geo_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
32625,268,"GEO","Georgia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2013/geo_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
32626,268,"GEO","Georgia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2013/geo_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
32627,268,"GEO","Georgia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2013/geo_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
32628,268,"GEO","Georgia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2013/geo_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
32629,268,"GEO","Georgia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2014/geo_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
32630,268,"GEO","Georgia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2014/geo_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
32631,268,"GEO","Georgia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2014/geo_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
32632,268,"GEO","Georgia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2014/geo_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
32633,268,"GEO","Georgia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2014/geo_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
32634,268,"GEO","Georgia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2014/geo_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
32635,268,"GEO","Georgia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2014/geo_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
32636,268,"GEO","Georgia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2014/geo_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
32637,268,"GEO","Georgia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2015/geo_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
32638,268,"GEO","Georgia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2015/geo_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
32639,268,"GEO","Georgia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2015/geo_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
32640,268,"GEO","Georgia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2015/geo_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
32641,268,"GEO","Georgia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2015/geo_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
32642,268,"GEO","Georgia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2015/geo_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
32643,268,"GEO","Georgia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2015/geo_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
32644,268,"GEO","Georgia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Annual/2015/geo_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
32645,270,"GMB","Gambia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2000/gmb_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
32646,270,"GMB","Gambia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2000/gmb_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
32647,270,"GMB","Gambia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2000/gmb_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
32648,270,"GMB","Gambia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2000/gmb_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
32649,270,"GMB","Gambia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2000/gmb_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
32650,270,"GMB","Gambia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2000/gmb_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
32651,270,"GMB","Gambia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2000/gmb_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
32652,270,"GMB","Gambia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2000/gmb_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
32653,270,"GMB","Gambia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2001/gmb_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
32654,270,"GMB","Gambia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2001/gmb_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
32655,270,"GMB","Gambia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2001/gmb_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
32656,270,"GMB","Gambia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2001/gmb_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
32657,270,"GMB","Gambia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2001/gmb_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
32658,270,"GMB","Gambia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2001/gmb_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
32659,270,"GMB","Gambia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2001/gmb_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
32660,270,"GMB","Gambia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2001/gmb_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
32661,270,"GMB","Gambia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2002/gmb_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
32662,270,"GMB","Gambia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2002/gmb_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
32663,270,"GMB","Gambia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2002/gmb_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
32664,270,"GMB","Gambia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2002/gmb_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
32665,270,"GMB","Gambia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2002/gmb_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
32666,270,"GMB","Gambia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2002/gmb_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
32667,270,"GMB","Gambia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2002/gmb_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
32668,270,"GMB","Gambia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2002/gmb_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
32669,270,"GMB","Gambia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2003/gmb_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
32670,270,"GMB","Gambia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2003/gmb_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
32671,270,"GMB","Gambia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2003/gmb_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
32672,270,"GMB","Gambia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2003/gmb_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
32673,270,"GMB","Gambia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2003/gmb_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
32674,270,"GMB","Gambia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2003/gmb_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
32675,270,"GMB","Gambia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2003/gmb_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
32676,270,"GMB","Gambia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2003/gmb_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
32677,270,"GMB","Gambia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2004/gmb_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
32678,270,"GMB","Gambia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2004/gmb_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
32679,270,"GMB","Gambia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2004/gmb_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
32680,270,"GMB","Gambia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2004/gmb_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
32681,270,"GMB","Gambia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2004/gmb_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
32682,270,"GMB","Gambia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2004/gmb_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
32683,270,"GMB","Gambia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2004/gmb_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
32684,270,"GMB","Gambia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2004/gmb_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
32685,270,"GMB","Gambia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2005/gmb_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
32686,270,"GMB","Gambia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2005/gmb_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
32687,270,"GMB","Gambia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2005/gmb_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
32688,270,"GMB","Gambia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2005/gmb_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
32689,270,"GMB","Gambia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2005/gmb_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
32690,270,"GMB","Gambia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2005/gmb_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
32691,270,"GMB","Gambia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2005/gmb_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
32692,270,"GMB","Gambia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2005/gmb_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
32693,270,"GMB","Gambia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2006/gmb_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
32694,270,"GMB","Gambia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2006/gmb_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
32695,270,"GMB","Gambia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2006/gmb_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
32696,270,"GMB","Gambia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2006/gmb_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
32697,270,"GMB","Gambia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2006/gmb_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
32698,270,"GMB","Gambia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2006/gmb_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
32699,270,"GMB","Gambia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2006/gmb_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
32700,270,"GMB","Gambia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2006/gmb_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
32701,270,"GMB","Gambia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2007/gmb_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
32702,270,"GMB","Gambia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2007/gmb_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
32703,270,"GMB","Gambia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2007/gmb_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
32704,270,"GMB","Gambia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2007/gmb_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
32705,270,"GMB","Gambia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2007/gmb_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
32706,270,"GMB","Gambia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2007/gmb_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
32707,270,"GMB","Gambia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2007/gmb_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
32708,270,"GMB","Gambia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2007/gmb_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
32709,270,"GMB","Gambia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2008/gmb_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
32710,270,"GMB","Gambia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2008/gmb_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
32711,270,"GMB","Gambia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2008/gmb_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
32712,270,"GMB","Gambia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2008/gmb_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
32713,270,"GMB","Gambia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2008/gmb_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
32714,270,"GMB","Gambia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2008/gmb_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
32715,270,"GMB","Gambia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2008/gmb_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
32716,270,"GMB","Gambia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2008/gmb_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
32717,270,"GMB","Gambia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2009/gmb_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
32718,270,"GMB","Gambia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2009/gmb_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
32719,270,"GMB","Gambia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2009/gmb_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
32720,270,"GMB","Gambia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2009/gmb_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
32721,270,"GMB","Gambia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2009/gmb_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
32722,270,"GMB","Gambia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2009/gmb_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
32723,270,"GMB","Gambia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2009/gmb_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
32724,270,"GMB","Gambia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2009/gmb_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
32725,270,"GMB","Gambia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2010/gmb_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
32726,270,"GMB","Gambia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2010/gmb_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
32727,270,"GMB","Gambia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2010/gmb_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
32728,270,"GMB","Gambia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2010/gmb_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
32729,270,"GMB","Gambia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2010/gmb_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
32730,270,"GMB","Gambia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2010/gmb_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
32731,270,"GMB","Gambia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2010/gmb_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
32732,270,"GMB","Gambia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2010/gmb_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
32733,270,"GMB","Gambia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2011/gmb_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
32734,270,"GMB","Gambia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2011/gmb_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
32735,270,"GMB","Gambia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2011/gmb_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
32736,270,"GMB","Gambia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2011/gmb_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
32737,270,"GMB","Gambia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2011/gmb_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
32738,270,"GMB","Gambia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2011/gmb_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
32739,270,"GMB","Gambia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2011/gmb_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
32740,270,"GMB","Gambia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2011/gmb_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
32741,270,"GMB","Gambia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2012/gmb_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
32742,270,"GMB","Gambia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2012/gmb_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
32743,270,"GMB","Gambia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2012/gmb_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
32744,270,"GMB","Gambia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2012/gmb_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
32745,270,"GMB","Gambia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2012/gmb_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
32746,270,"GMB","Gambia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2012/gmb_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
32747,270,"GMB","Gambia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2012/gmb_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
32748,270,"GMB","Gambia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2012/gmb_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
32749,270,"GMB","Gambia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2013/gmb_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
32750,270,"GMB","Gambia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2013/gmb_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
32751,270,"GMB","Gambia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2013/gmb_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
32752,270,"GMB","Gambia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2013/gmb_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
32753,270,"GMB","Gambia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2013/gmb_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
32754,270,"GMB","Gambia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2013/gmb_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
32755,270,"GMB","Gambia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2013/gmb_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
32756,270,"GMB","Gambia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2013/gmb_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
32757,270,"GMB","Gambia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2014/gmb_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
32758,270,"GMB","Gambia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2014/gmb_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
32759,270,"GMB","Gambia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2014/gmb_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
32760,270,"GMB","Gambia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2014/gmb_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
32761,270,"GMB","Gambia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2014/gmb_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
32762,270,"GMB","Gambia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2014/gmb_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
32763,270,"GMB","Gambia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2014/gmb_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
32764,270,"GMB","Gambia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2014/gmb_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
32765,270,"GMB","Gambia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2015/gmb_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
32766,270,"GMB","Gambia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2015/gmb_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
32767,270,"GMB","Gambia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2015/gmb_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
32768,270,"GMB","Gambia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2015/gmb_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
32769,270,"GMB","Gambia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2015/gmb_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
32770,270,"GMB","Gambia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2015/gmb_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
32771,270,"GMB","Gambia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2015/gmb_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
32772,270,"GMB","Gambia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Annual/2015/gmb_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
32773,275,"PSE","Palestina","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2000/pse_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
32774,275,"PSE","Palestina","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2000/pse_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
32775,275,"PSE","Palestina","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2000/pse_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
32776,275,"PSE","Palestina","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2000/pse_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
32777,275,"PSE","Palestina","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2000/pse_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
32778,275,"PSE","Palestina","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2000/pse_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
32779,275,"PSE","Palestina","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2000/pse_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
32780,275,"PSE","Palestina","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2000/pse_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
32781,275,"PSE","Palestina","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2001/pse_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
32782,275,"PSE","Palestina","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2001/pse_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
32783,275,"PSE","Palestina","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2001/pse_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
32784,275,"PSE","Palestina","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2001/pse_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
32785,275,"PSE","Palestina","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2001/pse_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
32786,275,"PSE","Palestina","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2001/pse_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
32787,275,"PSE","Palestina","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2001/pse_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
32788,275,"PSE","Palestina","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2001/pse_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
32789,275,"PSE","Palestina","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2002/pse_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
32790,275,"PSE","Palestina","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2002/pse_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
32791,275,"PSE","Palestina","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2002/pse_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
32792,275,"PSE","Palestina","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2002/pse_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
32793,275,"PSE","Palestina","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2002/pse_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
32794,275,"PSE","Palestina","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2002/pse_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
32795,275,"PSE","Palestina","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2002/pse_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
32796,275,"PSE","Palestina","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2002/pse_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
32797,275,"PSE","Palestina","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2003/pse_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
32798,275,"PSE","Palestina","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2003/pse_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
32799,275,"PSE","Palestina","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2003/pse_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
32800,275,"PSE","Palestina","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2003/pse_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
32801,275,"PSE","Palestina","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2003/pse_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
32802,275,"PSE","Palestina","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2003/pse_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
32803,275,"PSE","Palestina","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2003/pse_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
32804,275,"PSE","Palestina","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2003/pse_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
32805,275,"PSE","Palestina","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2004/pse_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
32806,275,"PSE","Palestina","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2004/pse_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
32807,275,"PSE","Palestina","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2004/pse_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
32808,275,"PSE","Palestina","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2004/pse_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
32809,275,"PSE","Palestina","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2004/pse_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
32810,275,"PSE","Palestina","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2004/pse_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
32811,275,"PSE","Palestina","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2004/pse_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
32812,275,"PSE","Palestina","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2004/pse_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
32813,275,"PSE","Palestina","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2005/pse_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
32814,275,"PSE","Palestina","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2005/pse_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
32815,275,"PSE","Palestina","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2005/pse_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
32816,275,"PSE","Palestina","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2005/pse_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
32817,275,"PSE","Palestina","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2005/pse_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
32818,275,"PSE","Palestina","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2005/pse_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
32819,275,"PSE","Palestina","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2005/pse_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
32820,275,"PSE","Palestina","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2005/pse_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
32821,275,"PSE","Palestina","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2006/pse_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
32822,275,"PSE","Palestina","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2006/pse_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
32823,275,"PSE","Palestina","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2006/pse_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
32824,275,"PSE","Palestina","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2006/pse_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
32825,275,"PSE","Palestina","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2006/pse_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
32826,275,"PSE","Palestina","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2006/pse_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
32827,275,"PSE","Palestina","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2006/pse_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
32828,275,"PSE","Palestina","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2006/pse_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
32829,275,"PSE","Palestina","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2007/pse_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
32830,275,"PSE","Palestina","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2007/pse_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
32831,275,"PSE","Palestina","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2007/pse_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
32832,275,"PSE","Palestina","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2007/pse_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
32833,275,"PSE","Palestina","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2007/pse_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
32834,275,"PSE","Palestina","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2007/pse_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
32835,275,"PSE","Palestina","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2007/pse_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
32836,275,"PSE","Palestina","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2007/pse_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
32837,275,"PSE","Palestina","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2008/pse_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
32838,275,"PSE","Palestina","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2008/pse_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
32839,275,"PSE","Palestina","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2008/pse_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
32840,275,"PSE","Palestina","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2008/pse_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
32841,275,"PSE","Palestina","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2008/pse_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
32842,275,"PSE","Palestina","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2008/pse_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
32843,275,"PSE","Palestina","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2008/pse_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
32844,275,"PSE","Palestina","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2008/pse_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
32845,275,"PSE","Palestina","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2009/pse_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
32846,275,"PSE","Palestina","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2009/pse_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
32847,275,"PSE","Palestina","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2009/pse_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
32848,275,"PSE","Palestina","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2009/pse_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
32849,275,"PSE","Palestina","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2009/pse_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
32850,275,"PSE","Palestina","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2009/pse_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
32851,275,"PSE","Palestina","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2009/pse_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
32852,275,"PSE","Palestina","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2009/pse_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
32853,275,"PSE","Palestina","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2010/pse_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
32854,275,"PSE","Palestina","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2010/pse_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
32855,275,"PSE","Palestina","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2010/pse_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
32856,275,"PSE","Palestina","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2010/pse_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
32857,275,"PSE","Palestina","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2010/pse_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
32858,275,"PSE","Palestina","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2010/pse_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
32859,275,"PSE","Palestina","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2010/pse_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
32860,275,"PSE","Palestina","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2010/pse_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
32861,275,"PSE","Palestina","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2011/pse_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
32862,275,"PSE","Palestina","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2011/pse_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
32863,275,"PSE","Palestina","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2011/pse_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
32864,275,"PSE","Palestina","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2011/pse_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
32865,275,"PSE","Palestina","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2011/pse_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
32866,275,"PSE","Palestina","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2011/pse_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
32867,275,"PSE","Palestina","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2011/pse_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
32868,275,"PSE","Palestina","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2011/pse_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
32869,275,"PSE","Palestina","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2012/pse_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
32870,275,"PSE","Palestina","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2012/pse_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
32871,275,"PSE","Palestina","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2012/pse_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
32872,275,"PSE","Palestina","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2012/pse_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
32873,275,"PSE","Palestina","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2012/pse_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
32874,275,"PSE","Palestina","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2012/pse_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
32875,275,"PSE","Palestina","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2012/pse_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
32876,275,"PSE","Palestina","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2012/pse_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
32877,275,"PSE","Palestina","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2013/pse_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
32878,275,"PSE","Palestina","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2013/pse_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
32879,275,"PSE","Palestina","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2013/pse_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
32880,275,"PSE","Palestina","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2013/pse_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
32881,275,"PSE","Palestina","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2013/pse_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
32882,275,"PSE","Palestina","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2013/pse_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
32883,275,"PSE","Palestina","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2013/pse_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
32884,275,"PSE","Palestina","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2013/pse_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
32885,275,"PSE","Palestina","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2014/pse_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
32886,275,"PSE","Palestina","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2014/pse_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
32887,275,"PSE","Palestina","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2014/pse_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
32888,275,"PSE","Palestina","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2014/pse_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
32889,275,"PSE","Palestina","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2014/pse_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
32890,275,"PSE","Palestina","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2014/pse_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
32891,275,"PSE","Palestina","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2014/pse_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
32892,275,"PSE","Palestina","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2014/pse_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
32893,275,"PSE","Palestina","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2015/pse_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
32894,275,"PSE","Palestina","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2015/pse_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
32895,275,"PSE","Palestina","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2015/pse_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
32896,275,"PSE","Palestina","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2015/pse_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
32897,275,"PSE","Palestina","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2015/pse_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
32898,275,"PSE","Palestina","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2015/pse_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
32899,275,"PSE","Palestina","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2015/pse_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
32900,275,"PSE","Palestina","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Annual/2015/pse_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
32901,276,"DEU","Germany","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2000/deu_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
32902,276,"DEU","Germany","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2000/deu_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
32903,276,"DEU","Germany","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2000/deu_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
32904,276,"DEU","Germany","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2000/deu_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
32905,276,"DEU","Germany","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2000/deu_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
32906,276,"DEU","Germany","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2000/deu_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
32907,276,"DEU","Germany","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2000/deu_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
32908,276,"DEU","Germany","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2000/deu_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
32909,276,"DEU","Germany","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2001/deu_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
32910,276,"DEU","Germany","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2001/deu_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
32911,276,"DEU","Germany","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2001/deu_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
32912,276,"DEU","Germany","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2001/deu_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
32913,276,"DEU","Germany","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2001/deu_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
32914,276,"DEU","Germany","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2001/deu_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
32915,276,"DEU","Germany","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2001/deu_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
32916,276,"DEU","Germany","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2001/deu_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
32917,276,"DEU","Germany","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2002/deu_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
32918,276,"DEU","Germany","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2002/deu_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
32919,276,"DEU","Germany","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2002/deu_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
32920,276,"DEU","Germany","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2002/deu_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
32921,276,"DEU","Germany","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2002/deu_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
32922,276,"DEU","Germany","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2002/deu_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
32923,276,"DEU","Germany","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2002/deu_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
32924,276,"DEU","Germany","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2002/deu_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
32925,276,"DEU","Germany","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2003/deu_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
32926,276,"DEU","Germany","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2003/deu_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
32927,276,"DEU","Germany","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2003/deu_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
32928,276,"DEU","Germany","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2003/deu_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
32929,276,"DEU","Germany","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2003/deu_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
32930,276,"DEU","Germany","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2003/deu_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
32931,276,"DEU","Germany","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2003/deu_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
32932,276,"DEU","Germany","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2003/deu_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
32933,276,"DEU","Germany","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2004/deu_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
32934,276,"DEU","Germany","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2004/deu_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
32935,276,"DEU","Germany","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2004/deu_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
32936,276,"DEU","Germany","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2004/deu_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
32937,276,"DEU","Germany","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2004/deu_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
32938,276,"DEU","Germany","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2004/deu_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
32939,276,"DEU","Germany","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2004/deu_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
32940,276,"DEU","Germany","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2004/deu_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
32941,276,"DEU","Germany","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2005/deu_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
32942,276,"DEU","Germany","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2005/deu_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
32943,276,"DEU","Germany","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2005/deu_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
32944,276,"DEU","Germany","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2005/deu_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
32945,276,"DEU","Germany","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2005/deu_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
32946,276,"DEU","Germany","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2005/deu_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
32947,276,"DEU","Germany","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2005/deu_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
32948,276,"DEU","Germany","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2005/deu_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
32949,276,"DEU","Germany","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2006/deu_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
32950,276,"DEU","Germany","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2006/deu_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
32951,276,"DEU","Germany","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2006/deu_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
32952,276,"DEU","Germany","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2006/deu_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
32953,276,"DEU","Germany","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2006/deu_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
32954,276,"DEU","Germany","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2006/deu_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
32955,276,"DEU","Germany","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2006/deu_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
32956,276,"DEU","Germany","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2006/deu_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
32957,276,"DEU","Germany","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2007/deu_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
32958,276,"DEU","Germany","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2007/deu_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
32959,276,"DEU","Germany","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2007/deu_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
32960,276,"DEU","Germany","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2007/deu_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
32961,276,"DEU","Germany","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2007/deu_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
32962,276,"DEU","Germany","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2007/deu_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
32963,276,"DEU","Germany","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2007/deu_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
32964,276,"DEU","Germany","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2007/deu_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
32965,276,"DEU","Germany","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2008/deu_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
32966,276,"DEU","Germany","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2008/deu_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
32967,276,"DEU","Germany","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2008/deu_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
32968,276,"DEU","Germany","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2008/deu_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
32969,276,"DEU","Germany","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2008/deu_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
32970,276,"DEU","Germany","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2008/deu_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
32971,276,"DEU","Germany","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2008/deu_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
32972,276,"DEU","Germany","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2008/deu_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
32973,276,"DEU","Germany","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2009/deu_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
32974,276,"DEU","Germany","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2009/deu_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
32975,276,"DEU","Germany","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2009/deu_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
32976,276,"DEU","Germany","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2009/deu_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
32977,276,"DEU","Germany","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2009/deu_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
32978,276,"DEU","Germany","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2009/deu_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
32979,276,"DEU","Germany","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2009/deu_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
32980,276,"DEU","Germany","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2009/deu_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
32981,276,"DEU","Germany","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2010/deu_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
32982,276,"DEU","Germany","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2010/deu_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
32983,276,"DEU","Germany","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2010/deu_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
32984,276,"DEU","Germany","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2010/deu_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
32985,276,"DEU","Germany","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2010/deu_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
32986,276,"DEU","Germany","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2010/deu_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
32987,276,"DEU","Germany","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2010/deu_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
32988,276,"DEU","Germany","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2010/deu_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
32989,276,"DEU","Germany","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2011/deu_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
32990,276,"DEU","Germany","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2011/deu_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
32991,276,"DEU","Germany","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2011/deu_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
32992,276,"DEU","Germany","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2011/deu_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
32993,276,"DEU","Germany","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2011/deu_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
32994,276,"DEU","Germany","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2011/deu_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
32995,276,"DEU","Germany","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2011/deu_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
32996,276,"DEU","Germany","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2011/deu_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
32997,276,"DEU","Germany","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2012/deu_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
32998,276,"DEU","Germany","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2012/deu_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
32999,276,"DEU","Germany","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2012/deu_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
33000,276,"DEU","Germany","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2012/deu_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
33001,276,"DEU","Germany","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2012/deu_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
33002,276,"DEU","Germany","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2012/deu_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
33003,276,"DEU","Germany","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2012/deu_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
33004,276,"DEU","Germany","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2012/deu_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
33005,276,"DEU","Germany","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2013/deu_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
33006,276,"DEU","Germany","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2013/deu_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
33007,276,"DEU","Germany","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2013/deu_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
33008,276,"DEU","Germany","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2013/deu_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
33009,276,"DEU","Germany","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2013/deu_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
33010,276,"DEU","Germany","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2013/deu_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
33011,276,"DEU","Germany","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2013/deu_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
33012,276,"DEU","Germany","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2013/deu_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
33013,276,"DEU","Germany","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2014/deu_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
33014,276,"DEU","Germany","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2014/deu_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
33015,276,"DEU","Germany","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2014/deu_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
33016,276,"DEU","Germany","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2014/deu_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
33017,276,"DEU","Germany","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2014/deu_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
33018,276,"DEU","Germany","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2014/deu_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
33019,276,"DEU","Germany","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2014/deu_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
33020,276,"DEU","Germany","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2014/deu_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
33021,276,"DEU","Germany","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2015/deu_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
33022,276,"DEU","Germany","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2015/deu_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
33023,276,"DEU","Germany","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2015/deu_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
33024,276,"DEU","Germany","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2015/deu_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
33025,276,"DEU","Germany","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2015/deu_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
33026,276,"DEU","Germany","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2015/deu_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
33027,276,"DEU","Germany","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2015/deu_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
33028,276,"DEU","Germany","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Annual/2015/deu_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
33029,288,"GHA","Ghana","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2000/gha_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
33030,288,"GHA","Ghana","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2000/gha_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
33031,288,"GHA","Ghana","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2000/gha_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
33032,288,"GHA","Ghana","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2000/gha_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
33033,288,"GHA","Ghana","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2000/gha_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
33034,288,"GHA","Ghana","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2000/gha_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
33035,288,"GHA","Ghana","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2000/gha_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
33036,288,"GHA","Ghana","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2000/gha_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
33037,288,"GHA","Ghana","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2001/gha_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
33038,288,"GHA","Ghana","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2001/gha_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
33039,288,"GHA","Ghana","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2001/gha_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
33040,288,"GHA","Ghana","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2001/gha_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
33041,288,"GHA","Ghana","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2001/gha_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
33042,288,"GHA","Ghana","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2001/gha_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
33043,288,"GHA","Ghana","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2001/gha_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
33044,288,"GHA","Ghana","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2001/gha_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
33045,288,"GHA","Ghana","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2002/gha_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
33046,288,"GHA","Ghana","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2002/gha_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
33047,288,"GHA","Ghana","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2002/gha_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
33048,288,"GHA","Ghana","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2002/gha_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
33049,288,"GHA","Ghana","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2002/gha_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
33050,288,"GHA","Ghana","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2002/gha_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
33051,288,"GHA","Ghana","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2002/gha_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
33052,288,"GHA","Ghana","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2002/gha_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
33053,288,"GHA","Ghana","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2003/gha_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
33054,288,"GHA","Ghana","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2003/gha_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
33055,288,"GHA","Ghana","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2003/gha_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
33056,288,"GHA","Ghana","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2003/gha_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
33057,288,"GHA","Ghana","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2003/gha_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
33058,288,"GHA","Ghana","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2003/gha_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
33059,288,"GHA","Ghana","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2003/gha_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
33060,288,"GHA","Ghana","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2003/gha_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
33061,288,"GHA","Ghana","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2004/gha_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
33062,288,"GHA","Ghana","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2004/gha_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
33063,288,"GHA","Ghana","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2004/gha_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
33064,288,"GHA","Ghana","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2004/gha_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
33065,288,"GHA","Ghana","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2004/gha_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
33066,288,"GHA","Ghana","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2004/gha_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
33067,288,"GHA","Ghana","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2004/gha_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
33068,288,"GHA","Ghana","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2004/gha_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
33069,288,"GHA","Ghana","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2005/gha_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
33070,288,"GHA","Ghana","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2005/gha_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
33071,288,"GHA","Ghana","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2005/gha_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
33072,288,"GHA","Ghana","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2005/gha_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
33073,288,"GHA","Ghana","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2005/gha_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
33074,288,"GHA","Ghana","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2005/gha_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
33075,288,"GHA","Ghana","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2005/gha_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
33076,288,"GHA","Ghana","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2005/gha_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
33077,288,"GHA","Ghana","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2006/gha_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
33078,288,"GHA","Ghana","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2006/gha_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
33079,288,"GHA","Ghana","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2006/gha_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
33080,288,"GHA","Ghana","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2006/gha_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
33081,288,"GHA","Ghana","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2006/gha_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
33082,288,"GHA","Ghana","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2006/gha_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
33083,288,"GHA","Ghana","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2006/gha_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
33084,288,"GHA","Ghana","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2006/gha_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
33085,288,"GHA","Ghana","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2007/gha_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
33086,288,"GHA","Ghana","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2007/gha_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
33087,288,"GHA","Ghana","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2007/gha_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
33088,288,"GHA","Ghana","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2007/gha_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
33089,288,"GHA","Ghana","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2007/gha_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
33090,288,"GHA","Ghana","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2007/gha_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
33091,288,"GHA","Ghana","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2007/gha_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
33092,288,"GHA","Ghana","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2007/gha_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
33093,288,"GHA","Ghana","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2008/gha_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
33094,288,"GHA","Ghana","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2008/gha_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
33095,288,"GHA","Ghana","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2008/gha_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
33096,288,"GHA","Ghana","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2008/gha_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
33097,288,"GHA","Ghana","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2008/gha_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
33098,288,"GHA","Ghana","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2008/gha_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
33099,288,"GHA","Ghana","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2008/gha_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
33100,288,"GHA","Ghana","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2008/gha_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
33101,288,"GHA","Ghana","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2009/gha_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
33102,288,"GHA","Ghana","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2009/gha_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
33103,288,"GHA","Ghana","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2009/gha_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
33104,288,"GHA","Ghana","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2009/gha_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
33105,288,"GHA","Ghana","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2009/gha_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
33106,288,"GHA","Ghana","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2009/gha_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
33107,288,"GHA","Ghana","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2009/gha_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
33108,288,"GHA","Ghana","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2009/gha_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
33109,288,"GHA","Ghana","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2010/gha_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
33110,288,"GHA","Ghana","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2010/gha_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
33111,288,"GHA","Ghana","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2010/gha_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
33112,288,"GHA","Ghana","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2010/gha_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
33113,288,"GHA","Ghana","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2010/gha_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
33114,288,"GHA","Ghana","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2010/gha_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
33115,288,"GHA","Ghana","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2010/gha_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
33116,288,"GHA","Ghana","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2010/gha_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
33117,288,"GHA","Ghana","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2011/gha_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
33118,288,"GHA","Ghana","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2011/gha_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
33119,288,"GHA","Ghana","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2011/gha_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
33120,288,"GHA","Ghana","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2011/gha_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
33121,288,"GHA","Ghana","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2011/gha_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
33122,288,"GHA","Ghana","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2011/gha_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
33123,288,"GHA","Ghana","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2011/gha_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
33124,288,"GHA","Ghana","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2011/gha_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
33125,288,"GHA","Ghana","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2012/gha_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
33126,288,"GHA","Ghana","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2012/gha_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
33127,288,"GHA","Ghana","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2012/gha_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
33128,288,"GHA","Ghana","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2012/gha_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
33129,288,"GHA","Ghana","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2012/gha_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
33130,288,"GHA","Ghana","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2012/gha_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
33131,288,"GHA","Ghana","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2012/gha_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
33132,288,"GHA","Ghana","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2012/gha_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
33133,288,"GHA","Ghana","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2013/gha_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
33134,288,"GHA","Ghana","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2013/gha_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
33135,288,"GHA","Ghana","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2013/gha_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
33136,288,"GHA","Ghana","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2013/gha_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
33137,288,"GHA","Ghana","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2013/gha_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
33138,288,"GHA","Ghana","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2013/gha_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
33139,288,"GHA","Ghana","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2013/gha_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
33140,288,"GHA","Ghana","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2013/gha_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
33141,288,"GHA","Ghana","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2014/gha_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
33142,288,"GHA","Ghana","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2014/gha_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
33143,288,"GHA","Ghana","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2014/gha_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
33144,288,"GHA","Ghana","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2014/gha_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
33145,288,"GHA","Ghana","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2014/gha_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
33146,288,"GHA","Ghana","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2014/gha_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
33147,288,"GHA","Ghana","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2014/gha_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
33148,288,"GHA","Ghana","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2014/gha_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
33149,288,"GHA","Ghana","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2015/gha_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
33150,288,"GHA","Ghana","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2015/gha_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
33151,288,"GHA","Ghana","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2015/gha_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
33152,288,"GHA","Ghana","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2015/gha_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
33153,288,"GHA","Ghana","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2015/gha_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
33154,288,"GHA","Ghana","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2015/gha_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
33155,288,"GHA","Ghana","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2015/gha_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
33156,288,"GHA","Ghana","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Annual/2015/gha_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
33157,292,"GIB","Gibraltar","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2000/gib_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
33158,292,"GIB","Gibraltar","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2000/gib_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
33159,292,"GIB","Gibraltar","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2000/gib_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
33160,292,"GIB","Gibraltar","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2000/gib_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
33161,292,"GIB","Gibraltar","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2000/gib_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
33162,292,"GIB","Gibraltar","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2000/gib_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
33163,292,"GIB","Gibraltar","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2000/gib_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
33164,292,"GIB","Gibraltar","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2000/gib_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
33165,292,"GIB","Gibraltar","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2001/gib_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
33166,292,"GIB","Gibraltar","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2001/gib_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
33167,292,"GIB","Gibraltar","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2001/gib_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
33168,292,"GIB","Gibraltar","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2001/gib_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
33169,292,"GIB","Gibraltar","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2001/gib_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
33170,292,"GIB","Gibraltar","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2001/gib_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
33171,292,"GIB","Gibraltar","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2001/gib_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
33172,292,"GIB","Gibraltar","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2001/gib_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
33173,292,"GIB","Gibraltar","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2002/gib_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
33174,292,"GIB","Gibraltar","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2002/gib_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
33175,292,"GIB","Gibraltar","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2002/gib_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
33176,292,"GIB","Gibraltar","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2002/gib_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
33177,292,"GIB","Gibraltar","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2002/gib_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
33178,292,"GIB","Gibraltar","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2002/gib_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
33179,292,"GIB","Gibraltar","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2002/gib_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
33180,292,"GIB","Gibraltar","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2002/gib_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
33181,292,"GIB","Gibraltar","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2003/gib_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
33182,292,"GIB","Gibraltar","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2003/gib_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
33183,292,"GIB","Gibraltar","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2003/gib_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
33184,292,"GIB","Gibraltar","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2003/gib_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
33185,292,"GIB","Gibraltar","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2003/gib_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
33186,292,"GIB","Gibraltar","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2003/gib_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
33187,292,"GIB","Gibraltar","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2003/gib_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
33188,292,"GIB","Gibraltar","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2003/gib_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
33189,292,"GIB","Gibraltar","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2004/gib_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
33190,292,"GIB","Gibraltar","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2004/gib_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
33191,292,"GIB","Gibraltar","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2004/gib_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
33192,292,"GIB","Gibraltar","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2004/gib_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
33193,292,"GIB","Gibraltar","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2004/gib_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
33194,292,"GIB","Gibraltar","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2004/gib_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
33195,292,"GIB","Gibraltar","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2004/gib_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
33196,292,"GIB","Gibraltar","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2004/gib_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
33197,292,"GIB","Gibraltar","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2005/gib_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
33198,292,"GIB","Gibraltar","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2005/gib_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
33199,292,"GIB","Gibraltar","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2005/gib_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
33200,292,"GIB","Gibraltar","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2005/gib_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
33201,292,"GIB","Gibraltar","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2005/gib_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
33202,292,"GIB","Gibraltar","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2005/gib_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
33203,292,"GIB","Gibraltar","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2005/gib_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
33204,292,"GIB","Gibraltar","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2005/gib_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
33205,292,"GIB","Gibraltar","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2006/gib_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
33206,292,"GIB","Gibraltar","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2006/gib_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
33207,292,"GIB","Gibraltar","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2006/gib_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
33208,292,"GIB","Gibraltar","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2006/gib_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
33209,292,"GIB","Gibraltar","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2006/gib_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
33210,292,"GIB","Gibraltar","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2006/gib_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
33211,292,"GIB","Gibraltar","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2006/gib_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
33212,292,"GIB","Gibraltar","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2006/gib_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
33213,292,"GIB","Gibraltar","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2007/gib_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
33214,292,"GIB","Gibraltar","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2007/gib_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
33215,292,"GIB","Gibraltar","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2007/gib_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
33216,292,"GIB","Gibraltar","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2007/gib_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
33217,292,"GIB","Gibraltar","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2007/gib_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
33218,292,"GIB","Gibraltar","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2007/gib_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
33219,292,"GIB","Gibraltar","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2007/gib_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
33220,292,"GIB","Gibraltar","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2007/gib_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
33221,292,"GIB","Gibraltar","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2008/gib_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
33222,292,"GIB","Gibraltar","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2008/gib_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
33223,292,"GIB","Gibraltar","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2008/gib_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
33224,292,"GIB","Gibraltar","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2008/gib_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
33225,292,"GIB","Gibraltar","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2008/gib_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
33226,292,"GIB","Gibraltar","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2008/gib_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
33227,292,"GIB","Gibraltar","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2008/gib_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
33228,292,"GIB","Gibraltar","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2008/gib_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
33229,292,"GIB","Gibraltar","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2009/gib_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
33230,292,"GIB","Gibraltar","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2009/gib_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
33231,292,"GIB","Gibraltar","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2009/gib_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
33232,292,"GIB","Gibraltar","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2009/gib_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
33233,292,"GIB","Gibraltar","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2009/gib_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
33234,292,"GIB","Gibraltar","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2009/gib_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
33235,292,"GIB","Gibraltar","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2009/gib_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
33236,292,"GIB","Gibraltar","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2009/gib_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
33237,292,"GIB","Gibraltar","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2010/gib_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
33238,292,"GIB","Gibraltar","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2010/gib_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
33239,292,"GIB","Gibraltar","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2010/gib_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
33240,292,"GIB","Gibraltar","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2010/gib_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
33241,292,"GIB","Gibraltar","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2010/gib_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
33242,292,"GIB","Gibraltar","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2010/gib_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
33243,292,"GIB","Gibraltar","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2010/gib_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
33244,292,"GIB","Gibraltar","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2010/gib_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
33245,292,"GIB","Gibraltar","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2011/gib_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
33246,292,"GIB","Gibraltar","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2011/gib_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
33247,292,"GIB","Gibraltar","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2011/gib_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
33248,292,"GIB","Gibraltar","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2011/gib_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
33249,292,"GIB","Gibraltar","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2011/gib_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
33250,292,"GIB","Gibraltar","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2011/gib_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
33251,292,"GIB","Gibraltar","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2011/gib_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
33252,292,"GIB","Gibraltar","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2011/gib_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
33253,292,"GIB","Gibraltar","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2012/gib_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
33254,292,"GIB","Gibraltar","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2012/gib_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
33255,292,"GIB","Gibraltar","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2012/gib_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
33256,292,"GIB","Gibraltar","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2012/gib_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
33257,292,"GIB","Gibraltar","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2012/gib_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
33258,292,"GIB","Gibraltar","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2012/gib_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
33259,292,"GIB","Gibraltar","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2012/gib_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
33260,292,"GIB","Gibraltar","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2012/gib_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
33261,292,"GIB","Gibraltar","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2013/gib_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
33262,292,"GIB","Gibraltar","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2013/gib_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
33263,292,"GIB","Gibraltar","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2013/gib_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
33264,292,"GIB","Gibraltar","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2013/gib_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
33265,292,"GIB","Gibraltar","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2013/gib_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
33266,292,"GIB","Gibraltar","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2013/gib_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
33267,292,"GIB","Gibraltar","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2013/gib_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
33268,292,"GIB","Gibraltar","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2013/gib_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
33269,292,"GIB","Gibraltar","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2014/gib_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
33270,292,"GIB","Gibraltar","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2014/gib_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
33271,292,"GIB","Gibraltar","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2014/gib_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
33272,292,"GIB","Gibraltar","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2014/gib_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
33273,292,"GIB","Gibraltar","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2014/gib_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
33274,292,"GIB","Gibraltar","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2014/gib_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
33275,292,"GIB","Gibraltar","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2014/gib_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
33276,292,"GIB","Gibraltar","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2014/gib_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
33277,292,"GIB","Gibraltar","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2015/gib_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
33278,292,"GIB","Gibraltar","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2015/gib_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
33279,292,"GIB","Gibraltar","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2015/gib_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
33280,292,"GIB","Gibraltar","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2015/gib_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
33281,292,"GIB","Gibraltar","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2015/gib_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
33282,292,"GIB","Gibraltar","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2015/gib_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
33283,292,"GIB","Gibraltar","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2015/gib_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
33284,292,"GIB","Gibraltar","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Annual/2015/gib_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
33285,296,"KIR","Kiribati","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2000/kir_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
33286,296,"KIR","Kiribati","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2000/kir_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
33287,296,"KIR","Kiribati","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2000/kir_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
33288,296,"KIR","Kiribati","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2000/kir_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
33289,296,"KIR","Kiribati","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2000/kir_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
33290,296,"KIR","Kiribati","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2000/kir_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
33291,296,"KIR","Kiribati","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2000/kir_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
33292,296,"KIR","Kiribati","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2000/kir_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
33293,296,"KIR","Kiribati","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2001/kir_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
33294,296,"KIR","Kiribati","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2001/kir_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
33295,296,"KIR","Kiribati","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2001/kir_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
33296,296,"KIR","Kiribati","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2001/kir_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
33297,296,"KIR","Kiribati","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2001/kir_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
33298,296,"KIR","Kiribati","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2001/kir_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
33299,296,"KIR","Kiribati","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2001/kir_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
33300,296,"KIR","Kiribati","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2001/kir_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
33301,296,"KIR","Kiribati","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2002/kir_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
33302,296,"KIR","Kiribati","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2002/kir_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
33303,296,"KIR","Kiribati","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2002/kir_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
33304,296,"KIR","Kiribati","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2002/kir_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
33305,296,"KIR","Kiribati","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2002/kir_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
33306,296,"KIR","Kiribati","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2002/kir_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
33307,296,"KIR","Kiribati","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2002/kir_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
33308,296,"KIR","Kiribati","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2002/kir_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
33309,296,"KIR","Kiribati","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2003/kir_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
33310,296,"KIR","Kiribati","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2003/kir_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
33311,296,"KIR","Kiribati","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2003/kir_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
33312,296,"KIR","Kiribati","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2003/kir_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
33313,296,"KIR","Kiribati","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2003/kir_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
33314,296,"KIR","Kiribati","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2003/kir_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
33315,296,"KIR","Kiribati","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2003/kir_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
33316,296,"KIR","Kiribati","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2003/kir_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
33317,296,"KIR","Kiribati","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2004/kir_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
33318,296,"KIR","Kiribati","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2004/kir_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
33319,296,"KIR","Kiribati","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2004/kir_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
33320,296,"KIR","Kiribati","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2004/kir_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
33321,296,"KIR","Kiribati","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2004/kir_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
33322,296,"KIR","Kiribati","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2004/kir_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
33323,296,"KIR","Kiribati","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2004/kir_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
33324,296,"KIR","Kiribati","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2004/kir_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
33325,296,"KIR","Kiribati","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2005/kir_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
33326,296,"KIR","Kiribati","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2005/kir_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
33327,296,"KIR","Kiribati","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2005/kir_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
33328,296,"KIR","Kiribati","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2005/kir_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
33329,296,"KIR","Kiribati","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2005/kir_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
33330,296,"KIR","Kiribati","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2005/kir_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
33331,296,"KIR","Kiribati","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2005/kir_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
33332,296,"KIR","Kiribati","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2005/kir_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
33333,296,"KIR","Kiribati","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2006/kir_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
33334,296,"KIR","Kiribati","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2006/kir_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
33335,296,"KIR","Kiribati","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2006/kir_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
33336,296,"KIR","Kiribati","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2006/kir_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
33337,296,"KIR","Kiribati","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2006/kir_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
33338,296,"KIR","Kiribati","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2006/kir_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
33339,296,"KIR","Kiribati","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2006/kir_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
33340,296,"KIR","Kiribati","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2006/kir_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
33341,296,"KIR","Kiribati","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2007/kir_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
33342,296,"KIR","Kiribati","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2007/kir_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
33343,296,"KIR","Kiribati","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2007/kir_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
33344,296,"KIR","Kiribati","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2007/kir_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
33345,296,"KIR","Kiribati","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2007/kir_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
33346,296,"KIR","Kiribati","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2007/kir_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
33347,296,"KIR","Kiribati","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2007/kir_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
33348,296,"KIR","Kiribati","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2007/kir_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
33349,296,"KIR","Kiribati","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2008/kir_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
33350,296,"KIR","Kiribati","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2008/kir_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
33351,296,"KIR","Kiribati","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2008/kir_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
33352,296,"KIR","Kiribati","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2008/kir_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
33353,296,"KIR","Kiribati","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2008/kir_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
33354,296,"KIR","Kiribati","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2008/kir_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
33355,296,"KIR","Kiribati","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2008/kir_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
33356,296,"KIR","Kiribati","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2008/kir_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
33357,296,"KIR","Kiribati","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2009/kir_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
33358,296,"KIR","Kiribati","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2009/kir_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
33359,296,"KIR","Kiribati","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2009/kir_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
33360,296,"KIR","Kiribati","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2009/kir_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
33361,296,"KIR","Kiribati","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2009/kir_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
33362,296,"KIR","Kiribati","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2009/kir_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
33363,296,"KIR","Kiribati","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2009/kir_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
33364,296,"KIR","Kiribati","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2009/kir_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
33365,296,"KIR","Kiribati","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2010/kir_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
33366,296,"KIR","Kiribati","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2010/kir_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
33367,296,"KIR","Kiribati","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2010/kir_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
33368,296,"KIR","Kiribati","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2010/kir_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
33369,296,"KIR","Kiribati","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2010/kir_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
33370,296,"KIR","Kiribati","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2010/kir_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
33371,296,"KIR","Kiribati","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2010/kir_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
33372,296,"KIR","Kiribati","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2010/kir_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
33373,296,"KIR","Kiribati","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2011/kir_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
33374,296,"KIR","Kiribati","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2011/kir_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
33375,296,"KIR","Kiribati","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2011/kir_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
33376,296,"KIR","Kiribati","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2011/kir_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
33377,296,"KIR","Kiribati","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2011/kir_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
33378,296,"KIR","Kiribati","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2011/kir_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
33379,296,"KIR","Kiribati","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2011/kir_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
33380,296,"KIR","Kiribati","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2011/kir_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
33381,296,"KIR","Kiribati","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2012/kir_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
33382,296,"KIR","Kiribati","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2012/kir_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
33383,296,"KIR","Kiribati","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2012/kir_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
33384,296,"KIR","Kiribati","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2012/kir_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
33385,296,"KIR","Kiribati","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2012/kir_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
33386,296,"KIR","Kiribati","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2012/kir_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
33387,296,"KIR","Kiribati","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2012/kir_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
33388,296,"KIR","Kiribati","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2012/kir_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
33389,296,"KIR","Kiribati","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2013/kir_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
33390,296,"KIR","Kiribati","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2013/kir_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
33391,296,"KIR","Kiribati","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2013/kir_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
33392,296,"KIR","Kiribati","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2013/kir_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
33393,296,"KIR","Kiribati","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2013/kir_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
33394,296,"KIR","Kiribati","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2013/kir_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
33395,296,"KIR","Kiribati","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2013/kir_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
33396,296,"KIR","Kiribati","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2013/kir_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
33397,296,"KIR","Kiribati","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2014/kir_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
33398,296,"KIR","Kiribati","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2014/kir_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
33399,296,"KIR","Kiribati","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2014/kir_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
33400,296,"KIR","Kiribati","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2014/kir_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
33401,296,"KIR","Kiribati","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2014/kir_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
33402,296,"KIR","Kiribati","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2014/kir_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
33403,296,"KIR","Kiribati","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2014/kir_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
33404,296,"KIR","Kiribati","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2014/kir_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
33405,296,"KIR","Kiribati","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2015/kir_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
33406,296,"KIR","Kiribati","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2015/kir_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
33407,296,"KIR","Kiribati","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2015/kir_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
33408,296,"KIR","Kiribati","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2015/kir_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
33409,296,"KIR","Kiribati","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2015/kir_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
33410,296,"KIR","Kiribati","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2015/kir_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
33411,296,"KIR","Kiribati","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2015/kir_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
33412,296,"KIR","Kiribati","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Annual/2015/kir_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
33413,300,"GRC","Greece","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2000/grc_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
33414,300,"GRC","Greece","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2000/grc_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
33415,300,"GRC","Greece","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2000/grc_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
33416,300,"GRC","Greece","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2000/grc_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
33417,300,"GRC","Greece","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2000/grc_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
33418,300,"GRC","Greece","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2000/grc_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
33419,300,"GRC","Greece","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2000/grc_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
33420,300,"GRC","Greece","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2000/grc_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
33421,300,"GRC","Greece","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2001/grc_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
33422,300,"GRC","Greece","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2001/grc_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
33423,300,"GRC","Greece","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2001/grc_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
33424,300,"GRC","Greece","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2001/grc_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
33425,300,"GRC","Greece","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2001/grc_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
33426,300,"GRC","Greece","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2001/grc_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
33427,300,"GRC","Greece","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2001/grc_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
33428,300,"GRC","Greece","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2001/grc_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
33429,300,"GRC","Greece","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2002/grc_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
33430,300,"GRC","Greece","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2002/grc_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
33431,300,"GRC","Greece","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2002/grc_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
33432,300,"GRC","Greece","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2002/grc_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
33433,300,"GRC","Greece","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2002/grc_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
33434,300,"GRC","Greece","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2002/grc_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
33435,300,"GRC","Greece","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2002/grc_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
33436,300,"GRC","Greece","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2002/grc_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
33437,300,"GRC","Greece","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2003/grc_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
33438,300,"GRC","Greece","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2003/grc_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
33439,300,"GRC","Greece","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2003/grc_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
33440,300,"GRC","Greece","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2003/grc_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
33441,300,"GRC","Greece","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2003/grc_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
33442,300,"GRC","Greece","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2003/grc_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
33443,300,"GRC","Greece","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2003/grc_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
33444,300,"GRC","Greece","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2003/grc_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
33445,300,"GRC","Greece","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2004/grc_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
33446,300,"GRC","Greece","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2004/grc_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
33447,300,"GRC","Greece","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2004/grc_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
33448,300,"GRC","Greece","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2004/grc_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
33449,300,"GRC","Greece","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2004/grc_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
33450,300,"GRC","Greece","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2004/grc_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
33451,300,"GRC","Greece","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2004/grc_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
33452,300,"GRC","Greece","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2004/grc_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
33453,300,"GRC","Greece","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2005/grc_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
33454,300,"GRC","Greece","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2005/grc_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
33455,300,"GRC","Greece","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2005/grc_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
33456,300,"GRC","Greece","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2005/grc_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
33457,300,"GRC","Greece","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2005/grc_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
33458,300,"GRC","Greece","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2005/grc_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
33459,300,"GRC","Greece","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2005/grc_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
33460,300,"GRC","Greece","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2005/grc_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
33461,300,"GRC","Greece","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2006/grc_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
33462,300,"GRC","Greece","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2006/grc_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
33463,300,"GRC","Greece","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2006/grc_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
33464,300,"GRC","Greece","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2006/grc_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
33465,300,"GRC","Greece","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2006/grc_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
33466,300,"GRC","Greece","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2006/grc_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
33467,300,"GRC","Greece","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2006/grc_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
33468,300,"GRC","Greece","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2006/grc_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
33469,300,"GRC","Greece","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2007/grc_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
33470,300,"GRC","Greece","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2007/grc_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
33471,300,"GRC","Greece","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2007/grc_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
33472,300,"GRC","Greece","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2007/grc_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
33473,300,"GRC","Greece","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2007/grc_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
33474,300,"GRC","Greece","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2007/grc_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
33475,300,"GRC","Greece","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2007/grc_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
33476,300,"GRC","Greece","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2007/grc_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
33477,300,"GRC","Greece","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2008/grc_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
33478,300,"GRC","Greece","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2008/grc_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
33479,300,"GRC","Greece","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2008/grc_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
33480,300,"GRC","Greece","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2008/grc_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
33481,300,"GRC","Greece","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2008/grc_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
33482,300,"GRC","Greece","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2008/grc_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
33483,300,"GRC","Greece","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2008/grc_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
33484,300,"GRC","Greece","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2008/grc_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
33485,300,"GRC","Greece","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2009/grc_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
33486,300,"GRC","Greece","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2009/grc_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
33487,300,"GRC","Greece","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2009/grc_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
33488,300,"GRC","Greece","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2009/grc_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
33489,300,"GRC","Greece","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2009/grc_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
33490,300,"GRC","Greece","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2009/grc_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
33491,300,"GRC","Greece","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2009/grc_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
33492,300,"GRC","Greece","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2009/grc_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
33493,300,"GRC","Greece","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2010/grc_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
33494,300,"GRC","Greece","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2010/grc_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
33495,300,"GRC","Greece","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2010/grc_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
33496,300,"GRC","Greece","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2010/grc_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
33497,300,"GRC","Greece","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2010/grc_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
33498,300,"GRC","Greece","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2010/grc_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
33499,300,"GRC","Greece","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2010/grc_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
33500,300,"GRC","Greece","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2010/grc_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
33501,300,"GRC","Greece","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2011/grc_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
33502,300,"GRC","Greece","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2011/grc_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
33503,300,"GRC","Greece","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2011/grc_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
33504,300,"GRC","Greece","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2011/grc_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
33505,300,"GRC","Greece","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2011/grc_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
33506,300,"GRC","Greece","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2011/grc_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
33507,300,"GRC","Greece","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2011/grc_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
33508,300,"GRC","Greece","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2011/grc_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
33509,300,"GRC","Greece","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2012/grc_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
33510,300,"GRC","Greece","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2012/grc_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
33511,300,"GRC","Greece","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2012/grc_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
33512,300,"GRC","Greece","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2012/grc_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
33513,300,"GRC","Greece","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2012/grc_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
33514,300,"GRC","Greece","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2012/grc_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
33515,300,"GRC","Greece","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2012/grc_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
33516,300,"GRC","Greece","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2012/grc_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
33517,300,"GRC","Greece","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2013/grc_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
33518,300,"GRC","Greece","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2013/grc_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
33519,300,"GRC","Greece","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2013/grc_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
33520,300,"GRC","Greece","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2013/grc_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
33521,300,"GRC","Greece","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2013/grc_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
33522,300,"GRC","Greece","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2013/grc_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
33523,300,"GRC","Greece","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2013/grc_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
33524,300,"GRC","Greece","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2013/grc_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
33525,300,"GRC","Greece","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2014/grc_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
33526,300,"GRC","Greece","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2014/grc_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
33527,300,"GRC","Greece","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2014/grc_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
33528,300,"GRC","Greece","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2014/grc_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
33529,300,"GRC","Greece","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2014/grc_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
33530,300,"GRC","Greece","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2014/grc_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
33531,300,"GRC","Greece","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2014/grc_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
33532,300,"GRC","Greece","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2014/grc_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
33533,300,"GRC","Greece","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2015/grc_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
33534,300,"GRC","Greece","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2015/grc_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
33535,300,"GRC","Greece","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2015/grc_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
33536,300,"GRC","Greece","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2015/grc_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
33537,300,"GRC","Greece","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2015/grc_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
33538,300,"GRC","Greece","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2015/grc_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
33539,300,"GRC","Greece","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2015/grc_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
33540,300,"GRC","Greece","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Annual/2015/grc_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
33541,308,"GRD","Grenada","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2000/grd_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
33542,308,"GRD","Grenada","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2000/grd_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
33543,308,"GRD","Grenada","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2000/grd_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
33544,308,"GRD","Grenada","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2000/grd_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
33545,308,"GRD","Grenada","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2000/grd_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
33546,308,"GRD","Grenada","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2000/grd_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
33547,308,"GRD","Grenada","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2000/grd_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
33548,308,"GRD","Grenada","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2000/grd_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
33549,308,"GRD","Grenada","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2001/grd_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
33550,308,"GRD","Grenada","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2001/grd_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
33551,308,"GRD","Grenada","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2001/grd_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
33552,308,"GRD","Grenada","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2001/grd_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
33553,308,"GRD","Grenada","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2001/grd_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
33554,308,"GRD","Grenada","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2001/grd_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
33555,308,"GRD","Grenada","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2001/grd_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
33556,308,"GRD","Grenada","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2001/grd_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
33557,308,"GRD","Grenada","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2002/grd_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
33558,308,"GRD","Grenada","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2002/grd_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
33559,308,"GRD","Grenada","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2002/grd_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
33560,308,"GRD","Grenada","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2002/grd_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
33561,308,"GRD","Grenada","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2002/grd_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
33562,308,"GRD","Grenada","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2002/grd_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
33563,308,"GRD","Grenada","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2002/grd_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
33564,308,"GRD","Grenada","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2002/grd_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
33565,308,"GRD","Grenada","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2003/grd_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
33566,308,"GRD","Grenada","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2003/grd_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
33567,308,"GRD","Grenada","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2003/grd_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
33568,308,"GRD","Grenada","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2003/grd_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
33569,308,"GRD","Grenada","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2003/grd_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
33570,308,"GRD","Grenada","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2003/grd_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
33571,308,"GRD","Grenada","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2003/grd_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
33572,308,"GRD","Grenada","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2003/grd_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
33573,308,"GRD","Grenada","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2004/grd_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
33574,308,"GRD","Grenada","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2004/grd_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
33575,308,"GRD","Grenada","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2004/grd_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
33576,308,"GRD","Grenada","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2004/grd_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
33577,308,"GRD","Grenada","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2004/grd_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
33578,308,"GRD","Grenada","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2004/grd_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
33579,308,"GRD","Grenada","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2004/grd_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
33580,308,"GRD","Grenada","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2004/grd_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
33581,308,"GRD","Grenada","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2005/grd_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
33582,308,"GRD","Grenada","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2005/grd_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
33583,308,"GRD","Grenada","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2005/grd_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
33584,308,"GRD","Grenada","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2005/grd_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
33585,308,"GRD","Grenada","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2005/grd_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
33586,308,"GRD","Grenada","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2005/grd_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
33587,308,"GRD","Grenada","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2005/grd_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
33588,308,"GRD","Grenada","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2005/grd_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
33589,308,"GRD","Grenada","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2006/grd_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
33590,308,"GRD","Grenada","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2006/grd_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
33591,308,"GRD","Grenada","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2006/grd_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
33592,308,"GRD","Grenada","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2006/grd_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
33593,308,"GRD","Grenada","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2006/grd_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
33594,308,"GRD","Grenada","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2006/grd_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
33595,308,"GRD","Grenada","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2006/grd_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
33596,308,"GRD","Grenada","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2006/grd_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
33597,308,"GRD","Grenada","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2007/grd_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
33598,308,"GRD","Grenada","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2007/grd_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
33599,308,"GRD","Grenada","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2007/grd_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
33600,308,"GRD","Grenada","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2007/grd_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
33601,308,"GRD","Grenada","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2007/grd_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
33602,308,"GRD","Grenada","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2007/grd_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
33603,308,"GRD","Grenada","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2007/grd_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
33604,308,"GRD","Grenada","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2007/grd_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
33605,308,"GRD","Grenada","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2008/grd_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
33606,308,"GRD","Grenada","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2008/grd_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
33607,308,"GRD","Grenada","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2008/grd_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
33608,308,"GRD","Grenada","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2008/grd_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
33609,308,"GRD","Grenada","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2008/grd_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
33610,308,"GRD","Grenada","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2008/grd_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
33611,308,"GRD","Grenada","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2008/grd_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
33612,308,"GRD","Grenada","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2008/grd_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
33613,308,"GRD","Grenada","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2009/grd_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
33614,308,"GRD","Grenada","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2009/grd_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
33615,308,"GRD","Grenada","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2009/grd_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
33616,308,"GRD","Grenada","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2009/grd_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
33617,308,"GRD","Grenada","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2009/grd_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
33618,308,"GRD","Grenada","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2009/grd_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
33619,308,"GRD","Grenada","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2009/grd_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
33620,308,"GRD","Grenada","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2009/grd_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
33621,308,"GRD","Grenada","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2010/grd_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
33622,308,"GRD","Grenada","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2010/grd_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
33623,308,"GRD","Grenada","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2010/grd_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
33624,308,"GRD","Grenada","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2010/grd_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
33625,308,"GRD","Grenada","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2010/grd_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
33626,308,"GRD","Grenada","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2010/grd_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
33627,308,"GRD","Grenada","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2010/grd_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
33628,308,"GRD","Grenada","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2010/grd_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
33629,308,"GRD","Grenada","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2011/grd_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
33630,308,"GRD","Grenada","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2011/grd_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
33631,308,"GRD","Grenada","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2011/grd_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
33632,308,"GRD","Grenada","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2011/grd_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
33633,308,"GRD","Grenada","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2011/grd_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
33634,308,"GRD","Grenada","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2011/grd_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
33635,308,"GRD","Grenada","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2011/grd_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
33636,308,"GRD","Grenada","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2011/grd_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
33637,308,"GRD","Grenada","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2012/grd_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
33638,308,"GRD","Grenada","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2012/grd_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
33639,308,"GRD","Grenada","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2012/grd_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
33640,308,"GRD","Grenada","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2012/grd_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
33641,308,"GRD","Grenada","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2012/grd_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
33642,308,"GRD","Grenada","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2012/grd_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
33643,308,"GRD","Grenada","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2012/grd_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
33644,308,"GRD","Grenada","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2012/grd_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
33645,308,"GRD","Grenada","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2013/grd_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
33646,308,"GRD","Grenada","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2013/grd_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
33647,308,"GRD","Grenada","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2013/grd_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
33648,308,"GRD","Grenada","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2013/grd_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
33649,308,"GRD","Grenada","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2013/grd_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
33650,308,"GRD","Grenada","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2013/grd_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
33651,308,"GRD","Grenada","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2013/grd_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
33652,308,"GRD","Grenada","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2013/grd_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
33653,308,"GRD","Grenada","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2014/grd_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
33654,308,"GRD","Grenada","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2014/grd_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
33655,308,"GRD","Grenada","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2014/grd_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
33656,308,"GRD","Grenada","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2014/grd_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
33657,308,"GRD","Grenada","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2014/grd_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
33658,308,"GRD","Grenada","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2014/grd_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
33659,308,"GRD","Grenada","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2014/grd_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
33660,308,"GRD","Grenada","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2014/grd_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
33661,308,"GRD","Grenada","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2015/grd_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
33662,308,"GRD","Grenada","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2015/grd_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
33663,308,"GRD","Grenada","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2015/grd_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
33664,308,"GRD","Grenada","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2015/grd_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
33665,308,"GRD","Grenada","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2015/grd_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
33666,308,"GRD","Grenada","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2015/grd_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
33667,308,"GRD","Grenada","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2015/grd_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
33668,308,"GRD","Grenada","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Annual/2015/grd_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
33669,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2000/glp_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
33670,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2000/glp_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
33671,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2000/glp_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
33672,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2000/glp_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
33673,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2000/glp_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
33674,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2000/glp_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
33675,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2000/glp_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
33676,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2000/glp_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
33677,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2001/glp_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
33678,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2001/glp_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
33679,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2001/glp_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
33680,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2001/glp_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
33681,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2001/glp_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
33682,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2001/glp_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
33683,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2001/glp_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
33684,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2001/glp_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
33685,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2002/glp_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
33686,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2002/glp_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
33687,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2002/glp_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
33688,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2002/glp_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
33689,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2002/glp_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
33690,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2002/glp_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
33691,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2002/glp_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
33692,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2002/glp_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
33693,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2003/glp_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
33694,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2003/glp_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
33695,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2003/glp_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
33696,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2003/glp_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
33697,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2003/glp_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
33698,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2003/glp_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
33699,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2003/glp_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
33700,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2003/glp_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
33701,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2004/glp_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
33702,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2004/glp_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
33703,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2004/glp_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
33704,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2004/glp_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
33705,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2004/glp_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
33706,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2004/glp_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
33707,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2004/glp_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
33708,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2004/glp_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
33709,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2005/glp_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
33710,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2005/glp_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
33711,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2005/glp_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
33712,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2005/glp_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
33713,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2005/glp_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
33714,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2005/glp_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
33715,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2005/glp_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
33716,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2005/glp_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
33717,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2006/glp_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
33718,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2006/glp_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
33719,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2006/glp_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
33720,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2006/glp_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
33721,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2006/glp_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
33722,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2006/glp_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
33723,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2006/glp_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
33724,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2006/glp_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
33725,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2007/glp_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
33726,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2007/glp_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
33727,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2007/glp_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
33728,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2007/glp_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
33729,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2007/glp_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
33730,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2007/glp_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
33731,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2007/glp_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
33732,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2007/glp_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
33733,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2008/glp_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
33734,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2008/glp_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
33735,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2008/glp_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
33736,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2008/glp_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
33737,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2008/glp_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
33738,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2008/glp_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
33739,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2008/glp_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
33740,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2008/glp_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
33741,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2009/glp_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
33742,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2009/glp_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
33743,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2009/glp_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
33744,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2009/glp_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
33745,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2009/glp_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
33746,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2009/glp_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
33747,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2009/glp_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
33748,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2009/glp_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
33749,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2010/glp_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
33750,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2010/glp_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
33751,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2010/glp_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
33752,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2010/glp_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
33753,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2010/glp_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
33754,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2010/glp_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
33755,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2010/glp_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
33756,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2010/glp_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
33757,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2011/glp_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
33758,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2011/glp_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
33759,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2011/glp_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
33760,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2011/glp_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
33761,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2011/glp_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
33762,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2011/glp_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
33763,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2011/glp_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
33764,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2011/glp_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
33765,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2012/glp_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
33766,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2012/glp_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
33767,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2012/glp_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
33768,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2012/glp_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
33769,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2012/glp_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
33770,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2012/glp_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
33771,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2012/glp_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
33772,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2012/glp_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
33773,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2013/glp_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
33774,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2013/glp_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
33775,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2013/glp_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
33776,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2013/glp_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
33777,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2013/glp_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
33778,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2013/glp_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
33779,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2013/glp_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
33780,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2013/glp_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
33781,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2014/glp_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
33782,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2014/glp_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
33783,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2014/glp_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
33784,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2014/glp_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
33785,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2014/glp_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
33786,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2014/glp_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
33787,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2014/glp_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
33788,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2014/glp_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
33789,312,"GLP","Guadeloupe","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2015/glp_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
33790,312,"GLP","Guadeloupe","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2015/glp_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
33791,312,"GLP","Guadeloupe","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2015/glp_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
33792,312,"GLP","Guadeloupe","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2015/glp_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
33793,312,"GLP","Guadeloupe","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2015/glp_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
33794,312,"GLP","Guadeloupe","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2015/glp_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
33795,312,"GLP","Guadeloupe","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2015/glp_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
33796,312,"GLP","Guadeloupe","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Annual/2015/glp_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
33797,316,"GUM","Guam","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2000/gum_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
33798,316,"GUM","Guam","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2000/gum_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
33799,316,"GUM","Guam","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2000/gum_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
33800,316,"GUM","Guam","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2000/gum_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
33801,316,"GUM","Guam","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2000/gum_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
33802,316,"GUM","Guam","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2000/gum_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
33803,316,"GUM","Guam","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2000/gum_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
33804,316,"GUM","Guam","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2000/gum_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
33805,316,"GUM","Guam","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2001/gum_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
33806,316,"GUM","Guam","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2001/gum_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
33807,316,"GUM","Guam","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2001/gum_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
33808,316,"GUM","Guam","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2001/gum_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
33809,316,"GUM","Guam","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2001/gum_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
33810,316,"GUM","Guam","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2001/gum_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
33811,316,"GUM","Guam","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2001/gum_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
33812,316,"GUM","Guam","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2001/gum_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
33813,316,"GUM","Guam","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2002/gum_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
33814,316,"GUM","Guam","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2002/gum_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
33815,316,"GUM","Guam","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2002/gum_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
33816,316,"GUM","Guam","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2002/gum_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
33817,316,"GUM","Guam","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2002/gum_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
33818,316,"GUM","Guam","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2002/gum_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
33819,316,"GUM","Guam","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2002/gum_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
33820,316,"GUM","Guam","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2002/gum_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
33821,316,"GUM","Guam","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2003/gum_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
33822,316,"GUM","Guam","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2003/gum_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
33823,316,"GUM","Guam","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2003/gum_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
33824,316,"GUM","Guam","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2003/gum_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
33825,316,"GUM","Guam","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2003/gum_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
33826,316,"GUM","Guam","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2003/gum_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
33827,316,"GUM","Guam","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2003/gum_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
33828,316,"GUM","Guam","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2003/gum_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
33829,316,"GUM","Guam","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2004/gum_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
33830,316,"GUM","Guam","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2004/gum_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
33831,316,"GUM","Guam","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2004/gum_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
33832,316,"GUM","Guam","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2004/gum_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
33833,316,"GUM","Guam","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2004/gum_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
33834,316,"GUM","Guam","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2004/gum_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
33835,316,"GUM","Guam","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2004/gum_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
33836,316,"GUM","Guam","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2004/gum_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
33837,316,"GUM","Guam","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2005/gum_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
33838,316,"GUM","Guam","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2005/gum_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
33839,316,"GUM","Guam","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2005/gum_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
33840,316,"GUM","Guam","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2005/gum_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
33841,316,"GUM","Guam","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2005/gum_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
33842,316,"GUM","Guam","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2005/gum_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
33843,316,"GUM","Guam","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2005/gum_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
33844,316,"GUM","Guam","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2005/gum_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
33845,316,"GUM","Guam","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2006/gum_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
33846,316,"GUM","Guam","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2006/gum_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
33847,316,"GUM","Guam","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2006/gum_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
33848,316,"GUM","Guam","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2006/gum_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
33849,316,"GUM","Guam","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2006/gum_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
33850,316,"GUM","Guam","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2006/gum_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
33851,316,"GUM","Guam","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2006/gum_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
33852,316,"GUM","Guam","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2006/gum_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
33853,316,"GUM","Guam","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2007/gum_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
33854,316,"GUM","Guam","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2007/gum_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
33855,316,"GUM","Guam","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2007/gum_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
33856,316,"GUM","Guam","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2007/gum_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
33857,316,"GUM","Guam","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2007/gum_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
33858,316,"GUM","Guam","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2007/gum_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
33859,316,"GUM","Guam","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2007/gum_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
33860,316,"GUM","Guam","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2007/gum_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
33861,316,"GUM","Guam","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2008/gum_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
33862,316,"GUM","Guam","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2008/gum_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
33863,316,"GUM","Guam","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2008/gum_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
33864,316,"GUM","Guam","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2008/gum_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
33865,316,"GUM","Guam","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2008/gum_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
33866,316,"GUM","Guam","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2008/gum_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
33867,316,"GUM","Guam","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2008/gum_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
33868,316,"GUM","Guam","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2008/gum_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
33869,316,"GUM","Guam","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2009/gum_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
33870,316,"GUM","Guam","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2009/gum_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
33871,316,"GUM","Guam","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2009/gum_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
33872,316,"GUM","Guam","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2009/gum_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
33873,316,"GUM","Guam","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2009/gum_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
33874,316,"GUM","Guam","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2009/gum_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
33875,316,"GUM","Guam","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2009/gum_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
33876,316,"GUM","Guam","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2009/gum_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
33877,316,"GUM","Guam","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2010/gum_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
33878,316,"GUM","Guam","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2010/gum_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
33879,316,"GUM","Guam","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2010/gum_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
33880,316,"GUM","Guam","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2010/gum_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
33881,316,"GUM","Guam","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2010/gum_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
33882,316,"GUM","Guam","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2010/gum_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
33883,316,"GUM","Guam","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2010/gum_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
33884,316,"GUM","Guam","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2010/gum_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
33885,316,"GUM","Guam","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2011/gum_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
33886,316,"GUM","Guam","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2011/gum_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
33887,316,"GUM","Guam","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2011/gum_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
33888,316,"GUM","Guam","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2011/gum_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
33889,316,"GUM","Guam","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2011/gum_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
33890,316,"GUM","Guam","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2011/gum_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
33891,316,"GUM","Guam","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2011/gum_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
33892,316,"GUM","Guam","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2011/gum_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
33893,316,"GUM","Guam","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2012/gum_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
33894,316,"GUM","Guam","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2012/gum_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
33895,316,"GUM","Guam","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2012/gum_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
33896,316,"GUM","Guam","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2012/gum_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
33897,316,"GUM","Guam","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2012/gum_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
33898,316,"GUM","Guam","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2012/gum_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
33899,316,"GUM","Guam","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2012/gum_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
33900,316,"GUM","Guam","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2012/gum_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
33901,316,"GUM","Guam","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2013/gum_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
33902,316,"GUM","Guam","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2013/gum_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
33903,316,"GUM","Guam","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2013/gum_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
33904,316,"GUM","Guam","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2013/gum_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
33905,316,"GUM","Guam","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2013/gum_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
33906,316,"GUM","Guam","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2013/gum_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
33907,316,"GUM","Guam","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2013/gum_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
33908,316,"GUM","Guam","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2013/gum_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
33909,316,"GUM","Guam","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2014/gum_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
33910,316,"GUM","Guam","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2014/gum_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
33911,316,"GUM","Guam","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2014/gum_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
33912,316,"GUM","Guam","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2014/gum_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
33913,316,"GUM","Guam","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2014/gum_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
33914,316,"GUM","Guam","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2014/gum_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
33915,316,"GUM","Guam","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2014/gum_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
33916,316,"GUM","Guam","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2014/gum_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
33917,316,"GUM","Guam","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2015/gum_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
33918,316,"GUM","Guam","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2015/gum_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
33919,316,"GUM","Guam","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2015/gum_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
33920,316,"GUM","Guam","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2015/gum_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
33921,316,"GUM","Guam","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2015/gum_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
33922,316,"GUM","Guam","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2015/gum_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
33923,316,"GUM","Guam","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2015/gum_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
33924,316,"GUM","Guam","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Annual/2015/gum_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
33925,320,"GTM","Guatemala","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2000/gtm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
33926,320,"GTM","Guatemala","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2000/gtm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
33927,320,"GTM","Guatemala","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2000/gtm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
33928,320,"GTM","Guatemala","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2000/gtm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
33929,320,"GTM","Guatemala","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2000/gtm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
33930,320,"GTM","Guatemala","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2000/gtm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
33931,320,"GTM","Guatemala","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2000/gtm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
33932,320,"GTM","Guatemala","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2000/gtm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
33933,320,"GTM","Guatemala","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2001/gtm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
33934,320,"GTM","Guatemala","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2001/gtm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
33935,320,"GTM","Guatemala","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2001/gtm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
33936,320,"GTM","Guatemala","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2001/gtm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
33937,320,"GTM","Guatemala","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2001/gtm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
33938,320,"GTM","Guatemala","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2001/gtm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
33939,320,"GTM","Guatemala","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2001/gtm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
33940,320,"GTM","Guatemala","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2001/gtm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
33941,320,"GTM","Guatemala","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2002/gtm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
33942,320,"GTM","Guatemala","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2002/gtm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
33943,320,"GTM","Guatemala","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2002/gtm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
33944,320,"GTM","Guatemala","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2002/gtm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
33945,320,"GTM","Guatemala","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2002/gtm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
33946,320,"GTM","Guatemala","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2002/gtm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
33947,320,"GTM","Guatemala","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2002/gtm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
33948,320,"GTM","Guatemala","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2002/gtm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
33949,320,"GTM","Guatemala","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2003/gtm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
33950,320,"GTM","Guatemala","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2003/gtm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
33951,320,"GTM","Guatemala","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2003/gtm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
33952,320,"GTM","Guatemala","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2003/gtm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
33953,320,"GTM","Guatemala","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2003/gtm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
33954,320,"GTM","Guatemala","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2003/gtm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
33955,320,"GTM","Guatemala","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2003/gtm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
33956,320,"GTM","Guatemala","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2003/gtm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
33957,320,"GTM","Guatemala","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2004/gtm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
33958,320,"GTM","Guatemala","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2004/gtm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
33959,320,"GTM","Guatemala","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2004/gtm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
33960,320,"GTM","Guatemala","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2004/gtm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
33961,320,"GTM","Guatemala","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2004/gtm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
33962,320,"GTM","Guatemala","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2004/gtm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
33963,320,"GTM","Guatemala","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2004/gtm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
33964,320,"GTM","Guatemala","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2004/gtm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
33965,320,"GTM","Guatemala","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2005/gtm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
33966,320,"GTM","Guatemala","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2005/gtm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
33967,320,"GTM","Guatemala","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2005/gtm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
33968,320,"GTM","Guatemala","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2005/gtm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
33969,320,"GTM","Guatemala","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2005/gtm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
33970,320,"GTM","Guatemala","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2005/gtm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
33971,320,"GTM","Guatemala","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2005/gtm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
33972,320,"GTM","Guatemala","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2005/gtm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
33973,320,"GTM","Guatemala","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2006/gtm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
33974,320,"GTM","Guatemala","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2006/gtm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
33975,320,"GTM","Guatemala","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2006/gtm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
33976,320,"GTM","Guatemala","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2006/gtm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
33977,320,"GTM","Guatemala","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2006/gtm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
33978,320,"GTM","Guatemala","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2006/gtm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
33979,320,"GTM","Guatemala","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2006/gtm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
33980,320,"GTM","Guatemala","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2006/gtm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
33981,320,"GTM","Guatemala","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2007/gtm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
33982,320,"GTM","Guatemala","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2007/gtm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
33983,320,"GTM","Guatemala","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2007/gtm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
33984,320,"GTM","Guatemala","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2007/gtm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
33985,320,"GTM","Guatemala","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2007/gtm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
33986,320,"GTM","Guatemala","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2007/gtm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
33987,320,"GTM","Guatemala","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2007/gtm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
33988,320,"GTM","Guatemala","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2007/gtm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
33989,320,"GTM","Guatemala","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2008/gtm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
33990,320,"GTM","Guatemala","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2008/gtm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
33991,320,"GTM","Guatemala","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2008/gtm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
33992,320,"GTM","Guatemala","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2008/gtm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
33993,320,"GTM","Guatemala","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2008/gtm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
33994,320,"GTM","Guatemala","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2008/gtm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
33995,320,"GTM","Guatemala","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2008/gtm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
33996,320,"GTM","Guatemala","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2008/gtm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
33997,320,"GTM","Guatemala","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2009/gtm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
33998,320,"GTM","Guatemala","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2009/gtm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
33999,320,"GTM","Guatemala","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2009/gtm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
34000,320,"GTM","Guatemala","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2009/gtm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
34001,320,"GTM","Guatemala","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2009/gtm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
34002,320,"GTM","Guatemala","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2009/gtm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
34003,320,"GTM","Guatemala","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2009/gtm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
34004,320,"GTM","Guatemala","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2009/gtm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
34005,320,"GTM","Guatemala","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2010/gtm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
34006,320,"GTM","Guatemala","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2010/gtm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
34007,320,"GTM","Guatemala","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2010/gtm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
34008,320,"GTM","Guatemala","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2010/gtm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
34009,320,"GTM","Guatemala","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2010/gtm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
34010,320,"GTM","Guatemala","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2010/gtm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
34011,320,"GTM","Guatemala","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2010/gtm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
34012,320,"GTM","Guatemala","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2010/gtm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
34013,320,"GTM","Guatemala","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2011/gtm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
34014,320,"GTM","Guatemala","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2011/gtm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
34015,320,"GTM","Guatemala","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2011/gtm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
34016,320,"GTM","Guatemala","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2011/gtm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
34017,320,"GTM","Guatemala","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2011/gtm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
34018,320,"GTM","Guatemala","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2011/gtm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
34019,320,"GTM","Guatemala","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2011/gtm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
34020,320,"GTM","Guatemala","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2011/gtm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
34021,320,"GTM","Guatemala","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2012/gtm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
34022,320,"GTM","Guatemala","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2012/gtm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
34023,320,"GTM","Guatemala","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2012/gtm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
34024,320,"GTM","Guatemala","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2012/gtm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
34025,320,"GTM","Guatemala","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2012/gtm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
34026,320,"GTM","Guatemala","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2012/gtm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
34027,320,"GTM","Guatemala","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2012/gtm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
34028,320,"GTM","Guatemala","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2012/gtm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
34029,320,"GTM","Guatemala","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2013/gtm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
34030,320,"GTM","Guatemala","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2013/gtm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
34031,320,"GTM","Guatemala","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2013/gtm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
34032,320,"GTM","Guatemala","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2013/gtm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
34033,320,"GTM","Guatemala","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2013/gtm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
34034,320,"GTM","Guatemala","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2013/gtm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
34035,320,"GTM","Guatemala","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2013/gtm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
34036,320,"GTM","Guatemala","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2013/gtm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
34037,320,"GTM","Guatemala","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2014/gtm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
34038,320,"GTM","Guatemala","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2014/gtm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
34039,320,"GTM","Guatemala","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2014/gtm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
34040,320,"GTM","Guatemala","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2014/gtm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
34041,320,"GTM","Guatemala","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2014/gtm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
34042,320,"GTM","Guatemala","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2014/gtm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
34043,320,"GTM","Guatemala","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2014/gtm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
34044,320,"GTM","Guatemala","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2014/gtm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
34045,320,"GTM","Guatemala","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2015/gtm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
34046,320,"GTM","Guatemala","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2015/gtm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
34047,320,"GTM","Guatemala","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2015/gtm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
34048,320,"GTM","Guatemala","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2015/gtm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
34049,320,"GTM","Guatemala","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2015/gtm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
34050,320,"GTM","Guatemala","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2015/gtm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
34051,320,"GTM","Guatemala","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2015/gtm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
34052,320,"GTM","Guatemala","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Annual/2015/gtm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
34053,324,"GIN","Guinea","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2000/gin_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
34054,324,"GIN","Guinea","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2000/gin_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
34055,324,"GIN","Guinea","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2000/gin_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
34056,324,"GIN","Guinea","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2000/gin_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
34057,324,"GIN","Guinea","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2000/gin_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
34058,324,"GIN","Guinea","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2000/gin_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
34059,324,"GIN","Guinea","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2000/gin_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
34060,324,"GIN","Guinea","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2000/gin_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
34061,324,"GIN","Guinea","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2001/gin_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
34062,324,"GIN","Guinea","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2001/gin_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
34063,324,"GIN","Guinea","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2001/gin_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
34064,324,"GIN","Guinea","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2001/gin_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
34065,324,"GIN","Guinea","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2001/gin_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
34066,324,"GIN","Guinea","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2001/gin_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
34067,324,"GIN","Guinea","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2001/gin_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
34068,324,"GIN","Guinea","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2001/gin_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
34069,324,"GIN","Guinea","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2002/gin_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
34070,324,"GIN","Guinea","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2002/gin_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
34071,324,"GIN","Guinea","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2002/gin_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
34072,324,"GIN","Guinea","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2002/gin_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
34073,324,"GIN","Guinea","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2002/gin_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
34074,324,"GIN","Guinea","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2002/gin_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
34075,324,"GIN","Guinea","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2002/gin_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
34076,324,"GIN","Guinea","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2002/gin_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
34077,324,"GIN","Guinea","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2003/gin_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
34078,324,"GIN","Guinea","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2003/gin_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
34079,324,"GIN","Guinea","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2003/gin_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
34080,324,"GIN","Guinea","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2003/gin_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
34081,324,"GIN","Guinea","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2003/gin_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
34082,324,"GIN","Guinea","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2003/gin_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
34083,324,"GIN","Guinea","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2003/gin_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
34084,324,"GIN","Guinea","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2003/gin_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
34085,324,"GIN","Guinea","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2004/gin_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
34086,324,"GIN","Guinea","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2004/gin_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
34087,324,"GIN","Guinea","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2004/gin_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
34088,324,"GIN","Guinea","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2004/gin_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
34089,324,"GIN","Guinea","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2004/gin_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
34090,324,"GIN","Guinea","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2004/gin_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
34091,324,"GIN","Guinea","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2004/gin_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
34092,324,"GIN","Guinea","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2004/gin_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
34093,324,"GIN","Guinea","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2005/gin_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
34094,324,"GIN","Guinea","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2005/gin_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
34095,324,"GIN","Guinea","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2005/gin_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
34096,324,"GIN","Guinea","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2005/gin_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
34097,324,"GIN","Guinea","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2005/gin_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
34098,324,"GIN","Guinea","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2005/gin_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
34099,324,"GIN","Guinea","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2005/gin_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
34100,324,"GIN","Guinea","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2005/gin_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
34101,324,"GIN","Guinea","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2006/gin_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
34102,324,"GIN","Guinea","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2006/gin_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
34103,324,"GIN","Guinea","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2006/gin_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
34104,324,"GIN","Guinea","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2006/gin_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
34105,324,"GIN","Guinea","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2006/gin_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
34106,324,"GIN","Guinea","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2006/gin_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
34107,324,"GIN","Guinea","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2006/gin_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
34108,324,"GIN","Guinea","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2006/gin_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
34109,324,"GIN","Guinea","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2007/gin_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
34110,324,"GIN","Guinea","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2007/gin_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
34111,324,"GIN","Guinea","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2007/gin_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
34112,324,"GIN","Guinea","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2007/gin_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
34113,324,"GIN","Guinea","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2007/gin_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
34114,324,"GIN","Guinea","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2007/gin_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
34115,324,"GIN","Guinea","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2007/gin_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
34116,324,"GIN","Guinea","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2007/gin_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
34117,324,"GIN","Guinea","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2008/gin_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
34118,324,"GIN","Guinea","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2008/gin_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
34119,324,"GIN","Guinea","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2008/gin_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
34120,324,"GIN","Guinea","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2008/gin_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
34121,324,"GIN","Guinea","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2008/gin_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
34122,324,"GIN","Guinea","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2008/gin_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
34123,324,"GIN","Guinea","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2008/gin_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
34124,324,"GIN","Guinea","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2008/gin_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
34125,324,"GIN","Guinea","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2009/gin_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
34126,324,"GIN","Guinea","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2009/gin_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
34127,324,"GIN","Guinea","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2009/gin_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
34128,324,"GIN","Guinea","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2009/gin_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
34129,324,"GIN","Guinea","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2009/gin_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
34130,324,"GIN","Guinea","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2009/gin_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
34131,324,"GIN","Guinea","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2009/gin_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
34132,324,"GIN","Guinea","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2009/gin_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
34133,324,"GIN","Guinea","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2010/gin_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
34134,324,"GIN","Guinea","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2010/gin_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
34135,324,"GIN","Guinea","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2010/gin_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
34136,324,"GIN","Guinea","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2010/gin_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
34137,324,"GIN","Guinea","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2010/gin_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
34138,324,"GIN","Guinea","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2010/gin_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
34139,324,"GIN","Guinea","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2010/gin_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
34140,324,"GIN","Guinea","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2010/gin_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
34141,324,"GIN","Guinea","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2011/gin_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
34142,324,"GIN","Guinea","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2011/gin_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
34143,324,"GIN","Guinea","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2011/gin_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
34144,324,"GIN","Guinea","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2011/gin_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
34145,324,"GIN","Guinea","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2011/gin_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
34146,324,"GIN","Guinea","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2011/gin_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
34147,324,"GIN","Guinea","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2011/gin_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
34148,324,"GIN","Guinea","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2011/gin_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
34149,324,"GIN","Guinea","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2012/gin_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
34150,324,"GIN","Guinea","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2012/gin_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
34151,324,"GIN","Guinea","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2012/gin_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
34152,324,"GIN","Guinea","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2012/gin_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
34153,324,"GIN","Guinea","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2012/gin_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
34154,324,"GIN","Guinea","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2012/gin_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
34155,324,"GIN","Guinea","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2012/gin_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
34156,324,"GIN","Guinea","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2012/gin_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
34157,324,"GIN","Guinea","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2013/gin_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
34158,324,"GIN","Guinea","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2013/gin_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
34159,324,"GIN","Guinea","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2013/gin_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
34160,324,"GIN","Guinea","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2013/gin_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
34161,324,"GIN","Guinea","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2013/gin_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
34162,324,"GIN","Guinea","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2013/gin_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
34163,324,"GIN","Guinea","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2013/gin_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
34164,324,"GIN","Guinea","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2013/gin_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
34165,324,"GIN","Guinea","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2014/gin_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
34166,324,"GIN","Guinea","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2014/gin_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
34167,324,"GIN","Guinea","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2014/gin_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
34168,324,"GIN","Guinea","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2014/gin_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
34169,324,"GIN","Guinea","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2014/gin_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
34170,324,"GIN","Guinea","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2014/gin_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
34171,324,"GIN","Guinea","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2014/gin_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
34172,324,"GIN","Guinea","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2014/gin_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
34173,324,"GIN","Guinea","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2015/gin_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
34174,324,"GIN","Guinea","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2015/gin_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
34175,324,"GIN","Guinea","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2015/gin_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
34176,324,"GIN","Guinea","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2015/gin_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
34177,324,"GIN","Guinea","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2015/gin_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
34178,324,"GIN","Guinea","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2015/gin_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
34179,324,"GIN","Guinea","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2015/gin_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
34180,324,"GIN","Guinea","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Annual/2015/gin_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
34181,328,"GUY","Guyana","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2000/guy_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
34182,328,"GUY","Guyana","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2000/guy_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
34183,328,"GUY","Guyana","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2000/guy_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
34184,328,"GUY","Guyana","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2000/guy_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
34185,328,"GUY","Guyana","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2000/guy_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
34186,328,"GUY","Guyana","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2000/guy_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
34187,328,"GUY","Guyana","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2000/guy_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
34188,328,"GUY","Guyana","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2000/guy_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
34189,328,"GUY","Guyana","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2001/guy_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
34190,328,"GUY","Guyana","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2001/guy_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
34191,328,"GUY","Guyana","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2001/guy_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
34192,328,"GUY","Guyana","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2001/guy_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
34193,328,"GUY","Guyana","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2001/guy_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
34194,328,"GUY","Guyana","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2001/guy_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
34195,328,"GUY","Guyana","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2001/guy_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
34196,328,"GUY","Guyana","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2001/guy_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
34197,328,"GUY","Guyana","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2002/guy_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
34198,328,"GUY","Guyana","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2002/guy_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
34199,328,"GUY","Guyana","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2002/guy_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
34200,328,"GUY","Guyana","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2002/guy_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
34201,328,"GUY","Guyana","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2002/guy_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
34202,328,"GUY","Guyana","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2002/guy_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
34203,328,"GUY","Guyana","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2002/guy_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
34204,328,"GUY","Guyana","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2002/guy_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
34205,328,"GUY","Guyana","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2003/guy_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
34206,328,"GUY","Guyana","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2003/guy_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
34207,328,"GUY","Guyana","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2003/guy_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
34208,328,"GUY","Guyana","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2003/guy_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
34209,328,"GUY","Guyana","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2003/guy_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
34210,328,"GUY","Guyana","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2003/guy_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
34211,328,"GUY","Guyana","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2003/guy_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
34212,328,"GUY","Guyana","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2003/guy_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
34213,328,"GUY","Guyana","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2004/guy_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
34214,328,"GUY","Guyana","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2004/guy_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
34215,328,"GUY","Guyana","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2004/guy_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
34216,328,"GUY","Guyana","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2004/guy_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
34217,328,"GUY","Guyana","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2004/guy_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
34218,328,"GUY","Guyana","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2004/guy_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
34219,328,"GUY","Guyana","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2004/guy_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
34220,328,"GUY","Guyana","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2004/guy_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
34221,328,"GUY","Guyana","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2005/guy_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
34222,328,"GUY","Guyana","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2005/guy_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
34223,328,"GUY","Guyana","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2005/guy_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
34224,328,"GUY","Guyana","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2005/guy_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
34225,328,"GUY","Guyana","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2005/guy_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
34226,328,"GUY","Guyana","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2005/guy_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
34227,328,"GUY","Guyana","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2005/guy_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
34228,328,"GUY","Guyana","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2005/guy_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
34229,328,"GUY","Guyana","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2006/guy_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
34230,328,"GUY","Guyana","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2006/guy_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
34231,328,"GUY","Guyana","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2006/guy_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
34232,328,"GUY","Guyana","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2006/guy_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
34233,328,"GUY","Guyana","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2006/guy_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
34234,328,"GUY","Guyana","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2006/guy_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
34235,328,"GUY","Guyana","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2006/guy_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
34236,328,"GUY","Guyana","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2006/guy_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
34237,328,"GUY","Guyana","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2007/guy_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
34238,328,"GUY","Guyana","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2007/guy_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
34239,328,"GUY","Guyana","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2007/guy_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
34240,328,"GUY","Guyana","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2007/guy_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
34241,328,"GUY","Guyana","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2007/guy_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
34242,328,"GUY","Guyana","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2007/guy_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
34243,328,"GUY","Guyana","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2007/guy_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
34244,328,"GUY","Guyana","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2007/guy_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
34245,328,"GUY","Guyana","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2008/guy_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
34246,328,"GUY","Guyana","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2008/guy_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
34247,328,"GUY","Guyana","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2008/guy_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
34248,328,"GUY","Guyana","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2008/guy_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
34249,328,"GUY","Guyana","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2008/guy_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
34250,328,"GUY","Guyana","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2008/guy_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
34251,328,"GUY","Guyana","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2008/guy_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
34252,328,"GUY","Guyana","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2008/guy_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
34253,328,"GUY","Guyana","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2009/guy_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
34254,328,"GUY","Guyana","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2009/guy_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
34255,328,"GUY","Guyana","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2009/guy_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
34256,328,"GUY","Guyana","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2009/guy_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
34257,328,"GUY","Guyana","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2009/guy_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
34258,328,"GUY","Guyana","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2009/guy_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
34259,328,"GUY","Guyana","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2009/guy_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
34260,328,"GUY","Guyana","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2009/guy_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
34261,328,"GUY","Guyana","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2010/guy_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
34262,328,"GUY","Guyana","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2010/guy_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
34263,328,"GUY","Guyana","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2010/guy_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
34264,328,"GUY","Guyana","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2010/guy_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
34265,328,"GUY","Guyana","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2010/guy_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
34266,328,"GUY","Guyana","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2010/guy_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
34267,328,"GUY","Guyana","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2010/guy_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
34268,328,"GUY","Guyana","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2010/guy_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
34269,328,"GUY","Guyana","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2011/guy_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
34270,328,"GUY","Guyana","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2011/guy_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
34271,328,"GUY","Guyana","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2011/guy_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
34272,328,"GUY","Guyana","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2011/guy_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
34273,328,"GUY","Guyana","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2011/guy_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
34274,328,"GUY","Guyana","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2011/guy_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
34275,328,"GUY","Guyana","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2011/guy_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
34276,328,"GUY","Guyana","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2011/guy_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
34277,328,"GUY","Guyana","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2012/guy_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
34278,328,"GUY","Guyana","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2012/guy_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
34279,328,"GUY","Guyana","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2012/guy_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
34280,328,"GUY","Guyana","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2012/guy_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
34281,328,"GUY","Guyana","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2012/guy_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
34282,328,"GUY","Guyana","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2012/guy_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
34283,328,"GUY","Guyana","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2012/guy_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
34284,328,"GUY","Guyana","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2012/guy_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
34285,328,"GUY","Guyana","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2013/guy_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
34286,328,"GUY","Guyana","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2013/guy_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
34287,328,"GUY","Guyana","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2013/guy_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
34288,328,"GUY","Guyana","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2013/guy_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
34289,328,"GUY","Guyana","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2013/guy_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
34290,328,"GUY","Guyana","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2013/guy_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
34291,328,"GUY","Guyana","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2013/guy_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
34292,328,"GUY","Guyana","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2013/guy_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
34293,328,"GUY","Guyana","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2014/guy_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
34294,328,"GUY","Guyana","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2014/guy_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
34295,328,"GUY","Guyana","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2014/guy_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
34296,328,"GUY","Guyana","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2014/guy_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
34297,328,"GUY","Guyana","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2014/guy_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
34298,328,"GUY","Guyana","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2014/guy_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
34299,328,"GUY","Guyana","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2014/guy_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
34300,328,"GUY","Guyana","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2014/guy_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
34301,328,"GUY","Guyana","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2015/guy_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
34302,328,"GUY","Guyana","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2015/guy_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
34303,328,"GUY","Guyana","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2015/guy_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
34304,328,"GUY","Guyana","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2015/guy_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
34305,328,"GUY","Guyana","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2015/guy_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
34306,328,"GUY","Guyana","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2015/guy_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
34307,328,"GUY","Guyana","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2015/guy_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
34308,328,"GUY","Guyana","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Annual/2015/guy_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
34309,332,"HTI","Haiti","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2000/hti_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
34310,332,"HTI","Haiti","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2000/hti_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
34311,332,"HTI","Haiti","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2000/hti_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
34312,332,"HTI","Haiti","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2000/hti_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
34313,332,"HTI","Haiti","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2000/hti_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
34314,332,"HTI","Haiti","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2000/hti_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
34315,332,"HTI","Haiti","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2000/hti_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
34316,332,"HTI","Haiti","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2000/hti_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
34317,332,"HTI","Haiti","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2001/hti_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
34318,332,"HTI","Haiti","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2001/hti_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
34319,332,"HTI","Haiti","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2001/hti_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
34320,332,"HTI","Haiti","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2001/hti_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
34321,332,"HTI","Haiti","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2001/hti_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
34322,332,"HTI","Haiti","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2001/hti_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
34323,332,"HTI","Haiti","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2001/hti_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
34324,332,"HTI","Haiti","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2001/hti_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
34325,332,"HTI","Haiti","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2002/hti_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
34326,332,"HTI","Haiti","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2002/hti_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
34327,332,"HTI","Haiti","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2002/hti_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
34328,332,"HTI","Haiti","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2002/hti_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
34329,332,"HTI","Haiti","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2002/hti_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
34330,332,"HTI","Haiti","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2002/hti_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
34331,332,"HTI","Haiti","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2002/hti_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
34332,332,"HTI","Haiti","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2002/hti_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
34333,332,"HTI","Haiti","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2003/hti_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
34334,332,"HTI","Haiti","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2003/hti_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
34335,332,"HTI","Haiti","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2003/hti_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
34336,332,"HTI","Haiti","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2003/hti_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
34337,332,"HTI","Haiti","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2003/hti_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
34338,332,"HTI","Haiti","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2003/hti_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
34339,332,"HTI","Haiti","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2003/hti_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
34340,332,"HTI","Haiti","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2003/hti_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
34341,332,"HTI","Haiti","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2004/hti_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
34342,332,"HTI","Haiti","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2004/hti_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
34343,332,"HTI","Haiti","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2004/hti_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
34344,332,"HTI","Haiti","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2004/hti_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
34345,332,"HTI","Haiti","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2004/hti_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
34346,332,"HTI","Haiti","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2004/hti_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
34347,332,"HTI","Haiti","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2004/hti_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
34348,332,"HTI","Haiti","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2004/hti_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
34349,332,"HTI","Haiti","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2005/hti_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
34350,332,"HTI","Haiti","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2005/hti_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
34351,332,"HTI","Haiti","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2005/hti_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
34352,332,"HTI","Haiti","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2005/hti_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
34353,332,"HTI","Haiti","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2005/hti_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
34354,332,"HTI","Haiti","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2005/hti_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
34355,332,"HTI","Haiti","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2005/hti_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
34356,332,"HTI","Haiti","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2005/hti_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
34357,332,"HTI","Haiti","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2006/hti_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
34358,332,"HTI","Haiti","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2006/hti_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
34359,332,"HTI","Haiti","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2006/hti_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
34360,332,"HTI","Haiti","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2006/hti_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
34361,332,"HTI","Haiti","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2006/hti_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
34362,332,"HTI","Haiti","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2006/hti_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
34363,332,"HTI","Haiti","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2006/hti_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
34364,332,"HTI","Haiti","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2006/hti_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
34365,332,"HTI","Haiti","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2007/hti_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
34366,332,"HTI","Haiti","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2007/hti_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
34367,332,"HTI","Haiti","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2007/hti_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
34368,332,"HTI","Haiti","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2007/hti_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
34369,332,"HTI","Haiti","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2007/hti_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
34370,332,"HTI","Haiti","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2007/hti_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
34371,332,"HTI","Haiti","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2007/hti_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
34372,332,"HTI","Haiti","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2007/hti_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
34373,332,"HTI","Haiti","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2008/hti_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
34374,332,"HTI","Haiti","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2008/hti_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
34375,332,"HTI","Haiti","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2008/hti_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
34376,332,"HTI","Haiti","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2008/hti_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
34377,332,"HTI","Haiti","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2008/hti_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
34378,332,"HTI","Haiti","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2008/hti_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
34379,332,"HTI","Haiti","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2008/hti_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
34380,332,"HTI","Haiti","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2008/hti_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
34381,332,"HTI","Haiti","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2009/hti_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
34382,332,"HTI","Haiti","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2009/hti_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
34383,332,"HTI","Haiti","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2009/hti_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
34384,332,"HTI","Haiti","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2009/hti_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
34385,332,"HTI","Haiti","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2009/hti_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
34386,332,"HTI","Haiti","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2009/hti_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
34387,332,"HTI","Haiti","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2009/hti_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
34388,332,"HTI","Haiti","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2009/hti_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
34389,332,"HTI","Haiti","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2010/hti_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
34390,332,"HTI","Haiti","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2010/hti_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
34391,332,"HTI","Haiti","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2010/hti_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
34392,332,"HTI","Haiti","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2010/hti_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
34393,332,"HTI","Haiti","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2010/hti_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
34394,332,"HTI","Haiti","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2010/hti_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
34395,332,"HTI","Haiti","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2010/hti_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
34396,332,"HTI","Haiti","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2010/hti_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
34397,332,"HTI","Haiti","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2011/hti_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
34398,332,"HTI","Haiti","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2011/hti_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
34399,332,"HTI","Haiti","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2011/hti_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
34400,332,"HTI","Haiti","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2011/hti_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
34401,332,"HTI","Haiti","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2011/hti_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
34402,332,"HTI","Haiti","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2011/hti_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
34403,332,"HTI","Haiti","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2011/hti_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
34404,332,"HTI","Haiti","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2011/hti_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
34405,332,"HTI","Haiti","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2012/hti_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
34406,332,"HTI","Haiti","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2012/hti_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
34407,332,"HTI","Haiti","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2012/hti_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
34408,332,"HTI","Haiti","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2012/hti_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
34409,332,"HTI","Haiti","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2012/hti_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
34410,332,"HTI","Haiti","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2012/hti_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
34411,332,"HTI","Haiti","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2012/hti_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
34412,332,"HTI","Haiti","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2012/hti_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
34413,332,"HTI","Haiti","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2013/hti_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
34414,332,"HTI","Haiti","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2013/hti_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
34415,332,"HTI","Haiti","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2013/hti_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
34416,332,"HTI","Haiti","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2013/hti_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
34417,332,"HTI","Haiti","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2013/hti_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
34418,332,"HTI","Haiti","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2013/hti_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
34419,332,"HTI","Haiti","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2013/hti_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
34420,332,"HTI","Haiti","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2013/hti_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
34421,332,"HTI","Haiti","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2014/hti_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
34422,332,"HTI","Haiti","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2014/hti_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
34423,332,"HTI","Haiti","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2014/hti_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
34424,332,"HTI","Haiti","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2014/hti_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
34425,332,"HTI","Haiti","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2014/hti_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
34426,332,"HTI","Haiti","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2014/hti_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
34427,332,"HTI","Haiti","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2014/hti_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
34428,332,"HTI","Haiti","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2014/hti_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
34429,332,"HTI","Haiti","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2015/hti_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
34430,332,"HTI","Haiti","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2015/hti_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
34431,332,"HTI","Haiti","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2015/hti_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
34432,332,"HTI","Haiti","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2015/hti_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
34433,332,"HTI","Haiti","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2015/hti_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
34434,332,"HTI","Haiti","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2015/hti_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
34435,332,"HTI","Haiti","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2015/hti_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
34436,332,"HTI","Haiti","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Annual/2015/hti_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
34437,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2000/hmd_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
34438,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2000/hmd_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
34439,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2000/hmd_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
34440,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2000/hmd_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
34441,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2000/hmd_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
34442,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2000/hmd_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
34443,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2000/hmd_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
34444,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2000/hmd_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
34445,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2001/hmd_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
34446,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2001/hmd_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
34447,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2001/hmd_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
34448,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2001/hmd_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
34449,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2001/hmd_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
34450,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2001/hmd_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
34451,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2001/hmd_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
34452,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2001/hmd_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
34453,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2002/hmd_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
34454,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2002/hmd_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
34455,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2002/hmd_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
34456,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2002/hmd_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
34457,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2002/hmd_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
34458,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2002/hmd_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
34459,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2002/hmd_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
34460,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2002/hmd_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
34461,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2003/hmd_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
34462,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2003/hmd_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
34463,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2003/hmd_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
34464,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2003/hmd_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
34465,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2003/hmd_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
34466,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2003/hmd_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
34467,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2003/hmd_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
34468,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2003/hmd_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
34469,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2004/hmd_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
34470,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2004/hmd_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
34471,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2004/hmd_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
34472,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2004/hmd_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
34473,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2004/hmd_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
34474,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2004/hmd_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
34475,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2004/hmd_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
34476,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2004/hmd_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
34477,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2005/hmd_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
34478,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2005/hmd_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
34479,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2005/hmd_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
34480,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2005/hmd_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
34481,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2005/hmd_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
34482,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2005/hmd_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
34483,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2005/hmd_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
34484,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2005/hmd_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
34485,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2006/hmd_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
34486,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2006/hmd_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
34487,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2006/hmd_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
34488,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2006/hmd_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
34489,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2006/hmd_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
34490,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2006/hmd_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
34491,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2006/hmd_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
34492,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2006/hmd_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
34493,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2007/hmd_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
34494,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2007/hmd_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
34495,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2007/hmd_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
34496,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2007/hmd_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
34497,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2007/hmd_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
34498,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2007/hmd_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
34499,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2007/hmd_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
34500,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2007/hmd_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
34501,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2008/hmd_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
34502,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2008/hmd_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
34503,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2008/hmd_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
34504,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2008/hmd_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
34505,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2008/hmd_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
34506,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2008/hmd_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
34507,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2008/hmd_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
34508,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2008/hmd_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
34509,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2009/hmd_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
34510,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2009/hmd_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
34511,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2009/hmd_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
34512,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2009/hmd_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
34513,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2009/hmd_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
34514,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2009/hmd_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
34515,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2009/hmd_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
34516,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2009/hmd_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
34517,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2010/hmd_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
34518,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2010/hmd_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
34519,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2010/hmd_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
34520,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2010/hmd_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
34521,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2010/hmd_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
34522,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2010/hmd_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
34523,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2010/hmd_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
34524,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2010/hmd_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
34525,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2011/hmd_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
34526,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2011/hmd_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
34527,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2011/hmd_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
34528,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2011/hmd_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
34529,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2011/hmd_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
34530,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2011/hmd_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
34531,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2011/hmd_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
34532,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2011/hmd_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
34533,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2012/hmd_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
34534,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2012/hmd_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
34535,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2012/hmd_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
34536,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2012/hmd_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
34537,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2012/hmd_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
34538,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2012/hmd_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
34539,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2012/hmd_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
34540,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2012/hmd_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
34541,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2013/hmd_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
34542,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2013/hmd_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
34543,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2013/hmd_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
34544,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2013/hmd_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
34545,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2013/hmd_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
34546,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2013/hmd_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
34547,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2013/hmd_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
34548,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2013/hmd_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
34549,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2014/hmd_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
34550,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2014/hmd_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
34551,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2014/hmd_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
34552,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2014/hmd_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
34553,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2014/hmd_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
34554,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2014/hmd_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
34555,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2014/hmd_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
34556,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2014/hmd_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
34557,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2015/hmd_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
34558,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2015/hmd_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
34559,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2015/hmd_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
34560,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2015/hmd_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
34561,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2015/hmd_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
34562,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2015/hmd_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
34563,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2015/hmd_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
34564,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Annual/2015/hmd_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
34565,336,"VAT","Vatican City","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2000/vat_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
34566,336,"VAT","Vatican City","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2000/vat_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
34567,336,"VAT","Vatican City","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2000/vat_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
34568,336,"VAT","Vatican City","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2000/vat_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
34569,336,"VAT","Vatican City","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2000/vat_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
34570,336,"VAT","Vatican City","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2000/vat_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
34571,336,"VAT","Vatican City","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2000/vat_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
34572,336,"VAT","Vatican City","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2000/vat_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
34573,336,"VAT","Vatican City","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2001/vat_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
34574,336,"VAT","Vatican City","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2001/vat_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
34575,336,"VAT","Vatican City","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2001/vat_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
34576,336,"VAT","Vatican City","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2001/vat_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
34577,336,"VAT","Vatican City","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2001/vat_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
34578,336,"VAT","Vatican City","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2001/vat_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
34579,336,"VAT","Vatican City","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2001/vat_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
34580,336,"VAT","Vatican City","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2001/vat_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
34581,336,"VAT","Vatican City","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2002/vat_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
34582,336,"VAT","Vatican City","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2002/vat_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
34583,336,"VAT","Vatican City","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2002/vat_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
34584,336,"VAT","Vatican City","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2002/vat_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
34585,336,"VAT","Vatican City","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2002/vat_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
34586,336,"VAT","Vatican City","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2002/vat_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
34587,336,"VAT","Vatican City","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2002/vat_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
34588,336,"VAT","Vatican City","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2002/vat_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
34589,336,"VAT","Vatican City","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2003/vat_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
34590,336,"VAT","Vatican City","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2003/vat_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
34591,336,"VAT","Vatican City","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2003/vat_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
34592,336,"VAT","Vatican City","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2003/vat_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
34593,336,"VAT","Vatican City","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2003/vat_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
34594,336,"VAT","Vatican City","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2003/vat_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
34595,336,"VAT","Vatican City","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2003/vat_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
34596,336,"VAT","Vatican City","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2003/vat_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
34597,336,"VAT","Vatican City","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2004/vat_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
34598,336,"VAT","Vatican City","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2004/vat_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
34599,336,"VAT","Vatican City","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2004/vat_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
34600,336,"VAT","Vatican City","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2004/vat_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
34601,336,"VAT","Vatican City","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2004/vat_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
34602,336,"VAT","Vatican City","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2004/vat_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
34603,336,"VAT","Vatican City","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2004/vat_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
34604,336,"VAT","Vatican City","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2004/vat_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
34605,336,"VAT","Vatican City","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2005/vat_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
34606,336,"VAT","Vatican City","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2005/vat_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
34607,336,"VAT","Vatican City","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2005/vat_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
34608,336,"VAT","Vatican City","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2005/vat_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
34609,336,"VAT","Vatican City","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2005/vat_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
34610,336,"VAT","Vatican City","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2005/vat_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
34611,336,"VAT","Vatican City","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2005/vat_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
34612,336,"VAT","Vatican City","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2005/vat_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
34613,336,"VAT","Vatican City","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2006/vat_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
34614,336,"VAT","Vatican City","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2006/vat_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
34615,336,"VAT","Vatican City","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2006/vat_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
34616,336,"VAT","Vatican City","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2006/vat_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
34617,336,"VAT","Vatican City","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2006/vat_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
34618,336,"VAT","Vatican City","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2006/vat_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
34619,336,"VAT","Vatican City","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2006/vat_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
34620,336,"VAT","Vatican City","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2006/vat_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
34621,336,"VAT","Vatican City","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2007/vat_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
34622,336,"VAT","Vatican City","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2007/vat_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
34623,336,"VAT","Vatican City","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2007/vat_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
34624,336,"VAT","Vatican City","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2007/vat_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
34625,336,"VAT","Vatican City","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2007/vat_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
34626,336,"VAT","Vatican City","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2007/vat_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
34627,336,"VAT","Vatican City","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2007/vat_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
34628,336,"VAT","Vatican City","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2007/vat_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
34629,336,"VAT","Vatican City","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2008/vat_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
34630,336,"VAT","Vatican City","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2008/vat_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
34631,336,"VAT","Vatican City","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2008/vat_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
34632,336,"VAT","Vatican City","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2008/vat_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
34633,336,"VAT","Vatican City","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2008/vat_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
34634,336,"VAT","Vatican City","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2008/vat_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
34635,336,"VAT","Vatican City","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2008/vat_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
34636,336,"VAT","Vatican City","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2008/vat_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
34637,336,"VAT","Vatican City","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2009/vat_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
34638,336,"VAT","Vatican City","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2009/vat_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
34639,336,"VAT","Vatican City","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2009/vat_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
34640,336,"VAT","Vatican City","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2009/vat_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
34641,336,"VAT","Vatican City","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2009/vat_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
34642,336,"VAT","Vatican City","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2009/vat_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
34643,336,"VAT","Vatican City","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2009/vat_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
34644,336,"VAT","Vatican City","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2009/vat_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
34645,336,"VAT","Vatican City","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2010/vat_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
34646,336,"VAT","Vatican City","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2010/vat_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
34647,336,"VAT","Vatican City","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2010/vat_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
34648,336,"VAT","Vatican City","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2010/vat_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
34649,336,"VAT","Vatican City","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2010/vat_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
34650,336,"VAT","Vatican City","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2010/vat_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
34651,336,"VAT","Vatican City","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2010/vat_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
34652,336,"VAT","Vatican City","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2010/vat_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
34653,336,"VAT","Vatican City","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2011/vat_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
34654,336,"VAT","Vatican City","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2011/vat_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
34655,336,"VAT","Vatican City","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2011/vat_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
34656,336,"VAT","Vatican City","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2011/vat_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
34657,336,"VAT","Vatican City","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2011/vat_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
34658,336,"VAT","Vatican City","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2011/vat_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
34659,336,"VAT","Vatican City","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2011/vat_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
34660,336,"VAT","Vatican City","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2011/vat_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
34661,336,"VAT","Vatican City","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2012/vat_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
34662,336,"VAT","Vatican City","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2012/vat_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
34663,336,"VAT","Vatican City","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2012/vat_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
34664,336,"VAT","Vatican City","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2012/vat_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
34665,336,"VAT","Vatican City","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2012/vat_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
34666,336,"VAT","Vatican City","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2012/vat_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
34667,336,"VAT","Vatican City","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2012/vat_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
34668,336,"VAT","Vatican City","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2012/vat_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
34669,336,"VAT","Vatican City","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2013/vat_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
34670,336,"VAT","Vatican City","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2013/vat_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
34671,336,"VAT","Vatican City","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2013/vat_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
34672,336,"VAT","Vatican City","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2013/vat_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
34673,336,"VAT","Vatican City","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2013/vat_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
34674,336,"VAT","Vatican City","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2013/vat_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
34675,336,"VAT","Vatican City","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2013/vat_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
34676,336,"VAT","Vatican City","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2013/vat_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
34677,336,"VAT","Vatican City","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2014/vat_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
34678,336,"VAT","Vatican City","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2014/vat_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
34679,336,"VAT","Vatican City","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2014/vat_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
34680,336,"VAT","Vatican City","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2014/vat_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
34681,336,"VAT","Vatican City","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2014/vat_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
34682,336,"VAT","Vatican City","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2014/vat_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
34683,336,"VAT","Vatican City","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2014/vat_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
34684,336,"VAT","Vatican City","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2014/vat_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
34685,336,"VAT","Vatican City","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2015/vat_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
34686,336,"VAT","Vatican City","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2015/vat_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
34687,336,"VAT","Vatican City","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2015/vat_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
34688,336,"VAT","Vatican City","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2015/vat_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
34689,336,"VAT","Vatican City","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2015/vat_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
34690,336,"VAT","Vatican City","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2015/vat_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
34691,336,"VAT","Vatican City","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2015/vat_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
34692,336,"VAT","Vatican City","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Annual/2015/vat_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
34693,340,"HND","Honduras","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2000/hnd_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
34694,340,"HND","Honduras","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2000/hnd_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
34695,340,"HND","Honduras","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2000/hnd_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
34696,340,"HND","Honduras","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2000/hnd_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
34697,340,"HND","Honduras","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2000/hnd_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
34698,340,"HND","Honduras","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2000/hnd_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
34699,340,"HND","Honduras","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2000/hnd_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
34700,340,"HND","Honduras","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2000/hnd_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
34701,340,"HND","Honduras","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2001/hnd_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
34702,340,"HND","Honduras","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2001/hnd_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
34703,340,"HND","Honduras","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2001/hnd_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
34704,340,"HND","Honduras","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2001/hnd_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
34705,340,"HND","Honduras","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2001/hnd_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
34706,340,"HND","Honduras","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2001/hnd_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
34707,340,"HND","Honduras","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2001/hnd_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
34708,340,"HND","Honduras","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2001/hnd_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
34709,340,"HND","Honduras","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2002/hnd_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
34710,340,"HND","Honduras","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2002/hnd_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
34711,340,"HND","Honduras","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2002/hnd_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
34712,340,"HND","Honduras","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2002/hnd_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
34713,340,"HND","Honduras","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2002/hnd_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
34714,340,"HND","Honduras","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2002/hnd_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
34715,340,"HND","Honduras","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2002/hnd_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
34716,340,"HND","Honduras","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2002/hnd_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
34717,340,"HND","Honduras","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2003/hnd_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
34718,340,"HND","Honduras","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2003/hnd_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
34719,340,"HND","Honduras","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2003/hnd_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
34720,340,"HND","Honduras","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2003/hnd_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
34721,340,"HND","Honduras","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2003/hnd_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
34722,340,"HND","Honduras","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2003/hnd_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
34723,340,"HND","Honduras","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2003/hnd_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
34724,340,"HND","Honduras","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2003/hnd_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
34725,340,"HND","Honduras","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2004/hnd_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
34726,340,"HND","Honduras","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2004/hnd_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
34727,340,"HND","Honduras","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2004/hnd_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
34728,340,"HND","Honduras","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2004/hnd_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
34729,340,"HND","Honduras","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2004/hnd_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
34730,340,"HND","Honduras","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2004/hnd_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
34731,340,"HND","Honduras","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2004/hnd_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
34732,340,"HND","Honduras","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2004/hnd_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
34733,340,"HND","Honduras","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2005/hnd_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
34734,340,"HND","Honduras","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2005/hnd_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
34735,340,"HND","Honduras","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2005/hnd_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
34736,340,"HND","Honduras","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2005/hnd_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
34737,340,"HND","Honduras","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2005/hnd_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
34738,340,"HND","Honduras","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2005/hnd_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
34739,340,"HND","Honduras","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2005/hnd_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
34740,340,"HND","Honduras","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2005/hnd_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
34741,340,"HND","Honduras","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2006/hnd_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
34742,340,"HND","Honduras","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2006/hnd_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
34743,340,"HND","Honduras","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2006/hnd_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
34744,340,"HND","Honduras","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2006/hnd_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
34745,340,"HND","Honduras","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2006/hnd_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
34746,340,"HND","Honduras","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2006/hnd_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
34747,340,"HND","Honduras","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2006/hnd_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
34748,340,"HND","Honduras","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2006/hnd_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
34749,340,"HND","Honduras","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2007/hnd_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
34750,340,"HND","Honduras","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2007/hnd_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
34751,340,"HND","Honduras","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2007/hnd_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
34752,340,"HND","Honduras","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2007/hnd_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
34753,340,"HND","Honduras","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2007/hnd_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
34754,340,"HND","Honduras","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2007/hnd_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
34755,340,"HND","Honduras","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2007/hnd_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
34756,340,"HND","Honduras","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2007/hnd_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
34757,340,"HND","Honduras","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2008/hnd_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
34758,340,"HND","Honduras","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2008/hnd_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
34759,340,"HND","Honduras","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2008/hnd_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
34760,340,"HND","Honduras","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2008/hnd_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
34761,340,"HND","Honduras","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2008/hnd_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
34762,340,"HND","Honduras","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2008/hnd_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
34763,340,"HND","Honduras","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2008/hnd_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
34764,340,"HND","Honduras","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2008/hnd_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
34765,340,"HND","Honduras","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2009/hnd_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
34766,340,"HND","Honduras","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2009/hnd_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
34767,340,"HND","Honduras","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2009/hnd_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
34768,340,"HND","Honduras","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2009/hnd_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
34769,340,"HND","Honduras","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2009/hnd_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
34770,340,"HND","Honduras","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2009/hnd_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
34771,340,"HND","Honduras","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2009/hnd_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
34772,340,"HND","Honduras","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2009/hnd_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
34773,340,"HND","Honduras","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2010/hnd_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
34774,340,"HND","Honduras","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2010/hnd_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
34775,340,"HND","Honduras","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2010/hnd_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
34776,340,"HND","Honduras","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2010/hnd_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
34777,340,"HND","Honduras","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2010/hnd_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
34778,340,"HND","Honduras","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2010/hnd_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
34779,340,"HND","Honduras","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2010/hnd_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
34780,340,"HND","Honduras","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2010/hnd_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
34781,340,"HND","Honduras","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2011/hnd_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
34782,340,"HND","Honduras","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2011/hnd_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
34783,340,"HND","Honduras","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2011/hnd_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
34784,340,"HND","Honduras","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2011/hnd_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
34785,340,"HND","Honduras","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2011/hnd_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
34786,340,"HND","Honduras","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2011/hnd_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
34787,340,"HND","Honduras","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2011/hnd_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
34788,340,"HND","Honduras","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2011/hnd_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
34789,340,"HND","Honduras","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2012/hnd_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
34790,340,"HND","Honduras","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2012/hnd_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
34791,340,"HND","Honduras","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2012/hnd_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
34792,340,"HND","Honduras","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2012/hnd_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
34793,340,"HND","Honduras","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2012/hnd_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
34794,340,"HND","Honduras","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2012/hnd_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
34795,340,"HND","Honduras","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2012/hnd_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
34796,340,"HND","Honduras","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2012/hnd_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
34797,340,"HND","Honduras","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2013/hnd_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
34798,340,"HND","Honduras","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2013/hnd_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
34799,340,"HND","Honduras","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2013/hnd_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
34800,340,"HND","Honduras","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2013/hnd_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
34801,340,"HND","Honduras","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2013/hnd_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
34802,340,"HND","Honduras","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2013/hnd_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
34803,340,"HND","Honduras","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2013/hnd_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
34804,340,"HND","Honduras","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2013/hnd_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
34805,340,"HND","Honduras","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2014/hnd_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
34806,340,"HND","Honduras","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2014/hnd_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
34807,340,"HND","Honduras","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2014/hnd_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
34808,340,"HND","Honduras","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2014/hnd_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
34809,340,"HND","Honduras","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2014/hnd_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
34810,340,"HND","Honduras","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2014/hnd_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
34811,340,"HND","Honduras","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2014/hnd_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
34812,340,"HND","Honduras","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2014/hnd_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
34813,340,"HND","Honduras","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2015/hnd_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
34814,340,"HND","Honduras","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2015/hnd_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
34815,340,"HND","Honduras","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2015/hnd_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
34816,340,"HND","Honduras","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2015/hnd_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
34817,340,"HND","Honduras","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2015/hnd_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
34818,340,"HND","Honduras","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2015/hnd_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
34819,340,"HND","Honduras","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2015/hnd_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
34820,340,"HND","Honduras","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Annual/2015/hnd_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
34821,344,"HKG","Hong Kong","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2000/hkg_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
34822,344,"HKG","Hong Kong","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2000/hkg_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
34823,344,"HKG","Hong Kong","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2000/hkg_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
34824,344,"HKG","Hong Kong","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2000/hkg_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
34825,344,"HKG","Hong Kong","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2000/hkg_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
34826,344,"HKG","Hong Kong","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2000/hkg_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
34827,344,"HKG","Hong Kong","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2000/hkg_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
34828,344,"HKG","Hong Kong","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2000/hkg_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
34829,344,"HKG","Hong Kong","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2001/hkg_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
34830,344,"HKG","Hong Kong","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2001/hkg_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
34831,344,"HKG","Hong Kong","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2001/hkg_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
34832,344,"HKG","Hong Kong","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2001/hkg_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
34833,344,"HKG","Hong Kong","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2001/hkg_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
34834,344,"HKG","Hong Kong","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2001/hkg_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
34835,344,"HKG","Hong Kong","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2001/hkg_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
34836,344,"HKG","Hong Kong","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2001/hkg_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
34837,344,"HKG","Hong Kong","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2002/hkg_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
34838,344,"HKG","Hong Kong","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2002/hkg_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
34839,344,"HKG","Hong Kong","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2002/hkg_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
34840,344,"HKG","Hong Kong","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2002/hkg_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
34841,344,"HKG","Hong Kong","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2002/hkg_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
34842,344,"HKG","Hong Kong","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2002/hkg_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
34843,344,"HKG","Hong Kong","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2002/hkg_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
34844,344,"HKG","Hong Kong","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2002/hkg_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
34845,344,"HKG","Hong Kong","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2003/hkg_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
34846,344,"HKG","Hong Kong","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2003/hkg_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
34847,344,"HKG","Hong Kong","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2003/hkg_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
34848,344,"HKG","Hong Kong","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2003/hkg_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
34849,344,"HKG","Hong Kong","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2003/hkg_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
34850,344,"HKG","Hong Kong","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2003/hkg_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
34851,344,"HKG","Hong Kong","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2003/hkg_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
34852,344,"HKG","Hong Kong","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2003/hkg_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
34853,344,"HKG","Hong Kong","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2004/hkg_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
34854,344,"HKG","Hong Kong","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2004/hkg_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
34855,344,"HKG","Hong Kong","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2004/hkg_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
34856,344,"HKG","Hong Kong","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2004/hkg_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
34857,344,"HKG","Hong Kong","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2004/hkg_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
34858,344,"HKG","Hong Kong","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2004/hkg_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
34859,344,"HKG","Hong Kong","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2004/hkg_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
34860,344,"HKG","Hong Kong","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2004/hkg_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
34861,344,"HKG","Hong Kong","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2005/hkg_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
34862,344,"HKG","Hong Kong","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2005/hkg_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
34863,344,"HKG","Hong Kong","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2005/hkg_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
34864,344,"HKG","Hong Kong","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2005/hkg_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
34865,344,"HKG","Hong Kong","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2005/hkg_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
34866,344,"HKG","Hong Kong","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2005/hkg_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
34867,344,"HKG","Hong Kong","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2005/hkg_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
34868,344,"HKG","Hong Kong","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2005/hkg_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
34869,344,"HKG","Hong Kong","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2006/hkg_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
34870,344,"HKG","Hong Kong","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2006/hkg_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
34871,344,"HKG","Hong Kong","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2006/hkg_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
34872,344,"HKG","Hong Kong","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2006/hkg_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
34873,344,"HKG","Hong Kong","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2006/hkg_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
34874,344,"HKG","Hong Kong","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2006/hkg_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
34875,344,"HKG","Hong Kong","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2006/hkg_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
34876,344,"HKG","Hong Kong","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2006/hkg_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
34877,344,"HKG","Hong Kong","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2007/hkg_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
34878,344,"HKG","Hong Kong","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2007/hkg_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
34879,344,"HKG","Hong Kong","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2007/hkg_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
34880,344,"HKG","Hong Kong","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2007/hkg_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
34881,344,"HKG","Hong Kong","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2007/hkg_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
34882,344,"HKG","Hong Kong","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2007/hkg_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
34883,344,"HKG","Hong Kong","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2007/hkg_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
34884,344,"HKG","Hong Kong","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2007/hkg_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
34885,344,"HKG","Hong Kong","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2008/hkg_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
34886,344,"HKG","Hong Kong","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2008/hkg_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
34887,344,"HKG","Hong Kong","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2008/hkg_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
34888,344,"HKG","Hong Kong","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2008/hkg_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
34889,344,"HKG","Hong Kong","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2008/hkg_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
34890,344,"HKG","Hong Kong","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2008/hkg_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
34891,344,"HKG","Hong Kong","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2008/hkg_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
34892,344,"HKG","Hong Kong","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2008/hkg_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
34893,344,"HKG","Hong Kong","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2009/hkg_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
34894,344,"HKG","Hong Kong","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2009/hkg_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
34895,344,"HKG","Hong Kong","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2009/hkg_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
34896,344,"HKG","Hong Kong","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2009/hkg_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
34897,344,"HKG","Hong Kong","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2009/hkg_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
34898,344,"HKG","Hong Kong","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2009/hkg_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
34899,344,"HKG","Hong Kong","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2009/hkg_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
34900,344,"HKG","Hong Kong","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2009/hkg_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
34901,344,"HKG","Hong Kong","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2010/hkg_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
34902,344,"HKG","Hong Kong","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2010/hkg_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
34903,344,"HKG","Hong Kong","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2010/hkg_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
34904,344,"HKG","Hong Kong","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2010/hkg_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
34905,344,"HKG","Hong Kong","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2010/hkg_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
34906,344,"HKG","Hong Kong","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2010/hkg_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
34907,344,"HKG","Hong Kong","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2010/hkg_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
34908,344,"HKG","Hong Kong","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2010/hkg_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
34909,344,"HKG","Hong Kong","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2011/hkg_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
34910,344,"HKG","Hong Kong","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2011/hkg_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
34911,344,"HKG","Hong Kong","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2011/hkg_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
34912,344,"HKG","Hong Kong","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2011/hkg_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
34913,344,"HKG","Hong Kong","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2011/hkg_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
34914,344,"HKG","Hong Kong","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2011/hkg_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
34915,344,"HKG","Hong Kong","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2011/hkg_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
34916,344,"HKG","Hong Kong","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2011/hkg_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
34917,344,"HKG","Hong Kong","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2012/hkg_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
34918,344,"HKG","Hong Kong","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2012/hkg_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
34919,344,"HKG","Hong Kong","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2012/hkg_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
34920,344,"HKG","Hong Kong","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2012/hkg_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
34921,344,"HKG","Hong Kong","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2012/hkg_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
34922,344,"HKG","Hong Kong","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2012/hkg_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
34923,344,"HKG","Hong Kong","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2012/hkg_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
34924,344,"HKG","Hong Kong","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2012/hkg_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
34925,344,"HKG","Hong Kong","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2013/hkg_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
34926,344,"HKG","Hong Kong","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2013/hkg_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
34927,344,"HKG","Hong Kong","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2013/hkg_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
34928,344,"HKG","Hong Kong","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2013/hkg_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
34929,344,"HKG","Hong Kong","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2013/hkg_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
34930,344,"HKG","Hong Kong","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2013/hkg_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
34931,344,"HKG","Hong Kong","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2013/hkg_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
34932,344,"HKG","Hong Kong","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2013/hkg_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
34933,344,"HKG","Hong Kong","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2014/hkg_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
34934,344,"HKG","Hong Kong","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2014/hkg_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
34935,344,"HKG","Hong Kong","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2014/hkg_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
34936,344,"HKG","Hong Kong","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2014/hkg_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
34937,344,"HKG","Hong Kong","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2014/hkg_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
34938,344,"HKG","Hong Kong","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2014/hkg_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
34939,344,"HKG","Hong Kong","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2014/hkg_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
34940,344,"HKG","Hong Kong","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2014/hkg_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
34941,344,"HKG","Hong Kong","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2015/hkg_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
34942,344,"HKG","Hong Kong","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2015/hkg_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
34943,344,"HKG","Hong Kong","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2015/hkg_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
34944,344,"HKG","Hong Kong","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2015/hkg_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
34945,344,"HKG","Hong Kong","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2015/hkg_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
34946,344,"HKG","Hong Kong","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2015/hkg_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
34947,344,"HKG","Hong Kong","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2015/hkg_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
34948,344,"HKG","Hong Kong","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Annual/2015/hkg_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
34949,348,"HUN","Hungary","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2000/hun_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
34950,348,"HUN","Hungary","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2000/hun_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
34951,348,"HUN","Hungary","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2000/hun_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
34952,348,"HUN","Hungary","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2000/hun_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
34953,348,"HUN","Hungary","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2000/hun_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
34954,348,"HUN","Hungary","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2000/hun_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
34955,348,"HUN","Hungary","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2000/hun_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
34956,348,"HUN","Hungary","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2000/hun_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
34957,348,"HUN","Hungary","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2001/hun_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
34958,348,"HUN","Hungary","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2001/hun_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
34959,348,"HUN","Hungary","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2001/hun_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
34960,348,"HUN","Hungary","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2001/hun_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
34961,348,"HUN","Hungary","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2001/hun_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
34962,348,"HUN","Hungary","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2001/hun_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
34963,348,"HUN","Hungary","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2001/hun_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
34964,348,"HUN","Hungary","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2001/hun_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
34965,348,"HUN","Hungary","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2002/hun_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
34966,348,"HUN","Hungary","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2002/hun_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
34967,348,"HUN","Hungary","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2002/hun_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
34968,348,"HUN","Hungary","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2002/hun_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
34969,348,"HUN","Hungary","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2002/hun_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
34970,348,"HUN","Hungary","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2002/hun_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
34971,348,"HUN","Hungary","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2002/hun_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
34972,348,"HUN","Hungary","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2002/hun_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
34973,348,"HUN","Hungary","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2003/hun_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
34974,348,"HUN","Hungary","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2003/hun_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
34975,348,"HUN","Hungary","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2003/hun_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
34976,348,"HUN","Hungary","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2003/hun_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
34977,348,"HUN","Hungary","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2003/hun_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
34978,348,"HUN","Hungary","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2003/hun_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
34979,348,"HUN","Hungary","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2003/hun_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
34980,348,"HUN","Hungary","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2003/hun_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
34981,348,"HUN","Hungary","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2004/hun_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
34982,348,"HUN","Hungary","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2004/hun_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
34983,348,"HUN","Hungary","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2004/hun_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
34984,348,"HUN","Hungary","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2004/hun_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
34985,348,"HUN","Hungary","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2004/hun_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
34986,348,"HUN","Hungary","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2004/hun_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
34987,348,"HUN","Hungary","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2004/hun_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
34988,348,"HUN","Hungary","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2004/hun_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
34989,348,"HUN","Hungary","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2005/hun_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
34990,348,"HUN","Hungary","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2005/hun_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
34991,348,"HUN","Hungary","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2005/hun_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
34992,348,"HUN","Hungary","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2005/hun_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
34993,348,"HUN","Hungary","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2005/hun_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
34994,348,"HUN","Hungary","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2005/hun_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
34995,348,"HUN","Hungary","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2005/hun_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
34996,348,"HUN","Hungary","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2005/hun_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
34997,348,"HUN","Hungary","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2006/hun_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
34998,348,"HUN","Hungary","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2006/hun_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
34999,348,"HUN","Hungary","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2006/hun_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
35000,348,"HUN","Hungary","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2006/hun_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
35001,348,"HUN","Hungary","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2006/hun_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
35002,348,"HUN","Hungary","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2006/hun_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
35003,348,"HUN","Hungary","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2006/hun_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
35004,348,"HUN","Hungary","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2006/hun_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
35005,348,"HUN","Hungary","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2007/hun_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
35006,348,"HUN","Hungary","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2007/hun_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
35007,348,"HUN","Hungary","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2007/hun_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
35008,348,"HUN","Hungary","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2007/hun_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
35009,348,"HUN","Hungary","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2007/hun_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
35010,348,"HUN","Hungary","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2007/hun_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
35011,348,"HUN","Hungary","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2007/hun_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
35012,348,"HUN","Hungary","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2007/hun_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
35013,348,"HUN","Hungary","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2008/hun_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
35014,348,"HUN","Hungary","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2008/hun_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
35015,348,"HUN","Hungary","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2008/hun_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
35016,348,"HUN","Hungary","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2008/hun_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
35017,348,"HUN","Hungary","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2008/hun_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
35018,348,"HUN","Hungary","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2008/hun_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
35019,348,"HUN","Hungary","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2008/hun_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
35020,348,"HUN","Hungary","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2008/hun_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
35021,348,"HUN","Hungary","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2009/hun_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
35022,348,"HUN","Hungary","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2009/hun_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
35023,348,"HUN","Hungary","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2009/hun_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
35024,348,"HUN","Hungary","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2009/hun_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
35025,348,"HUN","Hungary","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2009/hun_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
35026,348,"HUN","Hungary","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2009/hun_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
35027,348,"HUN","Hungary","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2009/hun_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
35028,348,"HUN","Hungary","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2009/hun_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
35029,348,"HUN","Hungary","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2010/hun_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
35030,348,"HUN","Hungary","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2010/hun_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
35031,348,"HUN","Hungary","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2010/hun_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
35032,348,"HUN","Hungary","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2010/hun_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
35033,348,"HUN","Hungary","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2010/hun_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
35034,348,"HUN","Hungary","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2010/hun_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
35035,348,"HUN","Hungary","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2010/hun_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
35036,348,"HUN","Hungary","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2010/hun_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
35037,348,"HUN","Hungary","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2011/hun_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
35038,348,"HUN","Hungary","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2011/hun_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
35039,348,"HUN","Hungary","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2011/hun_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
35040,348,"HUN","Hungary","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2011/hun_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
35041,348,"HUN","Hungary","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2011/hun_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
35042,348,"HUN","Hungary","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2011/hun_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
35043,348,"HUN","Hungary","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2011/hun_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
35044,348,"HUN","Hungary","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2011/hun_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
35045,348,"HUN","Hungary","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2012/hun_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
35046,348,"HUN","Hungary","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2012/hun_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
35047,348,"HUN","Hungary","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2012/hun_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
35048,348,"HUN","Hungary","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2012/hun_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
35049,348,"HUN","Hungary","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2012/hun_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
35050,348,"HUN","Hungary","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2012/hun_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
35051,348,"HUN","Hungary","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2012/hun_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
35052,348,"HUN","Hungary","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2012/hun_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
35053,348,"HUN","Hungary","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2013/hun_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
35054,348,"HUN","Hungary","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2013/hun_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
35055,348,"HUN","Hungary","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2013/hun_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
35056,348,"HUN","Hungary","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2013/hun_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
35057,348,"HUN","Hungary","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2013/hun_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
35058,348,"HUN","Hungary","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2013/hun_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
35059,348,"HUN","Hungary","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2013/hun_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
35060,348,"HUN","Hungary","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2013/hun_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
35061,348,"HUN","Hungary","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2014/hun_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
35062,348,"HUN","Hungary","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2014/hun_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
35063,348,"HUN","Hungary","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2014/hun_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
35064,348,"HUN","Hungary","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2014/hun_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
35065,348,"HUN","Hungary","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2014/hun_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
35066,348,"HUN","Hungary","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2014/hun_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
35067,348,"HUN","Hungary","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2014/hun_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
35068,348,"HUN","Hungary","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2014/hun_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
35069,348,"HUN","Hungary","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2015/hun_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
35070,348,"HUN","Hungary","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2015/hun_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
35071,348,"HUN","Hungary","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2015/hun_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
35072,348,"HUN","Hungary","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2015/hun_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
35073,348,"HUN","Hungary","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2015/hun_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
35074,348,"HUN","Hungary","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2015/hun_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
35075,348,"HUN","Hungary","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2015/hun_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
35076,348,"HUN","Hungary","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Annual/2015/hun_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
35077,352,"ISL","Iceland","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2000/isl_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
35078,352,"ISL","Iceland","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2000/isl_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
35079,352,"ISL","Iceland","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2000/isl_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
35080,352,"ISL","Iceland","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2000/isl_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
35081,352,"ISL","Iceland","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2000/isl_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
35082,352,"ISL","Iceland","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2000/isl_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
35083,352,"ISL","Iceland","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2000/isl_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
35084,352,"ISL","Iceland","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2000/isl_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
35085,352,"ISL","Iceland","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2001/isl_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
35086,352,"ISL","Iceland","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2001/isl_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
35087,352,"ISL","Iceland","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2001/isl_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
35088,352,"ISL","Iceland","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2001/isl_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
35089,352,"ISL","Iceland","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2001/isl_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
35090,352,"ISL","Iceland","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2001/isl_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
35091,352,"ISL","Iceland","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2001/isl_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
35092,352,"ISL","Iceland","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2001/isl_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
35093,352,"ISL","Iceland","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2002/isl_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
35094,352,"ISL","Iceland","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2002/isl_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
35095,352,"ISL","Iceland","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2002/isl_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
35096,352,"ISL","Iceland","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2002/isl_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
35097,352,"ISL","Iceland","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2002/isl_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
35098,352,"ISL","Iceland","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2002/isl_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
35099,352,"ISL","Iceland","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2002/isl_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
35100,352,"ISL","Iceland","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2002/isl_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
35101,352,"ISL","Iceland","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2003/isl_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
35102,352,"ISL","Iceland","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2003/isl_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
35103,352,"ISL","Iceland","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2003/isl_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
35104,352,"ISL","Iceland","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2003/isl_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
35105,352,"ISL","Iceland","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2003/isl_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
35106,352,"ISL","Iceland","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2003/isl_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
35107,352,"ISL","Iceland","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2003/isl_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
35108,352,"ISL","Iceland","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2003/isl_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
35109,352,"ISL","Iceland","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2004/isl_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
35110,352,"ISL","Iceland","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2004/isl_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
35111,352,"ISL","Iceland","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2004/isl_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
35112,352,"ISL","Iceland","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2004/isl_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
35113,352,"ISL","Iceland","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2004/isl_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
35114,352,"ISL","Iceland","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2004/isl_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
35115,352,"ISL","Iceland","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2004/isl_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
35116,352,"ISL","Iceland","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2004/isl_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
35117,352,"ISL","Iceland","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2005/isl_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
35118,352,"ISL","Iceland","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2005/isl_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
35119,352,"ISL","Iceland","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2005/isl_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
35120,352,"ISL","Iceland","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2005/isl_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
35121,352,"ISL","Iceland","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2005/isl_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
35122,352,"ISL","Iceland","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2005/isl_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
35123,352,"ISL","Iceland","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2005/isl_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
35124,352,"ISL","Iceland","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2005/isl_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
35125,352,"ISL","Iceland","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2006/isl_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
35126,352,"ISL","Iceland","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2006/isl_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
35127,352,"ISL","Iceland","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2006/isl_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
35128,352,"ISL","Iceland","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2006/isl_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
35129,352,"ISL","Iceland","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2006/isl_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
35130,352,"ISL","Iceland","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2006/isl_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
35131,352,"ISL","Iceland","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2006/isl_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
35132,352,"ISL","Iceland","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2006/isl_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
35133,352,"ISL","Iceland","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2007/isl_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
35134,352,"ISL","Iceland","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2007/isl_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
35135,352,"ISL","Iceland","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2007/isl_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
35136,352,"ISL","Iceland","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2007/isl_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
35137,352,"ISL","Iceland","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2007/isl_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
35138,352,"ISL","Iceland","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2007/isl_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
35139,352,"ISL","Iceland","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2007/isl_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
35140,352,"ISL","Iceland","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2007/isl_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
35141,352,"ISL","Iceland","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2008/isl_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
35142,352,"ISL","Iceland","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2008/isl_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
35143,352,"ISL","Iceland","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2008/isl_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
35144,352,"ISL","Iceland","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2008/isl_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
35145,352,"ISL","Iceland","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2008/isl_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
35146,352,"ISL","Iceland","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2008/isl_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
35147,352,"ISL","Iceland","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2008/isl_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
35148,352,"ISL","Iceland","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2008/isl_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
35149,352,"ISL","Iceland","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2009/isl_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
35150,352,"ISL","Iceland","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2009/isl_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
35151,352,"ISL","Iceland","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2009/isl_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
35152,352,"ISL","Iceland","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2009/isl_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
35153,352,"ISL","Iceland","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2009/isl_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
35154,352,"ISL","Iceland","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2009/isl_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
35155,352,"ISL","Iceland","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2009/isl_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
35156,352,"ISL","Iceland","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2009/isl_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
35157,352,"ISL","Iceland","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2010/isl_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
35158,352,"ISL","Iceland","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2010/isl_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
35159,352,"ISL","Iceland","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2010/isl_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
35160,352,"ISL","Iceland","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2010/isl_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
35161,352,"ISL","Iceland","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2010/isl_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
35162,352,"ISL","Iceland","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2010/isl_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
35163,352,"ISL","Iceland","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2010/isl_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
35164,352,"ISL","Iceland","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2010/isl_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
35165,352,"ISL","Iceland","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2011/isl_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
35166,352,"ISL","Iceland","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2011/isl_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
35167,352,"ISL","Iceland","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2011/isl_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
35168,352,"ISL","Iceland","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2011/isl_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
35169,352,"ISL","Iceland","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2011/isl_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
35170,352,"ISL","Iceland","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2011/isl_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
35171,352,"ISL","Iceland","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2011/isl_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
35172,352,"ISL","Iceland","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2011/isl_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
35173,352,"ISL","Iceland","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2012/isl_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
35174,352,"ISL","Iceland","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2012/isl_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
35175,352,"ISL","Iceland","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2012/isl_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
35176,352,"ISL","Iceland","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2012/isl_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
35177,352,"ISL","Iceland","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2012/isl_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
35178,352,"ISL","Iceland","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2012/isl_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
35179,352,"ISL","Iceland","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2012/isl_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
35180,352,"ISL","Iceland","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2012/isl_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
35181,352,"ISL","Iceland","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2013/isl_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
35182,352,"ISL","Iceland","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2013/isl_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
35183,352,"ISL","Iceland","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2013/isl_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
35184,352,"ISL","Iceland","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2013/isl_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
35185,352,"ISL","Iceland","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2013/isl_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
35186,352,"ISL","Iceland","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2013/isl_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
35187,352,"ISL","Iceland","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2013/isl_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
35188,352,"ISL","Iceland","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2013/isl_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
35189,352,"ISL","Iceland","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2014/isl_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
35190,352,"ISL","Iceland","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2014/isl_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
35191,352,"ISL","Iceland","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2014/isl_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
35192,352,"ISL","Iceland","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2014/isl_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
35193,352,"ISL","Iceland","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2014/isl_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
35194,352,"ISL","Iceland","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2014/isl_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
35195,352,"ISL","Iceland","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2014/isl_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
35196,352,"ISL","Iceland","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2014/isl_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
35197,352,"ISL","Iceland","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2015/isl_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
35198,352,"ISL","Iceland","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2015/isl_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
35199,352,"ISL","Iceland","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2015/isl_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
35200,352,"ISL","Iceland","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2015/isl_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
35201,352,"ISL","Iceland","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2015/isl_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
35202,352,"ISL","Iceland","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2015/isl_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
35203,352,"ISL","Iceland","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2015/isl_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
35204,352,"ISL","Iceland","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Annual/2015/isl_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
35205,356,"IND","India","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2000/ind_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
35206,356,"IND","India","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2000/ind_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
35207,356,"IND","India","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2000/ind_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
35208,356,"IND","India","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2000/ind_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
35209,356,"IND","India","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2000/ind_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
35210,356,"IND","India","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2000/ind_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
35211,356,"IND","India","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2000/ind_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
35212,356,"IND","India","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2000/ind_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
35213,356,"IND","India","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2001/ind_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
35214,356,"IND","India","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2001/ind_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
35215,356,"IND","India","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2001/ind_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
35216,356,"IND","India","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2001/ind_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
35217,356,"IND","India","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2001/ind_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
35218,356,"IND","India","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2001/ind_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
35219,356,"IND","India","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2001/ind_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
35220,356,"IND","India","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2001/ind_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
35221,356,"IND","India","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2002/ind_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
35222,356,"IND","India","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2002/ind_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
35223,356,"IND","India","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2002/ind_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
35224,356,"IND","India","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2002/ind_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
35225,356,"IND","India","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2002/ind_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
35226,356,"IND","India","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2002/ind_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
35227,356,"IND","India","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2002/ind_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
35228,356,"IND","India","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2002/ind_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
35229,356,"IND","India","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2003/ind_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
35230,356,"IND","India","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2003/ind_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
35231,356,"IND","India","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2003/ind_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
35232,356,"IND","India","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2003/ind_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
35233,356,"IND","India","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2003/ind_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
35234,356,"IND","India","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2003/ind_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
35235,356,"IND","India","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2003/ind_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
35236,356,"IND","India","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2003/ind_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
35237,356,"IND","India","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2004/ind_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
35238,356,"IND","India","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2004/ind_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
35239,356,"IND","India","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2004/ind_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
35240,356,"IND","India","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2004/ind_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
35241,356,"IND","India","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2004/ind_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
35242,356,"IND","India","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2004/ind_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
35243,356,"IND","India","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2004/ind_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
35244,356,"IND","India","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2004/ind_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
35245,356,"IND","India","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2005/ind_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
35246,356,"IND","India","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2005/ind_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
35247,356,"IND","India","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2005/ind_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
35248,356,"IND","India","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2005/ind_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
35249,356,"IND","India","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2005/ind_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
35250,356,"IND","India","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2005/ind_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
35251,356,"IND","India","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2005/ind_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
35252,356,"IND","India","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2005/ind_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
35253,356,"IND","India","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2006/ind_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
35254,356,"IND","India","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2006/ind_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
35255,356,"IND","India","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2006/ind_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
35256,356,"IND","India","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2006/ind_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
35257,356,"IND","India","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2006/ind_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
35258,356,"IND","India","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2006/ind_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
35259,356,"IND","India","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2006/ind_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
35260,356,"IND","India","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2006/ind_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
35261,356,"IND","India","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2007/ind_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
35262,356,"IND","India","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2007/ind_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
35263,356,"IND","India","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2007/ind_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
35264,356,"IND","India","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2007/ind_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
35265,356,"IND","India","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2007/ind_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
35266,356,"IND","India","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2007/ind_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
35267,356,"IND","India","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2007/ind_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
35268,356,"IND","India","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2007/ind_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
35269,356,"IND","India","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2008/ind_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
35270,356,"IND","India","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2008/ind_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
35271,356,"IND","India","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2008/ind_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
35272,356,"IND","India","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2008/ind_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
35273,356,"IND","India","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2008/ind_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
35274,356,"IND","India","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2008/ind_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
35275,356,"IND","India","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2008/ind_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
35276,356,"IND","India","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2008/ind_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
35277,356,"IND","India","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2009/ind_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
35278,356,"IND","India","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2009/ind_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
35279,356,"IND","India","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2009/ind_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
35280,356,"IND","India","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2009/ind_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
35281,356,"IND","India","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2009/ind_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
35282,356,"IND","India","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2009/ind_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
35283,356,"IND","India","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2009/ind_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
35284,356,"IND","India","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2009/ind_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
35285,356,"IND","India","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2010/ind_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
35286,356,"IND","India","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2010/ind_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
35287,356,"IND","India","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2010/ind_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
35288,356,"IND","India","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2010/ind_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
35289,356,"IND","India","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2010/ind_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
35290,356,"IND","India","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2010/ind_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
35291,356,"IND","India","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2010/ind_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
35292,356,"IND","India","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2010/ind_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
35293,356,"IND","India","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2011/ind_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
35294,356,"IND","India","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2011/ind_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
35295,356,"IND","India","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2011/ind_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
35296,356,"IND","India","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2011/ind_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
35297,356,"IND","India","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2011/ind_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
35298,356,"IND","India","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2011/ind_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
35299,356,"IND","India","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2011/ind_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
35300,356,"IND","India","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2011/ind_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
35301,356,"IND","India","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2012/ind_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
35302,356,"IND","India","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2012/ind_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
35303,356,"IND","India","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2012/ind_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
35304,356,"IND","India","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2012/ind_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
35305,356,"IND","India","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2012/ind_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
35306,356,"IND","India","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2012/ind_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
35307,356,"IND","India","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2012/ind_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
35308,356,"IND","India","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2012/ind_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
35309,356,"IND","India","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2013/ind_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
35310,356,"IND","India","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2013/ind_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
35311,356,"IND","India","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2013/ind_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
35312,356,"IND","India","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2013/ind_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
35313,356,"IND","India","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2013/ind_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
35314,356,"IND","India","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2013/ind_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
35315,356,"IND","India","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2013/ind_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
35316,356,"IND","India","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2013/ind_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
35317,356,"IND","India","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2014/ind_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
35318,356,"IND","India","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2014/ind_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
35319,356,"IND","India","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2014/ind_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
35320,356,"IND","India","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2014/ind_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
35321,356,"IND","India","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2014/ind_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
35322,356,"IND","India","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2014/ind_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
35323,356,"IND","India","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2014/ind_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
35324,356,"IND","India","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2014/ind_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
35325,356,"IND","India","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2015/ind_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
35326,356,"IND","India","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2015/ind_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
35327,356,"IND","India","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2015/ind_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
35328,356,"IND","India","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2015/ind_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
35329,356,"IND","India","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2015/ind_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
35330,356,"IND","India","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2015/ind_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
35331,356,"IND","India","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2015/ind_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
35332,356,"IND","India","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Annual/2015/ind_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
35333,364,"IRN","Iran","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2000/irn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
35334,364,"IRN","Iran","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2000/irn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
35335,364,"IRN","Iran","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2000/irn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
35336,364,"IRN","Iran","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2000/irn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
35337,364,"IRN","Iran","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2000/irn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
35338,364,"IRN","Iran","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2000/irn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
35339,364,"IRN","Iran","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2000/irn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
35340,364,"IRN","Iran","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2000/irn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
35341,364,"IRN","Iran","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2001/irn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
35342,364,"IRN","Iran","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2001/irn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
35343,364,"IRN","Iran","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2001/irn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
35344,364,"IRN","Iran","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2001/irn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
35345,364,"IRN","Iran","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2001/irn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
35346,364,"IRN","Iran","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2001/irn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
35347,364,"IRN","Iran","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2001/irn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
35348,364,"IRN","Iran","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2001/irn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
35349,364,"IRN","Iran","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2002/irn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
35350,364,"IRN","Iran","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2002/irn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
35351,364,"IRN","Iran","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2002/irn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
35352,364,"IRN","Iran","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2002/irn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
35353,364,"IRN","Iran","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2002/irn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
35354,364,"IRN","Iran","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2002/irn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
35355,364,"IRN","Iran","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2002/irn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
35356,364,"IRN","Iran","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2002/irn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
35357,364,"IRN","Iran","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2003/irn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
35358,364,"IRN","Iran","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2003/irn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
35359,364,"IRN","Iran","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2003/irn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
35360,364,"IRN","Iran","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2003/irn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
35361,364,"IRN","Iran","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2003/irn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
35362,364,"IRN","Iran","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2003/irn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
35363,364,"IRN","Iran","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2003/irn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
35364,364,"IRN","Iran","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2003/irn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
35365,364,"IRN","Iran","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2004/irn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
35366,364,"IRN","Iran","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2004/irn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
35367,364,"IRN","Iran","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2004/irn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
35368,364,"IRN","Iran","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2004/irn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
35369,364,"IRN","Iran","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2004/irn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
35370,364,"IRN","Iran","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2004/irn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
35371,364,"IRN","Iran","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2004/irn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
35372,364,"IRN","Iran","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2004/irn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
35373,364,"IRN","Iran","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2005/irn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
35374,364,"IRN","Iran","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2005/irn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
35375,364,"IRN","Iran","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2005/irn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
35376,364,"IRN","Iran","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2005/irn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
35377,364,"IRN","Iran","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2005/irn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
35378,364,"IRN","Iran","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2005/irn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
35379,364,"IRN","Iran","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2005/irn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
35380,364,"IRN","Iran","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2005/irn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
35381,364,"IRN","Iran","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2006/irn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
35382,364,"IRN","Iran","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2006/irn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
35383,364,"IRN","Iran","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2006/irn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
35384,364,"IRN","Iran","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2006/irn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
35385,364,"IRN","Iran","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2006/irn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
35386,364,"IRN","Iran","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2006/irn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
35387,364,"IRN","Iran","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2006/irn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
35388,364,"IRN","Iran","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2006/irn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
35389,364,"IRN","Iran","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2007/irn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
35390,364,"IRN","Iran","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2007/irn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
35391,364,"IRN","Iran","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2007/irn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
35392,364,"IRN","Iran","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2007/irn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
35393,364,"IRN","Iran","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2007/irn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
35394,364,"IRN","Iran","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2007/irn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
35395,364,"IRN","Iran","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2007/irn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
35396,364,"IRN","Iran","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2007/irn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
35397,364,"IRN","Iran","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2008/irn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
35398,364,"IRN","Iran","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2008/irn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
35399,364,"IRN","Iran","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2008/irn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
35400,364,"IRN","Iran","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2008/irn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
35401,364,"IRN","Iran","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2008/irn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
35402,364,"IRN","Iran","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2008/irn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
35403,364,"IRN","Iran","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2008/irn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
35404,364,"IRN","Iran","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2008/irn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
35405,364,"IRN","Iran","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2009/irn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
35406,364,"IRN","Iran","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2009/irn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
35407,364,"IRN","Iran","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2009/irn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
35408,364,"IRN","Iran","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2009/irn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
35409,364,"IRN","Iran","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2009/irn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
35410,364,"IRN","Iran","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2009/irn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
35411,364,"IRN","Iran","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2009/irn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
35412,364,"IRN","Iran","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2009/irn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
35413,364,"IRN","Iran","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2010/irn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
35414,364,"IRN","Iran","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2010/irn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
35415,364,"IRN","Iran","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2010/irn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
35416,364,"IRN","Iran","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2010/irn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
35417,364,"IRN","Iran","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2010/irn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
35418,364,"IRN","Iran","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2010/irn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
35419,364,"IRN","Iran","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2010/irn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
35420,364,"IRN","Iran","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2010/irn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
35421,364,"IRN","Iran","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2011/irn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
35422,364,"IRN","Iran","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2011/irn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
35423,364,"IRN","Iran","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2011/irn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
35424,364,"IRN","Iran","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2011/irn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
35425,364,"IRN","Iran","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2011/irn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
35426,364,"IRN","Iran","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2011/irn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
35427,364,"IRN","Iran","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2011/irn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
35428,364,"IRN","Iran","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2011/irn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
35429,364,"IRN","Iran","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2012/irn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
35430,364,"IRN","Iran","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2012/irn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
35431,364,"IRN","Iran","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2012/irn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
35432,364,"IRN","Iran","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2012/irn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
35433,364,"IRN","Iran","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2012/irn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
35434,364,"IRN","Iran","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2012/irn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
35435,364,"IRN","Iran","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2012/irn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
35436,364,"IRN","Iran","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2012/irn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
35437,364,"IRN","Iran","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2013/irn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
35438,364,"IRN","Iran","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2013/irn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
35439,364,"IRN","Iran","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2013/irn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
35440,364,"IRN","Iran","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2013/irn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
35441,364,"IRN","Iran","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2013/irn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
35442,364,"IRN","Iran","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2013/irn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
35443,364,"IRN","Iran","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2013/irn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
35444,364,"IRN","Iran","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2013/irn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
35445,364,"IRN","Iran","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2014/irn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
35446,364,"IRN","Iran","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2014/irn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
35447,364,"IRN","Iran","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2014/irn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
35448,364,"IRN","Iran","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2014/irn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
35449,364,"IRN","Iran","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2014/irn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
35450,364,"IRN","Iran","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2014/irn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
35451,364,"IRN","Iran","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2014/irn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
35452,364,"IRN","Iran","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2014/irn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
35453,364,"IRN","Iran","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2015/irn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
35454,364,"IRN","Iran","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2015/irn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
35455,364,"IRN","Iran","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2015/irn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
35456,364,"IRN","Iran","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2015/irn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
35457,364,"IRN","Iran","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2015/irn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
35458,364,"IRN","Iran","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2015/irn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
35459,364,"IRN","Iran","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2015/irn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
35460,364,"IRN","Iran","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Annual/2015/irn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
35461,368,"IRQ","Iraq","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2000/irq_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
35462,368,"IRQ","Iraq","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2000/irq_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
35463,368,"IRQ","Iraq","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2000/irq_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
35464,368,"IRQ","Iraq","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2000/irq_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
35465,368,"IRQ","Iraq","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2000/irq_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
35466,368,"IRQ","Iraq","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2000/irq_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
35467,368,"IRQ","Iraq","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2000/irq_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
35468,368,"IRQ","Iraq","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2000/irq_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
35469,368,"IRQ","Iraq","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2001/irq_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
35470,368,"IRQ","Iraq","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2001/irq_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
35471,368,"IRQ","Iraq","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2001/irq_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
35472,368,"IRQ","Iraq","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2001/irq_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
35473,368,"IRQ","Iraq","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2001/irq_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
35474,368,"IRQ","Iraq","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2001/irq_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
35475,368,"IRQ","Iraq","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2001/irq_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
35476,368,"IRQ","Iraq","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2001/irq_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
35477,368,"IRQ","Iraq","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2002/irq_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
35478,368,"IRQ","Iraq","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2002/irq_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
35479,368,"IRQ","Iraq","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2002/irq_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
35480,368,"IRQ","Iraq","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2002/irq_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
35481,368,"IRQ","Iraq","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2002/irq_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
35482,368,"IRQ","Iraq","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2002/irq_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
35483,368,"IRQ","Iraq","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2002/irq_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
35484,368,"IRQ","Iraq","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2002/irq_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
35485,368,"IRQ","Iraq","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2003/irq_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
35486,368,"IRQ","Iraq","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2003/irq_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
35487,368,"IRQ","Iraq","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2003/irq_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
35488,368,"IRQ","Iraq","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2003/irq_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
35489,368,"IRQ","Iraq","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2003/irq_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
35490,368,"IRQ","Iraq","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2003/irq_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
35491,368,"IRQ","Iraq","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2003/irq_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
35492,368,"IRQ","Iraq","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2003/irq_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
35493,368,"IRQ","Iraq","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2004/irq_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
35494,368,"IRQ","Iraq","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2004/irq_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
35495,368,"IRQ","Iraq","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2004/irq_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
35496,368,"IRQ","Iraq","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2004/irq_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
35497,368,"IRQ","Iraq","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2004/irq_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
35498,368,"IRQ","Iraq","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2004/irq_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
35499,368,"IRQ","Iraq","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2004/irq_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
35500,368,"IRQ","Iraq","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2004/irq_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
35501,368,"IRQ","Iraq","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2005/irq_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
35502,368,"IRQ","Iraq","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2005/irq_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
35503,368,"IRQ","Iraq","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2005/irq_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
35504,368,"IRQ","Iraq","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2005/irq_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
35505,368,"IRQ","Iraq","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2005/irq_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
35506,368,"IRQ","Iraq","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2005/irq_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
35507,368,"IRQ","Iraq","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2005/irq_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
35508,368,"IRQ","Iraq","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2005/irq_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
35509,368,"IRQ","Iraq","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2006/irq_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
35510,368,"IRQ","Iraq","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2006/irq_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
35511,368,"IRQ","Iraq","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2006/irq_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
35512,368,"IRQ","Iraq","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2006/irq_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
35513,368,"IRQ","Iraq","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2006/irq_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
35514,368,"IRQ","Iraq","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2006/irq_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
35515,368,"IRQ","Iraq","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2006/irq_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
35516,368,"IRQ","Iraq","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2006/irq_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
35517,368,"IRQ","Iraq","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2007/irq_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
35518,368,"IRQ","Iraq","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2007/irq_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
35519,368,"IRQ","Iraq","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2007/irq_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
35520,368,"IRQ","Iraq","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2007/irq_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
35521,368,"IRQ","Iraq","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2007/irq_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
35522,368,"IRQ","Iraq","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2007/irq_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
35523,368,"IRQ","Iraq","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2007/irq_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
35524,368,"IRQ","Iraq","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2007/irq_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
35525,368,"IRQ","Iraq","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2008/irq_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
35526,368,"IRQ","Iraq","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2008/irq_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
35527,368,"IRQ","Iraq","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2008/irq_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
35528,368,"IRQ","Iraq","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2008/irq_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
35529,368,"IRQ","Iraq","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2008/irq_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
35530,368,"IRQ","Iraq","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2008/irq_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
35531,368,"IRQ","Iraq","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2008/irq_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
35532,368,"IRQ","Iraq","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2008/irq_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
35533,368,"IRQ","Iraq","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2009/irq_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
35534,368,"IRQ","Iraq","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2009/irq_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
35535,368,"IRQ","Iraq","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2009/irq_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
35536,368,"IRQ","Iraq","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2009/irq_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
35537,368,"IRQ","Iraq","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2009/irq_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
35538,368,"IRQ","Iraq","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2009/irq_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
35539,368,"IRQ","Iraq","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2009/irq_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
35540,368,"IRQ","Iraq","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2009/irq_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
35541,368,"IRQ","Iraq","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2010/irq_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
35542,368,"IRQ","Iraq","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2010/irq_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
35543,368,"IRQ","Iraq","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2010/irq_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
35544,368,"IRQ","Iraq","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2010/irq_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
35545,368,"IRQ","Iraq","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2010/irq_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
35546,368,"IRQ","Iraq","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2010/irq_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
35547,368,"IRQ","Iraq","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2010/irq_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
35548,368,"IRQ","Iraq","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2010/irq_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
35549,368,"IRQ","Iraq","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2011/irq_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
35550,368,"IRQ","Iraq","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2011/irq_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
35551,368,"IRQ","Iraq","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2011/irq_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
35552,368,"IRQ","Iraq","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2011/irq_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
35553,368,"IRQ","Iraq","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2011/irq_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
35554,368,"IRQ","Iraq","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2011/irq_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
35555,368,"IRQ","Iraq","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2011/irq_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
35556,368,"IRQ","Iraq","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2011/irq_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
35557,368,"IRQ","Iraq","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2012/irq_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
35558,368,"IRQ","Iraq","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2012/irq_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
35559,368,"IRQ","Iraq","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2012/irq_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
35560,368,"IRQ","Iraq","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2012/irq_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
35561,368,"IRQ","Iraq","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2012/irq_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
35562,368,"IRQ","Iraq","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2012/irq_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
35563,368,"IRQ","Iraq","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2012/irq_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
35564,368,"IRQ","Iraq","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2012/irq_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
35565,368,"IRQ","Iraq","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2013/irq_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
35566,368,"IRQ","Iraq","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2013/irq_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
35567,368,"IRQ","Iraq","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2013/irq_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
35568,368,"IRQ","Iraq","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2013/irq_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
35569,368,"IRQ","Iraq","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2013/irq_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
35570,368,"IRQ","Iraq","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2013/irq_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
35571,368,"IRQ","Iraq","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2013/irq_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
35572,368,"IRQ","Iraq","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2013/irq_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
35573,368,"IRQ","Iraq","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2014/irq_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
35574,368,"IRQ","Iraq","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2014/irq_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
35575,368,"IRQ","Iraq","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2014/irq_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
35576,368,"IRQ","Iraq","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2014/irq_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
35577,368,"IRQ","Iraq","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2014/irq_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
35578,368,"IRQ","Iraq","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2014/irq_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
35579,368,"IRQ","Iraq","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2014/irq_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
35580,368,"IRQ","Iraq","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2014/irq_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
35581,368,"IRQ","Iraq","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2015/irq_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
35582,368,"IRQ","Iraq","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2015/irq_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
35583,368,"IRQ","Iraq","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2015/irq_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
35584,368,"IRQ","Iraq","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2015/irq_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
35585,368,"IRQ","Iraq","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2015/irq_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
35586,368,"IRQ","Iraq","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2015/irq_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
35587,368,"IRQ","Iraq","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2015/irq_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
35588,368,"IRQ","Iraq","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Annual/2015/irq_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
35589,372,"IRL","Ireland","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2000/irl_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
35590,372,"IRL","Ireland","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2000/irl_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
35591,372,"IRL","Ireland","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2000/irl_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
35592,372,"IRL","Ireland","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2000/irl_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
35593,372,"IRL","Ireland","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2000/irl_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
35594,372,"IRL","Ireland","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2000/irl_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
35595,372,"IRL","Ireland","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2000/irl_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
35596,372,"IRL","Ireland","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2000/irl_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
35597,372,"IRL","Ireland","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2001/irl_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
35598,372,"IRL","Ireland","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2001/irl_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
35599,372,"IRL","Ireland","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2001/irl_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
35600,372,"IRL","Ireland","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2001/irl_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
35601,372,"IRL","Ireland","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2001/irl_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
35602,372,"IRL","Ireland","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2001/irl_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
35603,372,"IRL","Ireland","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2001/irl_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
35604,372,"IRL","Ireland","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2001/irl_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
35605,372,"IRL","Ireland","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2002/irl_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
35606,372,"IRL","Ireland","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2002/irl_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
35607,372,"IRL","Ireland","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2002/irl_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
35608,372,"IRL","Ireland","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2002/irl_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
35609,372,"IRL","Ireland","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2002/irl_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
35610,372,"IRL","Ireland","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2002/irl_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
35611,372,"IRL","Ireland","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2002/irl_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
35612,372,"IRL","Ireland","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2002/irl_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
35613,372,"IRL","Ireland","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2003/irl_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
35614,372,"IRL","Ireland","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2003/irl_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
35615,372,"IRL","Ireland","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2003/irl_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
35616,372,"IRL","Ireland","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2003/irl_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
35617,372,"IRL","Ireland","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2003/irl_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
35618,372,"IRL","Ireland","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2003/irl_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
35619,372,"IRL","Ireland","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2003/irl_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
35620,372,"IRL","Ireland","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2003/irl_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
35621,372,"IRL","Ireland","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2004/irl_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
35622,372,"IRL","Ireland","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2004/irl_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
35623,372,"IRL","Ireland","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2004/irl_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
35624,372,"IRL","Ireland","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2004/irl_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
35625,372,"IRL","Ireland","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2004/irl_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
35626,372,"IRL","Ireland","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2004/irl_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
35627,372,"IRL","Ireland","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2004/irl_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
35628,372,"IRL","Ireland","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2004/irl_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
35629,372,"IRL","Ireland","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2005/irl_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
35630,372,"IRL","Ireland","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2005/irl_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
35631,372,"IRL","Ireland","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2005/irl_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
35632,372,"IRL","Ireland","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2005/irl_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
35633,372,"IRL","Ireland","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2005/irl_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
35634,372,"IRL","Ireland","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2005/irl_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
35635,372,"IRL","Ireland","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2005/irl_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
35636,372,"IRL","Ireland","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2005/irl_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
35637,372,"IRL","Ireland","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2006/irl_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
35638,372,"IRL","Ireland","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2006/irl_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
35639,372,"IRL","Ireland","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2006/irl_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
35640,372,"IRL","Ireland","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2006/irl_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
35641,372,"IRL","Ireland","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2006/irl_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
35642,372,"IRL","Ireland","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2006/irl_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
35643,372,"IRL","Ireland","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2006/irl_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
35644,372,"IRL","Ireland","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2006/irl_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
35645,372,"IRL","Ireland","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2007/irl_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
35646,372,"IRL","Ireland","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2007/irl_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
35647,372,"IRL","Ireland","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2007/irl_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
35648,372,"IRL","Ireland","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2007/irl_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
35649,372,"IRL","Ireland","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2007/irl_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
35650,372,"IRL","Ireland","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2007/irl_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
35651,372,"IRL","Ireland","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2007/irl_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
35652,372,"IRL","Ireland","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2007/irl_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
35653,372,"IRL","Ireland","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2008/irl_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
35654,372,"IRL","Ireland","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2008/irl_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
35655,372,"IRL","Ireland","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2008/irl_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
35656,372,"IRL","Ireland","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2008/irl_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
35657,372,"IRL","Ireland","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2008/irl_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
35658,372,"IRL","Ireland","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2008/irl_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
35659,372,"IRL","Ireland","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2008/irl_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
35660,372,"IRL","Ireland","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2008/irl_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
35661,372,"IRL","Ireland","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2009/irl_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
35662,372,"IRL","Ireland","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2009/irl_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
35663,372,"IRL","Ireland","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2009/irl_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
35664,372,"IRL","Ireland","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2009/irl_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
35665,372,"IRL","Ireland","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2009/irl_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
35666,372,"IRL","Ireland","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2009/irl_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
35667,372,"IRL","Ireland","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2009/irl_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
35668,372,"IRL","Ireland","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2009/irl_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
35669,372,"IRL","Ireland","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2010/irl_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
35670,372,"IRL","Ireland","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2010/irl_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
35671,372,"IRL","Ireland","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2010/irl_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
35672,372,"IRL","Ireland","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2010/irl_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
35673,372,"IRL","Ireland","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2010/irl_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
35674,372,"IRL","Ireland","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2010/irl_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
35675,372,"IRL","Ireland","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2010/irl_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
35676,372,"IRL","Ireland","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2010/irl_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
35677,372,"IRL","Ireland","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2011/irl_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
35678,372,"IRL","Ireland","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2011/irl_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
35679,372,"IRL","Ireland","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2011/irl_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
35680,372,"IRL","Ireland","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2011/irl_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
35681,372,"IRL","Ireland","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2011/irl_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
35682,372,"IRL","Ireland","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2011/irl_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
35683,372,"IRL","Ireland","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2011/irl_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
35684,372,"IRL","Ireland","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2011/irl_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
35685,372,"IRL","Ireland","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2012/irl_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
35686,372,"IRL","Ireland","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2012/irl_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
35687,372,"IRL","Ireland","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2012/irl_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
35688,372,"IRL","Ireland","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2012/irl_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
35689,372,"IRL","Ireland","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2012/irl_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
35690,372,"IRL","Ireland","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2012/irl_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
35691,372,"IRL","Ireland","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2012/irl_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
35692,372,"IRL","Ireland","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2012/irl_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
35693,372,"IRL","Ireland","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2013/irl_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
35694,372,"IRL","Ireland","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2013/irl_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
35695,372,"IRL","Ireland","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2013/irl_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
35696,372,"IRL","Ireland","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2013/irl_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
35697,372,"IRL","Ireland","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2013/irl_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
35698,372,"IRL","Ireland","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2013/irl_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
35699,372,"IRL","Ireland","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2013/irl_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
35700,372,"IRL","Ireland","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2013/irl_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
35701,372,"IRL","Ireland","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2014/irl_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
35702,372,"IRL","Ireland","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2014/irl_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
35703,372,"IRL","Ireland","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2014/irl_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
35704,372,"IRL","Ireland","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2014/irl_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
35705,372,"IRL","Ireland","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2014/irl_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
35706,372,"IRL","Ireland","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2014/irl_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
35707,372,"IRL","Ireland","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2014/irl_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
35708,372,"IRL","Ireland","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2014/irl_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
35709,372,"IRL","Ireland","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2015/irl_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
35710,372,"IRL","Ireland","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2015/irl_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
35711,372,"IRL","Ireland","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2015/irl_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
35712,372,"IRL","Ireland","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2015/irl_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
35713,372,"IRL","Ireland","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2015/irl_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
35714,372,"IRL","Ireland","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2015/irl_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
35715,372,"IRL","Ireland","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2015/irl_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
35716,372,"IRL","Ireland","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Annual/2015/irl_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
35717,376,"ISR","Israel","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2000/isr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
35718,376,"ISR","Israel","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2000/isr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
35719,376,"ISR","Israel","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2000/isr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
35720,376,"ISR","Israel","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2000/isr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
35721,376,"ISR","Israel","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2000/isr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
35722,376,"ISR","Israel","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2000/isr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
35723,376,"ISR","Israel","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2000/isr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
35724,376,"ISR","Israel","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2000/isr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
35725,376,"ISR","Israel","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2001/isr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
35726,376,"ISR","Israel","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2001/isr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
35727,376,"ISR","Israel","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2001/isr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
35728,376,"ISR","Israel","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2001/isr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
35729,376,"ISR","Israel","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2001/isr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
35730,376,"ISR","Israel","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2001/isr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
35731,376,"ISR","Israel","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2001/isr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
35732,376,"ISR","Israel","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2001/isr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
35733,376,"ISR","Israel","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2002/isr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
35734,376,"ISR","Israel","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2002/isr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
35735,376,"ISR","Israel","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2002/isr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
35736,376,"ISR","Israel","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2002/isr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
35737,376,"ISR","Israel","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2002/isr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
35738,376,"ISR","Israel","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2002/isr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
35739,376,"ISR","Israel","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2002/isr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
35740,376,"ISR","Israel","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2002/isr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
35741,376,"ISR","Israel","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2003/isr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
35742,376,"ISR","Israel","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2003/isr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
35743,376,"ISR","Israel","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2003/isr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
35744,376,"ISR","Israel","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2003/isr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
35745,376,"ISR","Israel","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2003/isr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
35746,376,"ISR","Israel","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2003/isr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
35747,376,"ISR","Israel","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2003/isr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
35748,376,"ISR","Israel","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2003/isr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
35749,376,"ISR","Israel","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2004/isr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
35750,376,"ISR","Israel","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2004/isr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
35751,376,"ISR","Israel","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2004/isr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
35752,376,"ISR","Israel","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2004/isr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
35753,376,"ISR","Israel","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2004/isr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
35754,376,"ISR","Israel","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2004/isr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
35755,376,"ISR","Israel","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2004/isr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
35756,376,"ISR","Israel","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2004/isr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
35757,376,"ISR","Israel","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2005/isr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
35758,376,"ISR","Israel","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2005/isr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
35759,376,"ISR","Israel","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2005/isr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
35760,376,"ISR","Israel","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2005/isr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
35761,376,"ISR","Israel","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2005/isr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
35762,376,"ISR","Israel","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2005/isr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
35763,376,"ISR","Israel","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2005/isr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
35764,376,"ISR","Israel","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2005/isr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
35765,376,"ISR","Israel","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2006/isr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
35766,376,"ISR","Israel","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2006/isr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
35767,376,"ISR","Israel","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2006/isr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
35768,376,"ISR","Israel","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2006/isr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
35769,376,"ISR","Israel","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2006/isr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
35770,376,"ISR","Israel","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2006/isr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
35771,376,"ISR","Israel","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2006/isr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
35772,376,"ISR","Israel","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2006/isr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
35773,376,"ISR","Israel","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2007/isr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
35774,376,"ISR","Israel","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2007/isr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
35775,376,"ISR","Israel","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2007/isr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
35776,376,"ISR","Israel","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2007/isr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
35777,376,"ISR","Israel","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2007/isr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
35778,376,"ISR","Israel","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2007/isr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
35779,376,"ISR","Israel","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2007/isr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
35780,376,"ISR","Israel","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2007/isr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
35781,376,"ISR","Israel","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2008/isr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
35782,376,"ISR","Israel","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2008/isr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
35783,376,"ISR","Israel","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2008/isr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
35784,376,"ISR","Israel","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2008/isr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
35785,376,"ISR","Israel","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2008/isr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
35786,376,"ISR","Israel","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2008/isr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
35787,376,"ISR","Israel","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2008/isr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
35788,376,"ISR","Israel","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2008/isr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
35789,376,"ISR","Israel","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2009/isr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
35790,376,"ISR","Israel","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2009/isr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
35791,376,"ISR","Israel","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2009/isr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
35792,376,"ISR","Israel","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2009/isr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
35793,376,"ISR","Israel","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2009/isr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
35794,376,"ISR","Israel","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2009/isr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
35795,376,"ISR","Israel","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2009/isr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
35796,376,"ISR","Israel","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2009/isr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
35797,376,"ISR","Israel","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2010/isr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
35798,376,"ISR","Israel","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2010/isr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
35799,376,"ISR","Israel","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2010/isr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
35800,376,"ISR","Israel","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2010/isr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
35801,376,"ISR","Israel","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2010/isr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
35802,376,"ISR","Israel","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2010/isr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
35803,376,"ISR","Israel","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2010/isr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
35804,376,"ISR","Israel","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2010/isr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
35805,376,"ISR","Israel","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2011/isr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
35806,376,"ISR","Israel","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2011/isr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
35807,376,"ISR","Israel","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2011/isr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
35808,376,"ISR","Israel","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2011/isr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
35809,376,"ISR","Israel","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2011/isr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
35810,376,"ISR","Israel","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2011/isr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
35811,376,"ISR","Israel","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2011/isr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
35812,376,"ISR","Israel","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2011/isr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
35813,376,"ISR","Israel","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2012/isr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
35814,376,"ISR","Israel","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2012/isr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
35815,376,"ISR","Israel","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2012/isr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
35816,376,"ISR","Israel","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2012/isr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
35817,376,"ISR","Israel","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2012/isr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
35818,376,"ISR","Israel","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2012/isr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
35819,376,"ISR","Israel","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2012/isr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
35820,376,"ISR","Israel","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2012/isr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
35821,376,"ISR","Israel","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2013/isr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
35822,376,"ISR","Israel","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2013/isr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
35823,376,"ISR","Israel","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2013/isr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
35824,376,"ISR","Israel","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2013/isr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
35825,376,"ISR","Israel","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2013/isr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
35826,376,"ISR","Israel","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2013/isr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
35827,376,"ISR","Israel","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2013/isr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
35828,376,"ISR","Israel","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2013/isr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
35829,376,"ISR","Israel","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2014/isr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
35830,376,"ISR","Israel","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2014/isr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
35831,376,"ISR","Israel","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2014/isr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
35832,376,"ISR","Israel","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2014/isr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
35833,376,"ISR","Israel","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2014/isr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
35834,376,"ISR","Israel","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2014/isr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
35835,376,"ISR","Israel","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2014/isr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
35836,376,"ISR","Israel","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2014/isr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
35837,376,"ISR","Israel","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2015/isr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
35838,376,"ISR","Israel","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2015/isr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
35839,376,"ISR","Israel","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2015/isr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
35840,376,"ISR","Israel","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2015/isr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
35841,376,"ISR","Israel","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2015/isr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
35842,376,"ISR","Israel","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2015/isr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
35843,376,"ISR","Israel","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2015/isr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
35844,376,"ISR","Israel","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Annual/2015/isr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
35845,380,"ITA","Italy","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2000/ita_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
35846,380,"ITA","Italy","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2000/ita_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
35847,380,"ITA","Italy","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2000/ita_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
35848,380,"ITA","Italy","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2000/ita_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
35849,380,"ITA","Italy","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2000/ita_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
35850,380,"ITA","Italy","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2000/ita_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
35851,380,"ITA","Italy","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2000/ita_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
35852,380,"ITA","Italy","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2000/ita_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
35853,380,"ITA","Italy","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2001/ita_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
35854,380,"ITA","Italy","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2001/ita_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
35855,380,"ITA","Italy","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2001/ita_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
35856,380,"ITA","Italy","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2001/ita_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
35857,380,"ITA","Italy","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2001/ita_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
35858,380,"ITA","Italy","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2001/ita_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
35859,380,"ITA","Italy","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2001/ita_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
35860,380,"ITA","Italy","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2001/ita_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
35861,380,"ITA","Italy","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2002/ita_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
35862,380,"ITA","Italy","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2002/ita_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
35863,380,"ITA","Italy","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2002/ita_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
35864,380,"ITA","Italy","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2002/ita_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
35865,380,"ITA","Italy","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2002/ita_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
35866,380,"ITA","Italy","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2002/ita_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
35867,380,"ITA","Italy","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2002/ita_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
35868,380,"ITA","Italy","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2002/ita_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
35869,380,"ITA","Italy","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2003/ita_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
35870,380,"ITA","Italy","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2003/ita_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
35871,380,"ITA","Italy","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2003/ita_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
35872,380,"ITA","Italy","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2003/ita_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
35873,380,"ITA","Italy","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2003/ita_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
35874,380,"ITA","Italy","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2003/ita_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
35875,380,"ITA","Italy","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2003/ita_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
35876,380,"ITA","Italy","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2003/ita_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
35877,380,"ITA","Italy","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2004/ita_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
35878,380,"ITA","Italy","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2004/ita_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
35879,380,"ITA","Italy","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2004/ita_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
35880,380,"ITA","Italy","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2004/ita_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
35881,380,"ITA","Italy","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2004/ita_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
35882,380,"ITA","Italy","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2004/ita_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
35883,380,"ITA","Italy","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2004/ita_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
35884,380,"ITA","Italy","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2004/ita_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
35885,380,"ITA","Italy","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2005/ita_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
35886,380,"ITA","Italy","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2005/ita_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
35887,380,"ITA","Italy","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2005/ita_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
35888,380,"ITA","Italy","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2005/ita_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
35889,380,"ITA","Italy","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2005/ita_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
35890,380,"ITA","Italy","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2005/ita_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
35891,380,"ITA","Italy","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2005/ita_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
35892,380,"ITA","Italy","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2005/ita_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
35893,380,"ITA","Italy","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2006/ita_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
35894,380,"ITA","Italy","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2006/ita_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
35895,380,"ITA","Italy","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2006/ita_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
35896,380,"ITA","Italy","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2006/ita_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
35897,380,"ITA","Italy","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2006/ita_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
35898,380,"ITA","Italy","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2006/ita_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
35899,380,"ITA","Italy","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2006/ita_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
35900,380,"ITA","Italy","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2006/ita_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
35901,380,"ITA","Italy","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2007/ita_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
35902,380,"ITA","Italy","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2007/ita_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
35903,380,"ITA","Italy","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2007/ita_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
35904,380,"ITA","Italy","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2007/ita_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
35905,380,"ITA","Italy","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2007/ita_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
35906,380,"ITA","Italy","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2007/ita_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
35907,380,"ITA","Italy","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2007/ita_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
35908,380,"ITA","Italy","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2007/ita_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
35909,380,"ITA","Italy","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2008/ita_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
35910,380,"ITA","Italy","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2008/ita_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
35911,380,"ITA","Italy","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2008/ita_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
35912,380,"ITA","Italy","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2008/ita_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
35913,380,"ITA","Italy","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2008/ita_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
35914,380,"ITA","Italy","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2008/ita_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
35915,380,"ITA","Italy","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2008/ita_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
35916,380,"ITA","Italy","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2008/ita_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
35917,380,"ITA","Italy","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2009/ita_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
35918,380,"ITA","Italy","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2009/ita_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
35919,380,"ITA","Italy","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2009/ita_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
35920,380,"ITA","Italy","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2009/ita_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
35921,380,"ITA","Italy","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2009/ita_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
35922,380,"ITA","Italy","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2009/ita_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
35923,380,"ITA","Italy","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2009/ita_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
35924,380,"ITA","Italy","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2009/ita_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
35925,380,"ITA","Italy","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2010/ita_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
35926,380,"ITA","Italy","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2010/ita_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
35927,380,"ITA","Italy","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2010/ita_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
35928,380,"ITA","Italy","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2010/ita_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
35929,380,"ITA","Italy","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2010/ita_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
35930,380,"ITA","Italy","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2010/ita_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
35931,380,"ITA","Italy","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2010/ita_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
35932,380,"ITA","Italy","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2010/ita_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
35933,380,"ITA","Italy","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2011/ita_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
35934,380,"ITA","Italy","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2011/ita_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
35935,380,"ITA","Italy","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2011/ita_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
35936,380,"ITA","Italy","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2011/ita_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
35937,380,"ITA","Italy","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2011/ita_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
35938,380,"ITA","Italy","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2011/ita_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
35939,380,"ITA","Italy","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2011/ita_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
35940,380,"ITA","Italy","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2011/ita_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
35941,380,"ITA","Italy","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2012/ita_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
35942,380,"ITA","Italy","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2012/ita_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
35943,380,"ITA","Italy","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2012/ita_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
35944,380,"ITA","Italy","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2012/ita_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
35945,380,"ITA","Italy","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2012/ita_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
35946,380,"ITA","Italy","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2012/ita_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
35947,380,"ITA","Italy","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2012/ita_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
35948,380,"ITA","Italy","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2012/ita_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
35949,380,"ITA","Italy","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2013/ita_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
35950,380,"ITA","Italy","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2013/ita_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
35951,380,"ITA","Italy","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2013/ita_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
35952,380,"ITA","Italy","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2013/ita_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
35953,380,"ITA","Italy","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2013/ita_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
35954,380,"ITA","Italy","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2013/ita_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
35955,380,"ITA","Italy","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2013/ita_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
35956,380,"ITA","Italy","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2013/ita_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
35957,380,"ITA","Italy","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2014/ita_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
35958,380,"ITA","Italy","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2014/ita_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
35959,380,"ITA","Italy","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2014/ita_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
35960,380,"ITA","Italy","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2014/ita_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
35961,380,"ITA","Italy","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2014/ita_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
35962,380,"ITA","Italy","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2014/ita_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
35963,380,"ITA","Italy","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2014/ita_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
35964,380,"ITA","Italy","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2014/ita_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
35965,380,"ITA","Italy","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2015/ita_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
35966,380,"ITA","Italy","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2015/ita_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
35967,380,"ITA","Italy","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2015/ita_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
35968,380,"ITA","Italy","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2015/ita_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
35969,380,"ITA","Italy","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2015/ita_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
35970,380,"ITA","Italy","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2015/ita_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
35971,380,"ITA","Italy","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2015/ita_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
35972,380,"ITA","Italy","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Annual/2015/ita_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
35973,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2000/civ_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
35974,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2000/civ_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
35975,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2000/civ_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
35976,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2000/civ_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
35977,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2000/civ_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
35978,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2000/civ_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
35979,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2000/civ_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
35980,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2000/civ_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
35981,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2001/civ_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
35982,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2001/civ_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
35983,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2001/civ_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
35984,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2001/civ_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
35985,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2001/civ_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
35986,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2001/civ_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
35987,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2001/civ_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
35988,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2001/civ_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
35989,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2002/civ_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
35990,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2002/civ_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
35991,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2002/civ_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
35992,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2002/civ_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
35993,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2002/civ_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
35994,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2002/civ_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
35995,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2002/civ_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
35996,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2002/civ_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
35997,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2003/civ_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
35998,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2003/civ_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
35999,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2003/civ_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
36000,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2003/civ_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
36001,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2003/civ_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
36002,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2003/civ_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
36003,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2003/civ_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
36004,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2003/civ_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
36005,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2004/civ_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
36006,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2004/civ_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
36007,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2004/civ_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
36008,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2004/civ_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
36009,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2004/civ_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
36010,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2004/civ_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
36011,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2004/civ_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
36012,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2004/civ_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
36013,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2005/civ_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
36014,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2005/civ_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
36015,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2005/civ_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
36016,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2005/civ_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
36017,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2005/civ_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
36018,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2005/civ_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
36019,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2005/civ_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
36020,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2005/civ_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
36021,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2006/civ_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
36022,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2006/civ_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
36023,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2006/civ_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
36024,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2006/civ_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
36025,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2006/civ_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
36026,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2006/civ_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
36027,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2006/civ_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
36028,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2006/civ_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
36029,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2007/civ_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
36030,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2007/civ_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
36031,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2007/civ_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
36032,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2007/civ_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
36033,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2007/civ_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
36034,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2007/civ_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
36035,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2007/civ_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
36036,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2007/civ_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
36037,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2008/civ_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
36038,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2008/civ_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
36039,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2008/civ_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
36040,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2008/civ_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
36041,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2008/civ_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
36042,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2008/civ_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
36043,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2008/civ_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
36044,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2008/civ_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
36045,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2009/civ_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
36046,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2009/civ_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
36047,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2009/civ_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
36048,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2009/civ_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
36049,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2009/civ_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
36050,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2009/civ_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
36051,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2009/civ_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
36052,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2009/civ_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
36053,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2010/civ_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
36054,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2010/civ_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
36055,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2010/civ_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
36056,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2010/civ_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
36057,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2010/civ_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
36058,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2010/civ_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
36059,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2010/civ_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
36060,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2010/civ_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
36061,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2011/civ_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
36062,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2011/civ_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
36063,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2011/civ_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
36064,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2011/civ_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
36065,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2011/civ_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
36066,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2011/civ_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
36067,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2011/civ_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
36068,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2011/civ_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
36069,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2012/civ_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
36070,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2012/civ_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
36071,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2012/civ_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
36072,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2012/civ_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
36073,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2012/civ_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
36074,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2012/civ_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
36075,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2012/civ_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
36076,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2012/civ_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
36077,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2013/civ_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
36078,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2013/civ_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
36079,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2013/civ_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
36080,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2013/civ_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
36081,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2013/civ_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
36082,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2013/civ_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
36083,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2013/civ_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
36084,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2013/civ_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
36085,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2014/civ_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
36086,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2014/civ_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
36087,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2014/civ_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
36088,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2014/civ_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
36089,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2014/civ_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
36090,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2014/civ_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
36091,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2014/civ_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
36092,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2014/civ_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
36093,384,"CIV","CIte dIvoire","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2015/civ_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
36094,384,"CIV","CIte dIvoire","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2015/civ_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
36095,384,"CIV","CIte dIvoire","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2015/civ_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
36096,384,"CIV","CIte dIvoire","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2015/civ_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
36097,384,"CIV","CIte dIvoire","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2015/civ_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
36098,384,"CIV","CIte dIvoire","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2015/civ_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
36099,384,"CIV","CIte dIvoire","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2015/civ_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
36100,384,"CIV","CIte dIvoire","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Annual/2015/civ_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
36101,388,"JAM","Jamaica","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2000/jam_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
36102,388,"JAM","Jamaica","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2000/jam_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
36103,388,"JAM","Jamaica","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2000/jam_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
36104,388,"JAM","Jamaica","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2000/jam_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
36105,388,"JAM","Jamaica","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2000/jam_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
36106,388,"JAM","Jamaica","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2000/jam_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
36107,388,"JAM","Jamaica","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2000/jam_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
36108,388,"JAM","Jamaica","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2000/jam_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
36109,388,"JAM","Jamaica","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2001/jam_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
36110,388,"JAM","Jamaica","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2001/jam_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
36111,388,"JAM","Jamaica","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2001/jam_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
36112,388,"JAM","Jamaica","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2001/jam_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
36113,388,"JAM","Jamaica","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2001/jam_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
36114,388,"JAM","Jamaica","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2001/jam_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
36115,388,"JAM","Jamaica","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2001/jam_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
36116,388,"JAM","Jamaica","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2001/jam_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
36117,388,"JAM","Jamaica","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2002/jam_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
36118,388,"JAM","Jamaica","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2002/jam_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
36119,388,"JAM","Jamaica","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2002/jam_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
36120,388,"JAM","Jamaica","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2002/jam_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
36121,388,"JAM","Jamaica","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2002/jam_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
36122,388,"JAM","Jamaica","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2002/jam_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
36123,388,"JAM","Jamaica","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2002/jam_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
36124,388,"JAM","Jamaica","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2002/jam_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
36125,388,"JAM","Jamaica","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2003/jam_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
36126,388,"JAM","Jamaica","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2003/jam_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
36127,388,"JAM","Jamaica","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2003/jam_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
36128,388,"JAM","Jamaica","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2003/jam_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
36129,388,"JAM","Jamaica","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2003/jam_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
36130,388,"JAM","Jamaica","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2003/jam_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
36131,388,"JAM","Jamaica","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2003/jam_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
36132,388,"JAM","Jamaica","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2003/jam_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
36133,388,"JAM","Jamaica","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2004/jam_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
36134,388,"JAM","Jamaica","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2004/jam_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
36135,388,"JAM","Jamaica","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2004/jam_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
36136,388,"JAM","Jamaica","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2004/jam_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
36137,388,"JAM","Jamaica","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2004/jam_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
36138,388,"JAM","Jamaica","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2004/jam_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
36139,388,"JAM","Jamaica","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2004/jam_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
36140,388,"JAM","Jamaica","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2004/jam_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
36141,388,"JAM","Jamaica","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2005/jam_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
36142,388,"JAM","Jamaica","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2005/jam_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
36143,388,"JAM","Jamaica","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2005/jam_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
36144,388,"JAM","Jamaica","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2005/jam_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
36145,388,"JAM","Jamaica","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2005/jam_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
36146,388,"JAM","Jamaica","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2005/jam_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
36147,388,"JAM","Jamaica","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2005/jam_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
36148,388,"JAM","Jamaica","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2005/jam_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
36149,388,"JAM","Jamaica","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2006/jam_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
36150,388,"JAM","Jamaica","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2006/jam_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
36151,388,"JAM","Jamaica","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2006/jam_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
36152,388,"JAM","Jamaica","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2006/jam_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
36153,388,"JAM","Jamaica","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2006/jam_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
36154,388,"JAM","Jamaica","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2006/jam_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
36155,388,"JAM","Jamaica","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2006/jam_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
36156,388,"JAM","Jamaica","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2006/jam_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
36157,388,"JAM","Jamaica","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2007/jam_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
36158,388,"JAM","Jamaica","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2007/jam_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
36159,388,"JAM","Jamaica","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2007/jam_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
36160,388,"JAM","Jamaica","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2007/jam_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
36161,388,"JAM","Jamaica","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2007/jam_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
36162,388,"JAM","Jamaica","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2007/jam_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
36163,388,"JAM","Jamaica","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2007/jam_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
36164,388,"JAM","Jamaica","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2007/jam_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
36165,388,"JAM","Jamaica","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2008/jam_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
36166,388,"JAM","Jamaica","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2008/jam_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
36167,388,"JAM","Jamaica","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2008/jam_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
36168,388,"JAM","Jamaica","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2008/jam_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
36169,388,"JAM","Jamaica","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2008/jam_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
36170,388,"JAM","Jamaica","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2008/jam_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
36171,388,"JAM","Jamaica","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2008/jam_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
36172,388,"JAM","Jamaica","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2008/jam_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
36173,388,"JAM","Jamaica","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2009/jam_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
36174,388,"JAM","Jamaica","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2009/jam_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
36175,388,"JAM","Jamaica","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2009/jam_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
36176,388,"JAM","Jamaica","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2009/jam_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
36177,388,"JAM","Jamaica","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2009/jam_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
36178,388,"JAM","Jamaica","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2009/jam_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
36179,388,"JAM","Jamaica","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2009/jam_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
36180,388,"JAM","Jamaica","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2009/jam_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
36181,388,"JAM","Jamaica","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2010/jam_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
36182,388,"JAM","Jamaica","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2010/jam_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
36183,388,"JAM","Jamaica","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2010/jam_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
36184,388,"JAM","Jamaica","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2010/jam_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
36185,388,"JAM","Jamaica","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2010/jam_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
36186,388,"JAM","Jamaica","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2010/jam_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
36187,388,"JAM","Jamaica","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2010/jam_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
36188,388,"JAM","Jamaica","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2010/jam_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
36189,388,"JAM","Jamaica","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2011/jam_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
36190,388,"JAM","Jamaica","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2011/jam_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
36191,388,"JAM","Jamaica","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2011/jam_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
36192,388,"JAM","Jamaica","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2011/jam_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
36193,388,"JAM","Jamaica","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2011/jam_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
36194,388,"JAM","Jamaica","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2011/jam_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
36195,388,"JAM","Jamaica","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2011/jam_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
36196,388,"JAM","Jamaica","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2011/jam_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
36197,388,"JAM","Jamaica","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2012/jam_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
36198,388,"JAM","Jamaica","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2012/jam_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
36199,388,"JAM","Jamaica","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2012/jam_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
36200,388,"JAM","Jamaica","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2012/jam_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
36201,388,"JAM","Jamaica","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2012/jam_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
36202,388,"JAM","Jamaica","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2012/jam_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
36203,388,"JAM","Jamaica","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2012/jam_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
36204,388,"JAM","Jamaica","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2012/jam_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
36205,388,"JAM","Jamaica","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2013/jam_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
36206,388,"JAM","Jamaica","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2013/jam_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
36207,388,"JAM","Jamaica","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2013/jam_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
36208,388,"JAM","Jamaica","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2013/jam_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
36209,388,"JAM","Jamaica","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2013/jam_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
36210,388,"JAM","Jamaica","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2013/jam_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
36211,388,"JAM","Jamaica","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2013/jam_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
36212,388,"JAM","Jamaica","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2013/jam_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
36213,388,"JAM","Jamaica","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2014/jam_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
36214,388,"JAM","Jamaica","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2014/jam_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
36215,388,"JAM","Jamaica","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2014/jam_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
36216,388,"JAM","Jamaica","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2014/jam_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
36217,388,"JAM","Jamaica","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2014/jam_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
36218,388,"JAM","Jamaica","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2014/jam_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
36219,388,"JAM","Jamaica","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2014/jam_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
36220,388,"JAM","Jamaica","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2014/jam_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
36221,388,"JAM","Jamaica","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2015/jam_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
36222,388,"JAM","Jamaica","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2015/jam_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
36223,388,"JAM","Jamaica","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2015/jam_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
36224,388,"JAM","Jamaica","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2015/jam_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
36225,388,"JAM","Jamaica","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2015/jam_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
36226,388,"JAM","Jamaica","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2015/jam_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
36227,388,"JAM","Jamaica","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2015/jam_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
36228,388,"JAM","Jamaica","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Annual/2015/jam_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
36229,392,"JPN","Japan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2000/jpn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
36230,392,"JPN","Japan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2000/jpn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
36231,392,"JPN","Japan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2000/jpn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
36232,392,"JPN","Japan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2000/jpn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
36233,392,"JPN","Japan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2000/jpn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
36234,392,"JPN","Japan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2000/jpn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
36235,392,"JPN","Japan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2000/jpn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
36236,392,"JPN","Japan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2000/jpn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
36237,392,"JPN","Japan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2001/jpn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
36238,392,"JPN","Japan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2001/jpn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
36239,392,"JPN","Japan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2001/jpn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
36240,392,"JPN","Japan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2001/jpn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
36241,392,"JPN","Japan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2001/jpn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
36242,392,"JPN","Japan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2001/jpn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
36243,392,"JPN","Japan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2001/jpn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
36244,392,"JPN","Japan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2001/jpn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
36245,392,"JPN","Japan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2002/jpn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
36246,392,"JPN","Japan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2002/jpn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
36247,392,"JPN","Japan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2002/jpn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
36248,392,"JPN","Japan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2002/jpn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
36249,392,"JPN","Japan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2002/jpn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
36250,392,"JPN","Japan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2002/jpn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
36251,392,"JPN","Japan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2002/jpn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
36252,392,"JPN","Japan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2002/jpn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
36253,392,"JPN","Japan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2003/jpn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
36254,392,"JPN","Japan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2003/jpn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
36255,392,"JPN","Japan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2003/jpn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
36256,392,"JPN","Japan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2003/jpn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
36257,392,"JPN","Japan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2003/jpn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
36258,392,"JPN","Japan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2003/jpn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
36259,392,"JPN","Japan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2003/jpn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
36260,392,"JPN","Japan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2003/jpn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
36261,392,"JPN","Japan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2004/jpn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
36262,392,"JPN","Japan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2004/jpn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
36263,392,"JPN","Japan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2004/jpn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
36264,392,"JPN","Japan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2004/jpn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
36265,392,"JPN","Japan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2004/jpn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
36266,392,"JPN","Japan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2004/jpn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
36267,392,"JPN","Japan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2004/jpn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
36268,392,"JPN","Japan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2004/jpn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
36269,392,"JPN","Japan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2005/jpn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
36270,392,"JPN","Japan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2005/jpn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
36271,392,"JPN","Japan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2005/jpn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
36272,392,"JPN","Japan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2005/jpn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
36273,392,"JPN","Japan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2005/jpn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
36274,392,"JPN","Japan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2005/jpn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
36275,392,"JPN","Japan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2005/jpn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
36276,392,"JPN","Japan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2005/jpn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
36277,392,"JPN","Japan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2006/jpn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
36278,392,"JPN","Japan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2006/jpn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
36279,392,"JPN","Japan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2006/jpn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
36280,392,"JPN","Japan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2006/jpn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
36281,392,"JPN","Japan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2006/jpn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
36282,392,"JPN","Japan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2006/jpn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
36283,392,"JPN","Japan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2006/jpn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
36284,392,"JPN","Japan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2006/jpn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
36285,392,"JPN","Japan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2007/jpn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
36286,392,"JPN","Japan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2007/jpn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
36287,392,"JPN","Japan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2007/jpn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
36288,392,"JPN","Japan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2007/jpn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
36289,392,"JPN","Japan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2007/jpn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
36290,392,"JPN","Japan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2007/jpn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
36291,392,"JPN","Japan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2007/jpn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
36292,392,"JPN","Japan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2007/jpn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
36293,392,"JPN","Japan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2008/jpn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
36294,392,"JPN","Japan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2008/jpn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
36295,392,"JPN","Japan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2008/jpn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
36296,392,"JPN","Japan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2008/jpn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
36297,392,"JPN","Japan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2008/jpn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
36298,392,"JPN","Japan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2008/jpn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
36299,392,"JPN","Japan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2008/jpn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
36300,392,"JPN","Japan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2008/jpn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
36301,392,"JPN","Japan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2009/jpn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
36302,392,"JPN","Japan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2009/jpn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
36303,392,"JPN","Japan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2009/jpn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
36304,392,"JPN","Japan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2009/jpn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
36305,392,"JPN","Japan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2009/jpn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
36306,392,"JPN","Japan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2009/jpn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
36307,392,"JPN","Japan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2009/jpn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
36308,392,"JPN","Japan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2009/jpn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
36309,392,"JPN","Japan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2010/jpn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
36310,392,"JPN","Japan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2010/jpn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
36311,392,"JPN","Japan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2010/jpn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
36312,392,"JPN","Japan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2010/jpn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
36313,392,"JPN","Japan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2010/jpn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
36314,392,"JPN","Japan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2010/jpn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
36315,392,"JPN","Japan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2010/jpn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
36316,392,"JPN","Japan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2010/jpn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
36317,392,"JPN","Japan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2011/jpn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
36318,392,"JPN","Japan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2011/jpn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
36319,392,"JPN","Japan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2011/jpn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
36320,392,"JPN","Japan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2011/jpn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
36321,392,"JPN","Japan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2011/jpn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
36322,392,"JPN","Japan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2011/jpn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
36323,392,"JPN","Japan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2011/jpn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
36324,392,"JPN","Japan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2011/jpn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
36325,392,"JPN","Japan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2012/jpn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
36326,392,"JPN","Japan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2012/jpn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
36327,392,"JPN","Japan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2012/jpn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
36328,392,"JPN","Japan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2012/jpn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
36329,392,"JPN","Japan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2012/jpn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
36330,392,"JPN","Japan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2012/jpn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
36331,392,"JPN","Japan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2012/jpn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
36332,392,"JPN","Japan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2012/jpn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
36333,392,"JPN","Japan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2013/jpn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
36334,392,"JPN","Japan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2013/jpn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
36335,392,"JPN","Japan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2013/jpn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
36336,392,"JPN","Japan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2013/jpn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
36337,392,"JPN","Japan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2013/jpn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
36338,392,"JPN","Japan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2013/jpn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
36339,392,"JPN","Japan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2013/jpn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
36340,392,"JPN","Japan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2013/jpn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
36341,392,"JPN","Japan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2014/jpn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
36342,392,"JPN","Japan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2014/jpn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
36343,392,"JPN","Japan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2014/jpn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
36344,392,"JPN","Japan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2014/jpn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
36345,392,"JPN","Japan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2014/jpn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
36346,392,"JPN","Japan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2014/jpn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
36347,392,"JPN","Japan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2014/jpn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
36348,392,"JPN","Japan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2014/jpn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
36349,392,"JPN","Japan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2015/jpn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
36350,392,"JPN","Japan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2015/jpn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
36351,392,"JPN","Japan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2015/jpn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
36352,392,"JPN","Japan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2015/jpn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
36353,392,"JPN","Japan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2015/jpn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
36354,392,"JPN","Japan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2015/jpn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
36355,392,"JPN","Japan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2015/jpn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
36356,392,"JPN","Japan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Annual/2015/jpn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
36357,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2000/kaz_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
36358,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2000/kaz_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
36359,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2000/kaz_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
36360,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2000/kaz_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
36361,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2000/kaz_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
36362,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2000/kaz_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
36363,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2000/kaz_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
36364,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2000/kaz_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
36365,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2001/kaz_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
36366,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2001/kaz_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
36367,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2001/kaz_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
36368,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2001/kaz_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
36369,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2001/kaz_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
36370,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2001/kaz_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
36371,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2001/kaz_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
36372,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2001/kaz_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
36373,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2002/kaz_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
36374,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2002/kaz_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
36375,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2002/kaz_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
36376,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2002/kaz_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
36377,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2002/kaz_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
36378,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2002/kaz_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
36379,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2002/kaz_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
36380,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2002/kaz_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
36381,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2003/kaz_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
36382,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2003/kaz_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
36383,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2003/kaz_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
36384,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2003/kaz_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
36385,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2003/kaz_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
36386,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2003/kaz_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
36387,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2003/kaz_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
36388,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2003/kaz_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
36389,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2004/kaz_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
36390,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2004/kaz_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
36391,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2004/kaz_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
36392,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2004/kaz_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
36393,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2004/kaz_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
36394,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2004/kaz_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
36395,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2004/kaz_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
36396,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2004/kaz_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
36397,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2005/kaz_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
36398,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2005/kaz_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
36399,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2005/kaz_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
36400,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2005/kaz_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
36401,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2005/kaz_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
36402,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2005/kaz_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
36403,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2005/kaz_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
36404,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2005/kaz_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
36405,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2006/kaz_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
36406,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2006/kaz_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
36407,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2006/kaz_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
36408,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2006/kaz_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
36409,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2006/kaz_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
36410,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2006/kaz_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
36411,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2006/kaz_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
36412,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2006/kaz_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
36413,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2007/kaz_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
36414,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2007/kaz_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
36415,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2007/kaz_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
36416,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2007/kaz_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
36417,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2007/kaz_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
36418,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2007/kaz_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
36419,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2007/kaz_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
36420,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2007/kaz_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
36421,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2008/kaz_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
36422,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2008/kaz_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
36423,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2008/kaz_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
36424,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2008/kaz_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
36425,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2008/kaz_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
36426,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2008/kaz_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
36427,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2008/kaz_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
36428,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2008/kaz_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
36429,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2009/kaz_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
36430,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2009/kaz_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
36431,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2009/kaz_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
36432,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2009/kaz_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
36433,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2009/kaz_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
36434,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2009/kaz_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
36435,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2009/kaz_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
36436,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2009/kaz_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
36437,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2010/kaz_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
36438,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2010/kaz_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
36439,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2010/kaz_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
36440,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2010/kaz_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
36441,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2010/kaz_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
36442,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2010/kaz_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
36443,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2010/kaz_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
36444,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2010/kaz_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
36445,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2011/kaz_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
36446,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2011/kaz_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
36447,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2011/kaz_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
36448,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2011/kaz_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
36449,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2011/kaz_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
36450,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2011/kaz_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
36451,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2011/kaz_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
36452,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2011/kaz_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
36453,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2012/kaz_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
36454,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2012/kaz_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
36455,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2012/kaz_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
36456,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2012/kaz_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
36457,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2012/kaz_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
36458,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2012/kaz_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
36459,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2012/kaz_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
36460,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2012/kaz_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
36461,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2013/kaz_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
36462,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2013/kaz_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
36463,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2013/kaz_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
36464,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2013/kaz_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
36465,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2013/kaz_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
36466,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2013/kaz_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
36467,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2013/kaz_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
36468,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2013/kaz_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
36469,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2014/kaz_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
36470,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2014/kaz_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
36471,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2014/kaz_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
36472,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2014/kaz_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
36473,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2014/kaz_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
36474,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2014/kaz_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
36475,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2014/kaz_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
36476,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2014/kaz_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
36477,398,"KAZ","Kazakhstan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2015/kaz_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
36478,398,"KAZ","Kazakhstan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2015/kaz_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
36479,398,"KAZ","Kazakhstan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2015/kaz_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
36480,398,"KAZ","Kazakhstan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2015/kaz_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
36481,398,"KAZ","Kazakhstan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2015/kaz_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
36482,398,"KAZ","Kazakhstan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2015/kaz_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
36483,398,"KAZ","Kazakhstan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2015/kaz_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
36484,398,"KAZ","Kazakhstan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Annual/2015/kaz_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
36485,400,"JOR","Jordan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2000/jor_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
36486,400,"JOR","Jordan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2000/jor_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
36487,400,"JOR","Jordan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2000/jor_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
36488,400,"JOR","Jordan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2000/jor_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
36489,400,"JOR","Jordan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2000/jor_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
36490,400,"JOR","Jordan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2000/jor_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
36491,400,"JOR","Jordan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2000/jor_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
36492,400,"JOR","Jordan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2000/jor_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
36493,400,"JOR","Jordan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2001/jor_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
36494,400,"JOR","Jordan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2001/jor_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
36495,400,"JOR","Jordan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2001/jor_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
36496,400,"JOR","Jordan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2001/jor_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
36497,400,"JOR","Jordan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2001/jor_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
36498,400,"JOR","Jordan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2001/jor_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
36499,400,"JOR","Jordan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2001/jor_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
36500,400,"JOR","Jordan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2001/jor_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
36501,400,"JOR","Jordan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2002/jor_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
36502,400,"JOR","Jordan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2002/jor_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
36503,400,"JOR","Jordan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2002/jor_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
36504,400,"JOR","Jordan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2002/jor_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
36505,400,"JOR","Jordan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2002/jor_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
36506,400,"JOR","Jordan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2002/jor_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
36507,400,"JOR","Jordan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2002/jor_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
36508,400,"JOR","Jordan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2002/jor_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
36509,400,"JOR","Jordan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2003/jor_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
36510,400,"JOR","Jordan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2003/jor_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
36511,400,"JOR","Jordan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2003/jor_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
36512,400,"JOR","Jordan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2003/jor_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
36513,400,"JOR","Jordan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2003/jor_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
36514,400,"JOR","Jordan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2003/jor_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
36515,400,"JOR","Jordan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2003/jor_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
36516,400,"JOR","Jordan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2003/jor_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
36517,400,"JOR","Jordan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2004/jor_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
36518,400,"JOR","Jordan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2004/jor_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
36519,400,"JOR","Jordan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2004/jor_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
36520,400,"JOR","Jordan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2004/jor_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
36521,400,"JOR","Jordan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2004/jor_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
36522,400,"JOR","Jordan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2004/jor_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
36523,400,"JOR","Jordan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2004/jor_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
36524,400,"JOR","Jordan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2004/jor_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
36525,400,"JOR","Jordan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2005/jor_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
36526,400,"JOR","Jordan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2005/jor_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
36527,400,"JOR","Jordan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2005/jor_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
36528,400,"JOR","Jordan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2005/jor_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
36529,400,"JOR","Jordan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2005/jor_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
36530,400,"JOR","Jordan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2005/jor_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
36531,400,"JOR","Jordan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2005/jor_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
36532,400,"JOR","Jordan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2005/jor_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
36533,400,"JOR","Jordan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2006/jor_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
36534,400,"JOR","Jordan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2006/jor_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
36535,400,"JOR","Jordan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2006/jor_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
36536,400,"JOR","Jordan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2006/jor_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
36537,400,"JOR","Jordan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2006/jor_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
36538,400,"JOR","Jordan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2006/jor_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
36539,400,"JOR","Jordan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2006/jor_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
36540,400,"JOR","Jordan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2006/jor_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
36541,400,"JOR","Jordan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2007/jor_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
36542,400,"JOR","Jordan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2007/jor_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
36543,400,"JOR","Jordan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2007/jor_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
36544,400,"JOR","Jordan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2007/jor_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
36545,400,"JOR","Jordan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2007/jor_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
36546,400,"JOR","Jordan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2007/jor_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
36547,400,"JOR","Jordan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2007/jor_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
36548,400,"JOR","Jordan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2007/jor_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
36549,400,"JOR","Jordan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2008/jor_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
36550,400,"JOR","Jordan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2008/jor_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
36551,400,"JOR","Jordan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2008/jor_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
36552,400,"JOR","Jordan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2008/jor_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
36553,400,"JOR","Jordan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2008/jor_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
36554,400,"JOR","Jordan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2008/jor_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
36555,400,"JOR","Jordan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2008/jor_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
36556,400,"JOR","Jordan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2008/jor_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
36557,400,"JOR","Jordan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2009/jor_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
36558,400,"JOR","Jordan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2009/jor_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
36559,400,"JOR","Jordan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2009/jor_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
36560,400,"JOR","Jordan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2009/jor_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
36561,400,"JOR","Jordan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2009/jor_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
36562,400,"JOR","Jordan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2009/jor_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
36563,400,"JOR","Jordan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2009/jor_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
36564,400,"JOR","Jordan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2009/jor_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
36565,400,"JOR","Jordan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2010/jor_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
36566,400,"JOR","Jordan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2010/jor_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
36567,400,"JOR","Jordan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2010/jor_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
36568,400,"JOR","Jordan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2010/jor_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
36569,400,"JOR","Jordan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2010/jor_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
36570,400,"JOR","Jordan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2010/jor_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
36571,400,"JOR","Jordan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2010/jor_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
36572,400,"JOR","Jordan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2010/jor_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
36573,400,"JOR","Jordan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2011/jor_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
36574,400,"JOR","Jordan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2011/jor_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
36575,400,"JOR","Jordan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2011/jor_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
36576,400,"JOR","Jordan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2011/jor_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
36577,400,"JOR","Jordan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2011/jor_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
36578,400,"JOR","Jordan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2011/jor_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
36579,400,"JOR","Jordan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2011/jor_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
36580,400,"JOR","Jordan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2011/jor_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
36581,400,"JOR","Jordan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2012/jor_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
36582,400,"JOR","Jordan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2012/jor_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
36583,400,"JOR","Jordan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2012/jor_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
36584,400,"JOR","Jordan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2012/jor_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
36585,400,"JOR","Jordan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2012/jor_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
36586,400,"JOR","Jordan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2012/jor_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
36587,400,"JOR","Jordan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2012/jor_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
36588,400,"JOR","Jordan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2012/jor_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
36589,400,"JOR","Jordan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2013/jor_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
36590,400,"JOR","Jordan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2013/jor_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
36591,400,"JOR","Jordan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2013/jor_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
36592,400,"JOR","Jordan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2013/jor_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
36593,400,"JOR","Jordan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2013/jor_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
36594,400,"JOR","Jordan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2013/jor_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
36595,400,"JOR","Jordan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2013/jor_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
36596,400,"JOR","Jordan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2013/jor_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
36597,400,"JOR","Jordan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2014/jor_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
36598,400,"JOR","Jordan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2014/jor_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
36599,400,"JOR","Jordan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2014/jor_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
36600,400,"JOR","Jordan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2014/jor_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
36601,400,"JOR","Jordan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2014/jor_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
36602,400,"JOR","Jordan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2014/jor_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
36603,400,"JOR","Jordan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2014/jor_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
36604,400,"JOR","Jordan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2014/jor_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
36605,400,"JOR","Jordan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2015/jor_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
36606,400,"JOR","Jordan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2015/jor_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
36607,400,"JOR","Jordan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2015/jor_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
36608,400,"JOR","Jordan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2015/jor_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
36609,400,"JOR","Jordan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2015/jor_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
36610,400,"JOR","Jordan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2015/jor_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
36611,400,"JOR","Jordan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2015/jor_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
36612,400,"JOR","Jordan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Annual/2015/jor_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
36613,404,"KEN","Kenya","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2000/ken_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
36614,404,"KEN","Kenya","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2000/ken_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
36615,404,"KEN","Kenya","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2000/ken_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
36616,404,"KEN","Kenya","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2000/ken_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
36617,404,"KEN","Kenya","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2000/ken_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
36618,404,"KEN","Kenya","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2000/ken_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
36619,404,"KEN","Kenya","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2000/ken_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
36620,404,"KEN","Kenya","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2000/ken_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
36621,404,"KEN","Kenya","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2001/ken_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
36622,404,"KEN","Kenya","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2001/ken_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
36623,404,"KEN","Kenya","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2001/ken_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
36624,404,"KEN","Kenya","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2001/ken_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
36625,404,"KEN","Kenya","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2001/ken_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
36626,404,"KEN","Kenya","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2001/ken_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
36627,404,"KEN","Kenya","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2001/ken_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
36628,404,"KEN","Kenya","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2001/ken_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
36629,404,"KEN","Kenya","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2002/ken_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
36630,404,"KEN","Kenya","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2002/ken_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
36631,404,"KEN","Kenya","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2002/ken_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
36632,404,"KEN","Kenya","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2002/ken_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
36633,404,"KEN","Kenya","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2002/ken_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
36634,404,"KEN","Kenya","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2002/ken_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
36635,404,"KEN","Kenya","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2002/ken_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
36636,404,"KEN","Kenya","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2002/ken_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
36637,404,"KEN","Kenya","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2003/ken_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
36638,404,"KEN","Kenya","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2003/ken_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
36639,404,"KEN","Kenya","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2003/ken_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
36640,404,"KEN","Kenya","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2003/ken_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
36641,404,"KEN","Kenya","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2003/ken_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
36642,404,"KEN","Kenya","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2003/ken_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
36643,404,"KEN","Kenya","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2003/ken_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
36644,404,"KEN","Kenya","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2003/ken_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
36645,404,"KEN","Kenya","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2004/ken_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
36646,404,"KEN","Kenya","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2004/ken_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
36647,404,"KEN","Kenya","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2004/ken_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
36648,404,"KEN","Kenya","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2004/ken_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
36649,404,"KEN","Kenya","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2004/ken_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
36650,404,"KEN","Kenya","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2004/ken_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
36651,404,"KEN","Kenya","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2004/ken_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
36652,404,"KEN","Kenya","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2004/ken_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
36653,404,"KEN","Kenya","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2005/ken_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
36654,404,"KEN","Kenya","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2005/ken_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
36655,404,"KEN","Kenya","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2005/ken_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
36656,404,"KEN","Kenya","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2005/ken_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
36657,404,"KEN","Kenya","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2005/ken_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
36658,404,"KEN","Kenya","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2005/ken_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
36659,404,"KEN","Kenya","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2005/ken_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
36660,404,"KEN","Kenya","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2005/ken_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
36661,404,"KEN","Kenya","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2006/ken_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
36662,404,"KEN","Kenya","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2006/ken_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
36663,404,"KEN","Kenya","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2006/ken_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
36664,404,"KEN","Kenya","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2006/ken_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
36665,404,"KEN","Kenya","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2006/ken_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
36666,404,"KEN","Kenya","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2006/ken_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
36667,404,"KEN","Kenya","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2006/ken_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
36668,404,"KEN","Kenya","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2006/ken_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
36669,404,"KEN","Kenya","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2007/ken_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
36670,404,"KEN","Kenya","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2007/ken_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
36671,404,"KEN","Kenya","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2007/ken_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
36672,404,"KEN","Kenya","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2007/ken_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
36673,404,"KEN","Kenya","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2007/ken_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
36674,404,"KEN","Kenya","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2007/ken_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
36675,404,"KEN","Kenya","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2007/ken_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
36676,404,"KEN","Kenya","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2007/ken_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
36677,404,"KEN","Kenya","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2008/ken_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
36678,404,"KEN","Kenya","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2008/ken_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
36679,404,"KEN","Kenya","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2008/ken_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
36680,404,"KEN","Kenya","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2008/ken_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
36681,404,"KEN","Kenya","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2008/ken_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
36682,404,"KEN","Kenya","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2008/ken_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
36683,404,"KEN","Kenya","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2008/ken_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
36684,404,"KEN","Kenya","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2008/ken_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
36685,404,"KEN","Kenya","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2009/ken_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
36686,404,"KEN","Kenya","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2009/ken_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
36687,404,"KEN","Kenya","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2009/ken_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
36688,404,"KEN","Kenya","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2009/ken_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
36689,404,"KEN","Kenya","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2009/ken_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
36690,404,"KEN","Kenya","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2009/ken_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
36691,404,"KEN","Kenya","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2009/ken_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
36692,404,"KEN","Kenya","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2009/ken_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
36693,404,"KEN","Kenya","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2010/ken_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
36694,404,"KEN","Kenya","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2010/ken_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
36695,404,"KEN","Kenya","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2010/ken_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
36696,404,"KEN","Kenya","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2010/ken_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
36697,404,"KEN","Kenya","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2010/ken_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
36698,404,"KEN","Kenya","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2010/ken_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
36699,404,"KEN","Kenya","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2010/ken_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
36700,404,"KEN","Kenya","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2010/ken_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
36701,404,"KEN","Kenya","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2011/ken_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
36702,404,"KEN","Kenya","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2011/ken_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
36703,404,"KEN","Kenya","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2011/ken_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
36704,404,"KEN","Kenya","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2011/ken_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
36705,404,"KEN","Kenya","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2011/ken_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
36706,404,"KEN","Kenya","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2011/ken_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
36707,404,"KEN","Kenya","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2011/ken_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
36708,404,"KEN","Kenya","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2011/ken_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
36709,404,"KEN","Kenya","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2012/ken_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
36710,404,"KEN","Kenya","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2012/ken_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
36711,404,"KEN","Kenya","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2012/ken_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
36712,404,"KEN","Kenya","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2012/ken_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
36713,404,"KEN","Kenya","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2012/ken_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
36714,404,"KEN","Kenya","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2012/ken_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
36715,404,"KEN","Kenya","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2012/ken_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
36716,404,"KEN","Kenya","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2012/ken_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
36717,404,"KEN","Kenya","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2013/ken_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
36718,404,"KEN","Kenya","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2013/ken_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
36719,404,"KEN","Kenya","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2013/ken_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
36720,404,"KEN","Kenya","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2013/ken_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
36721,404,"KEN","Kenya","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2013/ken_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
36722,404,"KEN","Kenya","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2013/ken_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
36723,404,"KEN","Kenya","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2013/ken_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
36724,404,"KEN","Kenya","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2013/ken_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
36725,404,"KEN","Kenya","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2014/ken_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
36726,404,"KEN","Kenya","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2014/ken_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
36727,404,"KEN","Kenya","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2014/ken_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
36728,404,"KEN","Kenya","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2014/ken_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
36729,404,"KEN","Kenya","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2014/ken_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
36730,404,"KEN","Kenya","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2014/ken_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
36731,404,"KEN","Kenya","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2014/ken_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
36732,404,"KEN","Kenya","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2014/ken_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
36733,404,"KEN","Kenya","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2015/ken_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
36734,404,"KEN","Kenya","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2015/ken_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
36735,404,"KEN","Kenya","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2015/ken_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
36736,404,"KEN","Kenya","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2015/ken_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
36737,404,"KEN","Kenya","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2015/ken_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
36738,404,"KEN","Kenya","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2015/ken_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
36739,404,"KEN","Kenya","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2015/ken_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
36740,404,"KEN","Kenya","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Annual/2015/ken_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
36741,408,"PRK","North Korea","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2000/prk_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
36742,408,"PRK","North Korea","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2000/prk_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
36743,408,"PRK","North Korea","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2000/prk_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
36744,408,"PRK","North Korea","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2000/prk_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
36745,408,"PRK","North Korea","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2000/prk_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
36746,408,"PRK","North Korea","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2000/prk_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
36747,408,"PRK","North Korea","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2000/prk_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
36748,408,"PRK","North Korea","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2000/prk_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
36749,408,"PRK","North Korea","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2001/prk_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
36750,408,"PRK","North Korea","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2001/prk_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
36751,408,"PRK","North Korea","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2001/prk_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
36752,408,"PRK","North Korea","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2001/prk_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
36753,408,"PRK","North Korea","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2001/prk_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
36754,408,"PRK","North Korea","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2001/prk_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
36755,408,"PRK","North Korea","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2001/prk_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
36756,408,"PRK","North Korea","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2001/prk_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
36757,408,"PRK","North Korea","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2002/prk_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
36758,408,"PRK","North Korea","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2002/prk_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
36759,408,"PRK","North Korea","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2002/prk_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
36760,408,"PRK","North Korea","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2002/prk_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
36761,408,"PRK","North Korea","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2002/prk_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
36762,408,"PRK","North Korea","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2002/prk_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
36763,408,"PRK","North Korea","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2002/prk_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
36764,408,"PRK","North Korea","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2002/prk_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
36765,408,"PRK","North Korea","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2003/prk_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
36766,408,"PRK","North Korea","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2003/prk_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
36767,408,"PRK","North Korea","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2003/prk_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
36768,408,"PRK","North Korea","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2003/prk_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
36769,408,"PRK","North Korea","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2003/prk_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
36770,408,"PRK","North Korea","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2003/prk_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
36771,408,"PRK","North Korea","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2003/prk_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
36772,408,"PRK","North Korea","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2003/prk_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
36773,408,"PRK","North Korea","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2004/prk_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
36774,408,"PRK","North Korea","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2004/prk_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
36775,408,"PRK","North Korea","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2004/prk_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
36776,408,"PRK","North Korea","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2004/prk_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
36777,408,"PRK","North Korea","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2004/prk_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
36778,408,"PRK","North Korea","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2004/prk_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
36779,408,"PRK","North Korea","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2004/prk_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
36780,408,"PRK","North Korea","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2004/prk_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
36781,408,"PRK","North Korea","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2005/prk_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
36782,408,"PRK","North Korea","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2005/prk_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
36783,408,"PRK","North Korea","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2005/prk_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
36784,408,"PRK","North Korea","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2005/prk_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
36785,408,"PRK","North Korea","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2005/prk_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
36786,408,"PRK","North Korea","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2005/prk_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
36787,408,"PRK","North Korea","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2005/prk_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
36788,408,"PRK","North Korea","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2005/prk_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
36789,408,"PRK","North Korea","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2006/prk_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
36790,408,"PRK","North Korea","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2006/prk_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
36791,408,"PRK","North Korea","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2006/prk_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
36792,408,"PRK","North Korea","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2006/prk_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
36793,408,"PRK","North Korea","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2006/prk_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
36794,408,"PRK","North Korea","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2006/prk_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
36795,408,"PRK","North Korea","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2006/prk_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
36796,408,"PRK","North Korea","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2006/prk_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
36797,408,"PRK","North Korea","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2007/prk_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
36798,408,"PRK","North Korea","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2007/prk_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
36799,408,"PRK","North Korea","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2007/prk_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
36800,408,"PRK","North Korea","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2007/prk_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
36801,408,"PRK","North Korea","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2007/prk_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
36802,408,"PRK","North Korea","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2007/prk_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
36803,408,"PRK","North Korea","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2007/prk_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
36804,408,"PRK","North Korea","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2007/prk_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
36805,408,"PRK","North Korea","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2008/prk_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
36806,408,"PRK","North Korea","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2008/prk_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
36807,408,"PRK","North Korea","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2008/prk_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
36808,408,"PRK","North Korea","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2008/prk_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
36809,408,"PRK","North Korea","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2008/prk_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
36810,408,"PRK","North Korea","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2008/prk_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
36811,408,"PRK","North Korea","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2008/prk_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
36812,408,"PRK","North Korea","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2008/prk_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
36813,408,"PRK","North Korea","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2009/prk_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
36814,408,"PRK","North Korea","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2009/prk_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
36815,408,"PRK","North Korea","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2009/prk_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
36816,408,"PRK","North Korea","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2009/prk_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
36817,408,"PRK","North Korea","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2009/prk_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
36818,408,"PRK","North Korea","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2009/prk_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
36819,408,"PRK","North Korea","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2009/prk_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
36820,408,"PRK","North Korea","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2009/prk_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
36821,408,"PRK","North Korea","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2010/prk_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
36822,408,"PRK","North Korea","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2010/prk_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
36823,408,"PRK","North Korea","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2010/prk_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
36824,408,"PRK","North Korea","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2010/prk_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
36825,408,"PRK","North Korea","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2010/prk_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
36826,408,"PRK","North Korea","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2010/prk_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
36827,408,"PRK","North Korea","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2010/prk_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
36828,408,"PRK","North Korea","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2010/prk_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
36829,408,"PRK","North Korea","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2011/prk_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
36830,408,"PRK","North Korea","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2011/prk_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
36831,408,"PRK","North Korea","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2011/prk_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
36832,408,"PRK","North Korea","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2011/prk_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
36833,408,"PRK","North Korea","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2011/prk_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
36834,408,"PRK","North Korea","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2011/prk_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
36835,408,"PRK","North Korea","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2011/prk_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
36836,408,"PRK","North Korea","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2011/prk_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
36837,408,"PRK","North Korea","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2012/prk_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
36838,408,"PRK","North Korea","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2012/prk_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
36839,408,"PRK","North Korea","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2012/prk_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
36840,408,"PRK","North Korea","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2012/prk_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
36841,408,"PRK","North Korea","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2012/prk_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
36842,408,"PRK","North Korea","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2012/prk_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
36843,408,"PRK","North Korea","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2012/prk_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
36844,408,"PRK","North Korea","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2012/prk_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
36845,408,"PRK","North Korea","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2013/prk_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
36846,408,"PRK","North Korea","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2013/prk_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
36847,408,"PRK","North Korea","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2013/prk_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
36848,408,"PRK","North Korea","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2013/prk_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
36849,408,"PRK","North Korea","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2013/prk_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
36850,408,"PRK","North Korea","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2013/prk_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
36851,408,"PRK","North Korea","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2013/prk_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
36852,408,"PRK","North Korea","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2013/prk_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
36853,408,"PRK","North Korea","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2014/prk_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
36854,408,"PRK","North Korea","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2014/prk_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
36855,408,"PRK","North Korea","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2014/prk_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
36856,408,"PRK","North Korea","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2014/prk_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
36857,408,"PRK","North Korea","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2014/prk_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
36858,408,"PRK","North Korea","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2014/prk_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
36859,408,"PRK","North Korea","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2014/prk_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
36860,408,"PRK","North Korea","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2014/prk_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
36861,408,"PRK","North Korea","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2015/prk_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
36862,408,"PRK","North Korea","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2015/prk_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
36863,408,"PRK","North Korea","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2015/prk_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
36864,408,"PRK","North Korea","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2015/prk_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
36865,408,"PRK","North Korea","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2015/prk_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
36866,408,"PRK","North Korea","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2015/prk_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
36867,408,"PRK","North Korea","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2015/prk_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
36868,408,"PRK","North Korea","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Annual/2015/prk_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
36869,410,"KOR","South Korea","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2000/kor_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
36870,410,"KOR","South Korea","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2000/kor_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
36871,410,"KOR","South Korea","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2000/kor_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
36872,410,"KOR","South Korea","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2000/kor_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
36873,410,"KOR","South Korea","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2000/kor_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
36874,410,"KOR","South Korea","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2000/kor_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
36875,410,"KOR","South Korea","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2000/kor_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
36876,410,"KOR","South Korea","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2000/kor_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
36877,410,"KOR","South Korea","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2001/kor_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
36878,410,"KOR","South Korea","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2001/kor_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
36879,410,"KOR","South Korea","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2001/kor_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
36880,410,"KOR","South Korea","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2001/kor_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
36881,410,"KOR","South Korea","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2001/kor_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
36882,410,"KOR","South Korea","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2001/kor_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
36883,410,"KOR","South Korea","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2001/kor_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
36884,410,"KOR","South Korea","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2001/kor_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
36885,410,"KOR","South Korea","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2002/kor_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
36886,410,"KOR","South Korea","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2002/kor_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
36887,410,"KOR","South Korea","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2002/kor_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
36888,410,"KOR","South Korea","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2002/kor_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
36889,410,"KOR","South Korea","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2002/kor_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
36890,410,"KOR","South Korea","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2002/kor_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
36891,410,"KOR","South Korea","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2002/kor_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
36892,410,"KOR","South Korea","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2002/kor_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
36893,410,"KOR","South Korea","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2003/kor_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
36894,410,"KOR","South Korea","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2003/kor_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
36895,410,"KOR","South Korea","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2003/kor_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
36896,410,"KOR","South Korea","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2003/kor_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
36897,410,"KOR","South Korea","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2003/kor_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
36898,410,"KOR","South Korea","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2003/kor_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
36899,410,"KOR","South Korea","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2003/kor_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
36900,410,"KOR","South Korea","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2003/kor_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
36901,410,"KOR","South Korea","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2004/kor_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
36902,410,"KOR","South Korea","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2004/kor_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
36903,410,"KOR","South Korea","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2004/kor_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
36904,410,"KOR","South Korea","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2004/kor_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
36905,410,"KOR","South Korea","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2004/kor_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
36906,410,"KOR","South Korea","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2004/kor_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
36907,410,"KOR","South Korea","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2004/kor_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
36908,410,"KOR","South Korea","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2004/kor_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
36909,410,"KOR","South Korea","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2005/kor_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
36910,410,"KOR","South Korea","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2005/kor_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
36911,410,"KOR","South Korea","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2005/kor_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
36912,410,"KOR","South Korea","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2005/kor_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
36913,410,"KOR","South Korea","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2005/kor_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
36914,410,"KOR","South Korea","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2005/kor_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
36915,410,"KOR","South Korea","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2005/kor_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
36916,410,"KOR","South Korea","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2005/kor_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
36917,410,"KOR","South Korea","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2006/kor_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
36918,410,"KOR","South Korea","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2006/kor_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
36919,410,"KOR","South Korea","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2006/kor_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
36920,410,"KOR","South Korea","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2006/kor_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
36921,410,"KOR","South Korea","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2006/kor_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
36922,410,"KOR","South Korea","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2006/kor_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
36923,410,"KOR","South Korea","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2006/kor_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
36924,410,"KOR","South Korea","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2006/kor_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
36925,410,"KOR","South Korea","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2007/kor_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
36926,410,"KOR","South Korea","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2007/kor_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
36927,410,"KOR","South Korea","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2007/kor_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
36928,410,"KOR","South Korea","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2007/kor_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
36929,410,"KOR","South Korea","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2007/kor_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
36930,410,"KOR","South Korea","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2007/kor_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
36931,410,"KOR","South Korea","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2007/kor_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
36932,410,"KOR","South Korea","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2007/kor_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
36933,410,"KOR","South Korea","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2008/kor_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
36934,410,"KOR","South Korea","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2008/kor_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
36935,410,"KOR","South Korea","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2008/kor_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
36936,410,"KOR","South Korea","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2008/kor_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
36937,410,"KOR","South Korea","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2008/kor_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
36938,410,"KOR","South Korea","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2008/kor_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
36939,410,"KOR","South Korea","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2008/kor_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
36940,410,"KOR","South Korea","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2008/kor_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
36941,410,"KOR","South Korea","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2009/kor_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
36942,410,"KOR","South Korea","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2009/kor_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
36943,410,"KOR","South Korea","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2009/kor_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
36944,410,"KOR","South Korea","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2009/kor_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
36945,410,"KOR","South Korea","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2009/kor_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
36946,410,"KOR","South Korea","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2009/kor_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
36947,410,"KOR","South Korea","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2009/kor_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
36948,410,"KOR","South Korea","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2009/kor_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
36949,410,"KOR","South Korea","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2010/kor_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
36950,410,"KOR","South Korea","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2010/kor_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
36951,410,"KOR","South Korea","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2010/kor_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
36952,410,"KOR","South Korea","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2010/kor_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
36953,410,"KOR","South Korea","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2010/kor_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
36954,410,"KOR","South Korea","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2010/kor_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
36955,410,"KOR","South Korea","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2010/kor_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
36956,410,"KOR","South Korea","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2010/kor_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
36957,410,"KOR","South Korea","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2011/kor_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
36958,410,"KOR","South Korea","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2011/kor_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
36959,410,"KOR","South Korea","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2011/kor_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
36960,410,"KOR","South Korea","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2011/kor_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
36961,410,"KOR","South Korea","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2011/kor_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
36962,410,"KOR","South Korea","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2011/kor_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
36963,410,"KOR","South Korea","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2011/kor_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
36964,410,"KOR","South Korea","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2011/kor_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
36965,410,"KOR","South Korea","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2012/kor_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
36966,410,"KOR","South Korea","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2012/kor_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
36967,410,"KOR","South Korea","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2012/kor_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
36968,410,"KOR","South Korea","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2012/kor_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
36969,410,"KOR","South Korea","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2012/kor_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
36970,410,"KOR","South Korea","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2012/kor_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
36971,410,"KOR","South Korea","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2012/kor_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
36972,410,"KOR","South Korea","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2012/kor_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
36973,410,"KOR","South Korea","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2013/kor_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
36974,410,"KOR","South Korea","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2013/kor_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
36975,410,"KOR","South Korea","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2013/kor_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
36976,410,"KOR","South Korea","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2013/kor_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
36977,410,"KOR","South Korea","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2013/kor_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
36978,410,"KOR","South Korea","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2013/kor_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
36979,410,"KOR","South Korea","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2013/kor_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
36980,410,"KOR","South Korea","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2013/kor_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
36981,410,"KOR","South Korea","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2014/kor_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
36982,410,"KOR","South Korea","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2014/kor_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
36983,410,"KOR","South Korea","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2014/kor_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
36984,410,"KOR","South Korea","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2014/kor_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
36985,410,"KOR","South Korea","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2014/kor_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
36986,410,"KOR","South Korea","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2014/kor_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
36987,410,"KOR","South Korea","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2014/kor_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
36988,410,"KOR","South Korea","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2014/kor_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
36989,410,"KOR","South Korea","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2015/kor_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
36990,410,"KOR","South Korea","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2015/kor_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
36991,410,"KOR","South Korea","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2015/kor_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
36992,410,"KOR","South Korea","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2015/kor_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
36993,410,"KOR","South Korea","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2015/kor_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
36994,410,"KOR","South Korea","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2015/kor_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
36995,410,"KOR","South Korea","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2015/kor_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
36996,410,"KOR","South Korea","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Annual/2015/kor_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
36997,414,"KWT","Kuwait","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2000/kwt_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
36998,414,"KWT","Kuwait","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2000/kwt_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
36999,414,"KWT","Kuwait","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2000/kwt_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
37000,414,"KWT","Kuwait","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2000/kwt_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
37001,414,"KWT","Kuwait","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2000/kwt_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
37002,414,"KWT","Kuwait","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2000/kwt_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
37003,414,"KWT","Kuwait","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2000/kwt_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
37004,414,"KWT","Kuwait","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2000/kwt_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
37005,414,"KWT","Kuwait","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2001/kwt_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
37006,414,"KWT","Kuwait","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2001/kwt_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
37007,414,"KWT","Kuwait","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2001/kwt_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
37008,414,"KWT","Kuwait","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2001/kwt_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
37009,414,"KWT","Kuwait","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2001/kwt_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
37010,414,"KWT","Kuwait","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2001/kwt_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
37011,414,"KWT","Kuwait","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2001/kwt_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
37012,414,"KWT","Kuwait","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2001/kwt_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
37013,414,"KWT","Kuwait","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2002/kwt_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
37014,414,"KWT","Kuwait","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2002/kwt_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
37015,414,"KWT","Kuwait","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2002/kwt_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
37016,414,"KWT","Kuwait","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2002/kwt_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
37017,414,"KWT","Kuwait","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2002/kwt_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
37018,414,"KWT","Kuwait","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2002/kwt_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
37019,414,"KWT","Kuwait","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2002/kwt_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
37020,414,"KWT","Kuwait","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2002/kwt_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
37021,414,"KWT","Kuwait","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2003/kwt_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
37022,414,"KWT","Kuwait","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2003/kwt_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
37023,414,"KWT","Kuwait","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2003/kwt_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
37024,414,"KWT","Kuwait","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2003/kwt_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
37025,414,"KWT","Kuwait","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2003/kwt_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
37026,414,"KWT","Kuwait","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2003/kwt_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
37027,414,"KWT","Kuwait","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2003/kwt_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
37028,414,"KWT","Kuwait","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2003/kwt_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
37029,414,"KWT","Kuwait","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2004/kwt_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
37030,414,"KWT","Kuwait","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2004/kwt_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
37031,414,"KWT","Kuwait","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2004/kwt_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
37032,414,"KWT","Kuwait","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2004/kwt_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
37033,414,"KWT","Kuwait","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2004/kwt_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
37034,414,"KWT","Kuwait","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2004/kwt_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
37035,414,"KWT","Kuwait","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2004/kwt_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
37036,414,"KWT","Kuwait","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2004/kwt_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
37037,414,"KWT","Kuwait","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2005/kwt_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
37038,414,"KWT","Kuwait","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2005/kwt_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
37039,414,"KWT","Kuwait","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2005/kwt_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
37040,414,"KWT","Kuwait","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2005/kwt_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
37041,414,"KWT","Kuwait","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2005/kwt_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
37042,414,"KWT","Kuwait","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2005/kwt_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
37043,414,"KWT","Kuwait","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2005/kwt_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
37044,414,"KWT","Kuwait","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2005/kwt_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
37045,414,"KWT","Kuwait","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2006/kwt_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
37046,414,"KWT","Kuwait","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2006/kwt_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
37047,414,"KWT","Kuwait","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2006/kwt_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
37048,414,"KWT","Kuwait","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2006/kwt_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
37049,414,"KWT","Kuwait","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2006/kwt_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
37050,414,"KWT","Kuwait","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2006/kwt_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
37051,414,"KWT","Kuwait","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2006/kwt_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
37052,414,"KWT","Kuwait","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2006/kwt_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
37053,414,"KWT","Kuwait","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2007/kwt_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
37054,414,"KWT","Kuwait","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2007/kwt_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
37055,414,"KWT","Kuwait","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2007/kwt_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
37056,414,"KWT","Kuwait","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2007/kwt_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
37057,414,"KWT","Kuwait","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2007/kwt_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
37058,414,"KWT","Kuwait","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2007/kwt_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
37059,414,"KWT","Kuwait","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2007/kwt_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
37060,414,"KWT","Kuwait","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2007/kwt_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
37061,414,"KWT","Kuwait","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2008/kwt_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
37062,414,"KWT","Kuwait","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2008/kwt_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
37063,414,"KWT","Kuwait","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2008/kwt_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
37064,414,"KWT","Kuwait","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2008/kwt_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
37065,414,"KWT","Kuwait","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2008/kwt_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
37066,414,"KWT","Kuwait","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2008/kwt_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
37067,414,"KWT","Kuwait","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2008/kwt_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
37068,414,"KWT","Kuwait","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2008/kwt_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
37069,414,"KWT","Kuwait","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2009/kwt_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
37070,414,"KWT","Kuwait","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2009/kwt_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
37071,414,"KWT","Kuwait","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2009/kwt_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
37072,414,"KWT","Kuwait","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2009/kwt_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
37073,414,"KWT","Kuwait","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2009/kwt_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
37074,414,"KWT","Kuwait","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2009/kwt_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
37075,414,"KWT","Kuwait","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2009/kwt_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
37076,414,"KWT","Kuwait","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2009/kwt_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
37077,414,"KWT","Kuwait","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2010/kwt_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
37078,414,"KWT","Kuwait","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2010/kwt_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
37079,414,"KWT","Kuwait","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2010/kwt_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
37080,414,"KWT","Kuwait","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2010/kwt_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
37081,414,"KWT","Kuwait","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2010/kwt_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
37082,414,"KWT","Kuwait","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2010/kwt_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
37083,414,"KWT","Kuwait","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2010/kwt_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
37084,414,"KWT","Kuwait","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2010/kwt_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
37085,414,"KWT","Kuwait","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2011/kwt_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
37086,414,"KWT","Kuwait","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2011/kwt_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
37087,414,"KWT","Kuwait","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2011/kwt_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
37088,414,"KWT","Kuwait","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2011/kwt_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
37089,414,"KWT","Kuwait","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2011/kwt_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
37090,414,"KWT","Kuwait","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2011/kwt_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
37091,414,"KWT","Kuwait","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2011/kwt_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
37092,414,"KWT","Kuwait","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2011/kwt_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
37093,414,"KWT","Kuwait","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2012/kwt_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
37094,414,"KWT","Kuwait","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2012/kwt_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
37095,414,"KWT","Kuwait","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2012/kwt_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
37096,414,"KWT","Kuwait","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2012/kwt_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
37097,414,"KWT","Kuwait","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2012/kwt_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
37098,414,"KWT","Kuwait","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2012/kwt_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
37099,414,"KWT","Kuwait","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2012/kwt_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
37100,414,"KWT","Kuwait","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2012/kwt_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
37101,414,"KWT","Kuwait","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2013/kwt_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
37102,414,"KWT","Kuwait","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2013/kwt_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
37103,414,"KWT","Kuwait","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2013/kwt_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
37104,414,"KWT","Kuwait","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2013/kwt_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
37105,414,"KWT","Kuwait","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2013/kwt_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
37106,414,"KWT","Kuwait","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2013/kwt_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
37107,414,"KWT","Kuwait","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2013/kwt_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
37108,414,"KWT","Kuwait","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2013/kwt_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
37109,414,"KWT","Kuwait","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2014/kwt_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
37110,414,"KWT","Kuwait","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2014/kwt_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
37111,414,"KWT","Kuwait","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2014/kwt_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
37112,414,"KWT","Kuwait","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2014/kwt_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
37113,414,"KWT","Kuwait","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2014/kwt_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
37114,414,"KWT","Kuwait","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2014/kwt_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
37115,414,"KWT","Kuwait","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2014/kwt_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
37116,414,"KWT","Kuwait","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2014/kwt_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
37117,414,"KWT","Kuwait","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2015/kwt_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
37118,414,"KWT","Kuwait","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2015/kwt_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
37119,414,"KWT","Kuwait","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2015/kwt_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
37120,414,"KWT","Kuwait","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2015/kwt_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
37121,414,"KWT","Kuwait","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2015/kwt_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
37122,414,"KWT","Kuwait","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2015/kwt_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
37123,414,"KWT","Kuwait","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2015/kwt_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
37124,414,"KWT","Kuwait","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Annual/2015/kwt_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
37125,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2000/kgz_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
37126,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2000/kgz_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
37127,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2000/kgz_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
37128,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2000/kgz_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
37129,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2000/kgz_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
37130,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2000/kgz_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
37131,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2000/kgz_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
37132,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2000/kgz_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
37133,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2001/kgz_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
37134,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2001/kgz_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
37135,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2001/kgz_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
37136,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2001/kgz_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
37137,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2001/kgz_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
37138,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2001/kgz_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
37139,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2001/kgz_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
37140,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2001/kgz_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
37141,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2002/kgz_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
37142,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2002/kgz_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
37143,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2002/kgz_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
37144,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2002/kgz_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
37145,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2002/kgz_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
37146,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2002/kgz_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
37147,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2002/kgz_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
37148,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2002/kgz_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
37149,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2003/kgz_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
37150,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2003/kgz_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
37151,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2003/kgz_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
37152,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2003/kgz_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
37153,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2003/kgz_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
37154,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2003/kgz_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
37155,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2003/kgz_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
37156,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2003/kgz_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
37157,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2004/kgz_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
37158,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2004/kgz_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
37159,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2004/kgz_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
37160,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2004/kgz_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
37161,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2004/kgz_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
37162,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2004/kgz_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
37163,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2004/kgz_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
37164,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2004/kgz_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
37165,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2005/kgz_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
37166,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2005/kgz_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
37167,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2005/kgz_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
37168,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2005/kgz_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
37169,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2005/kgz_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
37170,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2005/kgz_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
37171,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2005/kgz_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
37172,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2005/kgz_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
37173,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2006/kgz_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
37174,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2006/kgz_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
37175,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2006/kgz_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
37176,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2006/kgz_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
37177,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2006/kgz_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
37178,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2006/kgz_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
37179,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2006/kgz_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
37180,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2006/kgz_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
37181,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2007/kgz_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
37182,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2007/kgz_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
37183,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2007/kgz_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
37184,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2007/kgz_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
37185,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2007/kgz_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
37186,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2007/kgz_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
37187,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2007/kgz_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
37188,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2007/kgz_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
37189,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2008/kgz_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
37190,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2008/kgz_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
37191,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2008/kgz_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
37192,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2008/kgz_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
37193,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2008/kgz_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
37194,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2008/kgz_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
37195,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2008/kgz_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
37196,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2008/kgz_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
37197,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2009/kgz_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
37198,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2009/kgz_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
37199,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2009/kgz_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
37200,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2009/kgz_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
37201,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2009/kgz_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
37202,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2009/kgz_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
37203,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2009/kgz_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
37204,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2009/kgz_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
37205,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2010/kgz_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
37206,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2010/kgz_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
37207,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2010/kgz_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
37208,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2010/kgz_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
37209,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2010/kgz_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
37210,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2010/kgz_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
37211,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2010/kgz_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
37212,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2010/kgz_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
37213,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2011/kgz_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
37214,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2011/kgz_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
37215,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2011/kgz_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
37216,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2011/kgz_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
37217,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2011/kgz_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
37218,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2011/kgz_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
37219,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2011/kgz_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
37220,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2011/kgz_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
37221,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2012/kgz_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
37222,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2012/kgz_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
37223,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2012/kgz_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
37224,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2012/kgz_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
37225,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2012/kgz_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
37226,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2012/kgz_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
37227,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2012/kgz_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
37228,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2012/kgz_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
37229,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2013/kgz_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
37230,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2013/kgz_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
37231,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2013/kgz_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
37232,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2013/kgz_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
37233,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2013/kgz_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
37234,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2013/kgz_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
37235,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2013/kgz_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
37236,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2013/kgz_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
37237,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2014/kgz_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
37238,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2014/kgz_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
37239,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2014/kgz_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
37240,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2014/kgz_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
37241,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2014/kgz_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
37242,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2014/kgz_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
37243,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2014/kgz_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
37244,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2014/kgz_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
37245,417,"KGZ","Kyrgyzstan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2015/kgz_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
37246,417,"KGZ","Kyrgyzstan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2015/kgz_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
37247,417,"KGZ","Kyrgyzstan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2015/kgz_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
37248,417,"KGZ","Kyrgyzstan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2015/kgz_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
37249,417,"KGZ","Kyrgyzstan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2015/kgz_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
37250,417,"KGZ","Kyrgyzstan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2015/kgz_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
37251,417,"KGZ","Kyrgyzstan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2015/kgz_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
37252,417,"KGZ","Kyrgyzstan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Annual/2015/kgz_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
37253,418,"LAO","Laos","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2000/lao_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
37254,418,"LAO","Laos","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2000/lao_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
37255,418,"LAO","Laos","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2000/lao_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
37256,418,"LAO","Laos","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2000/lao_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
37257,418,"LAO","Laos","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2000/lao_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
37258,418,"LAO","Laos","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2000/lao_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
37259,418,"LAO","Laos","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2000/lao_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
37260,418,"LAO","Laos","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2000/lao_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
37261,418,"LAO","Laos","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2001/lao_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
37262,418,"LAO","Laos","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2001/lao_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
37263,418,"LAO","Laos","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2001/lao_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
37264,418,"LAO","Laos","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2001/lao_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
37265,418,"LAO","Laos","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2001/lao_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
37266,418,"LAO","Laos","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2001/lao_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
37267,418,"LAO","Laos","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2001/lao_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
37268,418,"LAO","Laos","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2001/lao_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
37269,418,"LAO","Laos","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2002/lao_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
37270,418,"LAO","Laos","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2002/lao_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
37271,418,"LAO","Laos","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2002/lao_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
37272,418,"LAO","Laos","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2002/lao_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
37273,418,"LAO","Laos","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2002/lao_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
37274,418,"LAO","Laos","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2002/lao_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
37275,418,"LAO","Laos","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2002/lao_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
37276,418,"LAO","Laos","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2002/lao_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
37277,418,"LAO","Laos","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2003/lao_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
37278,418,"LAO","Laos","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2003/lao_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
37279,418,"LAO","Laos","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2003/lao_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
37280,418,"LAO","Laos","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2003/lao_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
37281,418,"LAO","Laos","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2003/lao_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
37282,418,"LAO","Laos","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2003/lao_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
37283,418,"LAO","Laos","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2003/lao_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
37284,418,"LAO","Laos","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2003/lao_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
37285,418,"LAO","Laos","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2004/lao_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
37286,418,"LAO","Laos","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2004/lao_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
37287,418,"LAO","Laos","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2004/lao_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
37288,418,"LAO","Laos","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2004/lao_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
37289,418,"LAO","Laos","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2004/lao_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
37290,418,"LAO","Laos","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2004/lao_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
37291,418,"LAO","Laos","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2004/lao_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
37292,418,"LAO","Laos","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2004/lao_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
37293,418,"LAO","Laos","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2005/lao_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
37294,418,"LAO","Laos","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2005/lao_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
37295,418,"LAO","Laos","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2005/lao_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
37296,418,"LAO","Laos","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2005/lao_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
37297,418,"LAO","Laos","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2005/lao_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
37298,418,"LAO","Laos","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2005/lao_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
37299,418,"LAO","Laos","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2005/lao_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
37300,418,"LAO","Laos","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2005/lao_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
37301,418,"LAO","Laos","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2006/lao_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
37302,418,"LAO","Laos","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2006/lao_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
37303,418,"LAO","Laos","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2006/lao_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
37304,418,"LAO","Laos","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2006/lao_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
37305,418,"LAO","Laos","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2006/lao_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
37306,418,"LAO","Laos","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2006/lao_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
37307,418,"LAO","Laos","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2006/lao_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
37308,418,"LAO","Laos","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2006/lao_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
37309,418,"LAO","Laos","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2007/lao_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
37310,418,"LAO","Laos","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2007/lao_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
37311,418,"LAO","Laos","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2007/lao_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
37312,418,"LAO","Laos","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2007/lao_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
37313,418,"LAO","Laos","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2007/lao_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
37314,418,"LAO","Laos","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2007/lao_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
37315,418,"LAO","Laos","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2007/lao_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
37316,418,"LAO","Laos","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2007/lao_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
37317,418,"LAO","Laos","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2008/lao_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
37318,418,"LAO","Laos","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2008/lao_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
37319,418,"LAO","Laos","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2008/lao_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
37320,418,"LAO","Laos","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2008/lao_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
37321,418,"LAO","Laos","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2008/lao_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
37322,418,"LAO","Laos","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2008/lao_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
37323,418,"LAO","Laos","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2008/lao_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
37324,418,"LAO","Laos","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2008/lao_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
37325,418,"LAO","Laos","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2009/lao_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
37326,418,"LAO","Laos","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2009/lao_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
37327,418,"LAO","Laos","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2009/lao_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
37328,418,"LAO","Laos","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2009/lao_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
37329,418,"LAO","Laos","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2009/lao_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
37330,418,"LAO","Laos","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2009/lao_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
37331,418,"LAO","Laos","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2009/lao_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
37332,418,"LAO","Laos","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2009/lao_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
37333,418,"LAO","Laos","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2010/lao_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
37334,418,"LAO","Laos","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2010/lao_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
37335,418,"LAO","Laos","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2010/lao_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
37336,418,"LAO","Laos","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2010/lao_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
37337,418,"LAO","Laos","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2010/lao_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
37338,418,"LAO","Laos","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2010/lao_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
37339,418,"LAO","Laos","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2010/lao_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
37340,418,"LAO","Laos","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2010/lao_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
37341,418,"LAO","Laos","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2011/lao_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
37342,418,"LAO","Laos","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2011/lao_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
37343,418,"LAO","Laos","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2011/lao_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
37344,418,"LAO","Laos","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2011/lao_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
37345,418,"LAO","Laos","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2011/lao_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
37346,418,"LAO","Laos","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2011/lao_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
37347,418,"LAO","Laos","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2011/lao_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
37348,418,"LAO","Laos","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2011/lao_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
37349,418,"LAO","Laos","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2012/lao_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
37350,418,"LAO","Laos","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2012/lao_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
37351,418,"LAO","Laos","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2012/lao_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
37352,418,"LAO","Laos","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2012/lao_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
37353,418,"LAO","Laos","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2012/lao_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
37354,418,"LAO","Laos","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2012/lao_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
37355,418,"LAO","Laos","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2012/lao_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
37356,418,"LAO","Laos","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2012/lao_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
37357,418,"LAO","Laos","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2013/lao_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
37358,418,"LAO","Laos","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2013/lao_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
37359,418,"LAO","Laos","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2013/lao_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
37360,418,"LAO","Laos","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2013/lao_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
37361,418,"LAO","Laos","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2013/lao_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
37362,418,"LAO","Laos","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2013/lao_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
37363,418,"LAO","Laos","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2013/lao_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
37364,418,"LAO","Laos","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2013/lao_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
37365,418,"LAO","Laos","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2014/lao_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
37366,418,"LAO","Laos","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2014/lao_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
37367,418,"LAO","Laos","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2014/lao_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
37368,418,"LAO","Laos","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2014/lao_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
37369,418,"LAO","Laos","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2014/lao_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
37370,418,"LAO","Laos","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2014/lao_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
37371,418,"LAO","Laos","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2014/lao_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
37372,418,"LAO","Laos","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2014/lao_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
37373,418,"LAO","Laos","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2015/lao_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
37374,418,"LAO","Laos","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2015/lao_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
37375,418,"LAO","Laos","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2015/lao_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
37376,418,"LAO","Laos","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2015/lao_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
37377,418,"LAO","Laos","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2015/lao_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
37378,418,"LAO","Laos","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2015/lao_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
37379,418,"LAO","Laos","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2015/lao_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
37380,418,"LAO","Laos","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Annual/2015/lao_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
37381,422,"LBN","Lebanon","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2000/lbn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
37382,422,"LBN","Lebanon","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2000/lbn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
37383,422,"LBN","Lebanon","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2000/lbn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
37384,422,"LBN","Lebanon","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2000/lbn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
37385,422,"LBN","Lebanon","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2000/lbn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
37386,422,"LBN","Lebanon","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2000/lbn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
37387,422,"LBN","Lebanon","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2000/lbn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
37388,422,"LBN","Lebanon","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2000/lbn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
37389,422,"LBN","Lebanon","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2001/lbn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
37390,422,"LBN","Lebanon","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2001/lbn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
37391,422,"LBN","Lebanon","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2001/lbn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
37392,422,"LBN","Lebanon","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2001/lbn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
37393,422,"LBN","Lebanon","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2001/lbn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
37394,422,"LBN","Lebanon","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2001/lbn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
37395,422,"LBN","Lebanon","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2001/lbn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
37396,422,"LBN","Lebanon","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2001/lbn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
37397,422,"LBN","Lebanon","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2002/lbn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
37398,422,"LBN","Lebanon","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2002/lbn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
37399,422,"LBN","Lebanon","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2002/lbn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
37400,422,"LBN","Lebanon","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2002/lbn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
37401,422,"LBN","Lebanon","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2002/lbn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
37402,422,"LBN","Lebanon","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2002/lbn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
37403,422,"LBN","Lebanon","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2002/lbn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
37404,422,"LBN","Lebanon","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2002/lbn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
37405,422,"LBN","Lebanon","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2003/lbn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
37406,422,"LBN","Lebanon","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2003/lbn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
37407,422,"LBN","Lebanon","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2003/lbn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
37408,422,"LBN","Lebanon","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2003/lbn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
37409,422,"LBN","Lebanon","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2003/lbn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
37410,422,"LBN","Lebanon","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2003/lbn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
37411,422,"LBN","Lebanon","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2003/lbn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
37412,422,"LBN","Lebanon","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2003/lbn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
37413,422,"LBN","Lebanon","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2004/lbn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
37414,422,"LBN","Lebanon","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2004/lbn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
37415,422,"LBN","Lebanon","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2004/lbn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
37416,422,"LBN","Lebanon","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2004/lbn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
37417,422,"LBN","Lebanon","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2004/lbn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
37418,422,"LBN","Lebanon","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2004/lbn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
37419,422,"LBN","Lebanon","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2004/lbn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
37420,422,"LBN","Lebanon","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2004/lbn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
37421,422,"LBN","Lebanon","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2005/lbn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
37422,422,"LBN","Lebanon","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2005/lbn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
37423,422,"LBN","Lebanon","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2005/lbn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
37424,422,"LBN","Lebanon","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2005/lbn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
37425,422,"LBN","Lebanon","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2005/lbn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
37426,422,"LBN","Lebanon","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2005/lbn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
37427,422,"LBN","Lebanon","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2005/lbn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
37428,422,"LBN","Lebanon","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2005/lbn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
37429,422,"LBN","Lebanon","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2006/lbn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
37430,422,"LBN","Lebanon","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2006/lbn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
37431,422,"LBN","Lebanon","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2006/lbn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
37432,422,"LBN","Lebanon","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2006/lbn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
37433,422,"LBN","Lebanon","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2006/lbn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
37434,422,"LBN","Lebanon","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2006/lbn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
37435,422,"LBN","Lebanon","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2006/lbn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
37436,422,"LBN","Lebanon","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2006/lbn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
37437,422,"LBN","Lebanon","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2007/lbn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
37438,422,"LBN","Lebanon","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2007/lbn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
37439,422,"LBN","Lebanon","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2007/lbn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
37440,422,"LBN","Lebanon","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2007/lbn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
37441,422,"LBN","Lebanon","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2007/lbn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
37442,422,"LBN","Lebanon","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2007/lbn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
37443,422,"LBN","Lebanon","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2007/lbn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
37444,422,"LBN","Lebanon","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2007/lbn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
37445,422,"LBN","Lebanon","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2008/lbn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
37446,422,"LBN","Lebanon","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2008/lbn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
37447,422,"LBN","Lebanon","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2008/lbn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
37448,422,"LBN","Lebanon","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2008/lbn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
37449,422,"LBN","Lebanon","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2008/lbn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
37450,422,"LBN","Lebanon","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2008/lbn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
37451,422,"LBN","Lebanon","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2008/lbn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
37452,422,"LBN","Lebanon","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2008/lbn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
37453,422,"LBN","Lebanon","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2009/lbn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
37454,422,"LBN","Lebanon","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2009/lbn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
37455,422,"LBN","Lebanon","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2009/lbn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
37456,422,"LBN","Lebanon","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2009/lbn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
37457,422,"LBN","Lebanon","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2009/lbn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
37458,422,"LBN","Lebanon","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2009/lbn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
37459,422,"LBN","Lebanon","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2009/lbn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
37460,422,"LBN","Lebanon","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2009/lbn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
37461,422,"LBN","Lebanon","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2010/lbn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
37462,422,"LBN","Lebanon","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2010/lbn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
37463,422,"LBN","Lebanon","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2010/lbn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
37464,422,"LBN","Lebanon","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2010/lbn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
37465,422,"LBN","Lebanon","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2010/lbn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
37466,422,"LBN","Lebanon","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2010/lbn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
37467,422,"LBN","Lebanon","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2010/lbn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
37468,422,"LBN","Lebanon","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2010/lbn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
37469,422,"LBN","Lebanon","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2011/lbn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
37470,422,"LBN","Lebanon","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2011/lbn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
37471,422,"LBN","Lebanon","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2011/lbn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
37472,422,"LBN","Lebanon","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2011/lbn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
37473,422,"LBN","Lebanon","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2011/lbn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
37474,422,"LBN","Lebanon","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2011/lbn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
37475,422,"LBN","Lebanon","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2011/lbn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
37476,422,"LBN","Lebanon","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2011/lbn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
37477,422,"LBN","Lebanon","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2012/lbn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
37478,422,"LBN","Lebanon","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2012/lbn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
37479,422,"LBN","Lebanon","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2012/lbn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
37480,422,"LBN","Lebanon","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2012/lbn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
37481,422,"LBN","Lebanon","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2012/lbn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
37482,422,"LBN","Lebanon","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2012/lbn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
37483,422,"LBN","Lebanon","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2012/lbn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
37484,422,"LBN","Lebanon","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2012/lbn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
37485,422,"LBN","Lebanon","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2013/lbn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
37486,422,"LBN","Lebanon","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2013/lbn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
37487,422,"LBN","Lebanon","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2013/lbn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
37488,422,"LBN","Lebanon","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2013/lbn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
37489,422,"LBN","Lebanon","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2013/lbn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
37490,422,"LBN","Lebanon","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2013/lbn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
37491,422,"LBN","Lebanon","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2013/lbn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
37492,422,"LBN","Lebanon","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2013/lbn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
37493,422,"LBN","Lebanon","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2014/lbn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
37494,422,"LBN","Lebanon","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2014/lbn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
37495,422,"LBN","Lebanon","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2014/lbn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
37496,422,"LBN","Lebanon","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2014/lbn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
37497,422,"LBN","Lebanon","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2014/lbn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
37498,422,"LBN","Lebanon","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2014/lbn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
37499,422,"LBN","Lebanon","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2014/lbn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
37500,422,"LBN","Lebanon","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2014/lbn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
37501,422,"LBN","Lebanon","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2015/lbn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
37502,422,"LBN","Lebanon","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2015/lbn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
37503,422,"LBN","Lebanon","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2015/lbn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
37504,422,"LBN","Lebanon","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2015/lbn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
37505,422,"LBN","Lebanon","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2015/lbn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
37506,422,"LBN","Lebanon","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2015/lbn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
37507,422,"LBN","Lebanon","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2015/lbn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
37508,422,"LBN","Lebanon","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Annual/2015/lbn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
37509,426,"LSO","Lesotho","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2000/lso_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
37510,426,"LSO","Lesotho","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2000/lso_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
37511,426,"LSO","Lesotho","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2000/lso_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
37512,426,"LSO","Lesotho","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2000/lso_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
37513,426,"LSO","Lesotho","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2000/lso_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
37514,426,"LSO","Lesotho","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2000/lso_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
37515,426,"LSO","Lesotho","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2000/lso_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
37516,426,"LSO","Lesotho","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2000/lso_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
37517,426,"LSO","Lesotho","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2001/lso_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
37518,426,"LSO","Lesotho","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2001/lso_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
37519,426,"LSO","Lesotho","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2001/lso_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
37520,426,"LSO","Lesotho","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2001/lso_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
37521,426,"LSO","Lesotho","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2001/lso_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
37522,426,"LSO","Lesotho","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2001/lso_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
37523,426,"LSO","Lesotho","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2001/lso_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
37524,426,"LSO","Lesotho","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2001/lso_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
37525,426,"LSO","Lesotho","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2002/lso_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
37526,426,"LSO","Lesotho","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2002/lso_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
37527,426,"LSO","Lesotho","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2002/lso_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
37528,426,"LSO","Lesotho","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2002/lso_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
37529,426,"LSO","Lesotho","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2002/lso_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
37530,426,"LSO","Lesotho","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2002/lso_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
37531,426,"LSO","Lesotho","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2002/lso_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
37532,426,"LSO","Lesotho","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2002/lso_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
37533,426,"LSO","Lesotho","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2003/lso_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
37534,426,"LSO","Lesotho","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2003/lso_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
37535,426,"LSO","Lesotho","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2003/lso_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
37536,426,"LSO","Lesotho","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2003/lso_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
37537,426,"LSO","Lesotho","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2003/lso_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
37538,426,"LSO","Lesotho","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2003/lso_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
37539,426,"LSO","Lesotho","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2003/lso_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
37540,426,"LSO","Lesotho","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2003/lso_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
37541,426,"LSO","Lesotho","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2004/lso_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
37542,426,"LSO","Lesotho","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2004/lso_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
37543,426,"LSO","Lesotho","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2004/lso_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
37544,426,"LSO","Lesotho","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2004/lso_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
37545,426,"LSO","Lesotho","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2004/lso_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
37546,426,"LSO","Lesotho","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2004/lso_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
37547,426,"LSO","Lesotho","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2004/lso_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
37548,426,"LSO","Lesotho","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2004/lso_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
37549,426,"LSO","Lesotho","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2005/lso_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
37550,426,"LSO","Lesotho","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2005/lso_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
37551,426,"LSO","Lesotho","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2005/lso_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
37552,426,"LSO","Lesotho","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2005/lso_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
37553,426,"LSO","Lesotho","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2005/lso_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
37554,426,"LSO","Lesotho","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2005/lso_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
37555,426,"LSO","Lesotho","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2005/lso_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
37556,426,"LSO","Lesotho","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2005/lso_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
37557,426,"LSO","Lesotho","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2006/lso_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
37558,426,"LSO","Lesotho","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2006/lso_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
37559,426,"LSO","Lesotho","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2006/lso_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
37560,426,"LSO","Lesotho","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2006/lso_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
37561,426,"LSO","Lesotho","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2006/lso_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
37562,426,"LSO","Lesotho","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2006/lso_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
37563,426,"LSO","Lesotho","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2006/lso_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
37564,426,"LSO","Lesotho","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2006/lso_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
37565,426,"LSO","Lesotho","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2007/lso_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
37566,426,"LSO","Lesotho","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2007/lso_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
37567,426,"LSO","Lesotho","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2007/lso_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
37568,426,"LSO","Lesotho","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2007/lso_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
37569,426,"LSO","Lesotho","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2007/lso_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
37570,426,"LSO","Lesotho","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2007/lso_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
37571,426,"LSO","Lesotho","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2007/lso_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
37572,426,"LSO","Lesotho","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2007/lso_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
37573,426,"LSO","Lesotho","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2008/lso_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
37574,426,"LSO","Lesotho","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2008/lso_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
37575,426,"LSO","Lesotho","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2008/lso_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
37576,426,"LSO","Lesotho","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2008/lso_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
37577,426,"LSO","Lesotho","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2008/lso_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
37578,426,"LSO","Lesotho","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2008/lso_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
37579,426,"LSO","Lesotho","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2008/lso_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
37580,426,"LSO","Lesotho","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2008/lso_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
37581,426,"LSO","Lesotho","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2009/lso_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
37582,426,"LSO","Lesotho","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2009/lso_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
37583,426,"LSO","Lesotho","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2009/lso_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
37584,426,"LSO","Lesotho","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2009/lso_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
37585,426,"LSO","Lesotho","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2009/lso_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
37586,426,"LSO","Lesotho","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2009/lso_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
37587,426,"LSO","Lesotho","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2009/lso_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
37588,426,"LSO","Lesotho","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2009/lso_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
37589,426,"LSO","Lesotho","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2010/lso_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
37590,426,"LSO","Lesotho","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2010/lso_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
37591,426,"LSO","Lesotho","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2010/lso_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
37592,426,"LSO","Lesotho","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2010/lso_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
37593,426,"LSO","Lesotho","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2010/lso_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
37594,426,"LSO","Lesotho","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2010/lso_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
37595,426,"LSO","Lesotho","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2010/lso_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
37596,426,"LSO","Lesotho","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2010/lso_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
37597,426,"LSO","Lesotho","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2011/lso_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
37598,426,"LSO","Lesotho","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2011/lso_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
37599,426,"LSO","Lesotho","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2011/lso_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
37600,426,"LSO","Lesotho","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2011/lso_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
37601,426,"LSO","Lesotho","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2011/lso_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
37602,426,"LSO","Lesotho","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2011/lso_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
37603,426,"LSO","Lesotho","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2011/lso_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
37604,426,"LSO","Lesotho","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2011/lso_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
37605,426,"LSO","Lesotho","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2012/lso_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
37606,426,"LSO","Lesotho","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2012/lso_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
37607,426,"LSO","Lesotho","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2012/lso_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
37608,426,"LSO","Lesotho","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2012/lso_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
37609,426,"LSO","Lesotho","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2012/lso_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
37610,426,"LSO","Lesotho","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2012/lso_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
37611,426,"LSO","Lesotho","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2012/lso_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
37612,426,"LSO","Lesotho","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2012/lso_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
37613,426,"LSO","Lesotho","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2013/lso_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
37614,426,"LSO","Lesotho","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2013/lso_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
37615,426,"LSO","Lesotho","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2013/lso_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
37616,426,"LSO","Lesotho","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2013/lso_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
37617,426,"LSO","Lesotho","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2013/lso_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
37618,426,"LSO","Lesotho","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2013/lso_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
37619,426,"LSO","Lesotho","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2013/lso_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
37620,426,"LSO","Lesotho","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2013/lso_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
37621,426,"LSO","Lesotho","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2014/lso_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
37622,426,"LSO","Lesotho","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2014/lso_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
37623,426,"LSO","Lesotho","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2014/lso_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
37624,426,"LSO","Lesotho","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2014/lso_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
37625,426,"LSO","Lesotho","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2014/lso_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
37626,426,"LSO","Lesotho","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2014/lso_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
37627,426,"LSO","Lesotho","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2014/lso_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
37628,426,"LSO","Lesotho","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2014/lso_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
37629,426,"LSO","Lesotho","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2015/lso_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
37630,426,"LSO","Lesotho","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2015/lso_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
37631,426,"LSO","Lesotho","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2015/lso_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
37632,426,"LSO","Lesotho","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2015/lso_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
37633,426,"LSO","Lesotho","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2015/lso_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
37634,426,"LSO","Lesotho","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2015/lso_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
37635,426,"LSO","Lesotho","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2015/lso_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
37636,426,"LSO","Lesotho","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Annual/2015/lso_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
37637,428,"LVA","Latvia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2000/lva_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
37638,428,"LVA","Latvia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2000/lva_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
37639,428,"LVA","Latvia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2000/lva_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
37640,428,"LVA","Latvia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2000/lva_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
37641,428,"LVA","Latvia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2000/lva_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
37642,428,"LVA","Latvia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2000/lva_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
37643,428,"LVA","Latvia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2000/lva_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
37644,428,"LVA","Latvia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2000/lva_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
37645,428,"LVA","Latvia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2001/lva_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
37646,428,"LVA","Latvia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2001/lva_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
37647,428,"LVA","Latvia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2001/lva_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
37648,428,"LVA","Latvia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2001/lva_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
37649,428,"LVA","Latvia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2001/lva_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
37650,428,"LVA","Latvia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2001/lva_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
37651,428,"LVA","Latvia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2001/lva_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
37652,428,"LVA","Latvia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2001/lva_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
37653,428,"LVA","Latvia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2002/lva_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
37654,428,"LVA","Latvia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2002/lva_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
37655,428,"LVA","Latvia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2002/lva_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
37656,428,"LVA","Latvia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2002/lva_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
37657,428,"LVA","Latvia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2002/lva_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
37658,428,"LVA","Latvia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2002/lva_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
37659,428,"LVA","Latvia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2002/lva_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
37660,428,"LVA","Latvia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2002/lva_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
37661,428,"LVA","Latvia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2003/lva_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
37662,428,"LVA","Latvia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2003/lva_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
37663,428,"LVA","Latvia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2003/lva_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
37664,428,"LVA","Latvia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2003/lva_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
37665,428,"LVA","Latvia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2003/lva_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
37666,428,"LVA","Latvia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2003/lva_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
37667,428,"LVA","Latvia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2003/lva_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
37668,428,"LVA","Latvia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2003/lva_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
37669,428,"LVA","Latvia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2004/lva_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
37670,428,"LVA","Latvia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2004/lva_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
37671,428,"LVA","Latvia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2004/lva_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
37672,428,"LVA","Latvia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2004/lva_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
37673,428,"LVA","Latvia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2004/lva_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
37674,428,"LVA","Latvia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2004/lva_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
37675,428,"LVA","Latvia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2004/lva_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
37676,428,"LVA","Latvia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2004/lva_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
37677,428,"LVA","Latvia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2005/lva_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
37678,428,"LVA","Latvia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2005/lva_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
37679,428,"LVA","Latvia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2005/lva_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
37680,428,"LVA","Latvia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2005/lva_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
37681,428,"LVA","Latvia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2005/lva_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
37682,428,"LVA","Latvia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2005/lva_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
37683,428,"LVA","Latvia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2005/lva_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
37684,428,"LVA","Latvia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2005/lva_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
37685,428,"LVA","Latvia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2006/lva_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
37686,428,"LVA","Latvia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2006/lva_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
37687,428,"LVA","Latvia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2006/lva_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
37688,428,"LVA","Latvia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2006/lva_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
37689,428,"LVA","Latvia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2006/lva_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
37690,428,"LVA","Latvia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2006/lva_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
37691,428,"LVA","Latvia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2006/lva_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
37692,428,"LVA","Latvia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2006/lva_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
37693,428,"LVA","Latvia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2007/lva_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
37694,428,"LVA","Latvia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2007/lva_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
37695,428,"LVA","Latvia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2007/lva_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
37696,428,"LVA","Latvia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2007/lva_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
37697,428,"LVA","Latvia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2007/lva_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
37698,428,"LVA","Latvia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2007/lva_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
37699,428,"LVA","Latvia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2007/lva_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
37700,428,"LVA","Latvia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2007/lva_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
37701,428,"LVA","Latvia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2008/lva_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
37702,428,"LVA","Latvia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2008/lva_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
37703,428,"LVA","Latvia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2008/lva_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
37704,428,"LVA","Latvia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2008/lva_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
37705,428,"LVA","Latvia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2008/lva_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
37706,428,"LVA","Latvia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2008/lva_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
37707,428,"LVA","Latvia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2008/lva_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
37708,428,"LVA","Latvia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2008/lva_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
37709,428,"LVA","Latvia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2009/lva_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
37710,428,"LVA","Latvia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2009/lva_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
37711,428,"LVA","Latvia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2009/lva_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
37712,428,"LVA","Latvia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2009/lva_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
37713,428,"LVA","Latvia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2009/lva_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
37714,428,"LVA","Latvia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2009/lva_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
37715,428,"LVA","Latvia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2009/lva_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
37716,428,"LVA","Latvia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2009/lva_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
37717,428,"LVA","Latvia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2010/lva_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
37718,428,"LVA","Latvia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2010/lva_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
37719,428,"LVA","Latvia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2010/lva_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
37720,428,"LVA","Latvia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2010/lva_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
37721,428,"LVA","Latvia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2010/lva_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
37722,428,"LVA","Latvia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2010/lva_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
37723,428,"LVA","Latvia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2010/lva_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
37724,428,"LVA","Latvia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2010/lva_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
37725,428,"LVA","Latvia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2011/lva_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
37726,428,"LVA","Latvia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2011/lva_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
37727,428,"LVA","Latvia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2011/lva_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
37728,428,"LVA","Latvia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2011/lva_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
37729,428,"LVA","Latvia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2011/lva_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
37730,428,"LVA","Latvia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2011/lva_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
37731,428,"LVA","Latvia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2011/lva_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
37732,428,"LVA","Latvia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2011/lva_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
37733,428,"LVA","Latvia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2012/lva_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
37734,428,"LVA","Latvia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2012/lva_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
37735,428,"LVA","Latvia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2012/lva_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
37736,428,"LVA","Latvia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2012/lva_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
37737,428,"LVA","Latvia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2012/lva_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
37738,428,"LVA","Latvia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2012/lva_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
37739,428,"LVA","Latvia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2012/lva_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
37740,428,"LVA","Latvia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2012/lva_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
37741,428,"LVA","Latvia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2013/lva_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
37742,428,"LVA","Latvia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2013/lva_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
37743,428,"LVA","Latvia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2013/lva_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
37744,428,"LVA","Latvia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2013/lva_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
37745,428,"LVA","Latvia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2013/lva_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
37746,428,"LVA","Latvia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2013/lva_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
37747,428,"LVA","Latvia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2013/lva_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
37748,428,"LVA","Latvia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2013/lva_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
37749,428,"LVA","Latvia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2014/lva_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
37750,428,"LVA","Latvia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2014/lva_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
37751,428,"LVA","Latvia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2014/lva_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
37752,428,"LVA","Latvia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2014/lva_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
37753,428,"LVA","Latvia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2014/lva_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
37754,428,"LVA","Latvia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2014/lva_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
37755,428,"LVA","Latvia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2014/lva_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
37756,428,"LVA","Latvia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2014/lva_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
37757,428,"LVA","Latvia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2015/lva_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
37758,428,"LVA","Latvia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2015/lva_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
37759,428,"LVA","Latvia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2015/lva_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
37760,428,"LVA","Latvia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2015/lva_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
37761,428,"LVA","Latvia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2015/lva_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
37762,428,"LVA","Latvia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2015/lva_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
37763,428,"LVA","Latvia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2015/lva_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
37764,428,"LVA","Latvia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Annual/2015/lva_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
37765,430,"LBR","Liberia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2000/lbr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
37766,430,"LBR","Liberia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2000/lbr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
37767,430,"LBR","Liberia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2000/lbr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
37768,430,"LBR","Liberia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2000/lbr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
37769,430,"LBR","Liberia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2000/lbr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
37770,430,"LBR","Liberia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2000/lbr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
37771,430,"LBR","Liberia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2000/lbr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
37772,430,"LBR","Liberia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2000/lbr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
37773,430,"LBR","Liberia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2001/lbr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
37774,430,"LBR","Liberia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2001/lbr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
37775,430,"LBR","Liberia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2001/lbr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
37776,430,"LBR","Liberia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2001/lbr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
37777,430,"LBR","Liberia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2001/lbr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
37778,430,"LBR","Liberia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2001/lbr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
37779,430,"LBR","Liberia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2001/lbr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
37780,430,"LBR","Liberia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2001/lbr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
37781,430,"LBR","Liberia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2002/lbr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
37782,430,"LBR","Liberia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2002/lbr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
37783,430,"LBR","Liberia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2002/lbr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
37784,430,"LBR","Liberia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2002/lbr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
37785,430,"LBR","Liberia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2002/lbr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
37786,430,"LBR","Liberia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2002/lbr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
37787,430,"LBR","Liberia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2002/lbr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
37788,430,"LBR","Liberia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2002/lbr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
37789,430,"LBR","Liberia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2003/lbr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
37790,430,"LBR","Liberia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2003/lbr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
37791,430,"LBR","Liberia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2003/lbr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
37792,430,"LBR","Liberia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2003/lbr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
37793,430,"LBR","Liberia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2003/lbr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
37794,430,"LBR","Liberia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2003/lbr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
37795,430,"LBR","Liberia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2003/lbr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
37796,430,"LBR","Liberia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2003/lbr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
37797,430,"LBR","Liberia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2004/lbr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
37798,430,"LBR","Liberia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2004/lbr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
37799,430,"LBR","Liberia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2004/lbr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
37800,430,"LBR","Liberia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2004/lbr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
37801,430,"LBR","Liberia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2004/lbr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
37802,430,"LBR","Liberia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2004/lbr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
37803,430,"LBR","Liberia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2004/lbr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
37804,430,"LBR","Liberia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2004/lbr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
37805,430,"LBR","Liberia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2005/lbr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
37806,430,"LBR","Liberia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2005/lbr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
37807,430,"LBR","Liberia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2005/lbr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
37808,430,"LBR","Liberia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2005/lbr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
37809,430,"LBR","Liberia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2005/lbr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
37810,430,"LBR","Liberia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2005/lbr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
37811,430,"LBR","Liberia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2005/lbr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
37812,430,"LBR","Liberia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2005/lbr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
37813,430,"LBR","Liberia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2006/lbr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
37814,430,"LBR","Liberia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2006/lbr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
37815,430,"LBR","Liberia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2006/lbr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
37816,430,"LBR","Liberia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2006/lbr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
37817,430,"LBR","Liberia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2006/lbr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
37818,430,"LBR","Liberia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2006/lbr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
37819,430,"LBR","Liberia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2006/lbr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
37820,430,"LBR","Liberia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2006/lbr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
37821,430,"LBR","Liberia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2007/lbr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
37822,430,"LBR","Liberia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2007/lbr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
37823,430,"LBR","Liberia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2007/lbr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
37824,430,"LBR","Liberia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2007/lbr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
37825,430,"LBR","Liberia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2007/lbr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
37826,430,"LBR","Liberia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2007/lbr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
37827,430,"LBR","Liberia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2007/lbr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
37828,430,"LBR","Liberia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2007/lbr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
37829,430,"LBR","Liberia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2008/lbr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
37830,430,"LBR","Liberia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2008/lbr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
37831,430,"LBR","Liberia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2008/lbr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
37832,430,"LBR","Liberia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2008/lbr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
37833,430,"LBR","Liberia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2008/lbr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
37834,430,"LBR","Liberia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2008/lbr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
37835,430,"LBR","Liberia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2008/lbr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
37836,430,"LBR","Liberia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2008/lbr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
37837,430,"LBR","Liberia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2009/lbr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
37838,430,"LBR","Liberia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2009/lbr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
37839,430,"LBR","Liberia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2009/lbr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
37840,430,"LBR","Liberia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2009/lbr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
37841,430,"LBR","Liberia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2009/lbr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
37842,430,"LBR","Liberia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2009/lbr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
37843,430,"LBR","Liberia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2009/lbr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
37844,430,"LBR","Liberia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2009/lbr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
37845,430,"LBR","Liberia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2010/lbr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
37846,430,"LBR","Liberia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2010/lbr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
37847,430,"LBR","Liberia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2010/lbr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
37848,430,"LBR","Liberia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2010/lbr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
37849,430,"LBR","Liberia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2010/lbr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
37850,430,"LBR","Liberia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2010/lbr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
37851,430,"LBR","Liberia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2010/lbr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
37852,430,"LBR","Liberia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2010/lbr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
37853,430,"LBR","Liberia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2011/lbr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
37854,430,"LBR","Liberia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2011/lbr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
37855,430,"LBR","Liberia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2011/lbr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
37856,430,"LBR","Liberia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2011/lbr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
37857,430,"LBR","Liberia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2011/lbr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
37858,430,"LBR","Liberia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2011/lbr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
37859,430,"LBR","Liberia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2011/lbr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
37860,430,"LBR","Liberia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2011/lbr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
37861,430,"LBR","Liberia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2012/lbr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
37862,430,"LBR","Liberia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2012/lbr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
37863,430,"LBR","Liberia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2012/lbr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
37864,430,"LBR","Liberia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2012/lbr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
37865,430,"LBR","Liberia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2012/lbr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
37866,430,"LBR","Liberia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2012/lbr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
37867,430,"LBR","Liberia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2012/lbr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
37868,430,"LBR","Liberia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2012/lbr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
37869,430,"LBR","Liberia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2013/lbr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
37870,430,"LBR","Liberia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2013/lbr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
37871,430,"LBR","Liberia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2013/lbr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
37872,430,"LBR","Liberia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2013/lbr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
37873,430,"LBR","Liberia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2013/lbr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
37874,430,"LBR","Liberia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2013/lbr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
37875,430,"LBR","Liberia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2013/lbr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
37876,430,"LBR","Liberia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2013/lbr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
37877,430,"LBR","Liberia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2014/lbr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
37878,430,"LBR","Liberia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2014/lbr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
37879,430,"LBR","Liberia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2014/lbr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
37880,430,"LBR","Liberia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2014/lbr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
37881,430,"LBR","Liberia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2014/lbr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
37882,430,"LBR","Liberia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2014/lbr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
37883,430,"LBR","Liberia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2014/lbr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
37884,430,"LBR","Liberia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2014/lbr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
37885,430,"LBR","Liberia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2015/lbr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
37886,430,"LBR","Liberia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2015/lbr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
37887,430,"LBR","Liberia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2015/lbr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
37888,430,"LBR","Liberia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2015/lbr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
37889,430,"LBR","Liberia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2015/lbr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
37890,430,"LBR","Liberia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2015/lbr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
37891,430,"LBR","Liberia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2015/lbr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
37892,430,"LBR","Liberia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Annual/2015/lbr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
37893,434,"LBY","Libya","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2000/lby_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
37894,434,"LBY","Libya","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2000/lby_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
37895,434,"LBY","Libya","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2000/lby_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
37896,434,"LBY","Libya","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2000/lby_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
37897,434,"LBY","Libya","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2000/lby_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
37898,434,"LBY","Libya","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2000/lby_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
37899,434,"LBY","Libya","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2000/lby_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
37900,434,"LBY","Libya","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2000/lby_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
37901,434,"LBY","Libya","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2001/lby_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
37902,434,"LBY","Libya","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2001/lby_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
37903,434,"LBY","Libya","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2001/lby_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
37904,434,"LBY","Libya","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2001/lby_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
37905,434,"LBY","Libya","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2001/lby_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
37906,434,"LBY","Libya","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2001/lby_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
37907,434,"LBY","Libya","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2001/lby_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
37908,434,"LBY","Libya","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2001/lby_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
37909,434,"LBY","Libya","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2002/lby_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
37910,434,"LBY","Libya","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2002/lby_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
37911,434,"LBY","Libya","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2002/lby_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
37912,434,"LBY","Libya","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2002/lby_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
37913,434,"LBY","Libya","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2002/lby_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
37914,434,"LBY","Libya","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2002/lby_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
37915,434,"LBY","Libya","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2002/lby_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
37916,434,"LBY","Libya","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2002/lby_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
37917,434,"LBY","Libya","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2003/lby_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
37918,434,"LBY","Libya","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2003/lby_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
37919,434,"LBY","Libya","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2003/lby_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
37920,434,"LBY","Libya","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2003/lby_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
37921,434,"LBY","Libya","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2003/lby_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
37922,434,"LBY","Libya","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2003/lby_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
37923,434,"LBY","Libya","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2003/lby_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
37924,434,"LBY","Libya","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2003/lby_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
37925,434,"LBY","Libya","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2004/lby_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
37926,434,"LBY","Libya","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2004/lby_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
37927,434,"LBY","Libya","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2004/lby_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
37928,434,"LBY","Libya","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2004/lby_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
37929,434,"LBY","Libya","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2004/lby_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
37930,434,"LBY","Libya","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2004/lby_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
37931,434,"LBY","Libya","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2004/lby_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
37932,434,"LBY","Libya","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2004/lby_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
37933,434,"LBY","Libya","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2005/lby_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
37934,434,"LBY","Libya","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2005/lby_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
37935,434,"LBY","Libya","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2005/lby_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
37936,434,"LBY","Libya","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2005/lby_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
37937,434,"LBY","Libya","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2005/lby_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
37938,434,"LBY","Libya","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2005/lby_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
37939,434,"LBY","Libya","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2005/lby_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
37940,434,"LBY","Libya","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2005/lby_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
37941,434,"LBY","Libya","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2006/lby_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
37942,434,"LBY","Libya","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2006/lby_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
37943,434,"LBY","Libya","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2006/lby_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
37944,434,"LBY","Libya","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2006/lby_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
37945,434,"LBY","Libya","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2006/lby_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
37946,434,"LBY","Libya","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2006/lby_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
37947,434,"LBY","Libya","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2006/lby_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
37948,434,"LBY","Libya","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2006/lby_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
37949,434,"LBY","Libya","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2007/lby_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
37950,434,"LBY","Libya","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2007/lby_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
37951,434,"LBY","Libya","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2007/lby_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
37952,434,"LBY","Libya","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2007/lby_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
37953,434,"LBY","Libya","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2007/lby_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
37954,434,"LBY","Libya","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2007/lby_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
37955,434,"LBY","Libya","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2007/lby_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
37956,434,"LBY","Libya","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2007/lby_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
37957,434,"LBY","Libya","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2008/lby_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
37958,434,"LBY","Libya","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2008/lby_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
37959,434,"LBY","Libya","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2008/lby_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
37960,434,"LBY","Libya","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2008/lby_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
37961,434,"LBY","Libya","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2008/lby_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
37962,434,"LBY","Libya","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2008/lby_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
37963,434,"LBY","Libya","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2008/lby_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
37964,434,"LBY","Libya","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2008/lby_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
37965,434,"LBY","Libya","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2009/lby_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
37966,434,"LBY","Libya","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2009/lby_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
37967,434,"LBY","Libya","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2009/lby_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
37968,434,"LBY","Libya","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2009/lby_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
37969,434,"LBY","Libya","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2009/lby_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
37970,434,"LBY","Libya","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2009/lby_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
37971,434,"LBY","Libya","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2009/lby_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
37972,434,"LBY","Libya","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2009/lby_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
37973,434,"LBY","Libya","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2010/lby_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
37974,434,"LBY","Libya","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2010/lby_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
37975,434,"LBY","Libya","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2010/lby_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
37976,434,"LBY","Libya","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2010/lby_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
37977,434,"LBY","Libya","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2010/lby_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
37978,434,"LBY","Libya","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2010/lby_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
37979,434,"LBY","Libya","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2010/lby_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
37980,434,"LBY","Libya","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2010/lby_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
37981,434,"LBY","Libya","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2011/lby_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
37982,434,"LBY","Libya","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2011/lby_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
37983,434,"LBY","Libya","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2011/lby_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
37984,434,"LBY","Libya","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2011/lby_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
37985,434,"LBY","Libya","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2011/lby_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
37986,434,"LBY","Libya","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2011/lby_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
37987,434,"LBY","Libya","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2011/lby_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
37988,434,"LBY","Libya","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2011/lby_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
37989,434,"LBY","Libya","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2012/lby_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
37990,434,"LBY","Libya","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2012/lby_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
37991,434,"LBY","Libya","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2012/lby_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
37992,434,"LBY","Libya","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2012/lby_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
37993,434,"LBY","Libya","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2012/lby_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
37994,434,"LBY","Libya","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2012/lby_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
37995,434,"LBY","Libya","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2012/lby_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
37996,434,"LBY","Libya","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2012/lby_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
37997,434,"LBY","Libya","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2013/lby_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
37998,434,"LBY","Libya","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2013/lby_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
37999,434,"LBY","Libya","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2013/lby_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
38000,434,"LBY","Libya","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2013/lby_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
38001,434,"LBY","Libya","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2013/lby_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
38002,434,"LBY","Libya","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2013/lby_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
38003,434,"LBY","Libya","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2013/lby_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
38004,434,"LBY","Libya","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2013/lby_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
38005,434,"LBY","Libya","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2014/lby_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
38006,434,"LBY","Libya","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2014/lby_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
38007,434,"LBY","Libya","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2014/lby_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
38008,434,"LBY","Libya","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2014/lby_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
38009,434,"LBY","Libya","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2014/lby_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
38010,434,"LBY","Libya","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2014/lby_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
38011,434,"LBY","Libya","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2014/lby_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
38012,434,"LBY","Libya","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2014/lby_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
38013,434,"LBY","Libya","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2015/lby_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
38014,434,"LBY","Libya","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2015/lby_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
38015,434,"LBY","Libya","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2015/lby_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
38016,434,"LBY","Libya","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2015/lby_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
38017,434,"LBY","Libya","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2015/lby_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
38018,434,"LBY","Libya","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2015/lby_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
38019,434,"LBY","Libya","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2015/lby_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
38020,434,"LBY","Libya","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Annual/2015/lby_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
38021,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2000/lie_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
38022,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2000/lie_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
38023,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2000/lie_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
38024,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2000/lie_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
38025,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2000/lie_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
38026,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2000/lie_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
38027,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2000/lie_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
38028,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2000/lie_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
38029,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2001/lie_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
38030,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2001/lie_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
38031,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2001/lie_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
38032,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2001/lie_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
38033,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2001/lie_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
38034,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2001/lie_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
38035,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2001/lie_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
38036,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2001/lie_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
38037,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2002/lie_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
38038,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2002/lie_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
38039,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2002/lie_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
38040,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2002/lie_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
38041,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2002/lie_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
38042,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2002/lie_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
38043,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2002/lie_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
38044,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2002/lie_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
38045,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2003/lie_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
38046,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2003/lie_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
38047,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2003/lie_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
38048,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2003/lie_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
38049,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2003/lie_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
38050,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2003/lie_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
38051,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2003/lie_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
38052,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2003/lie_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
38053,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2004/lie_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
38054,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2004/lie_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
38055,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2004/lie_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
38056,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2004/lie_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
38057,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2004/lie_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
38058,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2004/lie_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
38059,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2004/lie_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
38060,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2004/lie_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
38061,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2005/lie_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
38062,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2005/lie_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
38063,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2005/lie_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
38064,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2005/lie_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
38065,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2005/lie_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
38066,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2005/lie_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
38067,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2005/lie_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
38068,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2005/lie_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
38069,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2006/lie_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
38070,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2006/lie_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
38071,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2006/lie_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
38072,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2006/lie_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
38073,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2006/lie_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
38074,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2006/lie_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
38075,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2006/lie_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
38076,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2006/lie_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
38077,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2007/lie_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
38078,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2007/lie_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
38079,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2007/lie_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
38080,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2007/lie_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
38081,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2007/lie_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
38082,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2007/lie_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
38083,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2007/lie_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
38084,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2007/lie_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
38085,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2008/lie_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
38086,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2008/lie_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
38087,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2008/lie_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
38088,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2008/lie_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
38089,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2008/lie_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
38090,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2008/lie_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
38091,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2008/lie_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
38092,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2008/lie_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
38093,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2009/lie_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
38094,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2009/lie_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
38095,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2009/lie_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
38096,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2009/lie_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
38097,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2009/lie_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
38098,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2009/lie_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
38099,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2009/lie_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
38100,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2009/lie_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
38101,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2010/lie_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
38102,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2010/lie_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
38103,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2010/lie_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
38104,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2010/lie_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
38105,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2010/lie_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
38106,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2010/lie_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
38107,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2010/lie_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
38108,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2010/lie_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
38109,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2011/lie_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
38110,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2011/lie_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
38111,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2011/lie_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
38112,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2011/lie_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
38113,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2011/lie_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
38114,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2011/lie_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
38115,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2011/lie_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
38116,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2011/lie_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
38117,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2012/lie_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
38118,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2012/lie_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
38119,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2012/lie_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
38120,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2012/lie_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
38121,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2012/lie_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
38122,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2012/lie_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
38123,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2012/lie_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
38124,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2012/lie_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
38125,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2013/lie_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
38126,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2013/lie_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
38127,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2013/lie_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
38128,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2013/lie_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
38129,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2013/lie_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
38130,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2013/lie_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
38131,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2013/lie_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
38132,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2013/lie_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
38133,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2014/lie_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
38134,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2014/lie_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
38135,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2014/lie_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
38136,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2014/lie_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
38137,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2014/lie_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
38138,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2014/lie_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
38139,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2014/lie_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
38140,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2014/lie_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
38141,438,"LIE","Liechtenstein","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2015/lie_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
38142,438,"LIE","Liechtenstein","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2015/lie_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
38143,438,"LIE","Liechtenstein","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2015/lie_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
38144,438,"LIE","Liechtenstein","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2015/lie_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
38145,438,"LIE","Liechtenstein","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2015/lie_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
38146,438,"LIE","Liechtenstein","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2015/lie_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
38147,438,"LIE","Liechtenstein","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2015/lie_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
38148,438,"LIE","Liechtenstein","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Annual/2015/lie_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
38149,440,"LTU","Lithuania","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2000/ltu_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
38150,440,"LTU","Lithuania","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2000/ltu_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
38151,440,"LTU","Lithuania","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2000/ltu_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
38152,440,"LTU","Lithuania","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2000/ltu_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
38153,440,"LTU","Lithuania","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2000/ltu_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
38154,440,"LTU","Lithuania","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2000/ltu_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
38155,440,"LTU","Lithuania","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2000/ltu_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
38156,440,"LTU","Lithuania","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2000/ltu_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
38157,440,"LTU","Lithuania","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2001/ltu_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
38158,440,"LTU","Lithuania","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2001/ltu_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
38159,440,"LTU","Lithuania","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2001/ltu_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
38160,440,"LTU","Lithuania","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2001/ltu_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
38161,440,"LTU","Lithuania","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2001/ltu_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
38162,440,"LTU","Lithuania","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2001/ltu_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
38163,440,"LTU","Lithuania","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2001/ltu_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
38164,440,"LTU","Lithuania","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2001/ltu_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
38165,440,"LTU","Lithuania","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2002/ltu_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
38166,440,"LTU","Lithuania","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2002/ltu_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
38167,440,"LTU","Lithuania","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2002/ltu_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
38168,440,"LTU","Lithuania","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2002/ltu_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
38169,440,"LTU","Lithuania","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2002/ltu_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
38170,440,"LTU","Lithuania","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2002/ltu_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
38171,440,"LTU","Lithuania","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2002/ltu_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
38172,440,"LTU","Lithuania","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2002/ltu_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
38173,440,"LTU","Lithuania","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2003/ltu_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
38174,440,"LTU","Lithuania","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2003/ltu_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
38175,440,"LTU","Lithuania","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2003/ltu_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
38176,440,"LTU","Lithuania","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2003/ltu_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
38177,440,"LTU","Lithuania","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2003/ltu_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
38178,440,"LTU","Lithuania","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2003/ltu_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
38179,440,"LTU","Lithuania","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2003/ltu_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
38180,440,"LTU","Lithuania","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2003/ltu_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
38181,440,"LTU","Lithuania","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2004/ltu_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
38182,440,"LTU","Lithuania","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2004/ltu_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
38183,440,"LTU","Lithuania","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2004/ltu_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
38184,440,"LTU","Lithuania","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2004/ltu_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
38185,440,"LTU","Lithuania","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2004/ltu_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
38186,440,"LTU","Lithuania","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2004/ltu_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
38187,440,"LTU","Lithuania","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2004/ltu_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
38188,440,"LTU","Lithuania","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2004/ltu_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
38189,440,"LTU","Lithuania","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2005/ltu_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
38190,440,"LTU","Lithuania","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2005/ltu_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
38191,440,"LTU","Lithuania","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2005/ltu_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
38192,440,"LTU","Lithuania","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2005/ltu_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
38193,440,"LTU","Lithuania","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2005/ltu_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
38194,440,"LTU","Lithuania","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2005/ltu_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
38195,440,"LTU","Lithuania","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2005/ltu_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
38196,440,"LTU","Lithuania","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2005/ltu_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
38197,440,"LTU","Lithuania","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2006/ltu_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
38198,440,"LTU","Lithuania","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2006/ltu_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
38199,440,"LTU","Lithuania","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2006/ltu_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
38200,440,"LTU","Lithuania","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2006/ltu_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
38201,440,"LTU","Lithuania","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2006/ltu_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
38202,440,"LTU","Lithuania","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2006/ltu_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
38203,440,"LTU","Lithuania","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2006/ltu_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
38204,440,"LTU","Lithuania","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2006/ltu_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
38205,440,"LTU","Lithuania","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2007/ltu_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
38206,440,"LTU","Lithuania","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2007/ltu_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
38207,440,"LTU","Lithuania","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2007/ltu_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
38208,440,"LTU","Lithuania","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2007/ltu_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
38209,440,"LTU","Lithuania","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2007/ltu_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
38210,440,"LTU","Lithuania","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2007/ltu_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
38211,440,"LTU","Lithuania","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2007/ltu_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
38212,440,"LTU","Lithuania","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2007/ltu_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
38213,440,"LTU","Lithuania","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2008/ltu_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
38214,440,"LTU","Lithuania","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2008/ltu_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
38215,440,"LTU","Lithuania","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2008/ltu_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
38216,440,"LTU","Lithuania","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2008/ltu_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
38217,440,"LTU","Lithuania","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2008/ltu_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
38218,440,"LTU","Lithuania","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2008/ltu_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
38219,440,"LTU","Lithuania","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2008/ltu_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
38220,440,"LTU","Lithuania","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2008/ltu_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
38221,440,"LTU","Lithuania","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2009/ltu_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
38222,440,"LTU","Lithuania","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2009/ltu_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
38223,440,"LTU","Lithuania","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2009/ltu_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
38224,440,"LTU","Lithuania","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2009/ltu_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
38225,440,"LTU","Lithuania","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2009/ltu_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
38226,440,"LTU","Lithuania","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2009/ltu_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
38227,440,"LTU","Lithuania","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2009/ltu_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
38228,440,"LTU","Lithuania","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2009/ltu_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
38229,440,"LTU","Lithuania","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2010/ltu_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
38230,440,"LTU","Lithuania","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2010/ltu_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
38231,440,"LTU","Lithuania","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2010/ltu_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
38232,440,"LTU","Lithuania","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2010/ltu_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
38233,440,"LTU","Lithuania","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2010/ltu_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
38234,440,"LTU","Lithuania","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2010/ltu_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
38235,440,"LTU","Lithuania","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2010/ltu_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
38236,440,"LTU","Lithuania","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2010/ltu_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
38237,440,"LTU","Lithuania","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2011/ltu_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
38238,440,"LTU","Lithuania","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2011/ltu_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
38239,440,"LTU","Lithuania","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2011/ltu_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
38240,440,"LTU","Lithuania","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2011/ltu_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
38241,440,"LTU","Lithuania","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2011/ltu_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
38242,440,"LTU","Lithuania","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2011/ltu_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
38243,440,"LTU","Lithuania","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2011/ltu_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
38244,440,"LTU","Lithuania","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2011/ltu_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
38245,440,"LTU","Lithuania","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2012/ltu_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
38246,440,"LTU","Lithuania","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2012/ltu_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
38247,440,"LTU","Lithuania","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2012/ltu_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
38248,440,"LTU","Lithuania","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2012/ltu_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
38249,440,"LTU","Lithuania","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2012/ltu_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
38250,440,"LTU","Lithuania","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2012/ltu_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
38251,440,"LTU","Lithuania","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2012/ltu_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
38252,440,"LTU","Lithuania","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2012/ltu_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
38253,440,"LTU","Lithuania","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2013/ltu_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
38254,440,"LTU","Lithuania","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2013/ltu_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
38255,440,"LTU","Lithuania","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2013/ltu_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
38256,440,"LTU","Lithuania","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2013/ltu_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
38257,440,"LTU","Lithuania","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2013/ltu_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
38258,440,"LTU","Lithuania","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2013/ltu_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
38259,440,"LTU","Lithuania","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2013/ltu_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
38260,440,"LTU","Lithuania","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2013/ltu_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
38261,440,"LTU","Lithuania","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2014/ltu_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
38262,440,"LTU","Lithuania","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2014/ltu_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
38263,440,"LTU","Lithuania","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2014/ltu_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
38264,440,"LTU","Lithuania","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2014/ltu_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
38265,440,"LTU","Lithuania","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2014/ltu_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
38266,440,"LTU","Lithuania","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2014/ltu_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
38267,440,"LTU","Lithuania","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2014/ltu_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
38268,440,"LTU","Lithuania","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2014/ltu_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
38269,440,"LTU","Lithuania","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2015/ltu_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
38270,440,"LTU","Lithuania","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2015/ltu_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
38271,440,"LTU","Lithuania","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2015/ltu_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
38272,440,"LTU","Lithuania","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2015/ltu_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
38273,440,"LTU","Lithuania","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2015/ltu_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
38274,440,"LTU","Lithuania","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2015/ltu_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
38275,440,"LTU","Lithuania","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2015/ltu_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
38276,440,"LTU","Lithuania","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Annual/2015/ltu_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
38277,442,"LUX","Luxembourg","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2000/lux_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
38278,442,"LUX","Luxembourg","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2000/lux_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
38279,442,"LUX","Luxembourg","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2000/lux_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
38280,442,"LUX","Luxembourg","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2000/lux_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
38281,442,"LUX","Luxembourg","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2000/lux_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
38282,442,"LUX","Luxembourg","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2000/lux_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
38283,442,"LUX","Luxembourg","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2000/lux_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
38284,442,"LUX","Luxembourg","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2000/lux_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
38285,442,"LUX","Luxembourg","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2001/lux_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
38286,442,"LUX","Luxembourg","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2001/lux_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
38287,442,"LUX","Luxembourg","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2001/lux_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
38288,442,"LUX","Luxembourg","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2001/lux_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
38289,442,"LUX","Luxembourg","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2001/lux_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
38290,442,"LUX","Luxembourg","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2001/lux_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
38291,442,"LUX","Luxembourg","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2001/lux_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
38292,442,"LUX","Luxembourg","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2001/lux_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
38293,442,"LUX","Luxembourg","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2002/lux_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
38294,442,"LUX","Luxembourg","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2002/lux_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
38295,442,"LUX","Luxembourg","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2002/lux_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
38296,442,"LUX","Luxembourg","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2002/lux_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
38297,442,"LUX","Luxembourg","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2002/lux_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
38298,442,"LUX","Luxembourg","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2002/lux_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
38299,442,"LUX","Luxembourg","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2002/lux_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
38300,442,"LUX","Luxembourg","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2002/lux_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
38301,442,"LUX","Luxembourg","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2003/lux_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
38302,442,"LUX","Luxembourg","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2003/lux_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
38303,442,"LUX","Luxembourg","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2003/lux_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
38304,442,"LUX","Luxembourg","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2003/lux_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
38305,442,"LUX","Luxembourg","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2003/lux_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
38306,442,"LUX","Luxembourg","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2003/lux_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
38307,442,"LUX","Luxembourg","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2003/lux_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
38308,442,"LUX","Luxembourg","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2003/lux_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
38309,442,"LUX","Luxembourg","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2004/lux_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
38310,442,"LUX","Luxembourg","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2004/lux_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
38311,442,"LUX","Luxembourg","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2004/lux_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
38312,442,"LUX","Luxembourg","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2004/lux_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
38313,442,"LUX","Luxembourg","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2004/lux_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
38314,442,"LUX","Luxembourg","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2004/lux_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
38315,442,"LUX","Luxembourg","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2004/lux_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
38316,442,"LUX","Luxembourg","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2004/lux_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
38317,442,"LUX","Luxembourg","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2005/lux_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
38318,442,"LUX","Luxembourg","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2005/lux_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
38319,442,"LUX","Luxembourg","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2005/lux_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
38320,442,"LUX","Luxembourg","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2005/lux_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
38321,442,"LUX","Luxembourg","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2005/lux_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
38322,442,"LUX","Luxembourg","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2005/lux_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
38323,442,"LUX","Luxembourg","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2005/lux_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
38324,442,"LUX","Luxembourg","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2005/lux_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
38325,442,"LUX","Luxembourg","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2006/lux_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
38326,442,"LUX","Luxembourg","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2006/lux_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
38327,442,"LUX","Luxembourg","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2006/lux_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
38328,442,"LUX","Luxembourg","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2006/lux_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
38329,442,"LUX","Luxembourg","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2006/lux_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
38330,442,"LUX","Luxembourg","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2006/lux_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
38331,442,"LUX","Luxembourg","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2006/lux_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
38332,442,"LUX","Luxembourg","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2006/lux_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
38333,442,"LUX","Luxembourg","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2007/lux_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
38334,442,"LUX","Luxembourg","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2007/lux_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
38335,442,"LUX","Luxembourg","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2007/lux_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
38336,442,"LUX","Luxembourg","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2007/lux_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
38337,442,"LUX","Luxembourg","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2007/lux_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
38338,442,"LUX","Luxembourg","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2007/lux_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
38339,442,"LUX","Luxembourg","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2007/lux_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
38340,442,"LUX","Luxembourg","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2007/lux_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
38341,442,"LUX","Luxembourg","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2008/lux_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
38342,442,"LUX","Luxembourg","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2008/lux_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
38343,442,"LUX","Luxembourg","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2008/lux_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
38344,442,"LUX","Luxembourg","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2008/lux_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
38345,442,"LUX","Luxembourg","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2008/lux_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
38346,442,"LUX","Luxembourg","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2008/lux_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
38347,442,"LUX","Luxembourg","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2008/lux_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
38348,442,"LUX","Luxembourg","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2008/lux_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
38349,442,"LUX","Luxembourg","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2009/lux_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
38350,442,"LUX","Luxembourg","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2009/lux_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
38351,442,"LUX","Luxembourg","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2009/lux_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
38352,442,"LUX","Luxembourg","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2009/lux_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
38353,442,"LUX","Luxembourg","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2009/lux_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
38354,442,"LUX","Luxembourg","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2009/lux_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
38355,442,"LUX","Luxembourg","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2009/lux_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
38356,442,"LUX","Luxembourg","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2009/lux_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
38357,442,"LUX","Luxembourg","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2010/lux_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
38358,442,"LUX","Luxembourg","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2010/lux_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
38359,442,"LUX","Luxembourg","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2010/lux_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
38360,442,"LUX","Luxembourg","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2010/lux_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
38361,442,"LUX","Luxembourg","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2010/lux_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
38362,442,"LUX","Luxembourg","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2010/lux_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
38363,442,"LUX","Luxembourg","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2010/lux_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
38364,442,"LUX","Luxembourg","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2010/lux_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
38365,442,"LUX","Luxembourg","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2011/lux_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
38366,442,"LUX","Luxembourg","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2011/lux_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
38367,442,"LUX","Luxembourg","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2011/lux_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
38368,442,"LUX","Luxembourg","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2011/lux_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
38369,442,"LUX","Luxembourg","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2011/lux_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
38370,442,"LUX","Luxembourg","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2011/lux_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
38371,442,"LUX","Luxembourg","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2011/lux_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
38372,442,"LUX","Luxembourg","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2011/lux_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
38373,442,"LUX","Luxembourg","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2012/lux_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
38374,442,"LUX","Luxembourg","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2012/lux_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
38375,442,"LUX","Luxembourg","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2012/lux_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
38376,442,"LUX","Luxembourg","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2012/lux_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
38377,442,"LUX","Luxembourg","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2012/lux_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
38378,442,"LUX","Luxembourg","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2012/lux_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
38379,442,"LUX","Luxembourg","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2012/lux_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
38380,442,"LUX","Luxembourg","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2012/lux_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
38381,442,"LUX","Luxembourg","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2013/lux_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
38382,442,"LUX","Luxembourg","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2013/lux_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
38383,442,"LUX","Luxembourg","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2013/lux_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
38384,442,"LUX","Luxembourg","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2013/lux_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
38385,442,"LUX","Luxembourg","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2013/lux_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
38386,442,"LUX","Luxembourg","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2013/lux_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
38387,442,"LUX","Luxembourg","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2013/lux_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
38388,442,"LUX","Luxembourg","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2013/lux_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
38389,442,"LUX","Luxembourg","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2014/lux_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
38390,442,"LUX","Luxembourg","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2014/lux_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
38391,442,"LUX","Luxembourg","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2014/lux_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
38392,442,"LUX","Luxembourg","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2014/lux_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
38393,442,"LUX","Luxembourg","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2014/lux_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
38394,442,"LUX","Luxembourg","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2014/lux_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
38395,442,"LUX","Luxembourg","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2014/lux_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
38396,442,"LUX","Luxembourg","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2014/lux_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
38397,442,"LUX","Luxembourg","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2015/lux_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
38398,442,"LUX","Luxembourg","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2015/lux_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
38399,442,"LUX","Luxembourg","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2015/lux_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
38400,442,"LUX","Luxembourg","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2015/lux_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
38401,442,"LUX","Luxembourg","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2015/lux_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
38402,442,"LUX","Luxembourg","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2015/lux_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
38403,442,"LUX","Luxembourg","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2015/lux_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
38404,442,"LUX","Luxembourg","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Annual/2015/lux_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
38405,446,"MAC","Macao","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2000/mac_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
38406,446,"MAC","Macao","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2000/mac_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
38407,446,"MAC","Macao","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2000/mac_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
38408,446,"MAC","Macao","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2000/mac_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
38409,446,"MAC","Macao","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2000/mac_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
38410,446,"MAC","Macao","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2000/mac_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
38411,446,"MAC","Macao","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2000/mac_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
38412,446,"MAC","Macao","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2000/mac_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
38413,446,"MAC","Macao","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2001/mac_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
38414,446,"MAC","Macao","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2001/mac_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
38415,446,"MAC","Macao","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2001/mac_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
38416,446,"MAC","Macao","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2001/mac_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
38417,446,"MAC","Macao","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2001/mac_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
38418,446,"MAC","Macao","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2001/mac_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
38419,446,"MAC","Macao","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2001/mac_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
38420,446,"MAC","Macao","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2001/mac_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
38421,446,"MAC","Macao","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2002/mac_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
38422,446,"MAC","Macao","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2002/mac_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
38423,446,"MAC","Macao","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2002/mac_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
38424,446,"MAC","Macao","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2002/mac_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
38425,446,"MAC","Macao","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2002/mac_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
38426,446,"MAC","Macao","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2002/mac_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
38427,446,"MAC","Macao","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2002/mac_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
38428,446,"MAC","Macao","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2002/mac_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
38429,446,"MAC","Macao","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2003/mac_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
38430,446,"MAC","Macao","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2003/mac_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
38431,446,"MAC","Macao","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2003/mac_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
38432,446,"MAC","Macao","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2003/mac_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
38433,446,"MAC","Macao","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2003/mac_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
38434,446,"MAC","Macao","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2003/mac_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
38435,446,"MAC","Macao","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2003/mac_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
38436,446,"MAC","Macao","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2003/mac_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
38437,446,"MAC","Macao","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2004/mac_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
38438,446,"MAC","Macao","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2004/mac_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
38439,446,"MAC","Macao","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2004/mac_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
38440,446,"MAC","Macao","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2004/mac_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
38441,446,"MAC","Macao","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2004/mac_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
38442,446,"MAC","Macao","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2004/mac_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
38443,446,"MAC","Macao","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2004/mac_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
38444,446,"MAC","Macao","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2004/mac_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
38445,446,"MAC","Macao","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2005/mac_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
38446,446,"MAC","Macao","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2005/mac_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
38447,446,"MAC","Macao","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2005/mac_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
38448,446,"MAC","Macao","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2005/mac_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
38449,446,"MAC","Macao","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2005/mac_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
38450,446,"MAC","Macao","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2005/mac_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
38451,446,"MAC","Macao","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2005/mac_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
38452,446,"MAC","Macao","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2005/mac_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
38453,446,"MAC","Macao","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2006/mac_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
38454,446,"MAC","Macao","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2006/mac_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
38455,446,"MAC","Macao","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2006/mac_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
38456,446,"MAC","Macao","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2006/mac_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
38457,446,"MAC","Macao","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2006/mac_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
38458,446,"MAC","Macao","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2006/mac_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
38459,446,"MAC","Macao","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2006/mac_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
38460,446,"MAC","Macao","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2006/mac_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
38461,446,"MAC","Macao","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2007/mac_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
38462,446,"MAC","Macao","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2007/mac_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
38463,446,"MAC","Macao","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2007/mac_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
38464,446,"MAC","Macao","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2007/mac_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
38465,446,"MAC","Macao","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2007/mac_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
38466,446,"MAC","Macao","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2007/mac_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
38467,446,"MAC","Macao","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2007/mac_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
38468,446,"MAC","Macao","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2007/mac_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
38469,446,"MAC","Macao","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2008/mac_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
38470,446,"MAC","Macao","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2008/mac_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
38471,446,"MAC","Macao","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2008/mac_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
38472,446,"MAC","Macao","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2008/mac_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
38473,446,"MAC","Macao","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2008/mac_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
38474,446,"MAC","Macao","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2008/mac_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
38475,446,"MAC","Macao","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2008/mac_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
38476,446,"MAC","Macao","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2008/mac_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
38477,446,"MAC","Macao","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2009/mac_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
38478,446,"MAC","Macao","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2009/mac_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
38479,446,"MAC","Macao","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2009/mac_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
38480,446,"MAC","Macao","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2009/mac_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
38481,446,"MAC","Macao","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2009/mac_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
38482,446,"MAC","Macao","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2009/mac_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
38483,446,"MAC","Macao","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2009/mac_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
38484,446,"MAC","Macao","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2009/mac_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
38485,446,"MAC","Macao","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2010/mac_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
38486,446,"MAC","Macao","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2010/mac_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
38487,446,"MAC","Macao","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2010/mac_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
38488,446,"MAC","Macao","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2010/mac_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
38489,446,"MAC","Macao","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2010/mac_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
38490,446,"MAC","Macao","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2010/mac_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
38491,446,"MAC","Macao","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2010/mac_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
38492,446,"MAC","Macao","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2010/mac_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
38493,446,"MAC","Macao","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2011/mac_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
38494,446,"MAC","Macao","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2011/mac_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
38495,446,"MAC","Macao","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2011/mac_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
38496,446,"MAC","Macao","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2011/mac_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
38497,446,"MAC","Macao","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2011/mac_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
38498,446,"MAC","Macao","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2011/mac_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
38499,446,"MAC","Macao","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2011/mac_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
38500,446,"MAC","Macao","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2011/mac_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
38501,446,"MAC","Macao","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2012/mac_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
38502,446,"MAC","Macao","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2012/mac_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
38503,446,"MAC","Macao","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2012/mac_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
38504,446,"MAC","Macao","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2012/mac_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
38505,446,"MAC","Macao","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2012/mac_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
38506,446,"MAC","Macao","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2012/mac_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
38507,446,"MAC","Macao","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2012/mac_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
38508,446,"MAC","Macao","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2012/mac_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
38509,446,"MAC","Macao","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2013/mac_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
38510,446,"MAC","Macao","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2013/mac_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
38511,446,"MAC","Macao","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2013/mac_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
38512,446,"MAC","Macao","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2013/mac_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
38513,446,"MAC","Macao","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2013/mac_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
38514,446,"MAC","Macao","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2013/mac_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
38515,446,"MAC","Macao","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2013/mac_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
38516,446,"MAC","Macao","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2013/mac_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
38517,446,"MAC","Macao","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2014/mac_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
38518,446,"MAC","Macao","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2014/mac_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
38519,446,"MAC","Macao","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2014/mac_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
38520,446,"MAC","Macao","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2014/mac_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
38521,446,"MAC","Macao","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2014/mac_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
38522,446,"MAC","Macao","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2014/mac_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
38523,446,"MAC","Macao","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2014/mac_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
38524,446,"MAC","Macao","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2014/mac_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
38525,446,"MAC","Macao","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2015/mac_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
38526,446,"MAC","Macao","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2015/mac_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
38527,446,"MAC","Macao","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2015/mac_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
38528,446,"MAC","Macao","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2015/mac_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
38529,446,"MAC","Macao","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2015/mac_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
38530,446,"MAC","Macao","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2015/mac_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
38531,446,"MAC","Macao","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2015/mac_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
38532,446,"MAC","Macao","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Annual/2015/mac_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
38533,450,"MDG","Madagascar","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2000/mdg_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
38534,450,"MDG","Madagascar","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2000/mdg_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
38535,450,"MDG","Madagascar","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2000/mdg_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
38536,450,"MDG","Madagascar","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2000/mdg_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
38537,450,"MDG","Madagascar","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2000/mdg_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
38538,450,"MDG","Madagascar","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2000/mdg_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
38539,450,"MDG","Madagascar","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2000/mdg_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
38540,450,"MDG","Madagascar","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2000/mdg_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
38541,450,"MDG","Madagascar","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2001/mdg_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
38542,450,"MDG","Madagascar","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2001/mdg_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
38543,450,"MDG","Madagascar","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2001/mdg_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
38544,450,"MDG","Madagascar","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2001/mdg_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
38545,450,"MDG","Madagascar","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2001/mdg_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
38546,450,"MDG","Madagascar","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2001/mdg_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
38547,450,"MDG","Madagascar","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2001/mdg_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
38548,450,"MDG","Madagascar","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2001/mdg_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
38549,450,"MDG","Madagascar","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2002/mdg_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
38550,450,"MDG","Madagascar","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2002/mdg_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
38551,450,"MDG","Madagascar","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2002/mdg_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
38552,450,"MDG","Madagascar","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2002/mdg_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
38553,450,"MDG","Madagascar","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2002/mdg_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
38554,450,"MDG","Madagascar","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2002/mdg_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
38555,450,"MDG","Madagascar","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2002/mdg_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
38556,450,"MDG","Madagascar","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2002/mdg_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
38557,450,"MDG","Madagascar","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2003/mdg_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
38558,450,"MDG","Madagascar","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2003/mdg_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
38559,450,"MDG","Madagascar","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2003/mdg_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
38560,450,"MDG","Madagascar","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2003/mdg_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
38561,450,"MDG","Madagascar","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2003/mdg_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
38562,450,"MDG","Madagascar","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2003/mdg_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
38563,450,"MDG","Madagascar","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2003/mdg_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
38564,450,"MDG","Madagascar","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2003/mdg_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
38565,450,"MDG","Madagascar","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2004/mdg_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
38566,450,"MDG","Madagascar","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2004/mdg_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
38567,450,"MDG","Madagascar","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2004/mdg_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
38568,450,"MDG","Madagascar","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2004/mdg_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
38569,450,"MDG","Madagascar","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2004/mdg_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
38570,450,"MDG","Madagascar","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2004/mdg_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
38571,450,"MDG","Madagascar","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2004/mdg_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
38572,450,"MDG","Madagascar","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2004/mdg_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
38573,450,"MDG","Madagascar","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2005/mdg_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
38574,450,"MDG","Madagascar","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2005/mdg_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
38575,450,"MDG","Madagascar","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2005/mdg_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
38576,450,"MDG","Madagascar","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2005/mdg_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
38577,450,"MDG","Madagascar","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2005/mdg_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
38578,450,"MDG","Madagascar","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2005/mdg_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
38579,450,"MDG","Madagascar","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2005/mdg_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
38580,450,"MDG","Madagascar","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2005/mdg_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
38581,450,"MDG","Madagascar","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2006/mdg_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
38582,450,"MDG","Madagascar","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2006/mdg_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
38583,450,"MDG","Madagascar","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2006/mdg_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
38584,450,"MDG","Madagascar","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2006/mdg_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
38585,450,"MDG","Madagascar","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2006/mdg_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
38586,450,"MDG","Madagascar","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2006/mdg_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
38587,450,"MDG","Madagascar","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2006/mdg_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
38588,450,"MDG","Madagascar","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2006/mdg_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
38589,450,"MDG","Madagascar","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2007/mdg_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
38590,450,"MDG","Madagascar","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2007/mdg_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
38591,450,"MDG","Madagascar","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2007/mdg_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
38592,450,"MDG","Madagascar","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2007/mdg_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
38593,450,"MDG","Madagascar","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2007/mdg_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
38594,450,"MDG","Madagascar","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2007/mdg_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
38595,450,"MDG","Madagascar","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2007/mdg_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
38596,450,"MDG","Madagascar","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2007/mdg_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
38597,450,"MDG","Madagascar","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2008/mdg_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
38598,450,"MDG","Madagascar","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2008/mdg_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
38599,450,"MDG","Madagascar","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2008/mdg_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
38600,450,"MDG","Madagascar","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2008/mdg_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
38601,450,"MDG","Madagascar","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2008/mdg_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
38602,450,"MDG","Madagascar","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2008/mdg_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
38603,450,"MDG","Madagascar","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2008/mdg_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
38604,450,"MDG","Madagascar","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2008/mdg_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
38605,450,"MDG","Madagascar","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2009/mdg_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
38606,450,"MDG","Madagascar","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2009/mdg_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
38607,450,"MDG","Madagascar","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2009/mdg_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
38608,450,"MDG","Madagascar","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2009/mdg_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
38609,450,"MDG","Madagascar","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2009/mdg_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
38610,450,"MDG","Madagascar","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2009/mdg_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
38611,450,"MDG","Madagascar","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2009/mdg_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
38612,450,"MDG","Madagascar","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2009/mdg_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
38613,450,"MDG","Madagascar","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2010/mdg_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
38614,450,"MDG","Madagascar","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2010/mdg_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
38615,450,"MDG","Madagascar","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2010/mdg_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
38616,450,"MDG","Madagascar","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2010/mdg_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
38617,450,"MDG","Madagascar","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2010/mdg_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
38618,450,"MDG","Madagascar","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2010/mdg_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
38619,450,"MDG","Madagascar","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2010/mdg_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
38620,450,"MDG","Madagascar","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2010/mdg_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
38621,450,"MDG","Madagascar","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2011/mdg_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
38622,450,"MDG","Madagascar","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2011/mdg_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
38623,450,"MDG","Madagascar","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2011/mdg_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
38624,450,"MDG","Madagascar","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2011/mdg_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
38625,450,"MDG","Madagascar","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2011/mdg_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
38626,450,"MDG","Madagascar","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2011/mdg_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
38627,450,"MDG","Madagascar","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2011/mdg_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
38628,450,"MDG","Madagascar","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2011/mdg_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
38629,450,"MDG","Madagascar","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2012/mdg_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
38630,450,"MDG","Madagascar","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2012/mdg_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
38631,450,"MDG","Madagascar","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2012/mdg_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
38632,450,"MDG","Madagascar","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2012/mdg_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
38633,450,"MDG","Madagascar","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2012/mdg_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
38634,450,"MDG","Madagascar","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2012/mdg_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
38635,450,"MDG","Madagascar","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2012/mdg_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
38636,450,"MDG","Madagascar","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2012/mdg_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
38637,450,"MDG","Madagascar","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2013/mdg_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
38638,450,"MDG","Madagascar","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2013/mdg_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
38639,450,"MDG","Madagascar","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2013/mdg_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
38640,450,"MDG","Madagascar","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2013/mdg_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
38641,450,"MDG","Madagascar","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2013/mdg_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
38642,450,"MDG","Madagascar","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2013/mdg_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
38643,450,"MDG","Madagascar","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2013/mdg_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
38644,450,"MDG","Madagascar","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2013/mdg_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
38645,450,"MDG","Madagascar","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2014/mdg_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
38646,450,"MDG","Madagascar","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2014/mdg_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
38647,450,"MDG","Madagascar","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2014/mdg_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
38648,450,"MDG","Madagascar","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2014/mdg_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
38649,450,"MDG","Madagascar","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2014/mdg_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
38650,450,"MDG","Madagascar","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2014/mdg_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
38651,450,"MDG","Madagascar","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2014/mdg_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
38652,450,"MDG","Madagascar","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2014/mdg_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
38653,450,"MDG","Madagascar","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2015/mdg_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
38654,450,"MDG","Madagascar","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2015/mdg_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
38655,450,"MDG","Madagascar","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2015/mdg_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
38656,450,"MDG","Madagascar","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2015/mdg_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
38657,450,"MDG","Madagascar","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2015/mdg_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
38658,450,"MDG","Madagascar","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2015/mdg_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
38659,450,"MDG","Madagascar","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2015/mdg_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
38660,450,"MDG","Madagascar","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Annual/2015/mdg_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
38661,454,"MWI","Malawi","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2000/mwi_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
38662,454,"MWI","Malawi","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2000/mwi_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
38663,454,"MWI","Malawi","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2000/mwi_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
38664,454,"MWI","Malawi","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2000/mwi_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
38665,454,"MWI","Malawi","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2000/mwi_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
38666,454,"MWI","Malawi","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2000/mwi_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
38667,454,"MWI","Malawi","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2000/mwi_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
38668,454,"MWI","Malawi","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2000/mwi_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
38669,454,"MWI","Malawi","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2001/mwi_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
38670,454,"MWI","Malawi","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2001/mwi_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
38671,454,"MWI","Malawi","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2001/mwi_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
38672,454,"MWI","Malawi","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2001/mwi_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
38673,454,"MWI","Malawi","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2001/mwi_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
38674,454,"MWI","Malawi","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2001/mwi_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
38675,454,"MWI","Malawi","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2001/mwi_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
38676,454,"MWI","Malawi","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2001/mwi_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
38677,454,"MWI","Malawi","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2002/mwi_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
38678,454,"MWI","Malawi","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2002/mwi_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
38679,454,"MWI","Malawi","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2002/mwi_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
38680,454,"MWI","Malawi","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2002/mwi_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
38681,454,"MWI","Malawi","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2002/mwi_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
38682,454,"MWI","Malawi","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2002/mwi_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
38683,454,"MWI","Malawi","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2002/mwi_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
38684,454,"MWI","Malawi","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2002/mwi_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
38685,454,"MWI","Malawi","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2003/mwi_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
38686,454,"MWI","Malawi","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2003/mwi_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
38687,454,"MWI","Malawi","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2003/mwi_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
38688,454,"MWI","Malawi","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2003/mwi_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
38689,454,"MWI","Malawi","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2003/mwi_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
38690,454,"MWI","Malawi","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2003/mwi_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
38691,454,"MWI","Malawi","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2003/mwi_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
38692,454,"MWI","Malawi","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2003/mwi_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
38693,454,"MWI","Malawi","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2004/mwi_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
38694,454,"MWI","Malawi","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2004/mwi_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
38695,454,"MWI","Malawi","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2004/mwi_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
38696,454,"MWI","Malawi","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2004/mwi_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
38697,454,"MWI","Malawi","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2004/mwi_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
38698,454,"MWI","Malawi","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2004/mwi_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
38699,454,"MWI","Malawi","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2004/mwi_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
38700,454,"MWI","Malawi","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2004/mwi_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
38701,454,"MWI","Malawi","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2005/mwi_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
38702,454,"MWI","Malawi","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2005/mwi_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
38703,454,"MWI","Malawi","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2005/mwi_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
38704,454,"MWI","Malawi","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2005/mwi_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
38705,454,"MWI","Malawi","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2005/mwi_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
38706,454,"MWI","Malawi","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2005/mwi_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
38707,454,"MWI","Malawi","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2005/mwi_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
38708,454,"MWI","Malawi","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2005/mwi_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
38709,454,"MWI","Malawi","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2006/mwi_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
38710,454,"MWI","Malawi","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2006/mwi_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
38711,454,"MWI","Malawi","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2006/mwi_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
38712,454,"MWI","Malawi","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2006/mwi_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
38713,454,"MWI","Malawi","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2006/mwi_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
38714,454,"MWI","Malawi","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2006/mwi_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
38715,454,"MWI","Malawi","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2006/mwi_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
38716,454,"MWI","Malawi","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2006/mwi_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
38717,454,"MWI","Malawi","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2007/mwi_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
38718,454,"MWI","Malawi","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2007/mwi_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
38719,454,"MWI","Malawi","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2007/mwi_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
38720,454,"MWI","Malawi","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2007/mwi_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
38721,454,"MWI","Malawi","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2007/mwi_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
38722,454,"MWI","Malawi","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2007/mwi_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
38723,454,"MWI","Malawi","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2007/mwi_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
38724,454,"MWI","Malawi","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2007/mwi_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
38725,454,"MWI","Malawi","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2008/mwi_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
38726,454,"MWI","Malawi","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2008/mwi_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
38727,454,"MWI","Malawi","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2008/mwi_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
38728,454,"MWI","Malawi","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2008/mwi_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
38729,454,"MWI","Malawi","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2008/mwi_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
38730,454,"MWI","Malawi","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2008/mwi_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
38731,454,"MWI","Malawi","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2008/mwi_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
38732,454,"MWI","Malawi","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2008/mwi_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
38733,454,"MWI","Malawi","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2009/mwi_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
38734,454,"MWI","Malawi","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2009/mwi_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
38735,454,"MWI","Malawi","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2009/mwi_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
38736,454,"MWI","Malawi","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2009/mwi_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
38737,454,"MWI","Malawi","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2009/mwi_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
38738,454,"MWI","Malawi","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2009/mwi_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
38739,454,"MWI","Malawi","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2009/mwi_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
38740,454,"MWI","Malawi","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2009/mwi_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
38741,454,"MWI","Malawi","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2010/mwi_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
38742,454,"MWI","Malawi","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2010/mwi_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
38743,454,"MWI","Malawi","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2010/mwi_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
38744,454,"MWI","Malawi","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2010/mwi_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
38745,454,"MWI","Malawi","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2010/mwi_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
38746,454,"MWI","Malawi","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2010/mwi_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
38747,454,"MWI","Malawi","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2010/mwi_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
38748,454,"MWI","Malawi","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2010/mwi_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
38749,454,"MWI","Malawi","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2011/mwi_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
38750,454,"MWI","Malawi","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2011/mwi_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
38751,454,"MWI","Malawi","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2011/mwi_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
38752,454,"MWI","Malawi","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2011/mwi_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
38753,454,"MWI","Malawi","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2011/mwi_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
38754,454,"MWI","Malawi","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2011/mwi_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
38755,454,"MWI","Malawi","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2011/mwi_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
38756,454,"MWI","Malawi","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2011/mwi_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
38757,454,"MWI","Malawi","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2012/mwi_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
38758,454,"MWI","Malawi","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2012/mwi_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
38759,454,"MWI","Malawi","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2012/mwi_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
38760,454,"MWI","Malawi","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2012/mwi_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
38761,454,"MWI","Malawi","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2012/mwi_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
38762,454,"MWI","Malawi","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2012/mwi_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
38763,454,"MWI","Malawi","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2012/mwi_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
38764,454,"MWI","Malawi","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2012/mwi_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
38765,454,"MWI","Malawi","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2013/mwi_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
38766,454,"MWI","Malawi","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2013/mwi_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
38767,454,"MWI","Malawi","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2013/mwi_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
38768,454,"MWI","Malawi","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2013/mwi_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
38769,454,"MWI","Malawi","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2013/mwi_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
38770,454,"MWI","Malawi","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2013/mwi_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
38771,454,"MWI","Malawi","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2013/mwi_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
38772,454,"MWI","Malawi","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2013/mwi_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
38773,454,"MWI","Malawi","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2014/mwi_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
38774,454,"MWI","Malawi","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2014/mwi_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
38775,454,"MWI","Malawi","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2014/mwi_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
38776,454,"MWI","Malawi","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2014/mwi_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
38777,454,"MWI","Malawi","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2014/mwi_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
38778,454,"MWI","Malawi","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2014/mwi_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
38779,454,"MWI","Malawi","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2014/mwi_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
38780,454,"MWI","Malawi","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2014/mwi_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
38781,454,"MWI","Malawi","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2015/mwi_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
38782,454,"MWI","Malawi","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2015/mwi_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
38783,454,"MWI","Malawi","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2015/mwi_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
38784,454,"MWI","Malawi","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2015/mwi_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
38785,454,"MWI","Malawi","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2015/mwi_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
38786,454,"MWI","Malawi","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2015/mwi_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
38787,454,"MWI","Malawi","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2015/mwi_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
38788,454,"MWI","Malawi","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Annual/2015/mwi_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
38789,458,"MYS","Malaysia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2000/mys_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
38790,458,"MYS","Malaysia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2000/mys_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
38791,458,"MYS","Malaysia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2000/mys_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
38792,458,"MYS","Malaysia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2000/mys_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
38793,458,"MYS","Malaysia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2000/mys_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
38794,458,"MYS","Malaysia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2000/mys_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
38795,458,"MYS","Malaysia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2000/mys_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
38796,458,"MYS","Malaysia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2000/mys_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
38797,458,"MYS","Malaysia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2001/mys_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
38798,458,"MYS","Malaysia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2001/mys_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
38799,458,"MYS","Malaysia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2001/mys_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
38800,458,"MYS","Malaysia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2001/mys_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
38801,458,"MYS","Malaysia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2001/mys_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
38802,458,"MYS","Malaysia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2001/mys_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
38803,458,"MYS","Malaysia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2001/mys_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
38804,458,"MYS","Malaysia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2001/mys_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
38805,458,"MYS","Malaysia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2002/mys_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
38806,458,"MYS","Malaysia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2002/mys_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
38807,458,"MYS","Malaysia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2002/mys_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
38808,458,"MYS","Malaysia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2002/mys_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
38809,458,"MYS","Malaysia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2002/mys_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
38810,458,"MYS","Malaysia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2002/mys_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
38811,458,"MYS","Malaysia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2002/mys_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
38812,458,"MYS","Malaysia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2002/mys_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
38813,458,"MYS","Malaysia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2003/mys_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
38814,458,"MYS","Malaysia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2003/mys_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
38815,458,"MYS","Malaysia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2003/mys_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
38816,458,"MYS","Malaysia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2003/mys_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
38817,458,"MYS","Malaysia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2003/mys_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
38818,458,"MYS","Malaysia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2003/mys_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
38819,458,"MYS","Malaysia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2003/mys_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
38820,458,"MYS","Malaysia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2003/mys_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
38821,458,"MYS","Malaysia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2004/mys_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
38822,458,"MYS","Malaysia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2004/mys_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
38823,458,"MYS","Malaysia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2004/mys_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
38824,458,"MYS","Malaysia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2004/mys_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
38825,458,"MYS","Malaysia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2004/mys_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
38826,458,"MYS","Malaysia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2004/mys_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
38827,458,"MYS","Malaysia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2004/mys_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
38828,458,"MYS","Malaysia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2004/mys_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
38829,458,"MYS","Malaysia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2005/mys_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
38830,458,"MYS","Malaysia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2005/mys_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
38831,458,"MYS","Malaysia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2005/mys_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
38832,458,"MYS","Malaysia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2005/mys_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
38833,458,"MYS","Malaysia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2005/mys_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
38834,458,"MYS","Malaysia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2005/mys_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
38835,458,"MYS","Malaysia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2005/mys_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
38836,458,"MYS","Malaysia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2005/mys_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
38837,458,"MYS","Malaysia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2006/mys_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
38838,458,"MYS","Malaysia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2006/mys_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
38839,458,"MYS","Malaysia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2006/mys_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
38840,458,"MYS","Malaysia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2006/mys_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
38841,458,"MYS","Malaysia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2006/mys_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
38842,458,"MYS","Malaysia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2006/mys_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
38843,458,"MYS","Malaysia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2006/mys_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
38844,458,"MYS","Malaysia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2006/mys_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
38845,458,"MYS","Malaysia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2007/mys_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
38846,458,"MYS","Malaysia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2007/mys_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
38847,458,"MYS","Malaysia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2007/mys_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
38848,458,"MYS","Malaysia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2007/mys_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
38849,458,"MYS","Malaysia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2007/mys_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
38850,458,"MYS","Malaysia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2007/mys_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
38851,458,"MYS","Malaysia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2007/mys_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
38852,458,"MYS","Malaysia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2007/mys_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
38853,458,"MYS","Malaysia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2008/mys_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
38854,458,"MYS","Malaysia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2008/mys_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
38855,458,"MYS","Malaysia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2008/mys_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
38856,458,"MYS","Malaysia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2008/mys_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
38857,458,"MYS","Malaysia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2008/mys_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
38858,458,"MYS","Malaysia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2008/mys_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
38859,458,"MYS","Malaysia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2008/mys_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
38860,458,"MYS","Malaysia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2008/mys_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
38861,458,"MYS","Malaysia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2009/mys_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
38862,458,"MYS","Malaysia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2009/mys_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
38863,458,"MYS","Malaysia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2009/mys_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
38864,458,"MYS","Malaysia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2009/mys_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
38865,458,"MYS","Malaysia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2009/mys_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
38866,458,"MYS","Malaysia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2009/mys_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
38867,458,"MYS","Malaysia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2009/mys_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
38868,458,"MYS","Malaysia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2009/mys_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
38869,458,"MYS","Malaysia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2010/mys_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
38870,458,"MYS","Malaysia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2010/mys_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
38871,458,"MYS","Malaysia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2010/mys_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
38872,458,"MYS","Malaysia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2010/mys_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
38873,458,"MYS","Malaysia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2010/mys_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
38874,458,"MYS","Malaysia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2010/mys_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
38875,458,"MYS","Malaysia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2010/mys_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
38876,458,"MYS","Malaysia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2010/mys_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
38877,458,"MYS","Malaysia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2011/mys_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
38878,458,"MYS","Malaysia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2011/mys_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
38879,458,"MYS","Malaysia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2011/mys_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
38880,458,"MYS","Malaysia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2011/mys_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
38881,458,"MYS","Malaysia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2011/mys_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
38882,458,"MYS","Malaysia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2011/mys_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
38883,458,"MYS","Malaysia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2011/mys_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
38884,458,"MYS","Malaysia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2011/mys_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
38885,458,"MYS","Malaysia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2012/mys_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
38886,458,"MYS","Malaysia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2012/mys_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
38887,458,"MYS","Malaysia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2012/mys_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
38888,458,"MYS","Malaysia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2012/mys_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
38889,458,"MYS","Malaysia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2012/mys_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
38890,458,"MYS","Malaysia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2012/mys_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
38891,458,"MYS","Malaysia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2012/mys_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
38892,458,"MYS","Malaysia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2012/mys_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
38893,458,"MYS","Malaysia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2013/mys_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
38894,458,"MYS","Malaysia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2013/mys_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
38895,458,"MYS","Malaysia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2013/mys_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
38896,458,"MYS","Malaysia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2013/mys_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
38897,458,"MYS","Malaysia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2013/mys_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
38898,458,"MYS","Malaysia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2013/mys_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
38899,458,"MYS","Malaysia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2013/mys_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
38900,458,"MYS","Malaysia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2013/mys_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
38901,458,"MYS","Malaysia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2014/mys_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
38902,458,"MYS","Malaysia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2014/mys_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
38903,458,"MYS","Malaysia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2014/mys_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
38904,458,"MYS","Malaysia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2014/mys_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
38905,458,"MYS","Malaysia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2014/mys_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
38906,458,"MYS","Malaysia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2014/mys_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
38907,458,"MYS","Malaysia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2014/mys_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
38908,458,"MYS","Malaysia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2014/mys_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
38909,458,"MYS","Malaysia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2015/mys_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
38910,458,"MYS","Malaysia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2015/mys_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
38911,458,"MYS","Malaysia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2015/mys_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
38912,458,"MYS","Malaysia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2015/mys_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
38913,458,"MYS","Malaysia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2015/mys_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
38914,458,"MYS","Malaysia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2015/mys_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
38915,458,"MYS","Malaysia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2015/mys_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
38916,458,"MYS","Malaysia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Annual/2015/mys_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
38917,462,"MDV","Maldives","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2000/mdv_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
38918,462,"MDV","Maldives","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2000/mdv_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
38919,462,"MDV","Maldives","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2000/mdv_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
38920,462,"MDV","Maldives","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2000/mdv_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
38921,462,"MDV","Maldives","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2000/mdv_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
38922,462,"MDV","Maldives","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2000/mdv_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
38923,462,"MDV","Maldives","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2000/mdv_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
38924,462,"MDV","Maldives","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2000/mdv_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
38925,462,"MDV","Maldives","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2001/mdv_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
38926,462,"MDV","Maldives","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2001/mdv_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
38927,462,"MDV","Maldives","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2001/mdv_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
38928,462,"MDV","Maldives","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2001/mdv_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
38929,462,"MDV","Maldives","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2001/mdv_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
38930,462,"MDV","Maldives","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2001/mdv_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
38931,462,"MDV","Maldives","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2001/mdv_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
38932,462,"MDV","Maldives","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2001/mdv_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
38933,462,"MDV","Maldives","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2002/mdv_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
38934,462,"MDV","Maldives","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2002/mdv_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
38935,462,"MDV","Maldives","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2002/mdv_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
38936,462,"MDV","Maldives","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2002/mdv_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
38937,462,"MDV","Maldives","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2002/mdv_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
38938,462,"MDV","Maldives","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2002/mdv_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
38939,462,"MDV","Maldives","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2002/mdv_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
38940,462,"MDV","Maldives","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2002/mdv_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
38941,462,"MDV","Maldives","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2003/mdv_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
38942,462,"MDV","Maldives","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2003/mdv_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
38943,462,"MDV","Maldives","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2003/mdv_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
38944,462,"MDV","Maldives","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2003/mdv_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
38945,462,"MDV","Maldives","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2003/mdv_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
38946,462,"MDV","Maldives","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2003/mdv_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
38947,462,"MDV","Maldives","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2003/mdv_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
38948,462,"MDV","Maldives","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2003/mdv_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
38949,462,"MDV","Maldives","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2004/mdv_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
38950,462,"MDV","Maldives","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2004/mdv_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
38951,462,"MDV","Maldives","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2004/mdv_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
38952,462,"MDV","Maldives","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2004/mdv_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
38953,462,"MDV","Maldives","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2004/mdv_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
38954,462,"MDV","Maldives","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2004/mdv_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
38955,462,"MDV","Maldives","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2004/mdv_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
38956,462,"MDV","Maldives","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2004/mdv_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
38957,462,"MDV","Maldives","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2005/mdv_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
38958,462,"MDV","Maldives","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2005/mdv_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
38959,462,"MDV","Maldives","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2005/mdv_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
38960,462,"MDV","Maldives","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2005/mdv_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
38961,462,"MDV","Maldives","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2005/mdv_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
38962,462,"MDV","Maldives","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2005/mdv_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
38963,462,"MDV","Maldives","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2005/mdv_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
38964,462,"MDV","Maldives","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2005/mdv_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
38965,462,"MDV","Maldives","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2006/mdv_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
38966,462,"MDV","Maldives","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2006/mdv_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
38967,462,"MDV","Maldives","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2006/mdv_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
38968,462,"MDV","Maldives","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2006/mdv_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
38969,462,"MDV","Maldives","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2006/mdv_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
38970,462,"MDV","Maldives","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2006/mdv_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
38971,462,"MDV","Maldives","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2006/mdv_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
38972,462,"MDV","Maldives","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2006/mdv_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
38973,462,"MDV","Maldives","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2007/mdv_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
38974,462,"MDV","Maldives","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2007/mdv_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
38975,462,"MDV","Maldives","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2007/mdv_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
38976,462,"MDV","Maldives","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2007/mdv_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
38977,462,"MDV","Maldives","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2007/mdv_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
38978,462,"MDV","Maldives","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2007/mdv_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
38979,462,"MDV","Maldives","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2007/mdv_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
38980,462,"MDV","Maldives","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2007/mdv_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
38981,462,"MDV","Maldives","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2008/mdv_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
38982,462,"MDV","Maldives","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2008/mdv_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
38983,462,"MDV","Maldives","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2008/mdv_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
38984,462,"MDV","Maldives","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2008/mdv_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
38985,462,"MDV","Maldives","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2008/mdv_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
38986,462,"MDV","Maldives","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2008/mdv_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
38987,462,"MDV","Maldives","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2008/mdv_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
38988,462,"MDV","Maldives","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2008/mdv_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
38989,462,"MDV","Maldives","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2009/mdv_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
38990,462,"MDV","Maldives","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2009/mdv_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
38991,462,"MDV","Maldives","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2009/mdv_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
38992,462,"MDV","Maldives","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2009/mdv_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
38993,462,"MDV","Maldives","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2009/mdv_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
38994,462,"MDV","Maldives","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2009/mdv_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
38995,462,"MDV","Maldives","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2009/mdv_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
38996,462,"MDV","Maldives","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2009/mdv_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
38997,462,"MDV","Maldives","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2010/mdv_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
38998,462,"MDV","Maldives","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2010/mdv_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
38999,462,"MDV","Maldives","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2010/mdv_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
39000,462,"MDV","Maldives","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2010/mdv_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
39001,462,"MDV","Maldives","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2010/mdv_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
39002,462,"MDV","Maldives","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2010/mdv_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
39003,462,"MDV","Maldives","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2010/mdv_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
39004,462,"MDV","Maldives","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2010/mdv_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
39005,462,"MDV","Maldives","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2011/mdv_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
39006,462,"MDV","Maldives","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2011/mdv_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
39007,462,"MDV","Maldives","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2011/mdv_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
39008,462,"MDV","Maldives","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2011/mdv_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
39009,462,"MDV","Maldives","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2011/mdv_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
39010,462,"MDV","Maldives","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2011/mdv_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
39011,462,"MDV","Maldives","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2011/mdv_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
39012,462,"MDV","Maldives","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2011/mdv_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
39013,462,"MDV","Maldives","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2012/mdv_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
39014,462,"MDV","Maldives","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2012/mdv_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
39015,462,"MDV","Maldives","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2012/mdv_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
39016,462,"MDV","Maldives","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2012/mdv_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
39017,462,"MDV","Maldives","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2012/mdv_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
39018,462,"MDV","Maldives","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2012/mdv_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
39019,462,"MDV","Maldives","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2012/mdv_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
39020,462,"MDV","Maldives","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2012/mdv_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
39021,462,"MDV","Maldives","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2013/mdv_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
39022,462,"MDV","Maldives","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2013/mdv_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
39023,462,"MDV","Maldives","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2013/mdv_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
39024,462,"MDV","Maldives","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2013/mdv_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
39025,462,"MDV","Maldives","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2013/mdv_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
39026,462,"MDV","Maldives","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2013/mdv_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
39027,462,"MDV","Maldives","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2013/mdv_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
39028,462,"MDV","Maldives","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2013/mdv_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
39029,462,"MDV","Maldives","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2014/mdv_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
39030,462,"MDV","Maldives","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2014/mdv_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
39031,462,"MDV","Maldives","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2014/mdv_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
39032,462,"MDV","Maldives","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2014/mdv_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
39033,462,"MDV","Maldives","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2014/mdv_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
39034,462,"MDV","Maldives","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2014/mdv_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
39035,462,"MDV","Maldives","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2014/mdv_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
39036,462,"MDV","Maldives","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2014/mdv_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
39037,462,"MDV","Maldives","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2015/mdv_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
39038,462,"MDV","Maldives","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2015/mdv_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
39039,462,"MDV","Maldives","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2015/mdv_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
39040,462,"MDV","Maldives","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2015/mdv_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
39041,462,"MDV","Maldives","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2015/mdv_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
39042,462,"MDV","Maldives","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2015/mdv_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
39043,462,"MDV","Maldives","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2015/mdv_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
39044,462,"MDV","Maldives","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Annual/2015/mdv_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
39045,466,"MLI","Mali","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2000/mli_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
39046,466,"MLI","Mali","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2000/mli_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
39047,466,"MLI","Mali","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2000/mli_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
39048,466,"MLI","Mali","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2000/mli_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
39049,466,"MLI","Mali","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2000/mli_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
39050,466,"MLI","Mali","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2000/mli_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
39051,466,"MLI","Mali","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2000/mli_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
39052,466,"MLI","Mali","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2000/mli_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
39053,466,"MLI","Mali","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2001/mli_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
39054,466,"MLI","Mali","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2001/mli_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
39055,466,"MLI","Mali","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2001/mli_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
39056,466,"MLI","Mali","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2001/mli_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
39057,466,"MLI","Mali","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2001/mli_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
39058,466,"MLI","Mali","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2001/mli_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
39059,466,"MLI","Mali","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2001/mli_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
39060,466,"MLI","Mali","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2001/mli_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
39061,466,"MLI","Mali","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2002/mli_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
39062,466,"MLI","Mali","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2002/mli_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
39063,466,"MLI","Mali","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2002/mli_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
39064,466,"MLI","Mali","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2002/mli_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
39065,466,"MLI","Mali","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2002/mli_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
39066,466,"MLI","Mali","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2002/mli_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
39067,466,"MLI","Mali","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2002/mli_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
39068,466,"MLI","Mali","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2002/mli_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
39069,466,"MLI","Mali","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2003/mli_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
39070,466,"MLI","Mali","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2003/mli_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
39071,466,"MLI","Mali","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2003/mli_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
39072,466,"MLI","Mali","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2003/mli_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
39073,466,"MLI","Mali","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2003/mli_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
39074,466,"MLI","Mali","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2003/mli_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
39075,466,"MLI","Mali","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2003/mli_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
39076,466,"MLI","Mali","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2003/mli_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
39077,466,"MLI","Mali","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2004/mli_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
39078,466,"MLI","Mali","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2004/mli_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
39079,466,"MLI","Mali","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2004/mli_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
39080,466,"MLI","Mali","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2004/mli_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
39081,466,"MLI","Mali","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2004/mli_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
39082,466,"MLI","Mali","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2004/mli_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
39083,466,"MLI","Mali","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2004/mli_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
39084,466,"MLI","Mali","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2004/mli_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
39085,466,"MLI","Mali","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2005/mli_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
39086,466,"MLI","Mali","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2005/mli_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
39087,466,"MLI","Mali","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2005/mli_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
39088,466,"MLI","Mali","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2005/mli_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
39089,466,"MLI","Mali","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2005/mli_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
39090,466,"MLI","Mali","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2005/mli_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
39091,466,"MLI","Mali","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2005/mli_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
39092,466,"MLI","Mali","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2005/mli_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
39093,466,"MLI","Mali","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2006/mli_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
39094,466,"MLI","Mali","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2006/mli_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
39095,466,"MLI","Mali","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2006/mli_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
39096,466,"MLI","Mali","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2006/mli_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
39097,466,"MLI","Mali","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2006/mli_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
39098,466,"MLI","Mali","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2006/mli_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
39099,466,"MLI","Mali","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2006/mli_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
39100,466,"MLI","Mali","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2006/mli_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
39101,466,"MLI","Mali","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2007/mli_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
39102,466,"MLI","Mali","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2007/mli_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
39103,466,"MLI","Mali","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2007/mli_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
39104,466,"MLI","Mali","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2007/mli_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
39105,466,"MLI","Mali","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2007/mli_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
39106,466,"MLI","Mali","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2007/mli_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
39107,466,"MLI","Mali","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2007/mli_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
39108,466,"MLI","Mali","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2007/mli_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
39109,466,"MLI","Mali","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2008/mli_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
39110,466,"MLI","Mali","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2008/mli_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
39111,466,"MLI","Mali","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2008/mli_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
39112,466,"MLI","Mali","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2008/mli_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
39113,466,"MLI","Mali","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2008/mli_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
39114,466,"MLI","Mali","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2008/mli_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
39115,466,"MLI","Mali","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2008/mli_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
39116,466,"MLI","Mali","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2008/mli_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
39117,466,"MLI","Mali","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2009/mli_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
39118,466,"MLI","Mali","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2009/mli_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
39119,466,"MLI","Mali","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2009/mli_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
39120,466,"MLI","Mali","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2009/mli_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
39121,466,"MLI","Mali","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2009/mli_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
39122,466,"MLI","Mali","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2009/mli_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
39123,466,"MLI","Mali","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2009/mli_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
39124,466,"MLI","Mali","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2009/mli_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
39125,466,"MLI","Mali","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2010/mli_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
39126,466,"MLI","Mali","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2010/mli_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
39127,466,"MLI","Mali","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2010/mli_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
39128,466,"MLI","Mali","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2010/mli_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
39129,466,"MLI","Mali","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2010/mli_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
39130,466,"MLI","Mali","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2010/mli_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
39131,466,"MLI","Mali","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2010/mli_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
39132,466,"MLI","Mali","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2010/mli_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
39133,466,"MLI","Mali","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2011/mli_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
39134,466,"MLI","Mali","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2011/mli_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
39135,466,"MLI","Mali","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2011/mli_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
39136,466,"MLI","Mali","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2011/mli_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
39137,466,"MLI","Mali","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2011/mli_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
39138,466,"MLI","Mali","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2011/mli_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
39139,466,"MLI","Mali","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2011/mli_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
39140,466,"MLI","Mali","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2011/mli_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
39141,466,"MLI","Mali","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2012/mli_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
39142,466,"MLI","Mali","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2012/mli_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
39143,466,"MLI","Mali","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2012/mli_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
39144,466,"MLI","Mali","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2012/mli_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
39145,466,"MLI","Mali","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2012/mli_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
39146,466,"MLI","Mali","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2012/mli_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
39147,466,"MLI","Mali","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2012/mli_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
39148,466,"MLI","Mali","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2012/mli_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
39149,466,"MLI","Mali","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2013/mli_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
39150,466,"MLI","Mali","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2013/mli_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
39151,466,"MLI","Mali","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2013/mli_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
39152,466,"MLI","Mali","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2013/mli_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
39153,466,"MLI","Mali","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2013/mli_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
39154,466,"MLI","Mali","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2013/mli_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
39155,466,"MLI","Mali","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2013/mli_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
39156,466,"MLI","Mali","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2013/mli_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
39157,466,"MLI","Mali","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2014/mli_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
39158,466,"MLI","Mali","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2014/mli_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
39159,466,"MLI","Mali","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2014/mli_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
39160,466,"MLI","Mali","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2014/mli_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
39161,466,"MLI","Mali","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2014/mli_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
39162,466,"MLI","Mali","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2014/mli_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
39163,466,"MLI","Mali","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2014/mli_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
39164,466,"MLI","Mali","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2014/mli_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
39165,466,"MLI","Mali","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2015/mli_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
39166,466,"MLI","Mali","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2015/mli_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
39167,466,"MLI","Mali","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2015/mli_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
39168,466,"MLI","Mali","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2015/mli_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
39169,466,"MLI","Mali","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2015/mli_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
39170,466,"MLI","Mali","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2015/mli_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
39171,466,"MLI","Mali","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2015/mli_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
39172,466,"MLI","Mali","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Annual/2015/mli_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
39173,470,"MLT","Malta","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2000/mlt_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
39174,470,"MLT","Malta","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2000/mlt_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
39175,470,"MLT","Malta","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2000/mlt_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
39176,470,"MLT","Malta","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2000/mlt_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
39177,470,"MLT","Malta","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2000/mlt_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
39178,470,"MLT","Malta","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2000/mlt_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
39179,470,"MLT","Malta","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2000/mlt_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
39180,470,"MLT","Malta","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2000/mlt_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
39181,470,"MLT","Malta","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2001/mlt_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
39182,470,"MLT","Malta","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2001/mlt_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
39183,470,"MLT","Malta","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2001/mlt_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
39184,470,"MLT","Malta","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2001/mlt_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
39185,470,"MLT","Malta","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2001/mlt_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
39186,470,"MLT","Malta","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2001/mlt_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
39187,470,"MLT","Malta","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2001/mlt_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
39188,470,"MLT","Malta","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2001/mlt_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
39189,470,"MLT","Malta","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2002/mlt_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
39190,470,"MLT","Malta","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2002/mlt_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
39191,470,"MLT","Malta","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2002/mlt_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
39192,470,"MLT","Malta","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2002/mlt_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
39193,470,"MLT","Malta","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2002/mlt_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
39194,470,"MLT","Malta","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2002/mlt_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
39195,470,"MLT","Malta","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2002/mlt_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
39196,470,"MLT","Malta","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2002/mlt_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
39197,470,"MLT","Malta","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2003/mlt_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
39198,470,"MLT","Malta","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2003/mlt_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
39199,470,"MLT","Malta","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2003/mlt_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
39200,470,"MLT","Malta","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2003/mlt_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
39201,470,"MLT","Malta","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2003/mlt_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
39202,470,"MLT","Malta","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2003/mlt_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
39203,470,"MLT","Malta","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2003/mlt_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
39204,470,"MLT","Malta","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2003/mlt_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
39205,470,"MLT","Malta","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2004/mlt_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
39206,470,"MLT","Malta","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2004/mlt_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
39207,470,"MLT","Malta","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2004/mlt_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
39208,470,"MLT","Malta","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2004/mlt_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
39209,470,"MLT","Malta","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2004/mlt_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
39210,470,"MLT","Malta","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2004/mlt_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
39211,470,"MLT","Malta","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2004/mlt_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
39212,470,"MLT","Malta","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2004/mlt_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
39213,470,"MLT","Malta","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2005/mlt_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
39214,470,"MLT","Malta","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2005/mlt_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
39215,470,"MLT","Malta","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2005/mlt_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
39216,470,"MLT","Malta","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2005/mlt_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
39217,470,"MLT","Malta","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2005/mlt_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
39218,470,"MLT","Malta","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2005/mlt_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
39219,470,"MLT","Malta","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2005/mlt_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
39220,470,"MLT","Malta","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2005/mlt_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
39221,470,"MLT","Malta","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2006/mlt_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
39222,470,"MLT","Malta","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2006/mlt_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
39223,470,"MLT","Malta","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2006/mlt_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
39224,470,"MLT","Malta","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2006/mlt_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
39225,470,"MLT","Malta","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2006/mlt_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
39226,470,"MLT","Malta","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2006/mlt_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
39227,470,"MLT","Malta","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2006/mlt_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
39228,470,"MLT","Malta","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2006/mlt_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
39229,470,"MLT","Malta","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2007/mlt_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
39230,470,"MLT","Malta","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2007/mlt_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
39231,470,"MLT","Malta","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2007/mlt_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
39232,470,"MLT","Malta","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2007/mlt_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
39233,470,"MLT","Malta","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2007/mlt_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
39234,470,"MLT","Malta","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2007/mlt_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
39235,470,"MLT","Malta","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2007/mlt_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
39236,470,"MLT","Malta","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2007/mlt_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
39237,470,"MLT","Malta","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2008/mlt_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
39238,470,"MLT","Malta","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2008/mlt_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
39239,470,"MLT","Malta","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2008/mlt_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
39240,470,"MLT","Malta","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2008/mlt_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
39241,470,"MLT","Malta","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2008/mlt_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
39242,470,"MLT","Malta","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2008/mlt_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
39243,470,"MLT","Malta","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2008/mlt_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
39244,470,"MLT","Malta","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2008/mlt_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
39245,470,"MLT","Malta","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2009/mlt_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
39246,470,"MLT","Malta","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2009/mlt_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
39247,470,"MLT","Malta","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2009/mlt_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
39248,470,"MLT","Malta","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2009/mlt_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
39249,470,"MLT","Malta","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2009/mlt_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
39250,470,"MLT","Malta","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2009/mlt_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
39251,470,"MLT","Malta","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2009/mlt_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
39252,470,"MLT","Malta","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2009/mlt_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
39253,470,"MLT","Malta","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2010/mlt_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
39254,470,"MLT","Malta","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2010/mlt_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
39255,470,"MLT","Malta","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2010/mlt_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
39256,470,"MLT","Malta","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2010/mlt_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
39257,470,"MLT","Malta","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2010/mlt_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
39258,470,"MLT","Malta","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2010/mlt_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
39259,470,"MLT","Malta","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2010/mlt_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
39260,470,"MLT","Malta","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2010/mlt_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
39261,470,"MLT","Malta","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2011/mlt_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
39262,470,"MLT","Malta","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2011/mlt_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
39263,470,"MLT","Malta","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2011/mlt_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
39264,470,"MLT","Malta","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2011/mlt_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
39265,470,"MLT","Malta","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2011/mlt_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
39266,470,"MLT","Malta","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2011/mlt_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
39267,470,"MLT","Malta","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2011/mlt_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
39268,470,"MLT","Malta","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2011/mlt_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
39269,470,"MLT","Malta","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2012/mlt_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
39270,470,"MLT","Malta","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2012/mlt_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
39271,470,"MLT","Malta","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2012/mlt_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
39272,470,"MLT","Malta","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2012/mlt_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
39273,470,"MLT","Malta","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2012/mlt_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
39274,470,"MLT","Malta","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2012/mlt_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
39275,470,"MLT","Malta","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2012/mlt_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
39276,470,"MLT","Malta","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2012/mlt_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
39277,470,"MLT","Malta","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2013/mlt_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
39278,470,"MLT","Malta","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2013/mlt_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
39279,470,"MLT","Malta","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2013/mlt_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
39280,470,"MLT","Malta","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2013/mlt_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
39281,470,"MLT","Malta","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2013/mlt_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
39282,470,"MLT","Malta","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2013/mlt_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
39283,470,"MLT","Malta","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2013/mlt_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
39284,470,"MLT","Malta","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2013/mlt_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
39285,470,"MLT","Malta","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2014/mlt_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
39286,470,"MLT","Malta","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2014/mlt_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
39287,470,"MLT","Malta","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2014/mlt_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
39288,470,"MLT","Malta","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2014/mlt_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
39289,470,"MLT","Malta","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2014/mlt_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
39290,470,"MLT","Malta","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2014/mlt_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
39291,470,"MLT","Malta","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2014/mlt_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
39292,470,"MLT","Malta","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2014/mlt_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
39293,470,"MLT","Malta","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2015/mlt_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
39294,470,"MLT","Malta","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2015/mlt_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
39295,470,"MLT","Malta","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2015/mlt_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
39296,470,"MLT","Malta","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2015/mlt_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
39297,470,"MLT","Malta","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2015/mlt_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
39298,470,"MLT","Malta","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2015/mlt_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
39299,470,"MLT","Malta","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2015/mlt_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
39300,470,"MLT","Malta","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Annual/2015/mlt_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
39301,474,"MTQ","Martinique","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2000/mtq_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
39302,474,"MTQ","Martinique","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2000/mtq_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
39303,474,"MTQ","Martinique","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2000/mtq_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
39304,474,"MTQ","Martinique","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2000/mtq_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
39305,474,"MTQ","Martinique","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2000/mtq_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
39306,474,"MTQ","Martinique","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2000/mtq_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
39307,474,"MTQ","Martinique","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2000/mtq_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
39308,474,"MTQ","Martinique","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2000/mtq_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
39309,474,"MTQ","Martinique","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2001/mtq_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
39310,474,"MTQ","Martinique","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2001/mtq_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
39311,474,"MTQ","Martinique","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2001/mtq_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
39312,474,"MTQ","Martinique","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2001/mtq_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
39313,474,"MTQ","Martinique","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2001/mtq_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
39314,474,"MTQ","Martinique","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2001/mtq_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
39315,474,"MTQ","Martinique","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2001/mtq_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
39316,474,"MTQ","Martinique","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2001/mtq_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
39317,474,"MTQ","Martinique","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2002/mtq_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
39318,474,"MTQ","Martinique","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2002/mtq_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
39319,474,"MTQ","Martinique","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2002/mtq_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
39320,474,"MTQ","Martinique","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2002/mtq_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
39321,474,"MTQ","Martinique","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2002/mtq_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
39322,474,"MTQ","Martinique","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2002/mtq_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
39323,474,"MTQ","Martinique","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2002/mtq_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
39324,474,"MTQ","Martinique","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2002/mtq_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
39325,474,"MTQ","Martinique","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2003/mtq_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
39326,474,"MTQ","Martinique","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2003/mtq_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
39327,474,"MTQ","Martinique","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2003/mtq_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
39328,474,"MTQ","Martinique","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2003/mtq_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
39329,474,"MTQ","Martinique","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2003/mtq_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
39330,474,"MTQ","Martinique","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2003/mtq_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
39331,474,"MTQ","Martinique","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2003/mtq_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
39332,474,"MTQ","Martinique","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2003/mtq_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
39333,474,"MTQ","Martinique","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2004/mtq_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
39334,474,"MTQ","Martinique","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2004/mtq_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
39335,474,"MTQ","Martinique","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2004/mtq_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
39336,474,"MTQ","Martinique","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2004/mtq_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
39337,474,"MTQ","Martinique","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2004/mtq_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
39338,474,"MTQ","Martinique","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2004/mtq_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
39339,474,"MTQ","Martinique","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2004/mtq_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
39340,474,"MTQ","Martinique","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2004/mtq_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
39341,474,"MTQ","Martinique","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2005/mtq_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
39342,474,"MTQ","Martinique","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2005/mtq_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
39343,474,"MTQ","Martinique","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2005/mtq_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
39344,474,"MTQ","Martinique","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2005/mtq_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
39345,474,"MTQ","Martinique","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2005/mtq_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
39346,474,"MTQ","Martinique","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2005/mtq_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
39347,474,"MTQ","Martinique","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2005/mtq_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
39348,474,"MTQ","Martinique","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2005/mtq_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
39349,474,"MTQ","Martinique","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2006/mtq_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
39350,474,"MTQ","Martinique","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2006/mtq_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
39351,474,"MTQ","Martinique","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2006/mtq_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
39352,474,"MTQ","Martinique","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2006/mtq_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
39353,474,"MTQ","Martinique","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2006/mtq_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
39354,474,"MTQ","Martinique","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2006/mtq_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
39355,474,"MTQ","Martinique","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2006/mtq_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
39356,474,"MTQ","Martinique","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2006/mtq_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
39357,474,"MTQ","Martinique","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2007/mtq_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
39358,474,"MTQ","Martinique","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2007/mtq_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
39359,474,"MTQ","Martinique","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2007/mtq_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
39360,474,"MTQ","Martinique","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2007/mtq_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
39361,474,"MTQ","Martinique","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2007/mtq_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
39362,474,"MTQ","Martinique","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2007/mtq_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
39363,474,"MTQ","Martinique","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2007/mtq_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
39364,474,"MTQ","Martinique","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2007/mtq_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
39365,474,"MTQ","Martinique","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2008/mtq_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
39366,474,"MTQ","Martinique","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2008/mtq_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
39367,474,"MTQ","Martinique","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2008/mtq_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
39368,474,"MTQ","Martinique","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2008/mtq_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
39369,474,"MTQ","Martinique","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2008/mtq_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
39370,474,"MTQ","Martinique","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2008/mtq_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
39371,474,"MTQ","Martinique","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2008/mtq_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
39372,474,"MTQ","Martinique","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2008/mtq_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
39373,474,"MTQ","Martinique","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2009/mtq_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
39374,474,"MTQ","Martinique","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2009/mtq_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
39375,474,"MTQ","Martinique","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2009/mtq_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
39376,474,"MTQ","Martinique","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2009/mtq_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
39377,474,"MTQ","Martinique","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2009/mtq_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
39378,474,"MTQ","Martinique","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2009/mtq_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
39379,474,"MTQ","Martinique","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2009/mtq_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
39380,474,"MTQ","Martinique","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2009/mtq_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
39381,474,"MTQ","Martinique","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2010/mtq_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
39382,474,"MTQ","Martinique","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2010/mtq_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
39383,474,"MTQ","Martinique","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2010/mtq_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
39384,474,"MTQ","Martinique","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2010/mtq_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
39385,474,"MTQ","Martinique","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2010/mtq_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
39386,474,"MTQ","Martinique","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2010/mtq_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
39387,474,"MTQ","Martinique","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2010/mtq_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
39388,474,"MTQ","Martinique","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2010/mtq_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
39389,474,"MTQ","Martinique","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2011/mtq_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
39390,474,"MTQ","Martinique","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2011/mtq_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
39391,474,"MTQ","Martinique","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2011/mtq_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
39392,474,"MTQ","Martinique","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2011/mtq_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
39393,474,"MTQ","Martinique","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2011/mtq_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
39394,474,"MTQ","Martinique","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2011/mtq_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
39395,474,"MTQ","Martinique","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2011/mtq_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
39396,474,"MTQ","Martinique","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2011/mtq_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
39397,474,"MTQ","Martinique","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2012/mtq_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
39398,474,"MTQ","Martinique","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2012/mtq_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
39399,474,"MTQ","Martinique","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2012/mtq_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
39400,474,"MTQ","Martinique","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2012/mtq_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
39401,474,"MTQ","Martinique","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2012/mtq_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
39402,474,"MTQ","Martinique","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2012/mtq_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
39403,474,"MTQ","Martinique","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2012/mtq_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
39404,474,"MTQ","Martinique","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2012/mtq_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
39405,474,"MTQ","Martinique","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2013/mtq_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
39406,474,"MTQ","Martinique","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2013/mtq_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
39407,474,"MTQ","Martinique","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2013/mtq_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
39408,474,"MTQ","Martinique","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2013/mtq_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
39409,474,"MTQ","Martinique","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2013/mtq_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
39410,474,"MTQ","Martinique","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2013/mtq_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
39411,474,"MTQ","Martinique","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2013/mtq_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
39412,474,"MTQ","Martinique","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2013/mtq_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
39413,474,"MTQ","Martinique","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2014/mtq_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
39414,474,"MTQ","Martinique","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2014/mtq_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
39415,474,"MTQ","Martinique","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2014/mtq_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
39416,474,"MTQ","Martinique","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2014/mtq_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
39417,474,"MTQ","Martinique","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2014/mtq_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
39418,474,"MTQ","Martinique","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2014/mtq_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
39419,474,"MTQ","Martinique","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2014/mtq_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
39420,474,"MTQ","Martinique","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2014/mtq_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
39421,474,"MTQ","Martinique","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2015/mtq_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
39422,474,"MTQ","Martinique","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2015/mtq_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
39423,474,"MTQ","Martinique","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2015/mtq_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
39424,474,"MTQ","Martinique","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2015/mtq_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
39425,474,"MTQ","Martinique","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2015/mtq_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
39426,474,"MTQ","Martinique","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2015/mtq_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
39427,474,"MTQ","Martinique","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2015/mtq_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
39428,474,"MTQ","Martinique","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Annual/2015/mtq_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
39429,478,"MRT","Mauritania","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2000/mrt_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
39430,478,"MRT","Mauritania","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2000/mrt_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
39431,478,"MRT","Mauritania","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2000/mrt_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
39432,478,"MRT","Mauritania","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2000/mrt_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
39433,478,"MRT","Mauritania","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2000/mrt_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
39434,478,"MRT","Mauritania","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2000/mrt_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
39435,478,"MRT","Mauritania","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2000/mrt_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
39436,478,"MRT","Mauritania","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2000/mrt_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
39437,478,"MRT","Mauritania","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2001/mrt_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
39438,478,"MRT","Mauritania","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2001/mrt_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
39439,478,"MRT","Mauritania","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2001/mrt_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
39440,478,"MRT","Mauritania","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2001/mrt_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
39441,478,"MRT","Mauritania","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2001/mrt_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
39442,478,"MRT","Mauritania","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2001/mrt_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
39443,478,"MRT","Mauritania","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2001/mrt_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
39444,478,"MRT","Mauritania","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2001/mrt_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
39445,478,"MRT","Mauritania","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2002/mrt_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
39446,478,"MRT","Mauritania","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2002/mrt_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
39447,478,"MRT","Mauritania","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2002/mrt_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
39448,478,"MRT","Mauritania","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2002/mrt_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
39449,478,"MRT","Mauritania","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2002/mrt_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
39450,478,"MRT","Mauritania","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2002/mrt_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
39451,478,"MRT","Mauritania","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2002/mrt_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
39452,478,"MRT","Mauritania","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2002/mrt_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
39453,478,"MRT","Mauritania","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2003/mrt_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
39454,478,"MRT","Mauritania","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2003/mrt_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
39455,478,"MRT","Mauritania","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2003/mrt_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
39456,478,"MRT","Mauritania","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2003/mrt_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
39457,478,"MRT","Mauritania","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2003/mrt_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
39458,478,"MRT","Mauritania","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2003/mrt_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
39459,478,"MRT","Mauritania","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2003/mrt_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
39460,478,"MRT","Mauritania","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2003/mrt_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
39461,478,"MRT","Mauritania","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2004/mrt_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
39462,478,"MRT","Mauritania","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2004/mrt_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
39463,478,"MRT","Mauritania","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2004/mrt_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
39464,478,"MRT","Mauritania","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2004/mrt_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
39465,478,"MRT","Mauritania","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2004/mrt_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
39466,478,"MRT","Mauritania","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2004/mrt_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
39467,478,"MRT","Mauritania","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2004/mrt_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
39468,478,"MRT","Mauritania","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2004/mrt_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
39469,478,"MRT","Mauritania","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2005/mrt_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
39470,478,"MRT","Mauritania","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2005/mrt_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
39471,478,"MRT","Mauritania","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2005/mrt_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
39472,478,"MRT","Mauritania","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2005/mrt_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
39473,478,"MRT","Mauritania","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2005/mrt_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
39474,478,"MRT","Mauritania","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2005/mrt_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
39475,478,"MRT","Mauritania","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2005/mrt_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
39476,478,"MRT","Mauritania","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2005/mrt_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
39477,478,"MRT","Mauritania","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2006/mrt_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
39478,478,"MRT","Mauritania","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2006/mrt_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
39479,478,"MRT","Mauritania","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2006/mrt_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
39480,478,"MRT","Mauritania","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2006/mrt_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
39481,478,"MRT","Mauritania","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2006/mrt_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
39482,478,"MRT","Mauritania","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2006/mrt_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
39483,478,"MRT","Mauritania","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2006/mrt_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
39484,478,"MRT","Mauritania","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2006/mrt_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
39485,478,"MRT","Mauritania","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2007/mrt_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
39486,478,"MRT","Mauritania","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2007/mrt_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
39487,478,"MRT","Mauritania","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2007/mrt_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
39488,478,"MRT","Mauritania","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2007/mrt_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
39489,478,"MRT","Mauritania","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2007/mrt_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
39490,478,"MRT","Mauritania","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2007/mrt_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
39491,478,"MRT","Mauritania","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2007/mrt_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
39492,478,"MRT","Mauritania","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2007/mrt_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
39493,478,"MRT","Mauritania","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2008/mrt_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
39494,478,"MRT","Mauritania","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2008/mrt_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
39495,478,"MRT","Mauritania","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2008/mrt_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
39496,478,"MRT","Mauritania","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2008/mrt_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
39497,478,"MRT","Mauritania","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2008/mrt_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
39498,478,"MRT","Mauritania","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2008/mrt_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
39499,478,"MRT","Mauritania","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2008/mrt_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
39500,478,"MRT","Mauritania","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2008/mrt_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
39501,478,"MRT","Mauritania","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2009/mrt_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
39502,478,"MRT","Mauritania","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2009/mrt_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
39503,478,"MRT","Mauritania","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2009/mrt_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
39504,478,"MRT","Mauritania","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2009/mrt_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
39505,478,"MRT","Mauritania","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2009/mrt_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
39506,478,"MRT","Mauritania","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2009/mrt_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
39507,478,"MRT","Mauritania","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2009/mrt_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
39508,478,"MRT","Mauritania","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2009/mrt_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
39509,478,"MRT","Mauritania","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2010/mrt_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
39510,478,"MRT","Mauritania","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2010/mrt_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
39511,478,"MRT","Mauritania","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2010/mrt_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
39512,478,"MRT","Mauritania","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2010/mrt_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
39513,478,"MRT","Mauritania","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2010/mrt_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
39514,478,"MRT","Mauritania","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2010/mrt_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
39515,478,"MRT","Mauritania","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2010/mrt_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
39516,478,"MRT","Mauritania","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2010/mrt_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
39517,478,"MRT","Mauritania","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2011/mrt_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
39518,478,"MRT","Mauritania","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2011/mrt_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
39519,478,"MRT","Mauritania","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2011/mrt_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
39520,478,"MRT","Mauritania","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2011/mrt_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
39521,478,"MRT","Mauritania","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2011/mrt_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
39522,478,"MRT","Mauritania","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2011/mrt_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
39523,478,"MRT","Mauritania","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2011/mrt_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
39524,478,"MRT","Mauritania","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2011/mrt_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
39525,478,"MRT","Mauritania","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2012/mrt_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
39526,478,"MRT","Mauritania","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2012/mrt_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
39527,478,"MRT","Mauritania","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2012/mrt_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
39528,478,"MRT","Mauritania","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2012/mrt_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
39529,478,"MRT","Mauritania","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2012/mrt_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
39530,478,"MRT","Mauritania","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2012/mrt_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
39531,478,"MRT","Mauritania","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2012/mrt_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
39532,478,"MRT","Mauritania","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2012/mrt_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
39533,478,"MRT","Mauritania","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2013/mrt_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
39534,478,"MRT","Mauritania","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2013/mrt_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
39535,478,"MRT","Mauritania","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2013/mrt_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
39536,478,"MRT","Mauritania","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2013/mrt_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
39537,478,"MRT","Mauritania","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2013/mrt_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
39538,478,"MRT","Mauritania","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2013/mrt_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
39539,478,"MRT","Mauritania","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2013/mrt_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
39540,478,"MRT","Mauritania","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2013/mrt_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
39541,478,"MRT","Mauritania","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2014/mrt_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
39542,478,"MRT","Mauritania","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2014/mrt_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
39543,478,"MRT","Mauritania","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2014/mrt_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
39544,478,"MRT","Mauritania","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2014/mrt_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
39545,478,"MRT","Mauritania","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2014/mrt_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
39546,478,"MRT","Mauritania","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2014/mrt_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
39547,478,"MRT","Mauritania","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2014/mrt_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
39548,478,"MRT","Mauritania","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2014/mrt_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
39549,478,"MRT","Mauritania","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2015/mrt_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
39550,478,"MRT","Mauritania","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2015/mrt_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
39551,478,"MRT","Mauritania","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2015/mrt_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
39552,478,"MRT","Mauritania","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2015/mrt_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
39553,478,"MRT","Mauritania","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2015/mrt_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
39554,478,"MRT","Mauritania","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2015/mrt_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
39555,478,"MRT","Mauritania","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2015/mrt_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
39556,478,"MRT","Mauritania","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Annual/2015/mrt_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
39557,480,"MUS","Mauritius","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2000/mus_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
39558,480,"MUS","Mauritius","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2000/mus_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
39559,480,"MUS","Mauritius","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2000/mus_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
39560,480,"MUS","Mauritius","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2000/mus_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
39561,480,"MUS","Mauritius","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2000/mus_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
39562,480,"MUS","Mauritius","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2000/mus_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
39563,480,"MUS","Mauritius","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2000/mus_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
39564,480,"MUS","Mauritius","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2000/mus_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
39565,480,"MUS","Mauritius","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2001/mus_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
39566,480,"MUS","Mauritius","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2001/mus_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
39567,480,"MUS","Mauritius","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2001/mus_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
39568,480,"MUS","Mauritius","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2001/mus_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
39569,480,"MUS","Mauritius","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2001/mus_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
39570,480,"MUS","Mauritius","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2001/mus_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
39571,480,"MUS","Mauritius","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2001/mus_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
39572,480,"MUS","Mauritius","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2001/mus_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
39573,480,"MUS","Mauritius","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2002/mus_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
39574,480,"MUS","Mauritius","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2002/mus_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
39575,480,"MUS","Mauritius","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2002/mus_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
39576,480,"MUS","Mauritius","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2002/mus_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
39577,480,"MUS","Mauritius","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2002/mus_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
39578,480,"MUS","Mauritius","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2002/mus_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
39579,480,"MUS","Mauritius","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2002/mus_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
39580,480,"MUS","Mauritius","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2002/mus_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
39581,480,"MUS","Mauritius","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2003/mus_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
39582,480,"MUS","Mauritius","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2003/mus_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
39583,480,"MUS","Mauritius","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2003/mus_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
39584,480,"MUS","Mauritius","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2003/mus_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
39585,480,"MUS","Mauritius","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2003/mus_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
39586,480,"MUS","Mauritius","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2003/mus_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
39587,480,"MUS","Mauritius","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2003/mus_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
39588,480,"MUS","Mauritius","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2003/mus_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
39589,480,"MUS","Mauritius","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2004/mus_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
39590,480,"MUS","Mauritius","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2004/mus_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
39591,480,"MUS","Mauritius","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2004/mus_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
39592,480,"MUS","Mauritius","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2004/mus_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
39593,480,"MUS","Mauritius","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2004/mus_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
39594,480,"MUS","Mauritius","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2004/mus_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
39595,480,"MUS","Mauritius","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2004/mus_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
39596,480,"MUS","Mauritius","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2004/mus_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
39597,480,"MUS","Mauritius","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2005/mus_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
39598,480,"MUS","Mauritius","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2005/mus_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
39599,480,"MUS","Mauritius","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2005/mus_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
39600,480,"MUS","Mauritius","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2005/mus_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
39601,480,"MUS","Mauritius","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2005/mus_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
39602,480,"MUS","Mauritius","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2005/mus_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
39603,480,"MUS","Mauritius","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2005/mus_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
39604,480,"MUS","Mauritius","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2005/mus_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
39605,480,"MUS","Mauritius","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2006/mus_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
39606,480,"MUS","Mauritius","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2006/mus_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
39607,480,"MUS","Mauritius","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2006/mus_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
39608,480,"MUS","Mauritius","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2006/mus_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
39609,480,"MUS","Mauritius","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2006/mus_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
39610,480,"MUS","Mauritius","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2006/mus_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
39611,480,"MUS","Mauritius","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2006/mus_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
39612,480,"MUS","Mauritius","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2006/mus_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
39613,480,"MUS","Mauritius","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2007/mus_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
39614,480,"MUS","Mauritius","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2007/mus_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
39615,480,"MUS","Mauritius","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2007/mus_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
39616,480,"MUS","Mauritius","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2007/mus_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
39617,480,"MUS","Mauritius","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2007/mus_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
39618,480,"MUS","Mauritius","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2007/mus_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
39619,480,"MUS","Mauritius","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2007/mus_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
39620,480,"MUS","Mauritius","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2007/mus_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
39621,480,"MUS","Mauritius","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2008/mus_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
39622,480,"MUS","Mauritius","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2008/mus_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
39623,480,"MUS","Mauritius","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2008/mus_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
39624,480,"MUS","Mauritius","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2008/mus_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
39625,480,"MUS","Mauritius","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2008/mus_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
39626,480,"MUS","Mauritius","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2008/mus_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
39627,480,"MUS","Mauritius","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2008/mus_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
39628,480,"MUS","Mauritius","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2008/mus_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
39629,480,"MUS","Mauritius","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2009/mus_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
39630,480,"MUS","Mauritius","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2009/mus_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
39631,480,"MUS","Mauritius","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2009/mus_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
39632,480,"MUS","Mauritius","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2009/mus_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
39633,480,"MUS","Mauritius","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2009/mus_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
39634,480,"MUS","Mauritius","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2009/mus_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
39635,480,"MUS","Mauritius","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2009/mus_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
39636,480,"MUS","Mauritius","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2009/mus_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
39637,480,"MUS","Mauritius","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2010/mus_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
39638,480,"MUS","Mauritius","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2010/mus_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
39639,480,"MUS","Mauritius","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2010/mus_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
39640,480,"MUS","Mauritius","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2010/mus_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
39641,480,"MUS","Mauritius","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2010/mus_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
39642,480,"MUS","Mauritius","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2010/mus_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
39643,480,"MUS","Mauritius","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2010/mus_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
39644,480,"MUS","Mauritius","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2010/mus_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
39645,480,"MUS","Mauritius","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2011/mus_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
39646,480,"MUS","Mauritius","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2011/mus_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
39647,480,"MUS","Mauritius","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2011/mus_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
39648,480,"MUS","Mauritius","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2011/mus_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
39649,480,"MUS","Mauritius","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2011/mus_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
39650,480,"MUS","Mauritius","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2011/mus_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
39651,480,"MUS","Mauritius","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2011/mus_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
39652,480,"MUS","Mauritius","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2011/mus_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
39653,480,"MUS","Mauritius","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2012/mus_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
39654,480,"MUS","Mauritius","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2012/mus_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
39655,480,"MUS","Mauritius","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2012/mus_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
39656,480,"MUS","Mauritius","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2012/mus_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
39657,480,"MUS","Mauritius","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2012/mus_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
39658,480,"MUS","Mauritius","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2012/mus_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
39659,480,"MUS","Mauritius","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2012/mus_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
39660,480,"MUS","Mauritius","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2012/mus_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
39661,480,"MUS","Mauritius","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2013/mus_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
39662,480,"MUS","Mauritius","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2013/mus_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
39663,480,"MUS","Mauritius","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2013/mus_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
39664,480,"MUS","Mauritius","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2013/mus_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
39665,480,"MUS","Mauritius","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2013/mus_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
39666,480,"MUS","Mauritius","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2013/mus_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
39667,480,"MUS","Mauritius","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2013/mus_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
39668,480,"MUS","Mauritius","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2013/mus_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
39669,480,"MUS","Mauritius","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2014/mus_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
39670,480,"MUS","Mauritius","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2014/mus_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
39671,480,"MUS","Mauritius","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2014/mus_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
39672,480,"MUS","Mauritius","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2014/mus_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
39673,480,"MUS","Mauritius","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2014/mus_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
39674,480,"MUS","Mauritius","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2014/mus_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
39675,480,"MUS","Mauritius","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2014/mus_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
39676,480,"MUS","Mauritius","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2014/mus_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
39677,480,"MUS","Mauritius","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2015/mus_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
39678,480,"MUS","Mauritius","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2015/mus_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
39679,480,"MUS","Mauritius","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2015/mus_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
39680,480,"MUS","Mauritius","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2015/mus_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
39681,480,"MUS","Mauritius","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2015/mus_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
39682,480,"MUS","Mauritius","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2015/mus_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
39683,480,"MUS","Mauritius","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2015/mus_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
39684,480,"MUS","Mauritius","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Annual/2015/mus_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
39685,484,"MEX","Mexico","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2000/mex_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
39686,484,"MEX","Mexico","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2000/mex_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
39687,484,"MEX","Mexico","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2000/mex_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
39688,484,"MEX","Mexico","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2000/mex_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
39689,484,"MEX","Mexico","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2000/mex_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
39690,484,"MEX","Mexico","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2000/mex_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
39691,484,"MEX","Mexico","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2000/mex_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
39692,484,"MEX","Mexico","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2000/mex_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
39693,484,"MEX","Mexico","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2001/mex_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
39694,484,"MEX","Mexico","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2001/mex_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
39695,484,"MEX","Mexico","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2001/mex_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
39696,484,"MEX","Mexico","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2001/mex_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
39697,484,"MEX","Mexico","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2001/mex_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
39698,484,"MEX","Mexico","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2001/mex_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
39699,484,"MEX","Mexico","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2001/mex_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
39700,484,"MEX","Mexico","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2001/mex_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
39701,484,"MEX","Mexico","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2002/mex_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
39702,484,"MEX","Mexico","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2002/mex_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
39703,484,"MEX","Mexico","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2002/mex_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
39704,484,"MEX","Mexico","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2002/mex_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
39705,484,"MEX","Mexico","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2002/mex_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
39706,484,"MEX","Mexico","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2002/mex_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
39707,484,"MEX","Mexico","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2002/mex_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
39708,484,"MEX","Mexico","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2002/mex_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
39709,484,"MEX","Mexico","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2003/mex_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
39710,484,"MEX","Mexico","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2003/mex_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
39711,484,"MEX","Mexico","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2003/mex_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
39712,484,"MEX","Mexico","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2003/mex_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
39713,484,"MEX","Mexico","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2003/mex_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
39714,484,"MEX","Mexico","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2003/mex_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
39715,484,"MEX","Mexico","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2003/mex_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
39716,484,"MEX","Mexico","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2003/mex_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
39717,484,"MEX","Mexico","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2004/mex_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
39718,484,"MEX","Mexico","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2004/mex_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
39719,484,"MEX","Mexico","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2004/mex_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
39720,484,"MEX","Mexico","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2004/mex_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
39721,484,"MEX","Mexico","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2004/mex_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
39722,484,"MEX","Mexico","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2004/mex_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
39723,484,"MEX","Mexico","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2004/mex_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
39724,484,"MEX","Mexico","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2004/mex_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
39725,484,"MEX","Mexico","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2005/mex_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
39726,484,"MEX","Mexico","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2005/mex_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
39727,484,"MEX","Mexico","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2005/mex_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
39728,484,"MEX","Mexico","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2005/mex_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
39729,484,"MEX","Mexico","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2005/mex_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
39730,484,"MEX","Mexico","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2005/mex_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
39731,484,"MEX","Mexico","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2005/mex_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
39732,484,"MEX","Mexico","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2005/mex_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
39733,484,"MEX","Mexico","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2006/mex_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
39734,484,"MEX","Mexico","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2006/mex_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
39735,484,"MEX","Mexico","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2006/mex_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
39736,484,"MEX","Mexico","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2006/mex_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
39737,484,"MEX","Mexico","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2006/mex_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
39738,484,"MEX","Mexico","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2006/mex_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
39739,484,"MEX","Mexico","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2006/mex_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
39740,484,"MEX","Mexico","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2006/mex_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
39741,484,"MEX","Mexico","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2007/mex_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
39742,484,"MEX","Mexico","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2007/mex_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
39743,484,"MEX","Mexico","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2007/mex_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
39744,484,"MEX","Mexico","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2007/mex_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
39745,484,"MEX","Mexico","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2007/mex_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
39746,484,"MEX","Mexico","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2007/mex_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
39747,484,"MEX","Mexico","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2007/mex_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
39748,484,"MEX","Mexico","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2007/mex_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
39749,484,"MEX","Mexico","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2008/mex_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
39750,484,"MEX","Mexico","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2008/mex_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
39751,484,"MEX","Mexico","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2008/mex_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
39752,484,"MEX","Mexico","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2008/mex_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
39753,484,"MEX","Mexico","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2008/mex_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
39754,484,"MEX","Mexico","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2008/mex_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
39755,484,"MEX","Mexico","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2008/mex_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
39756,484,"MEX","Mexico","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2008/mex_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
39757,484,"MEX","Mexico","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2009/mex_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
39758,484,"MEX","Mexico","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2009/mex_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
39759,484,"MEX","Mexico","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2009/mex_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
39760,484,"MEX","Mexico","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2009/mex_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
39761,484,"MEX","Mexico","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2009/mex_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
39762,484,"MEX","Mexico","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2009/mex_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
39763,484,"MEX","Mexico","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2009/mex_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
39764,484,"MEX","Mexico","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2009/mex_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
39765,484,"MEX","Mexico","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2010/mex_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
39766,484,"MEX","Mexico","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2010/mex_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
39767,484,"MEX","Mexico","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2010/mex_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
39768,484,"MEX","Mexico","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2010/mex_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
39769,484,"MEX","Mexico","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2010/mex_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
39770,484,"MEX","Mexico","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2010/mex_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
39771,484,"MEX","Mexico","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2010/mex_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
39772,484,"MEX","Mexico","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2010/mex_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
39773,484,"MEX","Mexico","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2011/mex_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
39774,484,"MEX","Mexico","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2011/mex_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
39775,484,"MEX","Mexico","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2011/mex_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
39776,484,"MEX","Mexico","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2011/mex_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
39777,484,"MEX","Mexico","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2011/mex_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
39778,484,"MEX","Mexico","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2011/mex_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
39779,484,"MEX","Mexico","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2011/mex_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
39780,484,"MEX","Mexico","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2011/mex_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
39781,484,"MEX","Mexico","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2012/mex_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
39782,484,"MEX","Mexico","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2012/mex_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
39783,484,"MEX","Mexico","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2012/mex_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
39784,484,"MEX","Mexico","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2012/mex_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
39785,484,"MEX","Mexico","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2012/mex_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
39786,484,"MEX","Mexico","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2012/mex_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
39787,484,"MEX","Mexico","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2012/mex_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
39788,484,"MEX","Mexico","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2012/mex_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
39789,484,"MEX","Mexico","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2013/mex_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
39790,484,"MEX","Mexico","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2013/mex_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
39791,484,"MEX","Mexico","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2013/mex_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
39792,484,"MEX","Mexico","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2013/mex_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
39793,484,"MEX","Mexico","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2013/mex_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
39794,484,"MEX","Mexico","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2013/mex_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
39795,484,"MEX","Mexico","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2013/mex_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
39796,484,"MEX","Mexico","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2013/mex_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
39797,484,"MEX","Mexico","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2014/mex_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
39798,484,"MEX","Mexico","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2014/mex_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
39799,484,"MEX","Mexico","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2014/mex_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
39800,484,"MEX","Mexico","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2014/mex_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
39801,484,"MEX","Mexico","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2014/mex_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
39802,484,"MEX","Mexico","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2014/mex_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
39803,484,"MEX","Mexico","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2014/mex_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
39804,484,"MEX","Mexico","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2014/mex_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
39805,484,"MEX","Mexico","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2015/mex_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
39806,484,"MEX","Mexico","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2015/mex_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
39807,484,"MEX","Mexico","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2015/mex_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
39808,484,"MEX","Mexico","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2015/mex_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
39809,484,"MEX","Mexico","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2015/mex_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
39810,484,"MEX","Mexico","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2015/mex_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
39811,484,"MEX","Mexico","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2015/mex_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
39812,484,"MEX","Mexico","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Annual/2015/mex_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
39813,492,"MCO","Monaco","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2000/mco_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
39814,492,"MCO","Monaco","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2000/mco_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
39815,492,"MCO","Monaco","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2000/mco_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
39816,492,"MCO","Monaco","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2000/mco_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
39817,492,"MCO","Monaco","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2000/mco_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
39818,492,"MCO","Monaco","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2000/mco_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
39819,492,"MCO","Monaco","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2000/mco_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
39820,492,"MCO","Monaco","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2000/mco_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
39821,492,"MCO","Monaco","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2001/mco_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
39822,492,"MCO","Monaco","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2001/mco_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
39823,492,"MCO","Monaco","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2001/mco_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
39824,492,"MCO","Monaco","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2001/mco_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
39825,492,"MCO","Monaco","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2001/mco_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
39826,492,"MCO","Monaco","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2001/mco_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
39827,492,"MCO","Monaco","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2001/mco_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
39828,492,"MCO","Monaco","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2001/mco_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
39829,492,"MCO","Monaco","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2002/mco_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
39830,492,"MCO","Monaco","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2002/mco_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
39831,492,"MCO","Monaco","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2002/mco_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
39832,492,"MCO","Monaco","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2002/mco_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
39833,492,"MCO","Monaco","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2002/mco_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
39834,492,"MCO","Monaco","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2002/mco_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
39835,492,"MCO","Monaco","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2002/mco_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
39836,492,"MCO","Monaco","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2002/mco_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
39837,492,"MCO","Monaco","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2003/mco_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
39838,492,"MCO","Monaco","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2003/mco_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
39839,492,"MCO","Monaco","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2003/mco_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
39840,492,"MCO","Monaco","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2003/mco_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
39841,492,"MCO","Monaco","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2003/mco_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
39842,492,"MCO","Monaco","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2003/mco_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
39843,492,"MCO","Monaco","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2003/mco_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
39844,492,"MCO","Monaco","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2003/mco_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
39845,492,"MCO","Monaco","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2004/mco_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
39846,492,"MCO","Monaco","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2004/mco_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
39847,492,"MCO","Monaco","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2004/mco_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
39848,492,"MCO","Monaco","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2004/mco_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
39849,492,"MCO","Monaco","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2004/mco_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
39850,492,"MCO","Monaco","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2004/mco_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
39851,492,"MCO","Monaco","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2004/mco_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
39852,492,"MCO","Monaco","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2004/mco_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
39853,492,"MCO","Monaco","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2005/mco_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
39854,492,"MCO","Monaco","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2005/mco_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
39855,492,"MCO","Monaco","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2005/mco_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
39856,492,"MCO","Monaco","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2005/mco_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
39857,492,"MCO","Monaco","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2005/mco_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
39858,492,"MCO","Monaco","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2005/mco_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
39859,492,"MCO","Monaco","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2005/mco_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
39860,492,"MCO","Monaco","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2005/mco_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
39861,492,"MCO","Monaco","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2006/mco_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
39862,492,"MCO","Monaco","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2006/mco_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
39863,492,"MCO","Monaco","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2006/mco_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
39864,492,"MCO","Monaco","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2006/mco_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
39865,492,"MCO","Monaco","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2006/mco_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
39866,492,"MCO","Monaco","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2006/mco_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
39867,492,"MCO","Monaco","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2006/mco_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
39868,492,"MCO","Monaco","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2006/mco_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
39869,492,"MCO","Monaco","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2007/mco_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
39870,492,"MCO","Monaco","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2007/mco_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
39871,492,"MCO","Monaco","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2007/mco_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
39872,492,"MCO","Monaco","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2007/mco_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
39873,492,"MCO","Monaco","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2007/mco_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
39874,492,"MCO","Monaco","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2007/mco_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
39875,492,"MCO","Monaco","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2007/mco_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
39876,492,"MCO","Monaco","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2007/mco_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
39877,492,"MCO","Monaco","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2008/mco_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
39878,492,"MCO","Monaco","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2008/mco_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
39879,492,"MCO","Monaco","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2008/mco_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
39880,492,"MCO","Monaco","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2008/mco_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
39881,492,"MCO","Monaco","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2008/mco_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
39882,492,"MCO","Monaco","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2008/mco_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
39883,492,"MCO","Monaco","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2008/mco_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
39884,492,"MCO","Monaco","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2008/mco_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
39885,492,"MCO","Monaco","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2009/mco_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
39886,492,"MCO","Monaco","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2009/mco_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
39887,492,"MCO","Monaco","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2009/mco_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
39888,492,"MCO","Monaco","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2009/mco_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
39889,492,"MCO","Monaco","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2009/mco_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
39890,492,"MCO","Monaco","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2009/mco_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
39891,492,"MCO","Monaco","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2009/mco_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
39892,492,"MCO","Monaco","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2009/mco_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
39893,492,"MCO","Monaco","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2010/mco_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
39894,492,"MCO","Monaco","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2010/mco_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
39895,492,"MCO","Monaco","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2010/mco_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
39896,492,"MCO","Monaco","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2010/mco_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
39897,492,"MCO","Monaco","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2010/mco_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
39898,492,"MCO","Monaco","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2010/mco_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
39899,492,"MCO","Monaco","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2010/mco_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
39900,492,"MCO","Monaco","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2010/mco_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
39901,492,"MCO","Monaco","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2011/mco_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
39902,492,"MCO","Monaco","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2011/mco_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
39903,492,"MCO","Monaco","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2011/mco_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
39904,492,"MCO","Monaco","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2011/mco_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
39905,492,"MCO","Monaco","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2011/mco_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
39906,492,"MCO","Monaco","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2011/mco_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
39907,492,"MCO","Monaco","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2011/mco_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
39908,492,"MCO","Monaco","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2011/mco_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
39909,492,"MCO","Monaco","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2012/mco_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
39910,492,"MCO","Monaco","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2012/mco_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
39911,492,"MCO","Monaco","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2012/mco_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
39912,492,"MCO","Monaco","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2012/mco_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
39913,492,"MCO","Monaco","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2012/mco_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
39914,492,"MCO","Monaco","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2012/mco_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
39915,492,"MCO","Monaco","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2012/mco_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
39916,492,"MCO","Monaco","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2012/mco_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
39917,492,"MCO","Monaco","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2013/mco_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
39918,492,"MCO","Monaco","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2013/mco_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
39919,492,"MCO","Monaco","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2013/mco_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
39920,492,"MCO","Monaco","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2013/mco_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
39921,492,"MCO","Monaco","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2013/mco_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
39922,492,"MCO","Monaco","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2013/mco_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
39923,492,"MCO","Monaco","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2013/mco_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
39924,492,"MCO","Monaco","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2013/mco_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
39925,492,"MCO","Monaco","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2014/mco_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
39926,492,"MCO","Monaco","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2014/mco_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
39927,492,"MCO","Monaco","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2014/mco_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
39928,492,"MCO","Monaco","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2014/mco_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
39929,492,"MCO","Monaco","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2014/mco_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
39930,492,"MCO","Monaco","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2014/mco_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
39931,492,"MCO","Monaco","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2014/mco_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
39932,492,"MCO","Monaco","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2014/mco_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
39933,492,"MCO","Monaco","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2015/mco_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
39934,492,"MCO","Monaco","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2015/mco_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
39935,492,"MCO","Monaco","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2015/mco_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
39936,492,"MCO","Monaco","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2015/mco_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
39937,492,"MCO","Monaco","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2015/mco_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
39938,492,"MCO","Monaco","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2015/mco_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
39939,492,"MCO","Monaco","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2015/mco_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
39940,492,"MCO","Monaco","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Annual/2015/mco_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
39941,496,"MNG","Mongolia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2000/mng_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
39942,496,"MNG","Mongolia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2000/mng_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
39943,496,"MNG","Mongolia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2000/mng_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
39944,496,"MNG","Mongolia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2000/mng_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
39945,496,"MNG","Mongolia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2000/mng_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
39946,496,"MNG","Mongolia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2000/mng_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
39947,496,"MNG","Mongolia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2000/mng_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
39948,496,"MNG","Mongolia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2000/mng_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
39949,496,"MNG","Mongolia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2001/mng_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
39950,496,"MNG","Mongolia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2001/mng_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
39951,496,"MNG","Mongolia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2001/mng_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
39952,496,"MNG","Mongolia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2001/mng_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
39953,496,"MNG","Mongolia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2001/mng_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
39954,496,"MNG","Mongolia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2001/mng_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
39955,496,"MNG","Mongolia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2001/mng_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
39956,496,"MNG","Mongolia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2001/mng_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
39957,496,"MNG","Mongolia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2002/mng_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
39958,496,"MNG","Mongolia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2002/mng_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
39959,496,"MNG","Mongolia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2002/mng_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
39960,496,"MNG","Mongolia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2002/mng_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
39961,496,"MNG","Mongolia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2002/mng_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
39962,496,"MNG","Mongolia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2002/mng_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
39963,496,"MNG","Mongolia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2002/mng_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
39964,496,"MNG","Mongolia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2002/mng_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
39965,496,"MNG","Mongolia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2003/mng_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
39966,496,"MNG","Mongolia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2003/mng_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
39967,496,"MNG","Mongolia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2003/mng_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
39968,496,"MNG","Mongolia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2003/mng_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
39969,496,"MNG","Mongolia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2003/mng_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
39970,496,"MNG","Mongolia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2003/mng_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
39971,496,"MNG","Mongolia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2003/mng_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
39972,496,"MNG","Mongolia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2003/mng_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
39973,496,"MNG","Mongolia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2004/mng_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
39974,496,"MNG","Mongolia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2004/mng_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
39975,496,"MNG","Mongolia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2004/mng_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
39976,496,"MNG","Mongolia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2004/mng_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
39977,496,"MNG","Mongolia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2004/mng_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
39978,496,"MNG","Mongolia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2004/mng_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
39979,496,"MNG","Mongolia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2004/mng_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
39980,496,"MNG","Mongolia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2004/mng_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
39981,496,"MNG","Mongolia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2005/mng_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
39982,496,"MNG","Mongolia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2005/mng_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
39983,496,"MNG","Mongolia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2005/mng_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
39984,496,"MNG","Mongolia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2005/mng_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
39985,496,"MNG","Mongolia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2005/mng_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
39986,496,"MNG","Mongolia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2005/mng_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
39987,496,"MNG","Mongolia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2005/mng_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
39988,496,"MNG","Mongolia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2005/mng_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
39989,496,"MNG","Mongolia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2006/mng_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
39990,496,"MNG","Mongolia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2006/mng_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
39991,496,"MNG","Mongolia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2006/mng_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
39992,496,"MNG","Mongolia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2006/mng_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
39993,496,"MNG","Mongolia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2006/mng_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
39994,496,"MNG","Mongolia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2006/mng_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
39995,496,"MNG","Mongolia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2006/mng_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
39996,496,"MNG","Mongolia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2006/mng_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
39997,496,"MNG","Mongolia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2007/mng_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
39998,496,"MNG","Mongolia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2007/mng_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
39999,496,"MNG","Mongolia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2007/mng_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
40000,496,"MNG","Mongolia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2007/mng_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
40001,496,"MNG","Mongolia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2007/mng_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
40002,496,"MNG","Mongolia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2007/mng_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
40003,496,"MNG","Mongolia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2007/mng_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
40004,496,"MNG","Mongolia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2007/mng_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
40005,496,"MNG","Mongolia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2008/mng_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
40006,496,"MNG","Mongolia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2008/mng_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
40007,496,"MNG","Mongolia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2008/mng_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
40008,496,"MNG","Mongolia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2008/mng_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
40009,496,"MNG","Mongolia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2008/mng_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
40010,496,"MNG","Mongolia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2008/mng_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
40011,496,"MNG","Mongolia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2008/mng_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
40012,496,"MNG","Mongolia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2008/mng_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
40013,496,"MNG","Mongolia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2009/mng_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
40014,496,"MNG","Mongolia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2009/mng_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
40015,496,"MNG","Mongolia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2009/mng_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
40016,496,"MNG","Mongolia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2009/mng_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
40017,496,"MNG","Mongolia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2009/mng_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
40018,496,"MNG","Mongolia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2009/mng_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
40019,496,"MNG","Mongolia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2009/mng_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
40020,496,"MNG","Mongolia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2009/mng_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
40021,496,"MNG","Mongolia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2010/mng_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
40022,496,"MNG","Mongolia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2010/mng_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
40023,496,"MNG","Mongolia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2010/mng_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
40024,496,"MNG","Mongolia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2010/mng_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
40025,496,"MNG","Mongolia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2010/mng_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
40026,496,"MNG","Mongolia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2010/mng_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
40027,496,"MNG","Mongolia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2010/mng_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
40028,496,"MNG","Mongolia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2010/mng_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
40029,496,"MNG","Mongolia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2011/mng_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
40030,496,"MNG","Mongolia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2011/mng_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
40031,496,"MNG","Mongolia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2011/mng_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
40032,496,"MNG","Mongolia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2011/mng_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
40033,496,"MNG","Mongolia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2011/mng_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
40034,496,"MNG","Mongolia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2011/mng_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
40035,496,"MNG","Mongolia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2011/mng_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
40036,496,"MNG","Mongolia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2011/mng_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
40037,496,"MNG","Mongolia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2012/mng_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
40038,496,"MNG","Mongolia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2012/mng_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
40039,496,"MNG","Mongolia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2012/mng_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
40040,496,"MNG","Mongolia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2012/mng_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
40041,496,"MNG","Mongolia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2012/mng_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
40042,496,"MNG","Mongolia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2012/mng_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
40043,496,"MNG","Mongolia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2012/mng_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
40044,496,"MNG","Mongolia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2012/mng_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
40045,496,"MNG","Mongolia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2013/mng_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
40046,496,"MNG","Mongolia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2013/mng_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
40047,496,"MNG","Mongolia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2013/mng_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
40048,496,"MNG","Mongolia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2013/mng_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
40049,496,"MNG","Mongolia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2013/mng_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
40050,496,"MNG","Mongolia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2013/mng_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
40051,496,"MNG","Mongolia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2013/mng_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
40052,496,"MNG","Mongolia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2013/mng_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
40053,496,"MNG","Mongolia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2014/mng_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
40054,496,"MNG","Mongolia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2014/mng_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
40055,496,"MNG","Mongolia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2014/mng_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
40056,496,"MNG","Mongolia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2014/mng_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
40057,496,"MNG","Mongolia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2014/mng_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
40058,496,"MNG","Mongolia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2014/mng_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
40059,496,"MNG","Mongolia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2014/mng_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
40060,496,"MNG","Mongolia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2014/mng_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
40061,496,"MNG","Mongolia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2015/mng_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
40062,496,"MNG","Mongolia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2015/mng_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
40063,496,"MNG","Mongolia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2015/mng_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
40064,496,"MNG","Mongolia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2015/mng_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
40065,496,"MNG","Mongolia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2015/mng_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
40066,496,"MNG","Mongolia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2015/mng_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
40067,496,"MNG","Mongolia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2015/mng_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
40068,496,"MNG","Mongolia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Annual/2015/mng_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
40069,498,"MDA","Moldova","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2000/mda_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
40070,498,"MDA","Moldova","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2000/mda_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
40071,498,"MDA","Moldova","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2000/mda_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
40072,498,"MDA","Moldova","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2000/mda_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
40073,498,"MDA","Moldova","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2000/mda_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
40074,498,"MDA","Moldova","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2000/mda_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
40075,498,"MDA","Moldova","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2000/mda_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
40076,498,"MDA","Moldova","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2000/mda_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
40077,498,"MDA","Moldova","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2001/mda_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
40078,498,"MDA","Moldova","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2001/mda_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
40079,498,"MDA","Moldova","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2001/mda_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
40080,498,"MDA","Moldova","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2001/mda_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
40081,498,"MDA","Moldova","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2001/mda_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
40082,498,"MDA","Moldova","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2001/mda_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
40083,498,"MDA","Moldova","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2001/mda_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
40084,498,"MDA","Moldova","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2001/mda_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
40085,498,"MDA","Moldova","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2002/mda_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
40086,498,"MDA","Moldova","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2002/mda_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
40087,498,"MDA","Moldova","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2002/mda_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
40088,498,"MDA","Moldova","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2002/mda_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
40089,498,"MDA","Moldova","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2002/mda_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
40090,498,"MDA","Moldova","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2002/mda_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
40091,498,"MDA","Moldova","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2002/mda_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
40092,498,"MDA","Moldova","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2002/mda_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
40093,498,"MDA","Moldova","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2003/mda_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
40094,498,"MDA","Moldova","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2003/mda_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
40095,498,"MDA","Moldova","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2003/mda_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
40096,498,"MDA","Moldova","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2003/mda_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
40097,498,"MDA","Moldova","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2003/mda_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
40098,498,"MDA","Moldova","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2003/mda_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
40099,498,"MDA","Moldova","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2003/mda_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
40100,498,"MDA","Moldova","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2003/mda_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
40101,498,"MDA","Moldova","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2004/mda_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
40102,498,"MDA","Moldova","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2004/mda_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
40103,498,"MDA","Moldova","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2004/mda_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
40104,498,"MDA","Moldova","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2004/mda_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
40105,498,"MDA","Moldova","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2004/mda_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
40106,498,"MDA","Moldova","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2004/mda_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
40107,498,"MDA","Moldova","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2004/mda_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
40108,498,"MDA","Moldova","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2004/mda_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
40109,498,"MDA","Moldova","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2005/mda_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
40110,498,"MDA","Moldova","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2005/mda_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
40111,498,"MDA","Moldova","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2005/mda_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
40112,498,"MDA","Moldova","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2005/mda_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
40113,498,"MDA","Moldova","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2005/mda_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
40114,498,"MDA","Moldova","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2005/mda_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
40115,498,"MDA","Moldova","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2005/mda_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
40116,498,"MDA","Moldova","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2005/mda_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
40117,498,"MDA","Moldova","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2006/mda_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
40118,498,"MDA","Moldova","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2006/mda_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
40119,498,"MDA","Moldova","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2006/mda_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
40120,498,"MDA","Moldova","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2006/mda_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
40121,498,"MDA","Moldova","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2006/mda_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
40122,498,"MDA","Moldova","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2006/mda_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
40123,498,"MDA","Moldova","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2006/mda_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
40124,498,"MDA","Moldova","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2006/mda_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
40125,498,"MDA","Moldova","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2007/mda_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
40126,498,"MDA","Moldova","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2007/mda_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
40127,498,"MDA","Moldova","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2007/mda_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
40128,498,"MDA","Moldova","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2007/mda_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
40129,498,"MDA","Moldova","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2007/mda_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
40130,498,"MDA","Moldova","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2007/mda_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
40131,498,"MDA","Moldova","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2007/mda_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
40132,498,"MDA","Moldova","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2007/mda_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
40133,498,"MDA","Moldova","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2008/mda_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
40134,498,"MDA","Moldova","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2008/mda_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
40135,498,"MDA","Moldova","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2008/mda_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
40136,498,"MDA","Moldova","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2008/mda_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
40137,498,"MDA","Moldova","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2008/mda_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
40138,498,"MDA","Moldova","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2008/mda_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
40139,498,"MDA","Moldova","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2008/mda_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
40140,498,"MDA","Moldova","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2008/mda_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
40141,498,"MDA","Moldova","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2009/mda_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
40142,498,"MDA","Moldova","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2009/mda_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
40143,498,"MDA","Moldova","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2009/mda_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
40144,498,"MDA","Moldova","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2009/mda_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
40145,498,"MDA","Moldova","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2009/mda_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
40146,498,"MDA","Moldova","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2009/mda_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
40147,498,"MDA","Moldova","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2009/mda_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
40148,498,"MDA","Moldova","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2009/mda_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
40149,498,"MDA","Moldova","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2010/mda_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
40150,498,"MDA","Moldova","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2010/mda_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
40151,498,"MDA","Moldova","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2010/mda_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
40152,498,"MDA","Moldova","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2010/mda_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
40153,498,"MDA","Moldova","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2010/mda_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
40154,498,"MDA","Moldova","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2010/mda_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
40155,498,"MDA","Moldova","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2010/mda_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
40156,498,"MDA","Moldova","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2010/mda_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
40157,498,"MDA","Moldova","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2011/mda_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
40158,498,"MDA","Moldova","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2011/mda_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
40159,498,"MDA","Moldova","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2011/mda_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
40160,498,"MDA","Moldova","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2011/mda_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
40161,498,"MDA","Moldova","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2011/mda_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
40162,498,"MDA","Moldova","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2011/mda_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
40163,498,"MDA","Moldova","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2011/mda_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
40164,498,"MDA","Moldova","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2011/mda_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
40165,498,"MDA","Moldova","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2012/mda_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
40166,498,"MDA","Moldova","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2012/mda_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
40167,498,"MDA","Moldova","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2012/mda_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
40168,498,"MDA","Moldova","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2012/mda_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
40169,498,"MDA","Moldova","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2012/mda_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
40170,498,"MDA","Moldova","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2012/mda_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
40171,498,"MDA","Moldova","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2012/mda_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
40172,498,"MDA","Moldova","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2012/mda_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
40173,498,"MDA","Moldova","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2013/mda_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
40174,498,"MDA","Moldova","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2013/mda_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
40175,498,"MDA","Moldova","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2013/mda_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
40176,498,"MDA","Moldova","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2013/mda_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
40177,498,"MDA","Moldova","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2013/mda_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
40178,498,"MDA","Moldova","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2013/mda_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
40179,498,"MDA","Moldova","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2013/mda_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
40180,498,"MDA","Moldova","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2013/mda_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
40181,498,"MDA","Moldova","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2014/mda_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
40182,498,"MDA","Moldova","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2014/mda_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
40183,498,"MDA","Moldova","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2014/mda_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
40184,498,"MDA","Moldova","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2014/mda_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
40185,498,"MDA","Moldova","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2014/mda_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
40186,498,"MDA","Moldova","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2014/mda_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
40187,498,"MDA","Moldova","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2014/mda_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
40188,498,"MDA","Moldova","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2014/mda_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
40189,498,"MDA","Moldova","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2015/mda_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
40190,498,"MDA","Moldova","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2015/mda_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
40191,498,"MDA","Moldova","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2015/mda_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
40192,498,"MDA","Moldova","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2015/mda_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
40193,498,"MDA","Moldova","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2015/mda_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
40194,498,"MDA","Moldova","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2015/mda_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
40195,498,"MDA","Moldova","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2015/mda_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
40196,498,"MDA","Moldova","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Annual/2015/mda_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
40197,499,"MNE","Montenegro","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2000/mne_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
40198,499,"MNE","Montenegro","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2000/mne_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
40199,499,"MNE","Montenegro","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2000/mne_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
40200,499,"MNE","Montenegro","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2000/mne_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
40201,499,"MNE","Montenegro","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2000/mne_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
40202,499,"MNE","Montenegro","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2000/mne_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
40203,499,"MNE","Montenegro","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2000/mne_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
40204,499,"MNE","Montenegro","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2000/mne_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
40205,499,"MNE","Montenegro","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2001/mne_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
40206,499,"MNE","Montenegro","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2001/mne_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
40207,499,"MNE","Montenegro","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2001/mne_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
40208,499,"MNE","Montenegro","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2001/mne_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
40209,499,"MNE","Montenegro","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2001/mne_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
40210,499,"MNE","Montenegro","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2001/mne_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
40211,499,"MNE","Montenegro","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2001/mne_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
40212,499,"MNE","Montenegro","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2001/mne_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
40213,499,"MNE","Montenegro","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2002/mne_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
40214,499,"MNE","Montenegro","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2002/mne_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
40215,499,"MNE","Montenegro","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2002/mne_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
40216,499,"MNE","Montenegro","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2002/mne_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
40217,499,"MNE","Montenegro","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2002/mne_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
40218,499,"MNE","Montenegro","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2002/mne_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
40219,499,"MNE","Montenegro","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2002/mne_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
40220,499,"MNE","Montenegro","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2002/mne_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
40221,499,"MNE","Montenegro","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2003/mne_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
40222,499,"MNE","Montenegro","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2003/mne_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
40223,499,"MNE","Montenegro","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2003/mne_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
40224,499,"MNE","Montenegro","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2003/mne_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
40225,499,"MNE","Montenegro","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2003/mne_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
40226,499,"MNE","Montenegro","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2003/mne_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
40227,499,"MNE","Montenegro","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2003/mne_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
40228,499,"MNE","Montenegro","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2003/mne_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
40229,499,"MNE","Montenegro","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2004/mne_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
40230,499,"MNE","Montenegro","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2004/mne_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
40231,499,"MNE","Montenegro","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2004/mne_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
40232,499,"MNE","Montenegro","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2004/mne_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
40233,499,"MNE","Montenegro","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2004/mne_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
40234,499,"MNE","Montenegro","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2004/mne_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
40235,499,"MNE","Montenegro","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2004/mne_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
40236,499,"MNE","Montenegro","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2004/mne_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
40237,499,"MNE","Montenegro","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2005/mne_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
40238,499,"MNE","Montenegro","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2005/mne_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
40239,499,"MNE","Montenegro","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2005/mne_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
40240,499,"MNE","Montenegro","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2005/mne_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
40241,499,"MNE","Montenegro","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2005/mne_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
40242,499,"MNE","Montenegro","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2005/mne_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
40243,499,"MNE","Montenegro","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2005/mne_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
40244,499,"MNE","Montenegro","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2005/mne_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
40245,499,"MNE","Montenegro","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2006/mne_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
40246,499,"MNE","Montenegro","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2006/mne_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
40247,499,"MNE","Montenegro","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2006/mne_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
40248,499,"MNE","Montenegro","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2006/mne_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
40249,499,"MNE","Montenegro","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2006/mne_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
40250,499,"MNE","Montenegro","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2006/mne_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
40251,499,"MNE","Montenegro","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2006/mne_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
40252,499,"MNE","Montenegro","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2006/mne_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
40253,499,"MNE","Montenegro","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2007/mne_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
40254,499,"MNE","Montenegro","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2007/mne_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
40255,499,"MNE","Montenegro","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2007/mne_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
40256,499,"MNE","Montenegro","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2007/mne_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
40257,499,"MNE","Montenegro","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2007/mne_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
40258,499,"MNE","Montenegro","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2007/mne_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
40259,499,"MNE","Montenegro","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2007/mne_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
40260,499,"MNE","Montenegro","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2007/mne_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
40261,499,"MNE","Montenegro","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2008/mne_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
40262,499,"MNE","Montenegro","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2008/mne_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
40263,499,"MNE","Montenegro","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2008/mne_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
40264,499,"MNE","Montenegro","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2008/mne_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
40265,499,"MNE","Montenegro","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2008/mne_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
40266,499,"MNE","Montenegro","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2008/mne_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
40267,499,"MNE","Montenegro","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2008/mne_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
40268,499,"MNE","Montenegro","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2008/mne_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
40269,499,"MNE","Montenegro","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2009/mne_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
40270,499,"MNE","Montenegro","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2009/mne_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
40271,499,"MNE","Montenegro","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2009/mne_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
40272,499,"MNE","Montenegro","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2009/mne_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
40273,499,"MNE","Montenegro","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2009/mne_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
40274,499,"MNE","Montenegro","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2009/mne_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
40275,499,"MNE","Montenegro","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2009/mne_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
40276,499,"MNE","Montenegro","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2009/mne_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
40277,499,"MNE","Montenegro","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2010/mne_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
40278,499,"MNE","Montenegro","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2010/mne_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
40279,499,"MNE","Montenegro","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2010/mne_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
40280,499,"MNE","Montenegro","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2010/mne_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
40281,499,"MNE","Montenegro","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2010/mne_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
40282,499,"MNE","Montenegro","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2010/mne_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
40283,499,"MNE","Montenegro","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2010/mne_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
40284,499,"MNE","Montenegro","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2010/mne_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
40285,499,"MNE","Montenegro","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2011/mne_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
40286,499,"MNE","Montenegro","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2011/mne_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
40287,499,"MNE","Montenegro","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2011/mne_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
40288,499,"MNE","Montenegro","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2011/mne_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
40289,499,"MNE","Montenegro","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2011/mne_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
40290,499,"MNE","Montenegro","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2011/mne_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
40291,499,"MNE","Montenegro","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2011/mne_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
40292,499,"MNE","Montenegro","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2011/mne_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
40293,499,"MNE","Montenegro","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2012/mne_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
40294,499,"MNE","Montenegro","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2012/mne_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
40295,499,"MNE","Montenegro","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2012/mne_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
40296,499,"MNE","Montenegro","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2012/mne_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
40297,499,"MNE","Montenegro","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2012/mne_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
40298,499,"MNE","Montenegro","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2012/mne_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
40299,499,"MNE","Montenegro","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2012/mne_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
40300,499,"MNE","Montenegro","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2012/mne_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
40301,499,"MNE","Montenegro","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2013/mne_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
40302,499,"MNE","Montenegro","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2013/mne_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
40303,499,"MNE","Montenegro","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2013/mne_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
40304,499,"MNE","Montenegro","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2013/mne_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
40305,499,"MNE","Montenegro","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2013/mne_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
40306,499,"MNE","Montenegro","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2013/mne_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
40307,499,"MNE","Montenegro","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2013/mne_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
40308,499,"MNE","Montenegro","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2013/mne_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
40309,499,"MNE","Montenegro","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2014/mne_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
40310,499,"MNE","Montenegro","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2014/mne_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
40311,499,"MNE","Montenegro","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2014/mne_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
40312,499,"MNE","Montenegro","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2014/mne_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
40313,499,"MNE","Montenegro","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2014/mne_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
40314,499,"MNE","Montenegro","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2014/mne_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
40315,499,"MNE","Montenegro","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2014/mne_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
40316,499,"MNE","Montenegro","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2014/mne_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
40317,499,"MNE","Montenegro","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2015/mne_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
40318,499,"MNE","Montenegro","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2015/mne_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
40319,499,"MNE","Montenegro","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2015/mne_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
40320,499,"MNE","Montenegro","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2015/mne_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
40321,499,"MNE","Montenegro","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2015/mne_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
40322,499,"MNE","Montenegro","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2015/mne_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
40323,499,"MNE","Montenegro","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2015/mne_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
40324,499,"MNE","Montenegro","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Annual/2015/mne_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
40325,500,"MSR","Montserrat","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2000/msr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
40326,500,"MSR","Montserrat","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2000/msr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
40327,500,"MSR","Montserrat","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2000/msr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
40328,500,"MSR","Montserrat","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2000/msr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
40329,500,"MSR","Montserrat","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2000/msr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
40330,500,"MSR","Montserrat","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2000/msr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
40331,500,"MSR","Montserrat","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2000/msr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
40332,500,"MSR","Montserrat","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2000/msr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
40333,500,"MSR","Montserrat","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2001/msr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
40334,500,"MSR","Montserrat","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2001/msr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
40335,500,"MSR","Montserrat","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2001/msr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
40336,500,"MSR","Montserrat","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2001/msr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
40337,500,"MSR","Montserrat","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2001/msr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
40338,500,"MSR","Montserrat","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2001/msr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
40339,500,"MSR","Montserrat","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2001/msr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
40340,500,"MSR","Montserrat","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2001/msr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
40341,500,"MSR","Montserrat","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2002/msr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
40342,500,"MSR","Montserrat","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2002/msr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
40343,500,"MSR","Montserrat","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2002/msr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
40344,500,"MSR","Montserrat","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2002/msr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
40345,500,"MSR","Montserrat","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2002/msr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
40346,500,"MSR","Montserrat","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2002/msr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
40347,500,"MSR","Montserrat","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2002/msr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
40348,500,"MSR","Montserrat","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2002/msr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
40349,500,"MSR","Montserrat","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2003/msr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
40350,500,"MSR","Montserrat","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2003/msr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
40351,500,"MSR","Montserrat","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2003/msr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
40352,500,"MSR","Montserrat","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2003/msr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
40353,500,"MSR","Montserrat","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2003/msr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
40354,500,"MSR","Montserrat","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2003/msr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
40355,500,"MSR","Montserrat","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2003/msr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
40356,500,"MSR","Montserrat","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2003/msr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
40357,500,"MSR","Montserrat","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2004/msr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
40358,500,"MSR","Montserrat","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2004/msr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
40359,500,"MSR","Montserrat","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2004/msr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
40360,500,"MSR","Montserrat","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2004/msr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
40361,500,"MSR","Montserrat","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2004/msr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
40362,500,"MSR","Montserrat","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2004/msr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
40363,500,"MSR","Montserrat","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2004/msr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
40364,500,"MSR","Montserrat","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2004/msr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
40365,500,"MSR","Montserrat","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2005/msr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
40366,500,"MSR","Montserrat","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2005/msr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
40367,500,"MSR","Montserrat","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2005/msr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
40368,500,"MSR","Montserrat","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2005/msr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
40369,500,"MSR","Montserrat","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2005/msr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
40370,500,"MSR","Montserrat","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2005/msr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
40371,500,"MSR","Montserrat","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2005/msr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
40372,500,"MSR","Montserrat","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2005/msr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
40373,500,"MSR","Montserrat","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2006/msr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
40374,500,"MSR","Montserrat","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2006/msr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
40375,500,"MSR","Montserrat","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2006/msr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
40376,500,"MSR","Montserrat","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2006/msr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
40377,500,"MSR","Montserrat","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2006/msr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
40378,500,"MSR","Montserrat","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2006/msr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
40379,500,"MSR","Montserrat","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2006/msr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
40380,500,"MSR","Montserrat","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2006/msr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
40381,500,"MSR","Montserrat","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2007/msr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
40382,500,"MSR","Montserrat","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2007/msr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
40383,500,"MSR","Montserrat","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2007/msr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
40384,500,"MSR","Montserrat","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2007/msr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
40385,500,"MSR","Montserrat","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2007/msr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
40386,500,"MSR","Montserrat","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2007/msr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
40387,500,"MSR","Montserrat","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2007/msr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
40388,500,"MSR","Montserrat","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2007/msr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
40389,500,"MSR","Montserrat","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2008/msr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
40390,500,"MSR","Montserrat","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2008/msr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
40391,500,"MSR","Montserrat","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2008/msr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
40392,500,"MSR","Montserrat","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2008/msr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
40393,500,"MSR","Montserrat","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2008/msr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
40394,500,"MSR","Montserrat","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2008/msr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
40395,500,"MSR","Montserrat","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2008/msr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
40396,500,"MSR","Montserrat","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2008/msr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
40397,500,"MSR","Montserrat","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2009/msr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
40398,500,"MSR","Montserrat","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2009/msr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
40399,500,"MSR","Montserrat","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2009/msr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
40400,500,"MSR","Montserrat","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2009/msr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
40401,500,"MSR","Montserrat","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2009/msr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
40402,500,"MSR","Montserrat","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2009/msr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
40403,500,"MSR","Montserrat","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2009/msr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
40404,500,"MSR","Montserrat","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2009/msr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
40405,500,"MSR","Montserrat","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2010/msr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
40406,500,"MSR","Montserrat","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2010/msr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
40407,500,"MSR","Montserrat","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2010/msr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
40408,500,"MSR","Montserrat","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2010/msr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
40409,500,"MSR","Montserrat","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2010/msr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
40410,500,"MSR","Montserrat","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2010/msr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
40411,500,"MSR","Montserrat","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2010/msr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
40412,500,"MSR","Montserrat","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2010/msr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
40413,500,"MSR","Montserrat","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2011/msr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
40414,500,"MSR","Montserrat","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2011/msr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
40415,500,"MSR","Montserrat","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2011/msr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
40416,500,"MSR","Montserrat","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2011/msr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
40417,500,"MSR","Montserrat","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2011/msr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
40418,500,"MSR","Montserrat","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2011/msr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
40419,500,"MSR","Montserrat","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2011/msr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
40420,500,"MSR","Montserrat","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2011/msr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
40421,500,"MSR","Montserrat","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2012/msr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
40422,500,"MSR","Montserrat","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2012/msr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
40423,500,"MSR","Montserrat","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2012/msr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
40424,500,"MSR","Montserrat","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2012/msr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
40425,500,"MSR","Montserrat","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2012/msr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
40426,500,"MSR","Montserrat","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2012/msr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
40427,500,"MSR","Montserrat","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2012/msr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
40428,500,"MSR","Montserrat","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2012/msr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
40429,500,"MSR","Montserrat","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2013/msr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
40430,500,"MSR","Montserrat","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2013/msr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
40431,500,"MSR","Montserrat","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2013/msr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
40432,500,"MSR","Montserrat","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2013/msr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
40433,500,"MSR","Montserrat","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2013/msr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
40434,500,"MSR","Montserrat","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2013/msr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
40435,500,"MSR","Montserrat","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2013/msr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
40436,500,"MSR","Montserrat","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2013/msr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
40437,500,"MSR","Montserrat","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2014/msr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
40438,500,"MSR","Montserrat","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2014/msr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
40439,500,"MSR","Montserrat","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2014/msr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
40440,500,"MSR","Montserrat","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2014/msr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
40441,500,"MSR","Montserrat","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2014/msr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
40442,500,"MSR","Montserrat","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2014/msr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
40443,500,"MSR","Montserrat","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2014/msr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
40444,500,"MSR","Montserrat","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2014/msr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
40445,500,"MSR","Montserrat","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2015/msr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
40446,500,"MSR","Montserrat","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2015/msr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
40447,500,"MSR","Montserrat","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2015/msr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
40448,500,"MSR","Montserrat","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2015/msr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
40449,500,"MSR","Montserrat","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2015/msr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
40450,500,"MSR","Montserrat","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2015/msr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
40451,500,"MSR","Montserrat","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2015/msr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
40452,500,"MSR","Montserrat","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Annual/2015/msr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
40453,504,"MAR","Morocco","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2000/mar_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
40454,504,"MAR","Morocco","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2000/mar_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
40455,504,"MAR","Morocco","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2000/mar_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
40456,504,"MAR","Morocco","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2000/mar_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
40457,504,"MAR","Morocco","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2000/mar_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
40458,504,"MAR","Morocco","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2000/mar_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
40459,504,"MAR","Morocco","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2000/mar_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
40460,504,"MAR","Morocco","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2000/mar_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
40461,504,"MAR","Morocco","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2001/mar_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
40462,504,"MAR","Morocco","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2001/mar_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
40463,504,"MAR","Morocco","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2001/mar_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
40464,504,"MAR","Morocco","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2001/mar_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
40465,504,"MAR","Morocco","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2001/mar_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
40466,504,"MAR","Morocco","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2001/mar_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
40467,504,"MAR","Morocco","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2001/mar_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
40468,504,"MAR","Morocco","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2001/mar_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
40469,504,"MAR","Morocco","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2002/mar_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
40470,504,"MAR","Morocco","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2002/mar_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
40471,504,"MAR","Morocco","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2002/mar_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
40472,504,"MAR","Morocco","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2002/mar_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
40473,504,"MAR","Morocco","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2002/mar_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
40474,504,"MAR","Morocco","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2002/mar_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
40475,504,"MAR","Morocco","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2002/mar_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
40476,504,"MAR","Morocco","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2002/mar_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
40477,504,"MAR","Morocco","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2003/mar_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
40478,504,"MAR","Morocco","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2003/mar_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
40479,504,"MAR","Morocco","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2003/mar_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
40480,504,"MAR","Morocco","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2003/mar_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
40481,504,"MAR","Morocco","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2003/mar_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
40482,504,"MAR","Morocco","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2003/mar_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
40483,504,"MAR","Morocco","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2003/mar_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
40484,504,"MAR","Morocco","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2003/mar_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
40485,504,"MAR","Morocco","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2004/mar_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
40486,504,"MAR","Morocco","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2004/mar_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
40487,504,"MAR","Morocco","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2004/mar_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
40488,504,"MAR","Morocco","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2004/mar_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
40489,504,"MAR","Morocco","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2004/mar_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
40490,504,"MAR","Morocco","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2004/mar_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
40491,504,"MAR","Morocco","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2004/mar_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
40492,504,"MAR","Morocco","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2004/mar_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
40493,504,"MAR","Morocco","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2005/mar_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
40494,504,"MAR","Morocco","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2005/mar_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
40495,504,"MAR","Morocco","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2005/mar_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
40496,504,"MAR","Morocco","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2005/mar_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
40497,504,"MAR","Morocco","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2005/mar_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
40498,504,"MAR","Morocco","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2005/mar_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
40499,504,"MAR","Morocco","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2005/mar_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
40500,504,"MAR","Morocco","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2005/mar_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
40501,504,"MAR","Morocco","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2006/mar_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
40502,504,"MAR","Morocco","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2006/mar_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
40503,504,"MAR","Morocco","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2006/mar_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
40504,504,"MAR","Morocco","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2006/mar_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
40505,504,"MAR","Morocco","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2006/mar_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
40506,504,"MAR","Morocco","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2006/mar_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
40507,504,"MAR","Morocco","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2006/mar_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
40508,504,"MAR","Morocco","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2006/mar_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
40509,504,"MAR","Morocco","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2007/mar_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
40510,504,"MAR","Morocco","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2007/mar_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
40511,504,"MAR","Morocco","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2007/mar_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
40512,504,"MAR","Morocco","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2007/mar_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
40513,504,"MAR","Morocco","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2007/mar_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
40514,504,"MAR","Morocco","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2007/mar_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
40515,504,"MAR","Morocco","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2007/mar_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
40516,504,"MAR","Morocco","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2007/mar_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
40517,504,"MAR","Morocco","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2008/mar_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
40518,504,"MAR","Morocco","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2008/mar_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
40519,504,"MAR","Morocco","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2008/mar_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
40520,504,"MAR","Morocco","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2008/mar_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
40521,504,"MAR","Morocco","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2008/mar_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
40522,504,"MAR","Morocco","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2008/mar_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
40523,504,"MAR","Morocco","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2008/mar_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
40524,504,"MAR","Morocco","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2008/mar_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
40525,504,"MAR","Morocco","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2009/mar_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
40526,504,"MAR","Morocco","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2009/mar_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
40527,504,"MAR","Morocco","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2009/mar_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
40528,504,"MAR","Morocco","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2009/mar_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
40529,504,"MAR","Morocco","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2009/mar_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
40530,504,"MAR","Morocco","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2009/mar_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
40531,504,"MAR","Morocco","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2009/mar_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
40532,504,"MAR","Morocco","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2009/mar_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
40533,504,"MAR","Morocco","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2010/mar_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
40534,504,"MAR","Morocco","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2010/mar_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
40535,504,"MAR","Morocco","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2010/mar_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
40536,504,"MAR","Morocco","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2010/mar_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
40537,504,"MAR","Morocco","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2010/mar_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
40538,504,"MAR","Morocco","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2010/mar_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
40539,504,"MAR","Morocco","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2010/mar_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
40540,504,"MAR","Morocco","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2010/mar_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
40541,504,"MAR","Morocco","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2011/mar_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
40542,504,"MAR","Morocco","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2011/mar_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
40543,504,"MAR","Morocco","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2011/mar_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
40544,504,"MAR","Morocco","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2011/mar_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
40545,504,"MAR","Morocco","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2011/mar_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
40546,504,"MAR","Morocco","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2011/mar_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
40547,504,"MAR","Morocco","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2011/mar_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
40548,504,"MAR","Morocco","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2011/mar_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
40549,504,"MAR","Morocco","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2012/mar_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
40550,504,"MAR","Morocco","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2012/mar_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
40551,504,"MAR","Morocco","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2012/mar_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
40552,504,"MAR","Morocco","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2012/mar_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
40553,504,"MAR","Morocco","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2012/mar_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
40554,504,"MAR","Morocco","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2012/mar_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
40555,504,"MAR","Morocco","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2012/mar_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
40556,504,"MAR","Morocco","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2012/mar_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
40557,504,"MAR","Morocco","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2013/mar_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
40558,504,"MAR","Morocco","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2013/mar_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
40559,504,"MAR","Morocco","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2013/mar_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
40560,504,"MAR","Morocco","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2013/mar_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
40561,504,"MAR","Morocco","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2013/mar_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
40562,504,"MAR","Morocco","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2013/mar_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
40563,504,"MAR","Morocco","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2013/mar_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
40564,504,"MAR","Morocco","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2013/mar_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
40565,504,"MAR","Morocco","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2014/mar_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
40566,504,"MAR","Morocco","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2014/mar_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
40567,504,"MAR","Morocco","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2014/mar_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
40568,504,"MAR","Morocco","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2014/mar_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
40569,504,"MAR","Morocco","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2014/mar_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
40570,504,"MAR","Morocco","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2014/mar_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
40571,504,"MAR","Morocco","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2014/mar_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
40572,504,"MAR","Morocco","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2014/mar_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
40573,504,"MAR","Morocco","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2015/mar_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
40574,504,"MAR","Morocco","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2015/mar_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
40575,504,"MAR","Morocco","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2015/mar_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
40576,504,"MAR","Morocco","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2015/mar_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
40577,504,"MAR","Morocco","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2015/mar_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
40578,504,"MAR","Morocco","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2015/mar_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
40579,504,"MAR","Morocco","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2015/mar_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
40580,504,"MAR","Morocco","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Annual/2015/mar_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
40581,508,"MOZ","Mozambique","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2000/moz_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
40582,508,"MOZ","Mozambique","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2000/moz_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
40583,508,"MOZ","Mozambique","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2000/moz_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
40584,508,"MOZ","Mozambique","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2000/moz_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
40585,508,"MOZ","Mozambique","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2000/moz_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
40586,508,"MOZ","Mozambique","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2000/moz_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
40587,508,"MOZ","Mozambique","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2000/moz_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
40588,508,"MOZ","Mozambique","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2000/moz_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
40589,508,"MOZ","Mozambique","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2001/moz_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
40590,508,"MOZ","Mozambique","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2001/moz_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
40591,508,"MOZ","Mozambique","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2001/moz_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
40592,508,"MOZ","Mozambique","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2001/moz_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
40593,508,"MOZ","Mozambique","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2001/moz_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
40594,508,"MOZ","Mozambique","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2001/moz_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
40595,508,"MOZ","Mozambique","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2001/moz_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
40596,508,"MOZ","Mozambique","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2001/moz_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
40597,508,"MOZ","Mozambique","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2002/moz_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
40598,508,"MOZ","Mozambique","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2002/moz_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
40599,508,"MOZ","Mozambique","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2002/moz_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
40600,508,"MOZ","Mozambique","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2002/moz_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
40601,508,"MOZ","Mozambique","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2002/moz_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
40602,508,"MOZ","Mozambique","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2002/moz_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
40603,508,"MOZ","Mozambique","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2002/moz_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
40604,508,"MOZ","Mozambique","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2002/moz_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
40605,508,"MOZ","Mozambique","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2003/moz_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
40606,508,"MOZ","Mozambique","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2003/moz_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
40607,508,"MOZ","Mozambique","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2003/moz_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
40608,508,"MOZ","Mozambique","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2003/moz_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
40609,508,"MOZ","Mozambique","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2003/moz_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
40610,508,"MOZ","Mozambique","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2003/moz_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
40611,508,"MOZ","Mozambique","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2003/moz_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
40612,508,"MOZ","Mozambique","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2003/moz_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
40613,508,"MOZ","Mozambique","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2004/moz_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
40614,508,"MOZ","Mozambique","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2004/moz_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
40615,508,"MOZ","Mozambique","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2004/moz_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
40616,508,"MOZ","Mozambique","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2004/moz_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
40617,508,"MOZ","Mozambique","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2004/moz_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
40618,508,"MOZ","Mozambique","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2004/moz_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
40619,508,"MOZ","Mozambique","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2004/moz_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
40620,508,"MOZ","Mozambique","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2004/moz_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
40621,508,"MOZ","Mozambique","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2005/moz_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
40622,508,"MOZ","Mozambique","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2005/moz_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
40623,508,"MOZ","Mozambique","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2005/moz_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
40624,508,"MOZ","Mozambique","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2005/moz_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
40625,508,"MOZ","Mozambique","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2005/moz_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
40626,508,"MOZ","Mozambique","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2005/moz_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
40627,508,"MOZ","Mozambique","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2005/moz_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
40628,508,"MOZ","Mozambique","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2005/moz_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
40629,508,"MOZ","Mozambique","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2006/moz_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
40630,508,"MOZ","Mozambique","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2006/moz_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
40631,508,"MOZ","Mozambique","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2006/moz_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
40632,508,"MOZ","Mozambique","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2006/moz_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
40633,508,"MOZ","Mozambique","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2006/moz_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
40634,508,"MOZ","Mozambique","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2006/moz_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
40635,508,"MOZ","Mozambique","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2006/moz_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
40636,508,"MOZ","Mozambique","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2006/moz_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
40637,508,"MOZ","Mozambique","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2007/moz_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
40638,508,"MOZ","Mozambique","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2007/moz_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
40639,508,"MOZ","Mozambique","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2007/moz_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
40640,508,"MOZ","Mozambique","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2007/moz_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
40641,508,"MOZ","Mozambique","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2007/moz_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
40642,508,"MOZ","Mozambique","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2007/moz_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
40643,508,"MOZ","Mozambique","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2007/moz_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
40644,508,"MOZ","Mozambique","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2007/moz_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
40645,508,"MOZ","Mozambique","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2008/moz_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
40646,508,"MOZ","Mozambique","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2008/moz_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
40647,508,"MOZ","Mozambique","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2008/moz_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
40648,508,"MOZ","Mozambique","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2008/moz_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
40649,508,"MOZ","Mozambique","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2008/moz_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
40650,508,"MOZ","Mozambique","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2008/moz_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
40651,508,"MOZ","Mozambique","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2008/moz_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
40652,508,"MOZ","Mozambique","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2008/moz_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
40653,508,"MOZ","Mozambique","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2009/moz_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
40654,508,"MOZ","Mozambique","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2009/moz_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
40655,508,"MOZ","Mozambique","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2009/moz_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
40656,508,"MOZ","Mozambique","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2009/moz_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
40657,508,"MOZ","Mozambique","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2009/moz_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
40658,508,"MOZ","Mozambique","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2009/moz_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
40659,508,"MOZ","Mozambique","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2009/moz_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
40660,508,"MOZ","Mozambique","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2009/moz_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
40661,508,"MOZ","Mozambique","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2010/moz_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
40662,508,"MOZ","Mozambique","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2010/moz_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
40663,508,"MOZ","Mozambique","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2010/moz_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
40664,508,"MOZ","Mozambique","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2010/moz_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
40665,508,"MOZ","Mozambique","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2010/moz_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
40666,508,"MOZ","Mozambique","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2010/moz_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
40667,508,"MOZ","Mozambique","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2010/moz_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
40668,508,"MOZ","Mozambique","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2010/moz_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
40669,508,"MOZ","Mozambique","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2011/moz_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
40670,508,"MOZ","Mozambique","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2011/moz_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
40671,508,"MOZ","Mozambique","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2011/moz_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
40672,508,"MOZ","Mozambique","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2011/moz_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
40673,508,"MOZ","Mozambique","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2011/moz_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
40674,508,"MOZ","Mozambique","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2011/moz_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
40675,508,"MOZ","Mozambique","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2011/moz_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
40676,508,"MOZ","Mozambique","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2011/moz_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
40677,508,"MOZ","Mozambique","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2012/moz_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
40678,508,"MOZ","Mozambique","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2012/moz_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
40679,508,"MOZ","Mozambique","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2012/moz_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
40680,508,"MOZ","Mozambique","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2012/moz_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
40681,508,"MOZ","Mozambique","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2012/moz_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
40682,508,"MOZ","Mozambique","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2012/moz_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
40683,508,"MOZ","Mozambique","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2012/moz_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
40684,508,"MOZ","Mozambique","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2012/moz_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
40685,508,"MOZ","Mozambique","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2013/moz_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
40686,508,"MOZ","Mozambique","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2013/moz_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
40687,508,"MOZ","Mozambique","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2013/moz_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
40688,508,"MOZ","Mozambique","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2013/moz_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
40689,508,"MOZ","Mozambique","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2013/moz_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
40690,508,"MOZ","Mozambique","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2013/moz_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
40691,508,"MOZ","Mozambique","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2013/moz_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
40692,508,"MOZ","Mozambique","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2013/moz_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
40693,508,"MOZ","Mozambique","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2014/moz_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
40694,508,"MOZ","Mozambique","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2014/moz_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
40695,508,"MOZ","Mozambique","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2014/moz_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
40696,508,"MOZ","Mozambique","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2014/moz_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
40697,508,"MOZ","Mozambique","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2014/moz_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
40698,508,"MOZ","Mozambique","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2014/moz_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
40699,508,"MOZ","Mozambique","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2014/moz_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
40700,508,"MOZ","Mozambique","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2014/moz_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
40701,508,"MOZ","Mozambique","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2015/moz_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
40702,508,"MOZ","Mozambique","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2015/moz_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
40703,508,"MOZ","Mozambique","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2015/moz_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
40704,508,"MOZ","Mozambique","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2015/moz_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
40705,508,"MOZ","Mozambique","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2015/moz_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
40706,508,"MOZ","Mozambique","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2015/moz_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
40707,508,"MOZ","Mozambique","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2015/moz_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
40708,508,"MOZ","Mozambique","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Annual/2015/moz_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
40709,512,"OMN","Oman","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2000/omn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
40710,512,"OMN","Oman","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2000/omn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
40711,512,"OMN","Oman","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2000/omn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
40712,512,"OMN","Oman","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2000/omn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
40713,512,"OMN","Oman","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2000/omn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
40714,512,"OMN","Oman","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2000/omn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
40715,512,"OMN","Oman","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2000/omn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
40716,512,"OMN","Oman","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2000/omn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
40717,512,"OMN","Oman","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2001/omn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
40718,512,"OMN","Oman","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2001/omn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
40719,512,"OMN","Oman","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2001/omn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
40720,512,"OMN","Oman","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2001/omn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
40721,512,"OMN","Oman","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2001/omn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
40722,512,"OMN","Oman","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2001/omn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
40723,512,"OMN","Oman","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2001/omn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
40724,512,"OMN","Oman","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2001/omn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
40725,512,"OMN","Oman","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2002/omn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
40726,512,"OMN","Oman","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2002/omn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
40727,512,"OMN","Oman","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2002/omn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
40728,512,"OMN","Oman","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2002/omn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
40729,512,"OMN","Oman","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2002/omn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
40730,512,"OMN","Oman","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2002/omn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
40731,512,"OMN","Oman","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2002/omn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
40732,512,"OMN","Oman","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2002/omn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
40733,512,"OMN","Oman","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2003/omn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
40734,512,"OMN","Oman","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2003/omn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
40735,512,"OMN","Oman","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2003/omn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
40736,512,"OMN","Oman","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2003/omn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
40737,512,"OMN","Oman","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2003/omn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
40738,512,"OMN","Oman","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2003/omn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
40739,512,"OMN","Oman","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2003/omn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
40740,512,"OMN","Oman","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2003/omn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
40741,512,"OMN","Oman","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2004/omn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
40742,512,"OMN","Oman","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2004/omn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
40743,512,"OMN","Oman","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2004/omn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
40744,512,"OMN","Oman","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2004/omn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
40745,512,"OMN","Oman","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2004/omn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
40746,512,"OMN","Oman","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2004/omn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
40747,512,"OMN","Oman","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2004/omn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
40748,512,"OMN","Oman","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2004/omn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
40749,512,"OMN","Oman","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2005/omn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
40750,512,"OMN","Oman","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2005/omn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
40751,512,"OMN","Oman","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2005/omn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
40752,512,"OMN","Oman","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2005/omn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
40753,512,"OMN","Oman","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2005/omn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
40754,512,"OMN","Oman","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2005/omn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
40755,512,"OMN","Oman","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2005/omn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
40756,512,"OMN","Oman","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2005/omn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
40757,512,"OMN","Oman","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2006/omn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
40758,512,"OMN","Oman","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2006/omn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
40759,512,"OMN","Oman","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2006/omn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
40760,512,"OMN","Oman","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2006/omn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
40761,512,"OMN","Oman","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2006/omn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
40762,512,"OMN","Oman","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2006/omn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
40763,512,"OMN","Oman","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2006/omn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
40764,512,"OMN","Oman","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2006/omn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
40765,512,"OMN","Oman","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2007/omn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
40766,512,"OMN","Oman","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2007/omn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
40767,512,"OMN","Oman","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2007/omn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
40768,512,"OMN","Oman","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2007/omn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
40769,512,"OMN","Oman","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2007/omn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
40770,512,"OMN","Oman","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2007/omn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
40771,512,"OMN","Oman","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2007/omn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
40772,512,"OMN","Oman","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2007/omn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
40773,512,"OMN","Oman","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2008/omn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
40774,512,"OMN","Oman","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2008/omn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
40775,512,"OMN","Oman","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2008/omn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
40776,512,"OMN","Oman","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2008/omn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
40777,512,"OMN","Oman","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2008/omn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
40778,512,"OMN","Oman","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2008/omn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
40779,512,"OMN","Oman","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2008/omn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
40780,512,"OMN","Oman","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2008/omn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
40781,512,"OMN","Oman","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2009/omn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
40782,512,"OMN","Oman","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2009/omn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
40783,512,"OMN","Oman","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2009/omn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
40784,512,"OMN","Oman","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2009/omn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
40785,512,"OMN","Oman","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2009/omn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
40786,512,"OMN","Oman","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2009/omn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
40787,512,"OMN","Oman","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2009/omn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
40788,512,"OMN","Oman","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2009/omn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
40789,512,"OMN","Oman","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2010/omn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
40790,512,"OMN","Oman","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2010/omn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
40791,512,"OMN","Oman","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2010/omn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
40792,512,"OMN","Oman","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2010/omn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
40793,512,"OMN","Oman","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2010/omn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
40794,512,"OMN","Oman","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2010/omn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
40795,512,"OMN","Oman","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2010/omn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
40796,512,"OMN","Oman","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2010/omn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
40797,512,"OMN","Oman","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2011/omn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
40798,512,"OMN","Oman","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2011/omn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
40799,512,"OMN","Oman","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2011/omn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
40800,512,"OMN","Oman","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2011/omn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
40801,512,"OMN","Oman","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2011/omn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
40802,512,"OMN","Oman","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2011/omn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
40803,512,"OMN","Oman","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2011/omn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
40804,512,"OMN","Oman","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2011/omn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
40805,512,"OMN","Oman","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2012/omn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
40806,512,"OMN","Oman","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2012/omn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
40807,512,"OMN","Oman","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2012/omn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
40808,512,"OMN","Oman","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2012/omn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
40809,512,"OMN","Oman","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2012/omn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
40810,512,"OMN","Oman","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2012/omn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
40811,512,"OMN","Oman","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2012/omn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
40812,512,"OMN","Oman","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2012/omn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
40813,512,"OMN","Oman","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2013/omn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
40814,512,"OMN","Oman","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2013/omn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
40815,512,"OMN","Oman","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2013/omn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
40816,512,"OMN","Oman","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2013/omn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
40817,512,"OMN","Oman","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2013/omn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
40818,512,"OMN","Oman","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2013/omn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
40819,512,"OMN","Oman","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2013/omn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
40820,512,"OMN","Oman","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2013/omn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
40821,512,"OMN","Oman","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2014/omn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
40822,512,"OMN","Oman","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2014/omn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
40823,512,"OMN","Oman","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2014/omn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
40824,512,"OMN","Oman","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2014/omn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
40825,512,"OMN","Oman","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2014/omn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
40826,512,"OMN","Oman","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2014/omn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
40827,512,"OMN","Oman","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2014/omn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
40828,512,"OMN","Oman","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2014/omn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
40829,512,"OMN","Oman","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2015/omn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
40830,512,"OMN","Oman","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2015/omn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
40831,512,"OMN","Oman","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2015/omn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
40832,512,"OMN","Oman","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2015/omn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
40833,512,"OMN","Oman","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2015/omn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
40834,512,"OMN","Oman","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2015/omn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
40835,512,"OMN","Oman","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2015/omn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
40836,512,"OMN","Oman","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Annual/2015/omn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
40837,516,"NAM","Namibia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2000/nam_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
40838,516,"NAM","Namibia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2000/nam_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
40839,516,"NAM","Namibia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2000/nam_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
40840,516,"NAM","Namibia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2000/nam_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
40841,516,"NAM","Namibia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2000/nam_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
40842,516,"NAM","Namibia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2000/nam_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
40843,516,"NAM","Namibia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2000/nam_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
40844,516,"NAM","Namibia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2000/nam_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
40845,516,"NAM","Namibia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2001/nam_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
40846,516,"NAM","Namibia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2001/nam_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
40847,516,"NAM","Namibia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2001/nam_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
40848,516,"NAM","Namibia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2001/nam_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
40849,516,"NAM","Namibia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2001/nam_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
40850,516,"NAM","Namibia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2001/nam_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
40851,516,"NAM","Namibia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2001/nam_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
40852,516,"NAM","Namibia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2001/nam_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
40853,516,"NAM","Namibia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2002/nam_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
40854,516,"NAM","Namibia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2002/nam_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
40855,516,"NAM","Namibia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2002/nam_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
40856,516,"NAM","Namibia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2002/nam_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
40857,516,"NAM","Namibia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2002/nam_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
40858,516,"NAM","Namibia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2002/nam_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
40859,516,"NAM","Namibia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2002/nam_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
40860,516,"NAM","Namibia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2002/nam_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
40861,516,"NAM","Namibia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2003/nam_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
40862,516,"NAM","Namibia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2003/nam_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
40863,516,"NAM","Namibia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2003/nam_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
40864,516,"NAM","Namibia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2003/nam_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
40865,516,"NAM","Namibia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2003/nam_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
40866,516,"NAM","Namibia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2003/nam_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
40867,516,"NAM","Namibia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2003/nam_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
40868,516,"NAM","Namibia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2003/nam_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
40869,516,"NAM","Namibia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2004/nam_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
40870,516,"NAM","Namibia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2004/nam_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
40871,516,"NAM","Namibia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2004/nam_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
40872,516,"NAM","Namibia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2004/nam_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
40873,516,"NAM","Namibia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2004/nam_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
40874,516,"NAM","Namibia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2004/nam_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
40875,516,"NAM","Namibia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2004/nam_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
40876,516,"NAM","Namibia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2004/nam_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
40877,516,"NAM","Namibia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2005/nam_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
40878,516,"NAM","Namibia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2005/nam_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
40879,516,"NAM","Namibia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2005/nam_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
40880,516,"NAM","Namibia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2005/nam_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
40881,516,"NAM","Namibia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2005/nam_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
40882,516,"NAM","Namibia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2005/nam_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
40883,516,"NAM","Namibia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2005/nam_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
40884,516,"NAM","Namibia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2005/nam_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
40885,516,"NAM","Namibia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2006/nam_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
40886,516,"NAM","Namibia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2006/nam_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
40887,516,"NAM","Namibia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2006/nam_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
40888,516,"NAM","Namibia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2006/nam_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
40889,516,"NAM","Namibia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2006/nam_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
40890,516,"NAM","Namibia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2006/nam_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
40891,516,"NAM","Namibia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2006/nam_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
40892,516,"NAM","Namibia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2006/nam_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
40893,516,"NAM","Namibia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2007/nam_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
40894,516,"NAM","Namibia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2007/nam_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
40895,516,"NAM","Namibia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2007/nam_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
40896,516,"NAM","Namibia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2007/nam_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
40897,516,"NAM","Namibia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2007/nam_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
40898,516,"NAM","Namibia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2007/nam_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
40899,516,"NAM","Namibia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2007/nam_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
40900,516,"NAM","Namibia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2007/nam_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
40901,516,"NAM","Namibia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2008/nam_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
40902,516,"NAM","Namibia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2008/nam_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
40903,516,"NAM","Namibia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2008/nam_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
40904,516,"NAM","Namibia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2008/nam_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
40905,516,"NAM","Namibia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2008/nam_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
40906,516,"NAM","Namibia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2008/nam_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
40907,516,"NAM","Namibia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2008/nam_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
40908,516,"NAM","Namibia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2008/nam_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
40909,516,"NAM","Namibia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2009/nam_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
40910,516,"NAM","Namibia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2009/nam_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
40911,516,"NAM","Namibia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2009/nam_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
40912,516,"NAM","Namibia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2009/nam_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
40913,516,"NAM","Namibia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2009/nam_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
40914,516,"NAM","Namibia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2009/nam_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
40915,516,"NAM","Namibia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2009/nam_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
40916,516,"NAM","Namibia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2009/nam_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
40917,516,"NAM","Namibia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2010/nam_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
40918,516,"NAM","Namibia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2010/nam_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
40919,516,"NAM","Namibia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2010/nam_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
40920,516,"NAM","Namibia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2010/nam_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
40921,516,"NAM","Namibia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2010/nam_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
40922,516,"NAM","Namibia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2010/nam_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
40923,516,"NAM","Namibia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2010/nam_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
40924,516,"NAM","Namibia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2010/nam_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
40925,516,"NAM","Namibia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2011/nam_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
40926,516,"NAM","Namibia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2011/nam_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
40927,516,"NAM","Namibia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2011/nam_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
40928,516,"NAM","Namibia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2011/nam_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
40929,516,"NAM","Namibia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2011/nam_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
40930,516,"NAM","Namibia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2011/nam_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
40931,516,"NAM","Namibia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2011/nam_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
40932,516,"NAM","Namibia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2011/nam_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
40933,516,"NAM","Namibia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2012/nam_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
40934,516,"NAM","Namibia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2012/nam_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
40935,516,"NAM","Namibia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2012/nam_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
40936,516,"NAM","Namibia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2012/nam_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
40937,516,"NAM","Namibia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2012/nam_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
40938,516,"NAM","Namibia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2012/nam_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
40939,516,"NAM","Namibia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2012/nam_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
40940,516,"NAM","Namibia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2012/nam_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
40941,516,"NAM","Namibia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2013/nam_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
40942,516,"NAM","Namibia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2013/nam_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
40943,516,"NAM","Namibia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2013/nam_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
40944,516,"NAM","Namibia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2013/nam_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
40945,516,"NAM","Namibia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2013/nam_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
40946,516,"NAM","Namibia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2013/nam_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
40947,516,"NAM","Namibia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2013/nam_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
40948,516,"NAM","Namibia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2013/nam_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
40949,516,"NAM","Namibia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2014/nam_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
40950,516,"NAM","Namibia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2014/nam_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
40951,516,"NAM","Namibia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2014/nam_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
40952,516,"NAM","Namibia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2014/nam_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
40953,516,"NAM","Namibia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2014/nam_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
40954,516,"NAM","Namibia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2014/nam_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
40955,516,"NAM","Namibia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2014/nam_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
40956,516,"NAM","Namibia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2014/nam_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
40957,516,"NAM","Namibia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2015/nam_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
40958,516,"NAM","Namibia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2015/nam_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
40959,516,"NAM","Namibia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2015/nam_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
40960,516,"NAM","Namibia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2015/nam_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
40961,516,"NAM","Namibia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2015/nam_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
40962,516,"NAM","Namibia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2015/nam_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
40963,516,"NAM","Namibia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2015/nam_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
40964,516,"NAM","Namibia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Annual/2015/nam_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
40965,520,"NRU","Nauru","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2000/nru_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
40966,520,"NRU","Nauru","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2000/nru_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
40967,520,"NRU","Nauru","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2000/nru_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
40968,520,"NRU","Nauru","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2000/nru_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
40969,520,"NRU","Nauru","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2000/nru_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
40970,520,"NRU","Nauru","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2000/nru_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
40971,520,"NRU","Nauru","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2000/nru_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
40972,520,"NRU","Nauru","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2000/nru_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
40973,520,"NRU","Nauru","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2001/nru_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
40974,520,"NRU","Nauru","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2001/nru_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
40975,520,"NRU","Nauru","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2001/nru_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
40976,520,"NRU","Nauru","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2001/nru_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
40977,520,"NRU","Nauru","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2001/nru_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
40978,520,"NRU","Nauru","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2001/nru_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
40979,520,"NRU","Nauru","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2001/nru_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
40980,520,"NRU","Nauru","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2001/nru_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
40981,520,"NRU","Nauru","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2002/nru_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
40982,520,"NRU","Nauru","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2002/nru_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
40983,520,"NRU","Nauru","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2002/nru_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
40984,520,"NRU","Nauru","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2002/nru_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
40985,520,"NRU","Nauru","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2002/nru_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
40986,520,"NRU","Nauru","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2002/nru_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
40987,520,"NRU","Nauru","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2002/nru_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
40988,520,"NRU","Nauru","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2002/nru_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
40989,520,"NRU","Nauru","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2003/nru_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
40990,520,"NRU","Nauru","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2003/nru_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
40991,520,"NRU","Nauru","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2003/nru_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
40992,520,"NRU","Nauru","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2003/nru_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
40993,520,"NRU","Nauru","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2003/nru_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
40994,520,"NRU","Nauru","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2003/nru_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
40995,520,"NRU","Nauru","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2003/nru_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
40996,520,"NRU","Nauru","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2003/nru_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
40997,520,"NRU","Nauru","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2004/nru_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
40998,520,"NRU","Nauru","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2004/nru_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
40999,520,"NRU","Nauru","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2004/nru_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
41000,520,"NRU","Nauru","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2004/nru_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
41001,520,"NRU","Nauru","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2004/nru_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
41002,520,"NRU","Nauru","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2004/nru_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
41003,520,"NRU","Nauru","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2004/nru_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
41004,520,"NRU","Nauru","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2004/nru_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
41005,520,"NRU","Nauru","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2005/nru_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
41006,520,"NRU","Nauru","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2005/nru_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
41007,520,"NRU","Nauru","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2005/nru_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
41008,520,"NRU","Nauru","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2005/nru_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
41009,520,"NRU","Nauru","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2005/nru_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
41010,520,"NRU","Nauru","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2005/nru_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
41011,520,"NRU","Nauru","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2005/nru_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
41012,520,"NRU","Nauru","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2005/nru_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
41013,520,"NRU","Nauru","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2006/nru_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
41014,520,"NRU","Nauru","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2006/nru_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
41015,520,"NRU","Nauru","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2006/nru_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
41016,520,"NRU","Nauru","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2006/nru_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
41017,520,"NRU","Nauru","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2006/nru_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
41018,520,"NRU","Nauru","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2006/nru_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
41019,520,"NRU","Nauru","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2006/nru_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
41020,520,"NRU","Nauru","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2006/nru_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
41021,520,"NRU","Nauru","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2007/nru_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
41022,520,"NRU","Nauru","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2007/nru_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
41023,520,"NRU","Nauru","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2007/nru_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
41024,520,"NRU","Nauru","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2007/nru_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
41025,520,"NRU","Nauru","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2007/nru_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
41026,520,"NRU","Nauru","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2007/nru_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
41027,520,"NRU","Nauru","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2007/nru_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
41028,520,"NRU","Nauru","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2007/nru_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
41029,520,"NRU","Nauru","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2008/nru_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
41030,520,"NRU","Nauru","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2008/nru_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
41031,520,"NRU","Nauru","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2008/nru_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
41032,520,"NRU","Nauru","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2008/nru_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
41033,520,"NRU","Nauru","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2008/nru_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
41034,520,"NRU","Nauru","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2008/nru_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
41035,520,"NRU","Nauru","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2008/nru_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
41036,520,"NRU","Nauru","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2008/nru_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
41037,520,"NRU","Nauru","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2009/nru_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
41038,520,"NRU","Nauru","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2009/nru_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
41039,520,"NRU","Nauru","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2009/nru_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
41040,520,"NRU","Nauru","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2009/nru_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
41041,520,"NRU","Nauru","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2009/nru_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
41042,520,"NRU","Nauru","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2009/nru_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
41043,520,"NRU","Nauru","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2009/nru_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
41044,520,"NRU","Nauru","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2009/nru_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
41045,520,"NRU","Nauru","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2010/nru_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
41046,520,"NRU","Nauru","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2010/nru_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
41047,520,"NRU","Nauru","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2010/nru_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
41048,520,"NRU","Nauru","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2010/nru_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
41049,520,"NRU","Nauru","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2010/nru_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
41050,520,"NRU","Nauru","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2010/nru_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
41051,520,"NRU","Nauru","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2010/nru_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
41052,520,"NRU","Nauru","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2010/nru_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
41053,520,"NRU","Nauru","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2011/nru_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
41054,520,"NRU","Nauru","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2011/nru_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
41055,520,"NRU","Nauru","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2011/nru_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
41056,520,"NRU","Nauru","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2011/nru_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
41057,520,"NRU","Nauru","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2011/nru_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
41058,520,"NRU","Nauru","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2011/nru_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
41059,520,"NRU","Nauru","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2011/nru_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
41060,520,"NRU","Nauru","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2011/nru_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
41061,520,"NRU","Nauru","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2012/nru_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
41062,520,"NRU","Nauru","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2012/nru_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
41063,520,"NRU","Nauru","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2012/nru_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
41064,520,"NRU","Nauru","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2012/nru_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
41065,520,"NRU","Nauru","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2012/nru_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
41066,520,"NRU","Nauru","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2012/nru_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
41067,520,"NRU","Nauru","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2012/nru_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
41068,520,"NRU","Nauru","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2012/nru_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
41069,520,"NRU","Nauru","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2013/nru_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
41070,520,"NRU","Nauru","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2013/nru_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
41071,520,"NRU","Nauru","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2013/nru_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
41072,520,"NRU","Nauru","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2013/nru_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
41073,520,"NRU","Nauru","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2013/nru_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
41074,520,"NRU","Nauru","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2013/nru_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
41075,520,"NRU","Nauru","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2013/nru_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
41076,520,"NRU","Nauru","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2013/nru_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
41077,520,"NRU","Nauru","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2014/nru_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
41078,520,"NRU","Nauru","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2014/nru_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
41079,520,"NRU","Nauru","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2014/nru_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
41080,520,"NRU","Nauru","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2014/nru_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
41081,520,"NRU","Nauru","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2014/nru_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
41082,520,"NRU","Nauru","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2014/nru_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
41083,520,"NRU","Nauru","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2014/nru_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
41084,520,"NRU","Nauru","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2014/nru_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
41085,520,"NRU","Nauru","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2015/nru_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
41086,520,"NRU","Nauru","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2015/nru_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
41087,520,"NRU","Nauru","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2015/nru_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
41088,520,"NRU","Nauru","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2015/nru_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
41089,520,"NRU","Nauru","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2015/nru_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
41090,520,"NRU","Nauru","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2015/nru_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
41091,520,"NRU","Nauru","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2015/nru_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
41092,520,"NRU","Nauru","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Annual/2015/nru_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
41093,524,"NPL","Nepal","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2000/npl_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
41094,524,"NPL","Nepal","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2000/npl_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
41095,524,"NPL","Nepal","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2000/npl_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
41096,524,"NPL","Nepal","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2000/npl_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
41097,524,"NPL","Nepal","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2000/npl_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
41098,524,"NPL","Nepal","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2000/npl_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
41099,524,"NPL","Nepal","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2000/npl_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
41100,524,"NPL","Nepal","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2000/npl_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
41101,524,"NPL","Nepal","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2001/npl_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
41102,524,"NPL","Nepal","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2001/npl_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
41103,524,"NPL","Nepal","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2001/npl_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
41104,524,"NPL","Nepal","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2001/npl_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
41105,524,"NPL","Nepal","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2001/npl_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
41106,524,"NPL","Nepal","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2001/npl_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
41107,524,"NPL","Nepal","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2001/npl_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
41108,524,"NPL","Nepal","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2001/npl_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
41109,524,"NPL","Nepal","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2002/npl_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
41110,524,"NPL","Nepal","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2002/npl_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
41111,524,"NPL","Nepal","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2002/npl_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
41112,524,"NPL","Nepal","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2002/npl_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
41113,524,"NPL","Nepal","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2002/npl_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
41114,524,"NPL","Nepal","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2002/npl_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
41115,524,"NPL","Nepal","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2002/npl_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
41116,524,"NPL","Nepal","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2002/npl_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
41117,524,"NPL","Nepal","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2003/npl_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
41118,524,"NPL","Nepal","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2003/npl_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
41119,524,"NPL","Nepal","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2003/npl_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
41120,524,"NPL","Nepal","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2003/npl_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
41121,524,"NPL","Nepal","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2003/npl_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
41122,524,"NPL","Nepal","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2003/npl_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
41123,524,"NPL","Nepal","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2003/npl_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
41124,524,"NPL","Nepal","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2003/npl_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
41125,524,"NPL","Nepal","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2004/npl_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
41126,524,"NPL","Nepal","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2004/npl_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
41127,524,"NPL","Nepal","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2004/npl_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
41128,524,"NPL","Nepal","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2004/npl_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
41129,524,"NPL","Nepal","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2004/npl_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
41130,524,"NPL","Nepal","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2004/npl_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
41131,524,"NPL","Nepal","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2004/npl_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
41132,524,"NPL","Nepal","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2004/npl_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
41133,524,"NPL","Nepal","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2005/npl_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
41134,524,"NPL","Nepal","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2005/npl_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
41135,524,"NPL","Nepal","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2005/npl_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
41136,524,"NPL","Nepal","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2005/npl_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
41137,524,"NPL","Nepal","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2005/npl_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
41138,524,"NPL","Nepal","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2005/npl_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
41139,524,"NPL","Nepal","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2005/npl_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
41140,524,"NPL","Nepal","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2005/npl_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
41141,524,"NPL","Nepal","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2006/npl_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
41142,524,"NPL","Nepal","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2006/npl_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
41143,524,"NPL","Nepal","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2006/npl_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
41144,524,"NPL","Nepal","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2006/npl_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
41145,524,"NPL","Nepal","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2006/npl_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
41146,524,"NPL","Nepal","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2006/npl_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
41147,524,"NPL","Nepal","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2006/npl_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
41148,524,"NPL","Nepal","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2006/npl_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
41149,524,"NPL","Nepal","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2007/npl_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
41150,524,"NPL","Nepal","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2007/npl_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
41151,524,"NPL","Nepal","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2007/npl_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
41152,524,"NPL","Nepal","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2007/npl_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
41153,524,"NPL","Nepal","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2007/npl_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
41154,524,"NPL","Nepal","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2007/npl_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
41155,524,"NPL","Nepal","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2007/npl_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
41156,524,"NPL","Nepal","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2007/npl_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
41157,524,"NPL","Nepal","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2008/npl_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
41158,524,"NPL","Nepal","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2008/npl_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
41159,524,"NPL","Nepal","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2008/npl_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
41160,524,"NPL","Nepal","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2008/npl_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
41161,524,"NPL","Nepal","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2008/npl_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
41162,524,"NPL","Nepal","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2008/npl_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
41163,524,"NPL","Nepal","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2008/npl_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
41164,524,"NPL","Nepal","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2008/npl_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
41165,524,"NPL","Nepal","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2009/npl_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
41166,524,"NPL","Nepal","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2009/npl_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
41167,524,"NPL","Nepal","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2009/npl_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
41168,524,"NPL","Nepal","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2009/npl_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
41169,524,"NPL","Nepal","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2009/npl_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
41170,524,"NPL","Nepal","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2009/npl_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
41171,524,"NPL","Nepal","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2009/npl_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
41172,524,"NPL","Nepal","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2009/npl_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
41173,524,"NPL","Nepal","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2010/npl_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
41174,524,"NPL","Nepal","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2010/npl_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
41175,524,"NPL","Nepal","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2010/npl_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
41176,524,"NPL","Nepal","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2010/npl_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
41177,524,"NPL","Nepal","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2010/npl_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
41178,524,"NPL","Nepal","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2010/npl_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
41179,524,"NPL","Nepal","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2010/npl_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
41180,524,"NPL","Nepal","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2010/npl_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
41181,524,"NPL","Nepal","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2011/npl_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
41182,524,"NPL","Nepal","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2011/npl_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
41183,524,"NPL","Nepal","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2011/npl_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
41184,524,"NPL","Nepal","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2011/npl_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
41185,524,"NPL","Nepal","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2011/npl_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
41186,524,"NPL","Nepal","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2011/npl_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
41187,524,"NPL","Nepal","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2011/npl_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
41188,524,"NPL","Nepal","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2011/npl_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
41189,524,"NPL","Nepal","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2012/npl_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
41190,524,"NPL","Nepal","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2012/npl_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
41191,524,"NPL","Nepal","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2012/npl_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
41192,524,"NPL","Nepal","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2012/npl_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
41193,524,"NPL","Nepal","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2012/npl_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
41194,524,"NPL","Nepal","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2012/npl_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
41195,524,"NPL","Nepal","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2012/npl_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
41196,524,"NPL","Nepal","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2012/npl_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
41197,524,"NPL","Nepal","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2013/npl_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
41198,524,"NPL","Nepal","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2013/npl_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
41199,524,"NPL","Nepal","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2013/npl_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
41200,524,"NPL","Nepal","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2013/npl_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
41201,524,"NPL","Nepal","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2013/npl_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
41202,524,"NPL","Nepal","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2013/npl_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
41203,524,"NPL","Nepal","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2013/npl_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
41204,524,"NPL","Nepal","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2013/npl_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
41205,524,"NPL","Nepal","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2014/npl_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
41206,524,"NPL","Nepal","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2014/npl_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
41207,524,"NPL","Nepal","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2014/npl_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
41208,524,"NPL","Nepal","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2014/npl_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
41209,524,"NPL","Nepal","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2014/npl_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
41210,524,"NPL","Nepal","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2014/npl_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
41211,524,"NPL","Nepal","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2014/npl_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
41212,524,"NPL","Nepal","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2014/npl_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
41213,524,"NPL","Nepal","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2015/npl_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
41214,524,"NPL","Nepal","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2015/npl_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
41215,524,"NPL","Nepal","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2015/npl_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
41216,524,"NPL","Nepal","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2015/npl_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
41217,524,"NPL","Nepal","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2015/npl_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
41218,524,"NPL","Nepal","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2015/npl_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
41219,524,"NPL","Nepal","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2015/npl_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
41220,524,"NPL","Nepal","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Annual/2015/npl_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
41221,528,"NLD","Netherlands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2000/nld_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
41222,528,"NLD","Netherlands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2000/nld_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
41223,528,"NLD","Netherlands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2000/nld_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
41224,528,"NLD","Netherlands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2000/nld_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
41225,528,"NLD","Netherlands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2000/nld_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
41226,528,"NLD","Netherlands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2000/nld_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
41227,528,"NLD","Netherlands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2000/nld_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
41228,528,"NLD","Netherlands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2000/nld_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
41229,528,"NLD","Netherlands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2001/nld_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
41230,528,"NLD","Netherlands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2001/nld_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
41231,528,"NLD","Netherlands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2001/nld_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
41232,528,"NLD","Netherlands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2001/nld_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
41233,528,"NLD","Netherlands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2001/nld_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
41234,528,"NLD","Netherlands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2001/nld_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
41235,528,"NLD","Netherlands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2001/nld_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
41236,528,"NLD","Netherlands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2001/nld_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
41237,528,"NLD","Netherlands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2002/nld_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
41238,528,"NLD","Netherlands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2002/nld_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
41239,528,"NLD","Netherlands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2002/nld_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
41240,528,"NLD","Netherlands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2002/nld_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
41241,528,"NLD","Netherlands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2002/nld_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
41242,528,"NLD","Netherlands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2002/nld_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
41243,528,"NLD","Netherlands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2002/nld_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
41244,528,"NLD","Netherlands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2002/nld_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
41245,528,"NLD","Netherlands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2003/nld_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
41246,528,"NLD","Netherlands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2003/nld_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
41247,528,"NLD","Netherlands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2003/nld_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
41248,528,"NLD","Netherlands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2003/nld_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
41249,528,"NLD","Netherlands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2003/nld_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
41250,528,"NLD","Netherlands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2003/nld_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
41251,528,"NLD","Netherlands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2003/nld_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
41252,528,"NLD","Netherlands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2003/nld_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
41253,528,"NLD","Netherlands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2004/nld_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
41254,528,"NLD","Netherlands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2004/nld_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
41255,528,"NLD","Netherlands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2004/nld_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
41256,528,"NLD","Netherlands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2004/nld_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
41257,528,"NLD","Netherlands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2004/nld_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
41258,528,"NLD","Netherlands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2004/nld_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
41259,528,"NLD","Netherlands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2004/nld_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
41260,528,"NLD","Netherlands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2004/nld_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
41261,528,"NLD","Netherlands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2005/nld_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
41262,528,"NLD","Netherlands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2005/nld_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
41263,528,"NLD","Netherlands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2005/nld_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
41264,528,"NLD","Netherlands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2005/nld_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
41265,528,"NLD","Netherlands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2005/nld_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
41266,528,"NLD","Netherlands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2005/nld_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
41267,528,"NLD","Netherlands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2005/nld_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
41268,528,"NLD","Netherlands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2005/nld_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
41269,528,"NLD","Netherlands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2006/nld_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
41270,528,"NLD","Netherlands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2006/nld_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
41271,528,"NLD","Netherlands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2006/nld_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
41272,528,"NLD","Netherlands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2006/nld_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
41273,528,"NLD","Netherlands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2006/nld_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
41274,528,"NLD","Netherlands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2006/nld_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
41275,528,"NLD","Netherlands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2006/nld_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
41276,528,"NLD","Netherlands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2006/nld_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
41277,528,"NLD","Netherlands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2007/nld_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
41278,528,"NLD","Netherlands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2007/nld_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
41279,528,"NLD","Netherlands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2007/nld_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
41280,528,"NLD","Netherlands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2007/nld_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
41281,528,"NLD","Netherlands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2007/nld_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
41282,528,"NLD","Netherlands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2007/nld_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
41283,528,"NLD","Netherlands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2007/nld_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
41284,528,"NLD","Netherlands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2007/nld_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
41285,528,"NLD","Netherlands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2008/nld_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
41286,528,"NLD","Netherlands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2008/nld_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
41287,528,"NLD","Netherlands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2008/nld_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
41288,528,"NLD","Netherlands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2008/nld_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
41289,528,"NLD","Netherlands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2008/nld_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
41290,528,"NLD","Netherlands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2008/nld_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
41291,528,"NLD","Netherlands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2008/nld_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
41292,528,"NLD","Netherlands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2008/nld_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
41293,528,"NLD","Netherlands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2009/nld_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
41294,528,"NLD","Netherlands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2009/nld_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
41295,528,"NLD","Netherlands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2009/nld_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
41296,528,"NLD","Netherlands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2009/nld_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
41297,528,"NLD","Netherlands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2009/nld_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
41298,528,"NLD","Netherlands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2009/nld_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
41299,528,"NLD","Netherlands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2009/nld_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
41300,528,"NLD","Netherlands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2009/nld_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
41301,528,"NLD","Netherlands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2010/nld_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
41302,528,"NLD","Netherlands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2010/nld_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
41303,528,"NLD","Netherlands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2010/nld_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
41304,528,"NLD","Netherlands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2010/nld_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
41305,528,"NLD","Netherlands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2010/nld_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
41306,528,"NLD","Netherlands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2010/nld_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
41307,528,"NLD","Netherlands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2010/nld_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
41308,528,"NLD","Netherlands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2010/nld_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
41309,528,"NLD","Netherlands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2011/nld_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
41310,528,"NLD","Netherlands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2011/nld_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
41311,528,"NLD","Netherlands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2011/nld_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
41312,528,"NLD","Netherlands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2011/nld_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
41313,528,"NLD","Netherlands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2011/nld_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
41314,528,"NLD","Netherlands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2011/nld_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
41315,528,"NLD","Netherlands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2011/nld_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
41316,528,"NLD","Netherlands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2011/nld_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
41317,528,"NLD","Netherlands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2012/nld_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
41318,528,"NLD","Netherlands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2012/nld_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
41319,528,"NLD","Netherlands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2012/nld_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
41320,528,"NLD","Netherlands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2012/nld_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
41321,528,"NLD","Netherlands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2012/nld_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
41322,528,"NLD","Netherlands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2012/nld_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
41323,528,"NLD","Netherlands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2012/nld_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
41324,528,"NLD","Netherlands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2012/nld_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
41325,528,"NLD","Netherlands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2013/nld_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
41326,528,"NLD","Netherlands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2013/nld_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
41327,528,"NLD","Netherlands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2013/nld_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
41328,528,"NLD","Netherlands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2013/nld_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
41329,528,"NLD","Netherlands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2013/nld_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
41330,528,"NLD","Netherlands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2013/nld_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
41331,528,"NLD","Netherlands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2013/nld_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
41332,528,"NLD","Netherlands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2013/nld_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
41333,528,"NLD","Netherlands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2014/nld_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
41334,528,"NLD","Netherlands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2014/nld_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
41335,528,"NLD","Netherlands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2014/nld_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
41336,528,"NLD","Netherlands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2014/nld_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
41337,528,"NLD","Netherlands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2014/nld_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
41338,528,"NLD","Netherlands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2014/nld_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
41339,528,"NLD","Netherlands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2014/nld_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
41340,528,"NLD","Netherlands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2014/nld_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
41341,528,"NLD","Netherlands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2015/nld_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
41342,528,"NLD","Netherlands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2015/nld_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
41343,528,"NLD","Netherlands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2015/nld_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
41344,528,"NLD","Netherlands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2015/nld_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
41345,528,"NLD","Netherlands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2015/nld_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
41346,528,"NLD","Netherlands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2015/nld_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
41347,528,"NLD","Netherlands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2015/nld_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
41348,528,"NLD","Netherlands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Annual/2015/nld_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
41349,531,"CUW","Curacao","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2000/cuw_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
41350,531,"CUW","Curacao","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2000/cuw_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
41351,531,"CUW","Curacao","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2000/cuw_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
41352,531,"CUW","Curacao","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2000/cuw_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
41353,531,"CUW","Curacao","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2000/cuw_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
41354,531,"CUW","Curacao","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2000/cuw_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
41355,531,"CUW","Curacao","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2000/cuw_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
41356,531,"CUW","Curacao","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2000/cuw_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
41357,531,"CUW","Curacao","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2001/cuw_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
41358,531,"CUW","Curacao","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2001/cuw_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
41359,531,"CUW","Curacao","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2001/cuw_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
41360,531,"CUW","Curacao","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2001/cuw_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
41361,531,"CUW","Curacao","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2001/cuw_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
41362,531,"CUW","Curacao","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2001/cuw_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
41363,531,"CUW","Curacao","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2001/cuw_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
41364,531,"CUW","Curacao","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2001/cuw_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
41365,531,"CUW","Curacao","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2002/cuw_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
41366,531,"CUW","Curacao","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2002/cuw_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
41367,531,"CUW","Curacao","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2002/cuw_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
41368,531,"CUW","Curacao","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2002/cuw_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
41369,531,"CUW","Curacao","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2002/cuw_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
41370,531,"CUW","Curacao","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2002/cuw_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
41371,531,"CUW","Curacao","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2002/cuw_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
41372,531,"CUW","Curacao","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2002/cuw_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
41373,531,"CUW","Curacao","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2003/cuw_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
41374,531,"CUW","Curacao","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2003/cuw_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
41375,531,"CUW","Curacao","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2003/cuw_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
41376,531,"CUW","Curacao","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2003/cuw_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
41377,531,"CUW","Curacao","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2003/cuw_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
41378,531,"CUW","Curacao","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2003/cuw_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
41379,531,"CUW","Curacao","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2003/cuw_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
41380,531,"CUW","Curacao","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2003/cuw_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
41381,531,"CUW","Curacao","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2004/cuw_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
41382,531,"CUW","Curacao","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2004/cuw_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
41383,531,"CUW","Curacao","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2004/cuw_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
41384,531,"CUW","Curacao","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2004/cuw_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
41385,531,"CUW","Curacao","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2004/cuw_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
41386,531,"CUW","Curacao","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2004/cuw_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
41387,531,"CUW","Curacao","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2004/cuw_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
41388,531,"CUW","Curacao","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2004/cuw_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
41389,531,"CUW","Curacao","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2005/cuw_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
41390,531,"CUW","Curacao","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2005/cuw_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
41391,531,"CUW","Curacao","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2005/cuw_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
41392,531,"CUW","Curacao","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2005/cuw_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
41393,531,"CUW","Curacao","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2005/cuw_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
41394,531,"CUW","Curacao","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2005/cuw_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
41395,531,"CUW","Curacao","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2005/cuw_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
41396,531,"CUW","Curacao","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2005/cuw_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
41397,531,"CUW","Curacao","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2006/cuw_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
41398,531,"CUW","Curacao","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2006/cuw_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
41399,531,"CUW","Curacao","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2006/cuw_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
41400,531,"CUW","Curacao","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2006/cuw_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
41401,531,"CUW","Curacao","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2006/cuw_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
41402,531,"CUW","Curacao","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2006/cuw_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
41403,531,"CUW","Curacao","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2006/cuw_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
41404,531,"CUW","Curacao","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2006/cuw_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
41405,531,"CUW","Curacao","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2007/cuw_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
41406,531,"CUW","Curacao","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2007/cuw_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
41407,531,"CUW","Curacao","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2007/cuw_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
41408,531,"CUW","Curacao","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2007/cuw_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
41409,531,"CUW","Curacao","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2007/cuw_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
41410,531,"CUW","Curacao","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2007/cuw_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
41411,531,"CUW","Curacao","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2007/cuw_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
41412,531,"CUW","Curacao","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2007/cuw_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
41413,531,"CUW","Curacao","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2008/cuw_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
41414,531,"CUW","Curacao","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2008/cuw_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
41415,531,"CUW","Curacao","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2008/cuw_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
41416,531,"CUW","Curacao","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2008/cuw_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
41417,531,"CUW","Curacao","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2008/cuw_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
41418,531,"CUW","Curacao","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2008/cuw_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
41419,531,"CUW","Curacao","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2008/cuw_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
41420,531,"CUW","Curacao","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2008/cuw_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
41421,531,"CUW","Curacao","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2009/cuw_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
41422,531,"CUW","Curacao","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2009/cuw_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
41423,531,"CUW","Curacao","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2009/cuw_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
41424,531,"CUW","Curacao","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2009/cuw_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
41425,531,"CUW","Curacao","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2009/cuw_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
41426,531,"CUW","Curacao","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2009/cuw_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
41427,531,"CUW","Curacao","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2009/cuw_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
41428,531,"CUW","Curacao","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2009/cuw_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
41429,531,"CUW","Curacao","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2010/cuw_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
41430,531,"CUW","Curacao","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2010/cuw_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
41431,531,"CUW","Curacao","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2010/cuw_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
41432,531,"CUW","Curacao","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2010/cuw_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
41433,531,"CUW","Curacao","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2010/cuw_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
41434,531,"CUW","Curacao","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2010/cuw_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
41435,531,"CUW","Curacao","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2010/cuw_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
41436,531,"CUW","Curacao","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2010/cuw_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
41437,531,"CUW","Curacao","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2011/cuw_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
41438,531,"CUW","Curacao","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2011/cuw_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
41439,531,"CUW","Curacao","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2011/cuw_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
41440,531,"CUW","Curacao","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2011/cuw_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
41441,531,"CUW","Curacao","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2011/cuw_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
41442,531,"CUW","Curacao","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2011/cuw_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
41443,531,"CUW","Curacao","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2011/cuw_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
41444,531,"CUW","Curacao","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2011/cuw_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
41445,531,"CUW","Curacao","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2012/cuw_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
41446,531,"CUW","Curacao","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2012/cuw_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
41447,531,"CUW","Curacao","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2012/cuw_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
41448,531,"CUW","Curacao","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2012/cuw_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
41449,531,"CUW","Curacao","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2012/cuw_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
41450,531,"CUW","Curacao","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2012/cuw_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
41451,531,"CUW","Curacao","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2012/cuw_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
41452,531,"CUW","Curacao","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2012/cuw_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
41453,531,"CUW","Curacao","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2013/cuw_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
41454,531,"CUW","Curacao","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2013/cuw_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
41455,531,"CUW","Curacao","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2013/cuw_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
41456,531,"CUW","Curacao","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2013/cuw_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
41457,531,"CUW","Curacao","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2013/cuw_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
41458,531,"CUW","Curacao","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2013/cuw_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
41459,531,"CUW","Curacao","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2013/cuw_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
41460,531,"CUW","Curacao","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2013/cuw_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
41461,531,"CUW","Curacao","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2014/cuw_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
41462,531,"CUW","Curacao","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2014/cuw_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
41463,531,"CUW","Curacao","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2014/cuw_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
41464,531,"CUW","Curacao","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2014/cuw_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
41465,531,"CUW","Curacao","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2014/cuw_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
41466,531,"CUW","Curacao","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2014/cuw_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
41467,531,"CUW","Curacao","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2014/cuw_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
41468,531,"CUW","Curacao","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2014/cuw_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
41469,531,"CUW","Curacao","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2015/cuw_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
41470,531,"CUW","Curacao","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2015/cuw_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
41471,531,"CUW","Curacao","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2015/cuw_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
41472,531,"CUW","Curacao","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2015/cuw_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
41473,531,"CUW","Curacao","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2015/cuw_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
41474,531,"CUW","Curacao","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2015/cuw_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
41475,531,"CUW","Curacao","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2015/cuw_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
41476,531,"CUW","Curacao","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Annual/2015/cuw_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
41477,533,"ABW","Aruba","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2000/abw_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
41478,533,"ABW","Aruba","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2000/abw_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
41479,533,"ABW","Aruba","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2000/abw_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
41480,533,"ABW","Aruba","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2000/abw_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
41481,533,"ABW","Aruba","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2000/abw_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
41482,533,"ABW","Aruba","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2000/abw_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
41483,533,"ABW","Aruba","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2000/abw_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
41484,533,"ABW","Aruba","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2000/abw_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
41485,533,"ABW","Aruba","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2001/abw_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
41486,533,"ABW","Aruba","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2001/abw_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
41487,533,"ABW","Aruba","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2001/abw_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
41488,533,"ABW","Aruba","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2001/abw_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
41489,533,"ABW","Aruba","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2001/abw_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
41490,533,"ABW","Aruba","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2001/abw_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
41491,533,"ABW","Aruba","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2001/abw_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
41492,533,"ABW","Aruba","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2001/abw_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
41493,533,"ABW","Aruba","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2002/abw_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
41494,533,"ABW","Aruba","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2002/abw_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
41495,533,"ABW","Aruba","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2002/abw_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
41496,533,"ABW","Aruba","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2002/abw_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
41497,533,"ABW","Aruba","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2002/abw_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
41498,533,"ABW","Aruba","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2002/abw_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
41499,533,"ABW","Aruba","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2002/abw_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
41500,533,"ABW","Aruba","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2002/abw_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
41501,533,"ABW","Aruba","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2003/abw_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
41502,533,"ABW","Aruba","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2003/abw_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
41503,533,"ABW","Aruba","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2003/abw_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
41504,533,"ABW","Aruba","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2003/abw_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
41505,533,"ABW","Aruba","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2003/abw_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
41506,533,"ABW","Aruba","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2003/abw_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
41507,533,"ABW","Aruba","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2003/abw_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
41508,533,"ABW","Aruba","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2003/abw_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
41509,533,"ABW","Aruba","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2004/abw_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
41510,533,"ABW","Aruba","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2004/abw_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
41511,533,"ABW","Aruba","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2004/abw_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
41512,533,"ABW","Aruba","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2004/abw_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
41513,533,"ABW","Aruba","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2004/abw_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
41514,533,"ABW","Aruba","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2004/abw_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
41515,533,"ABW","Aruba","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2004/abw_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
41516,533,"ABW","Aruba","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2004/abw_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
41517,533,"ABW","Aruba","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2005/abw_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
41518,533,"ABW","Aruba","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2005/abw_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
41519,533,"ABW","Aruba","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2005/abw_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
41520,533,"ABW","Aruba","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2005/abw_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
41521,533,"ABW","Aruba","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2005/abw_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
41522,533,"ABW","Aruba","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2005/abw_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
41523,533,"ABW","Aruba","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2005/abw_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
41524,533,"ABW","Aruba","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2005/abw_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
41525,533,"ABW","Aruba","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2006/abw_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
41526,533,"ABW","Aruba","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2006/abw_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
41527,533,"ABW","Aruba","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2006/abw_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
41528,533,"ABW","Aruba","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2006/abw_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
41529,533,"ABW","Aruba","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2006/abw_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
41530,533,"ABW","Aruba","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2006/abw_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
41531,533,"ABW","Aruba","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2006/abw_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
41532,533,"ABW","Aruba","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2006/abw_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
41533,533,"ABW","Aruba","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2007/abw_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
41534,533,"ABW","Aruba","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2007/abw_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
41535,533,"ABW","Aruba","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2007/abw_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
41536,533,"ABW","Aruba","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2007/abw_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
41537,533,"ABW","Aruba","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2007/abw_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
41538,533,"ABW","Aruba","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2007/abw_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
41539,533,"ABW","Aruba","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2007/abw_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
41540,533,"ABW","Aruba","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2007/abw_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
41541,533,"ABW","Aruba","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2008/abw_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
41542,533,"ABW","Aruba","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2008/abw_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
41543,533,"ABW","Aruba","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2008/abw_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
41544,533,"ABW","Aruba","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2008/abw_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
41545,533,"ABW","Aruba","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2008/abw_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
41546,533,"ABW","Aruba","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2008/abw_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
41547,533,"ABW","Aruba","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2008/abw_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
41548,533,"ABW","Aruba","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2008/abw_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
41549,533,"ABW","Aruba","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2009/abw_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
41550,533,"ABW","Aruba","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2009/abw_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
41551,533,"ABW","Aruba","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2009/abw_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
41552,533,"ABW","Aruba","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2009/abw_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
41553,533,"ABW","Aruba","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2009/abw_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
41554,533,"ABW","Aruba","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2009/abw_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
41555,533,"ABW","Aruba","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2009/abw_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
41556,533,"ABW","Aruba","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2009/abw_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
41557,533,"ABW","Aruba","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2010/abw_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
41558,533,"ABW","Aruba","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2010/abw_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
41559,533,"ABW","Aruba","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2010/abw_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
41560,533,"ABW","Aruba","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2010/abw_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
41561,533,"ABW","Aruba","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2010/abw_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
41562,533,"ABW","Aruba","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2010/abw_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
41563,533,"ABW","Aruba","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2010/abw_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
41564,533,"ABW","Aruba","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2010/abw_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
41565,533,"ABW","Aruba","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2011/abw_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
41566,533,"ABW","Aruba","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2011/abw_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
41567,533,"ABW","Aruba","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2011/abw_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
41568,533,"ABW","Aruba","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2011/abw_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
41569,533,"ABW","Aruba","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2011/abw_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
41570,533,"ABW","Aruba","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2011/abw_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
41571,533,"ABW","Aruba","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2011/abw_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
41572,533,"ABW","Aruba","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2011/abw_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
41573,533,"ABW","Aruba","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2012/abw_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
41574,533,"ABW","Aruba","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2012/abw_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
41575,533,"ABW","Aruba","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2012/abw_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
41576,533,"ABW","Aruba","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2012/abw_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
41577,533,"ABW","Aruba","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2012/abw_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
41578,533,"ABW","Aruba","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2012/abw_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
41579,533,"ABW","Aruba","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2012/abw_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
41580,533,"ABW","Aruba","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2012/abw_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
41581,533,"ABW","Aruba","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2013/abw_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
41582,533,"ABW","Aruba","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2013/abw_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
41583,533,"ABW","Aruba","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2013/abw_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
41584,533,"ABW","Aruba","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2013/abw_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
41585,533,"ABW","Aruba","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2013/abw_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
41586,533,"ABW","Aruba","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2013/abw_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
41587,533,"ABW","Aruba","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2013/abw_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
41588,533,"ABW","Aruba","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2013/abw_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
41589,533,"ABW","Aruba","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2014/abw_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
41590,533,"ABW","Aruba","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2014/abw_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
41591,533,"ABW","Aruba","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2014/abw_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
41592,533,"ABW","Aruba","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2014/abw_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
41593,533,"ABW","Aruba","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2014/abw_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
41594,533,"ABW","Aruba","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2014/abw_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
41595,533,"ABW","Aruba","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2014/abw_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
41596,533,"ABW","Aruba","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2014/abw_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
41597,533,"ABW","Aruba","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2015/abw_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
41598,533,"ABW","Aruba","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2015/abw_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
41599,533,"ABW","Aruba","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2015/abw_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
41600,533,"ABW","Aruba","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2015/abw_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
41601,533,"ABW","Aruba","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2015/abw_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
41602,533,"ABW","Aruba","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2015/abw_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
41603,533,"ABW","Aruba","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2015/abw_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
41604,533,"ABW","Aruba","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Annual/2015/abw_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
41605,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2000/sxm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
41606,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2000/sxm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
41607,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2000/sxm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
41608,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2000/sxm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
41609,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2000/sxm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
41610,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2000/sxm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
41611,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2000/sxm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
41612,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2000/sxm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
41613,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2001/sxm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
41614,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2001/sxm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
41615,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2001/sxm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
41616,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2001/sxm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
41617,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2001/sxm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
41618,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2001/sxm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
41619,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2001/sxm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
41620,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2001/sxm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
41621,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2002/sxm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
41622,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2002/sxm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
41623,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2002/sxm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
41624,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2002/sxm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
41625,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2002/sxm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
41626,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2002/sxm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
41627,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2002/sxm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
41628,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2002/sxm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
41629,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2003/sxm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
41630,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2003/sxm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
41631,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2003/sxm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
41632,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2003/sxm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
41633,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2003/sxm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
41634,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2003/sxm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
41635,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2003/sxm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
41636,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2003/sxm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
41637,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2004/sxm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
41638,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2004/sxm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
41639,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2004/sxm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
41640,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2004/sxm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
41641,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2004/sxm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
41642,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2004/sxm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
41643,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2004/sxm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
41644,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2004/sxm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
41645,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2005/sxm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
41646,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2005/sxm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
41647,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2005/sxm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
41648,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2005/sxm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
41649,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2005/sxm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
41650,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2005/sxm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
41651,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2005/sxm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
41652,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2005/sxm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
41653,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2006/sxm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
41654,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2006/sxm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
41655,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2006/sxm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
41656,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2006/sxm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
41657,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2006/sxm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
41658,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2006/sxm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
41659,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2006/sxm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
41660,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2006/sxm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
41661,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2007/sxm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
41662,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2007/sxm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
41663,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2007/sxm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
41664,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2007/sxm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
41665,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2007/sxm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
41666,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2007/sxm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
41667,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2007/sxm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
41668,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2007/sxm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
41669,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2008/sxm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
41670,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2008/sxm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
41671,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2008/sxm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
41672,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2008/sxm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
41673,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2008/sxm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
41674,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2008/sxm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
41675,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2008/sxm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
41676,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2008/sxm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
41677,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2009/sxm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
41678,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2009/sxm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
41679,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2009/sxm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
41680,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2009/sxm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
41681,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2009/sxm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
41682,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2009/sxm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
41683,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2009/sxm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
41684,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2009/sxm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
41685,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2010/sxm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
41686,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2010/sxm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
41687,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2010/sxm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
41688,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2010/sxm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
41689,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2010/sxm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
41690,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2010/sxm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
41691,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2010/sxm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
41692,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2010/sxm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
41693,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2011/sxm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
41694,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2011/sxm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
41695,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2011/sxm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
41696,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2011/sxm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
41697,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2011/sxm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
41698,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2011/sxm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
41699,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2011/sxm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
41700,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2011/sxm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
41701,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2012/sxm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
41702,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2012/sxm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
41703,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2012/sxm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
41704,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2012/sxm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
41705,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2012/sxm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
41706,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2012/sxm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
41707,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2012/sxm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
41708,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2012/sxm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
41709,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2013/sxm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
41710,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2013/sxm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
41711,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2013/sxm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
41712,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2013/sxm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
41713,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2013/sxm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
41714,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2013/sxm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
41715,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2013/sxm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
41716,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2013/sxm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
41717,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2014/sxm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
41718,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2014/sxm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
41719,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2014/sxm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
41720,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2014/sxm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
41721,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2014/sxm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
41722,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2014/sxm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
41723,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2014/sxm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
41724,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2014/sxm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
41725,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2015/sxm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
41726,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2015/sxm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
41727,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2015/sxm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
41728,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2015/sxm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
41729,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2015/sxm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
41730,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2015/sxm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
41731,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2015/sxm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
41732,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Annual/2015/sxm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
41733,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2000/bes_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
41734,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2000/bes_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
41735,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2000/bes_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
41736,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2000/bes_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
41737,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2000/bes_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
41738,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2000/bes_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
41739,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2000/bes_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
41740,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2000/bes_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
41741,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2001/bes_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
41742,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2001/bes_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
41743,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2001/bes_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
41744,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2001/bes_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
41745,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2001/bes_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
41746,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2001/bes_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
41747,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2001/bes_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
41748,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2001/bes_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
41749,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2002/bes_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
41750,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2002/bes_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
41751,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2002/bes_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
41752,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2002/bes_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
41753,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2002/bes_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
41754,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2002/bes_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
41755,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2002/bes_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
41756,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2002/bes_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
41757,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2003/bes_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
41758,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2003/bes_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
41759,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2003/bes_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
41760,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2003/bes_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
41761,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2003/bes_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
41762,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2003/bes_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
41763,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2003/bes_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
41764,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2003/bes_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
41765,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2004/bes_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
41766,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2004/bes_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
41767,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2004/bes_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
41768,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2004/bes_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
41769,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2004/bes_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
41770,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2004/bes_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
41771,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2004/bes_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
41772,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2004/bes_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
41773,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2005/bes_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
41774,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2005/bes_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
41775,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2005/bes_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
41776,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2005/bes_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
41777,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2005/bes_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
41778,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2005/bes_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
41779,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2005/bes_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
41780,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2005/bes_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
41781,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2006/bes_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
41782,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2006/bes_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
41783,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2006/bes_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
41784,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2006/bes_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
41785,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2006/bes_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
41786,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2006/bes_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
41787,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2006/bes_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
41788,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2006/bes_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
41789,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2007/bes_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
41790,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2007/bes_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
41791,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2007/bes_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
41792,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2007/bes_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
41793,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2007/bes_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
41794,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2007/bes_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
41795,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2007/bes_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
41796,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2007/bes_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
41797,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2008/bes_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
41798,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2008/bes_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
41799,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2008/bes_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
41800,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2008/bes_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
41801,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2008/bes_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
41802,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2008/bes_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
41803,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2008/bes_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
41804,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2008/bes_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
41805,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2009/bes_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
41806,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2009/bes_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
41807,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2009/bes_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
41808,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2009/bes_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
41809,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2009/bes_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
41810,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2009/bes_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
41811,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2009/bes_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
41812,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2009/bes_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
41813,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2010/bes_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
41814,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2010/bes_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
41815,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2010/bes_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
41816,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2010/bes_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
41817,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2010/bes_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
41818,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2010/bes_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
41819,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2010/bes_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
41820,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2010/bes_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
41821,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2011/bes_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
41822,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2011/bes_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
41823,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2011/bes_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
41824,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2011/bes_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
41825,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2011/bes_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
41826,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2011/bes_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
41827,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2011/bes_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
41828,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2011/bes_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
41829,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2012/bes_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
41830,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2012/bes_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
41831,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2012/bes_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
41832,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2012/bes_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
41833,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2012/bes_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
41834,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2012/bes_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
41835,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2012/bes_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
41836,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2012/bes_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
41837,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2013/bes_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
41838,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2013/bes_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
41839,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2013/bes_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
41840,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2013/bes_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
41841,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2013/bes_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
41842,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2013/bes_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
41843,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2013/bes_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
41844,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2013/bes_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
41845,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2014/bes_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
41846,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2014/bes_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
41847,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2014/bes_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
41848,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2014/bes_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
41849,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2014/bes_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
41850,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2014/bes_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
41851,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2014/bes_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
41852,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2014/bes_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
41853,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2015/bes_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
41854,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2015/bes_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
41855,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2015/bes_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
41856,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2015/bes_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
41857,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2015/bes_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
41858,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2015/bes_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
41859,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2015/bes_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
41860,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Annual/2015/bes_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
41861,540,"NCL","New Caledonia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2000/ncl_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
41862,540,"NCL","New Caledonia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2000/ncl_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
41863,540,"NCL","New Caledonia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2000/ncl_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
41864,540,"NCL","New Caledonia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2000/ncl_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
41865,540,"NCL","New Caledonia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2000/ncl_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
41866,540,"NCL","New Caledonia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2000/ncl_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
41867,540,"NCL","New Caledonia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2000/ncl_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
41868,540,"NCL","New Caledonia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2000/ncl_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
41869,540,"NCL","New Caledonia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2001/ncl_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
41870,540,"NCL","New Caledonia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2001/ncl_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
41871,540,"NCL","New Caledonia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2001/ncl_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
41872,540,"NCL","New Caledonia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2001/ncl_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
41873,540,"NCL","New Caledonia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2001/ncl_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
41874,540,"NCL","New Caledonia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2001/ncl_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
41875,540,"NCL","New Caledonia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2001/ncl_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
41876,540,"NCL","New Caledonia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2001/ncl_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
41877,540,"NCL","New Caledonia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2002/ncl_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
41878,540,"NCL","New Caledonia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2002/ncl_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
41879,540,"NCL","New Caledonia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2002/ncl_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
41880,540,"NCL","New Caledonia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2002/ncl_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
41881,540,"NCL","New Caledonia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2002/ncl_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
41882,540,"NCL","New Caledonia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2002/ncl_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
41883,540,"NCL","New Caledonia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2002/ncl_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
41884,540,"NCL","New Caledonia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2002/ncl_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
41885,540,"NCL","New Caledonia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2003/ncl_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
41886,540,"NCL","New Caledonia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2003/ncl_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
41887,540,"NCL","New Caledonia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2003/ncl_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
41888,540,"NCL","New Caledonia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2003/ncl_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
41889,540,"NCL","New Caledonia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2003/ncl_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
41890,540,"NCL","New Caledonia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2003/ncl_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
41891,540,"NCL","New Caledonia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2003/ncl_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
41892,540,"NCL","New Caledonia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2003/ncl_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
41893,540,"NCL","New Caledonia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2004/ncl_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
41894,540,"NCL","New Caledonia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2004/ncl_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
41895,540,"NCL","New Caledonia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2004/ncl_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
41896,540,"NCL","New Caledonia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2004/ncl_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
41897,540,"NCL","New Caledonia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2004/ncl_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
41898,540,"NCL","New Caledonia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2004/ncl_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
41899,540,"NCL","New Caledonia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2004/ncl_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
41900,540,"NCL","New Caledonia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2004/ncl_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
41901,540,"NCL","New Caledonia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2005/ncl_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
41902,540,"NCL","New Caledonia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2005/ncl_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
41903,540,"NCL","New Caledonia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2005/ncl_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
41904,540,"NCL","New Caledonia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2005/ncl_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
41905,540,"NCL","New Caledonia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2005/ncl_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
41906,540,"NCL","New Caledonia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2005/ncl_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
41907,540,"NCL","New Caledonia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2005/ncl_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
41908,540,"NCL","New Caledonia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2005/ncl_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
41909,540,"NCL","New Caledonia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2006/ncl_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
41910,540,"NCL","New Caledonia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2006/ncl_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
41911,540,"NCL","New Caledonia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2006/ncl_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
41912,540,"NCL","New Caledonia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2006/ncl_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
41913,540,"NCL","New Caledonia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2006/ncl_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
41914,540,"NCL","New Caledonia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2006/ncl_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
41915,540,"NCL","New Caledonia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2006/ncl_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
41916,540,"NCL","New Caledonia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2006/ncl_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
41917,540,"NCL","New Caledonia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2007/ncl_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
41918,540,"NCL","New Caledonia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2007/ncl_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
41919,540,"NCL","New Caledonia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2007/ncl_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
41920,540,"NCL","New Caledonia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2007/ncl_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
41921,540,"NCL","New Caledonia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2007/ncl_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
41922,540,"NCL","New Caledonia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2007/ncl_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
41923,540,"NCL","New Caledonia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2007/ncl_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
41924,540,"NCL","New Caledonia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2007/ncl_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
41925,540,"NCL","New Caledonia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2008/ncl_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
41926,540,"NCL","New Caledonia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2008/ncl_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
41927,540,"NCL","New Caledonia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2008/ncl_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
41928,540,"NCL","New Caledonia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2008/ncl_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
41929,540,"NCL","New Caledonia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2008/ncl_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
41930,540,"NCL","New Caledonia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2008/ncl_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
41931,540,"NCL","New Caledonia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2008/ncl_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
41932,540,"NCL","New Caledonia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2008/ncl_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
41933,540,"NCL","New Caledonia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2009/ncl_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
41934,540,"NCL","New Caledonia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2009/ncl_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
41935,540,"NCL","New Caledonia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2009/ncl_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
41936,540,"NCL","New Caledonia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2009/ncl_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
41937,540,"NCL","New Caledonia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2009/ncl_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
41938,540,"NCL","New Caledonia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2009/ncl_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
41939,540,"NCL","New Caledonia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2009/ncl_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
41940,540,"NCL","New Caledonia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2009/ncl_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
41941,540,"NCL","New Caledonia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2010/ncl_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
41942,540,"NCL","New Caledonia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2010/ncl_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
41943,540,"NCL","New Caledonia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2010/ncl_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
41944,540,"NCL","New Caledonia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2010/ncl_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
41945,540,"NCL","New Caledonia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2010/ncl_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
41946,540,"NCL","New Caledonia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2010/ncl_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
41947,540,"NCL","New Caledonia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2010/ncl_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
41948,540,"NCL","New Caledonia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2010/ncl_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
41949,540,"NCL","New Caledonia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2011/ncl_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
41950,540,"NCL","New Caledonia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2011/ncl_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
41951,540,"NCL","New Caledonia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2011/ncl_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
41952,540,"NCL","New Caledonia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2011/ncl_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
41953,540,"NCL","New Caledonia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2011/ncl_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
41954,540,"NCL","New Caledonia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2011/ncl_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
41955,540,"NCL","New Caledonia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2011/ncl_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
41956,540,"NCL","New Caledonia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2011/ncl_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
41957,540,"NCL","New Caledonia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2012/ncl_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
41958,540,"NCL","New Caledonia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2012/ncl_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
41959,540,"NCL","New Caledonia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2012/ncl_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
41960,540,"NCL","New Caledonia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2012/ncl_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
41961,540,"NCL","New Caledonia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2012/ncl_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
41962,540,"NCL","New Caledonia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2012/ncl_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
41963,540,"NCL","New Caledonia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2012/ncl_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
41964,540,"NCL","New Caledonia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2012/ncl_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
41965,540,"NCL","New Caledonia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2013/ncl_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
41966,540,"NCL","New Caledonia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2013/ncl_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
41967,540,"NCL","New Caledonia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2013/ncl_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
41968,540,"NCL","New Caledonia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2013/ncl_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
41969,540,"NCL","New Caledonia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2013/ncl_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
41970,540,"NCL","New Caledonia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2013/ncl_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
41971,540,"NCL","New Caledonia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2013/ncl_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
41972,540,"NCL","New Caledonia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2013/ncl_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
41973,540,"NCL","New Caledonia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2014/ncl_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
41974,540,"NCL","New Caledonia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2014/ncl_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
41975,540,"NCL","New Caledonia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2014/ncl_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
41976,540,"NCL","New Caledonia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2014/ncl_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
41977,540,"NCL","New Caledonia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2014/ncl_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
41978,540,"NCL","New Caledonia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2014/ncl_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
41979,540,"NCL","New Caledonia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2014/ncl_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
41980,540,"NCL","New Caledonia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2014/ncl_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
41981,540,"NCL","New Caledonia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2015/ncl_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
41982,540,"NCL","New Caledonia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2015/ncl_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
41983,540,"NCL","New Caledonia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2015/ncl_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
41984,540,"NCL","New Caledonia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2015/ncl_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
41985,540,"NCL","New Caledonia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2015/ncl_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
41986,540,"NCL","New Caledonia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2015/ncl_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
41987,540,"NCL","New Caledonia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2015/ncl_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
41988,540,"NCL","New Caledonia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Annual/2015/ncl_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
41989,548,"VUT","Vanuatu","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2000/vut_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
41990,548,"VUT","Vanuatu","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2000/vut_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
41991,548,"VUT","Vanuatu","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2000/vut_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
41992,548,"VUT","Vanuatu","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2000/vut_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
41993,548,"VUT","Vanuatu","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2000/vut_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
41994,548,"VUT","Vanuatu","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2000/vut_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
41995,548,"VUT","Vanuatu","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2000/vut_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
41996,548,"VUT","Vanuatu","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2000/vut_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
41997,548,"VUT","Vanuatu","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2001/vut_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
41998,548,"VUT","Vanuatu","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2001/vut_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
41999,548,"VUT","Vanuatu","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2001/vut_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
42000,548,"VUT","Vanuatu","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2001/vut_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
42001,548,"VUT","Vanuatu","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2001/vut_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
42002,548,"VUT","Vanuatu","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2001/vut_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
42003,548,"VUT","Vanuatu","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2001/vut_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
42004,548,"VUT","Vanuatu","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2001/vut_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
42005,548,"VUT","Vanuatu","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2002/vut_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
42006,548,"VUT","Vanuatu","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2002/vut_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
42007,548,"VUT","Vanuatu","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2002/vut_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
42008,548,"VUT","Vanuatu","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2002/vut_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
42009,548,"VUT","Vanuatu","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2002/vut_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
42010,548,"VUT","Vanuatu","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2002/vut_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
42011,548,"VUT","Vanuatu","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2002/vut_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
42012,548,"VUT","Vanuatu","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2002/vut_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
42013,548,"VUT","Vanuatu","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2003/vut_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
42014,548,"VUT","Vanuatu","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2003/vut_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
42015,548,"VUT","Vanuatu","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2003/vut_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
42016,548,"VUT","Vanuatu","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2003/vut_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
42017,548,"VUT","Vanuatu","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2003/vut_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
42018,548,"VUT","Vanuatu","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2003/vut_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
42019,548,"VUT","Vanuatu","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2003/vut_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
42020,548,"VUT","Vanuatu","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2003/vut_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
42021,548,"VUT","Vanuatu","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2004/vut_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
42022,548,"VUT","Vanuatu","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2004/vut_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
42023,548,"VUT","Vanuatu","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2004/vut_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
42024,548,"VUT","Vanuatu","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2004/vut_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
42025,548,"VUT","Vanuatu","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2004/vut_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
42026,548,"VUT","Vanuatu","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2004/vut_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
42027,548,"VUT","Vanuatu","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2004/vut_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
42028,548,"VUT","Vanuatu","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2004/vut_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
42029,548,"VUT","Vanuatu","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2005/vut_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
42030,548,"VUT","Vanuatu","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2005/vut_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
42031,548,"VUT","Vanuatu","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2005/vut_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
42032,548,"VUT","Vanuatu","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2005/vut_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
42033,548,"VUT","Vanuatu","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2005/vut_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
42034,548,"VUT","Vanuatu","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2005/vut_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
42035,548,"VUT","Vanuatu","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2005/vut_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
42036,548,"VUT","Vanuatu","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2005/vut_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
42037,548,"VUT","Vanuatu","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2006/vut_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
42038,548,"VUT","Vanuatu","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2006/vut_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
42039,548,"VUT","Vanuatu","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2006/vut_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
42040,548,"VUT","Vanuatu","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2006/vut_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
42041,548,"VUT","Vanuatu","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2006/vut_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
42042,548,"VUT","Vanuatu","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2006/vut_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
42043,548,"VUT","Vanuatu","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2006/vut_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
42044,548,"VUT","Vanuatu","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2006/vut_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
42045,548,"VUT","Vanuatu","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2007/vut_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
42046,548,"VUT","Vanuatu","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2007/vut_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
42047,548,"VUT","Vanuatu","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2007/vut_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
42048,548,"VUT","Vanuatu","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2007/vut_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
42049,548,"VUT","Vanuatu","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2007/vut_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
42050,548,"VUT","Vanuatu","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2007/vut_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
42051,548,"VUT","Vanuatu","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2007/vut_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
42052,548,"VUT","Vanuatu","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2007/vut_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
42053,548,"VUT","Vanuatu","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2008/vut_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
42054,548,"VUT","Vanuatu","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2008/vut_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
42055,548,"VUT","Vanuatu","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2008/vut_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
42056,548,"VUT","Vanuatu","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2008/vut_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
42057,548,"VUT","Vanuatu","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2008/vut_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
42058,548,"VUT","Vanuatu","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2008/vut_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
42059,548,"VUT","Vanuatu","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2008/vut_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
42060,548,"VUT","Vanuatu","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2008/vut_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
42061,548,"VUT","Vanuatu","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2009/vut_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
42062,548,"VUT","Vanuatu","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2009/vut_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
42063,548,"VUT","Vanuatu","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2009/vut_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
42064,548,"VUT","Vanuatu","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2009/vut_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
42065,548,"VUT","Vanuatu","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2009/vut_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
42066,548,"VUT","Vanuatu","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2009/vut_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
42067,548,"VUT","Vanuatu","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2009/vut_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
42068,548,"VUT","Vanuatu","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2009/vut_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
42069,548,"VUT","Vanuatu","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2010/vut_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
42070,548,"VUT","Vanuatu","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2010/vut_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
42071,548,"VUT","Vanuatu","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2010/vut_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
42072,548,"VUT","Vanuatu","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2010/vut_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
42073,548,"VUT","Vanuatu","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2010/vut_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
42074,548,"VUT","Vanuatu","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2010/vut_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
42075,548,"VUT","Vanuatu","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2010/vut_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
42076,548,"VUT","Vanuatu","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2010/vut_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
42077,548,"VUT","Vanuatu","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2011/vut_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
42078,548,"VUT","Vanuatu","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2011/vut_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
42079,548,"VUT","Vanuatu","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2011/vut_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
42080,548,"VUT","Vanuatu","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2011/vut_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
42081,548,"VUT","Vanuatu","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2011/vut_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
42082,548,"VUT","Vanuatu","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2011/vut_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
42083,548,"VUT","Vanuatu","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2011/vut_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
42084,548,"VUT","Vanuatu","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2011/vut_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
42085,548,"VUT","Vanuatu","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2012/vut_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
42086,548,"VUT","Vanuatu","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2012/vut_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
42087,548,"VUT","Vanuatu","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2012/vut_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
42088,548,"VUT","Vanuatu","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2012/vut_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
42089,548,"VUT","Vanuatu","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2012/vut_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
42090,548,"VUT","Vanuatu","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2012/vut_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
42091,548,"VUT","Vanuatu","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2012/vut_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
42092,548,"VUT","Vanuatu","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2012/vut_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
42093,548,"VUT","Vanuatu","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2013/vut_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
42094,548,"VUT","Vanuatu","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2013/vut_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
42095,548,"VUT","Vanuatu","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2013/vut_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
42096,548,"VUT","Vanuatu","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2013/vut_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
42097,548,"VUT","Vanuatu","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2013/vut_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
42098,548,"VUT","Vanuatu","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2013/vut_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
42099,548,"VUT","Vanuatu","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2013/vut_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
42100,548,"VUT","Vanuatu","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2013/vut_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
42101,548,"VUT","Vanuatu","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2014/vut_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
42102,548,"VUT","Vanuatu","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2014/vut_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
42103,548,"VUT","Vanuatu","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2014/vut_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
42104,548,"VUT","Vanuatu","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2014/vut_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
42105,548,"VUT","Vanuatu","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2014/vut_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
42106,548,"VUT","Vanuatu","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2014/vut_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
42107,548,"VUT","Vanuatu","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2014/vut_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
42108,548,"VUT","Vanuatu","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2014/vut_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
42109,548,"VUT","Vanuatu","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2015/vut_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
42110,548,"VUT","Vanuatu","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2015/vut_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
42111,548,"VUT","Vanuatu","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2015/vut_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
42112,548,"VUT","Vanuatu","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2015/vut_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
42113,548,"VUT","Vanuatu","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2015/vut_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
42114,548,"VUT","Vanuatu","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2015/vut_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
42115,548,"VUT","Vanuatu","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2015/vut_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
42116,548,"VUT","Vanuatu","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Annual/2015/vut_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
42117,554,"NZL","New Zealand","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2000/nzl_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
42118,554,"NZL","New Zealand","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2000/nzl_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
42119,554,"NZL","New Zealand","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2000/nzl_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
42120,554,"NZL","New Zealand","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2000/nzl_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
42121,554,"NZL","New Zealand","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2000/nzl_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
42122,554,"NZL","New Zealand","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2000/nzl_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
42123,554,"NZL","New Zealand","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2000/nzl_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
42124,554,"NZL","New Zealand","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2000/nzl_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
42125,554,"NZL","New Zealand","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2001/nzl_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
42126,554,"NZL","New Zealand","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2001/nzl_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
42127,554,"NZL","New Zealand","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2001/nzl_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
42128,554,"NZL","New Zealand","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2001/nzl_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
42129,554,"NZL","New Zealand","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2001/nzl_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
42130,554,"NZL","New Zealand","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2001/nzl_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
42131,554,"NZL","New Zealand","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2001/nzl_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
42132,554,"NZL","New Zealand","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2001/nzl_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
42133,554,"NZL","New Zealand","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2002/nzl_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
42134,554,"NZL","New Zealand","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2002/nzl_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
42135,554,"NZL","New Zealand","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2002/nzl_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
42136,554,"NZL","New Zealand","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2002/nzl_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
42137,554,"NZL","New Zealand","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2002/nzl_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
42138,554,"NZL","New Zealand","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2002/nzl_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
42139,554,"NZL","New Zealand","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2002/nzl_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
42140,554,"NZL","New Zealand","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2002/nzl_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
42141,554,"NZL","New Zealand","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2003/nzl_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
42142,554,"NZL","New Zealand","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2003/nzl_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
42143,554,"NZL","New Zealand","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2003/nzl_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
42144,554,"NZL","New Zealand","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2003/nzl_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
42145,554,"NZL","New Zealand","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2003/nzl_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
42146,554,"NZL","New Zealand","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2003/nzl_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
42147,554,"NZL","New Zealand","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2003/nzl_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
42148,554,"NZL","New Zealand","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2003/nzl_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
42149,554,"NZL","New Zealand","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2004/nzl_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
42150,554,"NZL","New Zealand","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2004/nzl_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
42151,554,"NZL","New Zealand","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2004/nzl_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
42152,554,"NZL","New Zealand","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2004/nzl_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
42153,554,"NZL","New Zealand","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2004/nzl_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
42154,554,"NZL","New Zealand","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2004/nzl_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
42155,554,"NZL","New Zealand","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2004/nzl_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
42156,554,"NZL","New Zealand","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2004/nzl_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
42157,554,"NZL","New Zealand","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2005/nzl_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
42158,554,"NZL","New Zealand","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2005/nzl_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
42159,554,"NZL","New Zealand","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2005/nzl_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
42160,554,"NZL","New Zealand","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2005/nzl_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
42161,554,"NZL","New Zealand","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2005/nzl_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
42162,554,"NZL","New Zealand","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2005/nzl_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
42163,554,"NZL","New Zealand","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2005/nzl_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
42164,554,"NZL","New Zealand","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2005/nzl_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
42165,554,"NZL","New Zealand","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2006/nzl_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
42166,554,"NZL","New Zealand","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2006/nzl_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
42167,554,"NZL","New Zealand","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2006/nzl_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
42168,554,"NZL","New Zealand","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2006/nzl_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
42169,554,"NZL","New Zealand","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2006/nzl_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
42170,554,"NZL","New Zealand","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2006/nzl_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
42171,554,"NZL","New Zealand","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2006/nzl_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
42172,554,"NZL","New Zealand","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2006/nzl_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
42173,554,"NZL","New Zealand","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2007/nzl_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
42174,554,"NZL","New Zealand","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2007/nzl_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
42175,554,"NZL","New Zealand","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2007/nzl_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
42176,554,"NZL","New Zealand","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2007/nzl_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
42177,554,"NZL","New Zealand","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2007/nzl_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
42178,554,"NZL","New Zealand","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2007/nzl_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
42179,554,"NZL","New Zealand","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2007/nzl_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
42180,554,"NZL","New Zealand","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2007/nzl_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
42181,554,"NZL","New Zealand","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2008/nzl_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
42182,554,"NZL","New Zealand","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2008/nzl_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
42183,554,"NZL","New Zealand","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2008/nzl_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
42184,554,"NZL","New Zealand","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2008/nzl_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
42185,554,"NZL","New Zealand","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2008/nzl_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
42186,554,"NZL","New Zealand","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2008/nzl_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
42187,554,"NZL","New Zealand","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2008/nzl_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
42188,554,"NZL","New Zealand","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2008/nzl_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
42189,554,"NZL","New Zealand","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2009/nzl_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
42190,554,"NZL","New Zealand","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2009/nzl_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
42191,554,"NZL","New Zealand","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2009/nzl_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
42192,554,"NZL","New Zealand","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2009/nzl_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
42193,554,"NZL","New Zealand","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2009/nzl_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
42194,554,"NZL","New Zealand","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2009/nzl_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
42195,554,"NZL","New Zealand","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2009/nzl_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
42196,554,"NZL","New Zealand","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2009/nzl_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
42197,554,"NZL","New Zealand","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2010/nzl_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
42198,554,"NZL","New Zealand","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2010/nzl_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
42199,554,"NZL","New Zealand","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2010/nzl_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
42200,554,"NZL","New Zealand","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2010/nzl_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
42201,554,"NZL","New Zealand","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2010/nzl_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
42202,554,"NZL","New Zealand","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2010/nzl_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
42203,554,"NZL","New Zealand","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2010/nzl_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
42204,554,"NZL","New Zealand","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2010/nzl_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
42205,554,"NZL","New Zealand","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2011/nzl_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
42206,554,"NZL","New Zealand","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2011/nzl_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
42207,554,"NZL","New Zealand","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2011/nzl_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
42208,554,"NZL","New Zealand","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2011/nzl_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
42209,554,"NZL","New Zealand","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2011/nzl_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
42210,554,"NZL","New Zealand","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2011/nzl_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
42211,554,"NZL","New Zealand","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2011/nzl_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
42212,554,"NZL","New Zealand","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2011/nzl_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
42213,554,"NZL","New Zealand","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2012/nzl_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
42214,554,"NZL","New Zealand","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2012/nzl_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
42215,554,"NZL","New Zealand","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2012/nzl_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
42216,554,"NZL","New Zealand","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2012/nzl_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
42217,554,"NZL","New Zealand","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2012/nzl_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
42218,554,"NZL","New Zealand","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2012/nzl_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
42219,554,"NZL","New Zealand","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2012/nzl_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
42220,554,"NZL","New Zealand","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2012/nzl_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
42221,554,"NZL","New Zealand","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2013/nzl_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
42222,554,"NZL","New Zealand","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2013/nzl_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
42223,554,"NZL","New Zealand","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2013/nzl_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
42224,554,"NZL","New Zealand","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2013/nzl_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
42225,554,"NZL","New Zealand","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2013/nzl_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
42226,554,"NZL","New Zealand","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2013/nzl_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
42227,554,"NZL","New Zealand","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2013/nzl_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
42228,554,"NZL","New Zealand","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2013/nzl_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
42229,554,"NZL","New Zealand","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2014/nzl_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
42230,554,"NZL","New Zealand","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2014/nzl_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
42231,554,"NZL","New Zealand","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2014/nzl_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
42232,554,"NZL","New Zealand","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2014/nzl_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
42233,554,"NZL","New Zealand","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2014/nzl_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
42234,554,"NZL","New Zealand","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2014/nzl_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
42235,554,"NZL","New Zealand","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2014/nzl_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
42236,554,"NZL","New Zealand","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2014/nzl_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
42237,554,"NZL","New Zealand","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2015/nzl_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
42238,554,"NZL","New Zealand","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2015/nzl_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
42239,554,"NZL","New Zealand","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2015/nzl_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
42240,554,"NZL","New Zealand","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2015/nzl_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
42241,554,"NZL","New Zealand","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2015/nzl_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
42242,554,"NZL","New Zealand","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2015/nzl_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
42243,554,"NZL","New Zealand","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2015/nzl_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
42244,554,"NZL","New Zealand","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Annual/2015/nzl_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
42245,558,"NIC","Nicaragua","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2000/nic_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
42246,558,"NIC","Nicaragua","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2000/nic_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
42247,558,"NIC","Nicaragua","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2000/nic_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
42248,558,"NIC","Nicaragua","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2000/nic_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
42249,558,"NIC","Nicaragua","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2000/nic_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
42250,558,"NIC","Nicaragua","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2000/nic_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
42251,558,"NIC","Nicaragua","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2000/nic_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
42252,558,"NIC","Nicaragua","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2000/nic_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
42253,558,"NIC","Nicaragua","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2001/nic_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
42254,558,"NIC","Nicaragua","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2001/nic_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
42255,558,"NIC","Nicaragua","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2001/nic_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
42256,558,"NIC","Nicaragua","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2001/nic_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
42257,558,"NIC","Nicaragua","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2001/nic_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
42258,558,"NIC","Nicaragua","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2001/nic_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
42259,558,"NIC","Nicaragua","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2001/nic_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
42260,558,"NIC","Nicaragua","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2001/nic_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
42261,558,"NIC","Nicaragua","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2002/nic_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
42262,558,"NIC","Nicaragua","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2002/nic_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
42263,558,"NIC","Nicaragua","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2002/nic_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
42264,558,"NIC","Nicaragua","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2002/nic_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
42265,558,"NIC","Nicaragua","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2002/nic_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
42266,558,"NIC","Nicaragua","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2002/nic_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
42267,558,"NIC","Nicaragua","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2002/nic_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
42268,558,"NIC","Nicaragua","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2002/nic_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
42269,558,"NIC","Nicaragua","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2003/nic_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
42270,558,"NIC","Nicaragua","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2003/nic_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
42271,558,"NIC","Nicaragua","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2003/nic_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
42272,558,"NIC","Nicaragua","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2003/nic_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
42273,558,"NIC","Nicaragua","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2003/nic_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
42274,558,"NIC","Nicaragua","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2003/nic_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
42275,558,"NIC","Nicaragua","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2003/nic_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
42276,558,"NIC","Nicaragua","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2003/nic_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
42277,558,"NIC","Nicaragua","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2004/nic_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
42278,558,"NIC","Nicaragua","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2004/nic_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
42279,558,"NIC","Nicaragua","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2004/nic_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
42280,558,"NIC","Nicaragua","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2004/nic_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
42281,558,"NIC","Nicaragua","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2004/nic_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
42282,558,"NIC","Nicaragua","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2004/nic_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
42283,558,"NIC","Nicaragua","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2004/nic_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
42284,558,"NIC","Nicaragua","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2004/nic_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
42285,558,"NIC","Nicaragua","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2005/nic_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
42286,558,"NIC","Nicaragua","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2005/nic_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
42287,558,"NIC","Nicaragua","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2005/nic_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
42288,558,"NIC","Nicaragua","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2005/nic_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
42289,558,"NIC","Nicaragua","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2005/nic_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
42290,558,"NIC","Nicaragua","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2005/nic_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
42291,558,"NIC","Nicaragua","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2005/nic_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
42292,558,"NIC","Nicaragua","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2005/nic_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
42293,558,"NIC","Nicaragua","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2006/nic_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
42294,558,"NIC","Nicaragua","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2006/nic_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
42295,558,"NIC","Nicaragua","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2006/nic_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
42296,558,"NIC","Nicaragua","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2006/nic_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
42297,558,"NIC","Nicaragua","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2006/nic_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
42298,558,"NIC","Nicaragua","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2006/nic_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
42299,558,"NIC","Nicaragua","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2006/nic_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
42300,558,"NIC","Nicaragua","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2006/nic_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
42301,558,"NIC","Nicaragua","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2007/nic_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
42302,558,"NIC","Nicaragua","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2007/nic_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
42303,558,"NIC","Nicaragua","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2007/nic_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
42304,558,"NIC","Nicaragua","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2007/nic_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
42305,558,"NIC","Nicaragua","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2007/nic_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
42306,558,"NIC","Nicaragua","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2007/nic_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
42307,558,"NIC","Nicaragua","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2007/nic_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
42308,558,"NIC","Nicaragua","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2007/nic_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
42309,558,"NIC","Nicaragua","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2008/nic_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
42310,558,"NIC","Nicaragua","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2008/nic_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
42311,558,"NIC","Nicaragua","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2008/nic_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
42312,558,"NIC","Nicaragua","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2008/nic_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
42313,558,"NIC","Nicaragua","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2008/nic_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
42314,558,"NIC","Nicaragua","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2008/nic_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
42315,558,"NIC","Nicaragua","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2008/nic_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
42316,558,"NIC","Nicaragua","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2008/nic_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
42317,558,"NIC","Nicaragua","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2009/nic_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
42318,558,"NIC","Nicaragua","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2009/nic_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
42319,558,"NIC","Nicaragua","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2009/nic_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
42320,558,"NIC","Nicaragua","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2009/nic_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
42321,558,"NIC","Nicaragua","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2009/nic_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
42322,558,"NIC","Nicaragua","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2009/nic_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
42323,558,"NIC","Nicaragua","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2009/nic_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
42324,558,"NIC","Nicaragua","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2009/nic_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
42325,558,"NIC","Nicaragua","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2010/nic_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
42326,558,"NIC","Nicaragua","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2010/nic_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
42327,558,"NIC","Nicaragua","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2010/nic_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
42328,558,"NIC","Nicaragua","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2010/nic_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
42329,558,"NIC","Nicaragua","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2010/nic_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
42330,558,"NIC","Nicaragua","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2010/nic_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
42331,558,"NIC","Nicaragua","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2010/nic_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
42332,558,"NIC","Nicaragua","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2010/nic_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
42333,558,"NIC","Nicaragua","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2011/nic_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
42334,558,"NIC","Nicaragua","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2011/nic_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
42335,558,"NIC","Nicaragua","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2011/nic_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
42336,558,"NIC","Nicaragua","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2011/nic_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
42337,558,"NIC","Nicaragua","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2011/nic_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
42338,558,"NIC","Nicaragua","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2011/nic_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
42339,558,"NIC","Nicaragua","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2011/nic_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
42340,558,"NIC","Nicaragua","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2011/nic_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
42341,558,"NIC","Nicaragua","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2012/nic_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
42342,558,"NIC","Nicaragua","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2012/nic_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
42343,558,"NIC","Nicaragua","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2012/nic_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
42344,558,"NIC","Nicaragua","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2012/nic_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
42345,558,"NIC","Nicaragua","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2012/nic_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
42346,558,"NIC","Nicaragua","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2012/nic_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
42347,558,"NIC","Nicaragua","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2012/nic_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
42348,558,"NIC","Nicaragua","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2012/nic_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
42349,558,"NIC","Nicaragua","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2013/nic_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
42350,558,"NIC","Nicaragua","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2013/nic_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
42351,558,"NIC","Nicaragua","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2013/nic_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
42352,558,"NIC","Nicaragua","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2013/nic_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
42353,558,"NIC","Nicaragua","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2013/nic_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
42354,558,"NIC","Nicaragua","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2013/nic_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
42355,558,"NIC","Nicaragua","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2013/nic_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
42356,558,"NIC","Nicaragua","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2013/nic_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
42357,558,"NIC","Nicaragua","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2014/nic_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
42358,558,"NIC","Nicaragua","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2014/nic_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
42359,558,"NIC","Nicaragua","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2014/nic_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
42360,558,"NIC","Nicaragua","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2014/nic_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
42361,558,"NIC","Nicaragua","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2014/nic_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
42362,558,"NIC","Nicaragua","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2014/nic_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
42363,558,"NIC","Nicaragua","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2014/nic_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
42364,558,"NIC","Nicaragua","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2014/nic_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
42365,558,"NIC","Nicaragua","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2015/nic_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
42366,558,"NIC","Nicaragua","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2015/nic_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
42367,558,"NIC","Nicaragua","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2015/nic_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
42368,558,"NIC","Nicaragua","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2015/nic_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
42369,558,"NIC","Nicaragua","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2015/nic_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
42370,558,"NIC","Nicaragua","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2015/nic_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
42371,558,"NIC","Nicaragua","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2015/nic_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
42372,558,"NIC","Nicaragua","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Annual/2015/nic_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
42373,562,"NER","Niger","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2000/ner_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
42374,562,"NER","Niger","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2000/ner_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
42375,562,"NER","Niger","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2000/ner_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
42376,562,"NER","Niger","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2000/ner_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
42377,562,"NER","Niger","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2000/ner_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
42378,562,"NER","Niger","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2000/ner_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
42379,562,"NER","Niger","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2000/ner_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
42380,562,"NER","Niger","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2000/ner_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
42381,562,"NER","Niger","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2001/ner_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
42382,562,"NER","Niger","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2001/ner_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
42383,562,"NER","Niger","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2001/ner_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
42384,562,"NER","Niger","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2001/ner_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
42385,562,"NER","Niger","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2001/ner_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
42386,562,"NER","Niger","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2001/ner_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
42387,562,"NER","Niger","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2001/ner_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
42388,562,"NER","Niger","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2001/ner_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
42389,562,"NER","Niger","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2002/ner_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
42390,562,"NER","Niger","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2002/ner_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
42391,562,"NER","Niger","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2002/ner_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
42392,562,"NER","Niger","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2002/ner_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
42393,562,"NER","Niger","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2002/ner_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
42394,562,"NER","Niger","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2002/ner_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
42395,562,"NER","Niger","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2002/ner_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
42396,562,"NER","Niger","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2002/ner_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
42397,562,"NER","Niger","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2003/ner_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
42398,562,"NER","Niger","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2003/ner_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
42399,562,"NER","Niger","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2003/ner_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
42400,562,"NER","Niger","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2003/ner_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
42401,562,"NER","Niger","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2003/ner_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
42402,562,"NER","Niger","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2003/ner_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
42403,562,"NER","Niger","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2003/ner_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
42404,562,"NER","Niger","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2003/ner_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
42405,562,"NER","Niger","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2004/ner_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
42406,562,"NER","Niger","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2004/ner_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
42407,562,"NER","Niger","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2004/ner_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
42408,562,"NER","Niger","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2004/ner_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
42409,562,"NER","Niger","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2004/ner_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
42410,562,"NER","Niger","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2004/ner_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
42411,562,"NER","Niger","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2004/ner_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
42412,562,"NER","Niger","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2004/ner_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
42413,562,"NER","Niger","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2005/ner_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
42414,562,"NER","Niger","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2005/ner_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
42415,562,"NER","Niger","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2005/ner_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
42416,562,"NER","Niger","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2005/ner_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
42417,562,"NER","Niger","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2005/ner_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
42418,562,"NER","Niger","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2005/ner_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
42419,562,"NER","Niger","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2005/ner_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
42420,562,"NER","Niger","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2005/ner_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
42421,562,"NER","Niger","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2006/ner_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
42422,562,"NER","Niger","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2006/ner_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
42423,562,"NER","Niger","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2006/ner_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
42424,562,"NER","Niger","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2006/ner_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
42425,562,"NER","Niger","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2006/ner_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
42426,562,"NER","Niger","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2006/ner_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
42427,562,"NER","Niger","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2006/ner_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
42428,562,"NER","Niger","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2006/ner_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
42429,562,"NER","Niger","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2007/ner_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
42430,562,"NER","Niger","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2007/ner_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
42431,562,"NER","Niger","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2007/ner_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
42432,562,"NER","Niger","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2007/ner_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
42433,562,"NER","Niger","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2007/ner_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
42434,562,"NER","Niger","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2007/ner_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
42435,562,"NER","Niger","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2007/ner_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
42436,562,"NER","Niger","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2007/ner_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
42437,562,"NER","Niger","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2008/ner_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
42438,562,"NER","Niger","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2008/ner_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
42439,562,"NER","Niger","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2008/ner_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
42440,562,"NER","Niger","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2008/ner_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
42441,562,"NER","Niger","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2008/ner_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
42442,562,"NER","Niger","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2008/ner_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
42443,562,"NER","Niger","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2008/ner_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
42444,562,"NER","Niger","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2008/ner_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
42445,562,"NER","Niger","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2009/ner_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
42446,562,"NER","Niger","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2009/ner_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
42447,562,"NER","Niger","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2009/ner_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
42448,562,"NER","Niger","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2009/ner_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
42449,562,"NER","Niger","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2009/ner_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
42450,562,"NER","Niger","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2009/ner_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
42451,562,"NER","Niger","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2009/ner_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
42452,562,"NER","Niger","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2009/ner_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
42453,562,"NER","Niger","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2010/ner_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
42454,562,"NER","Niger","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2010/ner_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
42455,562,"NER","Niger","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2010/ner_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
42456,562,"NER","Niger","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2010/ner_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
42457,562,"NER","Niger","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2010/ner_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
42458,562,"NER","Niger","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2010/ner_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
42459,562,"NER","Niger","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2010/ner_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
42460,562,"NER","Niger","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2010/ner_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
42461,562,"NER","Niger","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2011/ner_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
42462,562,"NER","Niger","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2011/ner_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
42463,562,"NER","Niger","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2011/ner_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
42464,562,"NER","Niger","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2011/ner_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
42465,562,"NER","Niger","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2011/ner_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
42466,562,"NER","Niger","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2011/ner_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
42467,562,"NER","Niger","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2011/ner_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
42468,562,"NER","Niger","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2011/ner_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
42469,562,"NER","Niger","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2012/ner_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
42470,562,"NER","Niger","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2012/ner_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
42471,562,"NER","Niger","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2012/ner_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
42472,562,"NER","Niger","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2012/ner_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
42473,562,"NER","Niger","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2012/ner_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
42474,562,"NER","Niger","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2012/ner_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
42475,562,"NER","Niger","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2012/ner_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
42476,562,"NER","Niger","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2012/ner_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
42477,562,"NER","Niger","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2013/ner_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
42478,562,"NER","Niger","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2013/ner_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
42479,562,"NER","Niger","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2013/ner_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
42480,562,"NER","Niger","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2013/ner_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
42481,562,"NER","Niger","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2013/ner_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
42482,562,"NER","Niger","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2013/ner_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
42483,562,"NER","Niger","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2013/ner_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
42484,562,"NER","Niger","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2013/ner_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
42485,562,"NER","Niger","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2014/ner_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
42486,562,"NER","Niger","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2014/ner_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
42487,562,"NER","Niger","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2014/ner_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
42488,562,"NER","Niger","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2014/ner_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
42489,562,"NER","Niger","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2014/ner_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
42490,562,"NER","Niger","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2014/ner_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
42491,562,"NER","Niger","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2014/ner_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
42492,562,"NER","Niger","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2014/ner_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
42493,562,"NER","Niger","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2015/ner_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
42494,562,"NER","Niger","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2015/ner_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
42495,562,"NER","Niger","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2015/ner_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
42496,562,"NER","Niger","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2015/ner_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
42497,562,"NER","Niger","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2015/ner_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
42498,562,"NER","Niger","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2015/ner_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
42499,562,"NER","Niger","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2015/ner_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
42500,562,"NER","Niger","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Annual/2015/ner_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
42501,566,"NGA","Nigeria","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2000/nga_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
42502,566,"NGA","Nigeria","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2000/nga_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
42503,566,"NGA","Nigeria","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2000/nga_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
42504,566,"NGA","Nigeria","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2000/nga_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
42505,566,"NGA","Nigeria","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2000/nga_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
42506,566,"NGA","Nigeria","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2000/nga_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
42507,566,"NGA","Nigeria","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2000/nga_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
42508,566,"NGA","Nigeria","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2000/nga_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
42509,566,"NGA","Nigeria","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2001/nga_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
42510,566,"NGA","Nigeria","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2001/nga_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
42511,566,"NGA","Nigeria","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2001/nga_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
42512,566,"NGA","Nigeria","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2001/nga_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
42513,566,"NGA","Nigeria","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2001/nga_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
42514,566,"NGA","Nigeria","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2001/nga_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
42515,566,"NGA","Nigeria","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2001/nga_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
42516,566,"NGA","Nigeria","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2001/nga_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
42517,566,"NGA","Nigeria","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2002/nga_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
42518,566,"NGA","Nigeria","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2002/nga_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
42519,566,"NGA","Nigeria","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2002/nga_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
42520,566,"NGA","Nigeria","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2002/nga_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
42521,566,"NGA","Nigeria","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2002/nga_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
42522,566,"NGA","Nigeria","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2002/nga_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
42523,566,"NGA","Nigeria","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2002/nga_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
42524,566,"NGA","Nigeria","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2002/nga_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
42525,566,"NGA","Nigeria","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2003/nga_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
42526,566,"NGA","Nigeria","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2003/nga_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
42527,566,"NGA","Nigeria","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2003/nga_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
42528,566,"NGA","Nigeria","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2003/nga_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
42529,566,"NGA","Nigeria","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2003/nga_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
42530,566,"NGA","Nigeria","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2003/nga_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
42531,566,"NGA","Nigeria","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2003/nga_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
42532,566,"NGA","Nigeria","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2003/nga_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
42533,566,"NGA","Nigeria","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2004/nga_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
42534,566,"NGA","Nigeria","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2004/nga_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
42535,566,"NGA","Nigeria","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2004/nga_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
42536,566,"NGA","Nigeria","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2004/nga_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
42537,566,"NGA","Nigeria","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2004/nga_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
42538,566,"NGA","Nigeria","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2004/nga_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
42539,566,"NGA","Nigeria","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2004/nga_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
42540,566,"NGA","Nigeria","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2004/nga_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
42541,566,"NGA","Nigeria","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2005/nga_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
42542,566,"NGA","Nigeria","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2005/nga_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
42543,566,"NGA","Nigeria","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2005/nga_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
42544,566,"NGA","Nigeria","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2005/nga_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
42545,566,"NGA","Nigeria","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2005/nga_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
42546,566,"NGA","Nigeria","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2005/nga_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
42547,566,"NGA","Nigeria","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2005/nga_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
42548,566,"NGA","Nigeria","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2005/nga_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
42549,566,"NGA","Nigeria","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2006/nga_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
42550,566,"NGA","Nigeria","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2006/nga_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
42551,566,"NGA","Nigeria","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2006/nga_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
42552,566,"NGA","Nigeria","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2006/nga_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
42553,566,"NGA","Nigeria","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2006/nga_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
42554,566,"NGA","Nigeria","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2006/nga_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
42555,566,"NGA","Nigeria","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2006/nga_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
42556,566,"NGA","Nigeria","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2006/nga_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
42557,566,"NGA","Nigeria","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2007/nga_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
42558,566,"NGA","Nigeria","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2007/nga_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
42559,566,"NGA","Nigeria","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2007/nga_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
42560,566,"NGA","Nigeria","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2007/nga_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
42561,566,"NGA","Nigeria","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2007/nga_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
42562,566,"NGA","Nigeria","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2007/nga_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
42563,566,"NGA","Nigeria","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2007/nga_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
42564,566,"NGA","Nigeria","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2007/nga_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
42565,566,"NGA","Nigeria","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2008/nga_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
42566,566,"NGA","Nigeria","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2008/nga_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
42567,566,"NGA","Nigeria","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2008/nga_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
42568,566,"NGA","Nigeria","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2008/nga_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
42569,566,"NGA","Nigeria","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2008/nga_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
42570,566,"NGA","Nigeria","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2008/nga_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
42571,566,"NGA","Nigeria","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2008/nga_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
42572,566,"NGA","Nigeria","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2008/nga_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
42573,566,"NGA","Nigeria","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2009/nga_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
42574,566,"NGA","Nigeria","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2009/nga_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
42575,566,"NGA","Nigeria","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2009/nga_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
42576,566,"NGA","Nigeria","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2009/nga_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
42577,566,"NGA","Nigeria","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2009/nga_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
42578,566,"NGA","Nigeria","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2009/nga_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
42579,566,"NGA","Nigeria","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2009/nga_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
42580,566,"NGA","Nigeria","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2009/nga_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
42581,566,"NGA","Nigeria","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2010/nga_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
42582,566,"NGA","Nigeria","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2010/nga_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
42583,566,"NGA","Nigeria","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2010/nga_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
42584,566,"NGA","Nigeria","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2010/nga_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
42585,566,"NGA","Nigeria","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2010/nga_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
42586,566,"NGA","Nigeria","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2010/nga_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
42587,566,"NGA","Nigeria","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2010/nga_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
42588,566,"NGA","Nigeria","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2010/nga_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
42589,566,"NGA","Nigeria","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2011/nga_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
42590,566,"NGA","Nigeria","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2011/nga_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
42591,566,"NGA","Nigeria","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2011/nga_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
42592,566,"NGA","Nigeria","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2011/nga_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
42593,566,"NGA","Nigeria","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2011/nga_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
42594,566,"NGA","Nigeria","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2011/nga_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
42595,566,"NGA","Nigeria","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2011/nga_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
42596,566,"NGA","Nigeria","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2011/nga_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
42597,566,"NGA","Nigeria","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2012/nga_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
42598,566,"NGA","Nigeria","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2012/nga_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
42599,566,"NGA","Nigeria","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2012/nga_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
42600,566,"NGA","Nigeria","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2012/nga_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
42601,566,"NGA","Nigeria","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2012/nga_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
42602,566,"NGA","Nigeria","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2012/nga_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
42603,566,"NGA","Nigeria","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2012/nga_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
42604,566,"NGA","Nigeria","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2012/nga_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
42605,566,"NGA","Nigeria","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2013/nga_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
42606,566,"NGA","Nigeria","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2013/nga_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
42607,566,"NGA","Nigeria","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2013/nga_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
42608,566,"NGA","Nigeria","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2013/nga_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
42609,566,"NGA","Nigeria","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2013/nga_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
42610,566,"NGA","Nigeria","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2013/nga_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
42611,566,"NGA","Nigeria","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2013/nga_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
42612,566,"NGA","Nigeria","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2013/nga_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
42613,566,"NGA","Nigeria","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2014/nga_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
42614,566,"NGA","Nigeria","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2014/nga_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
42615,566,"NGA","Nigeria","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2014/nga_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
42616,566,"NGA","Nigeria","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2014/nga_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
42617,566,"NGA","Nigeria","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2014/nga_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
42618,566,"NGA","Nigeria","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2014/nga_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
42619,566,"NGA","Nigeria","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2014/nga_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
42620,566,"NGA","Nigeria","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2014/nga_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
42621,566,"NGA","Nigeria","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2015/nga_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
42622,566,"NGA","Nigeria","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2015/nga_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
42623,566,"NGA","Nigeria","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2015/nga_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
42624,566,"NGA","Nigeria","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2015/nga_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
42625,566,"NGA","Nigeria","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2015/nga_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
42626,566,"NGA","Nigeria","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2015/nga_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
42627,566,"NGA","Nigeria","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2015/nga_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
42628,566,"NGA","Nigeria","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Annual/2015/nga_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
42629,570,"NIU","Niue","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2000/niu_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
42630,570,"NIU","Niue","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2000/niu_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
42631,570,"NIU","Niue","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2000/niu_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
42632,570,"NIU","Niue","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2000/niu_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
42633,570,"NIU","Niue","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2000/niu_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
42634,570,"NIU","Niue","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2000/niu_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
42635,570,"NIU","Niue","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2000/niu_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
42636,570,"NIU","Niue","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2000/niu_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
42637,570,"NIU","Niue","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2001/niu_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
42638,570,"NIU","Niue","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2001/niu_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
42639,570,"NIU","Niue","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2001/niu_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
42640,570,"NIU","Niue","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2001/niu_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
42641,570,"NIU","Niue","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2001/niu_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
42642,570,"NIU","Niue","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2001/niu_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
42643,570,"NIU","Niue","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2001/niu_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
42644,570,"NIU","Niue","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2001/niu_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
42645,570,"NIU","Niue","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2002/niu_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
42646,570,"NIU","Niue","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2002/niu_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
42647,570,"NIU","Niue","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2002/niu_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
42648,570,"NIU","Niue","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2002/niu_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
42649,570,"NIU","Niue","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2002/niu_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
42650,570,"NIU","Niue","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2002/niu_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
42651,570,"NIU","Niue","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2002/niu_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
42652,570,"NIU","Niue","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2002/niu_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
42653,570,"NIU","Niue","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2003/niu_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
42654,570,"NIU","Niue","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2003/niu_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
42655,570,"NIU","Niue","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2003/niu_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
42656,570,"NIU","Niue","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2003/niu_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
42657,570,"NIU","Niue","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2003/niu_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
42658,570,"NIU","Niue","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2003/niu_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
42659,570,"NIU","Niue","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2003/niu_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
42660,570,"NIU","Niue","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2003/niu_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
42661,570,"NIU","Niue","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2004/niu_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
42662,570,"NIU","Niue","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2004/niu_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
42663,570,"NIU","Niue","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2004/niu_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
42664,570,"NIU","Niue","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2004/niu_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
42665,570,"NIU","Niue","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2004/niu_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
42666,570,"NIU","Niue","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2004/niu_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
42667,570,"NIU","Niue","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2004/niu_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
42668,570,"NIU","Niue","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2004/niu_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
42669,570,"NIU","Niue","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2005/niu_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
42670,570,"NIU","Niue","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2005/niu_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
42671,570,"NIU","Niue","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2005/niu_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
42672,570,"NIU","Niue","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2005/niu_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
42673,570,"NIU","Niue","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2005/niu_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
42674,570,"NIU","Niue","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2005/niu_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
42675,570,"NIU","Niue","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2005/niu_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
42676,570,"NIU","Niue","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2005/niu_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
42677,570,"NIU","Niue","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2006/niu_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
42678,570,"NIU","Niue","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2006/niu_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
42679,570,"NIU","Niue","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2006/niu_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
42680,570,"NIU","Niue","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2006/niu_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
42681,570,"NIU","Niue","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2006/niu_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
42682,570,"NIU","Niue","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2006/niu_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
42683,570,"NIU","Niue","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2006/niu_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
42684,570,"NIU","Niue","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2006/niu_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
42685,570,"NIU","Niue","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2007/niu_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
42686,570,"NIU","Niue","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2007/niu_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
42687,570,"NIU","Niue","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2007/niu_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
42688,570,"NIU","Niue","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2007/niu_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
42689,570,"NIU","Niue","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2007/niu_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
42690,570,"NIU","Niue","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2007/niu_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
42691,570,"NIU","Niue","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2007/niu_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
42692,570,"NIU","Niue","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2007/niu_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
42693,570,"NIU","Niue","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2008/niu_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
42694,570,"NIU","Niue","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2008/niu_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
42695,570,"NIU","Niue","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2008/niu_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
42696,570,"NIU","Niue","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2008/niu_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
42697,570,"NIU","Niue","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2008/niu_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
42698,570,"NIU","Niue","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2008/niu_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
42699,570,"NIU","Niue","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2008/niu_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
42700,570,"NIU","Niue","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2008/niu_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
42701,570,"NIU","Niue","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2009/niu_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
42702,570,"NIU","Niue","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2009/niu_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
42703,570,"NIU","Niue","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2009/niu_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
42704,570,"NIU","Niue","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2009/niu_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
42705,570,"NIU","Niue","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2009/niu_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
42706,570,"NIU","Niue","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2009/niu_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
42707,570,"NIU","Niue","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2009/niu_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
42708,570,"NIU","Niue","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2009/niu_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
42709,570,"NIU","Niue","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2010/niu_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
42710,570,"NIU","Niue","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2010/niu_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
42711,570,"NIU","Niue","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2010/niu_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
42712,570,"NIU","Niue","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2010/niu_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
42713,570,"NIU","Niue","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2010/niu_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
42714,570,"NIU","Niue","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2010/niu_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
42715,570,"NIU","Niue","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2010/niu_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
42716,570,"NIU","Niue","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2010/niu_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
42717,570,"NIU","Niue","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2011/niu_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
42718,570,"NIU","Niue","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2011/niu_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
42719,570,"NIU","Niue","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2011/niu_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
42720,570,"NIU","Niue","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2011/niu_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
42721,570,"NIU","Niue","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2011/niu_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
42722,570,"NIU","Niue","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2011/niu_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
42723,570,"NIU","Niue","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2011/niu_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
42724,570,"NIU","Niue","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2011/niu_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
42725,570,"NIU","Niue","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2012/niu_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
42726,570,"NIU","Niue","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2012/niu_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
42727,570,"NIU","Niue","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2012/niu_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
42728,570,"NIU","Niue","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2012/niu_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
42729,570,"NIU","Niue","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2012/niu_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
42730,570,"NIU","Niue","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2012/niu_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
42731,570,"NIU","Niue","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2012/niu_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
42732,570,"NIU","Niue","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2012/niu_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
42733,570,"NIU","Niue","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2013/niu_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
42734,570,"NIU","Niue","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2013/niu_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
42735,570,"NIU","Niue","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2013/niu_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
42736,570,"NIU","Niue","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2013/niu_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
42737,570,"NIU","Niue","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2013/niu_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
42738,570,"NIU","Niue","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2013/niu_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
42739,570,"NIU","Niue","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2013/niu_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
42740,570,"NIU","Niue","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2013/niu_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
42741,570,"NIU","Niue","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2014/niu_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
42742,570,"NIU","Niue","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2014/niu_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
42743,570,"NIU","Niue","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2014/niu_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
42744,570,"NIU","Niue","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2014/niu_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
42745,570,"NIU","Niue","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2014/niu_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
42746,570,"NIU","Niue","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2014/niu_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
42747,570,"NIU","Niue","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2014/niu_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
42748,570,"NIU","Niue","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2014/niu_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
42749,570,"NIU","Niue","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2015/niu_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
42750,570,"NIU","Niue","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2015/niu_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
42751,570,"NIU","Niue","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2015/niu_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
42752,570,"NIU","Niue","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2015/niu_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
42753,570,"NIU","Niue","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2015/niu_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
42754,570,"NIU","Niue","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2015/niu_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
42755,570,"NIU","Niue","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2015/niu_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
42756,570,"NIU","Niue","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Annual/2015/niu_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
42757,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2000/nfk_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
42758,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2000/nfk_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
42759,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2000/nfk_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
42760,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2000/nfk_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
42761,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2000/nfk_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
42762,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2000/nfk_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
42763,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2000/nfk_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
42764,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2000/nfk_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
42765,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2001/nfk_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
42766,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2001/nfk_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
42767,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2001/nfk_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
42768,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2001/nfk_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
42769,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2001/nfk_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
42770,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2001/nfk_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
42771,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2001/nfk_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
42772,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2001/nfk_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
42773,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2002/nfk_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
42774,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2002/nfk_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
42775,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2002/nfk_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
42776,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2002/nfk_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
42777,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2002/nfk_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
42778,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2002/nfk_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
42779,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2002/nfk_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
42780,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2002/nfk_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
42781,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2003/nfk_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
42782,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2003/nfk_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
42783,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2003/nfk_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
42784,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2003/nfk_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
42785,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2003/nfk_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
42786,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2003/nfk_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
42787,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2003/nfk_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
42788,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2003/nfk_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
42789,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2004/nfk_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
42790,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2004/nfk_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
42791,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2004/nfk_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
42792,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2004/nfk_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
42793,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2004/nfk_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
42794,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2004/nfk_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
42795,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2004/nfk_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
42796,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2004/nfk_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
42797,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2005/nfk_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
42798,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2005/nfk_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
42799,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2005/nfk_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
42800,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2005/nfk_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
42801,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2005/nfk_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
42802,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2005/nfk_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
42803,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2005/nfk_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
42804,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2005/nfk_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
42805,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2006/nfk_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
42806,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2006/nfk_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
42807,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2006/nfk_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
42808,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2006/nfk_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
42809,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2006/nfk_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
42810,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2006/nfk_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
42811,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2006/nfk_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
42812,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2006/nfk_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
42813,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2007/nfk_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
42814,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2007/nfk_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
42815,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2007/nfk_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
42816,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2007/nfk_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
42817,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2007/nfk_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
42818,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2007/nfk_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
42819,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2007/nfk_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
42820,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2007/nfk_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
42821,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2008/nfk_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
42822,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2008/nfk_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
42823,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2008/nfk_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
42824,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2008/nfk_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
42825,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2008/nfk_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
42826,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2008/nfk_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
42827,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2008/nfk_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
42828,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2008/nfk_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
42829,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2009/nfk_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
42830,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2009/nfk_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
42831,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2009/nfk_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
42832,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2009/nfk_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
42833,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2009/nfk_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
42834,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2009/nfk_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
42835,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2009/nfk_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
42836,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2009/nfk_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
42837,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2010/nfk_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
42838,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2010/nfk_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
42839,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2010/nfk_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
42840,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2010/nfk_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
42841,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2010/nfk_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
42842,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2010/nfk_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
42843,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2010/nfk_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
42844,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2010/nfk_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
42845,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2011/nfk_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
42846,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2011/nfk_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
42847,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2011/nfk_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
42848,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2011/nfk_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
42849,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2011/nfk_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
42850,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2011/nfk_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
42851,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2011/nfk_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
42852,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2011/nfk_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
42853,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2012/nfk_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
42854,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2012/nfk_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
42855,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2012/nfk_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
42856,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2012/nfk_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
42857,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2012/nfk_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
42858,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2012/nfk_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
42859,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2012/nfk_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
42860,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2012/nfk_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
42861,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2013/nfk_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
42862,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2013/nfk_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
42863,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2013/nfk_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
42864,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2013/nfk_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
42865,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2013/nfk_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
42866,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2013/nfk_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
42867,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2013/nfk_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
42868,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2013/nfk_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
42869,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2014/nfk_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
42870,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2014/nfk_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
42871,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2014/nfk_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
42872,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2014/nfk_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
42873,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2014/nfk_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
42874,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2014/nfk_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
42875,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2014/nfk_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
42876,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2014/nfk_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
42877,574,"NFK","Norfolk Island","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2015/nfk_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
42878,574,"NFK","Norfolk Island","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2015/nfk_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
42879,574,"NFK","Norfolk Island","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2015/nfk_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
42880,574,"NFK","Norfolk Island","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2015/nfk_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
42881,574,"NFK","Norfolk Island","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2015/nfk_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
42882,574,"NFK","Norfolk Island","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2015/nfk_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
42883,574,"NFK","Norfolk Island","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2015/nfk_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
42884,574,"NFK","Norfolk Island","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Annual/2015/nfk_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
42885,578,"NOR","Norway","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2000/nor_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
42886,578,"NOR","Norway","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2000/nor_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
42887,578,"NOR","Norway","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2000/nor_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
42888,578,"NOR","Norway","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2000/nor_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
42889,578,"NOR","Norway","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2000/nor_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
42890,578,"NOR","Norway","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2000/nor_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
42891,578,"NOR","Norway","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2000/nor_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
42892,578,"NOR","Norway","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2000/nor_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
42893,578,"NOR","Norway","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2001/nor_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
42894,578,"NOR","Norway","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2001/nor_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
42895,578,"NOR","Norway","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2001/nor_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
42896,578,"NOR","Norway","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2001/nor_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
42897,578,"NOR","Norway","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2001/nor_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
42898,578,"NOR","Norway","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2001/nor_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
42899,578,"NOR","Norway","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2001/nor_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
42900,578,"NOR","Norway","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2001/nor_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
42901,578,"NOR","Norway","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2002/nor_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
42902,578,"NOR","Norway","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2002/nor_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
42903,578,"NOR","Norway","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2002/nor_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
42904,578,"NOR","Norway","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2002/nor_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
42905,578,"NOR","Norway","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2002/nor_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
42906,578,"NOR","Norway","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2002/nor_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
42907,578,"NOR","Norway","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2002/nor_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
42908,578,"NOR","Norway","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2002/nor_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
42909,578,"NOR","Norway","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2003/nor_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
42910,578,"NOR","Norway","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2003/nor_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
42911,578,"NOR","Norway","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2003/nor_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
42912,578,"NOR","Norway","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2003/nor_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
42913,578,"NOR","Norway","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2003/nor_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
42914,578,"NOR","Norway","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2003/nor_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
42915,578,"NOR","Norway","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2003/nor_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
42916,578,"NOR","Norway","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2003/nor_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
42917,578,"NOR","Norway","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2004/nor_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
42918,578,"NOR","Norway","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2004/nor_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
42919,578,"NOR","Norway","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2004/nor_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
42920,578,"NOR","Norway","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2004/nor_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
42921,578,"NOR","Norway","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2004/nor_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
42922,578,"NOR","Norway","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2004/nor_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
42923,578,"NOR","Norway","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2004/nor_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
42924,578,"NOR","Norway","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2004/nor_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
42925,578,"NOR","Norway","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2005/nor_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
42926,578,"NOR","Norway","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2005/nor_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
42927,578,"NOR","Norway","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2005/nor_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
42928,578,"NOR","Norway","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2005/nor_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
42929,578,"NOR","Norway","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2005/nor_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
42930,578,"NOR","Norway","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2005/nor_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
42931,578,"NOR","Norway","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2005/nor_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
42932,578,"NOR","Norway","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2005/nor_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
42933,578,"NOR","Norway","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2006/nor_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
42934,578,"NOR","Norway","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2006/nor_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
42935,578,"NOR","Norway","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2006/nor_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
42936,578,"NOR","Norway","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2006/nor_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
42937,578,"NOR","Norway","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2006/nor_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
42938,578,"NOR","Norway","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2006/nor_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
42939,578,"NOR","Norway","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2006/nor_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
42940,578,"NOR","Norway","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2006/nor_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
42941,578,"NOR","Norway","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2007/nor_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
42942,578,"NOR","Norway","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2007/nor_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
42943,578,"NOR","Norway","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2007/nor_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
42944,578,"NOR","Norway","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2007/nor_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
42945,578,"NOR","Norway","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2007/nor_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
42946,578,"NOR","Norway","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2007/nor_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
42947,578,"NOR","Norway","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2007/nor_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
42948,578,"NOR","Norway","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2007/nor_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
42949,578,"NOR","Norway","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2008/nor_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
42950,578,"NOR","Norway","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2008/nor_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
42951,578,"NOR","Norway","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2008/nor_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
42952,578,"NOR","Norway","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2008/nor_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
42953,578,"NOR","Norway","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2008/nor_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
42954,578,"NOR","Norway","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2008/nor_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
42955,578,"NOR","Norway","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2008/nor_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
42956,578,"NOR","Norway","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2008/nor_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
42957,578,"NOR","Norway","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2009/nor_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
42958,578,"NOR","Norway","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2009/nor_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
42959,578,"NOR","Norway","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2009/nor_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
42960,578,"NOR","Norway","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2009/nor_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
42961,578,"NOR","Norway","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2009/nor_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
42962,578,"NOR","Norway","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2009/nor_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
42963,578,"NOR","Norway","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2009/nor_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
42964,578,"NOR","Norway","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2009/nor_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
42965,578,"NOR","Norway","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2010/nor_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
42966,578,"NOR","Norway","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2010/nor_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
42967,578,"NOR","Norway","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2010/nor_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
42968,578,"NOR","Norway","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2010/nor_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
42969,578,"NOR","Norway","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2010/nor_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
42970,578,"NOR","Norway","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2010/nor_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
42971,578,"NOR","Norway","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2010/nor_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
42972,578,"NOR","Norway","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2010/nor_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
42973,578,"NOR","Norway","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2011/nor_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
42974,578,"NOR","Norway","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2011/nor_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
42975,578,"NOR","Norway","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2011/nor_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
42976,578,"NOR","Norway","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2011/nor_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
42977,578,"NOR","Norway","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2011/nor_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
42978,578,"NOR","Norway","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2011/nor_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
42979,578,"NOR","Norway","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2011/nor_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
42980,578,"NOR","Norway","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2011/nor_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
42981,578,"NOR","Norway","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2012/nor_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
42982,578,"NOR","Norway","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2012/nor_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
42983,578,"NOR","Norway","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2012/nor_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
42984,578,"NOR","Norway","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2012/nor_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
42985,578,"NOR","Norway","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2012/nor_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
42986,578,"NOR","Norway","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2012/nor_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
42987,578,"NOR","Norway","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2012/nor_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
42988,578,"NOR","Norway","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2012/nor_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
42989,578,"NOR","Norway","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2013/nor_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
42990,578,"NOR","Norway","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2013/nor_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
42991,578,"NOR","Norway","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2013/nor_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
42992,578,"NOR","Norway","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2013/nor_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
42993,578,"NOR","Norway","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2013/nor_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
42994,578,"NOR","Norway","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2013/nor_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
42995,578,"NOR","Norway","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2013/nor_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
42996,578,"NOR","Norway","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2013/nor_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
42997,578,"NOR","Norway","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2014/nor_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
42998,578,"NOR","Norway","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2014/nor_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
42999,578,"NOR","Norway","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2014/nor_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
43000,578,"NOR","Norway","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2014/nor_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
43001,578,"NOR","Norway","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2014/nor_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
43002,578,"NOR","Norway","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2014/nor_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
43003,578,"NOR","Norway","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2014/nor_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
43004,578,"NOR","Norway","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2014/nor_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
43005,578,"NOR","Norway","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2015/nor_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
43006,578,"NOR","Norway","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2015/nor_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
43007,578,"NOR","Norway","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2015/nor_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
43008,578,"NOR","Norway","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2015/nor_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
43009,578,"NOR","Norway","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2015/nor_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
43010,578,"NOR","Norway","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2015/nor_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
43011,578,"NOR","Norway","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2015/nor_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
43012,578,"NOR","Norway","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Annual/2015/nor_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
43013,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2000/mnp_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
43014,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2000/mnp_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
43015,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2000/mnp_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
43016,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2000/mnp_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
43017,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2000/mnp_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
43018,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2000/mnp_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
43019,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2000/mnp_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
43020,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2000/mnp_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
43021,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2001/mnp_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
43022,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2001/mnp_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
43023,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2001/mnp_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
43024,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2001/mnp_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
43025,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2001/mnp_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
43026,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2001/mnp_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
43027,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2001/mnp_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
43028,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2001/mnp_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
43029,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2002/mnp_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
43030,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2002/mnp_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
43031,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2002/mnp_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
43032,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2002/mnp_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
43033,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2002/mnp_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
43034,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2002/mnp_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
43035,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2002/mnp_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
43036,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2002/mnp_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
43037,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2003/mnp_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
43038,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2003/mnp_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
43039,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2003/mnp_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
43040,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2003/mnp_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
43041,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2003/mnp_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
43042,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2003/mnp_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
43043,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2003/mnp_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
43044,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2003/mnp_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
43045,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2004/mnp_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
43046,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2004/mnp_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
43047,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2004/mnp_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
43048,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2004/mnp_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
43049,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2004/mnp_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
43050,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2004/mnp_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
43051,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2004/mnp_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
43052,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2004/mnp_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
43053,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2005/mnp_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
43054,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2005/mnp_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
43055,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2005/mnp_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
43056,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2005/mnp_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
43057,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2005/mnp_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
43058,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2005/mnp_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
43059,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2005/mnp_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
43060,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2005/mnp_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
43061,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2006/mnp_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
43062,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2006/mnp_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
43063,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2006/mnp_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
43064,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2006/mnp_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
43065,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2006/mnp_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
43066,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2006/mnp_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
43067,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2006/mnp_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
43068,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2006/mnp_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
43069,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2007/mnp_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
43070,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2007/mnp_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
43071,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2007/mnp_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
43072,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2007/mnp_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
43073,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2007/mnp_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
43074,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2007/mnp_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
43075,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2007/mnp_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
43076,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2007/mnp_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
43077,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2008/mnp_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
43078,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2008/mnp_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
43079,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2008/mnp_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
43080,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2008/mnp_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
43081,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2008/mnp_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
43082,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2008/mnp_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
43083,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2008/mnp_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
43084,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2008/mnp_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
43085,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2009/mnp_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
43086,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2009/mnp_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
43087,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2009/mnp_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
43088,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2009/mnp_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
43089,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2009/mnp_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
43090,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2009/mnp_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
43091,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2009/mnp_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
43092,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2009/mnp_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
43093,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2010/mnp_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
43094,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2010/mnp_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
43095,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2010/mnp_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
43096,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2010/mnp_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
43097,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2010/mnp_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
43098,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2010/mnp_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
43099,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2010/mnp_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
43100,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2010/mnp_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
43101,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2011/mnp_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
43102,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2011/mnp_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
43103,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2011/mnp_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
43104,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2011/mnp_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
43105,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2011/mnp_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
43106,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2011/mnp_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
43107,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2011/mnp_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
43108,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2011/mnp_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
43109,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2012/mnp_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
43110,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2012/mnp_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
43111,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2012/mnp_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
43112,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2012/mnp_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
43113,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2012/mnp_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
43114,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2012/mnp_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
43115,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2012/mnp_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
43116,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2012/mnp_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
43117,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2013/mnp_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
43118,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2013/mnp_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
43119,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2013/mnp_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
43120,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2013/mnp_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
43121,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2013/mnp_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
43122,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2013/mnp_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
43123,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2013/mnp_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
43124,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2013/mnp_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
43125,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2014/mnp_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
43126,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2014/mnp_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
43127,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2014/mnp_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
43128,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2014/mnp_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
43129,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2014/mnp_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
43130,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2014/mnp_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
43131,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2014/mnp_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
43132,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2014/mnp_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
43133,580,"MNP","Northern Mariana Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2015/mnp_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
43134,580,"MNP","Northern Mariana Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2015/mnp_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
43135,580,"MNP","Northern Mariana Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2015/mnp_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
43136,580,"MNP","Northern Mariana Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2015/mnp_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
43137,580,"MNP","Northern Mariana Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2015/mnp_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
43138,580,"MNP","Northern Mariana Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2015/mnp_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
43139,580,"MNP","Northern Mariana Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2015/mnp_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
43140,580,"MNP","Northern Mariana Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Annual/2015/mnp_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
43141,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2000/umi_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
43142,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2000/umi_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
43143,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2000/umi_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
43144,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2000/umi_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
43145,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2000/umi_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
43146,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2000/umi_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
43147,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2000/umi_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
43148,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2000/umi_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
43149,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2001/umi_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
43150,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2001/umi_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
43151,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2001/umi_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
43152,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2001/umi_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
43153,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2001/umi_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
43154,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2001/umi_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
43155,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2001/umi_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
43156,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2001/umi_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
43157,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2002/umi_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
43158,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2002/umi_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
43159,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2002/umi_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
43160,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2002/umi_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
43161,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2002/umi_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
43162,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2002/umi_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
43163,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2002/umi_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
43164,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2002/umi_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
43165,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2003/umi_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
43166,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2003/umi_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
43167,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2003/umi_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
43168,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2003/umi_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
43169,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2003/umi_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
43170,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2003/umi_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
43171,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2003/umi_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
43172,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2003/umi_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
43173,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2004/umi_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
43174,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2004/umi_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
43175,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2004/umi_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
43176,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2004/umi_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
43177,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2004/umi_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
43178,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2004/umi_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
43179,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2004/umi_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
43180,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2004/umi_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
43181,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2005/umi_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
43182,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2005/umi_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
43183,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2005/umi_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
43184,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2005/umi_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
43185,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2005/umi_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
43186,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2005/umi_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
43187,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2005/umi_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
43188,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2005/umi_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
43189,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2006/umi_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
43190,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2006/umi_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
43191,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2006/umi_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
43192,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2006/umi_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
43193,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2006/umi_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
43194,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2006/umi_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
43195,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2006/umi_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
43196,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2006/umi_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
43197,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2007/umi_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
43198,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2007/umi_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
43199,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2007/umi_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
43200,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2007/umi_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
43201,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2007/umi_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
43202,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2007/umi_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
43203,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2007/umi_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
43204,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2007/umi_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
43205,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2008/umi_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
43206,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2008/umi_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
43207,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2008/umi_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
43208,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2008/umi_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
43209,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2008/umi_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
43210,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2008/umi_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
43211,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2008/umi_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
43212,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2008/umi_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
43213,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2009/umi_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
43214,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2009/umi_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
43215,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2009/umi_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
43216,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2009/umi_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
43217,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2009/umi_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
43218,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2009/umi_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
43219,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2009/umi_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
43220,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2009/umi_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
43221,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2010/umi_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
43222,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2010/umi_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
43223,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2010/umi_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
43224,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2010/umi_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
43225,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2010/umi_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
43226,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2010/umi_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
43227,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2010/umi_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
43228,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2010/umi_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
43229,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2011/umi_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
43230,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2011/umi_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
43231,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2011/umi_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
43232,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2011/umi_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
43233,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2011/umi_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
43234,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2011/umi_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
43235,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2011/umi_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
43236,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2011/umi_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
43237,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2012/umi_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
43238,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2012/umi_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
43239,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2012/umi_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
43240,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2012/umi_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
43241,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2012/umi_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
43242,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2012/umi_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
43243,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2012/umi_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
43244,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2012/umi_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
43245,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2013/umi_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
43246,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2013/umi_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
43247,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2013/umi_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
43248,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2013/umi_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
43249,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2013/umi_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
43250,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2013/umi_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
43251,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2013/umi_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
43252,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2013/umi_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
43253,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2014/umi_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
43254,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2014/umi_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
43255,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2014/umi_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
43256,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2014/umi_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
43257,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2014/umi_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
43258,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2014/umi_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
43259,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2014/umi_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
43260,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2014/umi_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
43261,581,"UMI","United States Minor Outlying Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2015/umi_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
43262,581,"UMI","United States Minor Outlying Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2015/umi_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
43263,581,"UMI","United States Minor Outlying Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2015/umi_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
43264,581,"UMI","United States Minor Outlying Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2015/umi_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
43265,581,"UMI","United States Minor Outlying Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2015/umi_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
43266,581,"UMI","United States Minor Outlying Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2015/umi_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
43267,581,"UMI","United States Minor Outlying Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2015/umi_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
43268,581,"UMI","United States Minor Outlying Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Annual/2015/umi_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
43269,583,"FSM","Micronesia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2000/fsm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
43270,583,"FSM","Micronesia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2000/fsm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
43271,583,"FSM","Micronesia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2000/fsm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
43272,583,"FSM","Micronesia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2000/fsm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
43273,583,"FSM","Micronesia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2000/fsm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
43274,583,"FSM","Micronesia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2000/fsm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
43275,583,"FSM","Micronesia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2000/fsm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
43276,583,"FSM","Micronesia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2000/fsm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
43277,583,"FSM","Micronesia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2001/fsm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
43278,583,"FSM","Micronesia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2001/fsm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
43279,583,"FSM","Micronesia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2001/fsm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
43280,583,"FSM","Micronesia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2001/fsm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
43281,583,"FSM","Micronesia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2001/fsm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
43282,583,"FSM","Micronesia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2001/fsm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
43283,583,"FSM","Micronesia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2001/fsm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
43284,583,"FSM","Micronesia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2001/fsm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
43285,583,"FSM","Micronesia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2002/fsm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
43286,583,"FSM","Micronesia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2002/fsm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
43287,583,"FSM","Micronesia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2002/fsm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
43288,583,"FSM","Micronesia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2002/fsm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
43289,583,"FSM","Micronesia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2002/fsm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
43290,583,"FSM","Micronesia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2002/fsm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
43291,583,"FSM","Micronesia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2002/fsm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
43292,583,"FSM","Micronesia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2002/fsm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
43293,583,"FSM","Micronesia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2003/fsm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
43294,583,"FSM","Micronesia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2003/fsm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
43295,583,"FSM","Micronesia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2003/fsm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
43296,583,"FSM","Micronesia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2003/fsm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
43297,583,"FSM","Micronesia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2003/fsm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
43298,583,"FSM","Micronesia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2003/fsm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
43299,583,"FSM","Micronesia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2003/fsm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
43300,583,"FSM","Micronesia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2003/fsm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
43301,583,"FSM","Micronesia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2004/fsm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
43302,583,"FSM","Micronesia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2004/fsm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
43303,583,"FSM","Micronesia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2004/fsm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
43304,583,"FSM","Micronesia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2004/fsm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
43305,583,"FSM","Micronesia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2004/fsm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
43306,583,"FSM","Micronesia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2004/fsm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
43307,583,"FSM","Micronesia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2004/fsm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
43308,583,"FSM","Micronesia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2004/fsm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
43309,583,"FSM","Micronesia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2005/fsm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
43310,583,"FSM","Micronesia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2005/fsm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
43311,583,"FSM","Micronesia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2005/fsm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
43312,583,"FSM","Micronesia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2005/fsm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
43313,583,"FSM","Micronesia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2005/fsm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
43314,583,"FSM","Micronesia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2005/fsm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
43315,583,"FSM","Micronesia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2005/fsm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
43316,583,"FSM","Micronesia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2005/fsm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
43317,583,"FSM","Micronesia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2006/fsm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
43318,583,"FSM","Micronesia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2006/fsm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
43319,583,"FSM","Micronesia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2006/fsm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
43320,583,"FSM","Micronesia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2006/fsm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
43321,583,"FSM","Micronesia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2006/fsm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
43322,583,"FSM","Micronesia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2006/fsm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
43323,583,"FSM","Micronesia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2006/fsm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
43324,583,"FSM","Micronesia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2006/fsm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
43325,583,"FSM","Micronesia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2007/fsm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
43326,583,"FSM","Micronesia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2007/fsm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
43327,583,"FSM","Micronesia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2007/fsm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
43328,583,"FSM","Micronesia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2007/fsm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
43329,583,"FSM","Micronesia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2007/fsm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
43330,583,"FSM","Micronesia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2007/fsm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
43331,583,"FSM","Micronesia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2007/fsm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
43332,583,"FSM","Micronesia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2007/fsm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
43333,583,"FSM","Micronesia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2008/fsm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
43334,583,"FSM","Micronesia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2008/fsm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
43335,583,"FSM","Micronesia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2008/fsm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
43336,583,"FSM","Micronesia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2008/fsm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
43337,583,"FSM","Micronesia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2008/fsm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
43338,583,"FSM","Micronesia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2008/fsm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
43339,583,"FSM","Micronesia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2008/fsm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
43340,583,"FSM","Micronesia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2008/fsm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
43341,583,"FSM","Micronesia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2009/fsm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
43342,583,"FSM","Micronesia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2009/fsm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
43343,583,"FSM","Micronesia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2009/fsm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
43344,583,"FSM","Micronesia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2009/fsm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
43345,583,"FSM","Micronesia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2009/fsm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
43346,583,"FSM","Micronesia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2009/fsm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
43347,583,"FSM","Micronesia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2009/fsm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
43348,583,"FSM","Micronesia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2009/fsm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
43349,583,"FSM","Micronesia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2010/fsm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
43350,583,"FSM","Micronesia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2010/fsm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
43351,583,"FSM","Micronesia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2010/fsm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
43352,583,"FSM","Micronesia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2010/fsm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
43353,583,"FSM","Micronesia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2010/fsm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
43354,583,"FSM","Micronesia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2010/fsm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
43355,583,"FSM","Micronesia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2010/fsm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
43356,583,"FSM","Micronesia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2010/fsm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
43357,583,"FSM","Micronesia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2011/fsm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
43358,583,"FSM","Micronesia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2011/fsm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
43359,583,"FSM","Micronesia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2011/fsm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
43360,583,"FSM","Micronesia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2011/fsm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
43361,583,"FSM","Micronesia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2011/fsm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
43362,583,"FSM","Micronesia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2011/fsm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
43363,583,"FSM","Micronesia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2011/fsm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
43364,583,"FSM","Micronesia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2011/fsm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
43365,583,"FSM","Micronesia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2012/fsm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
43366,583,"FSM","Micronesia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2012/fsm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
43367,583,"FSM","Micronesia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2012/fsm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
43368,583,"FSM","Micronesia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2012/fsm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
43369,583,"FSM","Micronesia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2012/fsm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
43370,583,"FSM","Micronesia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2012/fsm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
43371,583,"FSM","Micronesia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2012/fsm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
43372,583,"FSM","Micronesia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2012/fsm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
43373,583,"FSM","Micronesia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2013/fsm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
43374,583,"FSM","Micronesia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2013/fsm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
43375,583,"FSM","Micronesia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2013/fsm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
43376,583,"FSM","Micronesia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2013/fsm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
43377,583,"FSM","Micronesia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2013/fsm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
43378,583,"FSM","Micronesia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2013/fsm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
43379,583,"FSM","Micronesia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2013/fsm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
43380,583,"FSM","Micronesia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2013/fsm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
43381,583,"FSM","Micronesia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2014/fsm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
43382,583,"FSM","Micronesia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2014/fsm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
43383,583,"FSM","Micronesia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2014/fsm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
43384,583,"FSM","Micronesia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2014/fsm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
43385,583,"FSM","Micronesia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2014/fsm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
43386,583,"FSM","Micronesia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2014/fsm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
43387,583,"FSM","Micronesia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2014/fsm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
43388,583,"FSM","Micronesia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2014/fsm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
43389,583,"FSM","Micronesia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2015/fsm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
43390,583,"FSM","Micronesia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2015/fsm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
43391,583,"FSM","Micronesia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2015/fsm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
43392,583,"FSM","Micronesia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2015/fsm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
43393,583,"FSM","Micronesia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2015/fsm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
43394,583,"FSM","Micronesia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2015/fsm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
43395,583,"FSM","Micronesia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2015/fsm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
43396,583,"FSM","Micronesia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Annual/2015/fsm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
43397,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2000/mhl_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
43398,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2000/mhl_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
43399,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2000/mhl_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
43400,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2000/mhl_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
43401,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2000/mhl_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
43402,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2000/mhl_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
43403,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2000/mhl_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
43404,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2000/mhl_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
43405,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2001/mhl_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
43406,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2001/mhl_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
43407,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2001/mhl_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
43408,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2001/mhl_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
43409,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2001/mhl_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
43410,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2001/mhl_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
43411,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2001/mhl_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
43412,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2001/mhl_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
43413,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2002/mhl_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
43414,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2002/mhl_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
43415,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2002/mhl_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
43416,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2002/mhl_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
43417,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2002/mhl_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
43418,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2002/mhl_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
43419,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2002/mhl_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
43420,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2002/mhl_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
43421,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2003/mhl_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
43422,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2003/mhl_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
43423,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2003/mhl_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
43424,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2003/mhl_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
43425,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2003/mhl_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
43426,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2003/mhl_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
43427,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2003/mhl_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
43428,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2003/mhl_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
43429,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2004/mhl_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
43430,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2004/mhl_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
43431,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2004/mhl_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
43432,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2004/mhl_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
43433,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2004/mhl_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
43434,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2004/mhl_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
43435,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2004/mhl_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
43436,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2004/mhl_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
43437,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2005/mhl_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
43438,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2005/mhl_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
43439,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2005/mhl_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
43440,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2005/mhl_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
43441,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2005/mhl_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
43442,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2005/mhl_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
43443,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2005/mhl_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
43444,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2005/mhl_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
43445,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2006/mhl_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
43446,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2006/mhl_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
43447,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2006/mhl_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
43448,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2006/mhl_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
43449,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2006/mhl_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
43450,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2006/mhl_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
43451,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2006/mhl_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
43452,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2006/mhl_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
43453,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2007/mhl_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
43454,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2007/mhl_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
43455,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2007/mhl_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
43456,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2007/mhl_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
43457,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2007/mhl_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
43458,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2007/mhl_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
43459,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2007/mhl_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
43460,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2007/mhl_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
43461,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2008/mhl_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
43462,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2008/mhl_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
43463,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2008/mhl_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
43464,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2008/mhl_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
43465,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2008/mhl_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
43466,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2008/mhl_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
43467,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2008/mhl_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
43468,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2008/mhl_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
43469,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2009/mhl_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
43470,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2009/mhl_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
43471,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2009/mhl_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
43472,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2009/mhl_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
43473,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2009/mhl_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
43474,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2009/mhl_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
43475,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2009/mhl_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
43476,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2009/mhl_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
43477,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2010/mhl_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
43478,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2010/mhl_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
43479,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2010/mhl_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
43480,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2010/mhl_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
43481,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2010/mhl_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
43482,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2010/mhl_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
43483,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2010/mhl_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
43484,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2010/mhl_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
43485,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2011/mhl_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
43486,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2011/mhl_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
43487,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2011/mhl_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
43488,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2011/mhl_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
43489,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2011/mhl_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
43490,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2011/mhl_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
43491,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2011/mhl_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
43492,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2011/mhl_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
43493,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2012/mhl_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
43494,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2012/mhl_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
43495,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2012/mhl_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
43496,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2012/mhl_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
43497,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2012/mhl_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
43498,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2012/mhl_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
43499,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2012/mhl_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
43500,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2012/mhl_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
43501,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2013/mhl_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
43502,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2013/mhl_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
43503,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2013/mhl_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
43504,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2013/mhl_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
43505,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2013/mhl_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
43506,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2013/mhl_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
43507,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2013/mhl_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
43508,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2013/mhl_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
43509,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2014/mhl_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
43510,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2014/mhl_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
43511,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2014/mhl_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
43512,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2014/mhl_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
43513,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2014/mhl_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
43514,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2014/mhl_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
43515,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2014/mhl_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
43516,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2014/mhl_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
43517,584,"MHL","Marshall Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2015/mhl_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
43518,584,"MHL","Marshall Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2015/mhl_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
43519,584,"MHL","Marshall Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2015/mhl_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
43520,584,"MHL","Marshall Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2015/mhl_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
43521,584,"MHL","Marshall Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2015/mhl_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
43522,584,"MHL","Marshall Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2015/mhl_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
43523,584,"MHL","Marshall Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2015/mhl_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
43524,584,"MHL","Marshall Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Annual/2015/mhl_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
43525,585,"PLW","Palau","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2000/plw_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
43526,585,"PLW","Palau","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2000/plw_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
43527,585,"PLW","Palau","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2000/plw_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
43528,585,"PLW","Palau","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2000/plw_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
43529,585,"PLW","Palau","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2000/plw_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
43530,585,"PLW","Palau","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2000/plw_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
43531,585,"PLW","Palau","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2000/plw_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
43532,585,"PLW","Palau","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2000/plw_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
43533,585,"PLW","Palau","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2001/plw_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
43534,585,"PLW","Palau","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2001/plw_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
43535,585,"PLW","Palau","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2001/plw_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
43536,585,"PLW","Palau","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2001/plw_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
43537,585,"PLW","Palau","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2001/plw_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
43538,585,"PLW","Palau","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2001/plw_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
43539,585,"PLW","Palau","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2001/plw_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
43540,585,"PLW","Palau","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2001/plw_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
43541,585,"PLW","Palau","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2002/plw_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
43542,585,"PLW","Palau","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2002/plw_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
43543,585,"PLW","Palau","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2002/plw_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
43544,585,"PLW","Palau","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2002/plw_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
43545,585,"PLW","Palau","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2002/plw_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
43546,585,"PLW","Palau","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2002/plw_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
43547,585,"PLW","Palau","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2002/plw_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
43548,585,"PLW","Palau","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2002/plw_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
43549,585,"PLW","Palau","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2003/plw_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
43550,585,"PLW","Palau","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2003/plw_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
43551,585,"PLW","Palau","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2003/plw_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
43552,585,"PLW","Palau","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2003/plw_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
43553,585,"PLW","Palau","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2003/plw_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
43554,585,"PLW","Palau","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2003/plw_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
43555,585,"PLW","Palau","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2003/plw_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
43556,585,"PLW","Palau","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2003/plw_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
43557,585,"PLW","Palau","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2004/plw_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
43558,585,"PLW","Palau","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2004/plw_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
43559,585,"PLW","Palau","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2004/plw_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
43560,585,"PLW","Palau","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2004/plw_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
43561,585,"PLW","Palau","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2004/plw_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
43562,585,"PLW","Palau","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2004/plw_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
43563,585,"PLW","Palau","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2004/plw_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
43564,585,"PLW","Palau","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2004/plw_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
43565,585,"PLW","Palau","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2005/plw_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
43566,585,"PLW","Palau","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2005/plw_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
43567,585,"PLW","Palau","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2005/plw_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
43568,585,"PLW","Palau","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2005/plw_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
43569,585,"PLW","Palau","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2005/plw_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
43570,585,"PLW","Palau","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2005/plw_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
43571,585,"PLW","Palau","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2005/plw_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
43572,585,"PLW","Palau","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2005/plw_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
43573,585,"PLW","Palau","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2006/plw_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
43574,585,"PLW","Palau","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2006/plw_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
43575,585,"PLW","Palau","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2006/plw_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
43576,585,"PLW","Palau","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2006/plw_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
43577,585,"PLW","Palau","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2006/plw_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
43578,585,"PLW","Palau","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2006/plw_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
43579,585,"PLW","Palau","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2006/plw_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
43580,585,"PLW","Palau","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2006/plw_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
43581,585,"PLW","Palau","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2007/plw_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
43582,585,"PLW","Palau","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2007/plw_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
43583,585,"PLW","Palau","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2007/plw_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
43584,585,"PLW","Palau","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2007/plw_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
43585,585,"PLW","Palau","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2007/plw_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
43586,585,"PLW","Palau","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2007/plw_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
43587,585,"PLW","Palau","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2007/plw_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
43588,585,"PLW","Palau","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2007/plw_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
43589,585,"PLW","Palau","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2008/plw_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
43590,585,"PLW","Palau","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2008/plw_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
43591,585,"PLW","Palau","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2008/plw_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
43592,585,"PLW","Palau","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2008/plw_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
43593,585,"PLW","Palau","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2008/plw_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
43594,585,"PLW","Palau","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2008/plw_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
43595,585,"PLW","Palau","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2008/plw_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
43596,585,"PLW","Palau","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2008/plw_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
43597,585,"PLW","Palau","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2009/plw_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
43598,585,"PLW","Palau","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2009/plw_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
43599,585,"PLW","Palau","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2009/plw_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
43600,585,"PLW","Palau","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2009/plw_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
43601,585,"PLW","Palau","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2009/plw_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
43602,585,"PLW","Palau","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2009/plw_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
43603,585,"PLW","Palau","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2009/plw_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
43604,585,"PLW","Palau","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2009/plw_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
43605,585,"PLW","Palau","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2010/plw_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
43606,585,"PLW","Palau","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2010/plw_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
43607,585,"PLW","Palau","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2010/plw_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
43608,585,"PLW","Palau","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2010/plw_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
43609,585,"PLW","Palau","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2010/plw_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
43610,585,"PLW","Palau","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2010/plw_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
43611,585,"PLW","Palau","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2010/plw_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
43612,585,"PLW","Palau","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2010/plw_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
43613,585,"PLW","Palau","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2011/plw_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
43614,585,"PLW","Palau","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2011/plw_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
43615,585,"PLW","Palau","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2011/plw_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
43616,585,"PLW","Palau","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2011/plw_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
43617,585,"PLW","Palau","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2011/plw_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
43618,585,"PLW","Palau","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2011/plw_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
43619,585,"PLW","Palau","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2011/plw_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
43620,585,"PLW","Palau","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2011/plw_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
43621,585,"PLW","Palau","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2012/plw_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
43622,585,"PLW","Palau","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2012/plw_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
43623,585,"PLW","Palau","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2012/plw_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
43624,585,"PLW","Palau","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2012/plw_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
43625,585,"PLW","Palau","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2012/plw_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
43626,585,"PLW","Palau","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2012/plw_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
43627,585,"PLW","Palau","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2012/plw_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
43628,585,"PLW","Palau","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2012/plw_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
43629,585,"PLW","Palau","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2013/plw_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
43630,585,"PLW","Palau","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2013/plw_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
43631,585,"PLW","Palau","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2013/plw_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
43632,585,"PLW","Palau","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2013/plw_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
43633,585,"PLW","Palau","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2013/plw_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
43634,585,"PLW","Palau","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2013/plw_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
43635,585,"PLW","Palau","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2013/plw_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
43636,585,"PLW","Palau","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2013/plw_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
43637,585,"PLW","Palau","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2014/plw_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
43638,585,"PLW","Palau","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2014/plw_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
43639,585,"PLW","Palau","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2014/plw_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
43640,585,"PLW","Palau","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2014/plw_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
43641,585,"PLW","Palau","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2014/plw_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
43642,585,"PLW","Palau","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2014/plw_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
43643,585,"PLW","Palau","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2014/plw_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
43644,585,"PLW","Palau","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2014/plw_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
43645,585,"PLW","Palau","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2015/plw_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
43646,585,"PLW","Palau","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2015/plw_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
43647,585,"PLW","Palau","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2015/plw_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
43648,585,"PLW","Palau","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2015/plw_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
43649,585,"PLW","Palau","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2015/plw_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
43650,585,"PLW","Palau","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2015/plw_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
43651,585,"PLW","Palau","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2015/plw_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
43652,585,"PLW","Palau","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Annual/2015/plw_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
43653,586,"PAK","Pakistan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2000/pak_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
43654,586,"PAK","Pakistan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2000/pak_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
43655,586,"PAK","Pakistan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2000/pak_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
43656,586,"PAK","Pakistan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2000/pak_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
43657,586,"PAK","Pakistan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2000/pak_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
43658,586,"PAK","Pakistan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2000/pak_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
43659,586,"PAK","Pakistan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2000/pak_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
43660,586,"PAK","Pakistan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2000/pak_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
43661,586,"PAK","Pakistan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2001/pak_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
43662,586,"PAK","Pakistan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2001/pak_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
43663,586,"PAK","Pakistan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2001/pak_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
43664,586,"PAK","Pakistan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2001/pak_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
43665,586,"PAK","Pakistan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2001/pak_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
43666,586,"PAK","Pakistan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2001/pak_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
43667,586,"PAK","Pakistan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2001/pak_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
43668,586,"PAK","Pakistan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2001/pak_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
43669,586,"PAK","Pakistan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2002/pak_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
43670,586,"PAK","Pakistan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2002/pak_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
43671,586,"PAK","Pakistan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2002/pak_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
43672,586,"PAK","Pakistan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2002/pak_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
43673,586,"PAK","Pakistan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2002/pak_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
43674,586,"PAK","Pakistan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2002/pak_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
43675,586,"PAK","Pakistan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2002/pak_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
43676,586,"PAK","Pakistan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2002/pak_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
43677,586,"PAK","Pakistan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2003/pak_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
43678,586,"PAK","Pakistan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2003/pak_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
43679,586,"PAK","Pakistan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2003/pak_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
43680,586,"PAK","Pakistan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2003/pak_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
43681,586,"PAK","Pakistan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2003/pak_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
43682,586,"PAK","Pakistan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2003/pak_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
43683,586,"PAK","Pakistan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2003/pak_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
43684,586,"PAK","Pakistan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2003/pak_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
43685,586,"PAK","Pakistan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2004/pak_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
43686,586,"PAK","Pakistan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2004/pak_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
43687,586,"PAK","Pakistan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2004/pak_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
43688,586,"PAK","Pakistan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2004/pak_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
43689,586,"PAK","Pakistan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2004/pak_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
43690,586,"PAK","Pakistan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2004/pak_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
43691,586,"PAK","Pakistan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2004/pak_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
43692,586,"PAK","Pakistan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2004/pak_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
43693,586,"PAK","Pakistan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2005/pak_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
43694,586,"PAK","Pakistan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2005/pak_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
43695,586,"PAK","Pakistan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2005/pak_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
43696,586,"PAK","Pakistan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2005/pak_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
43697,586,"PAK","Pakistan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2005/pak_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
43698,586,"PAK","Pakistan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2005/pak_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
43699,586,"PAK","Pakistan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2005/pak_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
43700,586,"PAK","Pakistan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2005/pak_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
43701,586,"PAK","Pakistan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2006/pak_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
43702,586,"PAK","Pakistan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2006/pak_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
43703,586,"PAK","Pakistan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2006/pak_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
43704,586,"PAK","Pakistan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2006/pak_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
43705,586,"PAK","Pakistan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2006/pak_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
43706,586,"PAK","Pakistan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2006/pak_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
43707,586,"PAK","Pakistan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2006/pak_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
43708,586,"PAK","Pakistan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2006/pak_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
43709,586,"PAK","Pakistan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2007/pak_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
43710,586,"PAK","Pakistan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2007/pak_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
43711,586,"PAK","Pakistan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2007/pak_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
43712,586,"PAK","Pakistan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2007/pak_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
43713,586,"PAK","Pakistan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2007/pak_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
43714,586,"PAK","Pakistan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2007/pak_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
43715,586,"PAK","Pakistan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2007/pak_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
43716,586,"PAK","Pakistan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2007/pak_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
43717,586,"PAK","Pakistan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2008/pak_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
43718,586,"PAK","Pakistan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2008/pak_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
43719,586,"PAK","Pakistan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2008/pak_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
43720,586,"PAK","Pakistan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2008/pak_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
43721,586,"PAK","Pakistan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2008/pak_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
43722,586,"PAK","Pakistan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2008/pak_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
43723,586,"PAK","Pakistan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2008/pak_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
43724,586,"PAK","Pakistan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2008/pak_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
43725,586,"PAK","Pakistan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2009/pak_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
43726,586,"PAK","Pakistan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2009/pak_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
43727,586,"PAK","Pakistan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2009/pak_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
43728,586,"PAK","Pakistan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2009/pak_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
43729,586,"PAK","Pakistan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2009/pak_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
43730,586,"PAK","Pakistan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2009/pak_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
43731,586,"PAK","Pakistan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2009/pak_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
43732,586,"PAK","Pakistan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2009/pak_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
43733,586,"PAK","Pakistan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2010/pak_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
43734,586,"PAK","Pakistan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2010/pak_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
43735,586,"PAK","Pakistan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2010/pak_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
43736,586,"PAK","Pakistan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2010/pak_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
43737,586,"PAK","Pakistan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2010/pak_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
43738,586,"PAK","Pakistan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2010/pak_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
43739,586,"PAK","Pakistan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2010/pak_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
43740,586,"PAK","Pakistan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2010/pak_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
43741,586,"PAK","Pakistan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2011/pak_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
43742,586,"PAK","Pakistan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2011/pak_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
43743,586,"PAK","Pakistan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2011/pak_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
43744,586,"PAK","Pakistan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2011/pak_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
43745,586,"PAK","Pakistan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2011/pak_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
43746,586,"PAK","Pakistan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2011/pak_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
43747,586,"PAK","Pakistan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2011/pak_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
43748,586,"PAK","Pakistan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2011/pak_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
43749,586,"PAK","Pakistan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2012/pak_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
43750,586,"PAK","Pakistan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2012/pak_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
43751,586,"PAK","Pakistan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2012/pak_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
43752,586,"PAK","Pakistan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2012/pak_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
43753,586,"PAK","Pakistan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2012/pak_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
43754,586,"PAK","Pakistan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2012/pak_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
43755,586,"PAK","Pakistan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2012/pak_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
43756,586,"PAK","Pakistan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2012/pak_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
43757,586,"PAK","Pakistan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2013/pak_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
43758,586,"PAK","Pakistan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2013/pak_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
43759,586,"PAK","Pakistan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2013/pak_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
43760,586,"PAK","Pakistan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2013/pak_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
43761,586,"PAK","Pakistan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2013/pak_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
43762,586,"PAK","Pakistan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2013/pak_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
43763,586,"PAK","Pakistan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2013/pak_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
43764,586,"PAK","Pakistan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2013/pak_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
43765,586,"PAK","Pakistan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2014/pak_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
43766,586,"PAK","Pakistan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2014/pak_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
43767,586,"PAK","Pakistan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2014/pak_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
43768,586,"PAK","Pakistan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2014/pak_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
43769,586,"PAK","Pakistan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2014/pak_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
43770,586,"PAK","Pakistan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2014/pak_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
43771,586,"PAK","Pakistan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2014/pak_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
43772,586,"PAK","Pakistan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2014/pak_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
43773,586,"PAK","Pakistan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2015/pak_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
43774,586,"PAK","Pakistan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2015/pak_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
43775,586,"PAK","Pakistan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2015/pak_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
43776,586,"PAK","Pakistan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2015/pak_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
43777,586,"PAK","Pakistan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2015/pak_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
43778,586,"PAK","Pakistan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2015/pak_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
43779,586,"PAK","Pakistan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2015/pak_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
43780,586,"PAK","Pakistan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Annual/2015/pak_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
43781,591,"PAN","Panama","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2000/pan_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
43782,591,"PAN","Panama","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2000/pan_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
43783,591,"PAN","Panama","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2000/pan_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
43784,591,"PAN","Panama","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2000/pan_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
43785,591,"PAN","Panama","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2000/pan_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
43786,591,"PAN","Panama","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2000/pan_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
43787,591,"PAN","Panama","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2000/pan_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
43788,591,"PAN","Panama","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2000/pan_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
43789,591,"PAN","Panama","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2001/pan_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
43790,591,"PAN","Panama","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2001/pan_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
43791,591,"PAN","Panama","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2001/pan_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
43792,591,"PAN","Panama","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2001/pan_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
43793,591,"PAN","Panama","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2001/pan_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
43794,591,"PAN","Panama","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2001/pan_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
43795,591,"PAN","Panama","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2001/pan_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
43796,591,"PAN","Panama","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2001/pan_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
43797,591,"PAN","Panama","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2002/pan_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
43798,591,"PAN","Panama","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2002/pan_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
43799,591,"PAN","Panama","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2002/pan_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
43800,591,"PAN","Panama","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2002/pan_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
43801,591,"PAN","Panama","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2002/pan_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
43802,591,"PAN","Panama","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2002/pan_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
43803,591,"PAN","Panama","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2002/pan_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
43804,591,"PAN","Panama","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2002/pan_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
43805,591,"PAN","Panama","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2003/pan_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
43806,591,"PAN","Panama","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2003/pan_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
43807,591,"PAN","Panama","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2003/pan_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
43808,591,"PAN","Panama","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2003/pan_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
43809,591,"PAN","Panama","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2003/pan_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
43810,591,"PAN","Panama","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2003/pan_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
43811,591,"PAN","Panama","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2003/pan_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
43812,591,"PAN","Panama","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2003/pan_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
43813,591,"PAN","Panama","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2004/pan_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
43814,591,"PAN","Panama","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2004/pan_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
43815,591,"PAN","Panama","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2004/pan_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
43816,591,"PAN","Panama","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2004/pan_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
43817,591,"PAN","Panama","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2004/pan_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
43818,591,"PAN","Panama","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2004/pan_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
43819,591,"PAN","Panama","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2004/pan_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
43820,591,"PAN","Panama","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2004/pan_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
43821,591,"PAN","Panama","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2005/pan_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
43822,591,"PAN","Panama","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2005/pan_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
43823,591,"PAN","Panama","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2005/pan_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
43824,591,"PAN","Panama","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2005/pan_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
43825,591,"PAN","Panama","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2005/pan_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
43826,591,"PAN","Panama","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2005/pan_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
43827,591,"PAN","Panama","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2005/pan_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
43828,591,"PAN","Panama","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2005/pan_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
43829,591,"PAN","Panama","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2006/pan_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
43830,591,"PAN","Panama","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2006/pan_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
43831,591,"PAN","Panama","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2006/pan_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
43832,591,"PAN","Panama","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2006/pan_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
43833,591,"PAN","Panama","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2006/pan_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
43834,591,"PAN","Panama","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2006/pan_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
43835,591,"PAN","Panama","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2006/pan_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
43836,591,"PAN","Panama","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2006/pan_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
43837,591,"PAN","Panama","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2007/pan_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
43838,591,"PAN","Panama","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2007/pan_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
43839,591,"PAN","Panama","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2007/pan_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
43840,591,"PAN","Panama","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2007/pan_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
43841,591,"PAN","Panama","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2007/pan_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
43842,591,"PAN","Panama","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2007/pan_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
43843,591,"PAN","Panama","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2007/pan_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
43844,591,"PAN","Panama","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2007/pan_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
43845,591,"PAN","Panama","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2008/pan_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
43846,591,"PAN","Panama","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2008/pan_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
43847,591,"PAN","Panama","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2008/pan_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
43848,591,"PAN","Panama","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2008/pan_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
43849,591,"PAN","Panama","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2008/pan_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
43850,591,"PAN","Panama","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2008/pan_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
43851,591,"PAN","Panama","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2008/pan_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
43852,591,"PAN","Panama","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2008/pan_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
43853,591,"PAN","Panama","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2009/pan_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
43854,591,"PAN","Panama","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2009/pan_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
43855,591,"PAN","Panama","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2009/pan_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
43856,591,"PAN","Panama","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2009/pan_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
43857,591,"PAN","Panama","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2009/pan_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
43858,591,"PAN","Panama","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2009/pan_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
43859,591,"PAN","Panama","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2009/pan_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
43860,591,"PAN","Panama","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2009/pan_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
43861,591,"PAN","Panama","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2010/pan_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
43862,591,"PAN","Panama","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2010/pan_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
43863,591,"PAN","Panama","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2010/pan_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
43864,591,"PAN","Panama","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2010/pan_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
43865,591,"PAN","Panama","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2010/pan_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
43866,591,"PAN","Panama","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2010/pan_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
43867,591,"PAN","Panama","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2010/pan_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
43868,591,"PAN","Panama","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2010/pan_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
43869,591,"PAN","Panama","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2011/pan_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
43870,591,"PAN","Panama","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2011/pan_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
43871,591,"PAN","Panama","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2011/pan_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
43872,591,"PAN","Panama","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2011/pan_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
43873,591,"PAN","Panama","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2011/pan_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
43874,591,"PAN","Panama","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2011/pan_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
43875,591,"PAN","Panama","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2011/pan_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
43876,591,"PAN","Panama","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2011/pan_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
43877,591,"PAN","Panama","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2012/pan_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
43878,591,"PAN","Panama","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2012/pan_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
43879,591,"PAN","Panama","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2012/pan_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
43880,591,"PAN","Panama","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2012/pan_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
43881,591,"PAN","Panama","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2012/pan_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
43882,591,"PAN","Panama","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2012/pan_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
43883,591,"PAN","Panama","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2012/pan_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
43884,591,"PAN","Panama","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2012/pan_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
43885,591,"PAN","Panama","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2013/pan_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
43886,591,"PAN","Panama","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2013/pan_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
43887,591,"PAN","Panama","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2013/pan_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
43888,591,"PAN","Panama","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2013/pan_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
43889,591,"PAN","Panama","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2013/pan_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
43890,591,"PAN","Panama","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2013/pan_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
43891,591,"PAN","Panama","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2013/pan_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
43892,591,"PAN","Panama","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2013/pan_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
43893,591,"PAN","Panama","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2014/pan_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
43894,591,"PAN","Panama","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2014/pan_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
43895,591,"PAN","Panama","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2014/pan_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
43896,591,"PAN","Panama","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2014/pan_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
43897,591,"PAN","Panama","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2014/pan_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
43898,591,"PAN","Panama","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2014/pan_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
43899,591,"PAN","Panama","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2014/pan_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
43900,591,"PAN","Panama","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2014/pan_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
43901,591,"PAN","Panama","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2015/pan_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
43902,591,"PAN","Panama","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2015/pan_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
43903,591,"PAN","Panama","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2015/pan_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
43904,591,"PAN","Panama","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2015/pan_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
43905,591,"PAN","Panama","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2015/pan_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
43906,591,"PAN","Panama","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2015/pan_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
43907,591,"PAN","Panama","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2015/pan_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
43908,591,"PAN","Panama","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Annual/2015/pan_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
43909,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2000/png_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
43910,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2000/png_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
43911,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2000/png_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
43912,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2000/png_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
43913,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2000/png_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
43914,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2000/png_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
43915,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2000/png_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
43916,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2000/png_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
43917,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2001/png_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
43918,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2001/png_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
43919,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2001/png_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
43920,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2001/png_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
43921,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2001/png_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
43922,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2001/png_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
43923,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2001/png_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
43924,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2001/png_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
43925,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2002/png_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
43926,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2002/png_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
43927,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2002/png_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
43928,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2002/png_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
43929,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2002/png_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
43930,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2002/png_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
43931,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2002/png_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
43932,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2002/png_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
43933,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2003/png_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
43934,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2003/png_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
43935,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2003/png_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
43936,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2003/png_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
43937,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2003/png_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
43938,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2003/png_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
43939,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2003/png_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
43940,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2003/png_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
43941,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2004/png_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
43942,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2004/png_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
43943,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2004/png_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
43944,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2004/png_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
43945,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2004/png_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
43946,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2004/png_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
43947,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2004/png_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
43948,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2004/png_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
43949,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2005/png_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
43950,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2005/png_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
43951,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2005/png_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
43952,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2005/png_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
43953,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2005/png_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
43954,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2005/png_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
43955,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2005/png_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
43956,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2005/png_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
43957,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2006/png_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
43958,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2006/png_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
43959,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2006/png_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
43960,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2006/png_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
43961,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2006/png_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
43962,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2006/png_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
43963,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2006/png_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
43964,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2006/png_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
43965,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2007/png_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
43966,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2007/png_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
43967,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2007/png_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
43968,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2007/png_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
43969,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2007/png_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
43970,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2007/png_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
43971,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2007/png_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
43972,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2007/png_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
43973,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2008/png_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
43974,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2008/png_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
43975,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2008/png_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
43976,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2008/png_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
43977,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2008/png_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
43978,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2008/png_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
43979,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2008/png_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
43980,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2008/png_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
43981,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2009/png_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
43982,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2009/png_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
43983,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2009/png_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
43984,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2009/png_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
43985,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2009/png_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
43986,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2009/png_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
43987,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2009/png_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
43988,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2009/png_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
43989,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2010/png_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
43990,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2010/png_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
43991,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2010/png_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
43992,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2010/png_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
43993,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2010/png_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
43994,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2010/png_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
43995,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2010/png_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
43996,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2010/png_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
43997,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2011/png_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
43998,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2011/png_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
43999,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2011/png_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
44000,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2011/png_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
44001,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2011/png_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
44002,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2011/png_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
44003,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2011/png_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
44004,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2011/png_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
44005,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2012/png_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
44006,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2012/png_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
44007,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2012/png_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
44008,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2012/png_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
44009,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2012/png_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
44010,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2012/png_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
44011,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2012/png_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
44012,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2012/png_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
44013,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2013/png_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
44014,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2013/png_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
44015,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2013/png_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
44016,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2013/png_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
44017,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2013/png_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
44018,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2013/png_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
44019,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2013/png_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
44020,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2013/png_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
44021,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2014/png_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
44022,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2014/png_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
44023,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2014/png_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
44024,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2014/png_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
44025,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2014/png_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
44026,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2014/png_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
44027,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2014/png_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
44028,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2014/png_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
44029,598,"PNG","Papua New Guinea","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2015/png_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
44030,598,"PNG","Papua New Guinea","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2015/png_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
44031,598,"PNG","Papua New Guinea","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2015/png_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
44032,598,"PNG","Papua New Guinea","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2015/png_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
44033,598,"PNG","Papua New Guinea","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2015/png_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
44034,598,"PNG","Papua New Guinea","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2015/png_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
44035,598,"PNG","Papua New Guinea","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2015/png_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
44036,598,"PNG","Papua New Guinea","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Annual/2015/png_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
44037,600,"PRY","Paraguay","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2000/pry_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
44038,600,"PRY","Paraguay","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2000/pry_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
44039,600,"PRY","Paraguay","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2000/pry_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
44040,600,"PRY","Paraguay","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2000/pry_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
44041,600,"PRY","Paraguay","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2000/pry_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
44042,600,"PRY","Paraguay","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2000/pry_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
44043,600,"PRY","Paraguay","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2000/pry_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
44044,600,"PRY","Paraguay","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2000/pry_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
44045,600,"PRY","Paraguay","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2001/pry_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
44046,600,"PRY","Paraguay","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2001/pry_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
44047,600,"PRY","Paraguay","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2001/pry_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
44048,600,"PRY","Paraguay","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2001/pry_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
44049,600,"PRY","Paraguay","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2001/pry_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
44050,600,"PRY","Paraguay","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2001/pry_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
44051,600,"PRY","Paraguay","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2001/pry_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
44052,600,"PRY","Paraguay","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2001/pry_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
44053,600,"PRY","Paraguay","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2002/pry_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
44054,600,"PRY","Paraguay","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2002/pry_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
44055,600,"PRY","Paraguay","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2002/pry_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
44056,600,"PRY","Paraguay","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2002/pry_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
44057,600,"PRY","Paraguay","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2002/pry_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
44058,600,"PRY","Paraguay","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2002/pry_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
44059,600,"PRY","Paraguay","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2002/pry_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
44060,600,"PRY","Paraguay","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2002/pry_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
44061,600,"PRY","Paraguay","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2003/pry_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
44062,600,"PRY","Paraguay","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2003/pry_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
44063,600,"PRY","Paraguay","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2003/pry_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
44064,600,"PRY","Paraguay","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2003/pry_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
44065,600,"PRY","Paraguay","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2003/pry_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
44066,600,"PRY","Paraguay","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2003/pry_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
44067,600,"PRY","Paraguay","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2003/pry_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
44068,600,"PRY","Paraguay","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2003/pry_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
44069,600,"PRY","Paraguay","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2004/pry_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
44070,600,"PRY","Paraguay","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2004/pry_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
44071,600,"PRY","Paraguay","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2004/pry_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
44072,600,"PRY","Paraguay","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2004/pry_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
44073,600,"PRY","Paraguay","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2004/pry_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
44074,600,"PRY","Paraguay","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2004/pry_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
44075,600,"PRY","Paraguay","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2004/pry_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
44076,600,"PRY","Paraguay","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2004/pry_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
44077,600,"PRY","Paraguay","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2005/pry_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
44078,600,"PRY","Paraguay","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2005/pry_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
44079,600,"PRY","Paraguay","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2005/pry_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
44080,600,"PRY","Paraguay","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2005/pry_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
44081,600,"PRY","Paraguay","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2005/pry_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
44082,600,"PRY","Paraguay","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2005/pry_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
44083,600,"PRY","Paraguay","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2005/pry_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
44084,600,"PRY","Paraguay","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2005/pry_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
44085,600,"PRY","Paraguay","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2006/pry_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
44086,600,"PRY","Paraguay","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2006/pry_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
44087,600,"PRY","Paraguay","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2006/pry_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
44088,600,"PRY","Paraguay","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2006/pry_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
44089,600,"PRY","Paraguay","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2006/pry_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
44090,600,"PRY","Paraguay","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2006/pry_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
44091,600,"PRY","Paraguay","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2006/pry_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
44092,600,"PRY","Paraguay","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2006/pry_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
44093,600,"PRY","Paraguay","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2007/pry_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
44094,600,"PRY","Paraguay","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2007/pry_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
44095,600,"PRY","Paraguay","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2007/pry_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
44096,600,"PRY","Paraguay","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2007/pry_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
44097,600,"PRY","Paraguay","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2007/pry_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
44098,600,"PRY","Paraguay","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2007/pry_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
44099,600,"PRY","Paraguay","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2007/pry_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
44100,600,"PRY","Paraguay","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2007/pry_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
44101,600,"PRY","Paraguay","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2008/pry_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
44102,600,"PRY","Paraguay","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2008/pry_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
44103,600,"PRY","Paraguay","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2008/pry_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
44104,600,"PRY","Paraguay","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2008/pry_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
44105,600,"PRY","Paraguay","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2008/pry_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
44106,600,"PRY","Paraguay","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2008/pry_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
44107,600,"PRY","Paraguay","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2008/pry_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
44108,600,"PRY","Paraguay","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2008/pry_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
44109,600,"PRY","Paraguay","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2009/pry_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
44110,600,"PRY","Paraguay","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2009/pry_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
44111,600,"PRY","Paraguay","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2009/pry_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
44112,600,"PRY","Paraguay","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2009/pry_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
44113,600,"PRY","Paraguay","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2009/pry_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
44114,600,"PRY","Paraguay","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2009/pry_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
44115,600,"PRY","Paraguay","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2009/pry_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
44116,600,"PRY","Paraguay","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2009/pry_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
44117,600,"PRY","Paraguay","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2010/pry_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
44118,600,"PRY","Paraguay","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2010/pry_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
44119,600,"PRY","Paraguay","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2010/pry_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
44120,600,"PRY","Paraguay","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2010/pry_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
44121,600,"PRY","Paraguay","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2010/pry_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
44122,600,"PRY","Paraguay","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2010/pry_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
44123,600,"PRY","Paraguay","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2010/pry_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
44124,600,"PRY","Paraguay","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2010/pry_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
44125,600,"PRY","Paraguay","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2011/pry_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
44126,600,"PRY","Paraguay","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2011/pry_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
44127,600,"PRY","Paraguay","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2011/pry_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
44128,600,"PRY","Paraguay","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2011/pry_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
44129,600,"PRY","Paraguay","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2011/pry_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
44130,600,"PRY","Paraguay","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2011/pry_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
44131,600,"PRY","Paraguay","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2011/pry_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
44132,600,"PRY","Paraguay","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2011/pry_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
44133,600,"PRY","Paraguay","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2012/pry_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
44134,600,"PRY","Paraguay","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2012/pry_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
44135,600,"PRY","Paraguay","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2012/pry_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
44136,600,"PRY","Paraguay","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2012/pry_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
44137,600,"PRY","Paraguay","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2012/pry_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
44138,600,"PRY","Paraguay","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2012/pry_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
44139,600,"PRY","Paraguay","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2012/pry_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
44140,600,"PRY","Paraguay","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2012/pry_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
44141,600,"PRY","Paraguay","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2013/pry_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
44142,600,"PRY","Paraguay","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2013/pry_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
44143,600,"PRY","Paraguay","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2013/pry_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
44144,600,"PRY","Paraguay","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2013/pry_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
44145,600,"PRY","Paraguay","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2013/pry_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
44146,600,"PRY","Paraguay","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2013/pry_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
44147,600,"PRY","Paraguay","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2013/pry_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
44148,600,"PRY","Paraguay","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2013/pry_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
44149,600,"PRY","Paraguay","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2014/pry_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
44150,600,"PRY","Paraguay","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2014/pry_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
44151,600,"PRY","Paraguay","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2014/pry_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
44152,600,"PRY","Paraguay","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2014/pry_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
44153,600,"PRY","Paraguay","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2014/pry_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
44154,600,"PRY","Paraguay","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2014/pry_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
44155,600,"PRY","Paraguay","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2014/pry_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
44156,600,"PRY","Paraguay","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2014/pry_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
44157,600,"PRY","Paraguay","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2015/pry_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
44158,600,"PRY","Paraguay","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2015/pry_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
44159,600,"PRY","Paraguay","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2015/pry_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
44160,600,"PRY","Paraguay","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2015/pry_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
44161,600,"PRY","Paraguay","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2015/pry_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
44162,600,"PRY","Paraguay","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2015/pry_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
44163,600,"PRY","Paraguay","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2015/pry_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
44164,600,"PRY","Paraguay","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Annual/2015/pry_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
44165,604,"PER","Peru","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2000/per_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
44166,604,"PER","Peru","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2000/per_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
44167,604,"PER","Peru","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2000/per_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
44168,604,"PER","Peru","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2000/per_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
44169,604,"PER","Peru","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2000/per_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
44170,604,"PER","Peru","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2000/per_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
44171,604,"PER","Peru","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2000/per_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
44172,604,"PER","Peru","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2000/per_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
44173,604,"PER","Peru","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2001/per_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
44174,604,"PER","Peru","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2001/per_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
44175,604,"PER","Peru","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2001/per_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
44176,604,"PER","Peru","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2001/per_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
44177,604,"PER","Peru","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2001/per_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
44178,604,"PER","Peru","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2001/per_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
44179,604,"PER","Peru","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2001/per_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
44180,604,"PER","Peru","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2001/per_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
44181,604,"PER","Peru","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2002/per_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
44182,604,"PER","Peru","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2002/per_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
44183,604,"PER","Peru","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2002/per_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
44184,604,"PER","Peru","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2002/per_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
44185,604,"PER","Peru","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2002/per_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
44186,604,"PER","Peru","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2002/per_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
44187,604,"PER","Peru","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2002/per_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
44188,604,"PER","Peru","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2002/per_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
44189,604,"PER","Peru","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2003/per_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
44190,604,"PER","Peru","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2003/per_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
44191,604,"PER","Peru","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2003/per_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
44192,604,"PER","Peru","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2003/per_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
44193,604,"PER","Peru","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2003/per_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
44194,604,"PER","Peru","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2003/per_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
44195,604,"PER","Peru","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2003/per_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
44196,604,"PER","Peru","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2003/per_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
44197,604,"PER","Peru","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2004/per_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
44198,604,"PER","Peru","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2004/per_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
44199,604,"PER","Peru","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2004/per_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
44200,604,"PER","Peru","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2004/per_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
44201,604,"PER","Peru","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2004/per_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
44202,604,"PER","Peru","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2004/per_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
44203,604,"PER","Peru","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2004/per_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
44204,604,"PER","Peru","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2004/per_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
44205,604,"PER","Peru","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2005/per_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
44206,604,"PER","Peru","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2005/per_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
44207,604,"PER","Peru","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2005/per_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
44208,604,"PER","Peru","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2005/per_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
44209,604,"PER","Peru","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2005/per_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
44210,604,"PER","Peru","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2005/per_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
44211,604,"PER","Peru","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2005/per_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
44212,604,"PER","Peru","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2005/per_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
44213,604,"PER","Peru","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2006/per_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
44214,604,"PER","Peru","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2006/per_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
44215,604,"PER","Peru","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2006/per_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
44216,604,"PER","Peru","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2006/per_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
44217,604,"PER","Peru","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2006/per_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
44218,604,"PER","Peru","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2006/per_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
44219,604,"PER","Peru","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2006/per_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
44220,604,"PER","Peru","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2006/per_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
44221,604,"PER","Peru","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2007/per_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
44222,604,"PER","Peru","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2007/per_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
44223,604,"PER","Peru","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2007/per_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
44224,604,"PER","Peru","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2007/per_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
44225,604,"PER","Peru","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2007/per_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
44226,604,"PER","Peru","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2007/per_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
44227,604,"PER","Peru","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2007/per_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
44228,604,"PER","Peru","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2007/per_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
44229,604,"PER","Peru","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2008/per_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
44230,604,"PER","Peru","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2008/per_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
44231,604,"PER","Peru","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2008/per_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
44232,604,"PER","Peru","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2008/per_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
44233,604,"PER","Peru","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2008/per_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
44234,604,"PER","Peru","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2008/per_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
44235,604,"PER","Peru","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2008/per_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
44236,604,"PER","Peru","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2008/per_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
44237,604,"PER","Peru","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2009/per_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
44238,604,"PER","Peru","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2009/per_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
44239,604,"PER","Peru","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2009/per_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
44240,604,"PER","Peru","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2009/per_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
44241,604,"PER","Peru","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2009/per_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
44242,604,"PER","Peru","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2009/per_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
44243,604,"PER","Peru","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2009/per_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
44244,604,"PER","Peru","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2009/per_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
44245,604,"PER","Peru","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2010/per_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
44246,604,"PER","Peru","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2010/per_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
44247,604,"PER","Peru","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2010/per_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
44248,604,"PER","Peru","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2010/per_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
44249,604,"PER","Peru","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2010/per_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
44250,604,"PER","Peru","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2010/per_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
44251,604,"PER","Peru","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2010/per_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
44252,604,"PER","Peru","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2010/per_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
44253,604,"PER","Peru","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2011/per_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
44254,604,"PER","Peru","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2011/per_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
44255,604,"PER","Peru","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2011/per_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
44256,604,"PER","Peru","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2011/per_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
44257,604,"PER","Peru","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2011/per_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
44258,604,"PER","Peru","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2011/per_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
44259,604,"PER","Peru","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2011/per_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
44260,604,"PER","Peru","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2011/per_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
44261,604,"PER","Peru","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2012/per_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
44262,604,"PER","Peru","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2012/per_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
44263,604,"PER","Peru","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2012/per_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
44264,604,"PER","Peru","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2012/per_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
44265,604,"PER","Peru","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2012/per_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
44266,604,"PER","Peru","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2012/per_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
44267,604,"PER","Peru","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2012/per_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
44268,604,"PER","Peru","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2012/per_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
44269,604,"PER","Peru","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2013/per_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
44270,604,"PER","Peru","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2013/per_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
44271,604,"PER","Peru","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2013/per_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
44272,604,"PER","Peru","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2013/per_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
44273,604,"PER","Peru","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2013/per_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
44274,604,"PER","Peru","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2013/per_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
44275,604,"PER","Peru","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2013/per_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
44276,604,"PER","Peru","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2013/per_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
44277,604,"PER","Peru","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2014/per_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
44278,604,"PER","Peru","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2014/per_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
44279,604,"PER","Peru","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2014/per_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
44280,604,"PER","Peru","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2014/per_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
44281,604,"PER","Peru","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2014/per_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
44282,604,"PER","Peru","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2014/per_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
44283,604,"PER","Peru","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2014/per_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
44284,604,"PER","Peru","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2014/per_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
44285,604,"PER","Peru","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2015/per_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
44286,604,"PER","Peru","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2015/per_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
44287,604,"PER","Peru","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2015/per_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
44288,604,"PER","Peru","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2015/per_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
44289,604,"PER","Peru","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2015/per_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
44290,604,"PER","Peru","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2015/per_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
44291,604,"PER","Peru","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2015/per_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
44292,604,"PER","Peru","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Annual/2015/per_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
44293,608,"PHL","Philippines","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2000/phl_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
44294,608,"PHL","Philippines","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2000/phl_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
44295,608,"PHL","Philippines","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2000/phl_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
44296,608,"PHL","Philippines","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2000/phl_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
44297,608,"PHL","Philippines","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2000/phl_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
44298,608,"PHL","Philippines","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2000/phl_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
44299,608,"PHL","Philippines","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2000/phl_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
44300,608,"PHL","Philippines","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2000/phl_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
44301,608,"PHL","Philippines","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2001/phl_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
44302,608,"PHL","Philippines","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2001/phl_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
44303,608,"PHL","Philippines","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2001/phl_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
44304,608,"PHL","Philippines","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2001/phl_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
44305,608,"PHL","Philippines","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2001/phl_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
44306,608,"PHL","Philippines","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2001/phl_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
44307,608,"PHL","Philippines","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2001/phl_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
44308,608,"PHL","Philippines","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2001/phl_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
44309,608,"PHL","Philippines","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2002/phl_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
44310,608,"PHL","Philippines","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2002/phl_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
44311,608,"PHL","Philippines","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2002/phl_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
44312,608,"PHL","Philippines","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2002/phl_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
44313,608,"PHL","Philippines","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2002/phl_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
44314,608,"PHL","Philippines","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2002/phl_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
44315,608,"PHL","Philippines","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2002/phl_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
44316,608,"PHL","Philippines","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2002/phl_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
44317,608,"PHL","Philippines","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2003/phl_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
44318,608,"PHL","Philippines","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2003/phl_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
44319,608,"PHL","Philippines","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2003/phl_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
44320,608,"PHL","Philippines","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2003/phl_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
44321,608,"PHL","Philippines","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2003/phl_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
44322,608,"PHL","Philippines","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2003/phl_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
44323,608,"PHL","Philippines","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2003/phl_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
44324,608,"PHL","Philippines","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2003/phl_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
44325,608,"PHL","Philippines","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2004/phl_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
44326,608,"PHL","Philippines","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2004/phl_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
44327,608,"PHL","Philippines","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2004/phl_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
44328,608,"PHL","Philippines","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2004/phl_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
44329,608,"PHL","Philippines","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2004/phl_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
44330,608,"PHL","Philippines","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2004/phl_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
44331,608,"PHL","Philippines","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2004/phl_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
44332,608,"PHL","Philippines","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2004/phl_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
44333,608,"PHL","Philippines","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2005/phl_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
44334,608,"PHL","Philippines","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2005/phl_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
44335,608,"PHL","Philippines","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2005/phl_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
44336,608,"PHL","Philippines","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2005/phl_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
44337,608,"PHL","Philippines","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2005/phl_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
44338,608,"PHL","Philippines","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2005/phl_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
44339,608,"PHL","Philippines","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2005/phl_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
44340,608,"PHL","Philippines","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2005/phl_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
44341,608,"PHL","Philippines","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2006/phl_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
44342,608,"PHL","Philippines","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2006/phl_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
44343,608,"PHL","Philippines","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2006/phl_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
44344,608,"PHL","Philippines","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2006/phl_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
44345,608,"PHL","Philippines","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2006/phl_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
44346,608,"PHL","Philippines","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2006/phl_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
44347,608,"PHL","Philippines","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2006/phl_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
44348,608,"PHL","Philippines","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2006/phl_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
44349,608,"PHL","Philippines","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2007/phl_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
44350,608,"PHL","Philippines","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2007/phl_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
44351,608,"PHL","Philippines","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2007/phl_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
44352,608,"PHL","Philippines","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2007/phl_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
44353,608,"PHL","Philippines","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2007/phl_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
44354,608,"PHL","Philippines","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2007/phl_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
44355,608,"PHL","Philippines","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2007/phl_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
44356,608,"PHL","Philippines","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2007/phl_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
44357,608,"PHL","Philippines","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2008/phl_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
44358,608,"PHL","Philippines","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2008/phl_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
44359,608,"PHL","Philippines","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2008/phl_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
44360,608,"PHL","Philippines","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2008/phl_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
44361,608,"PHL","Philippines","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2008/phl_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
44362,608,"PHL","Philippines","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2008/phl_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
44363,608,"PHL","Philippines","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2008/phl_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
44364,608,"PHL","Philippines","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2008/phl_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
44365,608,"PHL","Philippines","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2009/phl_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
44366,608,"PHL","Philippines","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2009/phl_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
44367,608,"PHL","Philippines","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2009/phl_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
44368,608,"PHL","Philippines","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2009/phl_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
44369,608,"PHL","Philippines","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2009/phl_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
44370,608,"PHL","Philippines","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2009/phl_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
44371,608,"PHL","Philippines","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2009/phl_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
44372,608,"PHL","Philippines","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2009/phl_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
44373,608,"PHL","Philippines","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2010/phl_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
44374,608,"PHL","Philippines","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2010/phl_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
44375,608,"PHL","Philippines","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2010/phl_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
44376,608,"PHL","Philippines","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2010/phl_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
44377,608,"PHL","Philippines","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2010/phl_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
44378,608,"PHL","Philippines","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2010/phl_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
44379,608,"PHL","Philippines","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2010/phl_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
44380,608,"PHL","Philippines","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2010/phl_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
44381,608,"PHL","Philippines","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2011/phl_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
44382,608,"PHL","Philippines","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2011/phl_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
44383,608,"PHL","Philippines","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2011/phl_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
44384,608,"PHL","Philippines","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2011/phl_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
44385,608,"PHL","Philippines","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2011/phl_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
44386,608,"PHL","Philippines","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2011/phl_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
44387,608,"PHL","Philippines","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2011/phl_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
44388,608,"PHL","Philippines","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2011/phl_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
44389,608,"PHL","Philippines","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2012/phl_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
44390,608,"PHL","Philippines","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2012/phl_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
44391,608,"PHL","Philippines","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2012/phl_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
44392,608,"PHL","Philippines","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2012/phl_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
44393,608,"PHL","Philippines","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2012/phl_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
44394,608,"PHL","Philippines","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2012/phl_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
44395,608,"PHL","Philippines","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2012/phl_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
44396,608,"PHL","Philippines","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2012/phl_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
44397,608,"PHL","Philippines","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2013/phl_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
44398,608,"PHL","Philippines","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2013/phl_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
44399,608,"PHL","Philippines","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2013/phl_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
44400,608,"PHL","Philippines","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2013/phl_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
44401,608,"PHL","Philippines","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2013/phl_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
44402,608,"PHL","Philippines","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2013/phl_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
44403,608,"PHL","Philippines","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2013/phl_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
44404,608,"PHL","Philippines","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2013/phl_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
44405,608,"PHL","Philippines","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2014/phl_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
44406,608,"PHL","Philippines","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2014/phl_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
44407,608,"PHL","Philippines","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2014/phl_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
44408,608,"PHL","Philippines","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2014/phl_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
44409,608,"PHL","Philippines","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2014/phl_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
44410,608,"PHL","Philippines","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2014/phl_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
44411,608,"PHL","Philippines","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2014/phl_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
44412,608,"PHL","Philippines","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2014/phl_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
44413,608,"PHL","Philippines","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2015/phl_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
44414,608,"PHL","Philippines","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2015/phl_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
44415,608,"PHL","Philippines","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2015/phl_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
44416,608,"PHL","Philippines","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2015/phl_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
44417,608,"PHL","Philippines","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2015/phl_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
44418,608,"PHL","Philippines","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2015/phl_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
44419,608,"PHL","Philippines","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2015/phl_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
44420,608,"PHL","Philippines","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Annual/2015/phl_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
44421,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2000/pcn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
44422,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2000/pcn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
44423,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2000/pcn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
44424,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2000/pcn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
44425,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2000/pcn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
44426,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2000/pcn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
44427,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2000/pcn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
44428,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2000/pcn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
44429,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2001/pcn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
44430,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2001/pcn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
44431,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2001/pcn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
44432,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2001/pcn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
44433,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2001/pcn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
44434,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2001/pcn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
44435,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2001/pcn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
44436,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2001/pcn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
44437,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2002/pcn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
44438,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2002/pcn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
44439,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2002/pcn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
44440,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2002/pcn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
44441,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2002/pcn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
44442,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2002/pcn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
44443,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2002/pcn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
44444,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2002/pcn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
44445,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2003/pcn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
44446,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2003/pcn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
44447,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2003/pcn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
44448,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2003/pcn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
44449,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2003/pcn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
44450,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2003/pcn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
44451,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2003/pcn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
44452,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2003/pcn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
44453,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2004/pcn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
44454,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2004/pcn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
44455,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2004/pcn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
44456,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2004/pcn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
44457,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2004/pcn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
44458,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2004/pcn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
44459,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2004/pcn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
44460,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2004/pcn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
44461,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2005/pcn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
44462,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2005/pcn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
44463,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2005/pcn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
44464,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2005/pcn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
44465,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2005/pcn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
44466,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2005/pcn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
44467,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2005/pcn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
44468,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2005/pcn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
44469,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2006/pcn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
44470,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2006/pcn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
44471,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2006/pcn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
44472,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2006/pcn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
44473,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2006/pcn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
44474,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2006/pcn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
44475,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2006/pcn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
44476,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2006/pcn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
44477,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2007/pcn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
44478,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2007/pcn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
44479,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2007/pcn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
44480,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2007/pcn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
44481,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2007/pcn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
44482,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2007/pcn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
44483,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2007/pcn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
44484,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2007/pcn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
44485,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2008/pcn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
44486,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2008/pcn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
44487,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2008/pcn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
44488,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2008/pcn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
44489,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2008/pcn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
44490,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2008/pcn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
44491,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2008/pcn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
44492,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2008/pcn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
44493,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2009/pcn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
44494,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2009/pcn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
44495,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2009/pcn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
44496,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2009/pcn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
44497,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2009/pcn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
44498,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2009/pcn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
44499,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2009/pcn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
44500,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2009/pcn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
44501,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2010/pcn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
44502,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2010/pcn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
44503,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2010/pcn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
44504,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2010/pcn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
44505,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2010/pcn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
44506,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2010/pcn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
44507,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2010/pcn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
44508,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2010/pcn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
44509,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2011/pcn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
44510,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2011/pcn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
44511,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2011/pcn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
44512,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2011/pcn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
44513,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2011/pcn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
44514,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2011/pcn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
44515,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2011/pcn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
44516,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2011/pcn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
44517,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2012/pcn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
44518,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2012/pcn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
44519,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2012/pcn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
44520,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2012/pcn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
44521,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2012/pcn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
44522,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2012/pcn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
44523,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2012/pcn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
44524,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2012/pcn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
44525,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2013/pcn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
44526,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2013/pcn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
44527,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2013/pcn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
44528,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2013/pcn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
44529,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2013/pcn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
44530,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2013/pcn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
44531,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2013/pcn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
44532,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2013/pcn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
44533,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2014/pcn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
44534,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2014/pcn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
44535,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2014/pcn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
44536,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2014/pcn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
44537,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2014/pcn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
44538,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2014/pcn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
44539,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2014/pcn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
44540,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2014/pcn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
44541,612,"PCN","Pitcairn Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2015/pcn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
44542,612,"PCN","Pitcairn Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2015/pcn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
44543,612,"PCN","Pitcairn Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2015/pcn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
44544,612,"PCN","Pitcairn Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2015/pcn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
44545,612,"PCN","Pitcairn Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2015/pcn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
44546,612,"PCN","Pitcairn Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2015/pcn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
44547,612,"PCN","Pitcairn Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2015/pcn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
44548,612,"PCN","Pitcairn Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Annual/2015/pcn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
44549,616,"POL","Poland","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2000/pol_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
44550,616,"POL","Poland","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2000/pol_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
44551,616,"POL","Poland","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2000/pol_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
44552,616,"POL","Poland","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2000/pol_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
44553,616,"POL","Poland","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2000/pol_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
44554,616,"POL","Poland","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2000/pol_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
44555,616,"POL","Poland","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2000/pol_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
44556,616,"POL","Poland","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2000/pol_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
44557,616,"POL","Poland","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2001/pol_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
44558,616,"POL","Poland","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2001/pol_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
44559,616,"POL","Poland","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2001/pol_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
44560,616,"POL","Poland","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2001/pol_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
44561,616,"POL","Poland","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2001/pol_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
44562,616,"POL","Poland","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2001/pol_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
44563,616,"POL","Poland","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2001/pol_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
44564,616,"POL","Poland","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2001/pol_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
44565,616,"POL","Poland","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2002/pol_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
44566,616,"POL","Poland","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2002/pol_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
44567,616,"POL","Poland","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2002/pol_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
44568,616,"POL","Poland","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2002/pol_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
44569,616,"POL","Poland","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2002/pol_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
44570,616,"POL","Poland","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2002/pol_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
44571,616,"POL","Poland","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2002/pol_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
44572,616,"POL","Poland","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2002/pol_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
44573,616,"POL","Poland","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2003/pol_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
44574,616,"POL","Poland","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2003/pol_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
44575,616,"POL","Poland","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2003/pol_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
44576,616,"POL","Poland","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2003/pol_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
44577,616,"POL","Poland","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2003/pol_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
44578,616,"POL","Poland","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2003/pol_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
44579,616,"POL","Poland","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2003/pol_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
44580,616,"POL","Poland","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2003/pol_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
44581,616,"POL","Poland","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2004/pol_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
44582,616,"POL","Poland","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2004/pol_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
44583,616,"POL","Poland","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2004/pol_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
44584,616,"POL","Poland","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2004/pol_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
44585,616,"POL","Poland","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2004/pol_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
44586,616,"POL","Poland","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2004/pol_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
44587,616,"POL","Poland","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2004/pol_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
44588,616,"POL","Poland","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2004/pol_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
44589,616,"POL","Poland","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2005/pol_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
44590,616,"POL","Poland","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2005/pol_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
44591,616,"POL","Poland","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2005/pol_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
44592,616,"POL","Poland","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2005/pol_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
44593,616,"POL","Poland","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2005/pol_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
44594,616,"POL","Poland","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2005/pol_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
44595,616,"POL","Poland","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2005/pol_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
44596,616,"POL","Poland","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2005/pol_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
44597,616,"POL","Poland","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2006/pol_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
44598,616,"POL","Poland","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2006/pol_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
44599,616,"POL","Poland","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2006/pol_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
44600,616,"POL","Poland","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2006/pol_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
44601,616,"POL","Poland","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2006/pol_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
44602,616,"POL","Poland","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2006/pol_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
44603,616,"POL","Poland","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2006/pol_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
44604,616,"POL","Poland","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2006/pol_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
44605,616,"POL","Poland","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2007/pol_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
44606,616,"POL","Poland","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2007/pol_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
44607,616,"POL","Poland","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2007/pol_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
44608,616,"POL","Poland","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2007/pol_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
44609,616,"POL","Poland","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2007/pol_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
44610,616,"POL","Poland","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2007/pol_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
44611,616,"POL","Poland","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2007/pol_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
44612,616,"POL","Poland","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2007/pol_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
44613,616,"POL","Poland","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2008/pol_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
44614,616,"POL","Poland","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2008/pol_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
44615,616,"POL","Poland","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2008/pol_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
44616,616,"POL","Poland","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2008/pol_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
44617,616,"POL","Poland","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2008/pol_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
44618,616,"POL","Poland","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2008/pol_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
44619,616,"POL","Poland","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2008/pol_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
44620,616,"POL","Poland","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2008/pol_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
44621,616,"POL","Poland","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2009/pol_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
44622,616,"POL","Poland","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2009/pol_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
44623,616,"POL","Poland","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2009/pol_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
44624,616,"POL","Poland","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2009/pol_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
44625,616,"POL","Poland","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2009/pol_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
44626,616,"POL","Poland","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2009/pol_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
44627,616,"POL","Poland","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2009/pol_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
44628,616,"POL","Poland","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2009/pol_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
44629,616,"POL","Poland","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2010/pol_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
44630,616,"POL","Poland","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2010/pol_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
44631,616,"POL","Poland","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2010/pol_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
44632,616,"POL","Poland","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2010/pol_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
44633,616,"POL","Poland","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2010/pol_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
44634,616,"POL","Poland","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2010/pol_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
44635,616,"POL","Poland","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2010/pol_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
44636,616,"POL","Poland","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2010/pol_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
44637,616,"POL","Poland","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2011/pol_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
44638,616,"POL","Poland","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2011/pol_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
44639,616,"POL","Poland","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2011/pol_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
44640,616,"POL","Poland","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2011/pol_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
44641,616,"POL","Poland","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2011/pol_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
44642,616,"POL","Poland","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2011/pol_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
44643,616,"POL","Poland","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2011/pol_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
44644,616,"POL","Poland","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2011/pol_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
44645,616,"POL","Poland","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2012/pol_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
44646,616,"POL","Poland","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2012/pol_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
44647,616,"POL","Poland","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2012/pol_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
44648,616,"POL","Poland","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2012/pol_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
44649,616,"POL","Poland","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2012/pol_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
44650,616,"POL","Poland","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2012/pol_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
44651,616,"POL","Poland","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2012/pol_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
44652,616,"POL","Poland","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2012/pol_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
44653,616,"POL","Poland","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2013/pol_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
44654,616,"POL","Poland","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2013/pol_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
44655,616,"POL","Poland","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2013/pol_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
44656,616,"POL","Poland","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2013/pol_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
44657,616,"POL","Poland","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2013/pol_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
44658,616,"POL","Poland","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2013/pol_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
44659,616,"POL","Poland","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2013/pol_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
44660,616,"POL","Poland","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2013/pol_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
44661,616,"POL","Poland","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2014/pol_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
44662,616,"POL","Poland","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2014/pol_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
44663,616,"POL","Poland","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2014/pol_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
44664,616,"POL","Poland","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2014/pol_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
44665,616,"POL","Poland","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2014/pol_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
44666,616,"POL","Poland","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2014/pol_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
44667,616,"POL","Poland","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2014/pol_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
44668,616,"POL","Poland","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2014/pol_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
44669,616,"POL","Poland","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2015/pol_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
44670,616,"POL","Poland","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2015/pol_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
44671,616,"POL","Poland","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2015/pol_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
44672,616,"POL","Poland","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2015/pol_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
44673,616,"POL","Poland","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2015/pol_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
44674,616,"POL","Poland","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2015/pol_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
44675,616,"POL","Poland","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2015/pol_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
44676,616,"POL","Poland","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Annual/2015/pol_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
44677,620,"PRT","Portugal","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2000/prt_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
44678,620,"PRT","Portugal","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2000/prt_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
44679,620,"PRT","Portugal","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2000/prt_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
44680,620,"PRT","Portugal","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2000/prt_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
44681,620,"PRT","Portugal","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2000/prt_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
44682,620,"PRT","Portugal","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2000/prt_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
44683,620,"PRT","Portugal","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2000/prt_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
44684,620,"PRT","Portugal","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2000/prt_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
44685,620,"PRT","Portugal","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2001/prt_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
44686,620,"PRT","Portugal","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2001/prt_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
44687,620,"PRT","Portugal","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2001/prt_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
44688,620,"PRT","Portugal","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2001/prt_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
44689,620,"PRT","Portugal","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2001/prt_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
44690,620,"PRT","Portugal","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2001/prt_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
44691,620,"PRT","Portugal","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2001/prt_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
44692,620,"PRT","Portugal","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2001/prt_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
44693,620,"PRT","Portugal","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2002/prt_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
44694,620,"PRT","Portugal","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2002/prt_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
44695,620,"PRT","Portugal","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2002/prt_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
44696,620,"PRT","Portugal","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2002/prt_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
44697,620,"PRT","Portugal","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2002/prt_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
44698,620,"PRT","Portugal","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2002/prt_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
44699,620,"PRT","Portugal","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2002/prt_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
44700,620,"PRT","Portugal","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2002/prt_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
44701,620,"PRT","Portugal","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2003/prt_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
44702,620,"PRT","Portugal","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2003/prt_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
44703,620,"PRT","Portugal","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2003/prt_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
44704,620,"PRT","Portugal","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2003/prt_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
44705,620,"PRT","Portugal","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2003/prt_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
44706,620,"PRT","Portugal","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2003/prt_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
44707,620,"PRT","Portugal","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2003/prt_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
44708,620,"PRT","Portugal","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2003/prt_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
44709,620,"PRT","Portugal","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2004/prt_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
44710,620,"PRT","Portugal","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2004/prt_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
44711,620,"PRT","Portugal","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2004/prt_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
44712,620,"PRT","Portugal","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2004/prt_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
44713,620,"PRT","Portugal","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2004/prt_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
44714,620,"PRT","Portugal","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2004/prt_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
44715,620,"PRT","Portugal","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2004/prt_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
44716,620,"PRT","Portugal","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2004/prt_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
44717,620,"PRT","Portugal","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2005/prt_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
44718,620,"PRT","Portugal","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2005/prt_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
44719,620,"PRT","Portugal","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2005/prt_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
44720,620,"PRT","Portugal","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2005/prt_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
44721,620,"PRT","Portugal","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2005/prt_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
44722,620,"PRT","Portugal","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2005/prt_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
44723,620,"PRT","Portugal","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2005/prt_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
44724,620,"PRT","Portugal","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2005/prt_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
44725,620,"PRT","Portugal","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2006/prt_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
44726,620,"PRT","Portugal","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2006/prt_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
44727,620,"PRT","Portugal","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2006/prt_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
44728,620,"PRT","Portugal","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2006/prt_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
44729,620,"PRT","Portugal","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2006/prt_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
44730,620,"PRT","Portugal","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2006/prt_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
44731,620,"PRT","Portugal","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2006/prt_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
44732,620,"PRT","Portugal","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2006/prt_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
44733,620,"PRT","Portugal","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2007/prt_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
44734,620,"PRT","Portugal","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2007/prt_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
44735,620,"PRT","Portugal","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2007/prt_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
44736,620,"PRT","Portugal","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2007/prt_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
44737,620,"PRT","Portugal","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2007/prt_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
44738,620,"PRT","Portugal","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2007/prt_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
44739,620,"PRT","Portugal","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2007/prt_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
44740,620,"PRT","Portugal","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2007/prt_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
44741,620,"PRT","Portugal","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2008/prt_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
44742,620,"PRT","Portugal","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2008/prt_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
44743,620,"PRT","Portugal","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2008/prt_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
44744,620,"PRT","Portugal","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2008/prt_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
44745,620,"PRT","Portugal","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2008/prt_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
44746,620,"PRT","Portugal","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2008/prt_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
44747,620,"PRT","Portugal","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2008/prt_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
44748,620,"PRT","Portugal","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2008/prt_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
44749,620,"PRT","Portugal","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2009/prt_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
44750,620,"PRT","Portugal","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2009/prt_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
44751,620,"PRT","Portugal","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2009/prt_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
44752,620,"PRT","Portugal","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2009/prt_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
44753,620,"PRT","Portugal","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2009/prt_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
44754,620,"PRT","Portugal","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2009/prt_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
44755,620,"PRT","Portugal","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2009/prt_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
44756,620,"PRT","Portugal","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2009/prt_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
44757,620,"PRT","Portugal","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2010/prt_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
44758,620,"PRT","Portugal","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2010/prt_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
44759,620,"PRT","Portugal","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2010/prt_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
44760,620,"PRT","Portugal","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2010/prt_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
44761,620,"PRT","Portugal","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2010/prt_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
44762,620,"PRT","Portugal","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2010/prt_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
44763,620,"PRT","Portugal","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2010/prt_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
44764,620,"PRT","Portugal","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2010/prt_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
44765,620,"PRT","Portugal","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2011/prt_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
44766,620,"PRT","Portugal","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2011/prt_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
44767,620,"PRT","Portugal","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2011/prt_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
44768,620,"PRT","Portugal","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2011/prt_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
44769,620,"PRT","Portugal","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2011/prt_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
44770,620,"PRT","Portugal","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2011/prt_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
44771,620,"PRT","Portugal","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2011/prt_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
44772,620,"PRT","Portugal","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2011/prt_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
44773,620,"PRT","Portugal","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2012/prt_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
44774,620,"PRT","Portugal","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2012/prt_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
44775,620,"PRT","Portugal","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2012/prt_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
44776,620,"PRT","Portugal","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2012/prt_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
44777,620,"PRT","Portugal","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2012/prt_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
44778,620,"PRT","Portugal","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2012/prt_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
44779,620,"PRT","Portugal","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2012/prt_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
44780,620,"PRT","Portugal","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2012/prt_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
44781,620,"PRT","Portugal","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2013/prt_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
44782,620,"PRT","Portugal","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2013/prt_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
44783,620,"PRT","Portugal","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2013/prt_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
44784,620,"PRT","Portugal","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2013/prt_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
44785,620,"PRT","Portugal","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2013/prt_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
44786,620,"PRT","Portugal","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2013/prt_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
44787,620,"PRT","Portugal","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2013/prt_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
44788,620,"PRT","Portugal","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2013/prt_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
44789,620,"PRT","Portugal","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2014/prt_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
44790,620,"PRT","Portugal","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2014/prt_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
44791,620,"PRT","Portugal","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2014/prt_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
44792,620,"PRT","Portugal","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2014/prt_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
44793,620,"PRT","Portugal","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2014/prt_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
44794,620,"PRT","Portugal","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2014/prt_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
44795,620,"PRT","Portugal","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2014/prt_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
44796,620,"PRT","Portugal","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2014/prt_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
44797,620,"PRT","Portugal","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2015/prt_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
44798,620,"PRT","Portugal","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2015/prt_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
44799,620,"PRT","Portugal","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2015/prt_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
44800,620,"PRT","Portugal","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2015/prt_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
44801,620,"PRT","Portugal","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2015/prt_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
44802,620,"PRT","Portugal","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2015/prt_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
44803,620,"PRT","Portugal","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2015/prt_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
44804,620,"PRT","Portugal","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Annual/2015/prt_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
44805,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2000/gnb_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
44806,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2000/gnb_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
44807,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2000/gnb_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
44808,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2000/gnb_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
44809,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2000/gnb_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
44810,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2000/gnb_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
44811,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2000/gnb_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
44812,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2000/gnb_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
44813,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2001/gnb_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
44814,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2001/gnb_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
44815,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2001/gnb_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
44816,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2001/gnb_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
44817,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2001/gnb_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
44818,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2001/gnb_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
44819,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2001/gnb_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
44820,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2001/gnb_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
44821,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2002/gnb_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
44822,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2002/gnb_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
44823,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2002/gnb_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
44824,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2002/gnb_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
44825,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2002/gnb_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
44826,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2002/gnb_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
44827,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2002/gnb_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
44828,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2002/gnb_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
44829,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2003/gnb_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
44830,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2003/gnb_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
44831,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2003/gnb_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
44832,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2003/gnb_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
44833,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2003/gnb_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
44834,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2003/gnb_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
44835,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2003/gnb_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
44836,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2003/gnb_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
44837,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2004/gnb_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
44838,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2004/gnb_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
44839,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2004/gnb_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
44840,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2004/gnb_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
44841,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2004/gnb_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
44842,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2004/gnb_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
44843,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2004/gnb_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
44844,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2004/gnb_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
44845,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2005/gnb_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
44846,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2005/gnb_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
44847,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2005/gnb_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
44848,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2005/gnb_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
44849,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2005/gnb_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
44850,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2005/gnb_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
44851,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2005/gnb_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
44852,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2005/gnb_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
44853,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2006/gnb_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
44854,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2006/gnb_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
44855,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2006/gnb_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
44856,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2006/gnb_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
44857,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2006/gnb_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
44858,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2006/gnb_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
44859,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2006/gnb_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
44860,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2006/gnb_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
44861,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2007/gnb_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
44862,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2007/gnb_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
44863,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2007/gnb_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
44864,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2007/gnb_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
44865,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2007/gnb_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
44866,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2007/gnb_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
44867,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2007/gnb_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
44868,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2007/gnb_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
44869,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2008/gnb_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
44870,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2008/gnb_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
44871,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2008/gnb_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
44872,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2008/gnb_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
44873,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2008/gnb_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
44874,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2008/gnb_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
44875,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2008/gnb_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
44876,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2008/gnb_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
44877,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2009/gnb_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
44878,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2009/gnb_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
44879,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2009/gnb_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
44880,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2009/gnb_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
44881,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2009/gnb_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
44882,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2009/gnb_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
44883,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2009/gnb_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
44884,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2009/gnb_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
44885,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2010/gnb_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
44886,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2010/gnb_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
44887,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2010/gnb_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
44888,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2010/gnb_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
44889,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2010/gnb_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
44890,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2010/gnb_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
44891,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2010/gnb_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
44892,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2010/gnb_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
44893,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2011/gnb_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
44894,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2011/gnb_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
44895,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2011/gnb_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
44896,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2011/gnb_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
44897,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2011/gnb_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
44898,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2011/gnb_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
44899,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2011/gnb_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
44900,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2011/gnb_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
44901,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2012/gnb_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
44902,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2012/gnb_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
44903,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2012/gnb_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
44904,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2012/gnb_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
44905,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2012/gnb_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
44906,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2012/gnb_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
44907,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2012/gnb_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
44908,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2012/gnb_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
44909,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2013/gnb_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
44910,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2013/gnb_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
44911,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2013/gnb_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
44912,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2013/gnb_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
44913,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2013/gnb_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
44914,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2013/gnb_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
44915,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2013/gnb_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
44916,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2013/gnb_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
44917,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2014/gnb_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
44918,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2014/gnb_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
44919,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2014/gnb_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
44920,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2014/gnb_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
44921,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2014/gnb_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
44922,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2014/gnb_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
44923,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2014/gnb_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
44924,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2014/gnb_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
44925,624,"GNB","Guinea-Bissau","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2015/gnb_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
44926,624,"GNB","Guinea-Bissau","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2015/gnb_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
44927,624,"GNB","Guinea-Bissau","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2015/gnb_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
44928,624,"GNB","Guinea-Bissau","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2015/gnb_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
44929,624,"GNB","Guinea-Bissau","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2015/gnb_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
44930,624,"GNB","Guinea-Bissau","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2015/gnb_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
44931,624,"GNB","Guinea-Bissau","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2015/gnb_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
44932,624,"GNB","Guinea-Bissau","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Annual/2015/gnb_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
44933,626,"TLS","East Timor","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2000/tls_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
44934,626,"TLS","East Timor","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2000/tls_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
44935,626,"TLS","East Timor","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2000/tls_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
44936,626,"TLS","East Timor","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2000/tls_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
44937,626,"TLS","East Timor","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2000/tls_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
44938,626,"TLS","East Timor","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2000/tls_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
44939,626,"TLS","East Timor","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2000/tls_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
44940,626,"TLS","East Timor","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2000/tls_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
44941,626,"TLS","East Timor","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2001/tls_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
44942,626,"TLS","East Timor","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2001/tls_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
44943,626,"TLS","East Timor","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2001/tls_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
44944,626,"TLS","East Timor","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2001/tls_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
44945,626,"TLS","East Timor","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2001/tls_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
44946,626,"TLS","East Timor","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2001/tls_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
44947,626,"TLS","East Timor","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2001/tls_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
44948,626,"TLS","East Timor","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2001/tls_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
44949,626,"TLS","East Timor","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2002/tls_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
44950,626,"TLS","East Timor","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2002/tls_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
44951,626,"TLS","East Timor","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2002/tls_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
44952,626,"TLS","East Timor","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2002/tls_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
44953,626,"TLS","East Timor","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2002/tls_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
44954,626,"TLS","East Timor","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2002/tls_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
44955,626,"TLS","East Timor","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2002/tls_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
44956,626,"TLS","East Timor","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2002/tls_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
44957,626,"TLS","East Timor","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2003/tls_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
44958,626,"TLS","East Timor","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2003/tls_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
44959,626,"TLS","East Timor","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2003/tls_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
44960,626,"TLS","East Timor","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2003/tls_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
44961,626,"TLS","East Timor","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2003/tls_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
44962,626,"TLS","East Timor","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2003/tls_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
44963,626,"TLS","East Timor","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2003/tls_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
44964,626,"TLS","East Timor","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2003/tls_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
44965,626,"TLS","East Timor","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2004/tls_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
44966,626,"TLS","East Timor","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2004/tls_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
44967,626,"TLS","East Timor","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2004/tls_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
44968,626,"TLS","East Timor","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2004/tls_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
44969,626,"TLS","East Timor","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2004/tls_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
44970,626,"TLS","East Timor","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2004/tls_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
44971,626,"TLS","East Timor","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2004/tls_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
44972,626,"TLS","East Timor","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2004/tls_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
44973,626,"TLS","East Timor","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2005/tls_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
44974,626,"TLS","East Timor","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2005/tls_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
44975,626,"TLS","East Timor","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2005/tls_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
44976,626,"TLS","East Timor","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2005/tls_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
44977,626,"TLS","East Timor","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2005/tls_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
44978,626,"TLS","East Timor","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2005/tls_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
44979,626,"TLS","East Timor","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2005/tls_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
44980,626,"TLS","East Timor","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2005/tls_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
44981,626,"TLS","East Timor","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2006/tls_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
44982,626,"TLS","East Timor","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2006/tls_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
44983,626,"TLS","East Timor","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2006/tls_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
44984,626,"TLS","East Timor","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2006/tls_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
44985,626,"TLS","East Timor","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2006/tls_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
44986,626,"TLS","East Timor","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2006/tls_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
44987,626,"TLS","East Timor","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2006/tls_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
44988,626,"TLS","East Timor","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2006/tls_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
44989,626,"TLS","East Timor","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2007/tls_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
44990,626,"TLS","East Timor","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2007/tls_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
44991,626,"TLS","East Timor","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2007/tls_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
44992,626,"TLS","East Timor","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2007/tls_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
44993,626,"TLS","East Timor","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2007/tls_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
44994,626,"TLS","East Timor","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2007/tls_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
44995,626,"TLS","East Timor","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2007/tls_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
44996,626,"TLS","East Timor","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2007/tls_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
44997,626,"TLS","East Timor","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2008/tls_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
44998,626,"TLS","East Timor","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2008/tls_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
44999,626,"TLS","East Timor","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2008/tls_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
45000,626,"TLS","East Timor","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2008/tls_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
45001,626,"TLS","East Timor","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2008/tls_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
45002,626,"TLS","East Timor","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2008/tls_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
45003,626,"TLS","East Timor","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2008/tls_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
45004,626,"TLS","East Timor","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2008/tls_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
45005,626,"TLS","East Timor","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2009/tls_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
45006,626,"TLS","East Timor","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2009/tls_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
45007,626,"TLS","East Timor","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2009/tls_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
45008,626,"TLS","East Timor","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2009/tls_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
45009,626,"TLS","East Timor","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2009/tls_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
45010,626,"TLS","East Timor","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2009/tls_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
45011,626,"TLS","East Timor","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2009/tls_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
45012,626,"TLS","East Timor","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2009/tls_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
45013,626,"TLS","East Timor","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2010/tls_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
45014,626,"TLS","East Timor","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2010/tls_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
45015,626,"TLS","East Timor","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2010/tls_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
45016,626,"TLS","East Timor","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2010/tls_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
45017,626,"TLS","East Timor","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2010/tls_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
45018,626,"TLS","East Timor","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2010/tls_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
45019,626,"TLS","East Timor","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2010/tls_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
45020,626,"TLS","East Timor","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2010/tls_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
45021,626,"TLS","East Timor","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2011/tls_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
45022,626,"TLS","East Timor","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2011/tls_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
45023,626,"TLS","East Timor","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2011/tls_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
45024,626,"TLS","East Timor","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2011/tls_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
45025,626,"TLS","East Timor","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2011/tls_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
45026,626,"TLS","East Timor","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2011/tls_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
45027,626,"TLS","East Timor","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2011/tls_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
45028,626,"TLS","East Timor","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2011/tls_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
45029,626,"TLS","East Timor","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2012/tls_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
45030,626,"TLS","East Timor","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2012/tls_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
45031,626,"TLS","East Timor","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2012/tls_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
45032,626,"TLS","East Timor","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2012/tls_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
45033,626,"TLS","East Timor","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2012/tls_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
45034,626,"TLS","East Timor","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2012/tls_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
45035,626,"TLS","East Timor","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2012/tls_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
45036,626,"TLS","East Timor","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2012/tls_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
45037,626,"TLS","East Timor","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2013/tls_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
45038,626,"TLS","East Timor","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2013/tls_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
45039,626,"TLS","East Timor","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2013/tls_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
45040,626,"TLS","East Timor","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2013/tls_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
45041,626,"TLS","East Timor","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2013/tls_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
45042,626,"TLS","East Timor","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2013/tls_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
45043,626,"TLS","East Timor","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2013/tls_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
45044,626,"TLS","East Timor","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2013/tls_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
45045,626,"TLS","East Timor","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2014/tls_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
45046,626,"TLS","East Timor","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2014/tls_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
45047,626,"TLS","East Timor","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2014/tls_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
45048,626,"TLS","East Timor","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2014/tls_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
45049,626,"TLS","East Timor","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2014/tls_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
45050,626,"TLS","East Timor","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2014/tls_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
45051,626,"TLS","East Timor","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2014/tls_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
45052,626,"TLS","East Timor","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2014/tls_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
45053,626,"TLS","East Timor","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2015/tls_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
45054,626,"TLS","East Timor","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2015/tls_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
45055,626,"TLS","East Timor","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2015/tls_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
45056,626,"TLS","East Timor","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2015/tls_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
45057,626,"TLS","East Timor","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2015/tls_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
45058,626,"TLS","East Timor","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2015/tls_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
45059,626,"TLS","East Timor","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2015/tls_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
45060,626,"TLS","East Timor","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Annual/2015/tls_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
45061,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2000/pri_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
45062,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2000/pri_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
45063,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2000/pri_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
45064,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2000/pri_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
45065,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2000/pri_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
45066,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2000/pri_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
45067,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2000/pri_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
45068,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2000/pri_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
45069,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2001/pri_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
45070,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2001/pri_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
45071,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2001/pri_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
45072,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2001/pri_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
45073,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2001/pri_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
45074,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2001/pri_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
45075,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2001/pri_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
45076,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2001/pri_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
45077,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2002/pri_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
45078,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2002/pri_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
45079,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2002/pri_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
45080,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2002/pri_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
45081,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2002/pri_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
45082,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2002/pri_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
45083,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2002/pri_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
45084,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2002/pri_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
45085,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2003/pri_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
45086,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2003/pri_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
45087,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2003/pri_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
45088,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2003/pri_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
45089,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2003/pri_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
45090,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2003/pri_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
45091,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2003/pri_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
45092,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2003/pri_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
45093,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2004/pri_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
45094,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2004/pri_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
45095,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2004/pri_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
45096,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2004/pri_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
45097,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2004/pri_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
45098,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2004/pri_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
45099,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2004/pri_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
45100,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2004/pri_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
45101,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2005/pri_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
45102,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2005/pri_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
45103,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2005/pri_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
45104,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2005/pri_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
45105,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2005/pri_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
45106,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2005/pri_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
45107,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2005/pri_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
45108,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2005/pri_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
45109,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2006/pri_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
45110,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2006/pri_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
45111,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2006/pri_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
45112,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2006/pri_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
45113,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2006/pri_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
45114,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2006/pri_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
45115,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2006/pri_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
45116,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2006/pri_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
45117,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2007/pri_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
45118,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2007/pri_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
45119,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2007/pri_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
45120,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2007/pri_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
45121,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2007/pri_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
45122,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2007/pri_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
45123,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2007/pri_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
45124,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2007/pri_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
45125,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2008/pri_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
45126,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2008/pri_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
45127,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2008/pri_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
45128,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2008/pri_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
45129,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2008/pri_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
45130,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2008/pri_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
45131,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2008/pri_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
45132,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2008/pri_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
45133,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2009/pri_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
45134,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2009/pri_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
45135,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2009/pri_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
45136,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2009/pri_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
45137,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2009/pri_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
45138,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2009/pri_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
45139,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2009/pri_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
45140,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2009/pri_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
45141,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2010/pri_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
45142,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2010/pri_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
45143,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2010/pri_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
45144,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2010/pri_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
45145,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2010/pri_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
45146,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2010/pri_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
45147,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2010/pri_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
45148,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2010/pri_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
45149,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2011/pri_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
45150,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2011/pri_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
45151,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2011/pri_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
45152,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2011/pri_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
45153,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2011/pri_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
45154,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2011/pri_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
45155,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2011/pri_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
45156,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2011/pri_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
45157,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2012/pri_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
45158,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2012/pri_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
45159,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2012/pri_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
45160,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2012/pri_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
45161,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2012/pri_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
45162,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2012/pri_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
45163,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2012/pri_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
45164,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2012/pri_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
45165,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2013/pri_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
45166,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2013/pri_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
45167,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2013/pri_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
45168,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2013/pri_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
45169,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2013/pri_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
45170,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2013/pri_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
45171,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2013/pri_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
45172,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2013/pri_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
45173,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2014/pri_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
45174,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2014/pri_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
45175,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2014/pri_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
45176,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2014/pri_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
45177,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2014/pri_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
45178,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2014/pri_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
45179,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2014/pri_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
45180,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2014/pri_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
45181,630,"PRI","Puerto Rico","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2015/pri_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
45182,630,"PRI","Puerto Rico","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2015/pri_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
45183,630,"PRI","Puerto Rico","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2015/pri_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
45184,630,"PRI","Puerto Rico","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2015/pri_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
45185,630,"PRI","Puerto Rico","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2015/pri_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
45186,630,"PRI","Puerto Rico","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2015/pri_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
45187,630,"PRI","Puerto Rico","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2015/pri_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
45188,630,"PRI","Puerto Rico","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Annual/2015/pri_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
45189,634,"QAT","Qatar","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2000/qat_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
45190,634,"QAT","Qatar","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2000/qat_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
45191,634,"QAT","Qatar","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2000/qat_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
45192,634,"QAT","Qatar","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2000/qat_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
45193,634,"QAT","Qatar","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2000/qat_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
45194,634,"QAT","Qatar","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2000/qat_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
45195,634,"QAT","Qatar","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2000/qat_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
45196,634,"QAT","Qatar","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2000/qat_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
45197,634,"QAT","Qatar","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2001/qat_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
45198,634,"QAT","Qatar","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2001/qat_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
45199,634,"QAT","Qatar","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2001/qat_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
45200,634,"QAT","Qatar","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2001/qat_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
45201,634,"QAT","Qatar","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2001/qat_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
45202,634,"QAT","Qatar","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2001/qat_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
45203,634,"QAT","Qatar","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2001/qat_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
45204,634,"QAT","Qatar","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2001/qat_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
45205,634,"QAT","Qatar","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2002/qat_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
45206,634,"QAT","Qatar","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2002/qat_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
45207,634,"QAT","Qatar","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2002/qat_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
45208,634,"QAT","Qatar","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2002/qat_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
45209,634,"QAT","Qatar","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2002/qat_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
45210,634,"QAT","Qatar","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2002/qat_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
45211,634,"QAT","Qatar","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2002/qat_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
45212,634,"QAT","Qatar","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2002/qat_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
45213,634,"QAT","Qatar","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2003/qat_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
45214,634,"QAT","Qatar","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2003/qat_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
45215,634,"QAT","Qatar","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2003/qat_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
45216,634,"QAT","Qatar","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2003/qat_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
45217,634,"QAT","Qatar","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2003/qat_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
45218,634,"QAT","Qatar","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2003/qat_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
45219,634,"QAT","Qatar","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2003/qat_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
45220,634,"QAT","Qatar","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2003/qat_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
45221,634,"QAT","Qatar","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2004/qat_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
45222,634,"QAT","Qatar","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2004/qat_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
45223,634,"QAT","Qatar","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2004/qat_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
45224,634,"QAT","Qatar","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2004/qat_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
45225,634,"QAT","Qatar","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2004/qat_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
45226,634,"QAT","Qatar","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2004/qat_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
45227,634,"QAT","Qatar","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2004/qat_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
45228,634,"QAT","Qatar","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2004/qat_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
45229,634,"QAT","Qatar","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2005/qat_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
45230,634,"QAT","Qatar","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2005/qat_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
45231,634,"QAT","Qatar","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2005/qat_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
45232,634,"QAT","Qatar","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2005/qat_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
45233,634,"QAT","Qatar","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2005/qat_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
45234,634,"QAT","Qatar","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2005/qat_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
45235,634,"QAT","Qatar","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2005/qat_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
45236,634,"QAT","Qatar","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2005/qat_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
45237,634,"QAT","Qatar","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2006/qat_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
45238,634,"QAT","Qatar","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2006/qat_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
45239,634,"QAT","Qatar","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2006/qat_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
45240,634,"QAT","Qatar","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2006/qat_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
45241,634,"QAT","Qatar","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2006/qat_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
45242,634,"QAT","Qatar","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2006/qat_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
45243,634,"QAT","Qatar","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2006/qat_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
45244,634,"QAT","Qatar","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2006/qat_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
45245,634,"QAT","Qatar","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2007/qat_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
45246,634,"QAT","Qatar","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2007/qat_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
45247,634,"QAT","Qatar","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2007/qat_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
45248,634,"QAT","Qatar","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2007/qat_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
45249,634,"QAT","Qatar","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2007/qat_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
45250,634,"QAT","Qatar","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2007/qat_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
45251,634,"QAT","Qatar","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2007/qat_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
45252,634,"QAT","Qatar","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2007/qat_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
45253,634,"QAT","Qatar","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2008/qat_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
45254,634,"QAT","Qatar","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2008/qat_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
45255,634,"QAT","Qatar","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2008/qat_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
45256,634,"QAT","Qatar","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2008/qat_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
45257,634,"QAT","Qatar","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2008/qat_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
45258,634,"QAT","Qatar","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2008/qat_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
45259,634,"QAT","Qatar","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2008/qat_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
45260,634,"QAT","Qatar","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2008/qat_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
45261,634,"QAT","Qatar","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2009/qat_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
45262,634,"QAT","Qatar","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2009/qat_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
45263,634,"QAT","Qatar","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2009/qat_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
45264,634,"QAT","Qatar","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2009/qat_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
45265,634,"QAT","Qatar","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2009/qat_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
45266,634,"QAT","Qatar","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2009/qat_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
45267,634,"QAT","Qatar","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2009/qat_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
45268,634,"QAT","Qatar","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2009/qat_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
45269,634,"QAT","Qatar","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2010/qat_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
45270,634,"QAT","Qatar","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2010/qat_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
45271,634,"QAT","Qatar","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2010/qat_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
45272,634,"QAT","Qatar","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2010/qat_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
45273,634,"QAT","Qatar","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2010/qat_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
45274,634,"QAT","Qatar","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2010/qat_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
45275,634,"QAT","Qatar","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2010/qat_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
45276,634,"QAT","Qatar","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2010/qat_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
45277,634,"QAT","Qatar","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2011/qat_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
45278,634,"QAT","Qatar","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2011/qat_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
45279,634,"QAT","Qatar","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2011/qat_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
45280,634,"QAT","Qatar","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2011/qat_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
45281,634,"QAT","Qatar","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2011/qat_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
45282,634,"QAT","Qatar","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2011/qat_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
45283,634,"QAT","Qatar","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2011/qat_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
45284,634,"QAT","Qatar","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2011/qat_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
45285,634,"QAT","Qatar","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2012/qat_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
45286,634,"QAT","Qatar","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2012/qat_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
45287,634,"QAT","Qatar","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2012/qat_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
45288,634,"QAT","Qatar","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2012/qat_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
45289,634,"QAT","Qatar","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2012/qat_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
45290,634,"QAT","Qatar","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2012/qat_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
45291,634,"QAT","Qatar","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2012/qat_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
45292,634,"QAT","Qatar","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2012/qat_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
45293,634,"QAT","Qatar","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2013/qat_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
45294,634,"QAT","Qatar","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2013/qat_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
45295,634,"QAT","Qatar","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2013/qat_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
45296,634,"QAT","Qatar","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2013/qat_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
45297,634,"QAT","Qatar","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2013/qat_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
45298,634,"QAT","Qatar","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2013/qat_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
45299,634,"QAT","Qatar","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2013/qat_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
45300,634,"QAT","Qatar","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2013/qat_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
45301,634,"QAT","Qatar","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2014/qat_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
45302,634,"QAT","Qatar","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2014/qat_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
45303,634,"QAT","Qatar","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2014/qat_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
45304,634,"QAT","Qatar","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2014/qat_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
45305,634,"QAT","Qatar","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2014/qat_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
45306,634,"QAT","Qatar","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2014/qat_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
45307,634,"QAT","Qatar","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2014/qat_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
45308,634,"QAT","Qatar","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2014/qat_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
45309,634,"QAT","Qatar","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2015/qat_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
45310,634,"QAT","Qatar","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2015/qat_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
45311,634,"QAT","Qatar","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2015/qat_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
45312,634,"QAT","Qatar","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2015/qat_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
45313,634,"QAT","Qatar","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2015/qat_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
45314,634,"QAT","Qatar","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2015/qat_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
45315,634,"QAT","Qatar","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2015/qat_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
45316,634,"QAT","Qatar","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Annual/2015/qat_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
45317,638,"REU","Reunion","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2000/reu_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
45318,638,"REU","Reunion","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2000/reu_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
45319,638,"REU","Reunion","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2000/reu_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
45320,638,"REU","Reunion","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2000/reu_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
45321,638,"REU","Reunion","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2000/reu_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
45322,638,"REU","Reunion","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2000/reu_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
45323,638,"REU","Reunion","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2000/reu_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
45324,638,"REU","Reunion","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2000/reu_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
45325,638,"REU","Reunion","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2001/reu_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
45326,638,"REU","Reunion","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2001/reu_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
45327,638,"REU","Reunion","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2001/reu_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
45328,638,"REU","Reunion","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2001/reu_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
45329,638,"REU","Reunion","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2001/reu_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
45330,638,"REU","Reunion","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2001/reu_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
45331,638,"REU","Reunion","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2001/reu_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
45332,638,"REU","Reunion","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2001/reu_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
45333,638,"REU","Reunion","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2002/reu_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
45334,638,"REU","Reunion","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2002/reu_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
45335,638,"REU","Reunion","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2002/reu_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
45336,638,"REU","Reunion","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2002/reu_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
45337,638,"REU","Reunion","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2002/reu_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
45338,638,"REU","Reunion","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2002/reu_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
45339,638,"REU","Reunion","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2002/reu_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
45340,638,"REU","Reunion","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2002/reu_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
45341,638,"REU","Reunion","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2003/reu_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
45342,638,"REU","Reunion","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2003/reu_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
45343,638,"REU","Reunion","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2003/reu_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
45344,638,"REU","Reunion","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2003/reu_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
45345,638,"REU","Reunion","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2003/reu_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
45346,638,"REU","Reunion","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2003/reu_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
45347,638,"REU","Reunion","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2003/reu_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
45348,638,"REU","Reunion","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2003/reu_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
45349,638,"REU","Reunion","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2004/reu_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
45350,638,"REU","Reunion","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2004/reu_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
45351,638,"REU","Reunion","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2004/reu_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
45352,638,"REU","Reunion","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2004/reu_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
45353,638,"REU","Reunion","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2004/reu_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
45354,638,"REU","Reunion","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2004/reu_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
45355,638,"REU","Reunion","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2004/reu_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
45356,638,"REU","Reunion","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2004/reu_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
45357,638,"REU","Reunion","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2005/reu_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
45358,638,"REU","Reunion","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2005/reu_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
45359,638,"REU","Reunion","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2005/reu_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
45360,638,"REU","Reunion","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2005/reu_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
45361,638,"REU","Reunion","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2005/reu_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
45362,638,"REU","Reunion","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2005/reu_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
45363,638,"REU","Reunion","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2005/reu_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
45364,638,"REU","Reunion","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2005/reu_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
45365,638,"REU","Reunion","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2006/reu_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
45366,638,"REU","Reunion","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2006/reu_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
45367,638,"REU","Reunion","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2006/reu_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
45368,638,"REU","Reunion","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2006/reu_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
45369,638,"REU","Reunion","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2006/reu_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
45370,638,"REU","Reunion","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2006/reu_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
45371,638,"REU","Reunion","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2006/reu_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
45372,638,"REU","Reunion","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2006/reu_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
45373,638,"REU","Reunion","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2007/reu_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
45374,638,"REU","Reunion","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2007/reu_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
45375,638,"REU","Reunion","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2007/reu_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
45376,638,"REU","Reunion","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2007/reu_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
45377,638,"REU","Reunion","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2007/reu_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
45378,638,"REU","Reunion","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2007/reu_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
45379,638,"REU","Reunion","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2007/reu_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
45380,638,"REU","Reunion","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2007/reu_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
45381,638,"REU","Reunion","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2008/reu_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
45382,638,"REU","Reunion","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2008/reu_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
45383,638,"REU","Reunion","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2008/reu_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
45384,638,"REU","Reunion","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2008/reu_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
45385,638,"REU","Reunion","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2008/reu_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
45386,638,"REU","Reunion","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2008/reu_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
45387,638,"REU","Reunion","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2008/reu_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
45388,638,"REU","Reunion","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2008/reu_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
45389,638,"REU","Reunion","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2009/reu_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
45390,638,"REU","Reunion","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2009/reu_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
45391,638,"REU","Reunion","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2009/reu_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
45392,638,"REU","Reunion","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2009/reu_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
45393,638,"REU","Reunion","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2009/reu_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
45394,638,"REU","Reunion","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2009/reu_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
45395,638,"REU","Reunion","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2009/reu_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
45396,638,"REU","Reunion","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2009/reu_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
45397,638,"REU","Reunion","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2010/reu_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
45398,638,"REU","Reunion","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2010/reu_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
45399,638,"REU","Reunion","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2010/reu_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
45400,638,"REU","Reunion","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2010/reu_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
45401,638,"REU","Reunion","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2010/reu_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
45402,638,"REU","Reunion","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2010/reu_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
45403,638,"REU","Reunion","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2010/reu_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
45404,638,"REU","Reunion","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2010/reu_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
45405,638,"REU","Reunion","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2011/reu_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
45406,638,"REU","Reunion","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2011/reu_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
45407,638,"REU","Reunion","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2011/reu_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
45408,638,"REU","Reunion","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2011/reu_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
45409,638,"REU","Reunion","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2011/reu_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
45410,638,"REU","Reunion","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2011/reu_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
45411,638,"REU","Reunion","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2011/reu_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
45412,638,"REU","Reunion","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2011/reu_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
45413,638,"REU","Reunion","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2012/reu_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
45414,638,"REU","Reunion","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2012/reu_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
45415,638,"REU","Reunion","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2012/reu_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
45416,638,"REU","Reunion","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2012/reu_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
45417,638,"REU","Reunion","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2012/reu_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
45418,638,"REU","Reunion","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2012/reu_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
45419,638,"REU","Reunion","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2012/reu_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
45420,638,"REU","Reunion","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2012/reu_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
45421,638,"REU","Reunion","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2013/reu_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
45422,638,"REU","Reunion","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2013/reu_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
45423,638,"REU","Reunion","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2013/reu_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
45424,638,"REU","Reunion","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2013/reu_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
45425,638,"REU","Reunion","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2013/reu_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
45426,638,"REU","Reunion","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2013/reu_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
45427,638,"REU","Reunion","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2013/reu_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
45428,638,"REU","Reunion","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2013/reu_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
45429,638,"REU","Reunion","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2014/reu_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
45430,638,"REU","Reunion","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2014/reu_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
45431,638,"REU","Reunion","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2014/reu_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
45432,638,"REU","Reunion","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2014/reu_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
45433,638,"REU","Reunion","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2014/reu_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
45434,638,"REU","Reunion","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2014/reu_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
45435,638,"REU","Reunion","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2014/reu_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
45436,638,"REU","Reunion","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2014/reu_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
45437,638,"REU","Reunion","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2015/reu_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
45438,638,"REU","Reunion","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2015/reu_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
45439,638,"REU","Reunion","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2015/reu_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
45440,638,"REU","Reunion","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2015/reu_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
45441,638,"REU","Reunion","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2015/reu_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
45442,638,"REU","Reunion","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2015/reu_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
45443,638,"REU","Reunion","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2015/reu_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
45444,638,"REU","Reunion","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Annual/2015/reu_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
45445,642,"ROU","Romania","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2000/rou_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
45446,642,"ROU","Romania","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2000/rou_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
45447,642,"ROU","Romania","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2000/rou_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
45448,642,"ROU","Romania","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2000/rou_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
45449,642,"ROU","Romania","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2000/rou_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
45450,642,"ROU","Romania","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2000/rou_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
45451,642,"ROU","Romania","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2000/rou_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
45452,642,"ROU","Romania","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2000/rou_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
45453,642,"ROU","Romania","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2001/rou_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
45454,642,"ROU","Romania","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2001/rou_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
45455,642,"ROU","Romania","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2001/rou_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
45456,642,"ROU","Romania","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2001/rou_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
45457,642,"ROU","Romania","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2001/rou_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
45458,642,"ROU","Romania","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2001/rou_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
45459,642,"ROU","Romania","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2001/rou_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
45460,642,"ROU","Romania","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2001/rou_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
45461,642,"ROU","Romania","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2002/rou_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
45462,642,"ROU","Romania","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2002/rou_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
45463,642,"ROU","Romania","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2002/rou_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
45464,642,"ROU","Romania","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2002/rou_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
45465,642,"ROU","Romania","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2002/rou_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
45466,642,"ROU","Romania","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2002/rou_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
45467,642,"ROU","Romania","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2002/rou_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
45468,642,"ROU","Romania","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2002/rou_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
45469,642,"ROU","Romania","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2003/rou_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
45470,642,"ROU","Romania","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2003/rou_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
45471,642,"ROU","Romania","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2003/rou_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
45472,642,"ROU","Romania","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2003/rou_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
45473,642,"ROU","Romania","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2003/rou_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
45474,642,"ROU","Romania","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2003/rou_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
45475,642,"ROU","Romania","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2003/rou_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
45476,642,"ROU","Romania","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2003/rou_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
45477,642,"ROU","Romania","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2004/rou_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
45478,642,"ROU","Romania","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2004/rou_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
45479,642,"ROU","Romania","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2004/rou_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
45480,642,"ROU","Romania","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2004/rou_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
45481,642,"ROU","Romania","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2004/rou_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
45482,642,"ROU","Romania","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2004/rou_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
45483,642,"ROU","Romania","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2004/rou_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
45484,642,"ROU","Romania","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2004/rou_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
45485,642,"ROU","Romania","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2005/rou_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
45486,642,"ROU","Romania","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2005/rou_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
45487,642,"ROU","Romania","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2005/rou_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
45488,642,"ROU","Romania","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2005/rou_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
45489,642,"ROU","Romania","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2005/rou_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
45490,642,"ROU","Romania","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2005/rou_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
45491,642,"ROU","Romania","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2005/rou_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
45492,642,"ROU","Romania","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2005/rou_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
45493,642,"ROU","Romania","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2006/rou_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
45494,642,"ROU","Romania","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2006/rou_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
45495,642,"ROU","Romania","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2006/rou_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
45496,642,"ROU","Romania","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2006/rou_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
45497,642,"ROU","Romania","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2006/rou_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
45498,642,"ROU","Romania","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2006/rou_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
45499,642,"ROU","Romania","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2006/rou_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
45500,642,"ROU","Romania","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2006/rou_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
45501,642,"ROU","Romania","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2007/rou_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
45502,642,"ROU","Romania","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2007/rou_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
45503,642,"ROU","Romania","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2007/rou_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
45504,642,"ROU","Romania","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2007/rou_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
45505,642,"ROU","Romania","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2007/rou_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
45506,642,"ROU","Romania","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2007/rou_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
45507,642,"ROU","Romania","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2007/rou_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
45508,642,"ROU","Romania","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2007/rou_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
45509,642,"ROU","Romania","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2008/rou_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
45510,642,"ROU","Romania","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2008/rou_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
45511,642,"ROU","Romania","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2008/rou_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
45512,642,"ROU","Romania","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2008/rou_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
45513,642,"ROU","Romania","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2008/rou_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
45514,642,"ROU","Romania","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2008/rou_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
45515,642,"ROU","Romania","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2008/rou_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
45516,642,"ROU","Romania","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2008/rou_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
45517,642,"ROU","Romania","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2009/rou_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
45518,642,"ROU","Romania","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2009/rou_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
45519,642,"ROU","Romania","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2009/rou_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
45520,642,"ROU","Romania","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2009/rou_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
45521,642,"ROU","Romania","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2009/rou_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
45522,642,"ROU","Romania","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2009/rou_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
45523,642,"ROU","Romania","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2009/rou_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
45524,642,"ROU","Romania","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2009/rou_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
45525,642,"ROU","Romania","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2010/rou_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
45526,642,"ROU","Romania","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2010/rou_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
45527,642,"ROU","Romania","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2010/rou_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
45528,642,"ROU","Romania","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2010/rou_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
45529,642,"ROU","Romania","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2010/rou_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
45530,642,"ROU","Romania","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2010/rou_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
45531,642,"ROU","Romania","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2010/rou_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
45532,642,"ROU","Romania","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2010/rou_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
45533,642,"ROU","Romania","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2011/rou_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
45534,642,"ROU","Romania","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2011/rou_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
45535,642,"ROU","Romania","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2011/rou_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
45536,642,"ROU","Romania","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2011/rou_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
45537,642,"ROU","Romania","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2011/rou_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
45538,642,"ROU","Romania","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2011/rou_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
45539,642,"ROU","Romania","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2011/rou_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
45540,642,"ROU","Romania","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2011/rou_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
45541,642,"ROU","Romania","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2012/rou_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
45542,642,"ROU","Romania","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2012/rou_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
45543,642,"ROU","Romania","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2012/rou_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
45544,642,"ROU","Romania","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2012/rou_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
45545,642,"ROU","Romania","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2012/rou_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
45546,642,"ROU","Romania","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2012/rou_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
45547,642,"ROU","Romania","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2012/rou_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
45548,642,"ROU","Romania","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2012/rou_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
45549,642,"ROU","Romania","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2013/rou_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
45550,642,"ROU","Romania","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2013/rou_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
45551,642,"ROU","Romania","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2013/rou_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
45552,642,"ROU","Romania","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2013/rou_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
45553,642,"ROU","Romania","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2013/rou_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
45554,642,"ROU","Romania","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2013/rou_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
45555,642,"ROU","Romania","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2013/rou_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
45556,642,"ROU","Romania","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2013/rou_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
45557,642,"ROU","Romania","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2014/rou_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
45558,642,"ROU","Romania","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2014/rou_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
45559,642,"ROU","Romania","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2014/rou_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
45560,642,"ROU","Romania","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2014/rou_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
45561,642,"ROU","Romania","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2014/rou_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
45562,642,"ROU","Romania","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2014/rou_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
45563,642,"ROU","Romania","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2014/rou_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
45564,642,"ROU","Romania","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2014/rou_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
45565,642,"ROU","Romania","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2015/rou_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
45566,642,"ROU","Romania","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2015/rou_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
45567,642,"ROU","Romania","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2015/rou_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
45568,642,"ROU","Romania","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2015/rou_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
45569,642,"ROU","Romania","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2015/rou_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
45570,642,"ROU","Romania","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2015/rou_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
45571,642,"ROU","Romania","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2015/rou_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
45572,642,"ROU","Romania","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Annual/2015/rou_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
45573,646,"RWA","Rwanda","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2000/rwa_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
45574,646,"RWA","Rwanda","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2000/rwa_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
45575,646,"RWA","Rwanda","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2000/rwa_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
45576,646,"RWA","Rwanda","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2000/rwa_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
45577,646,"RWA","Rwanda","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2000/rwa_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
45578,646,"RWA","Rwanda","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2000/rwa_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
45579,646,"RWA","Rwanda","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2000/rwa_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
45580,646,"RWA","Rwanda","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2000/rwa_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
45581,646,"RWA","Rwanda","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2001/rwa_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
45582,646,"RWA","Rwanda","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2001/rwa_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
45583,646,"RWA","Rwanda","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2001/rwa_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
45584,646,"RWA","Rwanda","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2001/rwa_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
45585,646,"RWA","Rwanda","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2001/rwa_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
45586,646,"RWA","Rwanda","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2001/rwa_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
45587,646,"RWA","Rwanda","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2001/rwa_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
45588,646,"RWA","Rwanda","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2001/rwa_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
45589,646,"RWA","Rwanda","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2002/rwa_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
45590,646,"RWA","Rwanda","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2002/rwa_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
45591,646,"RWA","Rwanda","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2002/rwa_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
45592,646,"RWA","Rwanda","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2002/rwa_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
45593,646,"RWA","Rwanda","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2002/rwa_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
45594,646,"RWA","Rwanda","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2002/rwa_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
45595,646,"RWA","Rwanda","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2002/rwa_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
45596,646,"RWA","Rwanda","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2002/rwa_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
45597,646,"RWA","Rwanda","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2003/rwa_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
45598,646,"RWA","Rwanda","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2003/rwa_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
45599,646,"RWA","Rwanda","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2003/rwa_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
45600,646,"RWA","Rwanda","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2003/rwa_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
45601,646,"RWA","Rwanda","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2003/rwa_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
45602,646,"RWA","Rwanda","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2003/rwa_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
45603,646,"RWA","Rwanda","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2003/rwa_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
45604,646,"RWA","Rwanda","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2003/rwa_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
45605,646,"RWA","Rwanda","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2004/rwa_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
45606,646,"RWA","Rwanda","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2004/rwa_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
45607,646,"RWA","Rwanda","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2004/rwa_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
45608,646,"RWA","Rwanda","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2004/rwa_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
45609,646,"RWA","Rwanda","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2004/rwa_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
45610,646,"RWA","Rwanda","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2004/rwa_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
45611,646,"RWA","Rwanda","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2004/rwa_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
45612,646,"RWA","Rwanda","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2004/rwa_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
45613,646,"RWA","Rwanda","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2005/rwa_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
45614,646,"RWA","Rwanda","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2005/rwa_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
45615,646,"RWA","Rwanda","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2005/rwa_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
45616,646,"RWA","Rwanda","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2005/rwa_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
45617,646,"RWA","Rwanda","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2005/rwa_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
45618,646,"RWA","Rwanda","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2005/rwa_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
45619,646,"RWA","Rwanda","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2005/rwa_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
45620,646,"RWA","Rwanda","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2005/rwa_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
45621,646,"RWA","Rwanda","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2006/rwa_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
45622,646,"RWA","Rwanda","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2006/rwa_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
45623,646,"RWA","Rwanda","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2006/rwa_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
45624,646,"RWA","Rwanda","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2006/rwa_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
45625,646,"RWA","Rwanda","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2006/rwa_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
45626,646,"RWA","Rwanda","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2006/rwa_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
45627,646,"RWA","Rwanda","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2006/rwa_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
45628,646,"RWA","Rwanda","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2006/rwa_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
45629,646,"RWA","Rwanda","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2007/rwa_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
45630,646,"RWA","Rwanda","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2007/rwa_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
45631,646,"RWA","Rwanda","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2007/rwa_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
45632,646,"RWA","Rwanda","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2007/rwa_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
45633,646,"RWA","Rwanda","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2007/rwa_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
45634,646,"RWA","Rwanda","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2007/rwa_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
45635,646,"RWA","Rwanda","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2007/rwa_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
45636,646,"RWA","Rwanda","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2007/rwa_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
45637,646,"RWA","Rwanda","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2008/rwa_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
45638,646,"RWA","Rwanda","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2008/rwa_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
45639,646,"RWA","Rwanda","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2008/rwa_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
45640,646,"RWA","Rwanda","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2008/rwa_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
45641,646,"RWA","Rwanda","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2008/rwa_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
45642,646,"RWA","Rwanda","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2008/rwa_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
45643,646,"RWA","Rwanda","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2008/rwa_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
45644,646,"RWA","Rwanda","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2008/rwa_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
45645,646,"RWA","Rwanda","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2009/rwa_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
45646,646,"RWA","Rwanda","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2009/rwa_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
45647,646,"RWA","Rwanda","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2009/rwa_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
45648,646,"RWA","Rwanda","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2009/rwa_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
45649,646,"RWA","Rwanda","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2009/rwa_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
45650,646,"RWA","Rwanda","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2009/rwa_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
45651,646,"RWA","Rwanda","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2009/rwa_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
45652,646,"RWA","Rwanda","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2009/rwa_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
45653,646,"RWA","Rwanda","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2010/rwa_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
45654,646,"RWA","Rwanda","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2010/rwa_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
45655,646,"RWA","Rwanda","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2010/rwa_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
45656,646,"RWA","Rwanda","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2010/rwa_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
45657,646,"RWA","Rwanda","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2010/rwa_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
45658,646,"RWA","Rwanda","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2010/rwa_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
45659,646,"RWA","Rwanda","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2010/rwa_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
45660,646,"RWA","Rwanda","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2010/rwa_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
45661,646,"RWA","Rwanda","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2011/rwa_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
45662,646,"RWA","Rwanda","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2011/rwa_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
45663,646,"RWA","Rwanda","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2011/rwa_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
45664,646,"RWA","Rwanda","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2011/rwa_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
45665,646,"RWA","Rwanda","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2011/rwa_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
45666,646,"RWA","Rwanda","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2011/rwa_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
45667,646,"RWA","Rwanda","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2011/rwa_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
45668,646,"RWA","Rwanda","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2011/rwa_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
45669,646,"RWA","Rwanda","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2012/rwa_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
45670,646,"RWA","Rwanda","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2012/rwa_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
45671,646,"RWA","Rwanda","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2012/rwa_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
45672,646,"RWA","Rwanda","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2012/rwa_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
45673,646,"RWA","Rwanda","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2012/rwa_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
45674,646,"RWA","Rwanda","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2012/rwa_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
45675,646,"RWA","Rwanda","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2012/rwa_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
45676,646,"RWA","Rwanda","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2012/rwa_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
45677,646,"RWA","Rwanda","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2013/rwa_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
45678,646,"RWA","Rwanda","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2013/rwa_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
45679,646,"RWA","Rwanda","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2013/rwa_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
45680,646,"RWA","Rwanda","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2013/rwa_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
45681,646,"RWA","Rwanda","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2013/rwa_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
45682,646,"RWA","Rwanda","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2013/rwa_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
45683,646,"RWA","Rwanda","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2013/rwa_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
45684,646,"RWA","Rwanda","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2013/rwa_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
45685,646,"RWA","Rwanda","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2014/rwa_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
45686,646,"RWA","Rwanda","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2014/rwa_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
45687,646,"RWA","Rwanda","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2014/rwa_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
45688,646,"RWA","Rwanda","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2014/rwa_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
45689,646,"RWA","Rwanda","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2014/rwa_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
45690,646,"RWA","Rwanda","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2014/rwa_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
45691,646,"RWA","Rwanda","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2014/rwa_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
45692,646,"RWA","Rwanda","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2014/rwa_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
45693,646,"RWA","Rwanda","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2015/rwa_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
45694,646,"RWA","Rwanda","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2015/rwa_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
45695,646,"RWA","Rwanda","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2015/rwa_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
45696,646,"RWA","Rwanda","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2015/rwa_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
45697,646,"RWA","Rwanda","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2015/rwa_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
45698,646,"RWA","Rwanda","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2015/rwa_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
45699,646,"RWA","Rwanda","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2015/rwa_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
45700,646,"RWA","Rwanda","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Annual/2015/rwa_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
45701,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2000/blm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
45702,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2000/blm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
45703,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2000/blm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
45704,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2000/blm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
45705,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2000/blm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
45706,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2000/blm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
45707,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2000/blm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
45708,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2000/blm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
45709,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2001/blm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
45710,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2001/blm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
45711,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2001/blm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
45712,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2001/blm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
45713,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2001/blm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
45714,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2001/blm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
45715,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2001/blm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
45716,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2001/blm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
45717,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2002/blm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
45718,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2002/blm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
45719,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2002/blm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
45720,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2002/blm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
45721,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2002/blm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
45722,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2002/blm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
45723,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2002/blm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
45724,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2002/blm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
45725,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2003/blm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
45726,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2003/blm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
45727,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2003/blm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
45728,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2003/blm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
45729,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2003/blm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
45730,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2003/blm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
45731,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2003/blm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
45732,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2003/blm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
45733,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2004/blm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
45734,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2004/blm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
45735,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2004/blm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
45736,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2004/blm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
45737,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2004/blm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
45738,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2004/blm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
45739,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2004/blm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
45740,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2004/blm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
45741,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2005/blm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
45742,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2005/blm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
45743,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2005/blm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
45744,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2005/blm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
45745,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2005/blm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
45746,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2005/blm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
45747,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2005/blm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
45748,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2005/blm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
45749,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2006/blm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
45750,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2006/blm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
45751,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2006/blm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
45752,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2006/blm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
45753,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2006/blm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
45754,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2006/blm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
45755,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2006/blm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
45756,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2006/blm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
45757,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2007/blm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
45758,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2007/blm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
45759,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2007/blm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
45760,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2007/blm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
45761,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2007/blm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
45762,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2007/blm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
45763,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2007/blm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
45764,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2007/blm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
45765,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2008/blm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
45766,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2008/blm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
45767,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2008/blm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
45768,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2008/blm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
45769,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2008/blm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
45770,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2008/blm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
45771,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2008/blm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
45772,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2008/blm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
45773,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2009/blm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
45774,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2009/blm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
45775,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2009/blm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
45776,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2009/blm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
45777,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2009/blm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
45778,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2009/blm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
45779,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2009/blm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
45780,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2009/blm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
45781,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2010/blm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
45782,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2010/blm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
45783,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2010/blm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
45784,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2010/blm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
45785,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2010/blm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
45786,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2010/blm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
45787,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2010/blm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
45788,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2010/blm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
45789,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2011/blm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
45790,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2011/blm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
45791,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2011/blm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
45792,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2011/blm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
45793,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2011/blm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
45794,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2011/blm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
45795,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2011/blm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
45796,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2011/blm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
45797,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2012/blm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
45798,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2012/blm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
45799,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2012/blm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
45800,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2012/blm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
45801,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2012/blm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
45802,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2012/blm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
45803,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2012/blm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
45804,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2012/blm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
45805,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2013/blm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
45806,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2013/blm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
45807,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2013/blm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
45808,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2013/blm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
45809,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2013/blm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
45810,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2013/blm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
45811,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2013/blm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
45812,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2013/blm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
45813,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2014/blm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
45814,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2014/blm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
45815,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2014/blm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
45816,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2014/blm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
45817,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2014/blm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
45818,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2014/blm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
45819,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2014/blm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
45820,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2014/blm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
45821,652,"BLM","Saint Barthelemy","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2015/blm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
45822,652,"BLM","Saint Barthelemy","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2015/blm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
45823,652,"BLM","Saint Barthelemy","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2015/blm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
45824,652,"BLM","Saint Barthelemy","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2015/blm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
45825,652,"BLM","Saint Barthelemy","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2015/blm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
45826,652,"BLM","Saint Barthelemy","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2015/blm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
45827,652,"BLM","Saint Barthelemy","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2015/blm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
45828,652,"BLM","Saint Barthelemy","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Annual/2015/blm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
45829,654,"SHN","Saint Helena","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2000/shn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
45830,654,"SHN","Saint Helena","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2000/shn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
45831,654,"SHN","Saint Helena","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2000/shn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
45832,654,"SHN","Saint Helena","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2000/shn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
45833,654,"SHN","Saint Helena","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2000/shn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
45834,654,"SHN","Saint Helena","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2000/shn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
45835,654,"SHN","Saint Helena","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2000/shn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
45836,654,"SHN","Saint Helena","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2000/shn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
45837,654,"SHN","Saint Helena","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2001/shn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
45838,654,"SHN","Saint Helena","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2001/shn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
45839,654,"SHN","Saint Helena","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2001/shn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
45840,654,"SHN","Saint Helena","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2001/shn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
45841,654,"SHN","Saint Helena","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2001/shn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
45842,654,"SHN","Saint Helena","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2001/shn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
45843,654,"SHN","Saint Helena","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2001/shn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
45844,654,"SHN","Saint Helena","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2001/shn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
45845,654,"SHN","Saint Helena","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2002/shn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
45846,654,"SHN","Saint Helena","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2002/shn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
45847,654,"SHN","Saint Helena","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2002/shn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
45848,654,"SHN","Saint Helena","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2002/shn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
45849,654,"SHN","Saint Helena","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2002/shn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
45850,654,"SHN","Saint Helena","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2002/shn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
45851,654,"SHN","Saint Helena","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2002/shn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
45852,654,"SHN","Saint Helena","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2002/shn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
45853,654,"SHN","Saint Helena","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2003/shn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
45854,654,"SHN","Saint Helena","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2003/shn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
45855,654,"SHN","Saint Helena","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2003/shn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
45856,654,"SHN","Saint Helena","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2003/shn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
45857,654,"SHN","Saint Helena","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2003/shn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
45858,654,"SHN","Saint Helena","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2003/shn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
45859,654,"SHN","Saint Helena","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2003/shn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
45860,654,"SHN","Saint Helena","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2003/shn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
45861,654,"SHN","Saint Helena","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2004/shn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
45862,654,"SHN","Saint Helena","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2004/shn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
45863,654,"SHN","Saint Helena","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2004/shn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
45864,654,"SHN","Saint Helena","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2004/shn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
45865,654,"SHN","Saint Helena","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2004/shn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
45866,654,"SHN","Saint Helena","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2004/shn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
45867,654,"SHN","Saint Helena","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2004/shn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
45868,654,"SHN","Saint Helena","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2004/shn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
45869,654,"SHN","Saint Helena","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2005/shn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
45870,654,"SHN","Saint Helena","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2005/shn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
45871,654,"SHN","Saint Helena","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2005/shn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
45872,654,"SHN","Saint Helena","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2005/shn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
45873,654,"SHN","Saint Helena","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2005/shn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
45874,654,"SHN","Saint Helena","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2005/shn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
45875,654,"SHN","Saint Helena","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2005/shn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
45876,654,"SHN","Saint Helena","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2005/shn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
45877,654,"SHN","Saint Helena","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2006/shn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
45878,654,"SHN","Saint Helena","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2006/shn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
45879,654,"SHN","Saint Helena","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2006/shn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
45880,654,"SHN","Saint Helena","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2006/shn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
45881,654,"SHN","Saint Helena","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2006/shn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
45882,654,"SHN","Saint Helena","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2006/shn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
45883,654,"SHN","Saint Helena","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2006/shn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
45884,654,"SHN","Saint Helena","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2006/shn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
45885,654,"SHN","Saint Helena","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2007/shn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
45886,654,"SHN","Saint Helena","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2007/shn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
45887,654,"SHN","Saint Helena","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2007/shn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
45888,654,"SHN","Saint Helena","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2007/shn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
45889,654,"SHN","Saint Helena","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2007/shn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
45890,654,"SHN","Saint Helena","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2007/shn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
45891,654,"SHN","Saint Helena","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2007/shn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
45892,654,"SHN","Saint Helena","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2007/shn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
45893,654,"SHN","Saint Helena","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2008/shn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
45894,654,"SHN","Saint Helena","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2008/shn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
45895,654,"SHN","Saint Helena","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2008/shn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
45896,654,"SHN","Saint Helena","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2008/shn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
45897,654,"SHN","Saint Helena","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2008/shn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
45898,654,"SHN","Saint Helena","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2008/shn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
45899,654,"SHN","Saint Helena","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2008/shn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
45900,654,"SHN","Saint Helena","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2008/shn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
45901,654,"SHN","Saint Helena","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2009/shn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
45902,654,"SHN","Saint Helena","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2009/shn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
45903,654,"SHN","Saint Helena","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2009/shn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
45904,654,"SHN","Saint Helena","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2009/shn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
45905,654,"SHN","Saint Helena","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2009/shn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
45906,654,"SHN","Saint Helena","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2009/shn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
45907,654,"SHN","Saint Helena","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2009/shn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
45908,654,"SHN","Saint Helena","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2009/shn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
45909,654,"SHN","Saint Helena","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2010/shn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
45910,654,"SHN","Saint Helena","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2010/shn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
45911,654,"SHN","Saint Helena","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2010/shn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
45912,654,"SHN","Saint Helena","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2010/shn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
45913,654,"SHN","Saint Helena","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2010/shn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
45914,654,"SHN","Saint Helena","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2010/shn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
45915,654,"SHN","Saint Helena","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2010/shn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
45916,654,"SHN","Saint Helena","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2010/shn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
45917,654,"SHN","Saint Helena","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2011/shn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
45918,654,"SHN","Saint Helena","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2011/shn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
45919,654,"SHN","Saint Helena","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2011/shn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
45920,654,"SHN","Saint Helena","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2011/shn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
45921,654,"SHN","Saint Helena","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2011/shn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
45922,654,"SHN","Saint Helena","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2011/shn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
45923,654,"SHN","Saint Helena","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2011/shn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
45924,654,"SHN","Saint Helena","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2011/shn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
45925,654,"SHN","Saint Helena","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2012/shn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
45926,654,"SHN","Saint Helena","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2012/shn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
45927,654,"SHN","Saint Helena","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2012/shn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
45928,654,"SHN","Saint Helena","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2012/shn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
45929,654,"SHN","Saint Helena","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2012/shn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
45930,654,"SHN","Saint Helena","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2012/shn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
45931,654,"SHN","Saint Helena","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2012/shn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
45932,654,"SHN","Saint Helena","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2012/shn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
45933,654,"SHN","Saint Helena","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2013/shn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
45934,654,"SHN","Saint Helena","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2013/shn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
45935,654,"SHN","Saint Helena","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2013/shn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
45936,654,"SHN","Saint Helena","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2013/shn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
45937,654,"SHN","Saint Helena","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2013/shn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
45938,654,"SHN","Saint Helena","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2013/shn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
45939,654,"SHN","Saint Helena","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2013/shn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
45940,654,"SHN","Saint Helena","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2013/shn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
45941,654,"SHN","Saint Helena","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2014/shn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
45942,654,"SHN","Saint Helena","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2014/shn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
45943,654,"SHN","Saint Helena","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2014/shn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
45944,654,"SHN","Saint Helena","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2014/shn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
45945,654,"SHN","Saint Helena","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2014/shn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
45946,654,"SHN","Saint Helena","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2014/shn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
45947,654,"SHN","Saint Helena","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2014/shn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
45948,654,"SHN","Saint Helena","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2014/shn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
45949,654,"SHN","Saint Helena","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2015/shn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
45950,654,"SHN","Saint Helena","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2015/shn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
45951,654,"SHN","Saint Helena","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2015/shn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
45952,654,"SHN","Saint Helena","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2015/shn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
45953,654,"SHN","Saint Helena","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2015/shn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
45954,654,"SHN","Saint Helena","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2015/shn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
45955,654,"SHN","Saint Helena","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2015/shn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
45956,654,"SHN","Saint Helena","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Annual/2015/shn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
45957,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2000/kna_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
45958,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2000/kna_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
45959,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2000/kna_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
45960,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2000/kna_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
45961,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2000/kna_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
45962,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2000/kna_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
45963,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2000/kna_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
45964,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2000/kna_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
45965,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2001/kna_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
45966,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2001/kna_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
45967,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2001/kna_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
45968,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2001/kna_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
45969,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2001/kna_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
45970,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2001/kna_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
45971,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2001/kna_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
45972,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2001/kna_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
45973,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2002/kna_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
45974,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2002/kna_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
45975,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2002/kna_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
45976,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2002/kna_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
45977,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2002/kna_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
45978,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2002/kna_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
45979,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2002/kna_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
45980,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2002/kna_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
45981,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2003/kna_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
45982,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2003/kna_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
45983,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2003/kna_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
45984,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2003/kna_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
45985,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2003/kna_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
45986,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2003/kna_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
45987,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2003/kna_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
45988,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2003/kna_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
45989,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2004/kna_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
45990,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2004/kna_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
45991,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2004/kna_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
45992,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2004/kna_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
45993,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2004/kna_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
45994,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2004/kna_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
45995,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2004/kna_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
45996,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2004/kna_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
45997,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2005/kna_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
45998,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2005/kna_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
45999,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2005/kna_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
46000,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2005/kna_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
46001,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2005/kna_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
46002,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2005/kna_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
46003,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2005/kna_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
46004,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2005/kna_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
46005,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2006/kna_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
46006,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2006/kna_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
46007,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2006/kna_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
46008,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2006/kna_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
46009,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2006/kna_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
46010,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2006/kna_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
46011,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2006/kna_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
46012,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2006/kna_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
46013,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2007/kna_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
46014,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2007/kna_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
46015,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2007/kna_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
46016,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2007/kna_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
46017,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2007/kna_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
46018,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2007/kna_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
46019,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2007/kna_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
46020,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2007/kna_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
46021,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2008/kna_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
46022,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2008/kna_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
46023,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2008/kna_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
46024,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2008/kna_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
46025,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2008/kna_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
46026,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2008/kna_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
46027,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2008/kna_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
46028,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2008/kna_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
46029,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2009/kna_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
46030,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2009/kna_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
46031,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2009/kna_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
46032,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2009/kna_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
46033,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2009/kna_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
46034,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2009/kna_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
46035,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2009/kna_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
46036,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2009/kna_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
46037,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2010/kna_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
46038,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2010/kna_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
46039,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2010/kna_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
46040,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2010/kna_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
46041,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2010/kna_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
46042,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2010/kna_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
46043,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2010/kna_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
46044,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2010/kna_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
46045,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2011/kna_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
46046,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2011/kna_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
46047,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2011/kna_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
46048,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2011/kna_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
46049,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2011/kna_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
46050,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2011/kna_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
46051,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2011/kna_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
46052,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2011/kna_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
46053,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2012/kna_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
46054,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2012/kna_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
46055,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2012/kna_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
46056,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2012/kna_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
46057,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2012/kna_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
46058,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2012/kna_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
46059,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2012/kna_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
46060,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2012/kna_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
46061,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2013/kna_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
46062,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2013/kna_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
46063,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2013/kna_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
46064,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2013/kna_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
46065,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2013/kna_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
46066,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2013/kna_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
46067,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2013/kna_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
46068,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2013/kna_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
46069,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2014/kna_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
46070,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2014/kna_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
46071,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2014/kna_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
46072,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2014/kna_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
46073,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2014/kna_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
46074,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2014/kna_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
46075,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2014/kna_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
46076,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2014/kna_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
46077,659,"KNA","Saint Kitts and Nevis","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2015/kna_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
46078,659,"KNA","Saint Kitts and Nevis","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2015/kna_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
46079,659,"KNA","Saint Kitts and Nevis","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2015/kna_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
46080,659,"KNA","Saint Kitts and Nevis","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2015/kna_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
46081,659,"KNA","Saint Kitts and Nevis","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2015/kna_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
46082,659,"KNA","Saint Kitts and Nevis","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2015/kna_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
46083,659,"KNA","Saint Kitts and Nevis","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2015/kna_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
46084,659,"KNA","Saint Kitts and Nevis","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Annual/2015/kna_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
46085,660,"AIA","Anguilla","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2000/aia_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
46086,660,"AIA","Anguilla","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2000/aia_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
46087,660,"AIA","Anguilla","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2000/aia_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
46088,660,"AIA","Anguilla","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2000/aia_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
46089,660,"AIA","Anguilla","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2000/aia_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
46090,660,"AIA","Anguilla","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2000/aia_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
46091,660,"AIA","Anguilla","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2000/aia_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
46092,660,"AIA","Anguilla","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2000/aia_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
46093,660,"AIA","Anguilla","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2001/aia_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
46094,660,"AIA","Anguilla","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2001/aia_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
46095,660,"AIA","Anguilla","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2001/aia_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
46096,660,"AIA","Anguilla","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2001/aia_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
46097,660,"AIA","Anguilla","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2001/aia_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
46098,660,"AIA","Anguilla","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2001/aia_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
46099,660,"AIA","Anguilla","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2001/aia_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
46100,660,"AIA","Anguilla","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2001/aia_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
46101,660,"AIA","Anguilla","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2002/aia_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
46102,660,"AIA","Anguilla","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2002/aia_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
46103,660,"AIA","Anguilla","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2002/aia_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
46104,660,"AIA","Anguilla","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2002/aia_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
46105,660,"AIA","Anguilla","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2002/aia_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
46106,660,"AIA","Anguilla","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2002/aia_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
46107,660,"AIA","Anguilla","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2002/aia_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
46108,660,"AIA","Anguilla","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2002/aia_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
46109,660,"AIA","Anguilla","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2003/aia_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
46110,660,"AIA","Anguilla","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2003/aia_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
46111,660,"AIA","Anguilla","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2003/aia_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
46112,660,"AIA","Anguilla","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2003/aia_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
46113,660,"AIA","Anguilla","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2003/aia_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
46114,660,"AIA","Anguilla","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2003/aia_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
46115,660,"AIA","Anguilla","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2003/aia_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
46116,660,"AIA","Anguilla","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2003/aia_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
46117,660,"AIA","Anguilla","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2004/aia_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
46118,660,"AIA","Anguilla","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2004/aia_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
46119,660,"AIA","Anguilla","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2004/aia_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
46120,660,"AIA","Anguilla","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2004/aia_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
46121,660,"AIA","Anguilla","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2004/aia_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
46122,660,"AIA","Anguilla","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2004/aia_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
46123,660,"AIA","Anguilla","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2004/aia_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
46124,660,"AIA","Anguilla","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2004/aia_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
46125,660,"AIA","Anguilla","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2005/aia_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
46126,660,"AIA","Anguilla","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2005/aia_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
46127,660,"AIA","Anguilla","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2005/aia_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
46128,660,"AIA","Anguilla","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2005/aia_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
46129,660,"AIA","Anguilla","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2005/aia_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
46130,660,"AIA","Anguilla","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2005/aia_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
46131,660,"AIA","Anguilla","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2005/aia_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
46132,660,"AIA","Anguilla","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2005/aia_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
46133,660,"AIA","Anguilla","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2006/aia_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
46134,660,"AIA","Anguilla","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2006/aia_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
46135,660,"AIA","Anguilla","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2006/aia_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
46136,660,"AIA","Anguilla","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2006/aia_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
46137,660,"AIA","Anguilla","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2006/aia_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
46138,660,"AIA","Anguilla","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2006/aia_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
46139,660,"AIA","Anguilla","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2006/aia_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
46140,660,"AIA","Anguilla","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2006/aia_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
46141,660,"AIA","Anguilla","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2007/aia_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
46142,660,"AIA","Anguilla","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2007/aia_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
46143,660,"AIA","Anguilla","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2007/aia_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
46144,660,"AIA","Anguilla","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2007/aia_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
46145,660,"AIA","Anguilla","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2007/aia_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
46146,660,"AIA","Anguilla","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2007/aia_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
46147,660,"AIA","Anguilla","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2007/aia_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
46148,660,"AIA","Anguilla","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2007/aia_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
46149,660,"AIA","Anguilla","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2008/aia_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
46150,660,"AIA","Anguilla","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2008/aia_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
46151,660,"AIA","Anguilla","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2008/aia_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
46152,660,"AIA","Anguilla","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2008/aia_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
46153,660,"AIA","Anguilla","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2008/aia_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
46154,660,"AIA","Anguilla","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2008/aia_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
46155,660,"AIA","Anguilla","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2008/aia_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
46156,660,"AIA","Anguilla","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2008/aia_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
46157,660,"AIA","Anguilla","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2009/aia_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
46158,660,"AIA","Anguilla","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2009/aia_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
46159,660,"AIA","Anguilla","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2009/aia_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
46160,660,"AIA","Anguilla","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2009/aia_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
46161,660,"AIA","Anguilla","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2009/aia_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
46162,660,"AIA","Anguilla","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2009/aia_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
46163,660,"AIA","Anguilla","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2009/aia_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
46164,660,"AIA","Anguilla","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2009/aia_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
46165,660,"AIA","Anguilla","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2010/aia_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
46166,660,"AIA","Anguilla","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2010/aia_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
46167,660,"AIA","Anguilla","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2010/aia_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
46168,660,"AIA","Anguilla","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2010/aia_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
46169,660,"AIA","Anguilla","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2010/aia_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
46170,660,"AIA","Anguilla","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2010/aia_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
46171,660,"AIA","Anguilla","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2010/aia_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
46172,660,"AIA","Anguilla","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2010/aia_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
46173,660,"AIA","Anguilla","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2011/aia_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
46174,660,"AIA","Anguilla","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2011/aia_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
46175,660,"AIA","Anguilla","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2011/aia_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
46176,660,"AIA","Anguilla","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2011/aia_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
46177,660,"AIA","Anguilla","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2011/aia_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
46178,660,"AIA","Anguilla","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2011/aia_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
46179,660,"AIA","Anguilla","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2011/aia_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
46180,660,"AIA","Anguilla","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2011/aia_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
46181,660,"AIA","Anguilla","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2012/aia_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
46182,660,"AIA","Anguilla","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2012/aia_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
46183,660,"AIA","Anguilla","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2012/aia_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
46184,660,"AIA","Anguilla","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2012/aia_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
46185,660,"AIA","Anguilla","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2012/aia_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
46186,660,"AIA","Anguilla","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2012/aia_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
46187,660,"AIA","Anguilla","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2012/aia_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
46188,660,"AIA","Anguilla","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2012/aia_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
46189,660,"AIA","Anguilla","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2013/aia_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
46190,660,"AIA","Anguilla","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2013/aia_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
46191,660,"AIA","Anguilla","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2013/aia_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
46192,660,"AIA","Anguilla","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2013/aia_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
46193,660,"AIA","Anguilla","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2013/aia_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
46194,660,"AIA","Anguilla","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2013/aia_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
46195,660,"AIA","Anguilla","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2013/aia_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
46196,660,"AIA","Anguilla","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2013/aia_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
46197,660,"AIA","Anguilla","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2014/aia_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
46198,660,"AIA","Anguilla","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2014/aia_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
46199,660,"AIA","Anguilla","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2014/aia_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
46200,660,"AIA","Anguilla","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2014/aia_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
46201,660,"AIA","Anguilla","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2014/aia_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
46202,660,"AIA","Anguilla","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2014/aia_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
46203,660,"AIA","Anguilla","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2014/aia_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
46204,660,"AIA","Anguilla","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2014/aia_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
46205,660,"AIA","Anguilla","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2015/aia_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
46206,660,"AIA","Anguilla","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2015/aia_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
46207,660,"AIA","Anguilla","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2015/aia_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
46208,660,"AIA","Anguilla","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2015/aia_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
46209,660,"AIA","Anguilla","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2015/aia_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
46210,660,"AIA","Anguilla","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2015/aia_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
46211,660,"AIA","Anguilla","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2015/aia_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
46212,660,"AIA","Anguilla","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Annual/2015/aia_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
46213,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2000/lca_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
46214,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2000/lca_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
46215,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2000/lca_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
46216,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2000/lca_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
46217,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2000/lca_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
46218,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2000/lca_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
46219,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2000/lca_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
46220,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2000/lca_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
46221,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2001/lca_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
46222,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2001/lca_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
46223,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2001/lca_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
46224,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2001/lca_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
46225,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2001/lca_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
46226,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2001/lca_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
46227,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2001/lca_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
46228,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2001/lca_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
46229,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2002/lca_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
46230,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2002/lca_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
46231,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2002/lca_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
46232,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2002/lca_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
46233,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2002/lca_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
46234,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2002/lca_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
46235,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2002/lca_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
46236,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2002/lca_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
46237,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2003/lca_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
46238,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2003/lca_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
46239,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2003/lca_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
46240,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2003/lca_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
46241,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2003/lca_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
46242,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2003/lca_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
46243,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2003/lca_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
46244,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2003/lca_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
46245,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2004/lca_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
46246,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2004/lca_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
46247,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2004/lca_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
46248,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2004/lca_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
46249,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2004/lca_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
46250,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2004/lca_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
46251,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2004/lca_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
46252,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2004/lca_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
46253,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2005/lca_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
46254,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2005/lca_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
46255,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2005/lca_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
46256,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2005/lca_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
46257,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2005/lca_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
46258,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2005/lca_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
46259,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2005/lca_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
46260,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2005/lca_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
46261,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2006/lca_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
46262,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2006/lca_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
46263,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2006/lca_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
46264,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2006/lca_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
46265,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2006/lca_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
46266,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2006/lca_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
46267,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2006/lca_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
46268,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2006/lca_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
46269,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2007/lca_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
46270,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2007/lca_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
46271,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2007/lca_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
46272,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2007/lca_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
46273,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2007/lca_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
46274,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2007/lca_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
46275,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2007/lca_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
46276,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2007/lca_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
46277,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2008/lca_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
46278,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2008/lca_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
46279,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2008/lca_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
46280,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2008/lca_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
46281,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2008/lca_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
46282,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2008/lca_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
46283,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2008/lca_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
46284,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2008/lca_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
46285,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2009/lca_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
46286,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2009/lca_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
46287,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2009/lca_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
46288,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2009/lca_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
46289,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2009/lca_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
46290,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2009/lca_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
46291,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2009/lca_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
46292,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2009/lca_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
46293,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2010/lca_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
46294,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2010/lca_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
46295,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2010/lca_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
46296,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2010/lca_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
46297,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2010/lca_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
46298,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2010/lca_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
46299,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2010/lca_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
46300,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2010/lca_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
46301,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2011/lca_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
46302,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2011/lca_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
46303,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2011/lca_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
46304,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2011/lca_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
46305,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2011/lca_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
46306,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2011/lca_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
46307,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2011/lca_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
46308,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2011/lca_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
46309,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2012/lca_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
46310,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2012/lca_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
46311,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2012/lca_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
46312,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2012/lca_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
46313,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2012/lca_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
46314,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2012/lca_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
46315,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2012/lca_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
46316,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2012/lca_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
46317,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2013/lca_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
46318,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2013/lca_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
46319,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2013/lca_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
46320,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2013/lca_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
46321,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2013/lca_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
46322,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2013/lca_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
46323,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2013/lca_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
46324,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2013/lca_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
46325,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2014/lca_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
46326,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2014/lca_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
46327,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2014/lca_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
46328,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2014/lca_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
46329,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2014/lca_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
46330,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2014/lca_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
46331,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2014/lca_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
46332,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2014/lca_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
46333,662,"LCA","Saint Lucia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2015/lca_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
46334,662,"LCA","Saint Lucia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2015/lca_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
46335,662,"LCA","Saint Lucia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2015/lca_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
46336,662,"LCA","Saint Lucia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2015/lca_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
46337,662,"LCA","Saint Lucia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2015/lca_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
46338,662,"LCA","Saint Lucia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2015/lca_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
46339,662,"LCA","Saint Lucia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2015/lca_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
46340,662,"LCA","Saint Lucia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Annual/2015/lca_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
46341,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2000/maf_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
46342,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2000/maf_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
46343,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2000/maf_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
46344,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2000/maf_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
46345,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2000/maf_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
46346,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2000/maf_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
46347,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2000/maf_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
46348,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2000/maf_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
46349,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2001/maf_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
46350,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2001/maf_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
46351,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2001/maf_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
46352,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2001/maf_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
46353,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2001/maf_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
46354,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2001/maf_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
46355,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2001/maf_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
46356,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2001/maf_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
46357,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2002/maf_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
46358,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2002/maf_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
46359,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2002/maf_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
46360,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2002/maf_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
46361,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2002/maf_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
46362,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2002/maf_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
46363,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2002/maf_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
46364,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2002/maf_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
46365,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2003/maf_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
46366,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2003/maf_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
46367,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2003/maf_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
46368,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2003/maf_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
46369,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2003/maf_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
46370,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2003/maf_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
46371,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2003/maf_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
46372,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2003/maf_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
46373,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2004/maf_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
46374,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2004/maf_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
46375,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2004/maf_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
46376,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2004/maf_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
46377,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2004/maf_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
46378,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2004/maf_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
46379,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2004/maf_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
46380,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2004/maf_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
46381,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2005/maf_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
46382,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2005/maf_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
46383,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2005/maf_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
46384,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2005/maf_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
46385,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2005/maf_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
46386,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2005/maf_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
46387,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2005/maf_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
46388,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2005/maf_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
46389,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2006/maf_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
46390,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2006/maf_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
46391,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2006/maf_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
46392,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2006/maf_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
46393,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2006/maf_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
46394,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2006/maf_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
46395,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2006/maf_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
46396,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2006/maf_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
46397,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2007/maf_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
46398,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2007/maf_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
46399,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2007/maf_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
46400,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2007/maf_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
46401,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2007/maf_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
46402,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2007/maf_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
46403,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2007/maf_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
46404,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2007/maf_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
46405,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2008/maf_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
46406,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2008/maf_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
46407,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2008/maf_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
46408,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2008/maf_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
46409,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2008/maf_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
46410,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2008/maf_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
46411,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2008/maf_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
46412,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2008/maf_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
46413,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2009/maf_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
46414,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2009/maf_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
46415,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2009/maf_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
46416,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2009/maf_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
46417,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2009/maf_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
46418,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2009/maf_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
46419,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2009/maf_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
46420,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2009/maf_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
46421,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2010/maf_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
46422,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2010/maf_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
46423,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2010/maf_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
46424,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2010/maf_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
46425,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2010/maf_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
46426,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2010/maf_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
46427,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2010/maf_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
46428,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2010/maf_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
46429,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2011/maf_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
46430,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2011/maf_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
46431,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2011/maf_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
46432,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2011/maf_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
46433,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2011/maf_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
46434,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2011/maf_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
46435,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2011/maf_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
46436,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2011/maf_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
46437,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2012/maf_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
46438,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2012/maf_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
46439,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2012/maf_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
46440,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2012/maf_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
46441,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2012/maf_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
46442,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2012/maf_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
46443,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2012/maf_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
46444,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2012/maf_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
46445,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2013/maf_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
46446,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2013/maf_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
46447,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2013/maf_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
46448,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2013/maf_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
46449,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2013/maf_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
46450,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2013/maf_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
46451,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2013/maf_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
46452,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2013/maf_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
46453,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2014/maf_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
46454,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2014/maf_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
46455,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2014/maf_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
46456,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2014/maf_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
46457,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2014/maf_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
46458,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2014/maf_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
46459,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2014/maf_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
46460,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2014/maf_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
46461,663,"MAF","Saint Martin (French part)","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2015/maf_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
46462,663,"MAF","Saint Martin (French part)","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2015/maf_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
46463,663,"MAF","Saint Martin (French part)","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2015/maf_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
46464,663,"MAF","Saint Martin (French part)","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2015/maf_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
46465,663,"MAF","Saint Martin (French part)","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2015/maf_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
46466,663,"MAF","Saint Martin (French part)","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2015/maf_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
46467,663,"MAF","Saint Martin (French part)","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2015/maf_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
46468,663,"MAF","Saint Martin (French part)","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Annual/2015/maf_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
46469,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2000/spm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
46470,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2000/spm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
46471,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2000/spm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
46472,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2000/spm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
46473,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2000/spm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
46474,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2000/spm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
46475,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2000/spm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
46476,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2000/spm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
46477,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2001/spm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
46478,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2001/spm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
46479,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2001/spm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
46480,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2001/spm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
46481,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2001/spm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
46482,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2001/spm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
46483,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2001/spm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
46484,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2001/spm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
46485,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2002/spm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
46486,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2002/spm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
46487,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2002/spm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
46488,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2002/spm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
46489,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2002/spm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
46490,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2002/spm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
46491,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2002/spm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
46492,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2002/spm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
46493,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2003/spm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
46494,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2003/spm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
46495,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2003/spm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
46496,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2003/spm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
46497,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2003/spm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
46498,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2003/spm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
46499,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2003/spm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
46500,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2003/spm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
46501,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2004/spm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
46502,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2004/spm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
46503,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2004/spm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
46504,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2004/spm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
46505,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2004/spm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
46506,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2004/spm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
46507,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2004/spm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
46508,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2004/spm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
46509,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2005/spm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
46510,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2005/spm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
46511,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2005/spm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
46512,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2005/spm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
46513,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2005/spm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
46514,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2005/spm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
46515,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2005/spm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
46516,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2005/spm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
46517,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2006/spm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
46518,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2006/spm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
46519,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2006/spm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
46520,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2006/spm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
46521,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2006/spm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
46522,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2006/spm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
46523,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2006/spm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
46524,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2006/spm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
46525,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2007/spm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
46526,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2007/spm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
46527,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2007/spm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
46528,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2007/spm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
46529,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2007/spm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
46530,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2007/spm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
46531,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2007/spm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
46532,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2007/spm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
46533,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2008/spm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
46534,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2008/spm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
46535,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2008/spm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
46536,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2008/spm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
46537,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2008/spm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
46538,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2008/spm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
46539,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2008/spm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
46540,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2008/spm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
46541,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2009/spm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
46542,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2009/spm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
46543,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2009/spm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
46544,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2009/spm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
46545,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2009/spm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
46546,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2009/spm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
46547,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2009/spm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
46548,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2009/spm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
46549,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2010/spm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
46550,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2010/spm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
46551,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2010/spm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
46552,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2010/spm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
46553,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2010/spm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
46554,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2010/spm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
46555,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2010/spm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
46556,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2010/spm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
46557,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2011/spm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
46558,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2011/spm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
46559,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2011/spm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
46560,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2011/spm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
46561,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2011/spm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
46562,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2011/spm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
46563,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2011/spm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
46564,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2011/spm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
46565,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2012/spm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
46566,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2012/spm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
46567,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2012/spm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
46568,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2012/spm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
46569,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2012/spm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
46570,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2012/spm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
46571,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2012/spm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
46572,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2012/spm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
46573,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2013/spm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
46574,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2013/spm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
46575,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2013/spm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
46576,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2013/spm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
46577,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2013/spm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
46578,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2013/spm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
46579,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2013/spm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
46580,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2013/spm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
46581,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2014/spm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
46582,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2014/spm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
46583,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2014/spm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
46584,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2014/spm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
46585,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2014/spm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
46586,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2014/spm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
46587,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2014/spm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
46588,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2014/spm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
46589,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2015/spm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
46590,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2015/spm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
46591,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2015/spm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
46592,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2015/spm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
46593,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2015/spm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
46594,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2015/spm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
46595,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2015/spm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
46596,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Annual/2015/spm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
46597,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2000/vct_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
46598,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2000/vct_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
46599,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2000/vct_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
46600,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2000/vct_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
46601,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2000/vct_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
46602,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2000/vct_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
46603,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2000/vct_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
46604,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2000/vct_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
46605,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2001/vct_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
46606,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2001/vct_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
46607,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2001/vct_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
46608,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2001/vct_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
46609,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2001/vct_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
46610,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2001/vct_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
46611,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2001/vct_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
46612,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2001/vct_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
46613,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2002/vct_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
46614,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2002/vct_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
46615,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2002/vct_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
46616,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2002/vct_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
46617,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2002/vct_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
46618,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2002/vct_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
46619,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2002/vct_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
46620,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2002/vct_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
46621,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2003/vct_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
46622,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2003/vct_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
46623,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2003/vct_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
46624,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2003/vct_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
46625,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2003/vct_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
46626,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2003/vct_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
46627,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2003/vct_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
46628,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2003/vct_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
46629,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2004/vct_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
46630,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2004/vct_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
46631,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2004/vct_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
46632,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2004/vct_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
46633,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2004/vct_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
46634,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2004/vct_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
46635,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2004/vct_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
46636,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2004/vct_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
46637,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2005/vct_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
46638,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2005/vct_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
46639,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2005/vct_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
46640,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2005/vct_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
46641,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2005/vct_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
46642,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2005/vct_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
46643,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2005/vct_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
46644,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2005/vct_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
46645,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2006/vct_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
46646,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2006/vct_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
46647,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2006/vct_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
46648,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2006/vct_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
46649,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2006/vct_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
46650,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2006/vct_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
46651,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2006/vct_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
46652,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2006/vct_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
46653,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2007/vct_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
46654,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2007/vct_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
46655,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2007/vct_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
46656,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2007/vct_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
46657,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2007/vct_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
46658,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2007/vct_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
46659,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2007/vct_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
46660,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2007/vct_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
46661,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2008/vct_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
46662,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2008/vct_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
46663,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2008/vct_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
46664,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2008/vct_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
46665,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2008/vct_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
46666,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2008/vct_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
46667,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2008/vct_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
46668,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2008/vct_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
46669,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2009/vct_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
46670,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2009/vct_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
46671,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2009/vct_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
46672,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2009/vct_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
46673,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2009/vct_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
46674,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2009/vct_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
46675,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2009/vct_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
46676,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2009/vct_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
46677,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2010/vct_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
46678,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2010/vct_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
46679,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2010/vct_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
46680,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2010/vct_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
46681,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2010/vct_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
46682,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2010/vct_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
46683,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2010/vct_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
46684,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2010/vct_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
46685,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2011/vct_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
46686,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2011/vct_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
46687,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2011/vct_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
46688,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2011/vct_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
46689,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2011/vct_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
46690,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2011/vct_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
46691,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2011/vct_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
46692,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2011/vct_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
46693,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2012/vct_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
46694,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2012/vct_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
46695,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2012/vct_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
46696,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2012/vct_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
46697,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2012/vct_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
46698,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2012/vct_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
46699,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2012/vct_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
46700,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2012/vct_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
46701,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2013/vct_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
46702,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2013/vct_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
46703,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2013/vct_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
46704,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2013/vct_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
46705,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2013/vct_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
46706,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2013/vct_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
46707,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2013/vct_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
46708,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2013/vct_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
46709,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2014/vct_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
46710,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2014/vct_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
46711,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2014/vct_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
46712,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2014/vct_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
46713,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2014/vct_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
46714,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2014/vct_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
46715,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2014/vct_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
46716,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2014/vct_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
46717,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2015/vct_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
46718,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2015/vct_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
46719,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2015/vct_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
46720,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2015/vct_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
46721,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2015/vct_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
46722,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2015/vct_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
46723,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2015/vct_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
46724,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Annual/2015/vct_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
46725,674,"SMR","San Marino","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2000/smr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
46726,674,"SMR","San Marino","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2000/smr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
46727,674,"SMR","San Marino","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2000/smr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
46728,674,"SMR","San Marino","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2000/smr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
46729,674,"SMR","San Marino","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2000/smr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
46730,674,"SMR","San Marino","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2000/smr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
46731,674,"SMR","San Marino","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2000/smr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
46732,674,"SMR","San Marino","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2000/smr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
46733,674,"SMR","San Marino","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2001/smr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
46734,674,"SMR","San Marino","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2001/smr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
46735,674,"SMR","San Marino","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2001/smr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
46736,674,"SMR","San Marino","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2001/smr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
46737,674,"SMR","San Marino","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2001/smr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
46738,674,"SMR","San Marino","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2001/smr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
46739,674,"SMR","San Marino","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2001/smr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
46740,674,"SMR","San Marino","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2001/smr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
46741,674,"SMR","San Marino","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2002/smr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
46742,674,"SMR","San Marino","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2002/smr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
46743,674,"SMR","San Marino","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2002/smr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
46744,674,"SMR","San Marino","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2002/smr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
46745,674,"SMR","San Marino","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2002/smr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
46746,674,"SMR","San Marino","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2002/smr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
46747,674,"SMR","San Marino","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2002/smr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
46748,674,"SMR","San Marino","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2002/smr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
46749,674,"SMR","San Marino","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2003/smr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
46750,674,"SMR","San Marino","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2003/smr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
46751,674,"SMR","San Marino","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2003/smr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
46752,674,"SMR","San Marino","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2003/smr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
46753,674,"SMR","San Marino","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2003/smr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
46754,674,"SMR","San Marino","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2003/smr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
46755,674,"SMR","San Marino","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2003/smr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
46756,674,"SMR","San Marino","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2003/smr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
46757,674,"SMR","San Marino","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2004/smr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
46758,674,"SMR","San Marino","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2004/smr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
46759,674,"SMR","San Marino","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2004/smr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
46760,674,"SMR","San Marino","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2004/smr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
46761,674,"SMR","San Marino","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2004/smr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
46762,674,"SMR","San Marino","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2004/smr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
46763,674,"SMR","San Marino","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2004/smr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
46764,674,"SMR","San Marino","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2004/smr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
46765,674,"SMR","San Marino","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2005/smr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
46766,674,"SMR","San Marino","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2005/smr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
46767,674,"SMR","San Marino","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2005/smr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
46768,674,"SMR","San Marino","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2005/smr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
46769,674,"SMR","San Marino","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2005/smr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
46770,674,"SMR","San Marino","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2005/smr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
46771,674,"SMR","San Marino","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2005/smr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
46772,674,"SMR","San Marino","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2005/smr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
46773,674,"SMR","San Marino","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2006/smr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
46774,674,"SMR","San Marino","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2006/smr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
46775,674,"SMR","San Marino","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2006/smr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
46776,674,"SMR","San Marino","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2006/smr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
46777,674,"SMR","San Marino","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2006/smr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
46778,674,"SMR","San Marino","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2006/smr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
46779,674,"SMR","San Marino","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2006/smr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
46780,674,"SMR","San Marino","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2006/smr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
46781,674,"SMR","San Marino","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2007/smr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
46782,674,"SMR","San Marino","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2007/smr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
46783,674,"SMR","San Marino","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2007/smr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
46784,674,"SMR","San Marino","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2007/smr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
46785,674,"SMR","San Marino","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2007/smr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
46786,674,"SMR","San Marino","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2007/smr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
46787,674,"SMR","San Marino","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2007/smr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
46788,674,"SMR","San Marino","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2007/smr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
46789,674,"SMR","San Marino","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2008/smr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
46790,674,"SMR","San Marino","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2008/smr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
46791,674,"SMR","San Marino","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2008/smr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
46792,674,"SMR","San Marino","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2008/smr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
46793,674,"SMR","San Marino","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2008/smr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
46794,674,"SMR","San Marino","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2008/smr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
46795,674,"SMR","San Marino","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2008/smr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
46796,674,"SMR","San Marino","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2008/smr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
46797,674,"SMR","San Marino","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2009/smr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
46798,674,"SMR","San Marino","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2009/smr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
46799,674,"SMR","San Marino","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2009/smr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
46800,674,"SMR","San Marino","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2009/smr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
46801,674,"SMR","San Marino","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2009/smr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
46802,674,"SMR","San Marino","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2009/smr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
46803,674,"SMR","San Marino","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2009/smr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
46804,674,"SMR","San Marino","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2009/smr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
46805,674,"SMR","San Marino","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2010/smr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
46806,674,"SMR","San Marino","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2010/smr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
46807,674,"SMR","San Marino","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2010/smr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
46808,674,"SMR","San Marino","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2010/smr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
46809,674,"SMR","San Marino","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2010/smr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
46810,674,"SMR","San Marino","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2010/smr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
46811,674,"SMR","San Marino","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2010/smr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
46812,674,"SMR","San Marino","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2010/smr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
46813,674,"SMR","San Marino","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2011/smr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
46814,674,"SMR","San Marino","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2011/smr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
46815,674,"SMR","San Marino","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2011/smr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
46816,674,"SMR","San Marino","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2011/smr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
46817,674,"SMR","San Marino","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2011/smr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
46818,674,"SMR","San Marino","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2011/smr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
46819,674,"SMR","San Marino","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2011/smr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
46820,674,"SMR","San Marino","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2011/smr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
46821,674,"SMR","San Marino","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2012/smr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
46822,674,"SMR","San Marino","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2012/smr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
46823,674,"SMR","San Marino","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2012/smr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
46824,674,"SMR","San Marino","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2012/smr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
46825,674,"SMR","San Marino","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2012/smr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
46826,674,"SMR","San Marino","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2012/smr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
46827,674,"SMR","San Marino","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2012/smr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
46828,674,"SMR","San Marino","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2012/smr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
46829,674,"SMR","San Marino","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2013/smr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
46830,674,"SMR","San Marino","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2013/smr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
46831,674,"SMR","San Marino","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2013/smr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
46832,674,"SMR","San Marino","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2013/smr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
46833,674,"SMR","San Marino","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2013/smr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
46834,674,"SMR","San Marino","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2013/smr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
46835,674,"SMR","San Marino","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2013/smr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
46836,674,"SMR","San Marino","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2013/smr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
46837,674,"SMR","San Marino","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2014/smr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
46838,674,"SMR","San Marino","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2014/smr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
46839,674,"SMR","San Marino","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2014/smr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
46840,674,"SMR","San Marino","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2014/smr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
46841,674,"SMR","San Marino","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2014/smr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
46842,674,"SMR","San Marino","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2014/smr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
46843,674,"SMR","San Marino","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2014/smr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
46844,674,"SMR","San Marino","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2014/smr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
46845,674,"SMR","San Marino","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2015/smr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
46846,674,"SMR","San Marino","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2015/smr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
46847,674,"SMR","San Marino","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2015/smr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
46848,674,"SMR","San Marino","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2015/smr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
46849,674,"SMR","San Marino","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2015/smr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
46850,674,"SMR","San Marino","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2015/smr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
46851,674,"SMR","San Marino","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2015/smr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
46852,674,"SMR","San Marino","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Annual/2015/smr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
46853,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2000/stp_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
46854,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2000/stp_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
46855,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2000/stp_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
46856,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2000/stp_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
46857,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2000/stp_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
46858,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2000/stp_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
46859,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2000/stp_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
46860,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2000/stp_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
46861,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2001/stp_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
46862,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2001/stp_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
46863,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2001/stp_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
46864,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2001/stp_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
46865,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2001/stp_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
46866,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2001/stp_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
46867,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2001/stp_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
46868,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2001/stp_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
46869,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2002/stp_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
46870,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2002/stp_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
46871,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2002/stp_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
46872,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2002/stp_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
46873,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2002/stp_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
46874,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2002/stp_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
46875,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2002/stp_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
46876,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2002/stp_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
46877,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2003/stp_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
46878,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2003/stp_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
46879,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2003/stp_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
46880,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2003/stp_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
46881,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2003/stp_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
46882,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2003/stp_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
46883,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2003/stp_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
46884,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2003/stp_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
46885,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2004/stp_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
46886,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2004/stp_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
46887,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2004/stp_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
46888,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2004/stp_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
46889,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2004/stp_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
46890,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2004/stp_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
46891,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2004/stp_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
46892,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2004/stp_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
46893,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2005/stp_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
46894,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2005/stp_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
46895,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2005/stp_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
46896,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2005/stp_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
46897,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2005/stp_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
46898,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2005/stp_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
46899,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2005/stp_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
46900,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2005/stp_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
46901,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2006/stp_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
46902,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2006/stp_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
46903,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2006/stp_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
46904,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2006/stp_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
46905,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2006/stp_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
46906,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2006/stp_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
46907,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2006/stp_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
46908,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2006/stp_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
46909,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2007/stp_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
46910,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2007/stp_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
46911,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2007/stp_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
46912,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2007/stp_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
46913,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2007/stp_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
46914,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2007/stp_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
46915,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2007/stp_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
46916,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2007/stp_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
46917,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2008/stp_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
46918,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2008/stp_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
46919,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2008/stp_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
46920,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2008/stp_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
46921,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2008/stp_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
46922,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2008/stp_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
46923,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2008/stp_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
46924,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2008/stp_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
46925,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2009/stp_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
46926,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2009/stp_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
46927,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2009/stp_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
46928,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2009/stp_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
46929,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2009/stp_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
46930,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2009/stp_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
46931,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2009/stp_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
46932,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2009/stp_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
46933,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2010/stp_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
46934,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2010/stp_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
46935,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2010/stp_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
46936,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2010/stp_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
46937,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2010/stp_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
46938,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2010/stp_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
46939,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2010/stp_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
46940,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2010/stp_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
46941,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2011/stp_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
46942,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2011/stp_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
46943,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2011/stp_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
46944,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2011/stp_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
46945,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2011/stp_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
46946,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2011/stp_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
46947,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2011/stp_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
46948,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2011/stp_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
46949,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2012/stp_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
46950,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2012/stp_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
46951,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2012/stp_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
46952,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2012/stp_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
46953,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2012/stp_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
46954,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2012/stp_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
46955,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2012/stp_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
46956,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2012/stp_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
46957,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2013/stp_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
46958,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2013/stp_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
46959,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2013/stp_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
46960,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2013/stp_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
46961,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2013/stp_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
46962,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2013/stp_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
46963,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2013/stp_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
46964,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2013/stp_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
46965,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2014/stp_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
46966,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2014/stp_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
46967,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2014/stp_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
46968,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2014/stp_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
46969,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2014/stp_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
46970,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2014/stp_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
46971,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2014/stp_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
46972,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2014/stp_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
46973,678,"STP","Sao Tome and Principe","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2015/stp_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
46974,678,"STP","Sao Tome and Principe","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2015/stp_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
46975,678,"STP","Sao Tome and Principe","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2015/stp_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
46976,678,"STP","Sao Tome and Principe","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2015/stp_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
46977,678,"STP","Sao Tome and Principe","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2015/stp_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
46978,678,"STP","Sao Tome and Principe","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2015/stp_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
46979,678,"STP","Sao Tome and Principe","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2015/stp_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
46980,678,"STP","Sao Tome and Principe","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Annual/2015/stp_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
46981,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2000/sau_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
46982,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2000/sau_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
46983,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2000/sau_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
46984,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2000/sau_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
46985,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2000/sau_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
46986,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2000/sau_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
46987,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2000/sau_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
46988,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2000/sau_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
46989,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2001/sau_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
46990,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2001/sau_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
46991,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2001/sau_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
46992,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2001/sau_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
46993,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2001/sau_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
46994,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2001/sau_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
46995,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2001/sau_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
46996,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2001/sau_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
46997,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2002/sau_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
46998,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2002/sau_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
46999,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2002/sau_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
47000,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2002/sau_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
47001,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2002/sau_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
47002,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2002/sau_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
47003,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2002/sau_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
47004,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2002/sau_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
47005,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2003/sau_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
47006,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2003/sau_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
47007,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2003/sau_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
47008,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2003/sau_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
47009,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2003/sau_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
47010,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2003/sau_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
47011,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2003/sau_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
47012,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2003/sau_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
47013,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2004/sau_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
47014,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2004/sau_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
47015,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2004/sau_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
47016,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2004/sau_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
47017,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2004/sau_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
47018,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2004/sau_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
47019,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2004/sau_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
47020,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2004/sau_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
47021,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2005/sau_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
47022,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2005/sau_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
47023,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2005/sau_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
47024,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2005/sau_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
47025,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2005/sau_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
47026,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2005/sau_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
47027,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2005/sau_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
47028,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2005/sau_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
47029,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2006/sau_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
47030,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2006/sau_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
47031,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2006/sau_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
47032,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2006/sau_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
47033,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2006/sau_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
47034,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2006/sau_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
47035,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2006/sau_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
47036,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2006/sau_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
47037,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2007/sau_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
47038,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2007/sau_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
47039,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2007/sau_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
47040,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2007/sau_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
47041,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2007/sau_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
47042,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2007/sau_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
47043,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2007/sau_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
47044,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2007/sau_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
47045,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2008/sau_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
47046,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2008/sau_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
47047,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2008/sau_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
47048,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2008/sau_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
47049,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2008/sau_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
47050,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2008/sau_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
47051,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2008/sau_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
47052,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2008/sau_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
47053,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2009/sau_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
47054,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2009/sau_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
47055,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2009/sau_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
47056,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2009/sau_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
47057,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2009/sau_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
47058,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2009/sau_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
47059,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2009/sau_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
47060,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2009/sau_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
47061,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2010/sau_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
47062,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2010/sau_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
47063,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2010/sau_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
47064,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2010/sau_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
47065,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2010/sau_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
47066,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2010/sau_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
47067,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2010/sau_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
47068,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2010/sau_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
47069,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2011/sau_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
47070,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2011/sau_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
47071,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2011/sau_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
47072,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2011/sau_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
47073,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2011/sau_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
47074,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2011/sau_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
47075,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2011/sau_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
47076,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2011/sau_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
47077,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2012/sau_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
47078,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2012/sau_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
47079,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2012/sau_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
47080,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2012/sau_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
47081,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2012/sau_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
47082,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2012/sau_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
47083,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2012/sau_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
47084,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2012/sau_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
47085,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2013/sau_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
47086,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2013/sau_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
47087,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2013/sau_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
47088,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2013/sau_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
47089,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2013/sau_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
47090,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2013/sau_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
47091,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2013/sau_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
47092,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2013/sau_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
47093,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2014/sau_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
47094,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2014/sau_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
47095,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2014/sau_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
47096,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2014/sau_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
47097,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2014/sau_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
47098,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2014/sau_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
47099,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2014/sau_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
47100,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2014/sau_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
47101,682,"SAU","Saudi Arabia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2015/sau_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
47102,682,"SAU","Saudi Arabia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2015/sau_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
47103,682,"SAU","Saudi Arabia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2015/sau_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
47104,682,"SAU","Saudi Arabia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2015/sau_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
47105,682,"SAU","Saudi Arabia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2015/sau_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
47106,682,"SAU","Saudi Arabia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2015/sau_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
47107,682,"SAU","Saudi Arabia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2015/sau_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
47108,682,"SAU","Saudi Arabia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Annual/2015/sau_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
47109,686,"SEN","Senegal","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2000/sen_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
47110,686,"SEN","Senegal","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2000/sen_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
47111,686,"SEN","Senegal","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2000/sen_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
47112,686,"SEN","Senegal","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2000/sen_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
47113,686,"SEN","Senegal","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2000/sen_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
47114,686,"SEN","Senegal","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2000/sen_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
47115,686,"SEN","Senegal","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2000/sen_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
47116,686,"SEN","Senegal","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2000/sen_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
47117,686,"SEN","Senegal","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2001/sen_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
47118,686,"SEN","Senegal","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2001/sen_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
47119,686,"SEN","Senegal","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2001/sen_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
47120,686,"SEN","Senegal","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2001/sen_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
47121,686,"SEN","Senegal","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2001/sen_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
47122,686,"SEN","Senegal","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2001/sen_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
47123,686,"SEN","Senegal","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2001/sen_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
47124,686,"SEN","Senegal","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2001/sen_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
47125,686,"SEN","Senegal","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2002/sen_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
47126,686,"SEN","Senegal","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2002/sen_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
47127,686,"SEN","Senegal","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2002/sen_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
47128,686,"SEN","Senegal","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2002/sen_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
47129,686,"SEN","Senegal","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2002/sen_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
47130,686,"SEN","Senegal","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2002/sen_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
47131,686,"SEN","Senegal","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2002/sen_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
47132,686,"SEN","Senegal","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2002/sen_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
47133,686,"SEN","Senegal","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2003/sen_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
47134,686,"SEN","Senegal","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2003/sen_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
47135,686,"SEN","Senegal","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2003/sen_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
47136,686,"SEN","Senegal","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2003/sen_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
47137,686,"SEN","Senegal","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2003/sen_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
47138,686,"SEN","Senegal","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2003/sen_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
47139,686,"SEN","Senegal","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2003/sen_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
47140,686,"SEN","Senegal","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2003/sen_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
47141,686,"SEN","Senegal","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2004/sen_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
47142,686,"SEN","Senegal","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2004/sen_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
47143,686,"SEN","Senegal","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2004/sen_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
47144,686,"SEN","Senegal","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2004/sen_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
47145,686,"SEN","Senegal","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2004/sen_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
47146,686,"SEN","Senegal","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2004/sen_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
47147,686,"SEN","Senegal","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2004/sen_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
47148,686,"SEN","Senegal","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2004/sen_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
47149,686,"SEN","Senegal","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2005/sen_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
47150,686,"SEN","Senegal","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2005/sen_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
47151,686,"SEN","Senegal","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2005/sen_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
47152,686,"SEN","Senegal","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2005/sen_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
47153,686,"SEN","Senegal","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2005/sen_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
47154,686,"SEN","Senegal","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2005/sen_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
47155,686,"SEN","Senegal","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2005/sen_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
47156,686,"SEN","Senegal","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2005/sen_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
47157,686,"SEN","Senegal","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2006/sen_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
47158,686,"SEN","Senegal","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2006/sen_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
47159,686,"SEN","Senegal","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2006/sen_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
47160,686,"SEN","Senegal","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2006/sen_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
47161,686,"SEN","Senegal","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2006/sen_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
47162,686,"SEN","Senegal","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2006/sen_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
47163,686,"SEN","Senegal","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2006/sen_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
47164,686,"SEN","Senegal","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2006/sen_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
47165,686,"SEN","Senegal","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2007/sen_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
47166,686,"SEN","Senegal","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2007/sen_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
47167,686,"SEN","Senegal","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2007/sen_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
47168,686,"SEN","Senegal","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2007/sen_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
47169,686,"SEN","Senegal","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2007/sen_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
47170,686,"SEN","Senegal","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2007/sen_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
47171,686,"SEN","Senegal","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2007/sen_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
47172,686,"SEN","Senegal","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2007/sen_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
47173,686,"SEN","Senegal","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2008/sen_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
47174,686,"SEN","Senegal","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2008/sen_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
47175,686,"SEN","Senegal","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2008/sen_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
47176,686,"SEN","Senegal","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2008/sen_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
47177,686,"SEN","Senegal","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2008/sen_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
47178,686,"SEN","Senegal","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2008/sen_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
47179,686,"SEN","Senegal","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2008/sen_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
47180,686,"SEN","Senegal","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2008/sen_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
47181,686,"SEN","Senegal","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2009/sen_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
47182,686,"SEN","Senegal","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2009/sen_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
47183,686,"SEN","Senegal","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2009/sen_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
47184,686,"SEN","Senegal","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2009/sen_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
47185,686,"SEN","Senegal","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2009/sen_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
47186,686,"SEN","Senegal","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2009/sen_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
47187,686,"SEN","Senegal","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2009/sen_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
47188,686,"SEN","Senegal","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2009/sen_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
47189,686,"SEN","Senegal","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2010/sen_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
47190,686,"SEN","Senegal","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2010/sen_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
47191,686,"SEN","Senegal","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2010/sen_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
47192,686,"SEN","Senegal","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2010/sen_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
47193,686,"SEN","Senegal","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2010/sen_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
47194,686,"SEN","Senegal","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2010/sen_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
47195,686,"SEN","Senegal","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2010/sen_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
47196,686,"SEN","Senegal","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2010/sen_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
47197,686,"SEN","Senegal","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2011/sen_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
47198,686,"SEN","Senegal","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2011/sen_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
47199,686,"SEN","Senegal","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2011/sen_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
47200,686,"SEN","Senegal","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2011/sen_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
47201,686,"SEN","Senegal","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2011/sen_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
47202,686,"SEN","Senegal","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2011/sen_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
47203,686,"SEN","Senegal","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2011/sen_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
47204,686,"SEN","Senegal","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2011/sen_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
47205,686,"SEN","Senegal","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2012/sen_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
47206,686,"SEN","Senegal","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2012/sen_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
47207,686,"SEN","Senegal","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2012/sen_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
47208,686,"SEN","Senegal","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2012/sen_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
47209,686,"SEN","Senegal","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2012/sen_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
47210,686,"SEN","Senegal","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2012/sen_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
47211,686,"SEN","Senegal","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2012/sen_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
47212,686,"SEN","Senegal","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2012/sen_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
47213,686,"SEN","Senegal","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2013/sen_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
47214,686,"SEN","Senegal","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2013/sen_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
47215,686,"SEN","Senegal","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2013/sen_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
47216,686,"SEN","Senegal","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2013/sen_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
47217,686,"SEN","Senegal","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2013/sen_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
47218,686,"SEN","Senegal","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2013/sen_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
47219,686,"SEN","Senegal","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2013/sen_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
47220,686,"SEN","Senegal","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2013/sen_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
47221,686,"SEN","Senegal","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2014/sen_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
47222,686,"SEN","Senegal","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2014/sen_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
47223,686,"SEN","Senegal","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2014/sen_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
47224,686,"SEN","Senegal","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2014/sen_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
47225,686,"SEN","Senegal","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2014/sen_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
47226,686,"SEN","Senegal","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2014/sen_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
47227,686,"SEN","Senegal","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2014/sen_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
47228,686,"SEN","Senegal","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2014/sen_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
47229,686,"SEN","Senegal","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2015/sen_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
47230,686,"SEN","Senegal","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2015/sen_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
47231,686,"SEN","Senegal","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2015/sen_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
47232,686,"SEN","Senegal","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2015/sen_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
47233,686,"SEN","Senegal","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2015/sen_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
47234,686,"SEN","Senegal","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2015/sen_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
47235,686,"SEN","Senegal","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2015/sen_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
47236,686,"SEN","Senegal","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Annual/2015/sen_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
47237,688,"SRB","Serbia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2000/srb_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
47238,688,"SRB","Serbia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2000/srb_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
47239,688,"SRB","Serbia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2000/srb_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
47240,688,"SRB","Serbia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2000/srb_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
47241,688,"SRB","Serbia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2000/srb_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
47242,688,"SRB","Serbia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2000/srb_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
47243,688,"SRB","Serbia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2000/srb_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
47244,688,"SRB","Serbia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2000/srb_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
47245,688,"SRB","Serbia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2001/srb_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
47246,688,"SRB","Serbia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2001/srb_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
47247,688,"SRB","Serbia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2001/srb_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
47248,688,"SRB","Serbia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2001/srb_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
47249,688,"SRB","Serbia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2001/srb_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
47250,688,"SRB","Serbia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2001/srb_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
47251,688,"SRB","Serbia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2001/srb_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
47252,688,"SRB","Serbia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2001/srb_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
47253,688,"SRB","Serbia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2002/srb_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
47254,688,"SRB","Serbia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2002/srb_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
47255,688,"SRB","Serbia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2002/srb_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
47256,688,"SRB","Serbia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2002/srb_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
47257,688,"SRB","Serbia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2002/srb_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
47258,688,"SRB","Serbia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2002/srb_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
47259,688,"SRB","Serbia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2002/srb_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
47260,688,"SRB","Serbia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2002/srb_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
47261,688,"SRB","Serbia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2003/srb_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
47262,688,"SRB","Serbia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2003/srb_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
47263,688,"SRB","Serbia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2003/srb_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
47264,688,"SRB","Serbia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2003/srb_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
47265,688,"SRB","Serbia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2003/srb_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
47266,688,"SRB","Serbia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2003/srb_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
47267,688,"SRB","Serbia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2003/srb_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
47268,688,"SRB","Serbia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2003/srb_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
47269,688,"SRB","Serbia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2004/srb_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
47270,688,"SRB","Serbia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2004/srb_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
47271,688,"SRB","Serbia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2004/srb_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
47272,688,"SRB","Serbia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2004/srb_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
47273,688,"SRB","Serbia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2004/srb_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
47274,688,"SRB","Serbia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2004/srb_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
47275,688,"SRB","Serbia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2004/srb_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
47276,688,"SRB","Serbia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2004/srb_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
47277,688,"SRB","Serbia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2005/srb_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
47278,688,"SRB","Serbia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2005/srb_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
47279,688,"SRB","Serbia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2005/srb_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
47280,688,"SRB","Serbia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2005/srb_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
47281,688,"SRB","Serbia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2005/srb_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
47282,688,"SRB","Serbia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2005/srb_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
47283,688,"SRB","Serbia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2005/srb_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
47284,688,"SRB","Serbia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2005/srb_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
47285,688,"SRB","Serbia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2006/srb_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
47286,688,"SRB","Serbia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2006/srb_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
47287,688,"SRB","Serbia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2006/srb_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
47288,688,"SRB","Serbia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2006/srb_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
47289,688,"SRB","Serbia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2006/srb_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
47290,688,"SRB","Serbia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2006/srb_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
47291,688,"SRB","Serbia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2006/srb_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
47292,688,"SRB","Serbia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2006/srb_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
47293,688,"SRB","Serbia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2007/srb_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
47294,688,"SRB","Serbia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2007/srb_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
47295,688,"SRB","Serbia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2007/srb_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
47296,688,"SRB","Serbia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2007/srb_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
47297,688,"SRB","Serbia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2007/srb_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
47298,688,"SRB","Serbia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2007/srb_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
47299,688,"SRB","Serbia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2007/srb_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
47300,688,"SRB","Serbia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2007/srb_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
47301,688,"SRB","Serbia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2008/srb_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
47302,688,"SRB","Serbia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2008/srb_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
47303,688,"SRB","Serbia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2008/srb_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
47304,688,"SRB","Serbia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2008/srb_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
47305,688,"SRB","Serbia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2008/srb_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
47306,688,"SRB","Serbia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2008/srb_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
47307,688,"SRB","Serbia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2008/srb_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
47308,688,"SRB","Serbia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2008/srb_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
47309,688,"SRB","Serbia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2009/srb_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
47310,688,"SRB","Serbia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2009/srb_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
47311,688,"SRB","Serbia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2009/srb_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
47312,688,"SRB","Serbia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2009/srb_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
47313,688,"SRB","Serbia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2009/srb_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
47314,688,"SRB","Serbia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2009/srb_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
47315,688,"SRB","Serbia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2009/srb_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
47316,688,"SRB","Serbia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2009/srb_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
47317,688,"SRB","Serbia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2010/srb_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
47318,688,"SRB","Serbia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2010/srb_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
47319,688,"SRB","Serbia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2010/srb_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
47320,688,"SRB","Serbia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2010/srb_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
47321,688,"SRB","Serbia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2010/srb_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
47322,688,"SRB","Serbia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2010/srb_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
47323,688,"SRB","Serbia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2010/srb_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
47324,688,"SRB","Serbia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2010/srb_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
47325,688,"SRB","Serbia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2011/srb_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
47326,688,"SRB","Serbia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2011/srb_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
47327,688,"SRB","Serbia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2011/srb_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
47328,688,"SRB","Serbia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2011/srb_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
47329,688,"SRB","Serbia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2011/srb_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
47330,688,"SRB","Serbia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2011/srb_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
47331,688,"SRB","Serbia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2011/srb_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
47332,688,"SRB","Serbia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2011/srb_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
47333,688,"SRB","Serbia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2012/srb_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
47334,688,"SRB","Serbia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2012/srb_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
47335,688,"SRB","Serbia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2012/srb_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
47336,688,"SRB","Serbia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2012/srb_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
47337,688,"SRB","Serbia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2012/srb_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
47338,688,"SRB","Serbia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2012/srb_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
47339,688,"SRB","Serbia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2012/srb_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
47340,688,"SRB","Serbia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2012/srb_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
47341,688,"SRB","Serbia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2013/srb_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
47342,688,"SRB","Serbia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2013/srb_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
47343,688,"SRB","Serbia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2013/srb_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
47344,688,"SRB","Serbia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2013/srb_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
47345,688,"SRB","Serbia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2013/srb_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
47346,688,"SRB","Serbia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2013/srb_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
47347,688,"SRB","Serbia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2013/srb_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
47348,688,"SRB","Serbia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2013/srb_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
47349,688,"SRB","Serbia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2014/srb_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
47350,688,"SRB","Serbia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2014/srb_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
47351,688,"SRB","Serbia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2014/srb_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
47352,688,"SRB","Serbia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2014/srb_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
47353,688,"SRB","Serbia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2014/srb_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
47354,688,"SRB","Serbia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2014/srb_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
47355,688,"SRB","Serbia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2014/srb_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
47356,688,"SRB","Serbia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2014/srb_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
47357,688,"SRB","Serbia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2015/srb_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
47358,688,"SRB","Serbia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2015/srb_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
47359,688,"SRB","Serbia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2015/srb_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
47360,688,"SRB","Serbia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2015/srb_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
47361,688,"SRB","Serbia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2015/srb_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
47362,688,"SRB","Serbia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2015/srb_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
47363,688,"SRB","Serbia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2015/srb_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
47364,688,"SRB","Serbia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Annual/2015/srb_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
47365,690,"SYC","Seychelles","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2000/syc_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
47366,690,"SYC","Seychelles","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2000/syc_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
47367,690,"SYC","Seychelles","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2000/syc_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
47368,690,"SYC","Seychelles","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2000/syc_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
47369,690,"SYC","Seychelles","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2000/syc_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
47370,690,"SYC","Seychelles","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2000/syc_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
47371,690,"SYC","Seychelles","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2000/syc_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
47372,690,"SYC","Seychelles","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2000/syc_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
47373,690,"SYC","Seychelles","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2001/syc_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
47374,690,"SYC","Seychelles","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2001/syc_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
47375,690,"SYC","Seychelles","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2001/syc_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
47376,690,"SYC","Seychelles","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2001/syc_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
47377,690,"SYC","Seychelles","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2001/syc_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
47378,690,"SYC","Seychelles","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2001/syc_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
47379,690,"SYC","Seychelles","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2001/syc_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
47380,690,"SYC","Seychelles","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2001/syc_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
47381,690,"SYC","Seychelles","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2002/syc_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
47382,690,"SYC","Seychelles","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2002/syc_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
47383,690,"SYC","Seychelles","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2002/syc_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
47384,690,"SYC","Seychelles","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2002/syc_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
47385,690,"SYC","Seychelles","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2002/syc_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
47386,690,"SYC","Seychelles","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2002/syc_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
47387,690,"SYC","Seychelles","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2002/syc_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
47388,690,"SYC","Seychelles","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2002/syc_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
47389,690,"SYC","Seychelles","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2003/syc_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
47390,690,"SYC","Seychelles","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2003/syc_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
47391,690,"SYC","Seychelles","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2003/syc_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
47392,690,"SYC","Seychelles","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2003/syc_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
47393,690,"SYC","Seychelles","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2003/syc_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
47394,690,"SYC","Seychelles","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2003/syc_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
47395,690,"SYC","Seychelles","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2003/syc_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
47396,690,"SYC","Seychelles","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2003/syc_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
47397,690,"SYC","Seychelles","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2004/syc_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
47398,690,"SYC","Seychelles","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2004/syc_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
47399,690,"SYC","Seychelles","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2004/syc_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
47400,690,"SYC","Seychelles","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2004/syc_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
47401,690,"SYC","Seychelles","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2004/syc_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
47402,690,"SYC","Seychelles","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2004/syc_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
47403,690,"SYC","Seychelles","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2004/syc_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
47404,690,"SYC","Seychelles","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2004/syc_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
47405,690,"SYC","Seychelles","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2005/syc_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
47406,690,"SYC","Seychelles","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2005/syc_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
47407,690,"SYC","Seychelles","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2005/syc_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
47408,690,"SYC","Seychelles","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2005/syc_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
47409,690,"SYC","Seychelles","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2005/syc_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
47410,690,"SYC","Seychelles","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2005/syc_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
47411,690,"SYC","Seychelles","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2005/syc_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
47412,690,"SYC","Seychelles","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2005/syc_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
47413,690,"SYC","Seychelles","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2006/syc_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
47414,690,"SYC","Seychelles","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2006/syc_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
47415,690,"SYC","Seychelles","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2006/syc_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
47416,690,"SYC","Seychelles","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2006/syc_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
47417,690,"SYC","Seychelles","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2006/syc_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
47418,690,"SYC","Seychelles","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2006/syc_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
47419,690,"SYC","Seychelles","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2006/syc_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
47420,690,"SYC","Seychelles","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2006/syc_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
47421,690,"SYC","Seychelles","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2007/syc_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
47422,690,"SYC","Seychelles","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2007/syc_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
47423,690,"SYC","Seychelles","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2007/syc_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
47424,690,"SYC","Seychelles","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2007/syc_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
47425,690,"SYC","Seychelles","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2007/syc_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
47426,690,"SYC","Seychelles","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2007/syc_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
47427,690,"SYC","Seychelles","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2007/syc_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
47428,690,"SYC","Seychelles","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2007/syc_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
47429,690,"SYC","Seychelles","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2008/syc_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
47430,690,"SYC","Seychelles","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2008/syc_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
47431,690,"SYC","Seychelles","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2008/syc_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
47432,690,"SYC","Seychelles","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2008/syc_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
47433,690,"SYC","Seychelles","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2008/syc_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
47434,690,"SYC","Seychelles","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2008/syc_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
47435,690,"SYC","Seychelles","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2008/syc_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
47436,690,"SYC","Seychelles","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2008/syc_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
47437,690,"SYC","Seychelles","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2009/syc_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
47438,690,"SYC","Seychelles","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2009/syc_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
47439,690,"SYC","Seychelles","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2009/syc_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
47440,690,"SYC","Seychelles","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2009/syc_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
47441,690,"SYC","Seychelles","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2009/syc_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
47442,690,"SYC","Seychelles","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2009/syc_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
47443,690,"SYC","Seychelles","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2009/syc_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
47444,690,"SYC","Seychelles","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2009/syc_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
47445,690,"SYC","Seychelles","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2010/syc_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
47446,690,"SYC","Seychelles","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2010/syc_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
47447,690,"SYC","Seychelles","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2010/syc_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
47448,690,"SYC","Seychelles","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2010/syc_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
47449,690,"SYC","Seychelles","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2010/syc_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
47450,690,"SYC","Seychelles","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2010/syc_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
47451,690,"SYC","Seychelles","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2010/syc_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
47452,690,"SYC","Seychelles","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2010/syc_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
47453,690,"SYC","Seychelles","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2011/syc_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
47454,690,"SYC","Seychelles","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2011/syc_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
47455,690,"SYC","Seychelles","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2011/syc_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
47456,690,"SYC","Seychelles","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2011/syc_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
47457,690,"SYC","Seychelles","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2011/syc_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
47458,690,"SYC","Seychelles","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2011/syc_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
47459,690,"SYC","Seychelles","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2011/syc_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
47460,690,"SYC","Seychelles","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2011/syc_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
47461,690,"SYC","Seychelles","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2012/syc_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
47462,690,"SYC","Seychelles","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2012/syc_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
47463,690,"SYC","Seychelles","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2012/syc_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
47464,690,"SYC","Seychelles","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2012/syc_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
47465,690,"SYC","Seychelles","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2012/syc_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
47466,690,"SYC","Seychelles","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2012/syc_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
47467,690,"SYC","Seychelles","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2012/syc_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
47468,690,"SYC","Seychelles","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2012/syc_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
47469,690,"SYC","Seychelles","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2013/syc_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
47470,690,"SYC","Seychelles","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2013/syc_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
47471,690,"SYC","Seychelles","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2013/syc_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
47472,690,"SYC","Seychelles","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2013/syc_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
47473,690,"SYC","Seychelles","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2013/syc_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
47474,690,"SYC","Seychelles","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2013/syc_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
47475,690,"SYC","Seychelles","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2013/syc_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
47476,690,"SYC","Seychelles","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2013/syc_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
47477,690,"SYC","Seychelles","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2014/syc_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
47478,690,"SYC","Seychelles","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2014/syc_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
47479,690,"SYC","Seychelles","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2014/syc_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
47480,690,"SYC","Seychelles","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2014/syc_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
47481,690,"SYC","Seychelles","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2014/syc_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
47482,690,"SYC","Seychelles","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2014/syc_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
47483,690,"SYC","Seychelles","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2014/syc_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
47484,690,"SYC","Seychelles","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2014/syc_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
47485,690,"SYC","Seychelles","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2015/syc_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
47486,690,"SYC","Seychelles","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2015/syc_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
47487,690,"SYC","Seychelles","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2015/syc_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
47488,690,"SYC","Seychelles","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2015/syc_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
47489,690,"SYC","Seychelles","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2015/syc_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
47490,690,"SYC","Seychelles","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2015/syc_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
47491,690,"SYC","Seychelles","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2015/syc_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
47492,690,"SYC","Seychelles","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Annual/2015/syc_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
47493,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2000/sle_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
47494,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2000/sle_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
47495,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2000/sle_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
47496,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2000/sle_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
47497,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2000/sle_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
47498,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2000/sle_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
47499,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2000/sle_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
47500,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2000/sle_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
47501,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2001/sle_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
47502,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2001/sle_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
47503,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2001/sle_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
47504,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2001/sle_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
47505,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2001/sle_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
47506,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2001/sle_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
47507,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2001/sle_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
47508,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2001/sle_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
47509,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2002/sle_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
47510,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2002/sle_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
47511,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2002/sle_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
47512,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2002/sle_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
47513,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2002/sle_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
47514,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2002/sle_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
47515,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2002/sle_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
47516,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2002/sle_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
47517,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2003/sle_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
47518,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2003/sle_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
47519,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2003/sle_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
47520,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2003/sle_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
47521,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2003/sle_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
47522,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2003/sle_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
47523,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2003/sle_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
47524,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2003/sle_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
47525,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2004/sle_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
47526,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2004/sle_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
47527,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2004/sle_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
47528,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2004/sle_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
47529,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2004/sle_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
47530,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2004/sle_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
47531,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2004/sle_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
47532,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2004/sle_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
47533,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2005/sle_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
47534,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2005/sle_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
47535,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2005/sle_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
47536,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2005/sle_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
47537,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2005/sle_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
47538,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2005/sle_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
47539,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2005/sle_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
47540,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2005/sle_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
47541,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2006/sle_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
47542,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2006/sle_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
47543,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2006/sle_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
47544,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2006/sle_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
47545,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2006/sle_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
47546,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2006/sle_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
47547,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2006/sle_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
47548,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2006/sle_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
47549,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2007/sle_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
47550,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2007/sle_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
47551,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2007/sle_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
47552,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2007/sle_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
47553,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2007/sle_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
47554,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2007/sle_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
47555,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2007/sle_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
47556,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2007/sle_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
47557,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2008/sle_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
47558,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2008/sle_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
47559,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2008/sle_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
47560,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2008/sle_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
47561,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2008/sle_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
47562,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2008/sle_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
47563,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2008/sle_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
47564,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2008/sle_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
47565,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2009/sle_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
47566,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2009/sle_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
47567,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2009/sle_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
47568,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2009/sle_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
47569,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2009/sle_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
47570,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2009/sle_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
47571,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2009/sle_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
47572,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2009/sle_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
47573,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2010/sle_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
47574,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2010/sle_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
47575,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2010/sle_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
47576,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2010/sle_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
47577,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2010/sle_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
47578,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2010/sle_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
47579,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2010/sle_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
47580,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2010/sle_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
47581,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2011/sle_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
47582,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2011/sle_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
47583,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2011/sle_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
47584,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2011/sle_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
47585,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2011/sle_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
47586,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2011/sle_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
47587,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2011/sle_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
47588,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2011/sle_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
47589,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2012/sle_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
47590,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2012/sle_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
47591,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2012/sle_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
47592,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2012/sle_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
47593,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2012/sle_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
47594,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2012/sle_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
47595,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2012/sle_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
47596,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2012/sle_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
47597,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2013/sle_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
47598,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2013/sle_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
47599,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2013/sle_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
47600,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2013/sle_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
47601,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2013/sle_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
47602,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2013/sle_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
47603,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2013/sle_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
47604,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2013/sle_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
47605,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2014/sle_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
47606,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2014/sle_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
47607,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2014/sle_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
47608,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2014/sle_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
47609,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2014/sle_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
47610,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2014/sle_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
47611,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2014/sle_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
47612,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2014/sle_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
47613,694,"SLE","Sierra Leone","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2015/sle_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
47614,694,"SLE","Sierra Leone","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2015/sle_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
47615,694,"SLE","Sierra Leone","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2015/sle_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
47616,694,"SLE","Sierra Leone","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2015/sle_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
47617,694,"SLE","Sierra Leone","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2015/sle_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
47618,694,"SLE","Sierra Leone","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2015/sle_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
47619,694,"SLE","Sierra Leone","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2015/sle_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
47620,694,"SLE","Sierra Leone","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Annual/2015/sle_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
47621,702,"SGP","Singapore","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2000/sgp_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
47622,702,"SGP","Singapore","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2000/sgp_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
47623,702,"SGP","Singapore","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2000/sgp_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
47624,702,"SGP","Singapore","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2000/sgp_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
47625,702,"SGP","Singapore","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2000/sgp_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
47626,702,"SGP","Singapore","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2000/sgp_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
47627,702,"SGP","Singapore","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2000/sgp_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
47628,702,"SGP","Singapore","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2000/sgp_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
47629,702,"SGP","Singapore","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2001/sgp_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
47630,702,"SGP","Singapore","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2001/sgp_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
47631,702,"SGP","Singapore","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2001/sgp_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
47632,702,"SGP","Singapore","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2001/sgp_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
47633,702,"SGP","Singapore","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2001/sgp_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
47634,702,"SGP","Singapore","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2001/sgp_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
47635,702,"SGP","Singapore","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2001/sgp_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
47636,702,"SGP","Singapore","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2001/sgp_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
47637,702,"SGP","Singapore","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2002/sgp_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
47638,702,"SGP","Singapore","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2002/sgp_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
47639,702,"SGP","Singapore","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2002/sgp_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
47640,702,"SGP","Singapore","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2002/sgp_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
47641,702,"SGP","Singapore","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2002/sgp_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
47642,702,"SGP","Singapore","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2002/sgp_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
47643,702,"SGP","Singapore","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2002/sgp_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
47644,702,"SGP","Singapore","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2002/sgp_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
47645,702,"SGP","Singapore","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2003/sgp_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
47646,702,"SGP","Singapore","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2003/sgp_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
47647,702,"SGP","Singapore","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2003/sgp_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
47648,702,"SGP","Singapore","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2003/sgp_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
47649,702,"SGP","Singapore","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2003/sgp_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
47650,702,"SGP","Singapore","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2003/sgp_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
47651,702,"SGP","Singapore","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2003/sgp_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
47652,702,"SGP","Singapore","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2003/sgp_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
47653,702,"SGP","Singapore","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2004/sgp_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
47654,702,"SGP","Singapore","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2004/sgp_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
47655,702,"SGP","Singapore","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2004/sgp_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
47656,702,"SGP","Singapore","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2004/sgp_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
47657,702,"SGP","Singapore","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2004/sgp_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
47658,702,"SGP","Singapore","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2004/sgp_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
47659,702,"SGP","Singapore","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2004/sgp_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
47660,702,"SGP","Singapore","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2004/sgp_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
47661,702,"SGP","Singapore","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2005/sgp_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
47662,702,"SGP","Singapore","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2005/sgp_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
47663,702,"SGP","Singapore","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2005/sgp_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
47664,702,"SGP","Singapore","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2005/sgp_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
47665,702,"SGP","Singapore","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2005/sgp_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
47666,702,"SGP","Singapore","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2005/sgp_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
47667,702,"SGP","Singapore","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2005/sgp_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
47668,702,"SGP","Singapore","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2005/sgp_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
47669,702,"SGP","Singapore","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2006/sgp_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
47670,702,"SGP","Singapore","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2006/sgp_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
47671,702,"SGP","Singapore","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2006/sgp_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
47672,702,"SGP","Singapore","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2006/sgp_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
47673,702,"SGP","Singapore","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2006/sgp_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
47674,702,"SGP","Singapore","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2006/sgp_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
47675,702,"SGP","Singapore","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2006/sgp_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
47676,702,"SGP","Singapore","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2006/sgp_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
47677,702,"SGP","Singapore","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2007/sgp_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
47678,702,"SGP","Singapore","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2007/sgp_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
47679,702,"SGP","Singapore","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2007/sgp_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
47680,702,"SGP","Singapore","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2007/sgp_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
47681,702,"SGP","Singapore","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2007/sgp_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
47682,702,"SGP","Singapore","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2007/sgp_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
47683,702,"SGP","Singapore","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2007/sgp_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
47684,702,"SGP","Singapore","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2007/sgp_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
47685,702,"SGP","Singapore","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2008/sgp_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
47686,702,"SGP","Singapore","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2008/sgp_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
47687,702,"SGP","Singapore","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2008/sgp_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
47688,702,"SGP","Singapore","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2008/sgp_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
47689,702,"SGP","Singapore","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2008/sgp_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
47690,702,"SGP","Singapore","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2008/sgp_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
47691,702,"SGP","Singapore","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2008/sgp_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
47692,702,"SGP","Singapore","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2008/sgp_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
47693,702,"SGP","Singapore","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2009/sgp_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
47694,702,"SGP","Singapore","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2009/sgp_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
47695,702,"SGP","Singapore","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2009/sgp_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
47696,702,"SGP","Singapore","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2009/sgp_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
47697,702,"SGP","Singapore","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2009/sgp_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
47698,702,"SGP","Singapore","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2009/sgp_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
47699,702,"SGP","Singapore","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2009/sgp_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
47700,702,"SGP","Singapore","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2009/sgp_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
47701,702,"SGP","Singapore","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2010/sgp_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
47702,702,"SGP","Singapore","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2010/sgp_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
47703,702,"SGP","Singapore","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2010/sgp_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
47704,702,"SGP","Singapore","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2010/sgp_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
47705,702,"SGP","Singapore","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2010/sgp_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
47706,702,"SGP","Singapore","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2010/sgp_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
47707,702,"SGP","Singapore","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2010/sgp_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
47708,702,"SGP","Singapore","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2010/sgp_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
47709,702,"SGP","Singapore","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2011/sgp_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
47710,702,"SGP","Singapore","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2011/sgp_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
47711,702,"SGP","Singapore","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2011/sgp_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
47712,702,"SGP","Singapore","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2011/sgp_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
47713,702,"SGP","Singapore","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2011/sgp_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
47714,702,"SGP","Singapore","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2011/sgp_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
47715,702,"SGP","Singapore","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2011/sgp_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
47716,702,"SGP","Singapore","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2011/sgp_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
47717,702,"SGP","Singapore","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2012/sgp_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
47718,702,"SGP","Singapore","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2012/sgp_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
47719,702,"SGP","Singapore","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2012/sgp_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
47720,702,"SGP","Singapore","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2012/sgp_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
47721,702,"SGP","Singapore","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2012/sgp_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
47722,702,"SGP","Singapore","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2012/sgp_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
47723,702,"SGP","Singapore","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2012/sgp_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
47724,702,"SGP","Singapore","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2012/sgp_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
47725,702,"SGP","Singapore","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2013/sgp_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
47726,702,"SGP","Singapore","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2013/sgp_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
47727,702,"SGP","Singapore","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2013/sgp_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
47728,702,"SGP","Singapore","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2013/sgp_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
47729,702,"SGP","Singapore","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2013/sgp_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
47730,702,"SGP","Singapore","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2013/sgp_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
47731,702,"SGP","Singapore","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2013/sgp_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
47732,702,"SGP","Singapore","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2013/sgp_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
47733,702,"SGP","Singapore","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2014/sgp_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
47734,702,"SGP","Singapore","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2014/sgp_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
47735,702,"SGP","Singapore","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2014/sgp_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
47736,702,"SGP","Singapore","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2014/sgp_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
47737,702,"SGP","Singapore","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2014/sgp_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
47738,702,"SGP","Singapore","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2014/sgp_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
47739,702,"SGP","Singapore","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2014/sgp_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
47740,702,"SGP","Singapore","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2014/sgp_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
47741,702,"SGP","Singapore","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2015/sgp_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
47742,702,"SGP","Singapore","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2015/sgp_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
47743,702,"SGP","Singapore","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2015/sgp_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
47744,702,"SGP","Singapore","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2015/sgp_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
47745,702,"SGP","Singapore","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2015/sgp_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
47746,702,"SGP","Singapore","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2015/sgp_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
47747,702,"SGP","Singapore","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2015/sgp_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
47748,702,"SGP","Singapore","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Annual/2015/sgp_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
47749,703,"SVK","Slovakia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2000/svk_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
47750,703,"SVK","Slovakia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2000/svk_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
47751,703,"SVK","Slovakia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2000/svk_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
47752,703,"SVK","Slovakia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2000/svk_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
47753,703,"SVK","Slovakia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2000/svk_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
47754,703,"SVK","Slovakia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2000/svk_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
47755,703,"SVK","Slovakia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2000/svk_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
47756,703,"SVK","Slovakia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2000/svk_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
47757,703,"SVK","Slovakia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2001/svk_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
47758,703,"SVK","Slovakia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2001/svk_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
47759,703,"SVK","Slovakia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2001/svk_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
47760,703,"SVK","Slovakia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2001/svk_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
47761,703,"SVK","Slovakia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2001/svk_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
47762,703,"SVK","Slovakia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2001/svk_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
47763,703,"SVK","Slovakia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2001/svk_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
47764,703,"SVK","Slovakia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2001/svk_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
47765,703,"SVK","Slovakia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2002/svk_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
47766,703,"SVK","Slovakia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2002/svk_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
47767,703,"SVK","Slovakia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2002/svk_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
47768,703,"SVK","Slovakia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2002/svk_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
47769,703,"SVK","Slovakia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2002/svk_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
47770,703,"SVK","Slovakia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2002/svk_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
47771,703,"SVK","Slovakia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2002/svk_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
47772,703,"SVK","Slovakia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2002/svk_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
47773,703,"SVK","Slovakia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2003/svk_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
47774,703,"SVK","Slovakia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2003/svk_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
47775,703,"SVK","Slovakia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2003/svk_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
47776,703,"SVK","Slovakia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2003/svk_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
47777,703,"SVK","Slovakia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2003/svk_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
47778,703,"SVK","Slovakia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2003/svk_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
47779,703,"SVK","Slovakia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2003/svk_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
47780,703,"SVK","Slovakia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2003/svk_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
47781,703,"SVK","Slovakia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2004/svk_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
47782,703,"SVK","Slovakia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2004/svk_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
47783,703,"SVK","Slovakia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2004/svk_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
47784,703,"SVK","Slovakia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2004/svk_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
47785,703,"SVK","Slovakia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2004/svk_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
47786,703,"SVK","Slovakia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2004/svk_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
47787,703,"SVK","Slovakia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2004/svk_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
47788,703,"SVK","Slovakia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2004/svk_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
47789,703,"SVK","Slovakia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2005/svk_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
47790,703,"SVK","Slovakia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2005/svk_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
47791,703,"SVK","Slovakia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2005/svk_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
47792,703,"SVK","Slovakia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2005/svk_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
47793,703,"SVK","Slovakia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2005/svk_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
47794,703,"SVK","Slovakia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2005/svk_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
47795,703,"SVK","Slovakia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2005/svk_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
47796,703,"SVK","Slovakia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2005/svk_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
47797,703,"SVK","Slovakia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2006/svk_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
47798,703,"SVK","Slovakia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2006/svk_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
47799,703,"SVK","Slovakia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2006/svk_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
47800,703,"SVK","Slovakia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2006/svk_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
47801,703,"SVK","Slovakia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2006/svk_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
47802,703,"SVK","Slovakia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2006/svk_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
47803,703,"SVK","Slovakia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2006/svk_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
47804,703,"SVK","Slovakia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2006/svk_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
47805,703,"SVK","Slovakia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2007/svk_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
47806,703,"SVK","Slovakia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2007/svk_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
47807,703,"SVK","Slovakia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2007/svk_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
47808,703,"SVK","Slovakia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2007/svk_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
47809,703,"SVK","Slovakia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2007/svk_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
47810,703,"SVK","Slovakia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2007/svk_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
47811,703,"SVK","Slovakia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2007/svk_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
47812,703,"SVK","Slovakia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2007/svk_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
47813,703,"SVK","Slovakia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2008/svk_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
47814,703,"SVK","Slovakia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2008/svk_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
47815,703,"SVK","Slovakia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2008/svk_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
47816,703,"SVK","Slovakia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2008/svk_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
47817,703,"SVK","Slovakia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2008/svk_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
47818,703,"SVK","Slovakia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2008/svk_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
47819,703,"SVK","Slovakia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2008/svk_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
47820,703,"SVK","Slovakia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2008/svk_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
47821,703,"SVK","Slovakia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2009/svk_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
47822,703,"SVK","Slovakia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2009/svk_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
47823,703,"SVK","Slovakia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2009/svk_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
47824,703,"SVK","Slovakia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2009/svk_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
47825,703,"SVK","Slovakia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2009/svk_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
47826,703,"SVK","Slovakia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2009/svk_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
47827,703,"SVK","Slovakia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2009/svk_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
47828,703,"SVK","Slovakia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2009/svk_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
47829,703,"SVK","Slovakia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2010/svk_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
47830,703,"SVK","Slovakia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2010/svk_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
47831,703,"SVK","Slovakia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2010/svk_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
47832,703,"SVK","Slovakia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2010/svk_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
47833,703,"SVK","Slovakia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2010/svk_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
47834,703,"SVK","Slovakia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2010/svk_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
47835,703,"SVK","Slovakia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2010/svk_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
47836,703,"SVK","Slovakia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2010/svk_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
47837,703,"SVK","Slovakia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2011/svk_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
47838,703,"SVK","Slovakia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2011/svk_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
47839,703,"SVK","Slovakia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2011/svk_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
47840,703,"SVK","Slovakia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2011/svk_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
47841,703,"SVK","Slovakia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2011/svk_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
47842,703,"SVK","Slovakia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2011/svk_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
47843,703,"SVK","Slovakia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2011/svk_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
47844,703,"SVK","Slovakia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2011/svk_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
47845,703,"SVK","Slovakia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2012/svk_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
47846,703,"SVK","Slovakia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2012/svk_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
47847,703,"SVK","Slovakia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2012/svk_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
47848,703,"SVK","Slovakia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2012/svk_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
47849,703,"SVK","Slovakia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2012/svk_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
47850,703,"SVK","Slovakia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2012/svk_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
47851,703,"SVK","Slovakia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2012/svk_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
47852,703,"SVK","Slovakia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2012/svk_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
47853,703,"SVK","Slovakia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2013/svk_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
47854,703,"SVK","Slovakia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2013/svk_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
47855,703,"SVK","Slovakia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2013/svk_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
47856,703,"SVK","Slovakia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2013/svk_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
47857,703,"SVK","Slovakia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2013/svk_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
47858,703,"SVK","Slovakia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2013/svk_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
47859,703,"SVK","Slovakia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2013/svk_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
47860,703,"SVK","Slovakia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2013/svk_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
47861,703,"SVK","Slovakia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2014/svk_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
47862,703,"SVK","Slovakia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2014/svk_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
47863,703,"SVK","Slovakia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2014/svk_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
47864,703,"SVK","Slovakia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2014/svk_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
47865,703,"SVK","Slovakia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2014/svk_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
47866,703,"SVK","Slovakia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2014/svk_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
47867,703,"SVK","Slovakia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2014/svk_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
47868,703,"SVK","Slovakia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2014/svk_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
47869,703,"SVK","Slovakia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2015/svk_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
47870,703,"SVK","Slovakia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2015/svk_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
47871,703,"SVK","Slovakia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2015/svk_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
47872,703,"SVK","Slovakia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2015/svk_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
47873,703,"SVK","Slovakia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2015/svk_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
47874,703,"SVK","Slovakia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2015/svk_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
47875,703,"SVK","Slovakia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2015/svk_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
47876,703,"SVK","Slovakia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Annual/2015/svk_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
47877,704,"VNM","Vietnam","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2000/vnm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
47878,704,"VNM","Vietnam","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2000/vnm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
47879,704,"VNM","Vietnam","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2000/vnm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
47880,704,"VNM","Vietnam","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2000/vnm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
47881,704,"VNM","Vietnam","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2000/vnm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
47882,704,"VNM","Vietnam","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2000/vnm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
47883,704,"VNM","Vietnam","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2000/vnm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
47884,704,"VNM","Vietnam","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2000/vnm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
47885,704,"VNM","Vietnam","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2001/vnm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
47886,704,"VNM","Vietnam","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2001/vnm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
47887,704,"VNM","Vietnam","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2001/vnm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
47888,704,"VNM","Vietnam","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2001/vnm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
47889,704,"VNM","Vietnam","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2001/vnm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
47890,704,"VNM","Vietnam","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2001/vnm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
47891,704,"VNM","Vietnam","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2001/vnm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
47892,704,"VNM","Vietnam","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2001/vnm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
47893,704,"VNM","Vietnam","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2002/vnm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
47894,704,"VNM","Vietnam","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2002/vnm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
47895,704,"VNM","Vietnam","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2002/vnm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
47896,704,"VNM","Vietnam","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2002/vnm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
47897,704,"VNM","Vietnam","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2002/vnm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
47898,704,"VNM","Vietnam","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2002/vnm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
47899,704,"VNM","Vietnam","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2002/vnm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
47900,704,"VNM","Vietnam","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2002/vnm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
47901,704,"VNM","Vietnam","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2003/vnm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
47902,704,"VNM","Vietnam","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2003/vnm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
47903,704,"VNM","Vietnam","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2003/vnm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
47904,704,"VNM","Vietnam","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2003/vnm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
47905,704,"VNM","Vietnam","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2003/vnm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
47906,704,"VNM","Vietnam","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2003/vnm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
47907,704,"VNM","Vietnam","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2003/vnm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
47908,704,"VNM","Vietnam","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2003/vnm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
47909,704,"VNM","Vietnam","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2004/vnm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
47910,704,"VNM","Vietnam","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2004/vnm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
47911,704,"VNM","Vietnam","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2004/vnm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
47912,704,"VNM","Vietnam","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2004/vnm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
47913,704,"VNM","Vietnam","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2004/vnm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
47914,704,"VNM","Vietnam","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2004/vnm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
47915,704,"VNM","Vietnam","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2004/vnm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
47916,704,"VNM","Vietnam","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2004/vnm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
47917,704,"VNM","Vietnam","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2005/vnm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
47918,704,"VNM","Vietnam","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2005/vnm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
47919,704,"VNM","Vietnam","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2005/vnm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
47920,704,"VNM","Vietnam","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2005/vnm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
47921,704,"VNM","Vietnam","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2005/vnm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
47922,704,"VNM","Vietnam","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2005/vnm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
47923,704,"VNM","Vietnam","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2005/vnm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
47924,704,"VNM","Vietnam","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2005/vnm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
47925,704,"VNM","Vietnam","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2006/vnm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
47926,704,"VNM","Vietnam","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2006/vnm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
47927,704,"VNM","Vietnam","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2006/vnm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
47928,704,"VNM","Vietnam","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2006/vnm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
47929,704,"VNM","Vietnam","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2006/vnm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
47930,704,"VNM","Vietnam","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2006/vnm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
47931,704,"VNM","Vietnam","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2006/vnm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
47932,704,"VNM","Vietnam","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2006/vnm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
47933,704,"VNM","Vietnam","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2007/vnm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
47934,704,"VNM","Vietnam","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2007/vnm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
47935,704,"VNM","Vietnam","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2007/vnm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
47936,704,"VNM","Vietnam","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2007/vnm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
47937,704,"VNM","Vietnam","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2007/vnm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
47938,704,"VNM","Vietnam","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2007/vnm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
47939,704,"VNM","Vietnam","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2007/vnm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
47940,704,"VNM","Vietnam","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2007/vnm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
47941,704,"VNM","Vietnam","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2008/vnm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
47942,704,"VNM","Vietnam","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2008/vnm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
47943,704,"VNM","Vietnam","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2008/vnm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
47944,704,"VNM","Vietnam","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2008/vnm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
47945,704,"VNM","Vietnam","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2008/vnm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
47946,704,"VNM","Vietnam","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2008/vnm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
47947,704,"VNM","Vietnam","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2008/vnm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
47948,704,"VNM","Vietnam","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2008/vnm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
47949,704,"VNM","Vietnam","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2009/vnm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
47950,704,"VNM","Vietnam","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2009/vnm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
47951,704,"VNM","Vietnam","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2009/vnm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
47952,704,"VNM","Vietnam","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2009/vnm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
47953,704,"VNM","Vietnam","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2009/vnm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
47954,704,"VNM","Vietnam","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2009/vnm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
47955,704,"VNM","Vietnam","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2009/vnm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
47956,704,"VNM","Vietnam","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2009/vnm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
47957,704,"VNM","Vietnam","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2010/vnm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
47958,704,"VNM","Vietnam","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2010/vnm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
47959,704,"VNM","Vietnam","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2010/vnm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
47960,704,"VNM","Vietnam","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2010/vnm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
47961,704,"VNM","Vietnam","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2010/vnm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
47962,704,"VNM","Vietnam","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2010/vnm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
47963,704,"VNM","Vietnam","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2010/vnm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
47964,704,"VNM","Vietnam","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2010/vnm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
47965,704,"VNM","Vietnam","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2011/vnm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
47966,704,"VNM","Vietnam","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2011/vnm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
47967,704,"VNM","Vietnam","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2011/vnm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
47968,704,"VNM","Vietnam","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2011/vnm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
47969,704,"VNM","Vietnam","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2011/vnm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
47970,704,"VNM","Vietnam","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2011/vnm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
47971,704,"VNM","Vietnam","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2011/vnm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
47972,704,"VNM","Vietnam","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2011/vnm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
47973,704,"VNM","Vietnam","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2012/vnm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
47974,704,"VNM","Vietnam","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2012/vnm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
47975,704,"VNM","Vietnam","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2012/vnm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
47976,704,"VNM","Vietnam","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2012/vnm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
47977,704,"VNM","Vietnam","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2012/vnm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
47978,704,"VNM","Vietnam","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2012/vnm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
47979,704,"VNM","Vietnam","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2012/vnm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
47980,704,"VNM","Vietnam","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2012/vnm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
47981,704,"VNM","Vietnam","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2013/vnm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
47982,704,"VNM","Vietnam","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2013/vnm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
47983,704,"VNM","Vietnam","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2013/vnm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
47984,704,"VNM","Vietnam","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2013/vnm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
47985,704,"VNM","Vietnam","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2013/vnm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
47986,704,"VNM","Vietnam","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2013/vnm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
47987,704,"VNM","Vietnam","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2013/vnm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
47988,704,"VNM","Vietnam","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2013/vnm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
47989,704,"VNM","Vietnam","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2014/vnm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
47990,704,"VNM","Vietnam","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2014/vnm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
47991,704,"VNM","Vietnam","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2014/vnm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
47992,704,"VNM","Vietnam","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2014/vnm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
47993,704,"VNM","Vietnam","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2014/vnm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
47994,704,"VNM","Vietnam","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2014/vnm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
47995,704,"VNM","Vietnam","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2014/vnm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
47996,704,"VNM","Vietnam","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2014/vnm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
47997,704,"VNM","Vietnam","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2015/vnm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
47998,704,"VNM","Vietnam","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2015/vnm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
47999,704,"VNM","Vietnam","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2015/vnm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
48000,704,"VNM","Vietnam","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2015/vnm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
48001,704,"VNM","Vietnam","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2015/vnm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
48002,704,"VNM","Vietnam","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2015/vnm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
48003,704,"VNM","Vietnam","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2015/vnm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
48004,704,"VNM","Vietnam","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Annual/2015/vnm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
48005,705,"SVN","Slovenia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2000/svn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
48006,705,"SVN","Slovenia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2000/svn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
48007,705,"SVN","Slovenia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2000/svn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
48008,705,"SVN","Slovenia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2000/svn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
48009,705,"SVN","Slovenia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2000/svn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
48010,705,"SVN","Slovenia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2000/svn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
48011,705,"SVN","Slovenia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2000/svn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
48012,705,"SVN","Slovenia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2000/svn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
48013,705,"SVN","Slovenia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2001/svn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
48014,705,"SVN","Slovenia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2001/svn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
48015,705,"SVN","Slovenia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2001/svn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
48016,705,"SVN","Slovenia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2001/svn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
48017,705,"SVN","Slovenia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2001/svn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
48018,705,"SVN","Slovenia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2001/svn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
48019,705,"SVN","Slovenia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2001/svn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
48020,705,"SVN","Slovenia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2001/svn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
48021,705,"SVN","Slovenia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2002/svn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
48022,705,"SVN","Slovenia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2002/svn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
48023,705,"SVN","Slovenia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2002/svn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
48024,705,"SVN","Slovenia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2002/svn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
48025,705,"SVN","Slovenia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2002/svn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
48026,705,"SVN","Slovenia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2002/svn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
48027,705,"SVN","Slovenia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2002/svn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
48028,705,"SVN","Slovenia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2002/svn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
48029,705,"SVN","Slovenia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2003/svn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
48030,705,"SVN","Slovenia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2003/svn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
48031,705,"SVN","Slovenia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2003/svn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
48032,705,"SVN","Slovenia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2003/svn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
48033,705,"SVN","Slovenia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2003/svn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
48034,705,"SVN","Slovenia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2003/svn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
48035,705,"SVN","Slovenia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2003/svn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
48036,705,"SVN","Slovenia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2003/svn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
48037,705,"SVN","Slovenia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2004/svn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
48038,705,"SVN","Slovenia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2004/svn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
48039,705,"SVN","Slovenia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2004/svn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
48040,705,"SVN","Slovenia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2004/svn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
48041,705,"SVN","Slovenia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2004/svn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
48042,705,"SVN","Slovenia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2004/svn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
48043,705,"SVN","Slovenia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2004/svn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
48044,705,"SVN","Slovenia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2004/svn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
48045,705,"SVN","Slovenia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2005/svn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
48046,705,"SVN","Slovenia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2005/svn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
48047,705,"SVN","Slovenia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2005/svn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
48048,705,"SVN","Slovenia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2005/svn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
48049,705,"SVN","Slovenia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2005/svn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
48050,705,"SVN","Slovenia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2005/svn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
48051,705,"SVN","Slovenia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2005/svn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
48052,705,"SVN","Slovenia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2005/svn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
48053,705,"SVN","Slovenia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2006/svn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
48054,705,"SVN","Slovenia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2006/svn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
48055,705,"SVN","Slovenia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2006/svn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
48056,705,"SVN","Slovenia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2006/svn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
48057,705,"SVN","Slovenia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2006/svn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
48058,705,"SVN","Slovenia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2006/svn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
48059,705,"SVN","Slovenia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2006/svn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
48060,705,"SVN","Slovenia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2006/svn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
48061,705,"SVN","Slovenia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2007/svn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
48062,705,"SVN","Slovenia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2007/svn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
48063,705,"SVN","Slovenia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2007/svn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
48064,705,"SVN","Slovenia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2007/svn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
48065,705,"SVN","Slovenia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2007/svn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
48066,705,"SVN","Slovenia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2007/svn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
48067,705,"SVN","Slovenia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2007/svn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
48068,705,"SVN","Slovenia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2007/svn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
48069,705,"SVN","Slovenia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2008/svn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
48070,705,"SVN","Slovenia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2008/svn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
48071,705,"SVN","Slovenia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2008/svn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
48072,705,"SVN","Slovenia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2008/svn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
48073,705,"SVN","Slovenia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2008/svn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
48074,705,"SVN","Slovenia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2008/svn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
48075,705,"SVN","Slovenia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2008/svn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
48076,705,"SVN","Slovenia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2008/svn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
48077,705,"SVN","Slovenia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2009/svn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
48078,705,"SVN","Slovenia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2009/svn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
48079,705,"SVN","Slovenia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2009/svn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
48080,705,"SVN","Slovenia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2009/svn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
48081,705,"SVN","Slovenia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2009/svn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
48082,705,"SVN","Slovenia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2009/svn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
48083,705,"SVN","Slovenia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2009/svn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
48084,705,"SVN","Slovenia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2009/svn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
48085,705,"SVN","Slovenia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2010/svn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
48086,705,"SVN","Slovenia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2010/svn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
48087,705,"SVN","Slovenia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2010/svn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
48088,705,"SVN","Slovenia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2010/svn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
48089,705,"SVN","Slovenia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2010/svn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
48090,705,"SVN","Slovenia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2010/svn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
48091,705,"SVN","Slovenia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2010/svn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
48092,705,"SVN","Slovenia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2010/svn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
48093,705,"SVN","Slovenia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2011/svn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
48094,705,"SVN","Slovenia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2011/svn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
48095,705,"SVN","Slovenia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2011/svn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
48096,705,"SVN","Slovenia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2011/svn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
48097,705,"SVN","Slovenia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2011/svn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
48098,705,"SVN","Slovenia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2011/svn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
48099,705,"SVN","Slovenia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2011/svn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
48100,705,"SVN","Slovenia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2011/svn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
48101,705,"SVN","Slovenia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2012/svn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
48102,705,"SVN","Slovenia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2012/svn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
48103,705,"SVN","Slovenia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2012/svn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
48104,705,"SVN","Slovenia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2012/svn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
48105,705,"SVN","Slovenia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2012/svn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
48106,705,"SVN","Slovenia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2012/svn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
48107,705,"SVN","Slovenia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2012/svn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
48108,705,"SVN","Slovenia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2012/svn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
48109,705,"SVN","Slovenia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2013/svn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
48110,705,"SVN","Slovenia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2013/svn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
48111,705,"SVN","Slovenia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2013/svn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
48112,705,"SVN","Slovenia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2013/svn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
48113,705,"SVN","Slovenia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2013/svn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
48114,705,"SVN","Slovenia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2013/svn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
48115,705,"SVN","Slovenia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2013/svn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
48116,705,"SVN","Slovenia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2013/svn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
48117,705,"SVN","Slovenia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2014/svn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
48118,705,"SVN","Slovenia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2014/svn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
48119,705,"SVN","Slovenia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2014/svn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
48120,705,"SVN","Slovenia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2014/svn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
48121,705,"SVN","Slovenia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2014/svn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
48122,705,"SVN","Slovenia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2014/svn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
48123,705,"SVN","Slovenia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2014/svn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
48124,705,"SVN","Slovenia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2014/svn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
48125,705,"SVN","Slovenia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2015/svn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
48126,705,"SVN","Slovenia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2015/svn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
48127,705,"SVN","Slovenia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2015/svn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
48128,705,"SVN","Slovenia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2015/svn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
48129,705,"SVN","Slovenia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2015/svn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
48130,705,"SVN","Slovenia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2015/svn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
48131,705,"SVN","Slovenia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2015/svn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
48132,705,"SVN","Slovenia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Annual/2015/svn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
48133,706,"SOM","Somalia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2000/som_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
48134,706,"SOM","Somalia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2000/som_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
48135,706,"SOM","Somalia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2000/som_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
48136,706,"SOM","Somalia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2000/som_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
48137,706,"SOM","Somalia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2000/som_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
48138,706,"SOM","Somalia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2000/som_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
48139,706,"SOM","Somalia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2000/som_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
48140,706,"SOM","Somalia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2000/som_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
48141,706,"SOM","Somalia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2001/som_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
48142,706,"SOM","Somalia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2001/som_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
48143,706,"SOM","Somalia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2001/som_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
48144,706,"SOM","Somalia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2001/som_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
48145,706,"SOM","Somalia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2001/som_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
48146,706,"SOM","Somalia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2001/som_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
48147,706,"SOM","Somalia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2001/som_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
48148,706,"SOM","Somalia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2001/som_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
48149,706,"SOM","Somalia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2002/som_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
48150,706,"SOM","Somalia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2002/som_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
48151,706,"SOM","Somalia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2002/som_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
48152,706,"SOM","Somalia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2002/som_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
48153,706,"SOM","Somalia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2002/som_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
48154,706,"SOM","Somalia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2002/som_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
48155,706,"SOM","Somalia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2002/som_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
48156,706,"SOM","Somalia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2002/som_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
48157,706,"SOM","Somalia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2003/som_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
48158,706,"SOM","Somalia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2003/som_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
48159,706,"SOM","Somalia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2003/som_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
48160,706,"SOM","Somalia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2003/som_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
48161,706,"SOM","Somalia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2003/som_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
48162,706,"SOM","Somalia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2003/som_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
48163,706,"SOM","Somalia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2003/som_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
48164,706,"SOM","Somalia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2003/som_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
48165,706,"SOM","Somalia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2004/som_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
48166,706,"SOM","Somalia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2004/som_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
48167,706,"SOM","Somalia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2004/som_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
48168,706,"SOM","Somalia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2004/som_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
48169,706,"SOM","Somalia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2004/som_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
48170,706,"SOM","Somalia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2004/som_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
48171,706,"SOM","Somalia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2004/som_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
48172,706,"SOM","Somalia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2004/som_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
48173,706,"SOM","Somalia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2005/som_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
48174,706,"SOM","Somalia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2005/som_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
48175,706,"SOM","Somalia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2005/som_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
48176,706,"SOM","Somalia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2005/som_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
48177,706,"SOM","Somalia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2005/som_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
48178,706,"SOM","Somalia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2005/som_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
48179,706,"SOM","Somalia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2005/som_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
48180,706,"SOM","Somalia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2005/som_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
48181,706,"SOM","Somalia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2006/som_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
48182,706,"SOM","Somalia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2006/som_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
48183,706,"SOM","Somalia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2006/som_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
48184,706,"SOM","Somalia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2006/som_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
48185,706,"SOM","Somalia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2006/som_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
48186,706,"SOM","Somalia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2006/som_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
48187,706,"SOM","Somalia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2006/som_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
48188,706,"SOM","Somalia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2006/som_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
48189,706,"SOM","Somalia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2007/som_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
48190,706,"SOM","Somalia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2007/som_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
48191,706,"SOM","Somalia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2007/som_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
48192,706,"SOM","Somalia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2007/som_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
48193,706,"SOM","Somalia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2007/som_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
48194,706,"SOM","Somalia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2007/som_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
48195,706,"SOM","Somalia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2007/som_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
48196,706,"SOM","Somalia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2007/som_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
48197,706,"SOM","Somalia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2008/som_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
48198,706,"SOM","Somalia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2008/som_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
48199,706,"SOM","Somalia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2008/som_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
48200,706,"SOM","Somalia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2008/som_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
48201,706,"SOM","Somalia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2008/som_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
48202,706,"SOM","Somalia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2008/som_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
48203,706,"SOM","Somalia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2008/som_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
48204,706,"SOM","Somalia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2008/som_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
48205,706,"SOM","Somalia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2009/som_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
48206,706,"SOM","Somalia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2009/som_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
48207,706,"SOM","Somalia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2009/som_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
48208,706,"SOM","Somalia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2009/som_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
48209,706,"SOM","Somalia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2009/som_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
48210,706,"SOM","Somalia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2009/som_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
48211,706,"SOM","Somalia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2009/som_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
48212,706,"SOM","Somalia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2009/som_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
48213,706,"SOM","Somalia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2010/som_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
48214,706,"SOM","Somalia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2010/som_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
48215,706,"SOM","Somalia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2010/som_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
48216,706,"SOM","Somalia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2010/som_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
48217,706,"SOM","Somalia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2010/som_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
48218,706,"SOM","Somalia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2010/som_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
48219,706,"SOM","Somalia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2010/som_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
48220,706,"SOM","Somalia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2010/som_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
48221,706,"SOM","Somalia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2011/som_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
48222,706,"SOM","Somalia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2011/som_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
48223,706,"SOM","Somalia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2011/som_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
48224,706,"SOM","Somalia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2011/som_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
48225,706,"SOM","Somalia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2011/som_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
48226,706,"SOM","Somalia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2011/som_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
48227,706,"SOM","Somalia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2011/som_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
48228,706,"SOM","Somalia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2011/som_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
48229,706,"SOM","Somalia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2012/som_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
48230,706,"SOM","Somalia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2012/som_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
48231,706,"SOM","Somalia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2012/som_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
48232,706,"SOM","Somalia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2012/som_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
48233,706,"SOM","Somalia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2012/som_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
48234,706,"SOM","Somalia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2012/som_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
48235,706,"SOM","Somalia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2012/som_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
48236,706,"SOM","Somalia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2012/som_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
48237,706,"SOM","Somalia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2013/som_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
48238,706,"SOM","Somalia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2013/som_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
48239,706,"SOM","Somalia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2013/som_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
48240,706,"SOM","Somalia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2013/som_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
48241,706,"SOM","Somalia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2013/som_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
48242,706,"SOM","Somalia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2013/som_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
48243,706,"SOM","Somalia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2013/som_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
48244,706,"SOM","Somalia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2013/som_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
48245,706,"SOM","Somalia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2014/som_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
48246,706,"SOM","Somalia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2014/som_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
48247,706,"SOM","Somalia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2014/som_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
48248,706,"SOM","Somalia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2014/som_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
48249,706,"SOM","Somalia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2014/som_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
48250,706,"SOM","Somalia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2014/som_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
48251,706,"SOM","Somalia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2014/som_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
48252,706,"SOM","Somalia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2014/som_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
48253,706,"SOM","Somalia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2015/som_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
48254,706,"SOM","Somalia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2015/som_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
48255,706,"SOM","Somalia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2015/som_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
48256,706,"SOM","Somalia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2015/som_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
48257,706,"SOM","Somalia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2015/som_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
48258,706,"SOM","Somalia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2015/som_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
48259,706,"SOM","Somalia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2015/som_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
48260,706,"SOM","Somalia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Annual/2015/som_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
48261,710,"ZAF","South Africa","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2000/zaf_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
48262,710,"ZAF","South Africa","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2000/zaf_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
48263,710,"ZAF","South Africa","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2000/zaf_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
48264,710,"ZAF","South Africa","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2000/zaf_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
48265,710,"ZAF","South Africa","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2000/zaf_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
48266,710,"ZAF","South Africa","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2000/zaf_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
48267,710,"ZAF","South Africa","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2000/zaf_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
48268,710,"ZAF","South Africa","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2000/zaf_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
48269,710,"ZAF","South Africa","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2001/zaf_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
48270,710,"ZAF","South Africa","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2001/zaf_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
48271,710,"ZAF","South Africa","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2001/zaf_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
48272,710,"ZAF","South Africa","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2001/zaf_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
48273,710,"ZAF","South Africa","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2001/zaf_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
48274,710,"ZAF","South Africa","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2001/zaf_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
48275,710,"ZAF","South Africa","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2001/zaf_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
48276,710,"ZAF","South Africa","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2001/zaf_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
48277,710,"ZAF","South Africa","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2002/zaf_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
48278,710,"ZAF","South Africa","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2002/zaf_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
48279,710,"ZAF","South Africa","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2002/zaf_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
48280,710,"ZAF","South Africa","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2002/zaf_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
48281,710,"ZAF","South Africa","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2002/zaf_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
48282,710,"ZAF","South Africa","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2002/zaf_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
48283,710,"ZAF","South Africa","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2002/zaf_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
48284,710,"ZAF","South Africa","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2002/zaf_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
48285,710,"ZAF","South Africa","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2003/zaf_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
48286,710,"ZAF","South Africa","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2003/zaf_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
48287,710,"ZAF","South Africa","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2003/zaf_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
48288,710,"ZAF","South Africa","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2003/zaf_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
48289,710,"ZAF","South Africa","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2003/zaf_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
48290,710,"ZAF","South Africa","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2003/zaf_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
48291,710,"ZAF","South Africa","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2003/zaf_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
48292,710,"ZAF","South Africa","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2003/zaf_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
48293,710,"ZAF","South Africa","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2004/zaf_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
48294,710,"ZAF","South Africa","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2004/zaf_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
48295,710,"ZAF","South Africa","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2004/zaf_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
48296,710,"ZAF","South Africa","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2004/zaf_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
48297,710,"ZAF","South Africa","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2004/zaf_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
48298,710,"ZAF","South Africa","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2004/zaf_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
48299,710,"ZAF","South Africa","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2004/zaf_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
48300,710,"ZAF","South Africa","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2004/zaf_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
48301,710,"ZAF","South Africa","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2005/zaf_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
48302,710,"ZAF","South Africa","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2005/zaf_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
48303,710,"ZAF","South Africa","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2005/zaf_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
48304,710,"ZAF","South Africa","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2005/zaf_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
48305,710,"ZAF","South Africa","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2005/zaf_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
48306,710,"ZAF","South Africa","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2005/zaf_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
48307,710,"ZAF","South Africa","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2005/zaf_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
48308,710,"ZAF","South Africa","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2005/zaf_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
48309,710,"ZAF","South Africa","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2006/zaf_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
48310,710,"ZAF","South Africa","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2006/zaf_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
48311,710,"ZAF","South Africa","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2006/zaf_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
48312,710,"ZAF","South Africa","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2006/zaf_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
48313,710,"ZAF","South Africa","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2006/zaf_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
48314,710,"ZAF","South Africa","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2006/zaf_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
48315,710,"ZAF","South Africa","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2006/zaf_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
48316,710,"ZAF","South Africa","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2006/zaf_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
48317,710,"ZAF","South Africa","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2007/zaf_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
48318,710,"ZAF","South Africa","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2007/zaf_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
48319,710,"ZAF","South Africa","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2007/zaf_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
48320,710,"ZAF","South Africa","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2007/zaf_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
48321,710,"ZAF","South Africa","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2007/zaf_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
48322,710,"ZAF","South Africa","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2007/zaf_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
48323,710,"ZAF","South Africa","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2007/zaf_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
48324,710,"ZAF","South Africa","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2007/zaf_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
48325,710,"ZAF","South Africa","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2008/zaf_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
48326,710,"ZAF","South Africa","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2008/zaf_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
48327,710,"ZAF","South Africa","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2008/zaf_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
48328,710,"ZAF","South Africa","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2008/zaf_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
48329,710,"ZAF","South Africa","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2008/zaf_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
48330,710,"ZAF","South Africa","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2008/zaf_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
48331,710,"ZAF","South Africa","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2008/zaf_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
48332,710,"ZAF","South Africa","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2008/zaf_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
48333,710,"ZAF","South Africa","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2009/zaf_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
48334,710,"ZAF","South Africa","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2009/zaf_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
48335,710,"ZAF","South Africa","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2009/zaf_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
48336,710,"ZAF","South Africa","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2009/zaf_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
48337,710,"ZAF","South Africa","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2009/zaf_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
48338,710,"ZAF","South Africa","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2009/zaf_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
48339,710,"ZAF","South Africa","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2009/zaf_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
48340,710,"ZAF","South Africa","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2009/zaf_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
48341,710,"ZAF","South Africa","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2010/zaf_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
48342,710,"ZAF","South Africa","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2010/zaf_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
48343,710,"ZAF","South Africa","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2010/zaf_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
48344,710,"ZAF","South Africa","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2010/zaf_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
48345,710,"ZAF","South Africa","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2010/zaf_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
48346,710,"ZAF","South Africa","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2010/zaf_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
48347,710,"ZAF","South Africa","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2010/zaf_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
48348,710,"ZAF","South Africa","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2010/zaf_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
48349,710,"ZAF","South Africa","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2011/zaf_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
48350,710,"ZAF","South Africa","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2011/zaf_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
48351,710,"ZAF","South Africa","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2011/zaf_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
48352,710,"ZAF","South Africa","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2011/zaf_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
48353,710,"ZAF","South Africa","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2011/zaf_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
48354,710,"ZAF","South Africa","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2011/zaf_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
48355,710,"ZAF","South Africa","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2011/zaf_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
48356,710,"ZAF","South Africa","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2011/zaf_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
48357,710,"ZAF","South Africa","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2012/zaf_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
48358,710,"ZAF","South Africa","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2012/zaf_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
48359,710,"ZAF","South Africa","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2012/zaf_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
48360,710,"ZAF","South Africa","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2012/zaf_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
48361,710,"ZAF","South Africa","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2012/zaf_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
48362,710,"ZAF","South Africa","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2012/zaf_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
48363,710,"ZAF","South Africa","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2012/zaf_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
48364,710,"ZAF","South Africa","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2012/zaf_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
48365,710,"ZAF","South Africa","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2013/zaf_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
48366,710,"ZAF","South Africa","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2013/zaf_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
48367,710,"ZAF","South Africa","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2013/zaf_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
48368,710,"ZAF","South Africa","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2013/zaf_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
48369,710,"ZAF","South Africa","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2013/zaf_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
48370,710,"ZAF","South Africa","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2013/zaf_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
48371,710,"ZAF","South Africa","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2013/zaf_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
48372,710,"ZAF","South Africa","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2013/zaf_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
48373,710,"ZAF","South Africa","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2014/zaf_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
48374,710,"ZAF","South Africa","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2014/zaf_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
48375,710,"ZAF","South Africa","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2014/zaf_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
48376,710,"ZAF","South Africa","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2014/zaf_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
48377,710,"ZAF","South Africa","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2014/zaf_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
48378,710,"ZAF","South Africa","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2014/zaf_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
48379,710,"ZAF","South Africa","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2014/zaf_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
48380,710,"ZAF","South Africa","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2014/zaf_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
48381,710,"ZAF","South Africa","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2015/zaf_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
48382,710,"ZAF","South Africa","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2015/zaf_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
48383,710,"ZAF","South Africa","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2015/zaf_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
48384,710,"ZAF","South Africa","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2015/zaf_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
48385,710,"ZAF","South Africa","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2015/zaf_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
48386,710,"ZAF","South Africa","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2015/zaf_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
48387,710,"ZAF","South Africa","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2015/zaf_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
48388,710,"ZAF","South Africa","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Annual/2015/zaf_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
48389,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2000/zwe_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
48390,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2000/zwe_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
48391,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2000/zwe_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
48392,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2000/zwe_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
48393,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2000/zwe_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
48394,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2000/zwe_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
48395,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2000/zwe_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
48396,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2000/zwe_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
48397,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2001/zwe_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
48398,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2001/zwe_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
48399,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2001/zwe_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
48400,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2001/zwe_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
48401,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2001/zwe_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
48402,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2001/zwe_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
48403,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2001/zwe_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
48404,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2001/zwe_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
48405,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2002/zwe_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
48406,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2002/zwe_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
48407,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2002/zwe_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
48408,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2002/zwe_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
48409,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2002/zwe_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
48410,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2002/zwe_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
48411,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2002/zwe_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
48412,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2002/zwe_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
48413,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2003/zwe_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
48414,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2003/zwe_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
48415,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2003/zwe_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
48416,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2003/zwe_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
48417,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2003/zwe_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
48418,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2003/zwe_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
48419,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2003/zwe_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
48420,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2003/zwe_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
48421,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2004/zwe_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
48422,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2004/zwe_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
48423,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2004/zwe_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
48424,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2004/zwe_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
48425,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2004/zwe_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
48426,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2004/zwe_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
48427,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2004/zwe_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
48428,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2004/zwe_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
48429,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2005/zwe_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
48430,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2005/zwe_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
48431,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2005/zwe_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
48432,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2005/zwe_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
48433,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2005/zwe_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
48434,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2005/zwe_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
48435,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2005/zwe_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
48436,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2005/zwe_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
48437,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2006/zwe_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
48438,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2006/zwe_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
48439,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2006/zwe_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
48440,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2006/zwe_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
48441,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2006/zwe_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
48442,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2006/zwe_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
48443,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2006/zwe_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
48444,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2006/zwe_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
48445,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2007/zwe_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
48446,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2007/zwe_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
48447,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2007/zwe_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
48448,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2007/zwe_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
48449,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2007/zwe_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
48450,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2007/zwe_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
48451,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2007/zwe_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
48452,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2007/zwe_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
48453,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2008/zwe_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
48454,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2008/zwe_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
48455,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2008/zwe_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
48456,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2008/zwe_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
48457,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2008/zwe_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
48458,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2008/zwe_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
48459,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2008/zwe_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
48460,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2008/zwe_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
48461,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2009/zwe_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
48462,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2009/zwe_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
48463,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2009/zwe_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
48464,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2009/zwe_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
48465,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2009/zwe_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
48466,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2009/zwe_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
48467,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2009/zwe_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
48468,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2009/zwe_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
48469,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2010/zwe_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
48470,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2010/zwe_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
48471,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2010/zwe_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
48472,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2010/zwe_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
48473,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2010/zwe_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
48474,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2010/zwe_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
48475,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2010/zwe_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
48476,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2010/zwe_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
48477,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2011/zwe_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
48478,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2011/zwe_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
48479,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2011/zwe_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
48480,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2011/zwe_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
48481,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2011/zwe_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
48482,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2011/zwe_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
48483,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2011/zwe_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
48484,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2011/zwe_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
48485,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2012/zwe_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
48486,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2012/zwe_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
48487,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2012/zwe_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
48488,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2012/zwe_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
48489,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2012/zwe_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
48490,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2012/zwe_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
48491,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2012/zwe_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
48492,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2012/zwe_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
48493,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2013/zwe_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
48494,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2013/zwe_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
48495,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2013/zwe_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
48496,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2013/zwe_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
48497,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2013/zwe_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
48498,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2013/zwe_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
48499,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2013/zwe_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
48500,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2013/zwe_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
48501,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2014/zwe_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
48502,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2014/zwe_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
48503,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2014/zwe_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
48504,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2014/zwe_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
48505,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2014/zwe_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
48506,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2014/zwe_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
48507,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2014/zwe_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
48508,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2014/zwe_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
48509,716,"ZWE","Zimbabwe","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2015/zwe_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
48510,716,"ZWE","Zimbabwe","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2015/zwe_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
48511,716,"ZWE","Zimbabwe","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2015/zwe_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
48512,716,"ZWE","Zimbabwe","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2015/zwe_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
48513,716,"ZWE","Zimbabwe","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2015/zwe_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
48514,716,"ZWE","Zimbabwe","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2015/zwe_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
48515,716,"ZWE","Zimbabwe","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2015/zwe_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
48516,716,"ZWE","Zimbabwe","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Annual/2015/zwe_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
48517,724,"ESP","Spain","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2000/esp_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
48518,724,"ESP","Spain","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2000/esp_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
48519,724,"ESP","Spain","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2000/esp_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
48520,724,"ESP","Spain","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2000/esp_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
48521,724,"ESP","Spain","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2000/esp_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
48522,724,"ESP","Spain","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2000/esp_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
48523,724,"ESP","Spain","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2000/esp_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
48524,724,"ESP","Spain","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2000/esp_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
48525,724,"ESP","Spain","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2001/esp_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
48526,724,"ESP","Spain","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2001/esp_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
48527,724,"ESP","Spain","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2001/esp_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
48528,724,"ESP","Spain","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2001/esp_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
48529,724,"ESP","Spain","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2001/esp_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
48530,724,"ESP","Spain","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2001/esp_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
48531,724,"ESP","Spain","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2001/esp_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
48532,724,"ESP","Spain","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2001/esp_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
48533,724,"ESP","Spain","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2002/esp_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
48534,724,"ESP","Spain","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2002/esp_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
48535,724,"ESP","Spain","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2002/esp_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
48536,724,"ESP","Spain","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2002/esp_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
48537,724,"ESP","Spain","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2002/esp_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
48538,724,"ESP","Spain","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2002/esp_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
48539,724,"ESP","Spain","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2002/esp_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
48540,724,"ESP","Spain","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2002/esp_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
48541,724,"ESP","Spain","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2003/esp_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
48542,724,"ESP","Spain","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2003/esp_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
48543,724,"ESP","Spain","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2003/esp_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
48544,724,"ESP","Spain","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2003/esp_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
48545,724,"ESP","Spain","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2003/esp_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
48546,724,"ESP","Spain","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2003/esp_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
48547,724,"ESP","Spain","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2003/esp_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
48548,724,"ESP","Spain","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2003/esp_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
48549,724,"ESP","Spain","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2004/esp_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
48550,724,"ESP","Spain","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2004/esp_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
48551,724,"ESP","Spain","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2004/esp_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
48552,724,"ESP","Spain","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2004/esp_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
48553,724,"ESP","Spain","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2004/esp_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
48554,724,"ESP","Spain","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2004/esp_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
48555,724,"ESP","Spain","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2004/esp_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
48556,724,"ESP","Spain","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2004/esp_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
48557,724,"ESP","Spain","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2005/esp_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
48558,724,"ESP","Spain","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2005/esp_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
48559,724,"ESP","Spain","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2005/esp_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
48560,724,"ESP","Spain","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2005/esp_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
48561,724,"ESP","Spain","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2005/esp_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
48562,724,"ESP","Spain","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2005/esp_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
48563,724,"ESP","Spain","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2005/esp_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
48564,724,"ESP","Spain","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2005/esp_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
48565,724,"ESP","Spain","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2006/esp_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
48566,724,"ESP","Spain","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2006/esp_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
48567,724,"ESP","Spain","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2006/esp_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
48568,724,"ESP","Spain","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2006/esp_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
48569,724,"ESP","Spain","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2006/esp_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
48570,724,"ESP","Spain","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2006/esp_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
48571,724,"ESP","Spain","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2006/esp_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
48572,724,"ESP","Spain","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2006/esp_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
48573,724,"ESP","Spain","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2007/esp_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
48574,724,"ESP","Spain","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2007/esp_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
48575,724,"ESP","Spain","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2007/esp_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
48576,724,"ESP","Spain","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2007/esp_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
48577,724,"ESP","Spain","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2007/esp_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
48578,724,"ESP","Spain","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2007/esp_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
48579,724,"ESP","Spain","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2007/esp_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
48580,724,"ESP","Spain","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2007/esp_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
48581,724,"ESP","Spain","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2008/esp_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
48582,724,"ESP","Spain","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2008/esp_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
48583,724,"ESP","Spain","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2008/esp_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
48584,724,"ESP","Spain","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2008/esp_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
48585,724,"ESP","Spain","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2008/esp_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
48586,724,"ESP","Spain","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2008/esp_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
48587,724,"ESP","Spain","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2008/esp_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
48588,724,"ESP","Spain","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2008/esp_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
48589,724,"ESP","Spain","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2009/esp_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
48590,724,"ESP","Spain","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2009/esp_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
48591,724,"ESP","Spain","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2009/esp_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
48592,724,"ESP","Spain","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2009/esp_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
48593,724,"ESP","Spain","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2009/esp_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
48594,724,"ESP","Spain","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2009/esp_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
48595,724,"ESP","Spain","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2009/esp_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
48596,724,"ESP","Spain","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2009/esp_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
48597,724,"ESP","Spain","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2010/esp_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
48598,724,"ESP","Spain","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2010/esp_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
48599,724,"ESP","Spain","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2010/esp_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
48600,724,"ESP","Spain","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2010/esp_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
48601,724,"ESP","Spain","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2010/esp_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
48602,724,"ESP","Spain","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2010/esp_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
48603,724,"ESP","Spain","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2010/esp_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
48604,724,"ESP","Spain","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2010/esp_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
48605,724,"ESP","Spain","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2011/esp_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
48606,724,"ESP","Spain","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2011/esp_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
48607,724,"ESP","Spain","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2011/esp_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
48608,724,"ESP","Spain","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2011/esp_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
48609,724,"ESP","Spain","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2011/esp_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
48610,724,"ESP","Spain","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2011/esp_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
48611,724,"ESP","Spain","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2011/esp_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
48612,724,"ESP","Spain","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2011/esp_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
48613,724,"ESP","Spain","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2012/esp_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
48614,724,"ESP","Spain","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2012/esp_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
48615,724,"ESP","Spain","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2012/esp_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
48616,724,"ESP","Spain","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2012/esp_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
48617,724,"ESP","Spain","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2012/esp_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
48618,724,"ESP","Spain","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2012/esp_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
48619,724,"ESP","Spain","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2012/esp_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
48620,724,"ESP","Spain","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2012/esp_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
48621,724,"ESP","Spain","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2013/esp_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
48622,724,"ESP","Spain","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2013/esp_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
48623,724,"ESP","Spain","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2013/esp_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
48624,724,"ESP","Spain","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2013/esp_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
48625,724,"ESP","Spain","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2013/esp_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
48626,724,"ESP","Spain","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2013/esp_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
48627,724,"ESP","Spain","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2013/esp_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
48628,724,"ESP","Spain","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2013/esp_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
48629,724,"ESP","Spain","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2014/esp_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
48630,724,"ESP","Spain","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2014/esp_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
48631,724,"ESP","Spain","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2014/esp_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
48632,724,"ESP","Spain","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2014/esp_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
48633,724,"ESP","Spain","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2014/esp_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
48634,724,"ESP","Spain","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2014/esp_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
48635,724,"ESP","Spain","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2014/esp_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
48636,724,"ESP","Spain","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2014/esp_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
48637,724,"ESP","Spain","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2015/esp_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
48638,724,"ESP","Spain","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2015/esp_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
48639,724,"ESP","Spain","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2015/esp_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
48640,724,"ESP","Spain","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2015/esp_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
48641,724,"ESP","Spain","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2015/esp_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
48642,724,"ESP","Spain","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2015/esp_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
48643,724,"ESP","Spain","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2015/esp_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
48644,724,"ESP","Spain","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Annual/2015/esp_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
48645,728,"SSD","South Sudan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2000/ssd_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
48646,728,"SSD","South Sudan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2000/ssd_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
48647,728,"SSD","South Sudan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2000/ssd_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
48648,728,"SSD","South Sudan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2000/ssd_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
48649,728,"SSD","South Sudan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2000/ssd_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
48650,728,"SSD","South Sudan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2000/ssd_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
48651,728,"SSD","South Sudan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2000/ssd_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
48652,728,"SSD","South Sudan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2000/ssd_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
48653,728,"SSD","South Sudan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2001/ssd_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
48654,728,"SSD","South Sudan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2001/ssd_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
48655,728,"SSD","South Sudan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2001/ssd_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
48656,728,"SSD","South Sudan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2001/ssd_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
48657,728,"SSD","South Sudan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2001/ssd_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
48658,728,"SSD","South Sudan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2001/ssd_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
48659,728,"SSD","South Sudan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2001/ssd_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
48660,728,"SSD","South Sudan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2001/ssd_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
48661,728,"SSD","South Sudan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2002/ssd_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
48662,728,"SSD","South Sudan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2002/ssd_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
48663,728,"SSD","South Sudan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2002/ssd_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
48664,728,"SSD","South Sudan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2002/ssd_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
48665,728,"SSD","South Sudan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2002/ssd_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
48666,728,"SSD","South Sudan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2002/ssd_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
48667,728,"SSD","South Sudan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2002/ssd_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
48668,728,"SSD","South Sudan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2002/ssd_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
48669,728,"SSD","South Sudan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2003/ssd_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
48670,728,"SSD","South Sudan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2003/ssd_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
48671,728,"SSD","South Sudan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2003/ssd_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
48672,728,"SSD","South Sudan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2003/ssd_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
48673,728,"SSD","South Sudan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2003/ssd_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
48674,728,"SSD","South Sudan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2003/ssd_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
48675,728,"SSD","South Sudan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2003/ssd_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
48676,728,"SSD","South Sudan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2003/ssd_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
48677,728,"SSD","South Sudan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2004/ssd_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
48678,728,"SSD","South Sudan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2004/ssd_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
48679,728,"SSD","South Sudan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2004/ssd_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
48680,728,"SSD","South Sudan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2004/ssd_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
48681,728,"SSD","South Sudan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2004/ssd_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
48682,728,"SSD","South Sudan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2004/ssd_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
48683,728,"SSD","South Sudan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2004/ssd_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
48684,728,"SSD","South Sudan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2004/ssd_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
48685,728,"SSD","South Sudan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2005/ssd_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
48686,728,"SSD","South Sudan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2005/ssd_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
48687,728,"SSD","South Sudan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2005/ssd_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
48688,728,"SSD","South Sudan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2005/ssd_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
48689,728,"SSD","South Sudan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2005/ssd_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
48690,728,"SSD","South Sudan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2005/ssd_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
48691,728,"SSD","South Sudan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2005/ssd_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
48692,728,"SSD","South Sudan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2005/ssd_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
48693,728,"SSD","South Sudan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2006/ssd_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
48694,728,"SSD","South Sudan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2006/ssd_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
48695,728,"SSD","South Sudan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2006/ssd_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
48696,728,"SSD","South Sudan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2006/ssd_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
48697,728,"SSD","South Sudan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2006/ssd_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
48698,728,"SSD","South Sudan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2006/ssd_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
48699,728,"SSD","South Sudan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2006/ssd_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
48700,728,"SSD","South Sudan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2006/ssd_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
48701,728,"SSD","South Sudan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2007/ssd_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
48702,728,"SSD","South Sudan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2007/ssd_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
48703,728,"SSD","South Sudan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2007/ssd_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
48704,728,"SSD","South Sudan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2007/ssd_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
48705,728,"SSD","South Sudan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2007/ssd_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
48706,728,"SSD","South Sudan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2007/ssd_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
48707,728,"SSD","South Sudan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2007/ssd_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
48708,728,"SSD","South Sudan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2007/ssd_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
48709,728,"SSD","South Sudan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2008/ssd_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
48710,728,"SSD","South Sudan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2008/ssd_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
48711,728,"SSD","South Sudan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2008/ssd_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
48712,728,"SSD","South Sudan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2008/ssd_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
48713,728,"SSD","South Sudan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2008/ssd_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
48714,728,"SSD","South Sudan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2008/ssd_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
48715,728,"SSD","South Sudan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2008/ssd_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
48716,728,"SSD","South Sudan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2008/ssd_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
48717,728,"SSD","South Sudan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2009/ssd_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
48718,728,"SSD","South Sudan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2009/ssd_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
48719,728,"SSD","South Sudan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2009/ssd_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
48720,728,"SSD","South Sudan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2009/ssd_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
48721,728,"SSD","South Sudan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2009/ssd_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
48722,728,"SSD","South Sudan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2009/ssd_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
48723,728,"SSD","South Sudan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2009/ssd_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
48724,728,"SSD","South Sudan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2009/ssd_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
48725,728,"SSD","South Sudan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2010/ssd_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
48726,728,"SSD","South Sudan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2010/ssd_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
48727,728,"SSD","South Sudan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2010/ssd_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
48728,728,"SSD","South Sudan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2010/ssd_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
48729,728,"SSD","South Sudan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2010/ssd_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
48730,728,"SSD","South Sudan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2010/ssd_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
48731,728,"SSD","South Sudan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2010/ssd_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
48732,728,"SSD","South Sudan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2010/ssd_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
48733,728,"SSD","South Sudan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2011/ssd_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
48734,728,"SSD","South Sudan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2011/ssd_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
48735,728,"SSD","South Sudan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2011/ssd_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
48736,728,"SSD","South Sudan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2011/ssd_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
48737,728,"SSD","South Sudan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2011/ssd_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
48738,728,"SSD","South Sudan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2011/ssd_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
48739,728,"SSD","South Sudan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2011/ssd_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
48740,728,"SSD","South Sudan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2011/ssd_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
48741,728,"SSD","South Sudan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2012/ssd_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
48742,728,"SSD","South Sudan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2012/ssd_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
48743,728,"SSD","South Sudan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2012/ssd_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
48744,728,"SSD","South Sudan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2012/ssd_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
48745,728,"SSD","South Sudan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2012/ssd_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
48746,728,"SSD","South Sudan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2012/ssd_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
48747,728,"SSD","South Sudan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2012/ssd_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
48748,728,"SSD","South Sudan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2012/ssd_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
48749,728,"SSD","South Sudan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2013/ssd_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
48750,728,"SSD","South Sudan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2013/ssd_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
48751,728,"SSD","South Sudan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2013/ssd_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
48752,728,"SSD","South Sudan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2013/ssd_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
48753,728,"SSD","South Sudan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2013/ssd_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
48754,728,"SSD","South Sudan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2013/ssd_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
48755,728,"SSD","South Sudan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2013/ssd_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
48756,728,"SSD","South Sudan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2013/ssd_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
48757,728,"SSD","South Sudan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2014/ssd_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
48758,728,"SSD","South Sudan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2014/ssd_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
48759,728,"SSD","South Sudan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2014/ssd_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
48760,728,"SSD","South Sudan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2014/ssd_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
48761,728,"SSD","South Sudan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2014/ssd_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
48762,728,"SSD","South Sudan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2014/ssd_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
48763,728,"SSD","South Sudan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2014/ssd_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
48764,728,"SSD","South Sudan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2014/ssd_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
48765,728,"SSD","South Sudan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2015/ssd_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
48766,728,"SSD","South Sudan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2015/ssd_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
48767,728,"SSD","South Sudan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2015/ssd_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
48768,728,"SSD","South Sudan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2015/ssd_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
48769,728,"SSD","South Sudan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2015/ssd_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
48770,728,"SSD","South Sudan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2015/ssd_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
48771,728,"SSD","South Sudan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2015/ssd_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
48772,728,"SSD","South Sudan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Annual/2015/ssd_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
48773,729,"SDN","Sudan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2000/sdn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
48774,729,"SDN","Sudan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2000/sdn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
48775,729,"SDN","Sudan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2000/sdn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
48776,729,"SDN","Sudan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2000/sdn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
48777,729,"SDN","Sudan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2000/sdn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
48778,729,"SDN","Sudan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2000/sdn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
48779,729,"SDN","Sudan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2000/sdn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
48780,729,"SDN","Sudan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2000/sdn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
48781,729,"SDN","Sudan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2001/sdn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
48782,729,"SDN","Sudan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2001/sdn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
48783,729,"SDN","Sudan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2001/sdn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
48784,729,"SDN","Sudan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2001/sdn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
48785,729,"SDN","Sudan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2001/sdn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
48786,729,"SDN","Sudan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2001/sdn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
48787,729,"SDN","Sudan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2001/sdn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
48788,729,"SDN","Sudan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2001/sdn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
48789,729,"SDN","Sudan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2002/sdn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
48790,729,"SDN","Sudan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2002/sdn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
48791,729,"SDN","Sudan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2002/sdn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
48792,729,"SDN","Sudan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2002/sdn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
48793,729,"SDN","Sudan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2002/sdn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
48794,729,"SDN","Sudan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2002/sdn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
48795,729,"SDN","Sudan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2002/sdn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
48796,729,"SDN","Sudan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2002/sdn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
48797,729,"SDN","Sudan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2003/sdn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
48798,729,"SDN","Sudan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2003/sdn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
48799,729,"SDN","Sudan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2003/sdn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
48800,729,"SDN","Sudan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2003/sdn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
48801,729,"SDN","Sudan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2003/sdn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
48802,729,"SDN","Sudan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2003/sdn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
48803,729,"SDN","Sudan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2003/sdn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
48804,729,"SDN","Sudan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2003/sdn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
48805,729,"SDN","Sudan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2004/sdn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
48806,729,"SDN","Sudan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2004/sdn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
48807,729,"SDN","Sudan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2004/sdn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
48808,729,"SDN","Sudan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2004/sdn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
48809,729,"SDN","Sudan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2004/sdn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
48810,729,"SDN","Sudan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2004/sdn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
48811,729,"SDN","Sudan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2004/sdn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
48812,729,"SDN","Sudan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2004/sdn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
48813,729,"SDN","Sudan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2005/sdn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
48814,729,"SDN","Sudan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2005/sdn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
48815,729,"SDN","Sudan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2005/sdn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
48816,729,"SDN","Sudan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2005/sdn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
48817,729,"SDN","Sudan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2005/sdn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
48818,729,"SDN","Sudan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2005/sdn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
48819,729,"SDN","Sudan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2005/sdn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
48820,729,"SDN","Sudan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2005/sdn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
48821,729,"SDN","Sudan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2006/sdn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
48822,729,"SDN","Sudan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2006/sdn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
48823,729,"SDN","Sudan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2006/sdn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
48824,729,"SDN","Sudan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2006/sdn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
48825,729,"SDN","Sudan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2006/sdn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
48826,729,"SDN","Sudan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2006/sdn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
48827,729,"SDN","Sudan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2006/sdn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
48828,729,"SDN","Sudan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2006/sdn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
48829,729,"SDN","Sudan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2007/sdn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
48830,729,"SDN","Sudan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2007/sdn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
48831,729,"SDN","Sudan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2007/sdn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
48832,729,"SDN","Sudan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2007/sdn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
48833,729,"SDN","Sudan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2007/sdn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
48834,729,"SDN","Sudan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2007/sdn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
48835,729,"SDN","Sudan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2007/sdn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
48836,729,"SDN","Sudan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2007/sdn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
48837,729,"SDN","Sudan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2008/sdn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
48838,729,"SDN","Sudan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2008/sdn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
48839,729,"SDN","Sudan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2008/sdn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
48840,729,"SDN","Sudan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2008/sdn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
48841,729,"SDN","Sudan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2008/sdn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
48842,729,"SDN","Sudan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2008/sdn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
48843,729,"SDN","Sudan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2008/sdn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
48844,729,"SDN","Sudan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2008/sdn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
48845,729,"SDN","Sudan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2009/sdn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
48846,729,"SDN","Sudan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2009/sdn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
48847,729,"SDN","Sudan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2009/sdn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
48848,729,"SDN","Sudan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2009/sdn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
48849,729,"SDN","Sudan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2009/sdn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
48850,729,"SDN","Sudan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2009/sdn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
48851,729,"SDN","Sudan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2009/sdn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
48852,729,"SDN","Sudan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2009/sdn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
48853,729,"SDN","Sudan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2010/sdn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
48854,729,"SDN","Sudan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2010/sdn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
48855,729,"SDN","Sudan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2010/sdn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
48856,729,"SDN","Sudan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2010/sdn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
48857,729,"SDN","Sudan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2010/sdn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
48858,729,"SDN","Sudan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2010/sdn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
48859,729,"SDN","Sudan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2010/sdn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
48860,729,"SDN","Sudan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2010/sdn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
48861,729,"SDN","Sudan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2011/sdn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
48862,729,"SDN","Sudan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2011/sdn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
48863,729,"SDN","Sudan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2011/sdn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
48864,729,"SDN","Sudan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2011/sdn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
48865,729,"SDN","Sudan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2011/sdn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
48866,729,"SDN","Sudan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2011/sdn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
48867,729,"SDN","Sudan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2011/sdn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
48868,729,"SDN","Sudan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2011/sdn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
48869,729,"SDN","Sudan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2012/sdn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
48870,729,"SDN","Sudan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2012/sdn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
48871,729,"SDN","Sudan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2012/sdn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
48872,729,"SDN","Sudan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2012/sdn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
48873,729,"SDN","Sudan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2012/sdn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
48874,729,"SDN","Sudan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2012/sdn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
48875,729,"SDN","Sudan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2012/sdn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
48876,729,"SDN","Sudan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2012/sdn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
48877,729,"SDN","Sudan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2013/sdn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
48878,729,"SDN","Sudan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2013/sdn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
48879,729,"SDN","Sudan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2013/sdn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
48880,729,"SDN","Sudan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2013/sdn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
48881,729,"SDN","Sudan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2013/sdn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
48882,729,"SDN","Sudan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2013/sdn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
48883,729,"SDN","Sudan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2013/sdn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
48884,729,"SDN","Sudan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2013/sdn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
48885,729,"SDN","Sudan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2014/sdn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
48886,729,"SDN","Sudan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2014/sdn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
48887,729,"SDN","Sudan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2014/sdn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
48888,729,"SDN","Sudan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2014/sdn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
48889,729,"SDN","Sudan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2014/sdn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
48890,729,"SDN","Sudan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2014/sdn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
48891,729,"SDN","Sudan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2014/sdn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
48892,729,"SDN","Sudan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2014/sdn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
48893,729,"SDN","Sudan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2015/sdn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
48894,729,"SDN","Sudan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2015/sdn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
48895,729,"SDN","Sudan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2015/sdn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
48896,729,"SDN","Sudan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2015/sdn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
48897,729,"SDN","Sudan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2015/sdn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
48898,729,"SDN","Sudan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2015/sdn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
48899,729,"SDN","Sudan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2015/sdn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
48900,729,"SDN","Sudan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Annual/2015/sdn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
48901,732,"ESH","Western Sahara","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2000/esh_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
48902,732,"ESH","Western Sahara","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2000/esh_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
48903,732,"ESH","Western Sahara","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2000/esh_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
48904,732,"ESH","Western Sahara","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2000/esh_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
48905,732,"ESH","Western Sahara","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2000/esh_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
48906,732,"ESH","Western Sahara","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2000/esh_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
48907,732,"ESH","Western Sahara","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2000/esh_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
48908,732,"ESH","Western Sahara","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2000/esh_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
48909,732,"ESH","Western Sahara","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2001/esh_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
48910,732,"ESH","Western Sahara","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2001/esh_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
48911,732,"ESH","Western Sahara","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2001/esh_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
48912,732,"ESH","Western Sahara","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2001/esh_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
48913,732,"ESH","Western Sahara","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2001/esh_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
48914,732,"ESH","Western Sahara","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2001/esh_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
48915,732,"ESH","Western Sahara","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2001/esh_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
48916,732,"ESH","Western Sahara","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2001/esh_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
48917,732,"ESH","Western Sahara","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2002/esh_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
48918,732,"ESH","Western Sahara","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2002/esh_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
48919,732,"ESH","Western Sahara","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2002/esh_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
48920,732,"ESH","Western Sahara","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2002/esh_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
48921,732,"ESH","Western Sahara","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2002/esh_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
48922,732,"ESH","Western Sahara","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2002/esh_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
48923,732,"ESH","Western Sahara","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2002/esh_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
48924,732,"ESH","Western Sahara","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2002/esh_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
48925,732,"ESH","Western Sahara","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2003/esh_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
48926,732,"ESH","Western Sahara","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2003/esh_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
48927,732,"ESH","Western Sahara","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2003/esh_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
48928,732,"ESH","Western Sahara","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2003/esh_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
48929,732,"ESH","Western Sahara","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2003/esh_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
48930,732,"ESH","Western Sahara","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2003/esh_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
48931,732,"ESH","Western Sahara","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2003/esh_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
48932,732,"ESH","Western Sahara","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2003/esh_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
48933,732,"ESH","Western Sahara","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2004/esh_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
48934,732,"ESH","Western Sahara","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2004/esh_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
48935,732,"ESH","Western Sahara","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2004/esh_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
48936,732,"ESH","Western Sahara","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2004/esh_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
48937,732,"ESH","Western Sahara","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2004/esh_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
48938,732,"ESH","Western Sahara","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2004/esh_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
48939,732,"ESH","Western Sahara","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2004/esh_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
48940,732,"ESH","Western Sahara","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2004/esh_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
48941,732,"ESH","Western Sahara","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2005/esh_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
48942,732,"ESH","Western Sahara","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2005/esh_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
48943,732,"ESH","Western Sahara","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2005/esh_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
48944,732,"ESH","Western Sahara","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2005/esh_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
48945,732,"ESH","Western Sahara","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2005/esh_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
48946,732,"ESH","Western Sahara","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2005/esh_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
48947,732,"ESH","Western Sahara","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2005/esh_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
48948,732,"ESH","Western Sahara","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2005/esh_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
48949,732,"ESH","Western Sahara","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2006/esh_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
48950,732,"ESH","Western Sahara","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2006/esh_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
48951,732,"ESH","Western Sahara","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2006/esh_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
48952,732,"ESH","Western Sahara","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2006/esh_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
48953,732,"ESH","Western Sahara","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2006/esh_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
48954,732,"ESH","Western Sahara","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2006/esh_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
48955,732,"ESH","Western Sahara","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2006/esh_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
48956,732,"ESH","Western Sahara","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2006/esh_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
48957,732,"ESH","Western Sahara","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2007/esh_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
48958,732,"ESH","Western Sahara","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2007/esh_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
48959,732,"ESH","Western Sahara","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2007/esh_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
48960,732,"ESH","Western Sahara","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2007/esh_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
48961,732,"ESH","Western Sahara","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2007/esh_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
48962,732,"ESH","Western Sahara","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2007/esh_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
48963,732,"ESH","Western Sahara","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2007/esh_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
48964,732,"ESH","Western Sahara","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2007/esh_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
48965,732,"ESH","Western Sahara","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2008/esh_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
48966,732,"ESH","Western Sahara","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2008/esh_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
48967,732,"ESH","Western Sahara","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2008/esh_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
48968,732,"ESH","Western Sahara","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2008/esh_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
48969,732,"ESH","Western Sahara","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2008/esh_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
48970,732,"ESH","Western Sahara","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2008/esh_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
48971,732,"ESH","Western Sahara","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2008/esh_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
48972,732,"ESH","Western Sahara","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2008/esh_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
48973,732,"ESH","Western Sahara","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2009/esh_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
48974,732,"ESH","Western Sahara","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2009/esh_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
48975,732,"ESH","Western Sahara","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2009/esh_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
48976,732,"ESH","Western Sahara","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2009/esh_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
48977,732,"ESH","Western Sahara","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2009/esh_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
48978,732,"ESH","Western Sahara","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2009/esh_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
48979,732,"ESH","Western Sahara","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2009/esh_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
48980,732,"ESH","Western Sahara","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2009/esh_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
48981,732,"ESH","Western Sahara","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2010/esh_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
48982,732,"ESH","Western Sahara","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2010/esh_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
48983,732,"ESH","Western Sahara","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2010/esh_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
48984,732,"ESH","Western Sahara","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2010/esh_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
48985,732,"ESH","Western Sahara","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2010/esh_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
48986,732,"ESH","Western Sahara","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2010/esh_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
48987,732,"ESH","Western Sahara","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2010/esh_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
48988,732,"ESH","Western Sahara","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2010/esh_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
48989,732,"ESH","Western Sahara","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2011/esh_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
48990,732,"ESH","Western Sahara","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2011/esh_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
48991,732,"ESH","Western Sahara","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2011/esh_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
48992,732,"ESH","Western Sahara","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2011/esh_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
48993,732,"ESH","Western Sahara","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2011/esh_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
48994,732,"ESH","Western Sahara","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2011/esh_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
48995,732,"ESH","Western Sahara","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2011/esh_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
48996,732,"ESH","Western Sahara","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2011/esh_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
48997,732,"ESH","Western Sahara","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2012/esh_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
48998,732,"ESH","Western Sahara","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2012/esh_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
48999,732,"ESH","Western Sahara","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2012/esh_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
49000,732,"ESH","Western Sahara","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2012/esh_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
49001,732,"ESH","Western Sahara","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2012/esh_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
49002,732,"ESH","Western Sahara","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2012/esh_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
49003,732,"ESH","Western Sahara","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2012/esh_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
49004,732,"ESH","Western Sahara","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2012/esh_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
49005,732,"ESH","Western Sahara","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2013/esh_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
49006,732,"ESH","Western Sahara","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2013/esh_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
49007,732,"ESH","Western Sahara","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2013/esh_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
49008,732,"ESH","Western Sahara","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2013/esh_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
49009,732,"ESH","Western Sahara","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2013/esh_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
49010,732,"ESH","Western Sahara","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2013/esh_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
49011,732,"ESH","Western Sahara","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2013/esh_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
49012,732,"ESH","Western Sahara","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2013/esh_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
49013,732,"ESH","Western Sahara","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2014/esh_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
49014,732,"ESH","Western Sahara","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2014/esh_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
49015,732,"ESH","Western Sahara","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2014/esh_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
49016,732,"ESH","Western Sahara","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2014/esh_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
49017,732,"ESH","Western Sahara","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2014/esh_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
49018,732,"ESH","Western Sahara","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2014/esh_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
49019,732,"ESH","Western Sahara","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2014/esh_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
49020,732,"ESH","Western Sahara","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2014/esh_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
49021,732,"ESH","Western Sahara","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2015/esh_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
49022,732,"ESH","Western Sahara","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2015/esh_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
49023,732,"ESH","Western Sahara","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2015/esh_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
49024,732,"ESH","Western Sahara","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2015/esh_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
49025,732,"ESH","Western Sahara","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2015/esh_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
49026,732,"ESH","Western Sahara","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2015/esh_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
49027,732,"ESH","Western Sahara","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2015/esh_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
49028,732,"ESH","Western Sahara","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Annual/2015/esh_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
49029,740,"SUR","Suriname","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2000/sur_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
49030,740,"SUR","Suriname","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2000/sur_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
49031,740,"SUR","Suriname","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2000/sur_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
49032,740,"SUR","Suriname","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2000/sur_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
49033,740,"SUR","Suriname","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2000/sur_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
49034,740,"SUR","Suriname","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2000/sur_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
49035,740,"SUR","Suriname","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2000/sur_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
49036,740,"SUR","Suriname","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2000/sur_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
49037,740,"SUR","Suriname","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2001/sur_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
49038,740,"SUR","Suriname","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2001/sur_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
49039,740,"SUR","Suriname","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2001/sur_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
49040,740,"SUR","Suriname","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2001/sur_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
49041,740,"SUR","Suriname","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2001/sur_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
49042,740,"SUR","Suriname","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2001/sur_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
49043,740,"SUR","Suriname","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2001/sur_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
49044,740,"SUR","Suriname","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2001/sur_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
49045,740,"SUR","Suriname","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2002/sur_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
49046,740,"SUR","Suriname","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2002/sur_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
49047,740,"SUR","Suriname","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2002/sur_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
49048,740,"SUR","Suriname","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2002/sur_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
49049,740,"SUR","Suriname","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2002/sur_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
49050,740,"SUR","Suriname","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2002/sur_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
49051,740,"SUR","Suriname","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2002/sur_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
49052,740,"SUR","Suriname","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2002/sur_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
49053,740,"SUR","Suriname","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2003/sur_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
49054,740,"SUR","Suriname","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2003/sur_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
49055,740,"SUR","Suriname","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2003/sur_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
49056,740,"SUR","Suriname","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2003/sur_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
49057,740,"SUR","Suriname","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2003/sur_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
49058,740,"SUR","Suriname","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2003/sur_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
49059,740,"SUR","Suriname","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2003/sur_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
49060,740,"SUR","Suriname","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2003/sur_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
49061,740,"SUR","Suriname","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2004/sur_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
49062,740,"SUR","Suriname","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2004/sur_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
49063,740,"SUR","Suriname","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2004/sur_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
49064,740,"SUR","Suriname","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2004/sur_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
49065,740,"SUR","Suriname","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2004/sur_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
49066,740,"SUR","Suriname","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2004/sur_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
49067,740,"SUR","Suriname","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2004/sur_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
49068,740,"SUR","Suriname","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2004/sur_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
49069,740,"SUR","Suriname","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2005/sur_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
49070,740,"SUR","Suriname","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2005/sur_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
49071,740,"SUR","Suriname","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2005/sur_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
49072,740,"SUR","Suriname","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2005/sur_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
49073,740,"SUR","Suriname","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2005/sur_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
49074,740,"SUR","Suriname","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2005/sur_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
49075,740,"SUR","Suriname","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2005/sur_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
49076,740,"SUR","Suriname","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2005/sur_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
49077,740,"SUR","Suriname","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2006/sur_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
49078,740,"SUR","Suriname","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2006/sur_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
49079,740,"SUR","Suriname","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2006/sur_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
49080,740,"SUR","Suriname","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2006/sur_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
49081,740,"SUR","Suriname","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2006/sur_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
49082,740,"SUR","Suriname","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2006/sur_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
49083,740,"SUR","Suriname","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2006/sur_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
49084,740,"SUR","Suriname","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2006/sur_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
49085,740,"SUR","Suriname","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2007/sur_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
49086,740,"SUR","Suriname","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2007/sur_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
49087,740,"SUR","Suriname","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2007/sur_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
49088,740,"SUR","Suriname","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2007/sur_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
49089,740,"SUR","Suriname","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2007/sur_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
49090,740,"SUR","Suriname","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2007/sur_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
49091,740,"SUR","Suriname","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2007/sur_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
49092,740,"SUR","Suriname","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2007/sur_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
49093,740,"SUR","Suriname","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2008/sur_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
49094,740,"SUR","Suriname","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2008/sur_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
49095,740,"SUR","Suriname","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2008/sur_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
49096,740,"SUR","Suriname","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2008/sur_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
49097,740,"SUR","Suriname","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2008/sur_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
49098,740,"SUR","Suriname","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2008/sur_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
49099,740,"SUR","Suriname","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2008/sur_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
49100,740,"SUR","Suriname","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2008/sur_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
49101,740,"SUR","Suriname","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2009/sur_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
49102,740,"SUR","Suriname","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2009/sur_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
49103,740,"SUR","Suriname","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2009/sur_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
49104,740,"SUR","Suriname","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2009/sur_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
49105,740,"SUR","Suriname","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2009/sur_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
49106,740,"SUR","Suriname","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2009/sur_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
49107,740,"SUR","Suriname","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2009/sur_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
49108,740,"SUR","Suriname","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2009/sur_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
49109,740,"SUR","Suriname","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2010/sur_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
49110,740,"SUR","Suriname","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2010/sur_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
49111,740,"SUR","Suriname","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2010/sur_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
49112,740,"SUR","Suriname","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2010/sur_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
49113,740,"SUR","Suriname","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2010/sur_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
49114,740,"SUR","Suriname","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2010/sur_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
49115,740,"SUR","Suriname","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2010/sur_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
49116,740,"SUR","Suriname","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2010/sur_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
49117,740,"SUR","Suriname","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2011/sur_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
49118,740,"SUR","Suriname","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2011/sur_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
49119,740,"SUR","Suriname","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2011/sur_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
49120,740,"SUR","Suriname","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2011/sur_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
49121,740,"SUR","Suriname","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2011/sur_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
49122,740,"SUR","Suriname","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2011/sur_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
49123,740,"SUR","Suriname","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2011/sur_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
49124,740,"SUR","Suriname","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2011/sur_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
49125,740,"SUR","Suriname","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2012/sur_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
49126,740,"SUR","Suriname","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2012/sur_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
49127,740,"SUR","Suriname","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2012/sur_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
49128,740,"SUR","Suriname","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2012/sur_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
49129,740,"SUR","Suriname","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2012/sur_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
49130,740,"SUR","Suriname","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2012/sur_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
49131,740,"SUR","Suriname","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2012/sur_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
49132,740,"SUR","Suriname","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2012/sur_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
49133,740,"SUR","Suriname","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2013/sur_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
49134,740,"SUR","Suriname","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2013/sur_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
49135,740,"SUR","Suriname","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2013/sur_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
49136,740,"SUR","Suriname","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2013/sur_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
49137,740,"SUR","Suriname","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2013/sur_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
49138,740,"SUR","Suriname","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2013/sur_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
49139,740,"SUR","Suriname","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2013/sur_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
49140,740,"SUR","Suriname","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2013/sur_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
49141,740,"SUR","Suriname","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2014/sur_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
49142,740,"SUR","Suriname","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2014/sur_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
49143,740,"SUR","Suriname","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2014/sur_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
49144,740,"SUR","Suriname","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2014/sur_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
49145,740,"SUR","Suriname","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2014/sur_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
49146,740,"SUR","Suriname","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2014/sur_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
49147,740,"SUR","Suriname","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2014/sur_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
49148,740,"SUR","Suriname","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2014/sur_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
49149,740,"SUR","Suriname","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2015/sur_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
49150,740,"SUR","Suriname","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2015/sur_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
49151,740,"SUR","Suriname","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2015/sur_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
49152,740,"SUR","Suriname","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2015/sur_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
49153,740,"SUR","Suriname","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2015/sur_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
49154,740,"SUR","Suriname","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2015/sur_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
49155,740,"SUR","Suriname","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2015/sur_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
49156,740,"SUR","Suriname","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Annual/2015/sur_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
49157,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2000/sjm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
49158,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2000/sjm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
49159,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2000/sjm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
49160,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2000/sjm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
49161,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2000/sjm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
49162,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2000/sjm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
49163,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2000/sjm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
49164,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2000/sjm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
49165,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2001/sjm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
49166,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2001/sjm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
49167,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2001/sjm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
49168,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2001/sjm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
49169,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2001/sjm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
49170,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2001/sjm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
49171,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2001/sjm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
49172,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2001/sjm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
49173,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2002/sjm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
49174,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2002/sjm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
49175,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2002/sjm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
49176,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2002/sjm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
49177,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2002/sjm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
49178,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2002/sjm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
49179,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2002/sjm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
49180,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2002/sjm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
49181,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2003/sjm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
49182,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2003/sjm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
49183,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2003/sjm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
49184,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2003/sjm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
49185,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2003/sjm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
49186,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2003/sjm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
49187,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2003/sjm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
49188,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2003/sjm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
49189,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2004/sjm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
49190,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2004/sjm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
49191,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2004/sjm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
49192,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2004/sjm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
49193,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2004/sjm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
49194,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2004/sjm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
49195,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2004/sjm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
49196,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2004/sjm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
49197,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2005/sjm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
49198,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2005/sjm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
49199,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2005/sjm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
49200,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2005/sjm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
49201,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2005/sjm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
49202,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2005/sjm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
49203,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2005/sjm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
49204,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2005/sjm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
49205,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2006/sjm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
49206,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2006/sjm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
49207,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2006/sjm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
49208,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2006/sjm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
49209,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2006/sjm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
49210,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2006/sjm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
49211,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2006/sjm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
49212,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2006/sjm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
49213,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2007/sjm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
49214,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2007/sjm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
49215,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2007/sjm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
49216,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2007/sjm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
49217,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2007/sjm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
49218,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2007/sjm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
49219,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2007/sjm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
49220,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2007/sjm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
49221,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2008/sjm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
49222,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2008/sjm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
49223,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2008/sjm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
49224,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2008/sjm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
49225,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2008/sjm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
49226,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2008/sjm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
49227,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2008/sjm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
49228,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2008/sjm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
49229,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2009/sjm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
49230,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2009/sjm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
49231,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2009/sjm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
49232,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2009/sjm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
49233,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2009/sjm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
49234,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2009/sjm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
49235,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2009/sjm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
49236,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2009/sjm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
49237,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2010/sjm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
49238,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2010/sjm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
49239,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2010/sjm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
49240,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2010/sjm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
49241,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2010/sjm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
49242,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2010/sjm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
49243,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2010/sjm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
49244,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2010/sjm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
49245,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2011/sjm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
49246,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2011/sjm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
49247,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2011/sjm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
49248,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2011/sjm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
49249,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2011/sjm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
49250,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2011/sjm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
49251,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2011/sjm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
49252,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2011/sjm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
49253,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2012/sjm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
49254,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2012/sjm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
49255,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2012/sjm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
49256,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2012/sjm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
49257,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2012/sjm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
49258,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2012/sjm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
49259,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2012/sjm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
49260,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2012/sjm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
49261,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2013/sjm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
49262,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2013/sjm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
49263,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2013/sjm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
49264,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2013/sjm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
49265,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2013/sjm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
49266,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2013/sjm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
49267,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2013/sjm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
49268,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2013/sjm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
49269,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2014/sjm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
49270,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2014/sjm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
49271,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2014/sjm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
49272,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2014/sjm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
49273,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2014/sjm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
49274,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2014/sjm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
49275,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2014/sjm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
49276,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2014/sjm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
49277,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2015/sjm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
49278,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2015/sjm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
49279,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2015/sjm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
49280,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2015/sjm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
49281,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2015/sjm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
49282,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2015/sjm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
49283,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2015/sjm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
49284,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Annual/2015/sjm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
49285,748,"SWZ","Swaziland","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2000/swz_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
49286,748,"SWZ","Swaziland","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2000/swz_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
49287,748,"SWZ","Swaziland","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2000/swz_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
49288,748,"SWZ","Swaziland","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2000/swz_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
49289,748,"SWZ","Swaziland","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2000/swz_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
49290,748,"SWZ","Swaziland","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2000/swz_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
49291,748,"SWZ","Swaziland","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2000/swz_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
49292,748,"SWZ","Swaziland","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2000/swz_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
49293,748,"SWZ","Swaziland","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2001/swz_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
49294,748,"SWZ","Swaziland","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2001/swz_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
49295,748,"SWZ","Swaziland","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2001/swz_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
49296,748,"SWZ","Swaziland","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2001/swz_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
49297,748,"SWZ","Swaziland","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2001/swz_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
49298,748,"SWZ","Swaziland","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2001/swz_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
49299,748,"SWZ","Swaziland","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2001/swz_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
49300,748,"SWZ","Swaziland","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2001/swz_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
49301,748,"SWZ","Swaziland","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2002/swz_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
49302,748,"SWZ","Swaziland","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2002/swz_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
49303,748,"SWZ","Swaziland","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2002/swz_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
49304,748,"SWZ","Swaziland","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2002/swz_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
49305,748,"SWZ","Swaziland","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2002/swz_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
49306,748,"SWZ","Swaziland","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2002/swz_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
49307,748,"SWZ","Swaziland","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2002/swz_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
49308,748,"SWZ","Swaziland","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2002/swz_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
49309,748,"SWZ","Swaziland","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2003/swz_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
49310,748,"SWZ","Swaziland","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2003/swz_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
49311,748,"SWZ","Swaziland","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2003/swz_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
49312,748,"SWZ","Swaziland","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2003/swz_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
49313,748,"SWZ","Swaziland","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2003/swz_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
49314,748,"SWZ","Swaziland","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2003/swz_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
49315,748,"SWZ","Swaziland","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2003/swz_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
49316,748,"SWZ","Swaziland","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2003/swz_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
49317,748,"SWZ","Swaziland","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2004/swz_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
49318,748,"SWZ","Swaziland","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2004/swz_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
49319,748,"SWZ","Swaziland","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2004/swz_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
49320,748,"SWZ","Swaziland","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2004/swz_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
49321,748,"SWZ","Swaziland","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2004/swz_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
49322,748,"SWZ","Swaziland","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2004/swz_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
49323,748,"SWZ","Swaziland","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2004/swz_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
49324,748,"SWZ","Swaziland","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2004/swz_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
49325,748,"SWZ","Swaziland","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2005/swz_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
49326,748,"SWZ","Swaziland","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2005/swz_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
49327,748,"SWZ","Swaziland","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2005/swz_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
49328,748,"SWZ","Swaziland","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2005/swz_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
49329,748,"SWZ","Swaziland","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2005/swz_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
49330,748,"SWZ","Swaziland","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2005/swz_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
49331,748,"SWZ","Swaziland","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2005/swz_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
49332,748,"SWZ","Swaziland","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2005/swz_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
49333,748,"SWZ","Swaziland","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2006/swz_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
49334,748,"SWZ","Swaziland","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2006/swz_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
49335,748,"SWZ","Swaziland","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2006/swz_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
49336,748,"SWZ","Swaziland","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2006/swz_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
49337,748,"SWZ","Swaziland","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2006/swz_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
49338,748,"SWZ","Swaziland","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2006/swz_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
49339,748,"SWZ","Swaziland","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2006/swz_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
49340,748,"SWZ","Swaziland","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2006/swz_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
49341,748,"SWZ","Swaziland","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2007/swz_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
49342,748,"SWZ","Swaziland","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2007/swz_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
49343,748,"SWZ","Swaziland","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2007/swz_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
49344,748,"SWZ","Swaziland","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2007/swz_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
49345,748,"SWZ","Swaziland","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2007/swz_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
49346,748,"SWZ","Swaziland","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2007/swz_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
49347,748,"SWZ","Swaziland","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2007/swz_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
49348,748,"SWZ","Swaziland","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2007/swz_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
49349,748,"SWZ","Swaziland","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2008/swz_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
49350,748,"SWZ","Swaziland","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2008/swz_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
49351,748,"SWZ","Swaziland","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2008/swz_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
49352,748,"SWZ","Swaziland","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2008/swz_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
49353,748,"SWZ","Swaziland","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2008/swz_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
49354,748,"SWZ","Swaziland","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2008/swz_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
49355,748,"SWZ","Swaziland","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2008/swz_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
49356,748,"SWZ","Swaziland","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2008/swz_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
49357,748,"SWZ","Swaziland","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2009/swz_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
49358,748,"SWZ","Swaziland","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2009/swz_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
49359,748,"SWZ","Swaziland","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2009/swz_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
49360,748,"SWZ","Swaziland","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2009/swz_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
49361,748,"SWZ","Swaziland","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2009/swz_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
49362,748,"SWZ","Swaziland","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2009/swz_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
49363,748,"SWZ","Swaziland","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2009/swz_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
49364,748,"SWZ","Swaziland","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2009/swz_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
49365,748,"SWZ","Swaziland","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2010/swz_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
49366,748,"SWZ","Swaziland","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2010/swz_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
49367,748,"SWZ","Swaziland","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2010/swz_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
49368,748,"SWZ","Swaziland","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2010/swz_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
49369,748,"SWZ","Swaziland","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2010/swz_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
49370,748,"SWZ","Swaziland","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2010/swz_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
49371,748,"SWZ","Swaziland","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2010/swz_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
49372,748,"SWZ","Swaziland","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2010/swz_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
49373,748,"SWZ","Swaziland","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2011/swz_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
49374,748,"SWZ","Swaziland","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2011/swz_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
49375,748,"SWZ","Swaziland","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2011/swz_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
49376,748,"SWZ","Swaziland","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2011/swz_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
49377,748,"SWZ","Swaziland","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2011/swz_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
49378,748,"SWZ","Swaziland","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2011/swz_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
49379,748,"SWZ","Swaziland","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2011/swz_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
49380,748,"SWZ","Swaziland","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2011/swz_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
49381,748,"SWZ","Swaziland","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2012/swz_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
49382,748,"SWZ","Swaziland","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2012/swz_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
49383,748,"SWZ","Swaziland","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2012/swz_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
49384,748,"SWZ","Swaziland","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2012/swz_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
49385,748,"SWZ","Swaziland","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2012/swz_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
49386,748,"SWZ","Swaziland","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2012/swz_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
49387,748,"SWZ","Swaziland","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2012/swz_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
49388,748,"SWZ","Swaziland","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2012/swz_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
49389,748,"SWZ","Swaziland","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2013/swz_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
49390,748,"SWZ","Swaziland","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2013/swz_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
49391,748,"SWZ","Swaziland","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2013/swz_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
49392,748,"SWZ","Swaziland","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2013/swz_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
49393,748,"SWZ","Swaziland","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2013/swz_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
49394,748,"SWZ","Swaziland","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2013/swz_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
49395,748,"SWZ","Swaziland","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2013/swz_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
49396,748,"SWZ","Swaziland","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2013/swz_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
49397,748,"SWZ","Swaziland","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2014/swz_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
49398,748,"SWZ","Swaziland","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2014/swz_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
49399,748,"SWZ","Swaziland","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2014/swz_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
49400,748,"SWZ","Swaziland","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2014/swz_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
49401,748,"SWZ","Swaziland","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2014/swz_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
49402,748,"SWZ","Swaziland","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2014/swz_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
49403,748,"SWZ","Swaziland","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2014/swz_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
49404,748,"SWZ","Swaziland","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2014/swz_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
49405,748,"SWZ","Swaziland","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2015/swz_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
49406,748,"SWZ","Swaziland","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2015/swz_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
49407,748,"SWZ","Swaziland","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2015/swz_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
49408,748,"SWZ","Swaziland","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2015/swz_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
49409,748,"SWZ","Swaziland","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2015/swz_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
49410,748,"SWZ","Swaziland","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2015/swz_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
49411,748,"SWZ","Swaziland","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2015/swz_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
49412,748,"SWZ","Swaziland","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Annual/2015/swz_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
49413,752,"SWE","Sweden","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2000/swe_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
49414,752,"SWE","Sweden","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2000/swe_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
49415,752,"SWE","Sweden","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2000/swe_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
49416,752,"SWE","Sweden","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2000/swe_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
49417,752,"SWE","Sweden","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2000/swe_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
49418,752,"SWE","Sweden","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2000/swe_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
49419,752,"SWE","Sweden","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2000/swe_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
49420,752,"SWE","Sweden","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2000/swe_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
49421,752,"SWE","Sweden","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2001/swe_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
49422,752,"SWE","Sweden","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2001/swe_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
49423,752,"SWE","Sweden","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2001/swe_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
49424,752,"SWE","Sweden","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2001/swe_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
49425,752,"SWE","Sweden","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2001/swe_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
49426,752,"SWE","Sweden","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2001/swe_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
49427,752,"SWE","Sweden","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2001/swe_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
49428,752,"SWE","Sweden","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2001/swe_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
49429,752,"SWE","Sweden","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2002/swe_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
49430,752,"SWE","Sweden","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2002/swe_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
49431,752,"SWE","Sweden","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2002/swe_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
49432,752,"SWE","Sweden","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2002/swe_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
49433,752,"SWE","Sweden","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2002/swe_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
49434,752,"SWE","Sweden","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2002/swe_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
49435,752,"SWE","Sweden","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2002/swe_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
49436,752,"SWE","Sweden","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2002/swe_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
49437,752,"SWE","Sweden","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2003/swe_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
49438,752,"SWE","Sweden","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2003/swe_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
49439,752,"SWE","Sweden","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2003/swe_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
49440,752,"SWE","Sweden","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2003/swe_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
49441,752,"SWE","Sweden","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2003/swe_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
49442,752,"SWE","Sweden","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2003/swe_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
49443,752,"SWE","Sweden","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2003/swe_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
49444,752,"SWE","Sweden","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2003/swe_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
49445,752,"SWE","Sweden","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2004/swe_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
49446,752,"SWE","Sweden","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2004/swe_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
49447,752,"SWE","Sweden","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2004/swe_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
49448,752,"SWE","Sweden","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2004/swe_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
49449,752,"SWE","Sweden","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2004/swe_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
49450,752,"SWE","Sweden","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2004/swe_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
49451,752,"SWE","Sweden","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2004/swe_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
49452,752,"SWE","Sweden","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2004/swe_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
49453,752,"SWE","Sweden","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2005/swe_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
49454,752,"SWE","Sweden","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2005/swe_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
49455,752,"SWE","Sweden","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2005/swe_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
49456,752,"SWE","Sweden","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2005/swe_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
49457,752,"SWE","Sweden","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2005/swe_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
49458,752,"SWE","Sweden","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2005/swe_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
49459,752,"SWE","Sweden","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2005/swe_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
49460,752,"SWE","Sweden","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2005/swe_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
49461,752,"SWE","Sweden","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2006/swe_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
49462,752,"SWE","Sweden","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2006/swe_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
49463,752,"SWE","Sweden","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2006/swe_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
49464,752,"SWE","Sweden","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2006/swe_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
49465,752,"SWE","Sweden","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2006/swe_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
49466,752,"SWE","Sweden","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2006/swe_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
49467,752,"SWE","Sweden","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2006/swe_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
49468,752,"SWE","Sweden","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2006/swe_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
49469,752,"SWE","Sweden","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2007/swe_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
49470,752,"SWE","Sweden","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2007/swe_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
49471,752,"SWE","Sweden","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2007/swe_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
49472,752,"SWE","Sweden","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2007/swe_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
49473,752,"SWE","Sweden","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2007/swe_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
49474,752,"SWE","Sweden","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2007/swe_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
49475,752,"SWE","Sweden","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2007/swe_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
49476,752,"SWE","Sweden","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2007/swe_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
49477,752,"SWE","Sweden","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2008/swe_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
49478,752,"SWE","Sweden","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2008/swe_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
49479,752,"SWE","Sweden","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2008/swe_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
49480,752,"SWE","Sweden","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2008/swe_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
49481,752,"SWE","Sweden","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2008/swe_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
49482,752,"SWE","Sweden","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2008/swe_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
49483,752,"SWE","Sweden","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2008/swe_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
49484,752,"SWE","Sweden","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2008/swe_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
49485,752,"SWE","Sweden","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2009/swe_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
49486,752,"SWE","Sweden","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2009/swe_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
49487,752,"SWE","Sweden","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2009/swe_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
49488,752,"SWE","Sweden","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2009/swe_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
49489,752,"SWE","Sweden","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2009/swe_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
49490,752,"SWE","Sweden","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2009/swe_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
49491,752,"SWE","Sweden","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2009/swe_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
49492,752,"SWE","Sweden","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2009/swe_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
49493,752,"SWE","Sweden","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2010/swe_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
49494,752,"SWE","Sweden","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2010/swe_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
49495,752,"SWE","Sweden","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2010/swe_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
49496,752,"SWE","Sweden","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2010/swe_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
49497,752,"SWE","Sweden","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2010/swe_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
49498,752,"SWE","Sweden","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2010/swe_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
49499,752,"SWE","Sweden","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2010/swe_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
49500,752,"SWE","Sweden","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2010/swe_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
49501,752,"SWE","Sweden","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2011/swe_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
49502,752,"SWE","Sweden","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2011/swe_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
49503,752,"SWE","Sweden","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2011/swe_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
49504,752,"SWE","Sweden","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2011/swe_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
49505,752,"SWE","Sweden","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2011/swe_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
49506,752,"SWE","Sweden","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2011/swe_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
49507,752,"SWE","Sweden","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2011/swe_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
49508,752,"SWE","Sweden","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2011/swe_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
49509,752,"SWE","Sweden","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2012/swe_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
49510,752,"SWE","Sweden","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2012/swe_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
49511,752,"SWE","Sweden","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2012/swe_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
49512,752,"SWE","Sweden","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2012/swe_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
49513,752,"SWE","Sweden","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2012/swe_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
49514,752,"SWE","Sweden","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2012/swe_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
49515,752,"SWE","Sweden","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2012/swe_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
49516,752,"SWE","Sweden","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2012/swe_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
49517,752,"SWE","Sweden","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2013/swe_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
49518,752,"SWE","Sweden","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2013/swe_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
49519,752,"SWE","Sweden","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2013/swe_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
49520,752,"SWE","Sweden","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2013/swe_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
49521,752,"SWE","Sweden","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2013/swe_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
49522,752,"SWE","Sweden","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2013/swe_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
49523,752,"SWE","Sweden","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2013/swe_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
49524,752,"SWE","Sweden","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2013/swe_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
49525,752,"SWE","Sweden","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2014/swe_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
49526,752,"SWE","Sweden","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2014/swe_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
49527,752,"SWE","Sweden","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2014/swe_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
49528,752,"SWE","Sweden","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2014/swe_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
49529,752,"SWE","Sweden","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2014/swe_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
49530,752,"SWE","Sweden","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2014/swe_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
49531,752,"SWE","Sweden","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2014/swe_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
49532,752,"SWE","Sweden","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2014/swe_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
49533,752,"SWE","Sweden","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2015/swe_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
49534,752,"SWE","Sweden","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2015/swe_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
49535,752,"SWE","Sweden","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2015/swe_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
49536,752,"SWE","Sweden","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2015/swe_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
49537,752,"SWE","Sweden","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2015/swe_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
49538,752,"SWE","Sweden","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2015/swe_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
49539,752,"SWE","Sweden","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2015/swe_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
49540,752,"SWE","Sweden","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Annual/2015/swe_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
49541,756,"CHE","Switzerland","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2000/che_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
49542,756,"CHE","Switzerland","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2000/che_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
49543,756,"CHE","Switzerland","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2000/che_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
49544,756,"CHE","Switzerland","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2000/che_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
49545,756,"CHE","Switzerland","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2000/che_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
49546,756,"CHE","Switzerland","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2000/che_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
49547,756,"CHE","Switzerland","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2000/che_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
49548,756,"CHE","Switzerland","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2000/che_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
49549,756,"CHE","Switzerland","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2001/che_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
49550,756,"CHE","Switzerland","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2001/che_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
49551,756,"CHE","Switzerland","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2001/che_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
49552,756,"CHE","Switzerland","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2001/che_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
49553,756,"CHE","Switzerland","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2001/che_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
49554,756,"CHE","Switzerland","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2001/che_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
49555,756,"CHE","Switzerland","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2001/che_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
49556,756,"CHE","Switzerland","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2001/che_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
49557,756,"CHE","Switzerland","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2002/che_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
49558,756,"CHE","Switzerland","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2002/che_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
49559,756,"CHE","Switzerland","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2002/che_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
49560,756,"CHE","Switzerland","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2002/che_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
49561,756,"CHE","Switzerland","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2002/che_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
49562,756,"CHE","Switzerland","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2002/che_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
49563,756,"CHE","Switzerland","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2002/che_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
49564,756,"CHE","Switzerland","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2002/che_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
49565,756,"CHE","Switzerland","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2003/che_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
49566,756,"CHE","Switzerland","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2003/che_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
49567,756,"CHE","Switzerland","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2003/che_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
49568,756,"CHE","Switzerland","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2003/che_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
49569,756,"CHE","Switzerland","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2003/che_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
49570,756,"CHE","Switzerland","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2003/che_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
49571,756,"CHE","Switzerland","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2003/che_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
49572,756,"CHE","Switzerland","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2003/che_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
49573,756,"CHE","Switzerland","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2004/che_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
49574,756,"CHE","Switzerland","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2004/che_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
49575,756,"CHE","Switzerland","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2004/che_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
49576,756,"CHE","Switzerland","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2004/che_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
49577,756,"CHE","Switzerland","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2004/che_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
49578,756,"CHE","Switzerland","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2004/che_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
49579,756,"CHE","Switzerland","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2004/che_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
49580,756,"CHE","Switzerland","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2004/che_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
49581,756,"CHE","Switzerland","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2005/che_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
49582,756,"CHE","Switzerland","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2005/che_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
49583,756,"CHE","Switzerland","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2005/che_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
49584,756,"CHE","Switzerland","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2005/che_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
49585,756,"CHE","Switzerland","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2005/che_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
49586,756,"CHE","Switzerland","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2005/che_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
49587,756,"CHE","Switzerland","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2005/che_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
49588,756,"CHE","Switzerland","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2005/che_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
49589,756,"CHE","Switzerland","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2006/che_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
49590,756,"CHE","Switzerland","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2006/che_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
49591,756,"CHE","Switzerland","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2006/che_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
49592,756,"CHE","Switzerland","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2006/che_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
49593,756,"CHE","Switzerland","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2006/che_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
49594,756,"CHE","Switzerland","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2006/che_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
49595,756,"CHE","Switzerland","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2006/che_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
49596,756,"CHE","Switzerland","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2006/che_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
49597,756,"CHE","Switzerland","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2007/che_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
49598,756,"CHE","Switzerland","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2007/che_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
49599,756,"CHE","Switzerland","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2007/che_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
49600,756,"CHE","Switzerland","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2007/che_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
49601,756,"CHE","Switzerland","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2007/che_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
49602,756,"CHE","Switzerland","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2007/che_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
49603,756,"CHE","Switzerland","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2007/che_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
49604,756,"CHE","Switzerland","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2007/che_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
49605,756,"CHE","Switzerland","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2008/che_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
49606,756,"CHE","Switzerland","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2008/che_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
49607,756,"CHE","Switzerland","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2008/che_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
49608,756,"CHE","Switzerland","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2008/che_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
49609,756,"CHE","Switzerland","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2008/che_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
49610,756,"CHE","Switzerland","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2008/che_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
49611,756,"CHE","Switzerland","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2008/che_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
49612,756,"CHE","Switzerland","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2008/che_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
49613,756,"CHE","Switzerland","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2009/che_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
49614,756,"CHE","Switzerland","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2009/che_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
49615,756,"CHE","Switzerland","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2009/che_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
49616,756,"CHE","Switzerland","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2009/che_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
49617,756,"CHE","Switzerland","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2009/che_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
49618,756,"CHE","Switzerland","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2009/che_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
49619,756,"CHE","Switzerland","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2009/che_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
49620,756,"CHE","Switzerland","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2009/che_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
49621,756,"CHE","Switzerland","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2010/che_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
49622,756,"CHE","Switzerland","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2010/che_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
49623,756,"CHE","Switzerland","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2010/che_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
49624,756,"CHE","Switzerland","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2010/che_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
49625,756,"CHE","Switzerland","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2010/che_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
49626,756,"CHE","Switzerland","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2010/che_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
49627,756,"CHE","Switzerland","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2010/che_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
49628,756,"CHE","Switzerland","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2010/che_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
49629,756,"CHE","Switzerland","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2011/che_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
49630,756,"CHE","Switzerland","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2011/che_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
49631,756,"CHE","Switzerland","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2011/che_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
49632,756,"CHE","Switzerland","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2011/che_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
49633,756,"CHE","Switzerland","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2011/che_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
49634,756,"CHE","Switzerland","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2011/che_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
49635,756,"CHE","Switzerland","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2011/che_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
49636,756,"CHE","Switzerland","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2011/che_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
49637,756,"CHE","Switzerland","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2012/che_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
49638,756,"CHE","Switzerland","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2012/che_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
49639,756,"CHE","Switzerland","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2012/che_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
49640,756,"CHE","Switzerland","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2012/che_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
49641,756,"CHE","Switzerland","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2012/che_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
49642,756,"CHE","Switzerland","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2012/che_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
49643,756,"CHE","Switzerland","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2012/che_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
49644,756,"CHE","Switzerland","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2012/che_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
49645,756,"CHE","Switzerland","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2013/che_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
49646,756,"CHE","Switzerland","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2013/che_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
49647,756,"CHE","Switzerland","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2013/che_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
49648,756,"CHE","Switzerland","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2013/che_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
49649,756,"CHE","Switzerland","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2013/che_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
49650,756,"CHE","Switzerland","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2013/che_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
49651,756,"CHE","Switzerland","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2013/che_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
49652,756,"CHE","Switzerland","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2013/che_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
49653,756,"CHE","Switzerland","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2014/che_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
49654,756,"CHE","Switzerland","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2014/che_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
49655,756,"CHE","Switzerland","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2014/che_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
49656,756,"CHE","Switzerland","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2014/che_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
49657,756,"CHE","Switzerland","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2014/che_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
49658,756,"CHE","Switzerland","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2014/che_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
49659,756,"CHE","Switzerland","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2014/che_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
49660,756,"CHE","Switzerland","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2014/che_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
49661,756,"CHE","Switzerland","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2015/che_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
49662,756,"CHE","Switzerland","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2015/che_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
49663,756,"CHE","Switzerland","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2015/che_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
49664,756,"CHE","Switzerland","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2015/che_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
49665,756,"CHE","Switzerland","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2015/che_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
49666,756,"CHE","Switzerland","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2015/che_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
49667,756,"CHE","Switzerland","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2015/che_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
49668,756,"CHE","Switzerland","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Annual/2015/che_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
49669,760,"SYR","Syria","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2000/syr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
49670,760,"SYR","Syria","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2000/syr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
49671,760,"SYR","Syria","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2000/syr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
49672,760,"SYR","Syria","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2000/syr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
49673,760,"SYR","Syria","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2000/syr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
49674,760,"SYR","Syria","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2000/syr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
49675,760,"SYR","Syria","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2000/syr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
49676,760,"SYR","Syria","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2000/syr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
49677,760,"SYR","Syria","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2001/syr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
49678,760,"SYR","Syria","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2001/syr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
49679,760,"SYR","Syria","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2001/syr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
49680,760,"SYR","Syria","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2001/syr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
49681,760,"SYR","Syria","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2001/syr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
49682,760,"SYR","Syria","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2001/syr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
49683,760,"SYR","Syria","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2001/syr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
49684,760,"SYR","Syria","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2001/syr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
49685,760,"SYR","Syria","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2002/syr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
49686,760,"SYR","Syria","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2002/syr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
49687,760,"SYR","Syria","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2002/syr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
49688,760,"SYR","Syria","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2002/syr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
49689,760,"SYR","Syria","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2002/syr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
49690,760,"SYR","Syria","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2002/syr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
49691,760,"SYR","Syria","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2002/syr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
49692,760,"SYR","Syria","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2002/syr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
49693,760,"SYR","Syria","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2003/syr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
49694,760,"SYR","Syria","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2003/syr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
49695,760,"SYR","Syria","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2003/syr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
49696,760,"SYR","Syria","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2003/syr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
49697,760,"SYR","Syria","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2003/syr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
49698,760,"SYR","Syria","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2003/syr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
49699,760,"SYR","Syria","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2003/syr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
49700,760,"SYR","Syria","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2003/syr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
49701,760,"SYR","Syria","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2004/syr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
49702,760,"SYR","Syria","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2004/syr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
49703,760,"SYR","Syria","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2004/syr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
49704,760,"SYR","Syria","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2004/syr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
49705,760,"SYR","Syria","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2004/syr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
49706,760,"SYR","Syria","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2004/syr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
49707,760,"SYR","Syria","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2004/syr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
49708,760,"SYR","Syria","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2004/syr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
49709,760,"SYR","Syria","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2005/syr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
49710,760,"SYR","Syria","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2005/syr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
49711,760,"SYR","Syria","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2005/syr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
49712,760,"SYR","Syria","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2005/syr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
49713,760,"SYR","Syria","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2005/syr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
49714,760,"SYR","Syria","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2005/syr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
49715,760,"SYR","Syria","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2005/syr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
49716,760,"SYR","Syria","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2005/syr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
49717,760,"SYR","Syria","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2006/syr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
49718,760,"SYR","Syria","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2006/syr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
49719,760,"SYR","Syria","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2006/syr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
49720,760,"SYR","Syria","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2006/syr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
49721,760,"SYR","Syria","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2006/syr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
49722,760,"SYR","Syria","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2006/syr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
49723,760,"SYR","Syria","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2006/syr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
49724,760,"SYR","Syria","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2006/syr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
49725,760,"SYR","Syria","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2007/syr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
49726,760,"SYR","Syria","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2007/syr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
49727,760,"SYR","Syria","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2007/syr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
49728,760,"SYR","Syria","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2007/syr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
49729,760,"SYR","Syria","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2007/syr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
49730,760,"SYR","Syria","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2007/syr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
49731,760,"SYR","Syria","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2007/syr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
49732,760,"SYR","Syria","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2007/syr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
49733,760,"SYR","Syria","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2008/syr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
49734,760,"SYR","Syria","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2008/syr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
49735,760,"SYR","Syria","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2008/syr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
49736,760,"SYR","Syria","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2008/syr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
49737,760,"SYR","Syria","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2008/syr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
49738,760,"SYR","Syria","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2008/syr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
49739,760,"SYR","Syria","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2008/syr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
49740,760,"SYR","Syria","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2008/syr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
49741,760,"SYR","Syria","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2009/syr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
49742,760,"SYR","Syria","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2009/syr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
49743,760,"SYR","Syria","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2009/syr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
49744,760,"SYR","Syria","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2009/syr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
49745,760,"SYR","Syria","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2009/syr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
49746,760,"SYR","Syria","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2009/syr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
49747,760,"SYR","Syria","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2009/syr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
49748,760,"SYR","Syria","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2009/syr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
49749,760,"SYR","Syria","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2010/syr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
49750,760,"SYR","Syria","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2010/syr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
49751,760,"SYR","Syria","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2010/syr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
49752,760,"SYR","Syria","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2010/syr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
49753,760,"SYR","Syria","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2010/syr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
49754,760,"SYR","Syria","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2010/syr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
49755,760,"SYR","Syria","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2010/syr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
49756,760,"SYR","Syria","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2010/syr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
49757,760,"SYR","Syria","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2011/syr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
49758,760,"SYR","Syria","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2011/syr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
49759,760,"SYR","Syria","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2011/syr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
49760,760,"SYR","Syria","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2011/syr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
49761,760,"SYR","Syria","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2011/syr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
49762,760,"SYR","Syria","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2011/syr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
49763,760,"SYR","Syria","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2011/syr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
49764,760,"SYR","Syria","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2011/syr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
49765,760,"SYR","Syria","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2012/syr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
49766,760,"SYR","Syria","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2012/syr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
49767,760,"SYR","Syria","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2012/syr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
49768,760,"SYR","Syria","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2012/syr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
49769,760,"SYR","Syria","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2012/syr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
49770,760,"SYR","Syria","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2012/syr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
49771,760,"SYR","Syria","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2012/syr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
49772,760,"SYR","Syria","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2012/syr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
49773,760,"SYR","Syria","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2013/syr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
49774,760,"SYR","Syria","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2013/syr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
49775,760,"SYR","Syria","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2013/syr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
49776,760,"SYR","Syria","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2013/syr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
49777,760,"SYR","Syria","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2013/syr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
49778,760,"SYR","Syria","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2013/syr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
49779,760,"SYR","Syria","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2013/syr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
49780,760,"SYR","Syria","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2013/syr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
49781,760,"SYR","Syria","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2014/syr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
49782,760,"SYR","Syria","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2014/syr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
49783,760,"SYR","Syria","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2014/syr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
49784,760,"SYR","Syria","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2014/syr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
49785,760,"SYR","Syria","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2014/syr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
49786,760,"SYR","Syria","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2014/syr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
49787,760,"SYR","Syria","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2014/syr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
49788,760,"SYR","Syria","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2014/syr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
49789,760,"SYR","Syria","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2015/syr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
49790,760,"SYR","Syria","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2015/syr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
49791,760,"SYR","Syria","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2015/syr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
49792,760,"SYR","Syria","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2015/syr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
49793,760,"SYR","Syria","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2015/syr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
49794,760,"SYR","Syria","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2015/syr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
49795,760,"SYR","Syria","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2015/syr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
49796,760,"SYR","Syria","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Annual/2015/syr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
49797,762,"TJK","Tajikistan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2000/tjk_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
49798,762,"TJK","Tajikistan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2000/tjk_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
49799,762,"TJK","Tajikistan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2000/tjk_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
49800,762,"TJK","Tajikistan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2000/tjk_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
49801,762,"TJK","Tajikistan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2000/tjk_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
49802,762,"TJK","Tajikistan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2000/tjk_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
49803,762,"TJK","Tajikistan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2000/tjk_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
49804,762,"TJK","Tajikistan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2000/tjk_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
49805,762,"TJK","Tajikistan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2001/tjk_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
49806,762,"TJK","Tajikistan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2001/tjk_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
49807,762,"TJK","Tajikistan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2001/tjk_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
49808,762,"TJK","Tajikistan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2001/tjk_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
49809,762,"TJK","Tajikistan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2001/tjk_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
49810,762,"TJK","Tajikistan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2001/tjk_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
49811,762,"TJK","Tajikistan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2001/tjk_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
49812,762,"TJK","Tajikistan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2001/tjk_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
49813,762,"TJK","Tajikistan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2002/tjk_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
49814,762,"TJK","Tajikistan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2002/tjk_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
49815,762,"TJK","Tajikistan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2002/tjk_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
49816,762,"TJK","Tajikistan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2002/tjk_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
49817,762,"TJK","Tajikistan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2002/tjk_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
49818,762,"TJK","Tajikistan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2002/tjk_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
49819,762,"TJK","Tajikistan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2002/tjk_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
49820,762,"TJK","Tajikistan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2002/tjk_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
49821,762,"TJK","Tajikistan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2003/tjk_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
49822,762,"TJK","Tajikistan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2003/tjk_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
49823,762,"TJK","Tajikistan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2003/tjk_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
49824,762,"TJK","Tajikistan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2003/tjk_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
49825,762,"TJK","Tajikistan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2003/tjk_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
49826,762,"TJK","Tajikistan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2003/tjk_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
49827,762,"TJK","Tajikistan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2003/tjk_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
49828,762,"TJK","Tajikistan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2003/tjk_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
49829,762,"TJK","Tajikistan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2004/tjk_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
49830,762,"TJK","Tajikistan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2004/tjk_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
49831,762,"TJK","Tajikistan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2004/tjk_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
49832,762,"TJK","Tajikistan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2004/tjk_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
49833,762,"TJK","Tajikistan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2004/tjk_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
49834,762,"TJK","Tajikistan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2004/tjk_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
49835,762,"TJK","Tajikistan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2004/tjk_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
49836,762,"TJK","Tajikistan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2004/tjk_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
49837,762,"TJK","Tajikistan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2005/tjk_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
49838,762,"TJK","Tajikistan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2005/tjk_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
49839,762,"TJK","Tajikistan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2005/tjk_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
49840,762,"TJK","Tajikistan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2005/tjk_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
49841,762,"TJK","Tajikistan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2005/tjk_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
49842,762,"TJK","Tajikistan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2005/tjk_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
49843,762,"TJK","Tajikistan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2005/tjk_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
49844,762,"TJK","Tajikistan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2005/tjk_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
49845,762,"TJK","Tajikistan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2006/tjk_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
49846,762,"TJK","Tajikistan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2006/tjk_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
49847,762,"TJK","Tajikistan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2006/tjk_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
49848,762,"TJK","Tajikistan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2006/tjk_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
49849,762,"TJK","Tajikistan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2006/tjk_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
49850,762,"TJK","Tajikistan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2006/tjk_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
49851,762,"TJK","Tajikistan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2006/tjk_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
49852,762,"TJK","Tajikistan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2006/tjk_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
49853,762,"TJK","Tajikistan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2007/tjk_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
49854,762,"TJK","Tajikistan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2007/tjk_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
49855,762,"TJK","Tajikistan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2007/tjk_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
49856,762,"TJK","Tajikistan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2007/tjk_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
49857,762,"TJK","Tajikistan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2007/tjk_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
49858,762,"TJK","Tajikistan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2007/tjk_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
49859,762,"TJK","Tajikistan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2007/tjk_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
49860,762,"TJK","Tajikistan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2007/tjk_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
49861,762,"TJK","Tajikistan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2008/tjk_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
49862,762,"TJK","Tajikistan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2008/tjk_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
49863,762,"TJK","Tajikistan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2008/tjk_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
49864,762,"TJK","Tajikistan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2008/tjk_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
49865,762,"TJK","Tajikistan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2008/tjk_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
49866,762,"TJK","Tajikistan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2008/tjk_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
49867,762,"TJK","Tajikistan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2008/tjk_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
49868,762,"TJK","Tajikistan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2008/tjk_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
49869,762,"TJK","Tajikistan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2009/tjk_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
49870,762,"TJK","Tajikistan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2009/tjk_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
49871,762,"TJK","Tajikistan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2009/tjk_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
49872,762,"TJK","Tajikistan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2009/tjk_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
49873,762,"TJK","Tajikistan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2009/tjk_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
49874,762,"TJK","Tajikistan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2009/tjk_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
49875,762,"TJK","Tajikistan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2009/tjk_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
49876,762,"TJK","Tajikistan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2009/tjk_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
49877,762,"TJK","Tajikistan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2010/tjk_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
49878,762,"TJK","Tajikistan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2010/tjk_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
49879,762,"TJK","Tajikistan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2010/tjk_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
49880,762,"TJK","Tajikistan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2010/tjk_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
49881,762,"TJK","Tajikistan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2010/tjk_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
49882,762,"TJK","Tajikistan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2010/tjk_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
49883,762,"TJK","Tajikistan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2010/tjk_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
49884,762,"TJK","Tajikistan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2010/tjk_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
49885,762,"TJK","Tajikistan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2011/tjk_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
49886,762,"TJK","Tajikistan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2011/tjk_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
49887,762,"TJK","Tajikistan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2011/tjk_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
49888,762,"TJK","Tajikistan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2011/tjk_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
49889,762,"TJK","Tajikistan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2011/tjk_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
49890,762,"TJK","Tajikistan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2011/tjk_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
49891,762,"TJK","Tajikistan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2011/tjk_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
49892,762,"TJK","Tajikistan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2011/tjk_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
49893,762,"TJK","Tajikistan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2012/tjk_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
49894,762,"TJK","Tajikistan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2012/tjk_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
49895,762,"TJK","Tajikistan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2012/tjk_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
49896,762,"TJK","Tajikistan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2012/tjk_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
49897,762,"TJK","Tajikistan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2012/tjk_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
49898,762,"TJK","Tajikistan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2012/tjk_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
49899,762,"TJK","Tajikistan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2012/tjk_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
49900,762,"TJK","Tajikistan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2012/tjk_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
49901,762,"TJK","Tajikistan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2013/tjk_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
49902,762,"TJK","Tajikistan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2013/tjk_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
49903,762,"TJK","Tajikistan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2013/tjk_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
49904,762,"TJK","Tajikistan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2013/tjk_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
49905,762,"TJK","Tajikistan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2013/tjk_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
49906,762,"TJK","Tajikistan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2013/tjk_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
49907,762,"TJK","Tajikistan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2013/tjk_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
49908,762,"TJK","Tajikistan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2013/tjk_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
49909,762,"TJK","Tajikistan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2014/tjk_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
49910,762,"TJK","Tajikistan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2014/tjk_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
49911,762,"TJK","Tajikistan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2014/tjk_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
49912,762,"TJK","Tajikistan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2014/tjk_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
49913,762,"TJK","Tajikistan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2014/tjk_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
49914,762,"TJK","Tajikistan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2014/tjk_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
49915,762,"TJK","Tajikistan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2014/tjk_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
49916,762,"TJK","Tajikistan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2014/tjk_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
49917,762,"TJK","Tajikistan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2015/tjk_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
49918,762,"TJK","Tajikistan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2015/tjk_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
49919,762,"TJK","Tajikistan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2015/tjk_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
49920,762,"TJK","Tajikistan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2015/tjk_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
49921,762,"TJK","Tajikistan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2015/tjk_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
49922,762,"TJK","Tajikistan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2015/tjk_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
49923,762,"TJK","Tajikistan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2015/tjk_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
49924,762,"TJK","Tajikistan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Annual/2015/tjk_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
49925,764,"THA","Thailand","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2000/tha_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
49926,764,"THA","Thailand","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2000/tha_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
49927,764,"THA","Thailand","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2000/tha_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
49928,764,"THA","Thailand","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2000/tha_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
49929,764,"THA","Thailand","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2000/tha_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
49930,764,"THA","Thailand","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2000/tha_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
49931,764,"THA","Thailand","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2000/tha_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
49932,764,"THA","Thailand","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2000/tha_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
49933,764,"THA","Thailand","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2001/tha_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
49934,764,"THA","Thailand","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2001/tha_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
49935,764,"THA","Thailand","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2001/tha_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
49936,764,"THA","Thailand","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2001/tha_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
49937,764,"THA","Thailand","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2001/tha_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
49938,764,"THA","Thailand","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2001/tha_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
49939,764,"THA","Thailand","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2001/tha_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
49940,764,"THA","Thailand","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2001/tha_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
49941,764,"THA","Thailand","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2002/tha_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
49942,764,"THA","Thailand","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2002/tha_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
49943,764,"THA","Thailand","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2002/tha_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
49944,764,"THA","Thailand","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2002/tha_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
49945,764,"THA","Thailand","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2002/tha_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
49946,764,"THA","Thailand","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2002/tha_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
49947,764,"THA","Thailand","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2002/tha_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
49948,764,"THA","Thailand","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2002/tha_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
49949,764,"THA","Thailand","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2003/tha_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
49950,764,"THA","Thailand","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2003/tha_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
49951,764,"THA","Thailand","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2003/tha_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
49952,764,"THA","Thailand","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2003/tha_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
49953,764,"THA","Thailand","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2003/tha_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
49954,764,"THA","Thailand","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2003/tha_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
49955,764,"THA","Thailand","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2003/tha_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
49956,764,"THA","Thailand","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2003/tha_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
49957,764,"THA","Thailand","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2004/tha_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
49958,764,"THA","Thailand","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2004/tha_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
49959,764,"THA","Thailand","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2004/tha_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
49960,764,"THA","Thailand","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2004/tha_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
49961,764,"THA","Thailand","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2004/tha_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
49962,764,"THA","Thailand","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2004/tha_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
49963,764,"THA","Thailand","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2004/tha_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
49964,764,"THA","Thailand","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2004/tha_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
49965,764,"THA","Thailand","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2005/tha_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
49966,764,"THA","Thailand","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2005/tha_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
49967,764,"THA","Thailand","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2005/tha_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
49968,764,"THA","Thailand","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2005/tha_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
49969,764,"THA","Thailand","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2005/tha_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
49970,764,"THA","Thailand","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2005/tha_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
49971,764,"THA","Thailand","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2005/tha_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
49972,764,"THA","Thailand","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2005/tha_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
49973,764,"THA","Thailand","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2006/tha_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
49974,764,"THA","Thailand","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2006/tha_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
49975,764,"THA","Thailand","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2006/tha_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
49976,764,"THA","Thailand","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2006/tha_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
49977,764,"THA","Thailand","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2006/tha_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
49978,764,"THA","Thailand","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2006/tha_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
49979,764,"THA","Thailand","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2006/tha_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
49980,764,"THA","Thailand","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2006/tha_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
49981,764,"THA","Thailand","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2007/tha_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
49982,764,"THA","Thailand","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2007/tha_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
49983,764,"THA","Thailand","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2007/tha_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
49984,764,"THA","Thailand","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2007/tha_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
49985,764,"THA","Thailand","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2007/tha_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
49986,764,"THA","Thailand","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2007/tha_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
49987,764,"THA","Thailand","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2007/tha_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
49988,764,"THA","Thailand","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2007/tha_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
49989,764,"THA","Thailand","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2008/tha_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
49990,764,"THA","Thailand","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2008/tha_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
49991,764,"THA","Thailand","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2008/tha_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
49992,764,"THA","Thailand","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2008/tha_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
49993,764,"THA","Thailand","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2008/tha_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
49994,764,"THA","Thailand","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2008/tha_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
49995,764,"THA","Thailand","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2008/tha_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
49996,764,"THA","Thailand","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2008/tha_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
49997,764,"THA","Thailand","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2009/tha_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
49998,764,"THA","Thailand","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2009/tha_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
49999,764,"THA","Thailand","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2009/tha_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
50000,764,"THA","Thailand","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2009/tha_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
50001,764,"THA","Thailand","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2009/tha_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
50002,764,"THA","Thailand","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2009/tha_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
50003,764,"THA","Thailand","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2009/tha_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
50004,764,"THA","Thailand","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2009/tha_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
50005,764,"THA","Thailand","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2010/tha_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
50006,764,"THA","Thailand","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2010/tha_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
50007,764,"THA","Thailand","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2010/tha_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
50008,764,"THA","Thailand","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2010/tha_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
50009,764,"THA","Thailand","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2010/tha_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
50010,764,"THA","Thailand","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2010/tha_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
50011,764,"THA","Thailand","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2010/tha_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
50012,764,"THA","Thailand","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2010/tha_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
50013,764,"THA","Thailand","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2011/tha_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
50014,764,"THA","Thailand","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2011/tha_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
50015,764,"THA","Thailand","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2011/tha_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
50016,764,"THA","Thailand","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2011/tha_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
50017,764,"THA","Thailand","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2011/tha_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
50018,764,"THA","Thailand","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2011/tha_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
50019,764,"THA","Thailand","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2011/tha_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
50020,764,"THA","Thailand","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2011/tha_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
50021,764,"THA","Thailand","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2012/tha_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
50022,764,"THA","Thailand","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2012/tha_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
50023,764,"THA","Thailand","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2012/tha_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
50024,764,"THA","Thailand","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2012/tha_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
50025,764,"THA","Thailand","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2012/tha_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
50026,764,"THA","Thailand","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2012/tha_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
50027,764,"THA","Thailand","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2012/tha_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
50028,764,"THA","Thailand","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2012/tha_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
50029,764,"THA","Thailand","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2013/tha_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
50030,764,"THA","Thailand","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2013/tha_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
50031,764,"THA","Thailand","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2013/tha_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
50032,764,"THA","Thailand","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2013/tha_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
50033,764,"THA","Thailand","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2013/tha_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
50034,764,"THA","Thailand","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2013/tha_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
50035,764,"THA","Thailand","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2013/tha_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
50036,764,"THA","Thailand","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2013/tha_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
50037,764,"THA","Thailand","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2014/tha_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
50038,764,"THA","Thailand","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2014/tha_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
50039,764,"THA","Thailand","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2014/tha_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
50040,764,"THA","Thailand","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2014/tha_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
50041,764,"THA","Thailand","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2014/tha_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
50042,764,"THA","Thailand","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2014/tha_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
50043,764,"THA","Thailand","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2014/tha_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
50044,764,"THA","Thailand","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2014/tha_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
50045,764,"THA","Thailand","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2015/tha_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
50046,764,"THA","Thailand","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2015/tha_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
50047,764,"THA","Thailand","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2015/tha_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
50048,764,"THA","Thailand","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2015/tha_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
50049,764,"THA","Thailand","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2015/tha_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
50050,764,"THA","Thailand","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2015/tha_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
50051,764,"THA","Thailand","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2015/tha_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
50052,764,"THA","Thailand","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Annual/2015/tha_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
50053,768,"TGO","Togo","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2000/tgo_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
50054,768,"TGO","Togo","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2000/tgo_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
50055,768,"TGO","Togo","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2000/tgo_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
50056,768,"TGO","Togo","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2000/tgo_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
50057,768,"TGO","Togo","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2000/tgo_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
50058,768,"TGO","Togo","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2000/tgo_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
50059,768,"TGO","Togo","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2000/tgo_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
50060,768,"TGO","Togo","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2000/tgo_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
50061,768,"TGO","Togo","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2001/tgo_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
50062,768,"TGO","Togo","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2001/tgo_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
50063,768,"TGO","Togo","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2001/tgo_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
50064,768,"TGO","Togo","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2001/tgo_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
50065,768,"TGO","Togo","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2001/tgo_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
50066,768,"TGO","Togo","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2001/tgo_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
50067,768,"TGO","Togo","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2001/tgo_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
50068,768,"TGO","Togo","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2001/tgo_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
50069,768,"TGO","Togo","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2002/tgo_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
50070,768,"TGO","Togo","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2002/tgo_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
50071,768,"TGO","Togo","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2002/tgo_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
50072,768,"TGO","Togo","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2002/tgo_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
50073,768,"TGO","Togo","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2002/tgo_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
50074,768,"TGO","Togo","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2002/tgo_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
50075,768,"TGO","Togo","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2002/tgo_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
50076,768,"TGO","Togo","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2002/tgo_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
50077,768,"TGO","Togo","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2003/tgo_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
50078,768,"TGO","Togo","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2003/tgo_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
50079,768,"TGO","Togo","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2003/tgo_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
50080,768,"TGO","Togo","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2003/tgo_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
50081,768,"TGO","Togo","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2003/tgo_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
50082,768,"TGO","Togo","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2003/tgo_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
50083,768,"TGO","Togo","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2003/tgo_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
50084,768,"TGO","Togo","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2003/tgo_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
50085,768,"TGO","Togo","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2004/tgo_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
50086,768,"TGO","Togo","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2004/tgo_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
50087,768,"TGO","Togo","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2004/tgo_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
50088,768,"TGO","Togo","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2004/tgo_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
50089,768,"TGO","Togo","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2004/tgo_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
50090,768,"TGO","Togo","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2004/tgo_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
50091,768,"TGO","Togo","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2004/tgo_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
50092,768,"TGO","Togo","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2004/tgo_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
50093,768,"TGO","Togo","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2005/tgo_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
50094,768,"TGO","Togo","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2005/tgo_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
50095,768,"TGO","Togo","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2005/tgo_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
50096,768,"TGO","Togo","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2005/tgo_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
50097,768,"TGO","Togo","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2005/tgo_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
50098,768,"TGO","Togo","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2005/tgo_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
50099,768,"TGO","Togo","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2005/tgo_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
50100,768,"TGO","Togo","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2005/tgo_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
50101,768,"TGO","Togo","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2006/tgo_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
50102,768,"TGO","Togo","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2006/tgo_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
50103,768,"TGO","Togo","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2006/tgo_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
50104,768,"TGO","Togo","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2006/tgo_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
50105,768,"TGO","Togo","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2006/tgo_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
50106,768,"TGO","Togo","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2006/tgo_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
50107,768,"TGO","Togo","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2006/tgo_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
50108,768,"TGO","Togo","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2006/tgo_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
50109,768,"TGO","Togo","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2007/tgo_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
50110,768,"TGO","Togo","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2007/tgo_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
50111,768,"TGO","Togo","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2007/tgo_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
50112,768,"TGO","Togo","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2007/tgo_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
50113,768,"TGO","Togo","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2007/tgo_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
50114,768,"TGO","Togo","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2007/tgo_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
50115,768,"TGO","Togo","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2007/tgo_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
50116,768,"TGO","Togo","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2007/tgo_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
50117,768,"TGO","Togo","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2008/tgo_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
50118,768,"TGO","Togo","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2008/tgo_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
50119,768,"TGO","Togo","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2008/tgo_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
50120,768,"TGO","Togo","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2008/tgo_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
50121,768,"TGO","Togo","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2008/tgo_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
50122,768,"TGO","Togo","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2008/tgo_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
50123,768,"TGO","Togo","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2008/tgo_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
50124,768,"TGO","Togo","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2008/tgo_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
50125,768,"TGO","Togo","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2009/tgo_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
50126,768,"TGO","Togo","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2009/tgo_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
50127,768,"TGO","Togo","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2009/tgo_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
50128,768,"TGO","Togo","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2009/tgo_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
50129,768,"TGO","Togo","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2009/tgo_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
50130,768,"TGO","Togo","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2009/tgo_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
50131,768,"TGO","Togo","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2009/tgo_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
50132,768,"TGO","Togo","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2009/tgo_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
50133,768,"TGO","Togo","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2010/tgo_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
50134,768,"TGO","Togo","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2010/tgo_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
50135,768,"TGO","Togo","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2010/tgo_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
50136,768,"TGO","Togo","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2010/tgo_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
50137,768,"TGO","Togo","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2010/tgo_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
50138,768,"TGO","Togo","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2010/tgo_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
50139,768,"TGO","Togo","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2010/tgo_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
50140,768,"TGO","Togo","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2010/tgo_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
50141,768,"TGO","Togo","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2011/tgo_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
50142,768,"TGO","Togo","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2011/tgo_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
50143,768,"TGO","Togo","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2011/tgo_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
50144,768,"TGO","Togo","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2011/tgo_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
50145,768,"TGO","Togo","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2011/tgo_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
50146,768,"TGO","Togo","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2011/tgo_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
50147,768,"TGO","Togo","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2011/tgo_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
50148,768,"TGO","Togo","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2011/tgo_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
50149,768,"TGO","Togo","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2012/tgo_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
50150,768,"TGO","Togo","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2012/tgo_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
50151,768,"TGO","Togo","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2012/tgo_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
50152,768,"TGO","Togo","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2012/tgo_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
50153,768,"TGO","Togo","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2012/tgo_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
50154,768,"TGO","Togo","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2012/tgo_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
50155,768,"TGO","Togo","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2012/tgo_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
50156,768,"TGO","Togo","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2012/tgo_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
50157,768,"TGO","Togo","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2013/tgo_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
50158,768,"TGO","Togo","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2013/tgo_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
50159,768,"TGO","Togo","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2013/tgo_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
50160,768,"TGO","Togo","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2013/tgo_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
50161,768,"TGO","Togo","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2013/tgo_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
50162,768,"TGO","Togo","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2013/tgo_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
50163,768,"TGO","Togo","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2013/tgo_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
50164,768,"TGO","Togo","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2013/tgo_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
50165,768,"TGO","Togo","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2014/tgo_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
50166,768,"TGO","Togo","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2014/tgo_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
50167,768,"TGO","Togo","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2014/tgo_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
50168,768,"TGO","Togo","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2014/tgo_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
50169,768,"TGO","Togo","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2014/tgo_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
50170,768,"TGO","Togo","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2014/tgo_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
50171,768,"TGO","Togo","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2014/tgo_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
50172,768,"TGO","Togo","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2014/tgo_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
50173,768,"TGO","Togo","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2015/tgo_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
50174,768,"TGO","Togo","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2015/tgo_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
50175,768,"TGO","Togo","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2015/tgo_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
50176,768,"TGO","Togo","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2015/tgo_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
50177,768,"TGO","Togo","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2015/tgo_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
50178,768,"TGO","Togo","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2015/tgo_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
50179,768,"TGO","Togo","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2015/tgo_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
50180,768,"TGO","Togo","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Annual/2015/tgo_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
50181,772,"TKL","Tokelau","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2000/tkl_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
50182,772,"TKL","Tokelau","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2000/tkl_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
50183,772,"TKL","Tokelau","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2000/tkl_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
50184,772,"TKL","Tokelau","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2000/tkl_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
50185,772,"TKL","Tokelau","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2000/tkl_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
50186,772,"TKL","Tokelau","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2000/tkl_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
50187,772,"TKL","Tokelau","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2000/tkl_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
50188,772,"TKL","Tokelau","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2000/tkl_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
50189,772,"TKL","Tokelau","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2001/tkl_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
50190,772,"TKL","Tokelau","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2001/tkl_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
50191,772,"TKL","Tokelau","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2001/tkl_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
50192,772,"TKL","Tokelau","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2001/tkl_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
50193,772,"TKL","Tokelau","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2001/tkl_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
50194,772,"TKL","Tokelau","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2001/tkl_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
50195,772,"TKL","Tokelau","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2001/tkl_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
50196,772,"TKL","Tokelau","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2001/tkl_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
50197,772,"TKL","Tokelau","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2002/tkl_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
50198,772,"TKL","Tokelau","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2002/tkl_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
50199,772,"TKL","Tokelau","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2002/tkl_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
50200,772,"TKL","Tokelau","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2002/tkl_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
50201,772,"TKL","Tokelau","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2002/tkl_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
50202,772,"TKL","Tokelau","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2002/tkl_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
50203,772,"TKL","Tokelau","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2002/tkl_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
50204,772,"TKL","Tokelau","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2002/tkl_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
50205,772,"TKL","Tokelau","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2003/tkl_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
50206,772,"TKL","Tokelau","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2003/tkl_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
50207,772,"TKL","Tokelau","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2003/tkl_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
50208,772,"TKL","Tokelau","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2003/tkl_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
50209,772,"TKL","Tokelau","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2003/tkl_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
50210,772,"TKL","Tokelau","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2003/tkl_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
50211,772,"TKL","Tokelau","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2003/tkl_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
50212,772,"TKL","Tokelau","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2003/tkl_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
50213,772,"TKL","Tokelau","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2004/tkl_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
50214,772,"TKL","Tokelau","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2004/tkl_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
50215,772,"TKL","Tokelau","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2004/tkl_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
50216,772,"TKL","Tokelau","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2004/tkl_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
50217,772,"TKL","Tokelau","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2004/tkl_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
50218,772,"TKL","Tokelau","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2004/tkl_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
50219,772,"TKL","Tokelau","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2004/tkl_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
50220,772,"TKL","Tokelau","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2004/tkl_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
50221,772,"TKL","Tokelau","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2005/tkl_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
50222,772,"TKL","Tokelau","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2005/tkl_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
50223,772,"TKL","Tokelau","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2005/tkl_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
50224,772,"TKL","Tokelau","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2005/tkl_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
50225,772,"TKL","Tokelau","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2005/tkl_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
50226,772,"TKL","Tokelau","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2005/tkl_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
50227,772,"TKL","Tokelau","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2005/tkl_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
50228,772,"TKL","Tokelau","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2005/tkl_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
50229,772,"TKL","Tokelau","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2006/tkl_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
50230,772,"TKL","Tokelau","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2006/tkl_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
50231,772,"TKL","Tokelau","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2006/tkl_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
50232,772,"TKL","Tokelau","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2006/tkl_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
50233,772,"TKL","Tokelau","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2006/tkl_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
50234,772,"TKL","Tokelau","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2006/tkl_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
50235,772,"TKL","Tokelau","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2006/tkl_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
50236,772,"TKL","Tokelau","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2006/tkl_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
50237,772,"TKL","Tokelau","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2007/tkl_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
50238,772,"TKL","Tokelau","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2007/tkl_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
50239,772,"TKL","Tokelau","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2007/tkl_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
50240,772,"TKL","Tokelau","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2007/tkl_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
50241,772,"TKL","Tokelau","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2007/tkl_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
50242,772,"TKL","Tokelau","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2007/tkl_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
50243,772,"TKL","Tokelau","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2007/tkl_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
50244,772,"TKL","Tokelau","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2007/tkl_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
50245,772,"TKL","Tokelau","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2008/tkl_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
50246,772,"TKL","Tokelau","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2008/tkl_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
50247,772,"TKL","Tokelau","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2008/tkl_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
50248,772,"TKL","Tokelau","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2008/tkl_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
50249,772,"TKL","Tokelau","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2008/tkl_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
50250,772,"TKL","Tokelau","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2008/tkl_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
50251,772,"TKL","Tokelau","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2008/tkl_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
50252,772,"TKL","Tokelau","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2008/tkl_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
50253,772,"TKL","Tokelau","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2009/tkl_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
50254,772,"TKL","Tokelau","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2009/tkl_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
50255,772,"TKL","Tokelau","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2009/tkl_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
50256,772,"TKL","Tokelau","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2009/tkl_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
50257,772,"TKL","Tokelau","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2009/tkl_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
50258,772,"TKL","Tokelau","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2009/tkl_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
50259,772,"TKL","Tokelau","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2009/tkl_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
50260,772,"TKL","Tokelau","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2009/tkl_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
50261,772,"TKL","Tokelau","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2010/tkl_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
50262,772,"TKL","Tokelau","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2010/tkl_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
50263,772,"TKL","Tokelau","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2010/tkl_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
50264,772,"TKL","Tokelau","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2010/tkl_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
50265,772,"TKL","Tokelau","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2010/tkl_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
50266,772,"TKL","Tokelau","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2010/tkl_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
50267,772,"TKL","Tokelau","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2010/tkl_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
50268,772,"TKL","Tokelau","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2010/tkl_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
50269,772,"TKL","Tokelau","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2011/tkl_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
50270,772,"TKL","Tokelau","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2011/tkl_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
50271,772,"TKL","Tokelau","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2011/tkl_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
50272,772,"TKL","Tokelau","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2011/tkl_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
50273,772,"TKL","Tokelau","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2011/tkl_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
50274,772,"TKL","Tokelau","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2011/tkl_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
50275,772,"TKL","Tokelau","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2011/tkl_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
50276,772,"TKL","Tokelau","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2011/tkl_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
50277,772,"TKL","Tokelau","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2012/tkl_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
50278,772,"TKL","Tokelau","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2012/tkl_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
50279,772,"TKL","Tokelau","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2012/tkl_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
50280,772,"TKL","Tokelau","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2012/tkl_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
50281,772,"TKL","Tokelau","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2012/tkl_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
50282,772,"TKL","Tokelau","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2012/tkl_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
50283,772,"TKL","Tokelau","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2012/tkl_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
50284,772,"TKL","Tokelau","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2012/tkl_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
50285,772,"TKL","Tokelau","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2013/tkl_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
50286,772,"TKL","Tokelau","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2013/tkl_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
50287,772,"TKL","Tokelau","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2013/tkl_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
50288,772,"TKL","Tokelau","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2013/tkl_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
50289,772,"TKL","Tokelau","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2013/tkl_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
50290,772,"TKL","Tokelau","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2013/tkl_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
50291,772,"TKL","Tokelau","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2013/tkl_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
50292,772,"TKL","Tokelau","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2013/tkl_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
50293,772,"TKL","Tokelau","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2014/tkl_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
50294,772,"TKL","Tokelau","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2014/tkl_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
50295,772,"TKL","Tokelau","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2014/tkl_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
50296,772,"TKL","Tokelau","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2014/tkl_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
50297,772,"TKL","Tokelau","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2014/tkl_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
50298,772,"TKL","Tokelau","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2014/tkl_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
50299,772,"TKL","Tokelau","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2014/tkl_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
50300,772,"TKL","Tokelau","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2014/tkl_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
50301,772,"TKL","Tokelau","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2015/tkl_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
50302,772,"TKL","Tokelau","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2015/tkl_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
50303,772,"TKL","Tokelau","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2015/tkl_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
50304,772,"TKL","Tokelau","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2015/tkl_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
50305,772,"TKL","Tokelau","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2015/tkl_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
50306,772,"TKL","Tokelau","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2015/tkl_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
50307,772,"TKL","Tokelau","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2015/tkl_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
50308,772,"TKL","Tokelau","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Annual/2015/tkl_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
50309,776,"TON","Tonga","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2000/ton_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
50310,776,"TON","Tonga","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2000/ton_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
50311,776,"TON","Tonga","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2000/ton_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
50312,776,"TON","Tonga","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2000/ton_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
50313,776,"TON","Tonga","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2000/ton_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
50314,776,"TON","Tonga","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2000/ton_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
50315,776,"TON","Tonga","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2000/ton_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
50316,776,"TON","Tonga","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2000/ton_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
50317,776,"TON","Tonga","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2001/ton_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
50318,776,"TON","Tonga","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2001/ton_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
50319,776,"TON","Tonga","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2001/ton_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
50320,776,"TON","Tonga","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2001/ton_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
50321,776,"TON","Tonga","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2001/ton_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
50322,776,"TON","Tonga","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2001/ton_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
50323,776,"TON","Tonga","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2001/ton_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
50324,776,"TON","Tonga","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2001/ton_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
50325,776,"TON","Tonga","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2002/ton_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
50326,776,"TON","Tonga","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2002/ton_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
50327,776,"TON","Tonga","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2002/ton_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
50328,776,"TON","Tonga","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2002/ton_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
50329,776,"TON","Tonga","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2002/ton_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
50330,776,"TON","Tonga","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2002/ton_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
50331,776,"TON","Tonga","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2002/ton_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
50332,776,"TON","Tonga","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2002/ton_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
50333,776,"TON","Tonga","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2003/ton_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
50334,776,"TON","Tonga","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2003/ton_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
50335,776,"TON","Tonga","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2003/ton_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
50336,776,"TON","Tonga","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2003/ton_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
50337,776,"TON","Tonga","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2003/ton_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
50338,776,"TON","Tonga","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2003/ton_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
50339,776,"TON","Tonga","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2003/ton_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
50340,776,"TON","Tonga","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2003/ton_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
50341,776,"TON","Tonga","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2004/ton_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
50342,776,"TON","Tonga","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2004/ton_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
50343,776,"TON","Tonga","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2004/ton_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
50344,776,"TON","Tonga","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2004/ton_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
50345,776,"TON","Tonga","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2004/ton_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
50346,776,"TON","Tonga","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2004/ton_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
50347,776,"TON","Tonga","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2004/ton_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
50348,776,"TON","Tonga","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2004/ton_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
50349,776,"TON","Tonga","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2005/ton_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
50350,776,"TON","Tonga","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2005/ton_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
50351,776,"TON","Tonga","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2005/ton_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
50352,776,"TON","Tonga","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2005/ton_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
50353,776,"TON","Tonga","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2005/ton_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
50354,776,"TON","Tonga","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2005/ton_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
50355,776,"TON","Tonga","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2005/ton_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
50356,776,"TON","Tonga","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2005/ton_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
50357,776,"TON","Tonga","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2006/ton_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
50358,776,"TON","Tonga","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2006/ton_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
50359,776,"TON","Tonga","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2006/ton_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
50360,776,"TON","Tonga","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2006/ton_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
50361,776,"TON","Tonga","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2006/ton_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
50362,776,"TON","Tonga","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2006/ton_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
50363,776,"TON","Tonga","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2006/ton_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
50364,776,"TON","Tonga","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2006/ton_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
50365,776,"TON","Tonga","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2007/ton_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
50366,776,"TON","Tonga","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2007/ton_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
50367,776,"TON","Tonga","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2007/ton_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
50368,776,"TON","Tonga","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2007/ton_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
50369,776,"TON","Tonga","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2007/ton_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
50370,776,"TON","Tonga","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2007/ton_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
50371,776,"TON","Tonga","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2007/ton_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
50372,776,"TON","Tonga","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2007/ton_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
50373,776,"TON","Tonga","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2008/ton_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
50374,776,"TON","Tonga","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2008/ton_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
50375,776,"TON","Tonga","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2008/ton_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
50376,776,"TON","Tonga","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2008/ton_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
50377,776,"TON","Tonga","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2008/ton_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
50378,776,"TON","Tonga","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2008/ton_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
50379,776,"TON","Tonga","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2008/ton_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
50380,776,"TON","Tonga","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2008/ton_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
50381,776,"TON","Tonga","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2009/ton_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
50382,776,"TON","Tonga","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2009/ton_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
50383,776,"TON","Tonga","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2009/ton_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
50384,776,"TON","Tonga","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2009/ton_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
50385,776,"TON","Tonga","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2009/ton_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
50386,776,"TON","Tonga","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2009/ton_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
50387,776,"TON","Tonga","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2009/ton_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
50388,776,"TON","Tonga","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2009/ton_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
50389,776,"TON","Tonga","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2010/ton_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
50390,776,"TON","Tonga","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2010/ton_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
50391,776,"TON","Tonga","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2010/ton_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
50392,776,"TON","Tonga","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2010/ton_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
50393,776,"TON","Tonga","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2010/ton_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
50394,776,"TON","Tonga","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2010/ton_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
50395,776,"TON","Tonga","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2010/ton_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
50396,776,"TON","Tonga","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2010/ton_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
50397,776,"TON","Tonga","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2011/ton_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
50398,776,"TON","Tonga","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2011/ton_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
50399,776,"TON","Tonga","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2011/ton_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
50400,776,"TON","Tonga","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2011/ton_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
50401,776,"TON","Tonga","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2011/ton_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
50402,776,"TON","Tonga","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2011/ton_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
50403,776,"TON","Tonga","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2011/ton_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
50404,776,"TON","Tonga","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2011/ton_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
50405,776,"TON","Tonga","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2012/ton_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
50406,776,"TON","Tonga","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2012/ton_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
50407,776,"TON","Tonga","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2012/ton_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
50408,776,"TON","Tonga","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2012/ton_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
50409,776,"TON","Tonga","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2012/ton_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
50410,776,"TON","Tonga","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2012/ton_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
50411,776,"TON","Tonga","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2012/ton_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
50412,776,"TON","Tonga","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2012/ton_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
50413,776,"TON","Tonga","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2013/ton_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
50414,776,"TON","Tonga","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2013/ton_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
50415,776,"TON","Tonga","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2013/ton_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
50416,776,"TON","Tonga","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2013/ton_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
50417,776,"TON","Tonga","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2013/ton_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
50418,776,"TON","Tonga","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2013/ton_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
50419,776,"TON","Tonga","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2013/ton_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
50420,776,"TON","Tonga","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2013/ton_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
50421,776,"TON","Tonga","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2014/ton_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
50422,776,"TON","Tonga","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2014/ton_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
50423,776,"TON","Tonga","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2014/ton_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
50424,776,"TON","Tonga","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2014/ton_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
50425,776,"TON","Tonga","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2014/ton_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
50426,776,"TON","Tonga","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2014/ton_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
50427,776,"TON","Tonga","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2014/ton_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
50428,776,"TON","Tonga","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2014/ton_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
50429,776,"TON","Tonga","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2015/ton_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
50430,776,"TON","Tonga","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2015/ton_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
50431,776,"TON","Tonga","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2015/ton_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
50432,776,"TON","Tonga","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2015/ton_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
50433,776,"TON","Tonga","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2015/ton_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
50434,776,"TON","Tonga","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2015/ton_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
50435,776,"TON","Tonga","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2015/ton_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
50436,776,"TON","Tonga","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Annual/2015/ton_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
50437,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2000/tto_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
50438,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2000/tto_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
50439,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2000/tto_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
50440,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2000/tto_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
50441,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2000/tto_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
50442,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2000/tto_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
50443,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2000/tto_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
50444,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2000/tto_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
50445,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2001/tto_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
50446,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2001/tto_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
50447,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2001/tto_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
50448,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2001/tto_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
50449,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2001/tto_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
50450,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2001/tto_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
50451,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2001/tto_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
50452,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2001/tto_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
50453,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2002/tto_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
50454,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2002/tto_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
50455,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2002/tto_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
50456,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2002/tto_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
50457,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2002/tto_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
50458,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2002/tto_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
50459,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2002/tto_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
50460,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2002/tto_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
50461,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2003/tto_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
50462,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2003/tto_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
50463,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2003/tto_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
50464,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2003/tto_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
50465,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2003/tto_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
50466,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2003/tto_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
50467,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2003/tto_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
50468,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2003/tto_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
50469,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2004/tto_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
50470,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2004/tto_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
50471,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2004/tto_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
50472,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2004/tto_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
50473,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2004/tto_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
50474,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2004/tto_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
50475,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2004/tto_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
50476,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2004/tto_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
50477,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2005/tto_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
50478,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2005/tto_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
50479,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2005/tto_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
50480,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2005/tto_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
50481,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2005/tto_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
50482,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2005/tto_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
50483,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2005/tto_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
50484,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2005/tto_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
50485,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2006/tto_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
50486,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2006/tto_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
50487,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2006/tto_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
50488,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2006/tto_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
50489,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2006/tto_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
50490,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2006/tto_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
50491,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2006/tto_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
50492,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2006/tto_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
50493,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2007/tto_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
50494,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2007/tto_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
50495,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2007/tto_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
50496,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2007/tto_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
50497,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2007/tto_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
50498,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2007/tto_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
50499,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2007/tto_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
50500,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2007/tto_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
50501,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2008/tto_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
50502,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2008/tto_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
50503,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2008/tto_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
50504,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2008/tto_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
50505,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2008/tto_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
50506,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2008/tto_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
50507,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2008/tto_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
50508,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2008/tto_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
50509,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2009/tto_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
50510,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2009/tto_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
50511,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2009/tto_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
50512,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2009/tto_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
50513,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2009/tto_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
50514,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2009/tto_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
50515,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2009/tto_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
50516,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2009/tto_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
50517,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2010/tto_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
50518,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2010/tto_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
50519,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2010/tto_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
50520,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2010/tto_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
50521,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2010/tto_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
50522,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2010/tto_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
50523,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2010/tto_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
50524,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2010/tto_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
50525,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2011/tto_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
50526,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2011/tto_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
50527,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2011/tto_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
50528,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2011/tto_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
50529,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2011/tto_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
50530,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2011/tto_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
50531,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2011/tto_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
50532,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2011/tto_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
50533,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2012/tto_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
50534,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2012/tto_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
50535,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2012/tto_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
50536,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2012/tto_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
50537,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2012/tto_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
50538,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2012/tto_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
50539,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2012/tto_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
50540,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2012/tto_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
50541,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2013/tto_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
50542,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2013/tto_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
50543,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2013/tto_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
50544,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2013/tto_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
50545,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2013/tto_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
50546,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2013/tto_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
50547,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2013/tto_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
50548,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2013/tto_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
50549,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2014/tto_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
50550,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2014/tto_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
50551,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2014/tto_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
50552,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2014/tto_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
50553,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2014/tto_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
50554,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2014/tto_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
50555,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2014/tto_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
50556,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2014/tto_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
50557,780,"TTO","Trinidad and Tobago","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2015/tto_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
50558,780,"TTO","Trinidad and Tobago","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2015/tto_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
50559,780,"TTO","Trinidad and Tobago","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2015/tto_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
50560,780,"TTO","Trinidad and Tobago","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2015/tto_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
50561,780,"TTO","Trinidad and Tobago","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2015/tto_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
50562,780,"TTO","Trinidad and Tobago","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2015/tto_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
50563,780,"TTO","Trinidad and Tobago","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2015/tto_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
50564,780,"TTO","Trinidad and Tobago","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Annual/2015/tto_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
50565,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2000/are_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
50566,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2000/are_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
50567,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2000/are_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
50568,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2000/are_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
50569,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2000/are_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
50570,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2000/are_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
50571,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2000/are_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
50572,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2000/are_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
50573,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2001/are_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
50574,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2001/are_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
50575,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2001/are_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
50576,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2001/are_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
50577,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2001/are_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
50578,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2001/are_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
50579,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2001/are_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
50580,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2001/are_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
50581,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2002/are_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
50582,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2002/are_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
50583,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2002/are_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
50584,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2002/are_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
50585,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2002/are_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
50586,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2002/are_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
50587,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2002/are_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
50588,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2002/are_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
50589,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2003/are_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
50590,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2003/are_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
50591,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2003/are_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
50592,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2003/are_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
50593,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2003/are_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
50594,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2003/are_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
50595,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2003/are_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
50596,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2003/are_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
50597,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2004/are_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
50598,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2004/are_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
50599,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2004/are_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
50600,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2004/are_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
50601,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2004/are_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
50602,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2004/are_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
50603,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2004/are_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
50604,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2004/are_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
50605,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2005/are_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
50606,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2005/are_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
50607,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2005/are_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
50608,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2005/are_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
50609,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2005/are_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
50610,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2005/are_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
50611,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2005/are_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
50612,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2005/are_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
50613,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2006/are_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
50614,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2006/are_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
50615,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2006/are_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
50616,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2006/are_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
50617,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2006/are_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
50618,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2006/are_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
50619,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2006/are_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
50620,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2006/are_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
50621,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2007/are_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
50622,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2007/are_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
50623,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2007/are_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
50624,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2007/are_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
50625,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2007/are_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
50626,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2007/are_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
50627,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2007/are_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
50628,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2007/are_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
50629,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2008/are_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
50630,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2008/are_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
50631,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2008/are_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
50632,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2008/are_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
50633,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2008/are_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
50634,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2008/are_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
50635,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2008/are_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
50636,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2008/are_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
50637,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2009/are_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
50638,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2009/are_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
50639,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2009/are_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
50640,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2009/are_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
50641,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2009/are_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
50642,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2009/are_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
50643,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2009/are_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
50644,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2009/are_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
50645,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2010/are_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
50646,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2010/are_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
50647,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2010/are_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
50648,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2010/are_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
50649,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2010/are_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
50650,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2010/are_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
50651,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2010/are_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
50652,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2010/are_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
50653,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2011/are_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
50654,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2011/are_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
50655,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2011/are_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
50656,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2011/are_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
50657,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2011/are_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
50658,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2011/are_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
50659,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2011/are_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
50660,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2011/are_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
50661,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2012/are_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
50662,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2012/are_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
50663,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2012/are_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
50664,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2012/are_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
50665,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2012/are_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
50666,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2012/are_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
50667,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2012/are_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
50668,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2012/are_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
50669,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2013/are_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
50670,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2013/are_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
50671,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2013/are_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
50672,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2013/are_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
50673,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2013/are_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
50674,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2013/are_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
50675,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2013/are_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
50676,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2013/are_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
50677,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2014/are_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
50678,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2014/are_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
50679,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2014/are_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
50680,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2014/are_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
50681,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2014/are_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
50682,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2014/are_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
50683,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2014/are_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
50684,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2014/are_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
50685,784,"ARE","United Arab Emirates","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2015/are_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
50686,784,"ARE","United Arab Emirates","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2015/are_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
50687,784,"ARE","United Arab Emirates","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2015/are_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
50688,784,"ARE","United Arab Emirates","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2015/are_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
50689,784,"ARE","United Arab Emirates","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2015/are_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
50690,784,"ARE","United Arab Emirates","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2015/are_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
50691,784,"ARE","United Arab Emirates","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2015/are_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
50692,784,"ARE","United Arab Emirates","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Annual/2015/are_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
50693,788,"TUN","Tunisia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2000/tun_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
50694,788,"TUN","Tunisia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2000/tun_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
50695,788,"TUN","Tunisia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2000/tun_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
50696,788,"TUN","Tunisia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2000/tun_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
50697,788,"TUN","Tunisia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2000/tun_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
50698,788,"TUN","Tunisia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2000/tun_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
50699,788,"TUN","Tunisia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2000/tun_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
50700,788,"TUN","Tunisia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2000/tun_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
50701,788,"TUN","Tunisia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2001/tun_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
50702,788,"TUN","Tunisia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2001/tun_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
50703,788,"TUN","Tunisia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2001/tun_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
50704,788,"TUN","Tunisia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2001/tun_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
50705,788,"TUN","Tunisia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2001/tun_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
50706,788,"TUN","Tunisia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2001/tun_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
50707,788,"TUN","Tunisia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2001/tun_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
50708,788,"TUN","Tunisia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2001/tun_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
50709,788,"TUN","Tunisia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2002/tun_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
50710,788,"TUN","Tunisia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2002/tun_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
50711,788,"TUN","Tunisia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2002/tun_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
50712,788,"TUN","Tunisia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2002/tun_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
50713,788,"TUN","Tunisia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2002/tun_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
50714,788,"TUN","Tunisia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2002/tun_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
50715,788,"TUN","Tunisia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2002/tun_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
50716,788,"TUN","Tunisia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2002/tun_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
50717,788,"TUN","Tunisia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2003/tun_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
50718,788,"TUN","Tunisia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2003/tun_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
50719,788,"TUN","Tunisia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2003/tun_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
50720,788,"TUN","Tunisia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2003/tun_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
50721,788,"TUN","Tunisia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2003/tun_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
50722,788,"TUN","Tunisia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2003/tun_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
50723,788,"TUN","Tunisia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2003/tun_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
50724,788,"TUN","Tunisia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2003/tun_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
50725,788,"TUN","Tunisia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2004/tun_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
50726,788,"TUN","Tunisia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2004/tun_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
50727,788,"TUN","Tunisia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2004/tun_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
50728,788,"TUN","Tunisia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2004/tun_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
50729,788,"TUN","Tunisia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2004/tun_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
50730,788,"TUN","Tunisia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2004/tun_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
50731,788,"TUN","Tunisia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2004/tun_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
50732,788,"TUN","Tunisia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2004/tun_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
50733,788,"TUN","Tunisia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2005/tun_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
50734,788,"TUN","Tunisia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2005/tun_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
50735,788,"TUN","Tunisia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2005/tun_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
50736,788,"TUN","Tunisia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2005/tun_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
50737,788,"TUN","Tunisia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2005/tun_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
50738,788,"TUN","Tunisia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2005/tun_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
50739,788,"TUN","Tunisia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2005/tun_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
50740,788,"TUN","Tunisia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2005/tun_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
50741,788,"TUN","Tunisia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2006/tun_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
50742,788,"TUN","Tunisia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2006/tun_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
50743,788,"TUN","Tunisia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2006/tun_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
50744,788,"TUN","Tunisia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2006/tun_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
50745,788,"TUN","Tunisia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2006/tun_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
50746,788,"TUN","Tunisia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2006/tun_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
50747,788,"TUN","Tunisia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2006/tun_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
50748,788,"TUN","Tunisia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2006/tun_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
50749,788,"TUN","Tunisia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2007/tun_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
50750,788,"TUN","Tunisia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2007/tun_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
50751,788,"TUN","Tunisia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2007/tun_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
50752,788,"TUN","Tunisia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2007/tun_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
50753,788,"TUN","Tunisia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2007/tun_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
50754,788,"TUN","Tunisia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2007/tun_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
50755,788,"TUN","Tunisia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2007/tun_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
50756,788,"TUN","Tunisia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2007/tun_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
50757,788,"TUN","Tunisia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2008/tun_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
50758,788,"TUN","Tunisia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2008/tun_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
50759,788,"TUN","Tunisia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2008/tun_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
50760,788,"TUN","Tunisia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2008/tun_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
50761,788,"TUN","Tunisia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2008/tun_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
50762,788,"TUN","Tunisia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2008/tun_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
50763,788,"TUN","Tunisia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2008/tun_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
50764,788,"TUN","Tunisia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2008/tun_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
50765,788,"TUN","Tunisia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2009/tun_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
50766,788,"TUN","Tunisia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2009/tun_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
50767,788,"TUN","Tunisia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2009/tun_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
50768,788,"TUN","Tunisia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2009/tun_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
50769,788,"TUN","Tunisia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2009/tun_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
50770,788,"TUN","Tunisia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2009/tun_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
50771,788,"TUN","Tunisia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2009/tun_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
50772,788,"TUN","Tunisia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2009/tun_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
50773,788,"TUN","Tunisia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2010/tun_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
50774,788,"TUN","Tunisia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2010/tun_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
50775,788,"TUN","Tunisia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2010/tun_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
50776,788,"TUN","Tunisia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2010/tun_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
50777,788,"TUN","Tunisia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2010/tun_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
50778,788,"TUN","Tunisia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2010/tun_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
50779,788,"TUN","Tunisia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2010/tun_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
50780,788,"TUN","Tunisia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2010/tun_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
50781,788,"TUN","Tunisia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2011/tun_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
50782,788,"TUN","Tunisia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2011/tun_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
50783,788,"TUN","Tunisia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2011/tun_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
50784,788,"TUN","Tunisia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2011/tun_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
50785,788,"TUN","Tunisia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2011/tun_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
50786,788,"TUN","Tunisia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2011/tun_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
50787,788,"TUN","Tunisia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2011/tun_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
50788,788,"TUN","Tunisia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2011/tun_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
50789,788,"TUN","Tunisia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2012/tun_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
50790,788,"TUN","Tunisia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2012/tun_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
50791,788,"TUN","Tunisia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2012/tun_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
50792,788,"TUN","Tunisia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2012/tun_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
50793,788,"TUN","Tunisia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2012/tun_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
50794,788,"TUN","Tunisia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2012/tun_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
50795,788,"TUN","Tunisia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2012/tun_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
50796,788,"TUN","Tunisia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2012/tun_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
50797,788,"TUN","Tunisia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2013/tun_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
50798,788,"TUN","Tunisia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2013/tun_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
50799,788,"TUN","Tunisia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2013/tun_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
50800,788,"TUN","Tunisia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2013/tun_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
50801,788,"TUN","Tunisia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2013/tun_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
50802,788,"TUN","Tunisia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2013/tun_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
50803,788,"TUN","Tunisia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2013/tun_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
50804,788,"TUN","Tunisia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2013/tun_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
50805,788,"TUN","Tunisia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2014/tun_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
50806,788,"TUN","Tunisia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2014/tun_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
50807,788,"TUN","Tunisia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2014/tun_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
50808,788,"TUN","Tunisia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2014/tun_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
50809,788,"TUN","Tunisia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2014/tun_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
50810,788,"TUN","Tunisia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2014/tun_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
50811,788,"TUN","Tunisia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2014/tun_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
50812,788,"TUN","Tunisia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2014/tun_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
50813,788,"TUN","Tunisia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2015/tun_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
50814,788,"TUN","Tunisia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2015/tun_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
50815,788,"TUN","Tunisia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2015/tun_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
50816,788,"TUN","Tunisia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2015/tun_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
50817,788,"TUN","Tunisia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2015/tun_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
50818,788,"TUN","Tunisia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2015/tun_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
50819,788,"TUN","Tunisia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2015/tun_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
50820,788,"TUN","Tunisia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Annual/2015/tun_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
50821,792,"TUR","Turkey","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2000/tur_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
50822,792,"TUR","Turkey","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2000/tur_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
50823,792,"TUR","Turkey","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2000/tur_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
50824,792,"TUR","Turkey","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2000/tur_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
50825,792,"TUR","Turkey","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2000/tur_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
50826,792,"TUR","Turkey","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2000/tur_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
50827,792,"TUR","Turkey","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2000/tur_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
50828,792,"TUR","Turkey","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2000/tur_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
50829,792,"TUR","Turkey","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2001/tur_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
50830,792,"TUR","Turkey","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2001/tur_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
50831,792,"TUR","Turkey","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2001/tur_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
50832,792,"TUR","Turkey","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2001/tur_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
50833,792,"TUR","Turkey","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2001/tur_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
50834,792,"TUR","Turkey","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2001/tur_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
50835,792,"TUR","Turkey","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2001/tur_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
50836,792,"TUR","Turkey","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2001/tur_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
50837,792,"TUR","Turkey","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2002/tur_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
50838,792,"TUR","Turkey","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2002/tur_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
50839,792,"TUR","Turkey","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2002/tur_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
50840,792,"TUR","Turkey","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2002/tur_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
50841,792,"TUR","Turkey","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2002/tur_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
50842,792,"TUR","Turkey","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2002/tur_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
50843,792,"TUR","Turkey","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2002/tur_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
50844,792,"TUR","Turkey","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2002/tur_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
50845,792,"TUR","Turkey","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2003/tur_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
50846,792,"TUR","Turkey","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2003/tur_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
50847,792,"TUR","Turkey","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2003/tur_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
50848,792,"TUR","Turkey","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2003/tur_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
50849,792,"TUR","Turkey","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2003/tur_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
50850,792,"TUR","Turkey","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2003/tur_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
50851,792,"TUR","Turkey","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2003/tur_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
50852,792,"TUR","Turkey","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2003/tur_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
50853,792,"TUR","Turkey","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2004/tur_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
50854,792,"TUR","Turkey","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2004/tur_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
50855,792,"TUR","Turkey","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2004/tur_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
50856,792,"TUR","Turkey","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2004/tur_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
50857,792,"TUR","Turkey","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2004/tur_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
50858,792,"TUR","Turkey","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2004/tur_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
50859,792,"TUR","Turkey","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2004/tur_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
50860,792,"TUR","Turkey","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2004/tur_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
50861,792,"TUR","Turkey","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2005/tur_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
50862,792,"TUR","Turkey","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2005/tur_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
50863,792,"TUR","Turkey","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2005/tur_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
50864,792,"TUR","Turkey","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2005/tur_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
50865,792,"TUR","Turkey","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2005/tur_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
50866,792,"TUR","Turkey","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2005/tur_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
50867,792,"TUR","Turkey","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2005/tur_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
50868,792,"TUR","Turkey","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2005/tur_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
50869,792,"TUR","Turkey","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2006/tur_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
50870,792,"TUR","Turkey","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2006/tur_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
50871,792,"TUR","Turkey","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2006/tur_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
50872,792,"TUR","Turkey","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2006/tur_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
50873,792,"TUR","Turkey","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2006/tur_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
50874,792,"TUR","Turkey","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2006/tur_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
50875,792,"TUR","Turkey","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2006/tur_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
50876,792,"TUR","Turkey","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2006/tur_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
50877,792,"TUR","Turkey","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2007/tur_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
50878,792,"TUR","Turkey","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2007/tur_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
50879,792,"TUR","Turkey","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2007/tur_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
50880,792,"TUR","Turkey","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2007/tur_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
50881,792,"TUR","Turkey","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2007/tur_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
50882,792,"TUR","Turkey","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2007/tur_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
50883,792,"TUR","Turkey","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2007/tur_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
50884,792,"TUR","Turkey","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2007/tur_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
50885,792,"TUR","Turkey","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2008/tur_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
50886,792,"TUR","Turkey","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2008/tur_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
50887,792,"TUR","Turkey","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2008/tur_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
50888,792,"TUR","Turkey","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2008/tur_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
50889,792,"TUR","Turkey","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2008/tur_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
50890,792,"TUR","Turkey","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2008/tur_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
50891,792,"TUR","Turkey","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2008/tur_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
50892,792,"TUR","Turkey","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2008/tur_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
50893,792,"TUR","Turkey","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2009/tur_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
50894,792,"TUR","Turkey","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2009/tur_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
50895,792,"TUR","Turkey","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2009/tur_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
50896,792,"TUR","Turkey","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2009/tur_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
50897,792,"TUR","Turkey","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2009/tur_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
50898,792,"TUR","Turkey","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2009/tur_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
50899,792,"TUR","Turkey","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2009/tur_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
50900,792,"TUR","Turkey","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2009/tur_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
50901,792,"TUR","Turkey","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2010/tur_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
50902,792,"TUR","Turkey","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2010/tur_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
50903,792,"TUR","Turkey","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2010/tur_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
50904,792,"TUR","Turkey","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2010/tur_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
50905,792,"TUR","Turkey","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2010/tur_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
50906,792,"TUR","Turkey","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2010/tur_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
50907,792,"TUR","Turkey","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2010/tur_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
50908,792,"TUR","Turkey","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2010/tur_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
50909,792,"TUR","Turkey","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2011/tur_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
50910,792,"TUR","Turkey","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2011/tur_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
50911,792,"TUR","Turkey","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2011/tur_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
50912,792,"TUR","Turkey","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2011/tur_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
50913,792,"TUR","Turkey","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2011/tur_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
50914,792,"TUR","Turkey","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2011/tur_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
50915,792,"TUR","Turkey","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2011/tur_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
50916,792,"TUR","Turkey","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2011/tur_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
50917,792,"TUR","Turkey","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2012/tur_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
50918,792,"TUR","Turkey","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2012/tur_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
50919,792,"TUR","Turkey","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2012/tur_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
50920,792,"TUR","Turkey","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2012/tur_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
50921,792,"TUR","Turkey","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2012/tur_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
50922,792,"TUR","Turkey","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2012/tur_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
50923,792,"TUR","Turkey","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2012/tur_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
50924,792,"TUR","Turkey","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2012/tur_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
50925,792,"TUR","Turkey","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2013/tur_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
50926,792,"TUR","Turkey","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2013/tur_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
50927,792,"TUR","Turkey","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2013/tur_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
50928,792,"TUR","Turkey","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2013/tur_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
50929,792,"TUR","Turkey","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2013/tur_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
50930,792,"TUR","Turkey","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2013/tur_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
50931,792,"TUR","Turkey","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2013/tur_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
50932,792,"TUR","Turkey","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2013/tur_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
50933,792,"TUR","Turkey","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2014/tur_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
50934,792,"TUR","Turkey","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2014/tur_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
50935,792,"TUR","Turkey","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2014/tur_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
50936,792,"TUR","Turkey","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2014/tur_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
50937,792,"TUR","Turkey","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2014/tur_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
50938,792,"TUR","Turkey","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2014/tur_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
50939,792,"TUR","Turkey","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2014/tur_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
50940,792,"TUR","Turkey","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2014/tur_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
50941,792,"TUR","Turkey","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2015/tur_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
50942,792,"TUR","Turkey","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2015/tur_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
50943,792,"TUR","Turkey","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2015/tur_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
50944,792,"TUR","Turkey","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2015/tur_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
50945,792,"TUR","Turkey","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2015/tur_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
50946,792,"TUR","Turkey","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2015/tur_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
50947,792,"TUR","Turkey","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2015/tur_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
50948,792,"TUR","Turkey","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Annual/2015/tur_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
50949,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2000/tkm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
50950,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2000/tkm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
50951,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2000/tkm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
50952,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2000/tkm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
50953,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2000/tkm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
50954,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2000/tkm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
50955,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2000/tkm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
50956,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2000/tkm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
50957,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2001/tkm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
50958,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2001/tkm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
50959,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2001/tkm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
50960,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2001/tkm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
50961,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2001/tkm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
50962,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2001/tkm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
50963,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2001/tkm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
50964,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2001/tkm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
50965,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2002/tkm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
50966,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2002/tkm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
50967,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2002/tkm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
50968,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2002/tkm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
50969,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2002/tkm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
50970,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2002/tkm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
50971,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2002/tkm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
50972,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2002/tkm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
50973,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2003/tkm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
50974,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2003/tkm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
50975,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2003/tkm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
50976,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2003/tkm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
50977,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2003/tkm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
50978,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2003/tkm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
50979,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2003/tkm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
50980,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2003/tkm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
50981,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2004/tkm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
50982,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2004/tkm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
50983,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2004/tkm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
50984,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2004/tkm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
50985,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2004/tkm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
50986,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2004/tkm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
50987,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2004/tkm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
50988,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2004/tkm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
50989,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2005/tkm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
50990,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2005/tkm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
50991,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2005/tkm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
50992,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2005/tkm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
50993,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2005/tkm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
50994,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2005/tkm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
50995,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2005/tkm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
50996,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2005/tkm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
50997,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2006/tkm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
50998,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2006/tkm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
50999,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2006/tkm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
51000,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2006/tkm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
51001,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2006/tkm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
51002,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2006/tkm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
51003,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2006/tkm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
51004,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2006/tkm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
51005,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2007/tkm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
51006,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2007/tkm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
51007,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2007/tkm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
51008,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2007/tkm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
51009,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2007/tkm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
51010,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2007/tkm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
51011,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2007/tkm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
51012,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2007/tkm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
51013,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2008/tkm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
51014,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2008/tkm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
51015,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2008/tkm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
51016,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2008/tkm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
51017,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2008/tkm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
51018,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2008/tkm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
51019,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2008/tkm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
51020,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2008/tkm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
51021,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2009/tkm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
51022,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2009/tkm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
51023,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2009/tkm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
51024,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2009/tkm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
51025,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2009/tkm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
51026,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2009/tkm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
51027,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2009/tkm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
51028,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2009/tkm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
51029,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2010/tkm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
51030,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2010/tkm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
51031,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2010/tkm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
51032,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2010/tkm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
51033,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2010/tkm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
51034,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2010/tkm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
51035,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2010/tkm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
51036,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2010/tkm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
51037,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2011/tkm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
51038,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2011/tkm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
51039,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2011/tkm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
51040,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2011/tkm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
51041,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2011/tkm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
51042,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2011/tkm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
51043,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2011/tkm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
51044,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2011/tkm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
51045,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2012/tkm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
51046,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2012/tkm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
51047,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2012/tkm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
51048,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2012/tkm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
51049,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2012/tkm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
51050,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2012/tkm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
51051,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2012/tkm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
51052,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2012/tkm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
51053,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2013/tkm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
51054,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2013/tkm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
51055,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2013/tkm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
51056,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2013/tkm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
51057,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2013/tkm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
51058,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2013/tkm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
51059,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2013/tkm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
51060,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2013/tkm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
51061,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2014/tkm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
51062,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2014/tkm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
51063,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2014/tkm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
51064,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2014/tkm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
51065,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2014/tkm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
51066,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2014/tkm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
51067,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2014/tkm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
51068,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2014/tkm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
51069,795,"TKM","Turkmenistan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2015/tkm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
51070,795,"TKM","Turkmenistan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2015/tkm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
51071,795,"TKM","Turkmenistan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2015/tkm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
51072,795,"TKM","Turkmenistan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2015/tkm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
51073,795,"TKM","Turkmenistan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2015/tkm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
51074,795,"TKM","Turkmenistan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2015/tkm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
51075,795,"TKM","Turkmenistan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2015/tkm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
51076,795,"TKM","Turkmenistan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Annual/2015/tkm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
51077,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2000/tca_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
51078,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2000/tca_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
51079,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2000/tca_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
51080,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2000/tca_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
51081,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2000/tca_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
51082,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2000/tca_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
51083,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2000/tca_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
51084,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2000/tca_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
51085,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2001/tca_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
51086,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2001/tca_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
51087,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2001/tca_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
51088,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2001/tca_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
51089,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2001/tca_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
51090,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2001/tca_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
51091,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2001/tca_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
51092,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2001/tca_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
51093,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2002/tca_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
51094,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2002/tca_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
51095,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2002/tca_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
51096,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2002/tca_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
51097,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2002/tca_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
51098,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2002/tca_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
51099,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2002/tca_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
51100,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2002/tca_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
51101,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2003/tca_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
51102,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2003/tca_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
51103,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2003/tca_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
51104,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2003/tca_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
51105,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2003/tca_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
51106,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2003/tca_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
51107,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2003/tca_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
51108,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2003/tca_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
51109,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2004/tca_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
51110,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2004/tca_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
51111,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2004/tca_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
51112,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2004/tca_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
51113,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2004/tca_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
51114,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2004/tca_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
51115,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2004/tca_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
51116,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2004/tca_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
51117,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2005/tca_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
51118,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2005/tca_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
51119,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2005/tca_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
51120,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2005/tca_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
51121,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2005/tca_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
51122,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2005/tca_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
51123,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2005/tca_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
51124,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2005/tca_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
51125,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2006/tca_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
51126,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2006/tca_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
51127,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2006/tca_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
51128,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2006/tca_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
51129,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2006/tca_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
51130,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2006/tca_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
51131,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2006/tca_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
51132,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2006/tca_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
51133,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2007/tca_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
51134,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2007/tca_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
51135,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2007/tca_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
51136,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2007/tca_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
51137,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2007/tca_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
51138,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2007/tca_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
51139,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2007/tca_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
51140,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2007/tca_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
51141,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2008/tca_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
51142,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2008/tca_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
51143,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2008/tca_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
51144,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2008/tca_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
51145,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2008/tca_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
51146,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2008/tca_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
51147,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2008/tca_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
51148,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2008/tca_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
51149,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2009/tca_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
51150,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2009/tca_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
51151,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2009/tca_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
51152,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2009/tca_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
51153,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2009/tca_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
51154,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2009/tca_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
51155,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2009/tca_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
51156,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2009/tca_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
51157,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2010/tca_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
51158,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2010/tca_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
51159,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2010/tca_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
51160,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2010/tca_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
51161,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2010/tca_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
51162,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2010/tca_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
51163,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2010/tca_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
51164,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2010/tca_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
51165,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2011/tca_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
51166,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2011/tca_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
51167,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2011/tca_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
51168,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2011/tca_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
51169,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2011/tca_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
51170,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2011/tca_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
51171,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2011/tca_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
51172,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2011/tca_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
51173,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2012/tca_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
51174,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2012/tca_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
51175,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2012/tca_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
51176,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2012/tca_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
51177,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2012/tca_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
51178,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2012/tca_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
51179,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2012/tca_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
51180,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2012/tca_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
51181,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2013/tca_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
51182,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2013/tca_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
51183,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2013/tca_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
51184,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2013/tca_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
51185,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2013/tca_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
51186,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2013/tca_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
51187,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2013/tca_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
51188,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2013/tca_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
51189,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2014/tca_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
51190,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2014/tca_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
51191,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2014/tca_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
51192,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2014/tca_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
51193,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2014/tca_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
51194,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2014/tca_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
51195,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2014/tca_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
51196,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2014/tca_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
51197,796,"TCA","Turks and Caicos Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2015/tca_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
51198,796,"TCA","Turks and Caicos Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2015/tca_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
51199,796,"TCA","Turks and Caicos Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2015/tca_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
51200,796,"TCA","Turks and Caicos Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2015/tca_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
51201,796,"TCA","Turks and Caicos Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2015/tca_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
51202,796,"TCA","Turks and Caicos Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2015/tca_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
51203,796,"TCA","Turks and Caicos Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2015/tca_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
51204,796,"TCA","Turks and Caicos Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Annual/2015/tca_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
51205,798,"TUV","Tuvalu","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2000/tuv_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
51206,798,"TUV","Tuvalu","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2000/tuv_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
51207,798,"TUV","Tuvalu","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2000/tuv_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
51208,798,"TUV","Tuvalu","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2000/tuv_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
51209,798,"TUV","Tuvalu","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2000/tuv_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
51210,798,"TUV","Tuvalu","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2000/tuv_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
51211,798,"TUV","Tuvalu","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2000/tuv_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
51212,798,"TUV","Tuvalu","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2000/tuv_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
51213,798,"TUV","Tuvalu","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2001/tuv_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
51214,798,"TUV","Tuvalu","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2001/tuv_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
51215,798,"TUV","Tuvalu","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2001/tuv_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
51216,798,"TUV","Tuvalu","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2001/tuv_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
51217,798,"TUV","Tuvalu","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2001/tuv_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
51218,798,"TUV","Tuvalu","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2001/tuv_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
51219,798,"TUV","Tuvalu","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2001/tuv_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
51220,798,"TUV","Tuvalu","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2001/tuv_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
51221,798,"TUV","Tuvalu","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2002/tuv_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
51222,798,"TUV","Tuvalu","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2002/tuv_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
51223,798,"TUV","Tuvalu","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2002/tuv_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
51224,798,"TUV","Tuvalu","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2002/tuv_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
51225,798,"TUV","Tuvalu","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2002/tuv_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
51226,798,"TUV","Tuvalu","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2002/tuv_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
51227,798,"TUV","Tuvalu","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2002/tuv_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
51228,798,"TUV","Tuvalu","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2002/tuv_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
51229,798,"TUV","Tuvalu","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2003/tuv_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
51230,798,"TUV","Tuvalu","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2003/tuv_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
51231,798,"TUV","Tuvalu","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2003/tuv_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
51232,798,"TUV","Tuvalu","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2003/tuv_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
51233,798,"TUV","Tuvalu","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2003/tuv_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
51234,798,"TUV","Tuvalu","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2003/tuv_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
51235,798,"TUV","Tuvalu","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2003/tuv_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
51236,798,"TUV","Tuvalu","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2003/tuv_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
51237,798,"TUV","Tuvalu","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2004/tuv_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
51238,798,"TUV","Tuvalu","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2004/tuv_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
51239,798,"TUV","Tuvalu","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2004/tuv_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
51240,798,"TUV","Tuvalu","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2004/tuv_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
51241,798,"TUV","Tuvalu","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2004/tuv_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
51242,798,"TUV","Tuvalu","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2004/tuv_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
51243,798,"TUV","Tuvalu","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2004/tuv_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
51244,798,"TUV","Tuvalu","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2004/tuv_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
51245,798,"TUV","Tuvalu","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2005/tuv_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
51246,798,"TUV","Tuvalu","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2005/tuv_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
51247,798,"TUV","Tuvalu","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2005/tuv_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
51248,798,"TUV","Tuvalu","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2005/tuv_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
51249,798,"TUV","Tuvalu","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2005/tuv_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
51250,798,"TUV","Tuvalu","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2005/tuv_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
51251,798,"TUV","Tuvalu","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2005/tuv_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
51252,798,"TUV","Tuvalu","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2005/tuv_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
51253,798,"TUV","Tuvalu","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2006/tuv_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
51254,798,"TUV","Tuvalu","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2006/tuv_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
51255,798,"TUV","Tuvalu","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2006/tuv_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
51256,798,"TUV","Tuvalu","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2006/tuv_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
51257,798,"TUV","Tuvalu","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2006/tuv_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
51258,798,"TUV","Tuvalu","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2006/tuv_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
51259,798,"TUV","Tuvalu","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2006/tuv_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
51260,798,"TUV","Tuvalu","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2006/tuv_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
51261,798,"TUV","Tuvalu","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2007/tuv_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
51262,798,"TUV","Tuvalu","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2007/tuv_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
51263,798,"TUV","Tuvalu","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2007/tuv_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
51264,798,"TUV","Tuvalu","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2007/tuv_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
51265,798,"TUV","Tuvalu","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2007/tuv_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
51266,798,"TUV","Tuvalu","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2007/tuv_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
51267,798,"TUV","Tuvalu","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2007/tuv_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
51268,798,"TUV","Tuvalu","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2007/tuv_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
51269,798,"TUV","Tuvalu","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2008/tuv_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
51270,798,"TUV","Tuvalu","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2008/tuv_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
51271,798,"TUV","Tuvalu","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2008/tuv_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
51272,798,"TUV","Tuvalu","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2008/tuv_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
51273,798,"TUV","Tuvalu","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2008/tuv_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
51274,798,"TUV","Tuvalu","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2008/tuv_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
51275,798,"TUV","Tuvalu","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2008/tuv_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
51276,798,"TUV","Tuvalu","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2008/tuv_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
51277,798,"TUV","Tuvalu","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2009/tuv_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
51278,798,"TUV","Tuvalu","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2009/tuv_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
51279,798,"TUV","Tuvalu","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2009/tuv_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
51280,798,"TUV","Tuvalu","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2009/tuv_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
51281,798,"TUV","Tuvalu","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2009/tuv_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
51282,798,"TUV","Tuvalu","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2009/tuv_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
51283,798,"TUV","Tuvalu","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2009/tuv_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
51284,798,"TUV","Tuvalu","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2009/tuv_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
51285,798,"TUV","Tuvalu","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2010/tuv_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
51286,798,"TUV","Tuvalu","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2010/tuv_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
51287,798,"TUV","Tuvalu","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2010/tuv_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
51288,798,"TUV","Tuvalu","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2010/tuv_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
51289,798,"TUV","Tuvalu","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2010/tuv_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
51290,798,"TUV","Tuvalu","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2010/tuv_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
51291,798,"TUV","Tuvalu","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2010/tuv_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
51292,798,"TUV","Tuvalu","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2010/tuv_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
51293,798,"TUV","Tuvalu","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2011/tuv_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
51294,798,"TUV","Tuvalu","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2011/tuv_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
51295,798,"TUV","Tuvalu","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2011/tuv_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
51296,798,"TUV","Tuvalu","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2011/tuv_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
51297,798,"TUV","Tuvalu","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2011/tuv_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
51298,798,"TUV","Tuvalu","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2011/tuv_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
51299,798,"TUV","Tuvalu","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2011/tuv_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
51300,798,"TUV","Tuvalu","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2011/tuv_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
51301,798,"TUV","Tuvalu","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2012/tuv_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
51302,798,"TUV","Tuvalu","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2012/tuv_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
51303,798,"TUV","Tuvalu","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2012/tuv_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
51304,798,"TUV","Tuvalu","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2012/tuv_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
51305,798,"TUV","Tuvalu","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2012/tuv_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
51306,798,"TUV","Tuvalu","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2012/tuv_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
51307,798,"TUV","Tuvalu","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2012/tuv_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
51308,798,"TUV","Tuvalu","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2012/tuv_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
51309,798,"TUV","Tuvalu","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2013/tuv_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
51310,798,"TUV","Tuvalu","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2013/tuv_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
51311,798,"TUV","Tuvalu","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2013/tuv_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
51312,798,"TUV","Tuvalu","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2013/tuv_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
51313,798,"TUV","Tuvalu","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2013/tuv_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
51314,798,"TUV","Tuvalu","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2013/tuv_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
51315,798,"TUV","Tuvalu","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2013/tuv_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
51316,798,"TUV","Tuvalu","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2013/tuv_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
51317,798,"TUV","Tuvalu","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2014/tuv_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
51318,798,"TUV","Tuvalu","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2014/tuv_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
51319,798,"TUV","Tuvalu","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2014/tuv_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
51320,798,"TUV","Tuvalu","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2014/tuv_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
51321,798,"TUV","Tuvalu","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2014/tuv_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
51322,798,"TUV","Tuvalu","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2014/tuv_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
51323,798,"TUV","Tuvalu","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2014/tuv_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
51324,798,"TUV","Tuvalu","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2014/tuv_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
51325,798,"TUV","Tuvalu","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2015/tuv_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
51326,798,"TUV","Tuvalu","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2015/tuv_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
51327,798,"TUV","Tuvalu","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2015/tuv_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
51328,798,"TUV","Tuvalu","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2015/tuv_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
51329,798,"TUV","Tuvalu","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2015/tuv_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
51330,798,"TUV","Tuvalu","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2015/tuv_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
51331,798,"TUV","Tuvalu","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2015/tuv_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
51332,798,"TUV","Tuvalu","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Annual/2015/tuv_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
51333,800,"UGA","Uganda","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2000/uga_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
51334,800,"UGA","Uganda","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2000/uga_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
51335,800,"UGA","Uganda","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2000/uga_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
51336,800,"UGA","Uganda","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2000/uga_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
51337,800,"UGA","Uganda","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2000/uga_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
51338,800,"UGA","Uganda","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2000/uga_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
51339,800,"UGA","Uganda","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2000/uga_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
51340,800,"UGA","Uganda","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2000/uga_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
51341,800,"UGA","Uganda","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2001/uga_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
51342,800,"UGA","Uganda","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2001/uga_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
51343,800,"UGA","Uganda","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2001/uga_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
51344,800,"UGA","Uganda","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2001/uga_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
51345,800,"UGA","Uganda","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2001/uga_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
51346,800,"UGA","Uganda","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2001/uga_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
51347,800,"UGA","Uganda","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2001/uga_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
51348,800,"UGA","Uganda","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2001/uga_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
51349,800,"UGA","Uganda","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2002/uga_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
51350,800,"UGA","Uganda","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2002/uga_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
51351,800,"UGA","Uganda","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2002/uga_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
51352,800,"UGA","Uganda","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2002/uga_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
51353,800,"UGA","Uganda","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2002/uga_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
51354,800,"UGA","Uganda","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2002/uga_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
51355,800,"UGA","Uganda","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2002/uga_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
51356,800,"UGA","Uganda","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2002/uga_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
51357,800,"UGA","Uganda","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2003/uga_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
51358,800,"UGA","Uganda","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2003/uga_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
51359,800,"UGA","Uganda","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2003/uga_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
51360,800,"UGA","Uganda","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2003/uga_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
51361,800,"UGA","Uganda","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2003/uga_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
51362,800,"UGA","Uganda","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2003/uga_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
51363,800,"UGA","Uganda","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2003/uga_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
51364,800,"UGA","Uganda","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2003/uga_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
51365,800,"UGA","Uganda","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2004/uga_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
51366,800,"UGA","Uganda","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2004/uga_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
51367,800,"UGA","Uganda","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2004/uga_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
51368,800,"UGA","Uganda","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2004/uga_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
51369,800,"UGA","Uganda","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2004/uga_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
51370,800,"UGA","Uganda","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2004/uga_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
51371,800,"UGA","Uganda","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2004/uga_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
51372,800,"UGA","Uganda","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2004/uga_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
51373,800,"UGA","Uganda","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2005/uga_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
51374,800,"UGA","Uganda","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2005/uga_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
51375,800,"UGA","Uganda","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2005/uga_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
51376,800,"UGA","Uganda","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2005/uga_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
51377,800,"UGA","Uganda","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2005/uga_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
51378,800,"UGA","Uganda","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2005/uga_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
51379,800,"UGA","Uganda","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2005/uga_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
51380,800,"UGA","Uganda","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2005/uga_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
51381,800,"UGA","Uganda","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2006/uga_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
51382,800,"UGA","Uganda","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2006/uga_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
51383,800,"UGA","Uganda","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2006/uga_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
51384,800,"UGA","Uganda","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2006/uga_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
51385,800,"UGA","Uganda","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2006/uga_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
51386,800,"UGA","Uganda","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2006/uga_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
51387,800,"UGA","Uganda","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2006/uga_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
51388,800,"UGA","Uganda","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2006/uga_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
51389,800,"UGA","Uganda","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2007/uga_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
51390,800,"UGA","Uganda","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2007/uga_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
51391,800,"UGA","Uganda","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2007/uga_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
51392,800,"UGA","Uganda","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2007/uga_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
51393,800,"UGA","Uganda","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2007/uga_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
51394,800,"UGA","Uganda","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2007/uga_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
51395,800,"UGA","Uganda","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2007/uga_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
51396,800,"UGA","Uganda","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2007/uga_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
51397,800,"UGA","Uganda","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2008/uga_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
51398,800,"UGA","Uganda","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2008/uga_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
51399,800,"UGA","Uganda","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2008/uga_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
51400,800,"UGA","Uganda","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2008/uga_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
51401,800,"UGA","Uganda","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2008/uga_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
51402,800,"UGA","Uganda","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2008/uga_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
51403,800,"UGA","Uganda","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2008/uga_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
51404,800,"UGA","Uganda","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2008/uga_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
51405,800,"UGA","Uganda","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2009/uga_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
51406,800,"UGA","Uganda","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2009/uga_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
51407,800,"UGA","Uganda","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2009/uga_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
51408,800,"UGA","Uganda","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2009/uga_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
51409,800,"UGA","Uganda","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2009/uga_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
51410,800,"UGA","Uganda","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2009/uga_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
51411,800,"UGA","Uganda","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2009/uga_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
51412,800,"UGA","Uganda","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2009/uga_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
51413,800,"UGA","Uganda","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2010/uga_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
51414,800,"UGA","Uganda","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2010/uga_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
51415,800,"UGA","Uganda","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2010/uga_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
51416,800,"UGA","Uganda","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2010/uga_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
51417,800,"UGA","Uganda","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2010/uga_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
51418,800,"UGA","Uganda","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2010/uga_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
51419,800,"UGA","Uganda","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2010/uga_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
51420,800,"UGA","Uganda","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2010/uga_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
51421,800,"UGA","Uganda","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2011/uga_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
51422,800,"UGA","Uganda","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2011/uga_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
51423,800,"UGA","Uganda","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2011/uga_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
51424,800,"UGA","Uganda","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2011/uga_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
51425,800,"UGA","Uganda","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2011/uga_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
51426,800,"UGA","Uganda","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2011/uga_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
51427,800,"UGA","Uganda","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2011/uga_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
51428,800,"UGA","Uganda","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2011/uga_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
51429,800,"UGA","Uganda","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2012/uga_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
51430,800,"UGA","Uganda","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2012/uga_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
51431,800,"UGA","Uganda","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2012/uga_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
51432,800,"UGA","Uganda","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2012/uga_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
51433,800,"UGA","Uganda","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2012/uga_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
51434,800,"UGA","Uganda","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2012/uga_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
51435,800,"UGA","Uganda","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2012/uga_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
51436,800,"UGA","Uganda","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2012/uga_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
51437,800,"UGA","Uganda","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2013/uga_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
51438,800,"UGA","Uganda","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2013/uga_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
51439,800,"UGA","Uganda","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2013/uga_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
51440,800,"UGA","Uganda","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2013/uga_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
51441,800,"UGA","Uganda","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2013/uga_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
51442,800,"UGA","Uganda","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2013/uga_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
51443,800,"UGA","Uganda","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2013/uga_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
51444,800,"UGA","Uganda","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2013/uga_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
51445,800,"UGA","Uganda","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2014/uga_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
51446,800,"UGA","Uganda","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2014/uga_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
51447,800,"UGA","Uganda","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2014/uga_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
51448,800,"UGA","Uganda","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2014/uga_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
51449,800,"UGA","Uganda","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2014/uga_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
51450,800,"UGA","Uganda","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2014/uga_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
51451,800,"UGA","Uganda","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2014/uga_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
51452,800,"UGA","Uganda","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2014/uga_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
51453,800,"UGA","Uganda","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2015/uga_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
51454,800,"UGA","Uganda","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2015/uga_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
51455,800,"UGA","Uganda","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2015/uga_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
51456,800,"UGA","Uganda","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2015/uga_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
51457,800,"UGA","Uganda","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2015/uga_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
51458,800,"UGA","Uganda","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2015/uga_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
51459,800,"UGA","Uganda","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2015/uga_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
51460,800,"UGA","Uganda","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Annual/2015/uga_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
51461,804,"UKR","Ukraine","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2000/ukr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
51462,804,"UKR","Ukraine","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2000/ukr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
51463,804,"UKR","Ukraine","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2000/ukr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
51464,804,"UKR","Ukraine","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2000/ukr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
51465,804,"UKR","Ukraine","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2000/ukr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
51466,804,"UKR","Ukraine","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2000/ukr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
51467,804,"UKR","Ukraine","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2000/ukr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
51468,804,"UKR","Ukraine","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2000/ukr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
51469,804,"UKR","Ukraine","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2001/ukr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
51470,804,"UKR","Ukraine","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2001/ukr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
51471,804,"UKR","Ukraine","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2001/ukr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
51472,804,"UKR","Ukraine","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2001/ukr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
51473,804,"UKR","Ukraine","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2001/ukr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
51474,804,"UKR","Ukraine","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2001/ukr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
51475,804,"UKR","Ukraine","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2001/ukr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
51476,804,"UKR","Ukraine","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2001/ukr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
51477,804,"UKR","Ukraine","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2002/ukr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
51478,804,"UKR","Ukraine","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2002/ukr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
51479,804,"UKR","Ukraine","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2002/ukr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
51480,804,"UKR","Ukraine","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2002/ukr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
51481,804,"UKR","Ukraine","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2002/ukr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
51482,804,"UKR","Ukraine","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2002/ukr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
51483,804,"UKR","Ukraine","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2002/ukr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
51484,804,"UKR","Ukraine","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2002/ukr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
51485,804,"UKR","Ukraine","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2003/ukr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
51486,804,"UKR","Ukraine","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2003/ukr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
51487,804,"UKR","Ukraine","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2003/ukr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
51488,804,"UKR","Ukraine","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2003/ukr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
51489,804,"UKR","Ukraine","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2003/ukr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
51490,804,"UKR","Ukraine","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2003/ukr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
51491,804,"UKR","Ukraine","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2003/ukr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
51492,804,"UKR","Ukraine","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2003/ukr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
51493,804,"UKR","Ukraine","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2004/ukr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
51494,804,"UKR","Ukraine","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2004/ukr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
51495,804,"UKR","Ukraine","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2004/ukr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
51496,804,"UKR","Ukraine","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2004/ukr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
51497,804,"UKR","Ukraine","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2004/ukr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
51498,804,"UKR","Ukraine","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2004/ukr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
51499,804,"UKR","Ukraine","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2004/ukr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
51500,804,"UKR","Ukraine","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2004/ukr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
51501,804,"UKR","Ukraine","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2005/ukr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
51502,804,"UKR","Ukraine","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2005/ukr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
51503,804,"UKR","Ukraine","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2005/ukr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
51504,804,"UKR","Ukraine","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2005/ukr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
51505,804,"UKR","Ukraine","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2005/ukr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
51506,804,"UKR","Ukraine","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2005/ukr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
51507,804,"UKR","Ukraine","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2005/ukr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
51508,804,"UKR","Ukraine","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2005/ukr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
51509,804,"UKR","Ukraine","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2006/ukr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
51510,804,"UKR","Ukraine","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2006/ukr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
51511,804,"UKR","Ukraine","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2006/ukr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
51512,804,"UKR","Ukraine","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2006/ukr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
51513,804,"UKR","Ukraine","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2006/ukr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
51514,804,"UKR","Ukraine","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2006/ukr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
51515,804,"UKR","Ukraine","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2006/ukr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
51516,804,"UKR","Ukraine","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2006/ukr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
51517,804,"UKR","Ukraine","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2007/ukr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
51518,804,"UKR","Ukraine","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2007/ukr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
51519,804,"UKR","Ukraine","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2007/ukr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
51520,804,"UKR","Ukraine","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2007/ukr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
51521,804,"UKR","Ukraine","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2007/ukr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
51522,804,"UKR","Ukraine","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2007/ukr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
51523,804,"UKR","Ukraine","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2007/ukr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
51524,804,"UKR","Ukraine","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2007/ukr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
51525,804,"UKR","Ukraine","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2008/ukr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
51526,804,"UKR","Ukraine","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2008/ukr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
51527,804,"UKR","Ukraine","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2008/ukr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
51528,804,"UKR","Ukraine","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2008/ukr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
51529,804,"UKR","Ukraine","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2008/ukr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
51530,804,"UKR","Ukraine","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2008/ukr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
51531,804,"UKR","Ukraine","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2008/ukr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
51532,804,"UKR","Ukraine","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2008/ukr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
51533,804,"UKR","Ukraine","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2009/ukr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
51534,804,"UKR","Ukraine","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2009/ukr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
51535,804,"UKR","Ukraine","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2009/ukr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
51536,804,"UKR","Ukraine","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2009/ukr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
51537,804,"UKR","Ukraine","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2009/ukr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
51538,804,"UKR","Ukraine","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2009/ukr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
51539,804,"UKR","Ukraine","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2009/ukr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
51540,804,"UKR","Ukraine","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2009/ukr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
51541,804,"UKR","Ukraine","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2010/ukr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
51542,804,"UKR","Ukraine","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2010/ukr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
51543,804,"UKR","Ukraine","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2010/ukr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
51544,804,"UKR","Ukraine","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2010/ukr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
51545,804,"UKR","Ukraine","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2010/ukr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
51546,804,"UKR","Ukraine","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2010/ukr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
51547,804,"UKR","Ukraine","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2010/ukr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
51548,804,"UKR","Ukraine","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2010/ukr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
51549,804,"UKR","Ukraine","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2011/ukr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
51550,804,"UKR","Ukraine","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2011/ukr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
51551,804,"UKR","Ukraine","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2011/ukr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
51552,804,"UKR","Ukraine","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2011/ukr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
51553,804,"UKR","Ukraine","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2011/ukr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
51554,804,"UKR","Ukraine","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2011/ukr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
51555,804,"UKR","Ukraine","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2011/ukr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
51556,804,"UKR","Ukraine","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2011/ukr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
51557,804,"UKR","Ukraine","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2012/ukr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
51558,804,"UKR","Ukraine","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2012/ukr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
51559,804,"UKR","Ukraine","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2012/ukr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
51560,804,"UKR","Ukraine","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2012/ukr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
51561,804,"UKR","Ukraine","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2012/ukr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
51562,804,"UKR","Ukraine","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2012/ukr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
51563,804,"UKR","Ukraine","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2012/ukr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
51564,804,"UKR","Ukraine","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2012/ukr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
51565,804,"UKR","Ukraine","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2013/ukr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
51566,804,"UKR","Ukraine","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2013/ukr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
51567,804,"UKR","Ukraine","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2013/ukr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
51568,804,"UKR","Ukraine","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2013/ukr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
51569,804,"UKR","Ukraine","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2013/ukr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
51570,804,"UKR","Ukraine","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2013/ukr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
51571,804,"UKR","Ukraine","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2013/ukr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
51572,804,"UKR","Ukraine","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2013/ukr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
51573,804,"UKR","Ukraine","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2014/ukr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
51574,804,"UKR","Ukraine","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2014/ukr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
51575,804,"UKR","Ukraine","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2014/ukr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
51576,804,"UKR","Ukraine","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2014/ukr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
51577,804,"UKR","Ukraine","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2014/ukr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
51578,804,"UKR","Ukraine","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2014/ukr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
51579,804,"UKR","Ukraine","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2014/ukr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
51580,804,"UKR","Ukraine","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2014/ukr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
51581,804,"UKR","Ukraine","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2015/ukr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
51582,804,"UKR","Ukraine","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2015/ukr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
51583,804,"UKR","Ukraine","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2015/ukr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
51584,804,"UKR","Ukraine","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2015/ukr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
51585,804,"UKR","Ukraine","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2015/ukr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
51586,804,"UKR","Ukraine","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2015/ukr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
51587,804,"UKR","Ukraine","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2015/ukr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
51588,804,"UKR","Ukraine","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Annual/2015/ukr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
51589,807,"MKD","Macedonia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2000/mkd_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
51590,807,"MKD","Macedonia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2000/mkd_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
51591,807,"MKD","Macedonia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2000/mkd_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
51592,807,"MKD","Macedonia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2000/mkd_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
51593,807,"MKD","Macedonia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2000/mkd_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
51594,807,"MKD","Macedonia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2000/mkd_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
51595,807,"MKD","Macedonia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2000/mkd_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
51596,807,"MKD","Macedonia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2000/mkd_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
51597,807,"MKD","Macedonia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2001/mkd_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
51598,807,"MKD","Macedonia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2001/mkd_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
51599,807,"MKD","Macedonia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2001/mkd_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
51600,807,"MKD","Macedonia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2001/mkd_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
51601,807,"MKD","Macedonia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2001/mkd_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
51602,807,"MKD","Macedonia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2001/mkd_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
51603,807,"MKD","Macedonia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2001/mkd_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
51604,807,"MKD","Macedonia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2001/mkd_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
51605,807,"MKD","Macedonia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2002/mkd_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
51606,807,"MKD","Macedonia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2002/mkd_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
51607,807,"MKD","Macedonia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2002/mkd_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
51608,807,"MKD","Macedonia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2002/mkd_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
51609,807,"MKD","Macedonia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2002/mkd_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
51610,807,"MKD","Macedonia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2002/mkd_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
51611,807,"MKD","Macedonia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2002/mkd_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
51612,807,"MKD","Macedonia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2002/mkd_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
51613,807,"MKD","Macedonia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2003/mkd_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
51614,807,"MKD","Macedonia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2003/mkd_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
51615,807,"MKD","Macedonia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2003/mkd_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
51616,807,"MKD","Macedonia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2003/mkd_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
51617,807,"MKD","Macedonia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2003/mkd_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
51618,807,"MKD","Macedonia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2003/mkd_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
51619,807,"MKD","Macedonia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2003/mkd_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
51620,807,"MKD","Macedonia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2003/mkd_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
51621,807,"MKD","Macedonia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2004/mkd_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
51622,807,"MKD","Macedonia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2004/mkd_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
51623,807,"MKD","Macedonia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2004/mkd_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
51624,807,"MKD","Macedonia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2004/mkd_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
51625,807,"MKD","Macedonia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2004/mkd_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
51626,807,"MKD","Macedonia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2004/mkd_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
51627,807,"MKD","Macedonia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2004/mkd_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
51628,807,"MKD","Macedonia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2004/mkd_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
51629,807,"MKD","Macedonia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2005/mkd_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
51630,807,"MKD","Macedonia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2005/mkd_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
51631,807,"MKD","Macedonia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2005/mkd_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
51632,807,"MKD","Macedonia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2005/mkd_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
51633,807,"MKD","Macedonia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2005/mkd_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
51634,807,"MKD","Macedonia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2005/mkd_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
51635,807,"MKD","Macedonia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2005/mkd_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
51636,807,"MKD","Macedonia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2005/mkd_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
51637,807,"MKD","Macedonia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2006/mkd_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
51638,807,"MKD","Macedonia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2006/mkd_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
51639,807,"MKD","Macedonia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2006/mkd_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
51640,807,"MKD","Macedonia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2006/mkd_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
51641,807,"MKD","Macedonia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2006/mkd_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
51642,807,"MKD","Macedonia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2006/mkd_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
51643,807,"MKD","Macedonia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2006/mkd_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
51644,807,"MKD","Macedonia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2006/mkd_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
51645,807,"MKD","Macedonia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2007/mkd_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
51646,807,"MKD","Macedonia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2007/mkd_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
51647,807,"MKD","Macedonia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2007/mkd_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
51648,807,"MKD","Macedonia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2007/mkd_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
51649,807,"MKD","Macedonia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2007/mkd_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
51650,807,"MKD","Macedonia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2007/mkd_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
51651,807,"MKD","Macedonia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2007/mkd_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
51652,807,"MKD","Macedonia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2007/mkd_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
51653,807,"MKD","Macedonia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2008/mkd_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
51654,807,"MKD","Macedonia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2008/mkd_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
51655,807,"MKD","Macedonia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2008/mkd_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
51656,807,"MKD","Macedonia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2008/mkd_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
51657,807,"MKD","Macedonia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2008/mkd_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
51658,807,"MKD","Macedonia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2008/mkd_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
51659,807,"MKD","Macedonia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2008/mkd_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
51660,807,"MKD","Macedonia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2008/mkd_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
51661,807,"MKD","Macedonia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2009/mkd_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
51662,807,"MKD","Macedonia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2009/mkd_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
51663,807,"MKD","Macedonia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2009/mkd_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
51664,807,"MKD","Macedonia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2009/mkd_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
51665,807,"MKD","Macedonia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2009/mkd_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
51666,807,"MKD","Macedonia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2009/mkd_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
51667,807,"MKD","Macedonia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2009/mkd_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
51668,807,"MKD","Macedonia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2009/mkd_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
51669,807,"MKD","Macedonia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2010/mkd_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
51670,807,"MKD","Macedonia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2010/mkd_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
51671,807,"MKD","Macedonia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2010/mkd_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
51672,807,"MKD","Macedonia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2010/mkd_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
51673,807,"MKD","Macedonia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2010/mkd_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
51674,807,"MKD","Macedonia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2010/mkd_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
51675,807,"MKD","Macedonia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2010/mkd_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
51676,807,"MKD","Macedonia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2010/mkd_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
51677,807,"MKD","Macedonia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2011/mkd_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
51678,807,"MKD","Macedonia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2011/mkd_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
51679,807,"MKD","Macedonia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2011/mkd_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
51680,807,"MKD","Macedonia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2011/mkd_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
51681,807,"MKD","Macedonia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2011/mkd_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
51682,807,"MKD","Macedonia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2011/mkd_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
51683,807,"MKD","Macedonia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2011/mkd_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
51684,807,"MKD","Macedonia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2011/mkd_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
51685,807,"MKD","Macedonia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2012/mkd_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
51686,807,"MKD","Macedonia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2012/mkd_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
51687,807,"MKD","Macedonia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2012/mkd_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
51688,807,"MKD","Macedonia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2012/mkd_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
51689,807,"MKD","Macedonia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2012/mkd_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
51690,807,"MKD","Macedonia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2012/mkd_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
51691,807,"MKD","Macedonia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2012/mkd_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
51692,807,"MKD","Macedonia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2012/mkd_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
51693,807,"MKD","Macedonia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2013/mkd_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
51694,807,"MKD","Macedonia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2013/mkd_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
51695,807,"MKD","Macedonia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2013/mkd_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
51696,807,"MKD","Macedonia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2013/mkd_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
51697,807,"MKD","Macedonia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2013/mkd_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
51698,807,"MKD","Macedonia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2013/mkd_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
51699,807,"MKD","Macedonia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2013/mkd_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
51700,807,"MKD","Macedonia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2013/mkd_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
51701,807,"MKD","Macedonia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2014/mkd_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
51702,807,"MKD","Macedonia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2014/mkd_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
51703,807,"MKD","Macedonia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2014/mkd_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
51704,807,"MKD","Macedonia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2014/mkd_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
51705,807,"MKD","Macedonia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2014/mkd_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
51706,807,"MKD","Macedonia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2014/mkd_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
51707,807,"MKD","Macedonia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2014/mkd_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
51708,807,"MKD","Macedonia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2014/mkd_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
51709,807,"MKD","Macedonia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2015/mkd_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
51710,807,"MKD","Macedonia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2015/mkd_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
51711,807,"MKD","Macedonia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2015/mkd_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
51712,807,"MKD","Macedonia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2015/mkd_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
51713,807,"MKD","Macedonia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2015/mkd_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
51714,807,"MKD","Macedonia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2015/mkd_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
51715,807,"MKD","Macedonia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2015/mkd_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
51716,807,"MKD","Macedonia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Annual/2015/mkd_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
51717,818,"EGY","Egypt","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2000/egy_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
51718,818,"EGY","Egypt","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2000/egy_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
51719,818,"EGY","Egypt","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2000/egy_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
51720,818,"EGY","Egypt","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2000/egy_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
51721,818,"EGY","Egypt","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2000/egy_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
51722,818,"EGY","Egypt","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2000/egy_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
51723,818,"EGY","Egypt","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2000/egy_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
51724,818,"EGY","Egypt","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2000/egy_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
51725,818,"EGY","Egypt","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2001/egy_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
51726,818,"EGY","Egypt","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2001/egy_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
51727,818,"EGY","Egypt","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2001/egy_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
51728,818,"EGY","Egypt","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2001/egy_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
51729,818,"EGY","Egypt","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2001/egy_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
51730,818,"EGY","Egypt","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2001/egy_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
51731,818,"EGY","Egypt","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2001/egy_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
51732,818,"EGY","Egypt","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2001/egy_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
51733,818,"EGY","Egypt","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2002/egy_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
51734,818,"EGY","Egypt","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2002/egy_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
51735,818,"EGY","Egypt","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2002/egy_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
51736,818,"EGY","Egypt","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2002/egy_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
51737,818,"EGY","Egypt","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2002/egy_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
51738,818,"EGY","Egypt","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2002/egy_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
51739,818,"EGY","Egypt","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2002/egy_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
51740,818,"EGY","Egypt","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2002/egy_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
51741,818,"EGY","Egypt","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2003/egy_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
51742,818,"EGY","Egypt","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2003/egy_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
51743,818,"EGY","Egypt","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2003/egy_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
51744,818,"EGY","Egypt","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2003/egy_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
51745,818,"EGY","Egypt","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2003/egy_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
51746,818,"EGY","Egypt","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2003/egy_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
51747,818,"EGY","Egypt","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2003/egy_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
51748,818,"EGY","Egypt","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2003/egy_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
51749,818,"EGY","Egypt","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2004/egy_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
51750,818,"EGY","Egypt","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2004/egy_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
51751,818,"EGY","Egypt","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2004/egy_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
51752,818,"EGY","Egypt","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2004/egy_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
51753,818,"EGY","Egypt","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2004/egy_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
51754,818,"EGY","Egypt","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2004/egy_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
51755,818,"EGY","Egypt","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2004/egy_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
51756,818,"EGY","Egypt","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2004/egy_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
51757,818,"EGY","Egypt","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2005/egy_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
51758,818,"EGY","Egypt","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2005/egy_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
51759,818,"EGY","Egypt","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2005/egy_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
51760,818,"EGY","Egypt","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2005/egy_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
51761,818,"EGY","Egypt","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2005/egy_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
51762,818,"EGY","Egypt","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2005/egy_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
51763,818,"EGY","Egypt","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2005/egy_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
51764,818,"EGY","Egypt","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2005/egy_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
51765,818,"EGY","Egypt","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2006/egy_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
51766,818,"EGY","Egypt","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2006/egy_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
51767,818,"EGY","Egypt","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2006/egy_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
51768,818,"EGY","Egypt","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2006/egy_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
51769,818,"EGY","Egypt","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2006/egy_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
51770,818,"EGY","Egypt","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2006/egy_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
51771,818,"EGY","Egypt","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2006/egy_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
51772,818,"EGY","Egypt","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2006/egy_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
51773,818,"EGY","Egypt","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2007/egy_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
51774,818,"EGY","Egypt","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2007/egy_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
51775,818,"EGY","Egypt","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2007/egy_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
51776,818,"EGY","Egypt","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2007/egy_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
51777,818,"EGY","Egypt","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2007/egy_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
51778,818,"EGY","Egypt","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2007/egy_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
51779,818,"EGY","Egypt","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2007/egy_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
51780,818,"EGY","Egypt","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2007/egy_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
51781,818,"EGY","Egypt","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2008/egy_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
51782,818,"EGY","Egypt","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2008/egy_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
51783,818,"EGY","Egypt","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2008/egy_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
51784,818,"EGY","Egypt","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2008/egy_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
51785,818,"EGY","Egypt","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2008/egy_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
51786,818,"EGY","Egypt","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2008/egy_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
51787,818,"EGY","Egypt","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2008/egy_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
51788,818,"EGY","Egypt","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2008/egy_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
51789,818,"EGY","Egypt","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2009/egy_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
51790,818,"EGY","Egypt","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2009/egy_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
51791,818,"EGY","Egypt","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2009/egy_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
51792,818,"EGY","Egypt","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2009/egy_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
51793,818,"EGY","Egypt","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2009/egy_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
51794,818,"EGY","Egypt","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2009/egy_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
51795,818,"EGY","Egypt","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2009/egy_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
51796,818,"EGY","Egypt","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2009/egy_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
51797,818,"EGY","Egypt","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2010/egy_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
51798,818,"EGY","Egypt","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2010/egy_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
51799,818,"EGY","Egypt","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2010/egy_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
51800,818,"EGY","Egypt","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2010/egy_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
51801,818,"EGY","Egypt","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2010/egy_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
51802,818,"EGY","Egypt","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2010/egy_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
51803,818,"EGY","Egypt","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2010/egy_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
51804,818,"EGY","Egypt","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2010/egy_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
51805,818,"EGY","Egypt","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2011/egy_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
51806,818,"EGY","Egypt","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2011/egy_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
51807,818,"EGY","Egypt","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2011/egy_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
51808,818,"EGY","Egypt","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2011/egy_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
51809,818,"EGY","Egypt","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2011/egy_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
51810,818,"EGY","Egypt","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2011/egy_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
51811,818,"EGY","Egypt","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2011/egy_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
51812,818,"EGY","Egypt","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2011/egy_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
51813,818,"EGY","Egypt","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2012/egy_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
51814,818,"EGY","Egypt","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2012/egy_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
51815,818,"EGY","Egypt","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2012/egy_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
51816,818,"EGY","Egypt","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2012/egy_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
51817,818,"EGY","Egypt","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2012/egy_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
51818,818,"EGY","Egypt","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2012/egy_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
51819,818,"EGY","Egypt","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2012/egy_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
51820,818,"EGY","Egypt","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2012/egy_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
51821,818,"EGY","Egypt","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2013/egy_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
51822,818,"EGY","Egypt","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2013/egy_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
51823,818,"EGY","Egypt","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2013/egy_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
51824,818,"EGY","Egypt","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2013/egy_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
51825,818,"EGY","Egypt","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2013/egy_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
51826,818,"EGY","Egypt","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2013/egy_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
51827,818,"EGY","Egypt","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2013/egy_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
51828,818,"EGY","Egypt","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2013/egy_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
51829,818,"EGY","Egypt","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2014/egy_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
51830,818,"EGY","Egypt","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2014/egy_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
51831,818,"EGY","Egypt","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2014/egy_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
51832,818,"EGY","Egypt","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2014/egy_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
51833,818,"EGY","Egypt","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2014/egy_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
51834,818,"EGY","Egypt","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2014/egy_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
51835,818,"EGY","Egypt","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2014/egy_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
51836,818,"EGY","Egypt","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2014/egy_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
51837,818,"EGY","Egypt","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2015/egy_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
51838,818,"EGY","Egypt","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2015/egy_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
51839,818,"EGY","Egypt","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2015/egy_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
51840,818,"EGY","Egypt","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2015/egy_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
51841,818,"EGY","Egypt","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2015/egy_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
51842,818,"EGY","Egypt","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2015/egy_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
51843,818,"EGY","Egypt","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2015/egy_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
51844,818,"EGY","Egypt","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Annual/2015/egy_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
51845,826,"GBR","United Kingdom","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2000/gbr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
51846,826,"GBR","United Kingdom","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2000/gbr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
51847,826,"GBR","United Kingdom","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2000/gbr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
51848,826,"GBR","United Kingdom","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2000/gbr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
51849,826,"GBR","United Kingdom","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2000/gbr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
51850,826,"GBR","United Kingdom","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2000/gbr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
51851,826,"GBR","United Kingdom","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2000/gbr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
51852,826,"GBR","United Kingdom","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2000/gbr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
51853,826,"GBR","United Kingdom","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2001/gbr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
51854,826,"GBR","United Kingdom","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2001/gbr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
51855,826,"GBR","United Kingdom","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2001/gbr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
51856,826,"GBR","United Kingdom","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2001/gbr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
51857,826,"GBR","United Kingdom","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2001/gbr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
51858,826,"GBR","United Kingdom","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2001/gbr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
51859,826,"GBR","United Kingdom","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2001/gbr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
51860,826,"GBR","United Kingdom","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2001/gbr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
51861,826,"GBR","United Kingdom","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2002/gbr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
51862,826,"GBR","United Kingdom","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2002/gbr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
51863,826,"GBR","United Kingdom","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2002/gbr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
51864,826,"GBR","United Kingdom","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2002/gbr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
51865,826,"GBR","United Kingdom","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2002/gbr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
51866,826,"GBR","United Kingdom","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2002/gbr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
51867,826,"GBR","United Kingdom","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2002/gbr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
51868,826,"GBR","United Kingdom","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2002/gbr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
51869,826,"GBR","United Kingdom","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2003/gbr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
51870,826,"GBR","United Kingdom","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2003/gbr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
51871,826,"GBR","United Kingdom","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2003/gbr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
51872,826,"GBR","United Kingdom","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2003/gbr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
51873,826,"GBR","United Kingdom","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2003/gbr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
51874,826,"GBR","United Kingdom","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2003/gbr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
51875,826,"GBR","United Kingdom","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2003/gbr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
51876,826,"GBR","United Kingdom","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2003/gbr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
51877,826,"GBR","United Kingdom","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2004/gbr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
51878,826,"GBR","United Kingdom","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2004/gbr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
51879,826,"GBR","United Kingdom","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2004/gbr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
51880,826,"GBR","United Kingdom","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2004/gbr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
51881,826,"GBR","United Kingdom","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2004/gbr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
51882,826,"GBR","United Kingdom","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2004/gbr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
51883,826,"GBR","United Kingdom","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2004/gbr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
51884,826,"GBR","United Kingdom","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2004/gbr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
51885,826,"GBR","United Kingdom","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2005/gbr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
51886,826,"GBR","United Kingdom","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2005/gbr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
51887,826,"GBR","United Kingdom","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2005/gbr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
51888,826,"GBR","United Kingdom","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2005/gbr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
51889,826,"GBR","United Kingdom","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2005/gbr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
51890,826,"GBR","United Kingdom","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2005/gbr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
51891,826,"GBR","United Kingdom","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2005/gbr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
51892,826,"GBR","United Kingdom","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2005/gbr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
51893,826,"GBR","United Kingdom","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2006/gbr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
51894,826,"GBR","United Kingdom","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2006/gbr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
51895,826,"GBR","United Kingdom","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2006/gbr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
51896,826,"GBR","United Kingdom","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2006/gbr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
51897,826,"GBR","United Kingdom","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2006/gbr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
51898,826,"GBR","United Kingdom","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2006/gbr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
51899,826,"GBR","United Kingdom","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2006/gbr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
51900,826,"GBR","United Kingdom","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2006/gbr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
51901,826,"GBR","United Kingdom","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2007/gbr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
51902,826,"GBR","United Kingdom","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2007/gbr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
51903,826,"GBR","United Kingdom","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2007/gbr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
51904,826,"GBR","United Kingdom","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2007/gbr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
51905,826,"GBR","United Kingdom","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2007/gbr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
51906,826,"GBR","United Kingdom","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2007/gbr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
51907,826,"GBR","United Kingdom","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2007/gbr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
51908,826,"GBR","United Kingdom","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2007/gbr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
51909,826,"GBR","United Kingdom","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2008/gbr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
51910,826,"GBR","United Kingdom","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2008/gbr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
51911,826,"GBR","United Kingdom","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2008/gbr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
51912,826,"GBR","United Kingdom","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2008/gbr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
51913,826,"GBR","United Kingdom","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2008/gbr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
51914,826,"GBR","United Kingdom","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2008/gbr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
51915,826,"GBR","United Kingdom","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2008/gbr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
51916,826,"GBR","United Kingdom","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2008/gbr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
51917,826,"GBR","United Kingdom","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2009/gbr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
51918,826,"GBR","United Kingdom","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2009/gbr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
51919,826,"GBR","United Kingdom","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2009/gbr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
51920,826,"GBR","United Kingdom","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2009/gbr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
51921,826,"GBR","United Kingdom","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2009/gbr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
51922,826,"GBR","United Kingdom","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2009/gbr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
51923,826,"GBR","United Kingdom","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2009/gbr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
51924,826,"GBR","United Kingdom","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2009/gbr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
51925,826,"GBR","United Kingdom","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2010/gbr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
51926,826,"GBR","United Kingdom","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2010/gbr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
51927,826,"GBR","United Kingdom","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2010/gbr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
51928,826,"GBR","United Kingdom","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2010/gbr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
51929,826,"GBR","United Kingdom","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2010/gbr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
51930,826,"GBR","United Kingdom","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2010/gbr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
51931,826,"GBR","United Kingdom","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2010/gbr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
51932,826,"GBR","United Kingdom","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2010/gbr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
51933,826,"GBR","United Kingdom","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2011/gbr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
51934,826,"GBR","United Kingdom","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2011/gbr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
51935,826,"GBR","United Kingdom","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2011/gbr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
51936,826,"GBR","United Kingdom","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2011/gbr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
51937,826,"GBR","United Kingdom","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2011/gbr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
51938,826,"GBR","United Kingdom","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2011/gbr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
51939,826,"GBR","United Kingdom","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2011/gbr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
51940,826,"GBR","United Kingdom","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2011/gbr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
51941,826,"GBR","United Kingdom","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2012/gbr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
51942,826,"GBR","United Kingdom","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2012/gbr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
51943,826,"GBR","United Kingdom","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2012/gbr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
51944,826,"GBR","United Kingdom","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2012/gbr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
51945,826,"GBR","United Kingdom","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2012/gbr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
51946,826,"GBR","United Kingdom","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2012/gbr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
51947,826,"GBR","United Kingdom","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2012/gbr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
51948,826,"GBR","United Kingdom","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2012/gbr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
51949,826,"GBR","United Kingdom","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2013/gbr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
51950,826,"GBR","United Kingdom","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2013/gbr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
51951,826,"GBR","United Kingdom","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2013/gbr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
51952,826,"GBR","United Kingdom","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2013/gbr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
51953,826,"GBR","United Kingdom","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2013/gbr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
51954,826,"GBR","United Kingdom","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2013/gbr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
51955,826,"GBR","United Kingdom","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2013/gbr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
51956,826,"GBR","United Kingdom","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2013/gbr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
51957,826,"GBR","United Kingdom","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2014/gbr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
51958,826,"GBR","United Kingdom","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2014/gbr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
51959,826,"GBR","United Kingdom","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2014/gbr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
51960,826,"GBR","United Kingdom","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2014/gbr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
51961,826,"GBR","United Kingdom","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2014/gbr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
51962,826,"GBR","United Kingdom","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2014/gbr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
51963,826,"GBR","United Kingdom","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2014/gbr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
51964,826,"GBR","United Kingdom","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2014/gbr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
51965,826,"GBR","United Kingdom","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2015/gbr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
51966,826,"GBR","United Kingdom","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2015/gbr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
51967,826,"GBR","United Kingdom","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2015/gbr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
51968,826,"GBR","United Kingdom","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2015/gbr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
51969,826,"GBR","United Kingdom","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2015/gbr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
51970,826,"GBR","United Kingdom","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2015/gbr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
51971,826,"GBR","United Kingdom","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2015/gbr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
51972,826,"GBR","United Kingdom","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Annual/2015/gbr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
51973,831,"GGY","Guernsey","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2000/ggy_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
51974,831,"GGY","Guernsey","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2000/ggy_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
51975,831,"GGY","Guernsey","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2000/ggy_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
51976,831,"GGY","Guernsey","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2000/ggy_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
51977,831,"GGY","Guernsey","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2000/ggy_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
51978,831,"GGY","Guernsey","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2000/ggy_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
51979,831,"GGY","Guernsey","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2000/ggy_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
51980,831,"GGY","Guernsey","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2000/ggy_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
51981,831,"GGY","Guernsey","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2001/ggy_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
51982,831,"GGY","Guernsey","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2001/ggy_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
51983,831,"GGY","Guernsey","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2001/ggy_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
51984,831,"GGY","Guernsey","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2001/ggy_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
51985,831,"GGY","Guernsey","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2001/ggy_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
51986,831,"GGY","Guernsey","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2001/ggy_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
51987,831,"GGY","Guernsey","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2001/ggy_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
51988,831,"GGY","Guernsey","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2001/ggy_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
51989,831,"GGY","Guernsey","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2002/ggy_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
51990,831,"GGY","Guernsey","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2002/ggy_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
51991,831,"GGY","Guernsey","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2002/ggy_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
51992,831,"GGY","Guernsey","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2002/ggy_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
51993,831,"GGY","Guernsey","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2002/ggy_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
51994,831,"GGY","Guernsey","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2002/ggy_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
51995,831,"GGY","Guernsey","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2002/ggy_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
51996,831,"GGY","Guernsey","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2002/ggy_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
51997,831,"GGY","Guernsey","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2003/ggy_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
51998,831,"GGY","Guernsey","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2003/ggy_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
51999,831,"GGY","Guernsey","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2003/ggy_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
52000,831,"GGY","Guernsey","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2003/ggy_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
52001,831,"GGY","Guernsey","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2003/ggy_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
52002,831,"GGY","Guernsey","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2003/ggy_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
52003,831,"GGY","Guernsey","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2003/ggy_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
52004,831,"GGY","Guernsey","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2003/ggy_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
52005,831,"GGY","Guernsey","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2004/ggy_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
52006,831,"GGY","Guernsey","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2004/ggy_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
52007,831,"GGY","Guernsey","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2004/ggy_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
52008,831,"GGY","Guernsey","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2004/ggy_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
52009,831,"GGY","Guernsey","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2004/ggy_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
52010,831,"GGY","Guernsey","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2004/ggy_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
52011,831,"GGY","Guernsey","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2004/ggy_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
52012,831,"GGY","Guernsey","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2004/ggy_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
52013,831,"GGY","Guernsey","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2005/ggy_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
52014,831,"GGY","Guernsey","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2005/ggy_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
52015,831,"GGY","Guernsey","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2005/ggy_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
52016,831,"GGY","Guernsey","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2005/ggy_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
52017,831,"GGY","Guernsey","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2005/ggy_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
52018,831,"GGY","Guernsey","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2005/ggy_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
52019,831,"GGY","Guernsey","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2005/ggy_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
52020,831,"GGY","Guernsey","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2005/ggy_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
52021,831,"GGY","Guernsey","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2006/ggy_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
52022,831,"GGY","Guernsey","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2006/ggy_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
52023,831,"GGY","Guernsey","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2006/ggy_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
52024,831,"GGY","Guernsey","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2006/ggy_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
52025,831,"GGY","Guernsey","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2006/ggy_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
52026,831,"GGY","Guernsey","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2006/ggy_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
52027,831,"GGY","Guernsey","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2006/ggy_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
52028,831,"GGY","Guernsey","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2006/ggy_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
52029,831,"GGY","Guernsey","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2007/ggy_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
52030,831,"GGY","Guernsey","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2007/ggy_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
52031,831,"GGY","Guernsey","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2007/ggy_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
52032,831,"GGY","Guernsey","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2007/ggy_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
52033,831,"GGY","Guernsey","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2007/ggy_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
52034,831,"GGY","Guernsey","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2007/ggy_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
52035,831,"GGY","Guernsey","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2007/ggy_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
52036,831,"GGY","Guernsey","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2007/ggy_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
52037,831,"GGY","Guernsey","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2008/ggy_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
52038,831,"GGY","Guernsey","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2008/ggy_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
52039,831,"GGY","Guernsey","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2008/ggy_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
52040,831,"GGY","Guernsey","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2008/ggy_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
52041,831,"GGY","Guernsey","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2008/ggy_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
52042,831,"GGY","Guernsey","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2008/ggy_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
52043,831,"GGY","Guernsey","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2008/ggy_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
52044,831,"GGY","Guernsey","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2008/ggy_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
52045,831,"GGY","Guernsey","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2009/ggy_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
52046,831,"GGY","Guernsey","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2009/ggy_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
52047,831,"GGY","Guernsey","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2009/ggy_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
52048,831,"GGY","Guernsey","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2009/ggy_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
52049,831,"GGY","Guernsey","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2009/ggy_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
52050,831,"GGY","Guernsey","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2009/ggy_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
52051,831,"GGY","Guernsey","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2009/ggy_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
52052,831,"GGY","Guernsey","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2009/ggy_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
52053,831,"GGY","Guernsey","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2010/ggy_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
52054,831,"GGY","Guernsey","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2010/ggy_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
52055,831,"GGY","Guernsey","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2010/ggy_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
52056,831,"GGY","Guernsey","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2010/ggy_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
52057,831,"GGY","Guernsey","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2010/ggy_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
52058,831,"GGY","Guernsey","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2010/ggy_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
52059,831,"GGY","Guernsey","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2010/ggy_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
52060,831,"GGY","Guernsey","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2010/ggy_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
52061,831,"GGY","Guernsey","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2011/ggy_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
52062,831,"GGY","Guernsey","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2011/ggy_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
52063,831,"GGY","Guernsey","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2011/ggy_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
52064,831,"GGY","Guernsey","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2011/ggy_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
52065,831,"GGY","Guernsey","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2011/ggy_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
52066,831,"GGY","Guernsey","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2011/ggy_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
52067,831,"GGY","Guernsey","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2011/ggy_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
52068,831,"GGY","Guernsey","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2011/ggy_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
52069,831,"GGY","Guernsey","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2012/ggy_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
52070,831,"GGY","Guernsey","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2012/ggy_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
52071,831,"GGY","Guernsey","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2012/ggy_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
52072,831,"GGY","Guernsey","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2012/ggy_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
52073,831,"GGY","Guernsey","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2012/ggy_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
52074,831,"GGY","Guernsey","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2012/ggy_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
52075,831,"GGY","Guernsey","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2012/ggy_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
52076,831,"GGY","Guernsey","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2012/ggy_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
52077,831,"GGY","Guernsey","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2013/ggy_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
52078,831,"GGY","Guernsey","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2013/ggy_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
52079,831,"GGY","Guernsey","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2013/ggy_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
52080,831,"GGY","Guernsey","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2013/ggy_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
52081,831,"GGY","Guernsey","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2013/ggy_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
52082,831,"GGY","Guernsey","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2013/ggy_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
52083,831,"GGY","Guernsey","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2013/ggy_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
52084,831,"GGY","Guernsey","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2013/ggy_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
52085,831,"GGY","Guernsey","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2014/ggy_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
52086,831,"GGY","Guernsey","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2014/ggy_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
52087,831,"GGY","Guernsey","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2014/ggy_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
52088,831,"GGY","Guernsey","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2014/ggy_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
52089,831,"GGY","Guernsey","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2014/ggy_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
52090,831,"GGY","Guernsey","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2014/ggy_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
52091,831,"GGY","Guernsey","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2014/ggy_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
52092,831,"GGY","Guernsey","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2014/ggy_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
52093,831,"GGY","Guernsey","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2015/ggy_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
52094,831,"GGY","Guernsey","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2015/ggy_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
52095,831,"GGY","Guernsey","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2015/ggy_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
52096,831,"GGY","Guernsey","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2015/ggy_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
52097,831,"GGY","Guernsey","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2015/ggy_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
52098,831,"GGY","Guernsey","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2015/ggy_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
52099,831,"GGY","Guernsey","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2015/ggy_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
52100,831,"GGY","Guernsey","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Annual/2015/ggy_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
52101,832,"JEY","Jersey","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2000/jey_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
52102,832,"JEY","Jersey","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2000/jey_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
52103,832,"JEY","Jersey","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2000/jey_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
52104,832,"JEY","Jersey","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2000/jey_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
52105,832,"JEY","Jersey","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2000/jey_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
52106,832,"JEY","Jersey","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2000/jey_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
52107,832,"JEY","Jersey","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2000/jey_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
52108,832,"JEY","Jersey","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2000/jey_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
52109,832,"JEY","Jersey","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2001/jey_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
52110,832,"JEY","Jersey","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2001/jey_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
52111,832,"JEY","Jersey","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2001/jey_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
52112,832,"JEY","Jersey","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2001/jey_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
52113,832,"JEY","Jersey","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2001/jey_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
52114,832,"JEY","Jersey","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2001/jey_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
52115,832,"JEY","Jersey","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2001/jey_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
52116,832,"JEY","Jersey","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2001/jey_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
52117,832,"JEY","Jersey","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2002/jey_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
52118,832,"JEY","Jersey","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2002/jey_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
52119,832,"JEY","Jersey","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2002/jey_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
52120,832,"JEY","Jersey","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2002/jey_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
52121,832,"JEY","Jersey","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2002/jey_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
52122,832,"JEY","Jersey","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2002/jey_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
52123,832,"JEY","Jersey","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2002/jey_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
52124,832,"JEY","Jersey","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2002/jey_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
52125,832,"JEY","Jersey","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2003/jey_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
52126,832,"JEY","Jersey","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2003/jey_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
52127,832,"JEY","Jersey","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2003/jey_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
52128,832,"JEY","Jersey","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2003/jey_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
52129,832,"JEY","Jersey","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2003/jey_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
52130,832,"JEY","Jersey","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2003/jey_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
52131,832,"JEY","Jersey","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2003/jey_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
52132,832,"JEY","Jersey","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2003/jey_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
52133,832,"JEY","Jersey","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2004/jey_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
52134,832,"JEY","Jersey","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2004/jey_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
52135,832,"JEY","Jersey","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2004/jey_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
52136,832,"JEY","Jersey","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2004/jey_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
52137,832,"JEY","Jersey","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2004/jey_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
52138,832,"JEY","Jersey","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2004/jey_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
52139,832,"JEY","Jersey","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2004/jey_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
52140,832,"JEY","Jersey","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2004/jey_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
52141,832,"JEY","Jersey","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2005/jey_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
52142,832,"JEY","Jersey","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2005/jey_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
52143,832,"JEY","Jersey","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2005/jey_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
52144,832,"JEY","Jersey","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2005/jey_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
52145,832,"JEY","Jersey","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2005/jey_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
52146,832,"JEY","Jersey","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2005/jey_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
52147,832,"JEY","Jersey","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2005/jey_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
52148,832,"JEY","Jersey","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2005/jey_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
52149,832,"JEY","Jersey","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2006/jey_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
52150,832,"JEY","Jersey","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2006/jey_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
52151,832,"JEY","Jersey","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2006/jey_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
52152,832,"JEY","Jersey","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2006/jey_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
52153,832,"JEY","Jersey","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2006/jey_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
52154,832,"JEY","Jersey","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2006/jey_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
52155,832,"JEY","Jersey","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2006/jey_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
52156,832,"JEY","Jersey","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2006/jey_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
52157,832,"JEY","Jersey","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2007/jey_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
52158,832,"JEY","Jersey","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2007/jey_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
52159,832,"JEY","Jersey","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2007/jey_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
52160,832,"JEY","Jersey","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2007/jey_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
52161,832,"JEY","Jersey","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2007/jey_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
52162,832,"JEY","Jersey","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2007/jey_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
52163,832,"JEY","Jersey","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2007/jey_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
52164,832,"JEY","Jersey","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2007/jey_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
52165,832,"JEY","Jersey","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2008/jey_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
52166,832,"JEY","Jersey","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2008/jey_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
52167,832,"JEY","Jersey","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2008/jey_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
52168,832,"JEY","Jersey","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2008/jey_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
52169,832,"JEY","Jersey","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2008/jey_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
52170,832,"JEY","Jersey","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2008/jey_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
52171,832,"JEY","Jersey","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2008/jey_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
52172,832,"JEY","Jersey","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2008/jey_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
52173,832,"JEY","Jersey","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2009/jey_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
52174,832,"JEY","Jersey","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2009/jey_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
52175,832,"JEY","Jersey","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2009/jey_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
52176,832,"JEY","Jersey","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2009/jey_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
52177,832,"JEY","Jersey","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2009/jey_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
52178,832,"JEY","Jersey","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2009/jey_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
52179,832,"JEY","Jersey","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2009/jey_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
52180,832,"JEY","Jersey","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2009/jey_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
52181,832,"JEY","Jersey","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2010/jey_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
52182,832,"JEY","Jersey","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2010/jey_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
52183,832,"JEY","Jersey","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2010/jey_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
52184,832,"JEY","Jersey","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2010/jey_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
52185,832,"JEY","Jersey","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2010/jey_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
52186,832,"JEY","Jersey","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2010/jey_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
52187,832,"JEY","Jersey","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2010/jey_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
52188,832,"JEY","Jersey","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2010/jey_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
52189,832,"JEY","Jersey","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2011/jey_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
52190,832,"JEY","Jersey","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2011/jey_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
52191,832,"JEY","Jersey","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2011/jey_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
52192,832,"JEY","Jersey","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2011/jey_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
52193,832,"JEY","Jersey","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2011/jey_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
52194,832,"JEY","Jersey","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2011/jey_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
52195,832,"JEY","Jersey","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2011/jey_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
52196,832,"JEY","Jersey","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2011/jey_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
52197,832,"JEY","Jersey","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2012/jey_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
52198,832,"JEY","Jersey","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2012/jey_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
52199,832,"JEY","Jersey","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2012/jey_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
52200,832,"JEY","Jersey","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2012/jey_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
52201,832,"JEY","Jersey","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2012/jey_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
52202,832,"JEY","Jersey","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2012/jey_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
52203,832,"JEY","Jersey","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2012/jey_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
52204,832,"JEY","Jersey","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2012/jey_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
52205,832,"JEY","Jersey","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2013/jey_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
52206,832,"JEY","Jersey","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2013/jey_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
52207,832,"JEY","Jersey","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2013/jey_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
52208,832,"JEY","Jersey","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2013/jey_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
52209,832,"JEY","Jersey","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2013/jey_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
52210,832,"JEY","Jersey","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2013/jey_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
52211,832,"JEY","Jersey","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2013/jey_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
52212,832,"JEY","Jersey","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2013/jey_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
52213,832,"JEY","Jersey","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2014/jey_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
52214,832,"JEY","Jersey","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2014/jey_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
52215,832,"JEY","Jersey","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2014/jey_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
52216,832,"JEY","Jersey","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2014/jey_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
52217,832,"JEY","Jersey","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2014/jey_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
52218,832,"JEY","Jersey","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2014/jey_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
52219,832,"JEY","Jersey","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2014/jey_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
52220,832,"JEY","Jersey","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2014/jey_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
52221,832,"JEY","Jersey","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2015/jey_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
52222,832,"JEY","Jersey","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2015/jey_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
52223,832,"JEY","Jersey","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2015/jey_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
52224,832,"JEY","Jersey","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2015/jey_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
52225,832,"JEY","Jersey","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2015/jey_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
52226,832,"JEY","Jersey","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2015/jey_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
52227,832,"JEY","Jersey","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2015/jey_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
52228,832,"JEY","Jersey","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Annual/2015/jey_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
52229,833,"IMN","Isle of Man","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2000/imn_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
52230,833,"IMN","Isle of Man","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2000/imn_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
52231,833,"IMN","Isle of Man","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2000/imn_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
52232,833,"IMN","Isle of Man","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2000/imn_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
52233,833,"IMN","Isle of Man","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2000/imn_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
52234,833,"IMN","Isle of Man","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2000/imn_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
52235,833,"IMN","Isle of Man","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2000/imn_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
52236,833,"IMN","Isle of Man","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2000/imn_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
52237,833,"IMN","Isle of Man","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2001/imn_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
52238,833,"IMN","Isle of Man","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2001/imn_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
52239,833,"IMN","Isle of Man","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2001/imn_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
52240,833,"IMN","Isle of Man","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2001/imn_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
52241,833,"IMN","Isle of Man","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2001/imn_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
52242,833,"IMN","Isle of Man","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2001/imn_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
52243,833,"IMN","Isle of Man","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2001/imn_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
52244,833,"IMN","Isle of Man","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2001/imn_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
52245,833,"IMN","Isle of Man","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2002/imn_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
52246,833,"IMN","Isle of Man","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2002/imn_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
52247,833,"IMN","Isle of Man","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2002/imn_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
52248,833,"IMN","Isle of Man","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2002/imn_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
52249,833,"IMN","Isle of Man","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2002/imn_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
52250,833,"IMN","Isle of Man","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2002/imn_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
52251,833,"IMN","Isle of Man","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2002/imn_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
52252,833,"IMN","Isle of Man","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2002/imn_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
52253,833,"IMN","Isle of Man","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2003/imn_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
52254,833,"IMN","Isle of Man","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2003/imn_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
52255,833,"IMN","Isle of Man","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2003/imn_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
52256,833,"IMN","Isle of Man","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2003/imn_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
52257,833,"IMN","Isle of Man","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2003/imn_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
52258,833,"IMN","Isle of Man","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2003/imn_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
52259,833,"IMN","Isle of Man","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2003/imn_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
52260,833,"IMN","Isle of Man","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2003/imn_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
52261,833,"IMN","Isle of Man","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2004/imn_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
52262,833,"IMN","Isle of Man","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2004/imn_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
52263,833,"IMN","Isle of Man","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2004/imn_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
52264,833,"IMN","Isle of Man","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2004/imn_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
52265,833,"IMN","Isle of Man","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2004/imn_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
52266,833,"IMN","Isle of Man","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2004/imn_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
52267,833,"IMN","Isle of Man","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2004/imn_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
52268,833,"IMN","Isle of Man","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2004/imn_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
52269,833,"IMN","Isle of Man","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2005/imn_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
52270,833,"IMN","Isle of Man","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2005/imn_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
52271,833,"IMN","Isle of Man","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2005/imn_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
52272,833,"IMN","Isle of Man","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2005/imn_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
52273,833,"IMN","Isle of Man","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2005/imn_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
52274,833,"IMN","Isle of Man","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2005/imn_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
52275,833,"IMN","Isle of Man","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2005/imn_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
52276,833,"IMN","Isle of Man","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2005/imn_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
52277,833,"IMN","Isle of Man","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2006/imn_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
52278,833,"IMN","Isle of Man","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2006/imn_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
52279,833,"IMN","Isle of Man","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2006/imn_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
52280,833,"IMN","Isle of Man","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2006/imn_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
52281,833,"IMN","Isle of Man","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2006/imn_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
52282,833,"IMN","Isle of Man","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2006/imn_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
52283,833,"IMN","Isle of Man","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2006/imn_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
52284,833,"IMN","Isle of Man","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2006/imn_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
52285,833,"IMN","Isle of Man","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2007/imn_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
52286,833,"IMN","Isle of Man","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2007/imn_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
52287,833,"IMN","Isle of Man","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2007/imn_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
52288,833,"IMN","Isle of Man","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2007/imn_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
52289,833,"IMN","Isle of Man","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2007/imn_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
52290,833,"IMN","Isle of Man","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2007/imn_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
52291,833,"IMN","Isle of Man","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2007/imn_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
52292,833,"IMN","Isle of Man","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2007/imn_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
52293,833,"IMN","Isle of Man","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2008/imn_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
52294,833,"IMN","Isle of Man","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2008/imn_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
52295,833,"IMN","Isle of Man","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2008/imn_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
52296,833,"IMN","Isle of Man","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2008/imn_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
52297,833,"IMN","Isle of Man","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2008/imn_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
52298,833,"IMN","Isle of Man","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2008/imn_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
52299,833,"IMN","Isle of Man","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2008/imn_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
52300,833,"IMN","Isle of Man","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2008/imn_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
52301,833,"IMN","Isle of Man","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2009/imn_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
52302,833,"IMN","Isle of Man","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2009/imn_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
52303,833,"IMN","Isle of Man","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2009/imn_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
52304,833,"IMN","Isle of Man","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2009/imn_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
52305,833,"IMN","Isle of Man","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2009/imn_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
52306,833,"IMN","Isle of Man","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2009/imn_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
52307,833,"IMN","Isle of Man","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2009/imn_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
52308,833,"IMN","Isle of Man","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2009/imn_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
52309,833,"IMN","Isle of Man","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2010/imn_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
52310,833,"IMN","Isle of Man","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2010/imn_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
52311,833,"IMN","Isle of Man","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2010/imn_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
52312,833,"IMN","Isle of Man","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2010/imn_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
52313,833,"IMN","Isle of Man","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2010/imn_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
52314,833,"IMN","Isle of Man","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2010/imn_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
52315,833,"IMN","Isle of Man","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2010/imn_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
52316,833,"IMN","Isle of Man","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2010/imn_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
52317,833,"IMN","Isle of Man","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2011/imn_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
52318,833,"IMN","Isle of Man","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2011/imn_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
52319,833,"IMN","Isle of Man","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2011/imn_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
52320,833,"IMN","Isle of Man","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2011/imn_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
52321,833,"IMN","Isle of Man","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2011/imn_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
52322,833,"IMN","Isle of Man","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2011/imn_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
52323,833,"IMN","Isle of Man","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2011/imn_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
52324,833,"IMN","Isle of Man","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2011/imn_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
52325,833,"IMN","Isle of Man","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2012/imn_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
52326,833,"IMN","Isle of Man","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2012/imn_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
52327,833,"IMN","Isle of Man","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2012/imn_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
52328,833,"IMN","Isle of Man","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2012/imn_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
52329,833,"IMN","Isle of Man","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2012/imn_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
52330,833,"IMN","Isle of Man","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2012/imn_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
52331,833,"IMN","Isle of Man","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2012/imn_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
52332,833,"IMN","Isle of Man","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2012/imn_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
52333,833,"IMN","Isle of Man","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2013/imn_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
52334,833,"IMN","Isle of Man","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2013/imn_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
52335,833,"IMN","Isle of Man","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2013/imn_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
52336,833,"IMN","Isle of Man","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2013/imn_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
52337,833,"IMN","Isle of Man","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2013/imn_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
52338,833,"IMN","Isle of Man","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2013/imn_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
52339,833,"IMN","Isle of Man","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2013/imn_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
52340,833,"IMN","Isle of Man","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2013/imn_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
52341,833,"IMN","Isle of Man","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2014/imn_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
52342,833,"IMN","Isle of Man","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2014/imn_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
52343,833,"IMN","Isle of Man","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2014/imn_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
52344,833,"IMN","Isle of Man","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2014/imn_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
52345,833,"IMN","Isle of Man","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2014/imn_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
52346,833,"IMN","Isle of Man","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2014/imn_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
52347,833,"IMN","Isle of Man","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2014/imn_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
52348,833,"IMN","Isle of Man","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2014/imn_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
52349,833,"IMN","Isle of Man","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2015/imn_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
52350,833,"IMN","Isle of Man","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2015/imn_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
52351,833,"IMN","Isle of Man","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2015/imn_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
52352,833,"IMN","Isle of Man","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2015/imn_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
52353,833,"IMN","Isle of Man","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2015/imn_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
52354,833,"IMN","Isle of Man","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2015/imn_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
52355,833,"IMN","Isle of Man","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2015/imn_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
52356,833,"IMN","Isle of Man","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Annual/2015/imn_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
52357,834,"TZA","Tanzania","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2000/tza_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
52358,834,"TZA","Tanzania","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2000/tza_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
52359,834,"TZA","Tanzania","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2000/tza_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
52360,834,"TZA","Tanzania","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2000/tza_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
52361,834,"TZA","Tanzania","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2000/tza_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
52362,834,"TZA","Tanzania","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2000/tza_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
52363,834,"TZA","Tanzania","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2000/tza_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
52364,834,"TZA","Tanzania","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2000/tza_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
52365,834,"TZA","Tanzania","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2001/tza_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
52366,834,"TZA","Tanzania","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2001/tza_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
52367,834,"TZA","Tanzania","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2001/tza_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
52368,834,"TZA","Tanzania","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2001/tza_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
52369,834,"TZA","Tanzania","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2001/tza_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
52370,834,"TZA","Tanzania","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2001/tza_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
52371,834,"TZA","Tanzania","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2001/tza_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
52372,834,"TZA","Tanzania","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2001/tza_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
52373,834,"TZA","Tanzania","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2002/tza_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
52374,834,"TZA","Tanzania","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2002/tza_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
52375,834,"TZA","Tanzania","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2002/tza_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
52376,834,"TZA","Tanzania","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2002/tza_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
52377,834,"TZA","Tanzania","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2002/tza_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
52378,834,"TZA","Tanzania","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2002/tza_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
52379,834,"TZA","Tanzania","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2002/tza_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
52380,834,"TZA","Tanzania","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2002/tza_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
52381,834,"TZA","Tanzania","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2003/tza_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
52382,834,"TZA","Tanzania","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2003/tza_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
52383,834,"TZA","Tanzania","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2003/tza_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
52384,834,"TZA","Tanzania","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2003/tza_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
52385,834,"TZA","Tanzania","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2003/tza_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
52386,834,"TZA","Tanzania","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2003/tza_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
52387,834,"TZA","Tanzania","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2003/tza_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
52388,834,"TZA","Tanzania","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2003/tza_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
52389,834,"TZA","Tanzania","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2004/tza_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
52390,834,"TZA","Tanzania","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2004/tza_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
52391,834,"TZA","Tanzania","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2004/tza_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
52392,834,"TZA","Tanzania","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2004/tza_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
52393,834,"TZA","Tanzania","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2004/tza_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
52394,834,"TZA","Tanzania","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2004/tza_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
52395,834,"TZA","Tanzania","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2004/tza_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
52396,834,"TZA","Tanzania","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2004/tza_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
52397,834,"TZA","Tanzania","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2005/tza_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
52398,834,"TZA","Tanzania","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2005/tza_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
52399,834,"TZA","Tanzania","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2005/tza_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
52400,834,"TZA","Tanzania","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2005/tza_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
52401,834,"TZA","Tanzania","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2005/tza_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
52402,834,"TZA","Tanzania","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2005/tza_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
52403,834,"TZA","Tanzania","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2005/tza_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
52404,834,"TZA","Tanzania","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2005/tza_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
52405,834,"TZA","Tanzania","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2006/tza_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
52406,834,"TZA","Tanzania","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2006/tza_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
52407,834,"TZA","Tanzania","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2006/tza_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
52408,834,"TZA","Tanzania","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2006/tza_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
52409,834,"TZA","Tanzania","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2006/tza_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
52410,834,"TZA","Tanzania","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2006/tza_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
52411,834,"TZA","Tanzania","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2006/tza_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
52412,834,"TZA","Tanzania","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2006/tza_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
52413,834,"TZA","Tanzania","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2007/tza_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
52414,834,"TZA","Tanzania","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2007/tza_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
52415,834,"TZA","Tanzania","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2007/tza_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
52416,834,"TZA","Tanzania","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2007/tza_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
52417,834,"TZA","Tanzania","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2007/tza_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
52418,834,"TZA","Tanzania","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2007/tza_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
52419,834,"TZA","Tanzania","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2007/tza_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
52420,834,"TZA","Tanzania","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2007/tza_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
52421,834,"TZA","Tanzania","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2008/tza_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
52422,834,"TZA","Tanzania","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2008/tza_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
52423,834,"TZA","Tanzania","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2008/tza_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
52424,834,"TZA","Tanzania","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2008/tza_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
52425,834,"TZA","Tanzania","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2008/tza_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
52426,834,"TZA","Tanzania","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2008/tza_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
52427,834,"TZA","Tanzania","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2008/tza_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
52428,834,"TZA","Tanzania","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2008/tza_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
52429,834,"TZA","Tanzania","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2009/tza_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
52430,834,"TZA","Tanzania","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2009/tza_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
52431,834,"TZA","Tanzania","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2009/tza_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
52432,834,"TZA","Tanzania","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2009/tza_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
52433,834,"TZA","Tanzania","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2009/tza_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
52434,834,"TZA","Tanzania","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2009/tza_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
52435,834,"TZA","Tanzania","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2009/tza_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
52436,834,"TZA","Tanzania","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2009/tza_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
52437,834,"TZA","Tanzania","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2010/tza_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
52438,834,"TZA","Tanzania","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2010/tza_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
52439,834,"TZA","Tanzania","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2010/tza_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
52440,834,"TZA","Tanzania","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2010/tza_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
52441,834,"TZA","Tanzania","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2010/tza_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
52442,834,"TZA","Tanzania","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2010/tza_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
52443,834,"TZA","Tanzania","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2010/tza_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
52444,834,"TZA","Tanzania","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2010/tza_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
52445,834,"TZA","Tanzania","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2011/tza_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
52446,834,"TZA","Tanzania","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2011/tza_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
52447,834,"TZA","Tanzania","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2011/tza_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
52448,834,"TZA","Tanzania","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2011/tza_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
52449,834,"TZA","Tanzania","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2011/tza_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
52450,834,"TZA","Tanzania","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2011/tza_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
52451,834,"TZA","Tanzania","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2011/tza_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
52452,834,"TZA","Tanzania","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2011/tza_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
52453,834,"TZA","Tanzania","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2012/tza_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
52454,834,"TZA","Tanzania","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2012/tza_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
52455,834,"TZA","Tanzania","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2012/tza_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
52456,834,"TZA","Tanzania","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2012/tza_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
52457,834,"TZA","Tanzania","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2012/tza_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
52458,834,"TZA","Tanzania","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2012/tza_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
52459,834,"TZA","Tanzania","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2012/tza_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
52460,834,"TZA","Tanzania","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2012/tza_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
52461,834,"TZA","Tanzania","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2013/tza_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
52462,834,"TZA","Tanzania","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2013/tza_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
52463,834,"TZA","Tanzania","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2013/tza_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
52464,834,"TZA","Tanzania","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2013/tza_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
52465,834,"TZA","Tanzania","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2013/tza_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
52466,834,"TZA","Tanzania","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2013/tza_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
52467,834,"TZA","Tanzania","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2013/tza_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
52468,834,"TZA","Tanzania","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2013/tza_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
52469,834,"TZA","Tanzania","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2014/tza_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
52470,834,"TZA","Tanzania","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2014/tza_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
52471,834,"TZA","Tanzania","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2014/tza_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
52472,834,"TZA","Tanzania","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2014/tza_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
52473,834,"TZA","Tanzania","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2014/tza_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
52474,834,"TZA","Tanzania","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2014/tza_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
52475,834,"TZA","Tanzania","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2014/tza_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
52476,834,"TZA","Tanzania","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2014/tza_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
52477,834,"TZA","Tanzania","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2015/tza_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
52478,834,"TZA","Tanzania","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2015/tza_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
52479,834,"TZA","Tanzania","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2015/tza_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
52480,834,"TZA","Tanzania","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2015/tza_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
52481,834,"TZA","Tanzania","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2015/tza_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
52482,834,"TZA","Tanzania","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2015/tza_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
52483,834,"TZA","Tanzania","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2015/tza_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
52484,834,"TZA","Tanzania","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Annual/2015/tza_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
52485,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2000/bfa_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
52486,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2000/bfa_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
52487,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2000/bfa_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
52488,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2000/bfa_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
52489,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2000/bfa_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
52490,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2000/bfa_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
52491,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2000/bfa_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
52492,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2000/bfa_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
52493,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2001/bfa_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
52494,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2001/bfa_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
52495,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2001/bfa_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
52496,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2001/bfa_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
52497,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2001/bfa_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
52498,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2001/bfa_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
52499,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2001/bfa_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
52500,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2001/bfa_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
52501,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2002/bfa_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
52502,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2002/bfa_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
52503,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2002/bfa_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
52504,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2002/bfa_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
52505,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2002/bfa_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
52506,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2002/bfa_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
52507,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2002/bfa_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
52508,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2002/bfa_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
52509,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2003/bfa_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
52510,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2003/bfa_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
52511,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2003/bfa_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
52512,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2003/bfa_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
52513,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2003/bfa_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
52514,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2003/bfa_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
52515,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2003/bfa_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
52516,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2003/bfa_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
52517,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2004/bfa_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
52518,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2004/bfa_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
52519,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2004/bfa_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
52520,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2004/bfa_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
52521,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2004/bfa_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
52522,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2004/bfa_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
52523,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2004/bfa_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
52524,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2004/bfa_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
52525,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2005/bfa_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
52526,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2005/bfa_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
52527,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2005/bfa_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
52528,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2005/bfa_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
52529,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2005/bfa_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
52530,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2005/bfa_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
52531,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2005/bfa_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
52532,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2005/bfa_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
52533,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2006/bfa_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
52534,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2006/bfa_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
52535,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2006/bfa_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
52536,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2006/bfa_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
52537,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2006/bfa_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
52538,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2006/bfa_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
52539,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2006/bfa_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
52540,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2006/bfa_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
52541,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2007/bfa_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
52542,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2007/bfa_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
52543,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2007/bfa_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
52544,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2007/bfa_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
52545,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2007/bfa_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
52546,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2007/bfa_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
52547,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2007/bfa_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
52548,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2007/bfa_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
52549,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2008/bfa_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
52550,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2008/bfa_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
52551,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2008/bfa_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
52552,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2008/bfa_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
52553,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2008/bfa_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
52554,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2008/bfa_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
52555,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2008/bfa_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
52556,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2008/bfa_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
52557,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2009/bfa_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
52558,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2009/bfa_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
52559,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2009/bfa_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
52560,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2009/bfa_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
52561,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2009/bfa_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
52562,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2009/bfa_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
52563,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2009/bfa_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
52564,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2009/bfa_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
52565,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2010/bfa_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
52566,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2010/bfa_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
52567,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2010/bfa_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
52568,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2010/bfa_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
52569,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2010/bfa_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
52570,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2010/bfa_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
52571,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2010/bfa_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
52572,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2010/bfa_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
52573,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2011/bfa_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
52574,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2011/bfa_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
52575,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2011/bfa_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
52576,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2011/bfa_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
52577,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2011/bfa_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
52578,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2011/bfa_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
52579,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2011/bfa_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
52580,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2011/bfa_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
52581,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2012/bfa_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
52582,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2012/bfa_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
52583,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2012/bfa_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
52584,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2012/bfa_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
52585,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2012/bfa_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
52586,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2012/bfa_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
52587,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2012/bfa_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
52588,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2012/bfa_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
52589,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2013/bfa_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
52590,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2013/bfa_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
52591,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2013/bfa_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
52592,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2013/bfa_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
52593,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2013/bfa_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
52594,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2013/bfa_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
52595,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2013/bfa_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
52596,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2013/bfa_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
52597,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2014/bfa_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
52598,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2014/bfa_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
52599,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2014/bfa_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
52600,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2014/bfa_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
52601,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2014/bfa_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
52602,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2014/bfa_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
52603,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2014/bfa_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
52604,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2014/bfa_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
52605,854,"BFA","Burkina Faso","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2015/bfa_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
52606,854,"BFA","Burkina Faso","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2015/bfa_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
52607,854,"BFA","Burkina Faso","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2015/bfa_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
52608,854,"BFA","Burkina Faso","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2015/bfa_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
52609,854,"BFA","Burkina Faso","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2015/bfa_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
52610,854,"BFA","Burkina Faso","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2015/bfa_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
52611,854,"BFA","Burkina Faso","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2015/bfa_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
52612,854,"BFA","Burkina Faso","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Annual/2015/bfa_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
52613,858,"URY","Uruguay","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2000/ury_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
52614,858,"URY","Uruguay","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2000/ury_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
52615,858,"URY","Uruguay","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2000/ury_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
52616,858,"URY","Uruguay","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2000/ury_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
52617,858,"URY","Uruguay","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2000/ury_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
52618,858,"URY","Uruguay","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2000/ury_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
52619,858,"URY","Uruguay","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2000/ury_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
52620,858,"URY","Uruguay","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2000/ury_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
52621,858,"URY","Uruguay","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2001/ury_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
52622,858,"URY","Uruguay","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2001/ury_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
52623,858,"URY","Uruguay","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2001/ury_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
52624,858,"URY","Uruguay","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2001/ury_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
52625,858,"URY","Uruguay","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2001/ury_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
52626,858,"URY","Uruguay","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2001/ury_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
52627,858,"URY","Uruguay","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2001/ury_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
52628,858,"URY","Uruguay","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2001/ury_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
52629,858,"URY","Uruguay","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2002/ury_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
52630,858,"URY","Uruguay","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2002/ury_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
52631,858,"URY","Uruguay","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2002/ury_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
52632,858,"URY","Uruguay","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2002/ury_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
52633,858,"URY","Uruguay","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2002/ury_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
52634,858,"URY","Uruguay","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2002/ury_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
52635,858,"URY","Uruguay","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2002/ury_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
52636,858,"URY","Uruguay","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2002/ury_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
52637,858,"URY","Uruguay","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2003/ury_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
52638,858,"URY","Uruguay","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2003/ury_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
52639,858,"URY","Uruguay","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2003/ury_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
52640,858,"URY","Uruguay","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2003/ury_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
52641,858,"URY","Uruguay","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2003/ury_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
52642,858,"URY","Uruguay","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2003/ury_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
52643,858,"URY","Uruguay","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2003/ury_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
52644,858,"URY","Uruguay","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2003/ury_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
52645,858,"URY","Uruguay","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2004/ury_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
52646,858,"URY","Uruguay","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2004/ury_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
52647,858,"URY","Uruguay","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2004/ury_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
52648,858,"URY","Uruguay","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2004/ury_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
52649,858,"URY","Uruguay","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2004/ury_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
52650,858,"URY","Uruguay","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2004/ury_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
52651,858,"URY","Uruguay","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2004/ury_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
52652,858,"URY","Uruguay","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2004/ury_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
52653,858,"URY","Uruguay","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2005/ury_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
52654,858,"URY","Uruguay","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2005/ury_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
52655,858,"URY","Uruguay","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2005/ury_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
52656,858,"URY","Uruguay","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2005/ury_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
52657,858,"URY","Uruguay","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2005/ury_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
52658,858,"URY","Uruguay","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2005/ury_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
52659,858,"URY","Uruguay","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2005/ury_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
52660,858,"URY","Uruguay","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2005/ury_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
52661,858,"URY","Uruguay","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2006/ury_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
52662,858,"URY","Uruguay","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2006/ury_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
52663,858,"URY","Uruguay","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2006/ury_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
52664,858,"URY","Uruguay","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2006/ury_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
52665,858,"URY","Uruguay","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2006/ury_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
52666,858,"URY","Uruguay","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2006/ury_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
52667,858,"URY","Uruguay","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2006/ury_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
52668,858,"URY","Uruguay","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2006/ury_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
52669,858,"URY","Uruguay","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2007/ury_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
52670,858,"URY","Uruguay","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2007/ury_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
52671,858,"URY","Uruguay","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2007/ury_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
52672,858,"URY","Uruguay","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2007/ury_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
52673,858,"URY","Uruguay","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2007/ury_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
52674,858,"URY","Uruguay","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2007/ury_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
52675,858,"URY","Uruguay","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2007/ury_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
52676,858,"URY","Uruguay","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2007/ury_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
52677,858,"URY","Uruguay","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2008/ury_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
52678,858,"URY","Uruguay","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2008/ury_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
52679,858,"URY","Uruguay","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2008/ury_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
52680,858,"URY","Uruguay","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2008/ury_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
52681,858,"URY","Uruguay","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2008/ury_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
52682,858,"URY","Uruguay","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2008/ury_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
52683,858,"URY","Uruguay","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2008/ury_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
52684,858,"URY","Uruguay","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2008/ury_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
52685,858,"URY","Uruguay","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2009/ury_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
52686,858,"URY","Uruguay","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2009/ury_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
52687,858,"URY","Uruguay","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2009/ury_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
52688,858,"URY","Uruguay","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2009/ury_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
52689,858,"URY","Uruguay","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2009/ury_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
52690,858,"URY","Uruguay","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2009/ury_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
52691,858,"URY","Uruguay","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2009/ury_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
52692,858,"URY","Uruguay","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2009/ury_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
52693,858,"URY","Uruguay","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2010/ury_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
52694,858,"URY","Uruguay","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2010/ury_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
52695,858,"URY","Uruguay","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2010/ury_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
52696,858,"URY","Uruguay","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2010/ury_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
52697,858,"URY","Uruguay","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2010/ury_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
52698,858,"URY","Uruguay","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2010/ury_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
52699,858,"URY","Uruguay","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2010/ury_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
52700,858,"URY","Uruguay","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2010/ury_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
52701,858,"URY","Uruguay","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2011/ury_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
52702,858,"URY","Uruguay","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2011/ury_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
52703,858,"URY","Uruguay","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2011/ury_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
52704,858,"URY","Uruguay","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2011/ury_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
52705,858,"URY","Uruguay","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2011/ury_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
52706,858,"URY","Uruguay","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2011/ury_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
52707,858,"URY","Uruguay","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2011/ury_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
52708,858,"URY","Uruguay","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2011/ury_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
52709,858,"URY","Uruguay","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2012/ury_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
52710,858,"URY","Uruguay","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2012/ury_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
52711,858,"URY","Uruguay","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2012/ury_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
52712,858,"URY","Uruguay","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2012/ury_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
52713,858,"URY","Uruguay","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2012/ury_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
52714,858,"URY","Uruguay","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2012/ury_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
52715,858,"URY","Uruguay","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2012/ury_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
52716,858,"URY","Uruguay","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2012/ury_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
52717,858,"URY","Uruguay","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2013/ury_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
52718,858,"URY","Uruguay","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2013/ury_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
52719,858,"URY","Uruguay","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2013/ury_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
52720,858,"URY","Uruguay","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2013/ury_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
52721,858,"URY","Uruguay","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2013/ury_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
52722,858,"URY","Uruguay","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2013/ury_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
52723,858,"URY","Uruguay","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2013/ury_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
52724,858,"URY","Uruguay","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2013/ury_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
52725,858,"URY","Uruguay","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2014/ury_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
52726,858,"URY","Uruguay","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2014/ury_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
52727,858,"URY","Uruguay","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2014/ury_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
52728,858,"URY","Uruguay","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2014/ury_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
52729,858,"URY","Uruguay","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2014/ury_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
52730,858,"URY","Uruguay","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2014/ury_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
52731,858,"URY","Uruguay","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2014/ury_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
52732,858,"URY","Uruguay","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2014/ury_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
52733,858,"URY","Uruguay","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2015/ury_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
52734,858,"URY","Uruguay","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2015/ury_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
52735,858,"URY","Uruguay","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2015/ury_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
52736,858,"URY","Uruguay","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2015/ury_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
52737,858,"URY","Uruguay","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2015/ury_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
52738,858,"URY","Uruguay","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2015/ury_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
52739,858,"URY","Uruguay","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2015/ury_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
52740,858,"URY","Uruguay","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Annual/2015/ury_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
52741,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2000/uzb_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
52742,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2000/uzb_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
52743,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2000/uzb_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
52744,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2000/uzb_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
52745,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2000/uzb_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
52746,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2000/uzb_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
52747,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2000/uzb_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
52748,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2000/uzb_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
52749,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2001/uzb_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
52750,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2001/uzb_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
52751,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2001/uzb_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
52752,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2001/uzb_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
52753,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2001/uzb_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
52754,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2001/uzb_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
52755,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2001/uzb_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
52756,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2001/uzb_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
52757,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2002/uzb_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
52758,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2002/uzb_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
52759,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2002/uzb_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
52760,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2002/uzb_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
52761,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2002/uzb_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
52762,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2002/uzb_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
52763,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2002/uzb_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
52764,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2002/uzb_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
52765,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2003/uzb_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
52766,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2003/uzb_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
52767,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2003/uzb_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
52768,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2003/uzb_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
52769,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2003/uzb_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
52770,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2003/uzb_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
52771,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2003/uzb_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
52772,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2003/uzb_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
52773,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2004/uzb_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
52774,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2004/uzb_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
52775,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2004/uzb_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
52776,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2004/uzb_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
52777,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2004/uzb_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
52778,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2004/uzb_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
52779,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2004/uzb_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
52780,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2004/uzb_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
52781,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2005/uzb_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
52782,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2005/uzb_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
52783,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2005/uzb_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
52784,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2005/uzb_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
52785,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2005/uzb_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
52786,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2005/uzb_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
52787,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2005/uzb_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
52788,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2005/uzb_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
52789,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2006/uzb_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
52790,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2006/uzb_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
52791,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2006/uzb_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
52792,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2006/uzb_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
52793,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2006/uzb_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
52794,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2006/uzb_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
52795,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2006/uzb_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
52796,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2006/uzb_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
52797,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2007/uzb_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
52798,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2007/uzb_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
52799,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2007/uzb_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
52800,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2007/uzb_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
52801,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2007/uzb_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
52802,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2007/uzb_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
52803,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2007/uzb_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
52804,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2007/uzb_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
52805,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2008/uzb_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
52806,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2008/uzb_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
52807,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2008/uzb_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
52808,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2008/uzb_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
52809,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2008/uzb_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
52810,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2008/uzb_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
52811,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2008/uzb_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
52812,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2008/uzb_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
52813,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2009/uzb_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
52814,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2009/uzb_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
52815,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2009/uzb_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
52816,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2009/uzb_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
52817,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2009/uzb_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
52818,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2009/uzb_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
52819,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2009/uzb_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
52820,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2009/uzb_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
52821,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2010/uzb_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
52822,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2010/uzb_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
52823,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2010/uzb_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
52824,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2010/uzb_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
52825,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2010/uzb_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
52826,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2010/uzb_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
52827,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2010/uzb_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
52828,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2010/uzb_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
52829,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2011/uzb_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
52830,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2011/uzb_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
52831,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2011/uzb_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
52832,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2011/uzb_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
52833,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2011/uzb_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
52834,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2011/uzb_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
52835,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2011/uzb_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
52836,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2011/uzb_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
52837,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2012/uzb_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
52838,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2012/uzb_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
52839,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2012/uzb_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
52840,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2012/uzb_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
52841,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2012/uzb_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
52842,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2012/uzb_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
52843,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2012/uzb_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
52844,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2012/uzb_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
52845,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2013/uzb_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
52846,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2013/uzb_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
52847,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2013/uzb_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
52848,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2013/uzb_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
52849,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2013/uzb_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
52850,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2013/uzb_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
52851,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2013/uzb_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
52852,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2013/uzb_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
52853,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2014/uzb_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
52854,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2014/uzb_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
52855,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2014/uzb_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
52856,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2014/uzb_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
52857,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2014/uzb_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
52858,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2014/uzb_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
52859,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2014/uzb_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
52860,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2014/uzb_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
52861,860,"UZB","Uzbekistan","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2015/uzb_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
52862,860,"UZB","Uzbekistan","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2015/uzb_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
52863,860,"UZB","Uzbekistan","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2015/uzb_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
52864,860,"UZB","Uzbekistan","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2015/uzb_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
52865,860,"UZB","Uzbekistan","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2015/uzb_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
52866,860,"UZB","Uzbekistan","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2015/uzb_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
52867,860,"UZB","Uzbekistan","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2015/uzb_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
52868,860,"UZB","Uzbekistan","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Annual/2015/uzb_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
52869,862,"VEN","Venezuela","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2000/ven_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
52870,862,"VEN","Venezuela","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2000/ven_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
52871,862,"VEN","Venezuela","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2000/ven_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
52872,862,"VEN","Venezuela","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2000/ven_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
52873,862,"VEN","Venezuela","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2000/ven_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
52874,862,"VEN","Venezuela","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2000/ven_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
52875,862,"VEN","Venezuela","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2000/ven_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
52876,862,"VEN","Venezuela","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2000/ven_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
52877,862,"VEN","Venezuela","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2001/ven_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
52878,862,"VEN","Venezuela","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2001/ven_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
52879,862,"VEN","Venezuela","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2001/ven_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
52880,862,"VEN","Venezuela","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2001/ven_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
52881,862,"VEN","Venezuela","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2001/ven_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
52882,862,"VEN","Venezuela","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2001/ven_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
52883,862,"VEN","Venezuela","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2001/ven_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
52884,862,"VEN","Venezuela","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2001/ven_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
52885,862,"VEN","Venezuela","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2002/ven_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
52886,862,"VEN","Venezuela","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2002/ven_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
52887,862,"VEN","Venezuela","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2002/ven_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
52888,862,"VEN","Venezuela","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2002/ven_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
52889,862,"VEN","Venezuela","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2002/ven_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
52890,862,"VEN","Venezuela","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2002/ven_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
52891,862,"VEN","Venezuela","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2002/ven_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
52892,862,"VEN","Venezuela","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2002/ven_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
52893,862,"VEN","Venezuela","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2003/ven_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
52894,862,"VEN","Venezuela","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2003/ven_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
52895,862,"VEN","Venezuela","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2003/ven_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
52896,862,"VEN","Venezuela","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2003/ven_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
52897,862,"VEN","Venezuela","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2003/ven_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
52898,862,"VEN","Venezuela","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2003/ven_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
52899,862,"VEN","Venezuela","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2003/ven_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
52900,862,"VEN","Venezuela","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2003/ven_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
52901,862,"VEN","Venezuela","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2004/ven_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
52902,862,"VEN","Venezuela","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2004/ven_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
52903,862,"VEN","Venezuela","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2004/ven_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
52904,862,"VEN","Venezuela","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2004/ven_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
52905,862,"VEN","Venezuela","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2004/ven_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
52906,862,"VEN","Venezuela","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2004/ven_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
52907,862,"VEN","Venezuela","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2004/ven_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
52908,862,"VEN","Venezuela","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2004/ven_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
52909,862,"VEN","Venezuela","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2005/ven_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
52910,862,"VEN","Venezuela","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2005/ven_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
52911,862,"VEN","Venezuela","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2005/ven_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
52912,862,"VEN","Venezuela","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2005/ven_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
52913,862,"VEN","Venezuela","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2005/ven_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
52914,862,"VEN","Venezuela","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2005/ven_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
52915,862,"VEN","Venezuela","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2005/ven_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
52916,862,"VEN","Venezuela","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2005/ven_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
52917,862,"VEN","Venezuela","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2006/ven_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
52918,862,"VEN","Venezuela","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2006/ven_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
52919,862,"VEN","Venezuela","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2006/ven_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
52920,862,"VEN","Venezuela","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2006/ven_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
52921,862,"VEN","Venezuela","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2006/ven_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
52922,862,"VEN","Venezuela","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2006/ven_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
52923,862,"VEN","Venezuela","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2006/ven_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
52924,862,"VEN","Venezuela","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2006/ven_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
52925,862,"VEN","Venezuela","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2007/ven_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
52926,862,"VEN","Venezuela","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2007/ven_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
52927,862,"VEN","Venezuela","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2007/ven_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
52928,862,"VEN","Venezuela","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2007/ven_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
52929,862,"VEN","Venezuela","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2007/ven_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
52930,862,"VEN","Venezuela","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2007/ven_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
52931,862,"VEN","Venezuela","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2007/ven_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
52932,862,"VEN","Venezuela","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2007/ven_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
52933,862,"VEN","Venezuela","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2008/ven_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
52934,862,"VEN","Venezuela","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2008/ven_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
52935,862,"VEN","Venezuela","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2008/ven_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
52936,862,"VEN","Venezuela","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2008/ven_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
52937,862,"VEN","Venezuela","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2008/ven_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
52938,862,"VEN","Venezuela","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2008/ven_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
52939,862,"VEN","Venezuela","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2008/ven_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
52940,862,"VEN","Venezuela","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2008/ven_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
52941,862,"VEN","Venezuela","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2009/ven_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
52942,862,"VEN","Venezuela","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2009/ven_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
52943,862,"VEN","Venezuela","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2009/ven_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
52944,862,"VEN","Venezuela","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2009/ven_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
52945,862,"VEN","Venezuela","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2009/ven_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
52946,862,"VEN","Venezuela","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2009/ven_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
52947,862,"VEN","Venezuela","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2009/ven_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
52948,862,"VEN","Venezuela","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2009/ven_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
52949,862,"VEN","Venezuela","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2010/ven_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
52950,862,"VEN","Venezuela","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2010/ven_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
52951,862,"VEN","Venezuela","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2010/ven_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
52952,862,"VEN","Venezuela","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2010/ven_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
52953,862,"VEN","Venezuela","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2010/ven_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
52954,862,"VEN","Venezuela","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2010/ven_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
52955,862,"VEN","Venezuela","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2010/ven_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
52956,862,"VEN","Venezuela","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2010/ven_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
52957,862,"VEN","Venezuela","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2011/ven_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
52958,862,"VEN","Venezuela","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2011/ven_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
52959,862,"VEN","Venezuela","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2011/ven_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
52960,862,"VEN","Venezuela","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2011/ven_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
52961,862,"VEN","Venezuela","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2011/ven_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
52962,862,"VEN","Venezuela","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2011/ven_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
52963,862,"VEN","Venezuela","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2011/ven_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
52964,862,"VEN","Venezuela","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2011/ven_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
52965,862,"VEN","Venezuela","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2012/ven_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
52966,862,"VEN","Venezuela","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2012/ven_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
52967,862,"VEN","Venezuela","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2012/ven_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
52968,862,"VEN","Venezuela","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2012/ven_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
52969,862,"VEN","Venezuela","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2012/ven_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
52970,862,"VEN","Venezuela","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2012/ven_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
52971,862,"VEN","Venezuela","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2012/ven_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
52972,862,"VEN","Venezuela","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2012/ven_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
52973,862,"VEN","Venezuela","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2013/ven_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
52974,862,"VEN","Venezuela","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2013/ven_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
52975,862,"VEN","Venezuela","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2013/ven_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
52976,862,"VEN","Venezuela","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2013/ven_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
52977,862,"VEN","Venezuela","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2013/ven_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
52978,862,"VEN","Venezuela","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2013/ven_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
52979,862,"VEN","Venezuela","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2013/ven_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
52980,862,"VEN","Venezuela","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2013/ven_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
52981,862,"VEN","Venezuela","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2014/ven_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
52982,862,"VEN","Venezuela","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2014/ven_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
52983,862,"VEN","Venezuela","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2014/ven_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
52984,862,"VEN","Venezuela","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2014/ven_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
52985,862,"VEN","Venezuela","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2014/ven_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
52986,862,"VEN","Venezuela","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2014/ven_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
52987,862,"VEN","Venezuela","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2014/ven_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
52988,862,"VEN","Venezuela","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2014/ven_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
52989,862,"VEN","Venezuela","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2015/ven_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
52990,862,"VEN","Venezuela","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2015/ven_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
52991,862,"VEN","Venezuela","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2015/ven_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
52992,862,"VEN","Venezuela","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2015/ven_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
52993,862,"VEN","Venezuela","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2015/ven_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
52994,862,"VEN","Venezuela","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2015/ven_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
52995,862,"VEN","Venezuela","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2015/ven_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
52996,862,"VEN","Venezuela","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Annual/2015/ven_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
52997,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2000/wlf_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
52998,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2000/wlf_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
52999,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2000/wlf_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
53000,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2000/wlf_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
53001,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2000/wlf_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
53002,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2000/wlf_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
53003,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2000/wlf_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
53004,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2000/wlf_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
53005,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2001/wlf_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
53006,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2001/wlf_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
53007,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2001/wlf_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
53008,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2001/wlf_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
53009,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2001/wlf_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
53010,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2001/wlf_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
53011,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2001/wlf_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
53012,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2001/wlf_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
53013,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2002/wlf_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
53014,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2002/wlf_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
53015,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2002/wlf_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
53016,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2002/wlf_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
53017,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2002/wlf_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
53018,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2002/wlf_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
53019,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2002/wlf_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
53020,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2002/wlf_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
53021,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2003/wlf_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
53022,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2003/wlf_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
53023,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2003/wlf_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
53024,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2003/wlf_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
53025,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2003/wlf_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
53026,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2003/wlf_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
53027,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2003/wlf_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
53028,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2003/wlf_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
53029,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2004/wlf_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
53030,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2004/wlf_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
53031,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2004/wlf_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
53032,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2004/wlf_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
53033,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2004/wlf_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
53034,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2004/wlf_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
53035,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2004/wlf_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
53036,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2004/wlf_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
53037,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2005/wlf_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
53038,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2005/wlf_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
53039,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2005/wlf_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
53040,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2005/wlf_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
53041,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2005/wlf_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
53042,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2005/wlf_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
53043,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2005/wlf_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
53044,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2005/wlf_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
53045,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2006/wlf_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
53046,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2006/wlf_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
53047,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2006/wlf_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
53048,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2006/wlf_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
53049,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2006/wlf_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
53050,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2006/wlf_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
53051,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2006/wlf_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
53052,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2006/wlf_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
53053,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2007/wlf_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
53054,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2007/wlf_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
53055,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2007/wlf_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
53056,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2007/wlf_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
53057,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2007/wlf_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
53058,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2007/wlf_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
53059,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2007/wlf_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
53060,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2007/wlf_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
53061,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2008/wlf_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
53062,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2008/wlf_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
53063,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2008/wlf_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
53064,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2008/wlf_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
53065,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2008/wlf_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
53066,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2008/wlf_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
53067,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2008/wlf_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
53068,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2008/wlf_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
53069,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2009/wlf_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
53070,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2009/wlf_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
53071,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2009/wlf_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
53072,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2009/wlf_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
53073,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2009/wlf_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
53074,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2009/wlf_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
53075,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2009/wlf_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
53076,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2009/wlf_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
53077,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2010/wlf_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
53078,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2010/wlf_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
53079,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2010/wlf_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
53080,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2010/wlf_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
53081,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2010/wlf_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
53082,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2010/wlf_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
53083,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2010/wlf_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
53084,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2010/wlf_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
53085,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2011/wlf_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
53086,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2011/wlf_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
53087,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2011/wlf_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
53088,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2011/wlf_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
53089,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2011/wlf_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
53090,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2011/wlf_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
53091,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2011/wlf_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
53092,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2011/wlf_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
53093,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2012/wlf_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
53094,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2012/wlf_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
53095,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2012/wlf_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
53096,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2012/wlf_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
53097,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2012/wlf_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
53098,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2012/wlf_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
53099,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2012/wlf_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
53100,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2012/wlf_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
53101,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2013/wlf_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
53102,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2013/wlf_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
53103,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2013/wlf_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
53104,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2013/wlf_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
53105,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2013/wlf_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
53106,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2013/wlf_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
53107,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2013/wlf_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
53108,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2013/wlf_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
53109,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2014/wlf_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
53110,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2014/wlf_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
53111,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2014/wlf_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
53112,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2014/wlf_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
53113,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2014/wlf_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
53114,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2014/wlf_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
53115,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2014/wlf_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
53116,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2014/wlf_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
53117,876,"WLF","Wallis and Futuna","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2015/wlf_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
53118,876,"WLF","Wallis and Futuna","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2015/wlf_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
53119,876,"WLF","Wallis and Futuna","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2015/wlf_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
53120,876,"WLF","Wallis and Futuna","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2015/wlf_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
53121,876,"WLF","Wallis and Futuna","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2015/wlf_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
53122,876,"WLF","Wallis and Futuna","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2015/wlf_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
53123,876,"WLF","Wallis and Futuna","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2015/wlf_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
53124,876,"WLF","Wallis and Futuna","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Annual/2015/wlf_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
53125,882,"WSM","Samoa","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2000/wsm_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
53126,882,"WSM","Samoa","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2000/wsm_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
53127,882,"WSM","Samoa","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2000/wsm_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
53128,882,"WSM","Samoa","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2000/wsm_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
53129,882,"WSM","Samoa","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2000/wsm_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
53130,882,"WSM","Samoa","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2000/wsm_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
53131,882,"WSM","Samoa","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2000/wsm_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
53132,882,"WSM","Samoa","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2000/wsm_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
53133,882,"WSM","Samoa","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2001/wsm_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
53134,882,"WSM","Samoa","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2001/wsm_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
53135,882,"WSM","Samoa","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2001/wsm_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
53136,882,"WSM","Samoa","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2001/wsm_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
53137,882,"WSM","Samoa","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2001/wsm_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
53138,882,"WSM","Samoa","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2001/wsm_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
53139,882,"WSM","Samoa","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2001/wsm_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
53140,882,"WSM","Samoa","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2001/wsm_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
53141,882,"WSM","Samoa","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2002/wsm_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
53142,882,"WSM","Samoa","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2002/wsm_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
53143,882,"WSM","Samoa","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2002/wsm_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
53144,882,"WSM","Samoa","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2002/wsm_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
53145,882,"WSM","Samoa","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2002/wsm_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
53146,882,"WSM","Samoa","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2002/wsm_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
53147,882,"WSM","Samoa","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2002/wsm_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
53148,882,"WSM","Samoa","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2002/wsm_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
53149,882,"WSM","Samoa","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2003/wsm_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
53150,882,"WSM","Samoa","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2003/wsm_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
53151,882,"WSM","Samoa","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2003/wsm_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
53152,882,"WSM","Samoa","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2003/wsm_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
53153,882,"WSM","Samoa","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2003/wsm_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
53154,882,"WSM","Samoa","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2003/wsm_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
53155,882,"WSM","Samoa","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2003/wsm_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
53156,882,"WSM","Samoa","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2003/wsm_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
53157,882,"WSM","Samoa","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2004/wsm_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
53158,882,"WSM","Samoa","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2004/wsm_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
53159,882,"WSM","Samoa","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2004/wsm_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
53160,882,"WSM","Samoa","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2004/wsm_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
53161,882,"WSM","Samoa","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2004/wsm_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
53162,882,"WSM","Samoa","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2004/wsm_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
53163,882,"WSM","Samoa","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2004/wsm_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
53164,882,"WSM","Samoa","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2004/wsm_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
53165,882,"WSM","Samoa","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2005/wsm_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
53166,882,"WSM","Samoa","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2005/wsm_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
53167,882,"WSM","Samoa","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2005/wsm_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
53168,882,"WSM","Samoa","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2005/wsm_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
53169,882,"WSM","Samoa","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2005/wsm_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
53170,882,"WSM","Samoa","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2005/wsm_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
53171,882,"WSM","Samoa","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2005/wsm_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
53172,882,"WSM","Samoa","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2005/wsm_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
53173,882,"WSM","Samoa","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2006/wsm_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
53174,882,"WSM","Samoa","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2006/wsm_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
53175,882,"WSM","Samoa","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2006/wsm_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
53176,882,"WSM","Samoa","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2006/wsm_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
53177,882,"WSM","Samoa","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2006/wsm_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
53178,882,"WSM","Samoa","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2006/wsm_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
53179,882,"WSM","Samoa","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2006/wsm_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
53180,882,"WSM","Samoa","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2006/wsm_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
53181,882,"WSM","Samoa","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2007/wsm_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
53182,882,"WSM","Samoa","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2007/wsm_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
53183,882,"WSM","Samoa","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2007/wsm_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
53184,882,"WSM","Samoa","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2007/wsm_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
53185,882,"WSM","Samoa","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2007/wsm_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
53186,882,"WSM","Samoa","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2007/wsm_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
53187,882,"WSM","Samoa","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2007/wsm_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
53188,882,"WSM","Samoa","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2007/wsm_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
53189,882,"WSM","Samoa","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2008/wsm_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
53190,882,"WSM","Samoa","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2008/wsm_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
53191,882,"WSM","Samoa","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2008/wsm_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
53192,882,"WSM","Samoa","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2008/wsm_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
53193,882,"WSM","Samoa","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2008/wsm_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
53194,882,"WSM","Samoa","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2008/wsm_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
53195,882,"WSM","Samoa","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2008/wsm_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
53196,882,"WSM","Samoa","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2008/wsm_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
53197,882,"WSM","Samoa","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2009/wsm_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
53198,882,"WSM","Samoa","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2009/wsm_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
53199,882,"WSM","Samoa","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2009/wsm_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
53200,882,"WSM","Samoa","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2009/wsm_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
53201,882,"WSM","Samoa","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2009/wsm_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
53202,882,"WSM","Samoa","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2009/wsm_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
53203,882,"WSM","Samoa","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2009/wsm_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
53204,882,"WSM","Samoa","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2009/wsm_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
53205,882,"WSM","Samoa","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2010/wsm_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
53206,882,"WSM","Samoa","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2010/wsm_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
53207,882,"WSM","Samoa","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2010/wsm_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
53208,882,"WSM","Samoa","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2010/wsm_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
53209,882,"WSM","Samoa","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2010/wsm_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
53210,882,"WSM","Samoa","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2010/wsm_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
53211,882,"WSM","Samoa","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2010/wsm_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
53212,882,"WSM","Samoa","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2010/wsm_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
53213,882,"WSM","Samoa","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2011/wsm_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
53214,882,"WSM","Samoa","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2011/wsm_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
53215,882,"WSM","Samoa","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2011/wsm_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
53216,882,"WSM","Samoa","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2011/wsm_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
53217,882,"WSM","Samoa","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2011/wsm_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
53218,882,"WSM","Samoa","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2011/wsm_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
53219,882,"WSM","Samoa","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2011/wsm_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
53220,882,"WSM","Samoa","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2011/wsm_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
53221,882,"WSM","Samoa","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2012/wsm_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
53222,882,"WSM","Samoa","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2012/wsm_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
53223,882,"WSM","Samoa","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2012/wsm_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
53224,882,"WSM","Samoa","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2012/wsm_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
53225,882,"WSM","Samoa","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2012/wsm_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
53226,882,"WSM","Samoa","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2012/wsm_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
53227,882,"WSM","Samoa","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2012/wsm_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
53228,882,"WSM","Samoa","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2012/wsm_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
53229,882,"WSM","Samoa","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2013/wsm_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
53230,882,"WSM","Samoa","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2013/wsm_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
53231,882,"WSM","Samoa","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2013/wsm_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
53232,882,"WSM","Samoa","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2013/wsm_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
53233,882,"WSM","Samoa","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2013/wsm_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
53234,882,"WSM","Samoa","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2013/wsm_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
53235,882,"WSM","Samoa","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2013/wsm_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
53236,882,"WSM","Samoa","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2013/wsm_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
53237,882,"WSM","Samoa","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2014/wsm_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
53238,882,"WSM","Samoa","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2014/wsm_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
53239,882,"WSM","Samoa","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2014/wsm_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
53240,882,"WSM","Samoa","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2014/wsm_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
53241,882,"WSM","Samoa","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2014/wsm_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
53242,882,"WSM","Samoa","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2014/wsm_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
53243,882,"WSM","Samoa","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2014/wsm_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
53244,882,"WSM","Samoa","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2014/wsm_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
53245,882,"WSM","Samoa","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2015/wsm_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
53246,882,"WSM","Samoa","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2015/wsm_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
53247,882,"WSM","Samoa","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2015/wsm_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
53248,882,"WSM","Samoa","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2015/wsm_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
53249,882,"WSM","Samoa","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2015/wsm_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
53250,882,"WSM","Samoa","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2015/wsm_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
53251,882,"WSM","Samoa","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2015/wsm_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
53252,882,"WSM","Samoa","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Annual/2015/wsm_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
53253,887,"YEM","Yemen","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2000/yem_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
53254,887,"YEM","Yemen","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2000/yem_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
53255,887,"YEM","Yemen","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2000/yem_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
53256,887,"YEM","Yemen","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2000/yem_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
53257,887,"YEM","Yemen","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2000/yem_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
53258,887,"YEM","Yemen","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2000/yem_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
53259,887,"YEM","Yemen","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2000/yem_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
53260,887,"YEM","Yemen","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2000/yem_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
53261,887,"YEM","Yemen","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2001/yem_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
53262,887,"YEM","Yemen","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2001/yem_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
53263,887,"YEM","Yemen","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2001/yem_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
53264,887,"YEM","Yemen","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2001/yem_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
53265,887,"YEM","Yemen","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2001/yem_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
53266,887,"YEM","Yemen","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2001/yem_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
53267,887,"YEM","Yemen","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2001/yem_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
53268,887,"YEM","Yemen","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2001/yem_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
53269,887,"YEM","Yemen","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2002/yem_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
53270,887,"YEM","Yemen","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2002/yem_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
53271,887,"YEM","Yemen","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2002/yem_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
53272,887,"YEM","Yemen","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2002/yem_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
53273,887,"YEM","Yemen","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2002/yem_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
53274,887,"YEM","Yemen","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2002/yem_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
53275,887,"YEM","Yemen","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2002/yem_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
53276,887,"YEM","Yemen","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2002/yem_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
53277,887,"YEM","Yemen","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2003/yem_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
53278,887,"YEM","Yemen","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2003/yem_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
53279,887,"YEM","Yemen","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2003/yem_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
53280,887,"YEM","Yemen","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2003/yem_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
53281,887,"YEM","Yemen","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2003/yem_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
53282,887,"YEM","Yemen","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2003/yem_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
53283,887,"YEM","Yemen","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2003/yem_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
53284,887,"YEM","Yemen","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2003/yem_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
53285,887,"YEM","Yemen","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2004/yem_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
53286,887,"YEM","Yemen","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2004/yem_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
53287,887,"YEM","Yemen","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2004/yem_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
53288,887,"YEM","Yemen","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2004/yem_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
53289,887,"YEM","Yemen","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2004/yem_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
53290,887,"YEM","Yemen","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2004/yem_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
53291,887,"YEM","Yemen","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2004/yem_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
53292,887,"YEM","Yemen","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2004/yem_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
53293,887,"YEM","Yemen","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2005/yem_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
53294,887,"YEM","Yemen","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2005/yem_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
53295,887,"YEM","Yemen","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2005/yem_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
53296,887,"YEM","Yemen","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2005/yem_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
53297,887,"YEM","Yemen","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2005/yem_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
53298,887,"YEM","Yemen","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2005/yem_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
53299,887,"YEM","Yemen","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2005/yem_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
53300,887,"YEM","Yemen","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2005/yem_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
53301,887,"YEM","Yemen","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2006/yem_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
53302,887,"YEM","Yemen","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2006/yem_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
53303,887,"YEM","Yemen","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2006/yem_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
53304,887,"YEM","Yemen","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2006/yem_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
53305,887,"YEM","Yemen","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2006/yem_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
53306,887,"YEM","Yemen","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2006/yem_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
53307,887,"YEM","Yemen","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2006/yem_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
53308,887,"YEM","Yemen","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2006/yem_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
53309,887,"YEM","Yemen","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2007/yem_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
53310,887,"YEM","Yemen","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2007/yem_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
53311,887,"YEM","Yemen","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2007/yem_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
53312,887,"YEM","Yemen","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2007/yem_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
53313,887,"YEM","Yemen","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2007/yem_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
53314,887,"YEM","Yemen","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2007/yem_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
53315,887,"YEM","Yemen","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2007/yem_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
53316,887,"YEM","Yemen","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2007/yem_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
53317,887,"YEM","Yemen","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2008/yem_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
53318,887,"YEM","Yemen","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2008/yem_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
53319,887,"YEM","Yemen","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2008/yem_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
53320,887,"YEM","Yemen","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2008/yem_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
53321,887,"YEM","Yemen","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2008/yem_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
53322,887,"YEM","Yemen","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2008/yem_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
53323,887,"YEM","Yemen","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2008/yem_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
53324,887,"YEM","Yemen","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2008/yem_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
53325,887,"YEM","Yemen","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2009/yem_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
53326,887,"YEM","Yemen","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2009/yem_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
53327,887,"YEM","Yemen","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2009/yem_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
53328,887,"YEM","Yemen","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2009/yem_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
53329,887,"YEM","Yemen","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2009/yem_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
53330,887,"YEM","Yemen","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2009/yem_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
53331,887,"YEM","Yemen","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2009/yem_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
53332,887,"YEM","Yemen","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2009/yem_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
53333,887,"YEM","Yemen","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2010/yem_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
53334,887,"YEM","Yemen","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2010/yem_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
53335,887,"YEM","Yemen","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2010/yem_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
53336,887,"YEM","Yemen","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2010/yem_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
53337,887,"YEM","Yemen","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2010/yem_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
53338,887,"YEM","Yemen","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2010/yem_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
53339,887,"YEM","Yemen","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2010/yem_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
53340,887,"YEM","Yemen","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2010/yem_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
53341,887,"YEM","Yemen","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2011/yem_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
53342,887,"YEM","Yemen","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2011/yem_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
53343,887,"YEM","Yemen","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2011/yem_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
53344,887,"YEM","Yemen","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2011/yem_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
53345,887,"YEM","Yemen","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2011/yem_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
53346,887,"YEM","Yemen","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2011/yem_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
53347,887,"YEM","Yemen","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2011/yem_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
53348,887,"YEM","Yemen","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2011/yem_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
53349,887,"YEM","Yemen","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2012/yem_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
53350,887,"YEM","Yemen","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2012/yem_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
53351,887,"YEM","Yemen","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2012/yem_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
53352,887,"YEM","Yemen","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2012/yem_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
53353,887,"YEM","Yemen","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2012/yem_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
53354,887,"YEM","Yemen","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2012/yem_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
53355,887,"YEM","Yemen","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2012/yem_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
53356,887,"YEM","Yemen","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2012/yem_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
53357,887,"YEM","Yemen","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2013/yem_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
53358,887,"YEM","Yemen","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2013/yem_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
53359,887,"YEM","Yemen","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2013/yem_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
53360,887,"YEM","Yemen","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2013/yem_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
53361,887,"YEM","Yemen","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2013/yem_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
53362,887,"YEM","Yemen","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2013/yem_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
53363,887,"YEM","Yemen","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2013/yem_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
53364,887,"YEM","Yemen","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2013/yem_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
53365,887,"YEM","Yemen","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2014/yem_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
53366,887,"YEM","Yemen","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2014/yem_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
53367,887,"YEM","Yemen","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2014/yem_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
53368,887,"YEM","Yemen","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2014/yem_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
53369,887,"YEM","Yemen","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2014/yem_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
53370,887,"YEM","Yemen","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2014/yem_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
53371,887,"YEM","Yemen","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2014/yem_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
53372,887,"YEM","Yemen","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2014/yem_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
53373,887,"YEM","Yemen","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2015/yem_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
53374,887,"YEM","Yemen","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2015/yem_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
53375,887,"YEM","Yemen","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2015/yem_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
53376,887,"YEM","Yemen","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2015/yem_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
53377,887,"YEM","Yemen","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2015/yem_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
53378,887,"YEM","Yemen","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2015/yem_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
53379,887,"YEM","Yemen","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2015/yem_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
53380,887,"YEM","Yemen","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Annual/2015/yem_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
53381,894,"ZMB","Zambia","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2000/zmb_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
53382,894,"ZMB","Zambia","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2000/zmb_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
53383,894,"ZMB","Zambia","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2000/zmb_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
53384,894,"ZMB","Zambia","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2000/zmb_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
53385,894,"ZMB","Zambia","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2000/zmb_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
53386,894,"ZMB","Zambia","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2000/zmb_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
53387,894,"ZMB","Zambia","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2000/zmb_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
53388,894,"ZMB","Zambia","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2000/zmb_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
53389,894,"ZMB","Zambia","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2001/zmb_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
53390,894,"ZMB","Zambia","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2001/zmb_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
53391,894,"ZMB","Zambia","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2001/zmb_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
53392,894,"ZMB","Zambia","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2001/zmb_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
53393,894,"ZMB","Zambia","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2001/zmb_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
53394,894,"ZMB","Zambia","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2001/zmb_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
53395,894,"ZMB","Zambia","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2001/zmb_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
53396,894,"ZMB","Zambia","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2001/zmb_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
53397,894,"ZMB","Zambia","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2002/zmb_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
53398,894,"ZMB","Zambia","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2002/zmb_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
53399,894,"ZMB","Zambia","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2002/zmb_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
53400,894,"ZMB","Zambia","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2002/zmb_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
53401,894,"ZMB","Zambia","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2002/zmb_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
53402,894,"ZMB","Zambia","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2002/zmb_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
53403,894,"ZMB","Zambia","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2002/zmb_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
53404,894,"ZMB","Zambia","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2002/zmb_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
53405,894,"ZMB","Zambia","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2003/zmb_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
53406,894,"ZMB","Zambia","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2003/zmb_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
53407,894,"ZMB","Zambia","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2003/zmb_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
53408,894,"ZMB","Zambia","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2003/zmb_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
53409,894,"ZMB","Zambia","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2003/zmb_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
53410,894,"ZMB","Zambia","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2003/zmb_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
53411,894,"ZMB","Zambia","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2003/zmb_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
53412,894,"ZMB","Zambia","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2003/zmb_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
53413,894,"ZMB","Zambia","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2004/zmb_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
53414,894,"ZMB","Zambia","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2004/zmb_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
53415,894,"ZMB","Zambia","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2004/zmb_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
53416,894,"ZMB","Zambia","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2004/zmb_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
53417,894,"ZMB","Zambia","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2004/zmb_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
53418,894,"ZMB","Zambia","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2004/zmb_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
53419,894,"ZMB","Zambia","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2004/zmb_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
53420,894,"ZMB","Zambia","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2004/zmb_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
53421,894,"ZMB","Zambia","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2005/zmb_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
53422,894,"ZMB","Zambia","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2005/zmb_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
53423,894,"ZMB","Zambia","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2005/zmb_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
53424,894,"ZMB","Zambia","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2005/zmb_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
53425,894,"ZMB","Zambia","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2005/zmb_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
53426,894,"ZMB","Zambia","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2005/zmb_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
53427,894,"ZMB","Zambia","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2005/zmb_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
53428,894,"ZMB","Zambia","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2005/zmb_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
53429,894,"ZMB","Zambia","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2006/zmb_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
53430,894,"ZMB","Zambia","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2006/zmb_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
53431,894,"ZMB","Zambia","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2006/zmb_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
53432,894,"ZMB","Zambia","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2006/zmb_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
53433,894,"ZMB","Zambia","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2006/zmb_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
53434,894,"ZMB","Zambia","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2006/zmb_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
53435,894,"ZMB","Zambia","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2006/zmb_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
53436,894,"ZMB","Zambia","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2006/zmb_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
53437,894,"ZMB","Zambia","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2007/zmb_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
53438,894,"ZMB","Zambia","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2007/zmb_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
53439,894,"ZMB","Zambia","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2007/zmb_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
53440,894,"ZMB","Zambia","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2007/zmb_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
53441,894,"ZMB","Zambia","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2007/zmb_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
53442,894,"ZMB","Zambia","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2007/zmb_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
53443,894,"ZMB","Zambia","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2007/zmb_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
53444,894,"ZMB","Zambia","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2007/zmb_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
53445,894,"ZMB","Zambia","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2008/zmb_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
53446,894,"ZMB","Zambia","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2008/zmb_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
53447,894,"ZMB","Zambia","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2008/zmb_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
53448,894,"ZMB","Zambia","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2008/zmb_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
53449,894,"ZMB","Zambia","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2008/zmb_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
53450,894,"ZMB","Zambia","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2008/zmb_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
53451,894,"ZMB","Zambia","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2008/zmb_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
53452,894,"ZMB","Zambia","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2008/zmb_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
53453,894,"ZMB","Zambia","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2009/zmb_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
53454,894,"ZMB","Zambia","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2009/zmb_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
53455,894,"ZMB","Zambia","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2009/zmb_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
53456,894,"ZMB","Zambia","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2009/zmb_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
53457,894,"ZMB","Zambia","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2009/zmb_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
53458,894,"ZMB","Zambia","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2009/zmb_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
53459,894,"ZMB","Zambia","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2009/zmb_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
53460,894,"ZMB","Zambia","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2009/zmb_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
53461,894,"ZMB","Zambia","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2010/zmb_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
53462,894,"ZMB","Zambia","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2010/zmb_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
53463,894,"ZMB","Zambia","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2010/zmb_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
53464,894,"ZMB","Zambia","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2010/zmb_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
53465,894,"ZMB","Zambia","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2010/zmb_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
53466,894,"ZMB","Zambia","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2010/zmb_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
53467,894,"ZMB","Zambia","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2010/zmb_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
53468,894,"ZMB","Zambia","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2010/zmb_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
53469,894,"ZMB","Zambia","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2011/zmb_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
53470,894,"ZMB","Zambia","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2011/zmb_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
53471,894,"ZMB","Zambia","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2011/zmb_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
53472,894,"ZMB","Zambia","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2011/zmb_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
53473,894,"ZMB","Zambia","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2011/zmb_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
53474,894,"ZMB","Zambia","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2011/zmb_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
53475,894,"ZMB","Zambia","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2011/zmb_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
53476,894,"ZMB","Zambia","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2011/zmb_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
53477,894,"ZMB","Zambia","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2012/zmb_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
53478,894,"ZMB","Zambia","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2012/zmb_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
53479,894,"ZMB","Zambia","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2012/zmb_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
53480,894,"ZMB","Zambia","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2012/zmb_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
53481,894,"ZMB","Zambia","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2012/zmb_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
53482,894,"ZMB","Zambia","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2012/zmb_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
53483,894,"ZMB","Zambia","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2012/zmb_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
53484,894,"ZMB","Zambia","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2012/zmb_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
53485,894,"ZMB","Zambia","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2013/zmb_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
53486,894,"ZMB","Zambia","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2013/zmb_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
53487,894,"ZMB","Zambia","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2013/zmb_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
53488,894,"ZMB","Zambia","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2013/zmb_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
53489,894,"ZMB","Zambia","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2013/zmb_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
53490,894,"ZMB","Zambia","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2013/zmb_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
53491,894,"ZMB","Zambia","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2013/zmb_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
53492,894,"ZMB","Zambia","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2013/zmb_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
53493,894,"ZMB","Zambia","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2014/zmb_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
53494,894,"ZMB","Zambia","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2014/zmb_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
53495,894,"ZMB","Zambia","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2014/zmb_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
53496,894,"ZMB","Zambia","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2014/zmb_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
53497,894,"ZMB","Zambia","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2014/zmb_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
53498,894,"ZMB","Zambia","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2014/zmb_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
53499,894,"ZMB","Zambia","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2014/zmb_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
53500,894,"ZMB","Zambia","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2014/zmb_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
53501,894,"ZMB","Zambia","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2015/zmb_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
53502,894,"ZMB","Zambia","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2015/zmb_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
53503,894,"ZMB","Zambia","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2015/zmb_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
53504,894,"ZMB","Zambia","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2015/zmb_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
53505,894,"ZMB","Zambia","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2015/zmb_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
53506,894,"ZMB","Zambia","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2015/zmb_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
53507,894,"ZMB","Zambia","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2015/zmb_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
53508,894,"ZMB","Zambia","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Annual/2015/zmb_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
53509,900,"KOS","Kosovo","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2000/kos_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
53510,900,"KOS","Kosovo","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2000/kos_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
53511,900,"KOS","Kosovo","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2000/kos_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
53512,900,"KOS","Kosovo","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2000/kos_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
53513,900,"KOS","Kosovo","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2000/kos_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
53514,900,"KOS","Kosovo","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2000/kos_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
53515,900,"KOS","Kosovo","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2000/kos_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
53516,900,"KOS","Kosovo","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2000/kos_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
53517,900,"KOS","Kosovo","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2001/kos_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
53518,900,"KOS","Kosovo","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2001/kos_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
53519,900,"KOS","Kosovo","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2001/kos_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
53520,900,"KOS","Kosovo","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2001/kos_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
53521,900,"KOS","Kosovo","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2001/kos_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
53522,900,"KOS","Kosovo","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2001/kos_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
53523,900,"KOS","Kosovo","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2001/kos_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
53524,900,"KOS","Kosovo","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2001/kos_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
53525,900,"KOS","Kosovo","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2002/kos_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
53526,900,"KOS","Kosovo","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2002/kos_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
53527,900,"KOS","Kosovo","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2002/kos_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
53528,900,"KOS","Kosovo","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2002/kos_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
53529,900,"KOS","Kosovo","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2002/kos_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
53530,900,"KOS","Kosovo","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2002/kos_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
53531,900,"KOS","Kosovo","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2002/kos_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
53532,900,"KOS","Kosovo","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2002/kos_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
53533,900,"KOS","Kosovo","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2003/kos_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
53534,900,"KOS","Kosovo","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2003/kos_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
53535,900,"KOS","Kosovo","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2003/kos_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
53536,900,"KOS","Kosovo","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2003/kos_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
53537,900,"KOS","Kosovo","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2003/kos_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
53538,900,"KOS","Kosovo","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2003/kos_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
53539,900,"KOS","Kosovo","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2003/kos_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
53540,900,"KOS","Kosovo","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2003/kos_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
53541,900,"KOS","Kosovo","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2004/kos_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
53542,900,"KOS","Kosovo","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2004/kos_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
53543,900,"KOS","Kosovo","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2004/kos_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
53544,900,"KOS","Kosovo","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2004/kos_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
53545,900,"KOS","Kosovo","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2004/kos_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
53546,900,"KOS","Kosovo","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2004/kos_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
53547,900,"KOS","Kosovo","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2004/kos_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
53548,900,"KOS","Kosovo","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2004/kos_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
53549,900,"KOS","Kosovo","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2005/kos_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
53550,900,"KOS","Kosovo","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2005/kos_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
53551,900,"KOS","Kosovo","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2005/kos_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
53552,900,"KOS","Kosovo","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2005/kos_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
53553,900,"KOS","Kosovo","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2005/kos_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
53554,900,"KOS","Kosovo","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2005/kos_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
53555,900,"KOS","Kosovo","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2005/kos_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
53556,900,"KOS","Kosovo","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2005/kos_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
53557,900,"KOS","Kosovo","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2006/kos_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
53558,900,"KOS","Kosovo","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2006/kos_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
53559,900,"KOS","Kosovo","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2006/kos_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
53560,900,"KOS","Kosovo","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2006/kos_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
53561,900,"KOS","Kosovo","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2006/kos_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
53562,900,"KOS","Kosovo","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2006/kos_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
53563,900,"KOS","Kosovo","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2006/kos_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
53564,900,"KOS","Kosovo","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2006/kos_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
53565,900,"KOS","Kosovo","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2007/kos_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
53566,900,"KOS","Kosovo","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2007/kos_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
53567,900,"KOS","Kosovo","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2007/kos_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
53568,900,"KOS","Kosovo","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2007/kos_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
53569,900,"KOS","Kosovo","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2007/kos_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
53570,900,"KOS","Kosovo","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2007/kos_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
53571,900,"KOS","Kosovo","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2007/kos_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
53572,900,"KOS","Kosovo","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2007/kos_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
53573,900,"KOS","Kosovo","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2008/kos_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
53574,900,"KOS","Kosovo","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2008/kos_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
53575,900,"KOS","Kosovo","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2008/kos_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
53576,900,"KOS","Kosovo","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2008/kos_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
53577,900,"KOS","Kosovo","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2008/kos_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
53578,900,"KOS","Kosovo","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2008/kos_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
53579,900,"KOS","Kosovo","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2008/kos_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
53580,900,"KOS","Kosovo","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2008/kos_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
53581,900,"KOS","Kosovo","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2009/kos_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
53582,900,"KOS","Kosovo","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2009/kos_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
53583,900,"KOS","Kosovo","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2009/kos_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
53584,900,"KOS","Kosovo","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2009/kos_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
53585,900,"KOS","Kosovo","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2009/kos_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
53586,900,"KOS","Kosovo","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2009/kos_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
53587,900,"KOS","Kosovo","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2009/kos_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
53588,900,"KOS","Kosovo","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2009/kos_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
53589,900,"KOS","Kosovo","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2010/kos_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
53590,900,"KOS","Kosovo","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2010/kos_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
53591,900,"KOS","Kosovo","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2010/kos_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
53592,900,"KOS","Kosovo","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2010/kos_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
53593,900,"KOS","Kosovo","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2010/kos_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
53594,900,"KOS","Kosovo","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2010/kos_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
53595,900,"KOS","Kosovo","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2010/kos_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
53596,900,"KOS","Kosovo","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2010/kos_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
53597,900,"KOS","Kosovo","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2011/kos_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
53598,900,"KOS","Kosovo","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2011/kos_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
53599,900,"KOS","Kosovo","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2011/kos_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
53600,900,"KOS","Kosovo","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2011/kos_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
53601,900,"KOS","Kosovo","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2011/kos_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
53602,900,"KOS","Kosovo","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2011/kos_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
53603,900,"KOS","Kosovo","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2011/kos_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
53604,900,"KOS","Kosovo","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2011/kos_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
53605,900,"KOS","Kosovo","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2012/kos_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
53606,900,"KOS","Kosovo","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2012/kos_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
53607,900,"KOS","Kosovo","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2012/kos_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
53608,900,"KOS","Kosovo","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2012/kos_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
53609,900,"KOS","Kosovo","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2012/kos_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
53610,900,"KOS","Kosovo","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2012/kos_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
53611,900,"KOS","Kosovo","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2012/kos_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
53612,900,"KOS","Kosovo","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2012/kos_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
53613,900,"KOS","Kosovo","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2013/kos_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
53614,900,"KOS","Kosovo","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2013/kos_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
53615,900,"KOS","Kosovo","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2013/kos_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
53616,900,"KOS","Kosovo","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2013/kos_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
53617,900,"KOS","Kosovo","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2013/kos_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
53618,900,"KOS","Kosovo","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2013/kos_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
53619,900,"KOS","Kosovo","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2013/kos_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
53620,900,"KOS","Kosovo","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2013/kos_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
53621,900,"KOS","Kosovo","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2014/kos_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
53622,900,"KOS","Kosovo","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2014/kos_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
53623,900,"KOS","Kosovo","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2014/kos_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
53624,900,"KOS","Kosovo","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2014/kos_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
53625,900,"KOS","Kosovo","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2014/kos_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
53626,900,"KOS","Kosovo","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2014/kos_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
53627,900,"KOS","Kosovo","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2014/kos_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
53628,900,"KOS","Kosovo","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2014/kos_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
53629,900,"KOS","Kosovo","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2015/kos_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
53630,900,"KOS","Kosovo","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2015/kos_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
53631,900,"KOS","Kosovo","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2015/kos_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
53632,900,"KOS","Kosovo","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2015/kos_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
53633,900,"KOS","Kosovo","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2015/kos_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
53634,900,"KOS","Kosovo","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2015/kos_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
53635,900,"KOS","Kosovo","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2015/kos_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
53636,900,"KOS","Kosovo","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Annual/2015/kos_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
53637,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2000","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2000/spr_esaccilc_dst011_100m_2000.tif","Distance to ESA-CCI-LC cultivated area edges 2000"
53638,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2000","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2000/spr_esaccilc_dst040_100m_2000.tif","Distance to ESA-CCI-LC woody-tree area edges 2000"
53639,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2000","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2000/spr_esaccilc_dst130_100m_2000.tif","Distance to ESA-CCI-LC shrub area edges 2000"
53640,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2000","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2000/spr_esaccilc_dst140_100m_2000.tif","Distance to ESA-CCI-LC herbaceous area edges 2000"
53641,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2000","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2000/spr_esaccilc_dst150_100m_2000.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2000"
53642,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2000","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2000/spr_esaccilc_dst160_100m_2000.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2000"
53643,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2000","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2000/spr_esaccilc_dst190_100m_2000.tif","Distance to ESA-CCI-LC artificial surface edges 2000"
53644,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2000","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2000/spr_esaccilc_dst200_100m_2000.tif","Distance to ESA-CCI-LC bare area edges 2000"
53645,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2001","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2001/spr_esaccilc_dst011_100m_2001.tif","Distance to ESA-CCI-LC cultivated area edges 2001"
53646,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2001","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2001/spr_esaccilc_dst040_100m_2001.tif","Distance to ESA-CCI-LC woody-tree area edges 2001"
53647,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2001","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2001/spr_esaccilc_dst130_100m_2001.tif","Distance to ESA-CCI-LC shrub area edges 2001"
53648,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2001","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2001/spr_esaccilc_dst140_100m_2001.tif","Distance to ESA-CCI-LC herbaceous area edges 2001"
53649,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2001","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2001/spr_esaccilc_dst150_100m_2001.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2001"
53650,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2001","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2001/spr_esaccilc_dst160_100m_2001.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2001"
53651,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2001","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2001/spr_esaccilc_dst190_100m_2001.tif","Distance to ESA-CCI-LC artificial surface edges 2001"
53652,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2001","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2001/spr_esaccilc_dst200_100m_2001.tif","Distance to ESA-CCI-LC bare area edges 2001"
53653,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2002","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2002/spr_esaccilc_dst011_100m_2002.tif","Distance to ESA-CCI-LC cultivated area edges 2002"
53654,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2002","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2002/spr_esaccilc_dst040_100m_2002.tif","Distance to ESA-CCI-LC woody-tree area edges 2002"
53655,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2002","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2002/spr_esaccilc_dst130_100m_2002.tif","Distance to ESA-CCI-LC shrub area edges 2002"
53656,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2002","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2002/spr_esaccilc_dst140_100m_2002.tif","Distance to ESA-CCI-LC herbaceous area edges 2002"
53657,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2002","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2002/spr_esaccilc_dst150_100m_2002.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2002"
53658,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2002","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2002/spr_esaccilc_dst160_100m_2002.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2002"
53659,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2002","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2002/spr_esaccilc_dst190_100m_2002.tif","Distance to ESA-CCI-LC artificial surface edges 2002"
53660,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2002","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2002/spr_esaccilc_dst200_100m_2002.tif","Distance to ESA-CCI-LC bare area edges 2002"
53661,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2003","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2003/spr_esaccilc_dst011_100m_2003.tif","Distance to ESA-CCI-LC cultivated area edges 2003"
53662,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2003","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2003/spr_esaccilc_dst040_100m_2003.tif","Distance to ESA-CCI-LC woody-tree area edges 2003"
53663,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2003","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2003/spr_esaccilc_dst130_100m_2003.tif","Distance to ESA-CCI-LC shrub area edges 2003"
53664,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2003","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2003/spr_esaccilc_dst140_100m_2003.tif","Distance to ESA-CCI-LC herbaceous area edges 2003"
53665,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2003","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2003/spr_esaccilc_dst150_100m_2003.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2003"
53666,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2003","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2003/spr_esaccilc_dst160_100m_2003.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2003"
53667,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2003","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2003/spr_esaccilc_dst190_100m_2003.tif","Distance to ESA-CCI-LC artificial surface edges 2003"
53668,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2003","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2003/spr_esaccilc_dst200_100m_2003.tif","Distance to ESA-CCI-LC bare area edges 2003"
53669,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2004","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2004/spr_esaccilc_dst011_100m_2004.tif","Distance to ESA-CCI-LC cultivated area edges 2004"
53670,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2004","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2004/spr_esaccilc_dst040_100m_2004.tif","Distance to ESA-CCI-LC woody-tree area edges 2004"
53671,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2004","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2004/spr_esaccilc_dst130_100m_2004.tif","Distance to ESA-CCI-LC shrub area edges 2004"
53672,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2004","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2004/spr_esaccilc_dst140_100m_2004.tif","Distance to ESA-CCI-LC herbaceous area edges 2004"
53673,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2004","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2004/spr_esaccilc_dst150_100m_2004.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2004"
53674,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2004","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2004/spr_esaccilc_dst160_100m_2004.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2004"
53675,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2004","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2004/spr_esaccilc_dst190_100m_2004.tif","Distance to ESA-CCI-LC artificial surface edges 2004"
53676,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2004","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2004/spr_esaccilc_dst200_100m_2004.tif","Distance to ESA-CCI-LC bare area edges 2004"
53677,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2005","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2005/spr_esaccilc_dst011_100m_2005.tif","Distance to ESA-CCI-LC cultivated area edges 2005"
53678,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2005","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2005/spr_esaccilc_dst040_100m_2005.tif","Distance to ESA-CCI-LC woody-tree area edges 2005"
53679,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2005","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2005/spr_esaccilc_dst130_100m_2005.tif","Distance to ESA-CCI-LC shrub area edges 2005"
53680,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2005","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2005/spr_esaccilc_dst140_100m_2005.tif","Distance to ESA-CCI-LC herbaceous area edges 2005"
53681,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2005","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2005/spr_esaccilc_dst150_100m_2005.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2005"
53682,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2005","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2005/spr_esaccilc_dst160_100m_2005.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2005"
53683,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2005","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2005/spr_esaccilc_dst190_100m_2005.tif","Distance to ESA-CCI-LC artificial surface edges 2005"
53684,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2005","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2005/spr_esaccilc_dst200_100m_2005.tif","Distance to ESA-CCI-LC bare area edges 2005"
53685,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2006","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2006/spr_esaccilc_dst011_100m_2006.tif","Distance to ESA-CCI-LC cultivated area edges 2006"
53686,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2006","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2006/spr_esaccilc_dst040_100m_2006.tif","Distance to ESA-CCI-LC woody-tree area edges 2006"
53687,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2006","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2006/spr_esaccilc_dst130_100m_2006.tif","Distance to ESA-CCI-LC shrub area edges 2006"
53688,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2006","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2006/spr_esaccilc_dst140_100m_2006.tif","Distance to ESA-CCI-LC herbaceous area edges 2006"
53689,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2006","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2006/spr_esaccilc_dst150_100m_2006.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2006"
53690,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2006","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2006/spr_esaccilc_dst160_100m_2006.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2006"
53691,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2006","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2006/spr_esaccilc_dst190_100m_2006.tif","Distance to ESA-CCI-LC artificial surface edges 2006"
53692,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2006","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2006/spr_esaccilc_dst200_100m_2006.tif","Distance to ESA-CCI-LC bare area edges 2006"
53693,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2007","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2007/spr_esaccilc_dst011_100m_2007.tif","Distance to ESA-CCI-LC cultivated area edges 2007"
53694,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2007","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2007/spr_esaccilc_dst040_100m_2007.tif","Distance to ESA-CCI-LC woody-tree area edges 2007"
53695,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2007","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2007/spr_esaccilc_dst130_100m_2007.tif","Distance to ESA-CCI-LC shrub area edges 2007"
53696,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2007","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2007/spr_esaccilc_dst140_100m_2007.tif","Distance to ESA-CCI-LC herbaceous area edges 2007"
53697,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2007","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2007/spr_esaccilc_dst150_100m_2007.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2007"
53698,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2007","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2007/spr_esaccilc_dst160_100m_2007.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2007"
53699,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2007","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2007/spr_esaccilc_dst190_100m_2007.tif","Distance to ESA-CCI-LC artificial surface edges 2007"
53700,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2007","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2007/spr_esaccilc_dst200_100m_2007.tif","Distance to ESA-CCI-LC bare area edges 2007"
53701,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2008","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2008/spr_esaccilc_dst011_100m_2008.tif","Distance to ESA-CCI-LC cultivated area edges 2008"
53702,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2008","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2008/spr_esaccilc_dst040_100m_2008.tif","Distance to ESA-CCI-LC woody-tree area edges 2008"
53703,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2008","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2008/spr_esaccilc_dst130_100m_2008.tif","Distance to ESA-CCI-LC shrub area edges 2008"
53704,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2008","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2008/spr_esaccilc_dst140_100m_2008.tif","Distance to ESA-CCI-LC herbaceous area edges 2008"
53705,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2008","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2008/spr_esaccilc_dst150_100m_2008.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2008"
53706,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2008","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2008/spr_esaccilc_dst160_100m_2008.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2008"
53707,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2008","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2008/spr_esaccilc_dst190_100m_2008.tif","Distance to ESA-CCI-LC artificial surface edges 2008"
53708,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2008","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2008/spr_esaccilc_dst200_100m_2008.tif","Distance to ESA-CCI-LC bare area edges 2008"
53709,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2009","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2009/spr_esaccilc_dst011_100m_2009.tif","Distance to ESA-CCI-LC cultivated area edges 2009"
53710,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2009","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2009/spr_esaccilc_dst040_100m_2009.tif","Distance to ESA-CCI-LC woody-tree area edges 2009"
53711,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2009","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2009/spr_esaccilc_dst130_100m_2009.tif","Distance to ESA-CCI-LC shrub area edges 2009"
53712,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2009","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2009/spr_esaccilc_dst140_100m_2009.tif","Distance to ESA-CCI-LC herbaceous area edges 2009"
53713,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2009","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2009/spr_esaccilc_dst150_100m_2009.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2009"
53714,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2009","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2009/spr_esaccilc_dst160_100m_2009.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2009"
53715,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2009","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2009/spr_esaccilc_dst190_100m_2009.tif","Distance to ESA-CCI-LC artificial surface edges 2009"
53716,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2009","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2009/spr_esaccilc_dst200_100m_2009.tif","Distance to ESA-CCI-LC bare area edges 2009"
53717,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2010","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2010/spr_esaccilc_dst011_100m_2010.tif","Distance to ESA-CCI-LC cultivated area edges 2010"
53718,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2010","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2010/spr_esaccilc_dst040_100m_2010.tif","Distance to ESA-CCI-LC woody-tree area edges 2010"
53719,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2010","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2010/spr_esaccilc_dst130_100m_2010.tif","Distance to ESA-CCI-LC shrub area edges 2010"
53720,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2010","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2010/spr_esaccilc_dst140_100m_2010.tif","Distance to ESA-CCI-LC herbaceous area edges 2010"
53721,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2010","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2010/spr_esaccilc_dst150_100m_2010.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2010"
53722,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2010","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2010/spr_esaccilc_dst160_100m_2010.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2010"
53723,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2010","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2010/spr_esaccilc_dst190_100m_2010.tif","Distance to ESA-CCI-LC artificial surface edges 2010"
53724,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2010","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2010/spr_esaccilc_dst200_100m_2010.tif","Distance to ESA-CCI-LC bare area edges 2010"
53725,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2011","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2011/spr_esaccilc_dst011_100m_2011.tif","Distance to ESA-CCI-LC cultivated area edges 2011"
53726,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2011","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2011/spr_esaccilc_dst040_100m_2011.tif","Distance to ESA-CCI-LC woody-tree area edges 2011"
53727,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2011","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2011/spr_esaccilc_dst130_100m_2011.tif","Distance to ESA-CCI-LC shrub area edges 2011"
53728,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2011","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2011/spr_esaccilc_dst140_100m_2011.tif","Distance to ESA-CCI-LC herbaceous area edges 2011"
53729,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2011","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2011/spr_esaccilc_dst150_100m_2011.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2011"
53730,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2011","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2011/spr_esaccilc_dst160_100m_2011.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2011"
53731,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2011","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2011/spr_esaccilc_dst190_100m_2011.tif","Distance to ESA-CCI-LC artificial surface edges 2011"
53732,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2011","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2011/spr_esaccilc_dst200_100m_2011.tif","Distance to ESA-CCI-LC bare area edges 2011"
53733,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2012","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2012/spr_esaccilc_dst011_100m_2012.tif","Distance to ESA-CCI-LC cultivated area edges 2012"
53734,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2012","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2012/spr_esaccilc_dst040_100m_2012.tif","Distance to ESA-CCI-LC woody-tree area edges 2012"
53735,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2012","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2012/spr_esaccilc_dst130_100m_2012.tif","Distance to ESA-CCI-LC shrub area edges 2012"
53736,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2012","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2012/spr_esaccilc_dst140_100m_2012.tif","Distance to ESA-CCI-LC herbaceous area edges 2012"
53737,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2012","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2012/spr_esaccilc_dst150_100m_2012.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2012"
53738,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2012","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2012/spr_esaccilc_dst160_100m_2012.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2012"
53739,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2012","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2012/spr_esaccilc_dst190_100m_2012.tif","Distance to ESA-CCI-LC artificial surface edges 2012"
53740,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2012","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2012/spr_esaccilc_dst200_100m_2012.tif","Distance to ESA-CCI-LC bare area edges 2012"
53741,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2013","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2013/spr_esaccilc_dst011_100m_2013.tif","Distance to ESA-CCI-LC cultivated area edges 2013"
53742,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2013","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2013/spr_esaccilc_dst040_100m_2013.tif","Distance to ESA-CCI-LC woody-tree area edges 2013"
53743,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2013","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2013/spr_esaccilc_dst130_100m_2013.tif","Distance to ESA-CCI-LC shrub area edges 2013"
53744,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2013","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2013/spr_esaccilc_dst140_100m_2013.tif","Distance to ESA-CCI-LC herbaceous area edges 2013"
53745,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2013","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2013/spr_esaccilc_dst150_100m_2013.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2013"
53746,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2013","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2013/spr_esaccilc_dst160_100m_2013.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2013"
53747,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2013","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2013/spr_esaccilc_dst190_100m_2013.tif","Distance to ESA-CCI-LC artificial surface edges 2013"
53748,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2013","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2013/spr_esaccilc_dst200_100m_2013.tif","Distance to ESA-CCI-LC bare area edges 2013"
53749,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2014","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2014/spr_esaccilc_dst011_100m_2014.tif","Distance to ESA-CCI-LC cultivated area edges 2014"
53750,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2014","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2014/spr_esaccilc_dst040_100m_2014.tif","Distance to ESA-CCI-LC woody-tree area edges 2014"
53751,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2014","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2014/spr_esaccilc_dst130_100m_2014.tif","Distance to ESA-CCI-LC shrub area edges 2014"
53752,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2014","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2014/spr_esaccilc_dst140_100m_2014.tif","Distance to ESA-CCI-LC herbaceous area edges 2014"
53753,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2014","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2014/spr_esaccilc_dst150_100m_2014.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2014"
53754,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2014","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2014/spr_esaccilc_dst160_100m_2014.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2014"
53755,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2014","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2014/spr_esaccilc_dst190_100m_2014.tif","Distance to ESA-CCI-LC artificial surface edges 2014"
53756,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2014","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2014/spr_esaccilc_dst200_100m_2014.tif","Distance to ESA-CCI-LC bare area edges 2014"
53757,901,"SPR","Spratly Islands","esaccilc_dst011_100m_2015","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2015/spr_esaccilc_dst011_100m_2015.tif","Distance to ESA-CCI-LC cultivated area edges 2015"
53758,901,"SPR","Spratly Islands","esaccilc_dst040_100m_2015","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2015/spr_esaccilc_dst040_100m_2015.tif","Distance to ESA-CCI-LC woody-tree area edges 2015"
53759,901,"SPR","Spratly Islands","esaccilc_dst130_100m_2015","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2015/spr_esaccilc_dst130_100m_2015.tif","Distance to ESA-CCI-LC shrub area edges 2015"
53760,901,"SPR","Spratly Islands","esaccilc_dst140_100m_2015","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2015/spr_esaccilc_dst140_100m_2015.tif","Distance to ESA-CCI-LC herbaceous area edges 2015"
53761,901,"SPR","Spratly Islands","esaccilc_dst150_100m_2015","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2015/spr_esaccilc_dst150_100m_2015.tif","Distance to  ESA-CCI-LC sparse vegetation area edges 2015"
53762,901,"SPR","Spratly Islands","esaccilc_dst160_100m_2015","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2015/spr_esaccilc_dst160_100m_2015.tif","Distance to  ESA-CCI-LC aquatic vegetation area edges 2015"
53763,901,"SPR","Spratly Islands","esaccilc_dst190_100m_2015","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2015/spr_esaccilc_dst190_100m_2015.tif","Distance to ESA-CCI-LC artificial surface edges 2015"
53764,901,"SPR","Spratly Islands","esaccilc_dst200_100m_2015","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Annual/2015/spr_esaccilc_dst200_100m_2015.tif","Distance to ESA-CCI-LC bare area edges 2015"
53765,643,"RUS","Russia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Water/Binary/rus_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53766,643,"RUS","Russia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/RUS/ESA_CCI_Water/DST/rus_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53767,360,"IDN","Indonesia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Water/Binary/idn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53768,360,"IDN","Indonesia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IDN/ESA_CCI_Water/DST/idn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53769,840,"USA","United States","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Water/Binary/usa_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53770,840,"USA","United States","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/USA/ESA_CCI_Water/DST/usa_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53771,850,"VIR","Virgin_Islands_U_S","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Water/Binary/vir_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53772,850,"VIR","Virgin_Islands_U_S","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VIR/ESA_CCI_Water/DST/vir_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53773,304,"GRL","Greenland","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Water/Binary/grl_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53774,304,"GRL","Greenland","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GRL/ESA_CCI_Water/DST/grl_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53775,156,"CHN","China","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Water/Binary/chn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53776,156,"CHN","China","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CHN/ESA_CCI_Water/DST/chn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53777,36,"AUS","Australia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Water/Binary/aus_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53778,36,"AUS","Australia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AUS/ESA_CCI_Water/DST/aus_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53779,76,"BRA","Brazil","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Water/Binary/bra_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53780,76,"BRA","Brazil","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BRA/ESA_CCI_Water/DST/bra_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53781,124,"CAN","Canada","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Water/Binary/can_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53782,124,"CAN","Canada","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CAN/ESA_CCI_Water/DST/can_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53783,152,"CHL","Chile","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Water/Binary/chl_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53784,152,"CHL","Chile","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CHL/ESA_CCI_Water/DST/chl_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53785,4,"AFG","Afghanistan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Water/Binary/afg_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53786,4,"AFG","Afghanistan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AFG/ESA_CCI_Water/DST/afg_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53787,8,"ALB","Albania","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Water/Binary/alb_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53788,8,"ALB","Albania","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ALB/ESA_CCI_Water/DST/alb_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53789,10,"ATA","Antarctica","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Water/Binary/ata_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53790,10,"ATA","Antarctica","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ATA/ESA_CCI_Water/DST/ata_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53791,12,"DZA","Algeria","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Water/Binary/dza_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53792,12,"DZA","Algeria","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DZA/ESA_CCI_Water/DST/dza_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53793,16,"ASM","American Samoa","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Water/Binary/asm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53794,16,"ASM","American Samoa","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ASM/ESA_CCI_Water/DST/asm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53795,20,"AND","Andorra","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Water/Binary/and_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53796,20,"AND","Andorra","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AND/ESA_CCI_Water/DST/and_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53797,24,"AGO","Angola","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Water/Binary/ago_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53798,24,"AGO","Angola","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AGO/ESA_CCI_Water/DST/ago_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53799,28,"ATG","Antigua and Barbuda","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Water/Binary/atg_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53800,28,"ATG","Antigua and Barbuda","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ATG/ESA_CCI_Water/DST/atg_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53801,31,"AZE","Azerbaijan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Water/Binary/aze_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53802,31,"AZE","Azerbaijan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AZE/ESA_CCI_Water/DST/aze_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53803,32,"ARG","Argentina","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Water/Binary/arg_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53804,32,"ARG","Argentina","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ARG/ESA_CCI_Water/DST/arg_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53805,40,"AUT","Austria","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Water/Binary/aut_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53806,40,"AUT","Austria","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AUT/ESA_CCI_Water/DST/aut_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53807,44,"BHS","Bahamas","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Water/Binary/bhs_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53808,44,"BHS","Bahamas","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BHS/ESA_CCI_Water/DST/bhs_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53809,48,"BHR","Bahrain","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Water/Binary/bhr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53810,48,"BHR","Bahrain","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BHR/ESA_CCI_Water/DST/bhr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53811,50,"BGD","Bangladesh","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Water/Binary/bgd_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53812,50,"BGD","Bangladesh","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BGD/ESA_CCI_Water/DST/bgd_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53813,51,"ARM","Armenia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Water/Binary/arm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53814,51,"ARM","Armenia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ARM/ESA_CCI_Water/DST/arm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53815,52,"BRB","Barbados","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Water/Binary/brb_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53816,52,"BRB","Barbados","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BRB/ESA_CCI_Water/DST/brb_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53817,56,"BEL","Belgium","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Water/Binary/bel_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53818,56,"BEL","Belgium","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BEL/ESA_CCI_Water/DST/bel_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53819,60,"BMU","Bermuda","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Water/Binary/bmu_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53820,60,"BMU","Bermuda","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BMU/ESA_CCI_Water/DST/bmu_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53821,64,"BTN","Bhutan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Water/Binary/btn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53822,64,"BTN","Bhutan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BTN/ESA_CCI_Water/DST/btn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53823,68,"BOL","Bolivia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Water/Binary/bol_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53824,68,"BOL","Bolivia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BOL/ESA_CCI_Water/DST/bol_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53825,70,"BIH","Bosnia and Herzegovina","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Water/Binary/bih_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53826,70,"BIH","Bosnia and Herzegovina","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BIH/ESA_CCI_Water/DST/bih_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53827,72,"BWA","Botswana","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Water/Binary/bwa_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53828,72,"BWA","Botswana","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BWA/ESA_CCI_Water/DST/bwa_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53829,74,"BVT","Bouvet Island","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Water/Binary/bvt_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53830,74,"BVT","Bouvet Island","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BVT/ESA_CCI_Water/DST/bvt_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53831,84,"BLZ","Belize","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Water/Binary/blz_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53832,84,"BLZ","Belize","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BLZ/ESA_CCI_Water/DST/blz_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53833,86,"IOT","British Indian Ocean Territory","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Water/Binary/iot_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53834,86,"IOT","British Indian Ocean Territory","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IOT/ESA_CCI_Water/DST/iot_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53835,90,"SLB","Solomon Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Water/Binary/slb_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53836,90,"SLB","Solomon Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SLB/ESA_CCI_Water/DST/slb_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53837,92,"VGB","British Virgin Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Water/Binary/vgb_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53838,92,"VGB","British Virgin Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VGB/ESA_CCI_Water/DST/vgb_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53839,96,"BRN","Brunei","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Water/Binary/brn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53840,96,"BRN","Brunei","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BRN/ESA_CCI_Water/DST/brn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53841,100,"BGR","Bulgaria","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Water/Binary/bgr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53842,100,"BGR","Bulgaria","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BGR/ESA_CCI_Water/DST/bgr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53843,104,"MMR","Myanmar","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Water/Binary/mmr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53844,104,"MMR","Myanmar","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MMR/ESA_CCI_Water/DST/mmr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53845,108,"BDI","Burundi","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Water/Binary/bdi_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53846,108,"BDI","Burundi","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BDI/ESA_CCI_Water/DST/bdi_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53847,112,"BLR","Belarus","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Water/Binary/blr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53848,112,"BLR","Belarus","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BLR/ESA_CCI_Water/DST/blr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53849,116,"KHM","Cambodia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Water/Binary/khm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53850,116,"KHM","Cambodia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KHM/ESA_CCI_Water/DST/khm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53851,120,"CMR","Cameroon","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Water/Binary/cmr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53852,120,"CMR","Cameroon","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CMR/ESA_CCI_Water/DST/cmr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53853,132,"CPV","Cape Verde","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Water/Binary/cpv_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53854,132,"CPV","Cape Verde","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CPV/ESA_CCI_Water/DST/cpv_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53855,136,"CYM","Cayman Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Water/Binary/cym_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53856,136,"CYM","Cayman Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CYM/ESA_CCI_Water/DST/cym_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53857,140,"CAF","Central African Republic","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Water/Binary/caf_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53858,140,"CAF","Central African Republic","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CAF/ESA_CCI_Water/DST/caf_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53859,144,"LKA","Sri Lanka","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Water/Binary/lka_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53860,144,"LKA","Sri Lanka","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LKA/ESA_CCI_Water/DST/lka_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53861,148,"TCD","Chad","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Water/Binary/tcd_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53862,148,"TCD","Chad","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TCD/ESA_CCI_Water/DST/tcd_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53863,158,"TWN","Taiwan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Water/Binary/twn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53864,158,"TWN","Taiwan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TWN/ESA_CCI_Water/DST/twn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53865,170,"COL","Colombia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Water/Binary/col_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53866,170,"COL","Colombia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/COL/ESA_CCI_Water/DST/col_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53867,174,"COM","Comoros","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Water/Binary/com_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53868,174,"COM","Comoros","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/COM/ESA_CCI_Water/DST/com_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53869,175,"MYT","Mayotte","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Water/Binary/myt_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53870,175,"MYT","Mayotte","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MYT/ESA_CCI_Water/DST/myt_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53871,178,"COG","Republic of Congo","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Water/Binary/cog_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53872,178,"COG","Republic of Congo","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/COG/ESA_CCI_Water/DST/cog_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53873,180,"COD","Democratic Republic of the Congo","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Water/Binary/cod_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53874,180,"COD","Democratic Republic of the Congo","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/COD/ESA_CCI_Water/DST/cod_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53875,184,"COK","Cook Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Water/Binary/cok_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53876,184,"COK","Cook Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/COK/ESA_CCI_Water/DST/cok_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53877,188,"CRI","Costa Rica","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Water/Binary/cri_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53878,188,"CRI","Costa Rica","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CRI/ESA_CCI_Water/DST/cri_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53879,191,"HRV","Croatia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Water/Binary/hrv_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53880,191,"HRV","Croatia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HRV/ESA_CCI_Water/DST/hrv_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53881,192,"CUB","Cuba","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Water/Binary/cub_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53882,192,"CUB","Cuba","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CUB/ESA_CCI_Water/DST/cub_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53883,196,"CYP","Cyprus","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Water/Binary/cyp_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53884,196,"CYP","Cyprus","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CYP/ESA_CCI_Water/DST/cyp_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53885,203,"CZE","Czech Republic","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Water/Binary/cze_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53886,203,"CZE","Czech Republic","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CZE/ESA_CCI_Water/DST/cze_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53887,204,"BEN","Benin","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Water/Binary/ben_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53888,204,"BEN","Benin","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BEN/ESA_CCI_Water/DST/ben_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53889,208,"DNK","Denmark","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Water/Binary/dnk_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53890,208,"DNK","Denmark","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DNK/ESA_CCI_Water/DST/dnk_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53891,212,"DMA","Dominica","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Water/Binary/dma_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53892,212,"DMA","Dominica","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DMA/ESA_CCI_Water/DST/dma_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53893,214,"DOM","Dominican Republic","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Water/Binary/dom_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53894,214,"DOM","Dominican Republic","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DOM/ESA_CCI_Water/DST/dom_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53895,218,"ECU","Ecuador","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Water/Binary/ecu_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53896,218,"ECU","Ecuador","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ECU/ESA_CCI_Water/DST/ecu_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53897,222,"SLV","El Salvador","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Water/Binary/slv_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53898,222,"SLV","El Salvador","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SLV/ESA_CCI_Water/DST/slv_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53899,226,"GNQ","Equatorial Guinea","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Water/Binary/gnq_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53900,226,"GNQ","Equatorial Guinea","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GNQ/ESA_CCI_Water/DST/gnq_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53901,231,"ETH","Ethiopia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Water/Binary/eth_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53902,231,"ETH","Ethiopia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ETH/ESA_CCI_Water/DST/eth_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53903,232,"ERI","Eritrea","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Water/Binary/eri_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53904,232,"ERI","Eritrea","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ERI/ESA_CCI_Water/DST/eri_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53905,233,"EST","Estonia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Water/Binary/est_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53906,233,"EST","Estonia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/EST/ESA_CCI_Water/DST/est_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53907,234,"FRO","Faroe Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Water/Binary/fro_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53908,234,"FRO","Faroe Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FRO/ESA_CCI_Water/DST/fro_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53909,238,"FLK","Falkland Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Water/Binary/flk_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53910,238,"FLK","Falkland Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FLK/ESA_CCI_Water/DST/flk_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53911,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Water/Binary/sgs_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53912,239,"SGS","South Georgia and the South Sandwich Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SGS/ESA_CCI_Water/DST/sgs_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53913,242,"FJI","Fiji","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Water/Binary/fji_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53914,242,"FJI","Fiji","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FJI/ESA_CCI_Water/DST/fji_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53915,246,"FIN","Finland","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Water/Binary/fin_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53916,246,"FIN","Finland","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FIN/ESA_CCI_Water/DST/fin_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53917,248,"ALA","Aland Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Water/Binary/ala_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53918,248,"ALA","Aland Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ALA/ESA_CCI_Water/DST/ala_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53919,250,"FRA","France","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Water/Binary/fra_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53920,250,"FRA","France","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FRA/ESA_CCI_Water/DST/fra_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53921,254,"GUF","French Guiana","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Water/Binary/guf_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53922,254,"GUF","French Guiana","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GUF/ESA_CCI_Water/DST/guf_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53923,258,"PYF","French Polynesia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Water/Binary/pyf_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53924,258,"PYF","French Polynesia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PYF/ESA_CCI_Water/DST/pyf_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53925,260,"ATF","French Southern Territories","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Water/Binary/atf_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53926,260,"ATF","French Southern Territories","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ATF/ESA_CCI_Water/DST/atf_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53927,262,"DJI","Djibouti","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Water/Binary/dji_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53928,262,"DJI","Djibouti","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DJI/ESA_CCI_Water/DST/dji_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53929,266,"GAB","Gabon","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Water/Binary/gab_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53930,266,"GAB","Gabon","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GAB/ESA_CCI_Water/DST/gab_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53931,268,"GEO","Georgia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Water/Binary/geo_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53932,268,"GEO","Georgia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GEO/ESA_CCI_Water/DST/geo_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53933,270,"GMB","Gambia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Water/Binary/gmb_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53934,270,"GMB","Gambia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GMB/ESA_CCI_Water/DST/gmb_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53935,275,"PSE","Palestina","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Water/Binary/pse_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53936,275,"PSE","Palestina","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PSE/ESA_CCI_Water/DST/pse_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53937,276,"DEU","Germany","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Water/Binary/deu_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53938,276,"DEU","Germany","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/DEU/ESA_CCI_Water/DST/deu_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53939,288,"GHA","Ghana","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Water/Binary/gha_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53940,288,"GHA","Ghana","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GHA/ESA_CCI_Water/DST/gha_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53941,292,"GIB","Gibraltar","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Water/Binary/gib_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53942,292,"GIB","Gibraltar","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GIB/ESA_CCI_Water/DST/gib_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53943,296,"KIR","Kiribati","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Water/Binary/kir_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53944,296,"KIR","Kiribati","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KIR/ESA_CCI_Water/DST/kir_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53945,300,"GRC","Greece","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Water/Binary/grc_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53946,300,"GRC","Greece","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GRC/ESA_CCI_Water/DST/grc_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53947,308,"GRD","Grenada","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Water/Binary/grd_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53948,308,"GRD","Grenada","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GRD/ESA_CCI_Water/DST/grd_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53949,312,"GLP","Guadeloupe","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Water/Binary/glp_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53950,312,"GLP","Guadeloupe","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GLP/ESA_CCI_Water/DST/glp_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53951,316,"GUM","Guam","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Water/Binary/gum_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53952,316,"GUM","Guam","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GUM/ESA_CCI_Water/DST/gum_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53953,320,"GTM","Guatemala","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Water/Binary/gtm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53954,320,"GTM","Guatemala","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GTM/ESA_CCI_Water/DST/gtm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53955,324,"GIN","Guinea","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Water/Binary/gin_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53956,324,"GIN","Guinea","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GIN/ESA_CCI_Water/DST/gin_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53957,328,"GUY","Guyana","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Water/Binary/guy_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53958,328,"GUY","Guyana","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GUY/ESA_CCI_Water/DST/guy_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53959,332,"HTI","Haiti","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Water/Binary/hti_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53960,332,"HTI","Haiti","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HTI/ESA_CCI_Water/DST/hti_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53961,334,"HMD","Heard Island and McDonald Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Water/Binary/hmd_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53962,334,"HMD","Heard Island and McDonald Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HMD/ESA_CCI_Water/DST/hmd_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53963,336,"VAT","Vatican City","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Water/Binary/vat_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53964,336,"VAT","Vatican City","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VAT/ESA_CCI_Water/DST/vat_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53965,340,"HND","Honduras","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Water/Binary/hnd_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53966,340,"HND","Honduras","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HND/ESA_CCI_Water/DST/hnd_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53967,344,"HKG","Hong Kong","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Water/Binary/hkg_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53968,344,"HKG","Hong Kong","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HKG/ESA_CCI_Water/DST/hkg_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53969,348,"HUN","Hungary","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Water/Binary/hun_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53970,348,"HUN","Hungary","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/HUN/ESA_CCI_Water/DST/hun_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53971,352,"ISL","Iceland","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Water/Binary/isl_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53972,352,"ISL","Iceland","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ISL/ESA_CCI_Water/DST/isl_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53973,356,"IND","India","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Water/Binary/ind_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53974,356,"IND","India","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IND/ESA_CCI_Water/DST/ind_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53975,364,"IRN","Iran","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Water/Binary/irn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53976,364,"IRN","Iran","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IRN/ESA_CCI_Water/DST/irn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53977,368,"IRQ","Iraq","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Water/Binary/irq_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53978,368,"IRQ","Iraq","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IRQ/ESA_CCI_Water/DST/irq_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53979,372,"IRL","Ireland","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Water/Binary/irl_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53980,372,"IRL","Ireland","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IRL/ESA_CCI_Water/DST/irl_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53981,376,"ISR","Israel","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Water/Binary/isr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53982,376,"ISR","Israel","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ISR/ESA_CCI_Water/DST/isr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53983,380,"ITA","Italy","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Water/Binary/ita_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53984,380,"ITA","Italy","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ITA/ESA_CCI_Water/DST/ita_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53985,384,"CIV","CIte dIvoire","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Water/Binary/civ_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53986,384,"CIV","CIte dIvoire","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CIV/ESA_CCI_Water/DST/civ_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53987,388,"JAM","Jamaica","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Water/Binary/jam_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53988,388,"JAM","Jamaica","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/JAM/ESA_CCI_Water/DST/jam_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53989,392,"JPN","Japan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Water/Binary/jpn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53990,392,"JPN","Japan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/JPN/ESA_CCI_Water/DST/jpn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53991,398,"KAZ","Kazakhstan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Water/Binary/kaz_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53992,398,"KAZ","Kazakhstan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KAZ/ESA_CCI_Water/DST/kaz_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53993,400,"JOR","Jordan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Water/Binary/jor_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53994,400,"JOR","Jordan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/JOR/ESA_CCI_Water/DST/jor_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53995,404,"KEN","Kenya","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Water/Binary/ken_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53996,404,"KEN","Kenya","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KEN/ESA_CCI_Water/DST/ken_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53997,408,"PRK","North Korea","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Water/Binary/prk_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
53998,408,"PRK","North Korea","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PRK/ESA_CCI_Water/DST/prk_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
53999,410,"KOR","South Korea","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Water/Binary/kor_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54000,410,"KOR","South Korea","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KOR/ESA_CCI_Water/DST/kor_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54001,414,"KWT","Kuwait","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Water/Binary/kwt_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54002,414,"KWT","Kuwait","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KWT/ESA_CCI_Water/DST/kwt_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54003,417,"KGZ","Kyrgyzstan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Water/Binary/kgz_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54004,417,"KGZ","Kyrgyzstan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KGZ/ESA_CCI_Water/DST/kgz_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54005,418,"LAO","Laos","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Water/Binary/lao_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54006,418,"LAO","Laos","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LAO/ESA_CCI_Water/DST/lao_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54007,422,"LBN","Lebanon","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Water/Binary/lbn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54008,422,"LBN","Lebanon","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LBN/ESA_CCI_Water/DST/lbn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54009,426,"LSO","Lesotho","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Water/Binary/lso_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54010,426,"LSO","Lesotho","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LSO/ESA_CCI_Water/DST/lso_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54011,428,"LVA","Latvia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Water/Binary/lva_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54012,428,"LVA","Latvia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LVA/ESA_CCI_Water/DST/lva_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54013,430,"LBR","Liberia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Water/Binary/lbr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54014,430,"LBR","Liberia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LBR/ESA_CCI_Water/DST/lbr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54015,434,"LBY","Libya","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Water/Binary/lby_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54016,434,"LBY","Libya","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LBY/ESA_CCI_Water/DST/lby_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54017,438,"LIE","Liechtenstein","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Water/Binary/lie_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54018,438,"LIE","Liechtenstein","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LIE/ESA_CCI_Water/DST/lie_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54019,440,"LTU","Lithuania","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Water/Binary/ltu_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54020,440,"LTU","Lithuania","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LTU/ESA_CCI_Water/DST/ltu_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54021,442,"LUX","Luxembourg","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Water/Binary/lux_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54022,442,"LUX","Luxembourg","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LUX/ESA_CCI_Water/DST/lux_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54023,446,"MAC","Macao","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Water/Binary/mac_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54024,446,"MAC","Macao","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MAC/ESA_CCI_Water/DST/mac_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54025,450,"MDG","Madagascar","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Water/Binary/mdg_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54026,450,"MDG","Madagascar","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MDG/ESA_CCI_Water/DST/mdg_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54027,454,"MWI","Malawi","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Water/Binary/mwi_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54028,454,"MWI","Malawi","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MWI/ESA_CCI_Water/DST/mwi_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54029,458,"MYS","Malaysia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Water/Binary/mys_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54030,458,"MYS","Malaysia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MYS/ESA_CCI_Water/DST/mys_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54031,462,"MDV","Maldives","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Water/Binary/mdv_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54032,462,"MDV","Maldives","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MDV/ESA_CCI_Water/DST/mdv_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54033,466,"MLI","Mali","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Water/Binary/mli_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54034,466,"MLI","Mali","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MLI/ESA_CCI_Water/DST/mli_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54035,470,"MLT","Malta","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Water/Binary/mlt_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54036,470,"MLT","Malta","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MLT/ESA_CCI_Water/DST/mlt_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54037,474,"MTQ","Martinique","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Water/Binary/mtq_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54038,474,"MTQ","Martinique","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MTQ/ESA_CCI_Water/DST/mtq_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54039,478,"MRT","Mauritania","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Water/Binary/mrt_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54040,478,"MRT","Mauritania","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MRT/ESA_CCI_Water/DST/mrt_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54041,480,"MUS","Mauritius","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Water/Binary/mus_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54042,480,"MUS","Mauritius","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MUS/ESA_CCI_Water/DST/mus_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54043,484,"MEX","Mexico","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Water/Binary/mex_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54044,484,"MEX","Mexico","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MEX/ESA_CCI_Water/DST/mex_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54045,492,"MCO","Monaco","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Water/Binary/mco_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54046,492,"MCO","Monaco","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MCO/ESA_CCI_Water/DST/mco_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54047,496,"MNG","Mongolia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Water/Binary/mng_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54048,496,"MNG","Mongolia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MNG/ESA_CCI_Water/DST/mng_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54049,498,"MDA","Moldova","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Water/Binary/mda_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54050,498,"MDA","Moldova","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MDA/ESA_CCI_Water/DST/mda_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54051,499,"MNE","Montenegro","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Water/Binary/mne_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54052,499,"MNE","Montenegro","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MNE/ESA_CCI_Water/DST/mne_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54053,500,"MSR","Montserrat","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Water/Binary/msr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54054,500,"MSR","Montserrat","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MSR/ESA_CCI_Water/DST/msr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54055,504,"MAR","Morocco","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Water/Binary/mar_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54056,504,"MAR","Morocco","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MAR/ESA_CCI_Water/DST/mar_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54057,508,"MOZ","Mozambique","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Water/Binary/moz_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54058,508,"MOZ","Mozambique","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MOZ/ESA_CCI_Water/DST/moz_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54059,512,"OMN","Oman","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Water/Binary/omn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54060,512,"OMN","Oman","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/OMN/ESA_CCI_Water/DST/omn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54061,516,"NAM","Namibia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Water/Binary/nam_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54062,516,"NAM","Namibia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NAM/ESA_CCI_Water/DST/nam_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54063,520,"NRU","Nauru","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Water/Binary/nru_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54064,520,"NRU","Nauru","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NRU/ESA_CCI_Water/DST/nru_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54065,524,"NPL","Nepal","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Water/Binary/npl_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54066,524,"NPL","Nepal","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NPL/ESA_CCI_Water/DST/npl_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54067,528,"NLD","Netherlands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Water/Binary/nld_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54068,528,"NLD","Netherlands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NLD/ESA_CCI_Water/DST/nld_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54069,531,"CUW","Curacao","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Water/Binary/cuw_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54070,531,"CUW","Curacao","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CUW/ESA_CCI_Water/DST/cuw_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54071,533,"ABW","Aruba","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Water/Binary/abw_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54072,533,"ABW","Aruba","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ABW/ESA_CCI_Water/DST/abw_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54073,534,"SXM","Sint Maarten (Dutch part)","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Water/Binary/sxm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54074,534,"SXM","Sint Maarten (Dutch part)","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SXM/ESA_CCI_Water/DST/sxm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54075,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Water/Binary/bes_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54076,535,"BES","Bonaire, Sint Eustatius and Saba","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BES/ESA_CCI_Water/DST/bes_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54077,540,"NCL","New Caledonia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Water/Binary/ncl_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54078,540,"NCL","New Caledonia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NCL/ESA_CCI_Water/DST/ncl_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54079,548,"VUT","Vanuatu","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Water/Binary/vut_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54080,548,"VUT","Vanuatu","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VUT/ESA_CCI_Water/DST/vut_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54081,554,"NZL","New Zealand","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Water/Binary/nzl_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54082,554,"NZL","New Zealand","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NZL/ESA_CCI_Water/DST/nzl_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54083,558,"NIC","Nicaragua","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Water/Binary/nic_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54084,558,"NIC","Nicaragua","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NIC/ESA_CCI_Water/DST/nic_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54085,562,"NER","Niger","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Water/Binary/ner_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54086,562,"NER","Niger","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NER/ESA_CCI_Water/DST/ner_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54087,566,"NGA","Nigeria","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Water/Binary/nga_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54088,566,"NGA","Nigeria","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NGA/ESA_CCI_Water/DST/nga_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54089,570,"NIU","Niue","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Water/Binary/niu_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54090,570,"NIU","Niue","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NIU/ESA_CCI_Water/DST/niu_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54091,574,"NFK","Norfolk Island","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Water/Binary/nfk_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54092,574,"NFK","Norfolk Island","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NFK/ESA_CCI_Water/DST/nfk_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54093,578,"NOR","Norway","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Water/Binary/nor_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54094,578,"NOR","Norway","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/NOR/ESA_CCI_Water/DST/nor_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54095,580,"MNP","Northern Mariana Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Water/Binary/mnp_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54096,580,"MNP","Northern Mariana Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MNP/ESA_CCI_Water/DST/mnp_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54097,581,"UMI","United States Minor Outlying Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Water/Binary/umi_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54098,581,"UMI","United States Minor Outlying Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/UMI/ESA_CCI_Water/DST/umi_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54099,583,"FSM","Micronesia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Water/Binary/fsm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54100,583,"FSM","Micronesia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/FSM/ESA_CCI_Water/DST/fsm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54101,584,"MHL","Marshall Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Water/Binary/mhl_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54102,584,"MHL","Marshall Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MHL/ESA_CCI_Water/DST/mhl_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54103,585,"PLW","Palau","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Water/Binary/plw_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54104,585,"PLW","Palau","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PLW/ESA_CCI_Water/DST/plw_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54105,586,"PAK","Pakistan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Water/Binary/pak_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54106,586,"PAK","Pakistan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PAK/ESA_CCI_Water/DST/pak_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54107,591,"PAN","Panama","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Water/Binary/pan_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54108,591,"PAN","Panama","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PAN/ESA_CCI_Water/DST/pan_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54109,598,"PNG","Papua New Guinea","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Water/Binary/png_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54110,598,"PNG","Papua New Guinea","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PNG/ESA_CCI_Water/DST/png_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54111,600,"PRY","Paraguay","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Water/Binary/pry_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54112,600,"PRY","Paraguay","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PRY/ESA_CCI_Water/DST/pry_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54113,604,"PER","Peru","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Water/Binary/per_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54114,604,"PER","Peru","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PER/ESA_CCI_Water/DST/per_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54115,608,"PHL","Philippines","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Water/Binary/phl_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54116,608,"PHL","Philippines","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PHL/ESA_CCI_Water/DST/phl_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54117,612,"PCN","Pitcairn Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Water/Binary/pcn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54118,612,"PCN","Pitcairn Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PCN/ESA_CCI_Water/DST/pcn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54119,616,"POL","Poland","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Water/Binary/pol_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54120,616,"POL","Poland","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/POL/ESA_CCI_Water/DST/pol_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54121,620,"PRT","Portugal","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Water/Binary/prt_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54122,620,"PRT","Portugal","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PRT/ESA_CCI_Water/DST/prt_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54123,624,"GNB","Guinea-Bissau","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Water/Binary/gnb_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54124,624,"GNB","Guinea-Bissau","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GNB/ESA_CCI_Water/DST/gnb_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54125,626,"TLS","East Timor","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Water/Binary/tls_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54126,626,"TLS","East Timor","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TLS/ESA_CCI_Water/DST/tls_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54127,630,"PRI","Puerto Rico","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Water/Binary/pri_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54128,630,"PRI","Puerto Rico","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/PRI/ESA_CCI_Water/DST/pri_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54129,634,"QAT","Qatar","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Water/Binary/qat_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54130,634,"QAT","Qatar","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/QAT/ESA_CCI_Water/DST/qat_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54131,638,"REU","Reunion","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Water/Binary/reu_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54132,638,"REU","Reunion","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/REU/ESA_CCI_Water/DST/reu_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54133,642,"ROU","Romania","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Water/Binary/rou_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54134,642,"ROU","Romania","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ROU/ESA_CCI_Water/DST/rou_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54135,646,"RWA","Rwanda","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Water/Binary/rwa_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54136,646,"RWA","Rwanda","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/RWA/ESA_CCI_Water/DST/rwa_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54137,652,"BLM","Saint Barthelemy","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Water/Binary/blm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54138,652,"BLM","Saint Barthelemy","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BLM/ESA_CCI_Water/DST/blm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54139,654,"SHN","Saint Helena","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Water/Binary/shn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54140,654,"SHN","Saint Helena","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SHN/ESA_CCI_Water/DST/shn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54141,659,"KNA","Saint Kitts and Nevis","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Water/Binary/kna_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54142,659,"KNA","Saint Kitts and Nevis","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KNA/ESA_CCI_Water/DST/kna_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54143,660,"AIA","Anguilla","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Water/Binary/aia_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54144,660,"AIA","Anguilla","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/AIA/ESA_CCI_Water/DST/aia_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54145,662,"LCA","Saint Lucia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Water/Binary/lca_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54146,662,"LCA","Saint Lucia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/LCA/ESA_CCI_Water/DST/lca_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54147,663,"MAF","Saint Martin (French part)","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Water/Binary/maf_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54148,663,"MAF","Saint Martin (French part)","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MAF/ESA_CCI_Water/DST/maf_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54149,666,"SPM","Saint Pierre and Miquelon","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Water/Binary/spm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54150,666,"SPM","Saint Pierre and Miquelon","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SPM/ESA_CCI_Water/DST/spm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54151,670,"VCT","Saint Vincent and the Grenadines","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Water/Binary/vct_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54152,670,"VCT","Saint Vincent and the Grenadines","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VCT/ESA_CCI_Water/DST/vct_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54153,674,"SMR","San Marino","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Water/Binary/smr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54154,674,"SMR","San Marino","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SMR/ESA_CCI_Water/DST/smr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54155,678,"STP","Sao Tome and Principe","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Water/Binary/stp_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54156,678,"STP","Sao Tome and Principe","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/STP/ESA_CCI_Water/DST/stp_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54157,682,"SAU","Saudi Arabia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Water/Binary/sau_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54158,682,"SAU","Saudi Arabia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SAU/ESA_CCI_Water/DST/sau_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54159,686,"SEN","Senegal","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Water/Binary/sen_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54160,686,"SEN","Senegal","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SEN/ESA_CCI_Water/DST/sen_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54161,688,"SRB","Serbia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Water/Binary/srb_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54162,688,"SRB","Serbia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SRB/ESA_CCI_Water/DST/srb_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54163,690,"SYC","Seychelles","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Water/Binary/syc_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54164,690,"SYC","Seychelles","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SYC/ESA_CCI_Water/DST/syc_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54165,694,"SLE","Sierra Leone","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Water/Binary/sle_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54166,694,"SLE","Sierra Leone","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SLE/ESA_CCI_Water/DST/sle_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54167,702,"SGP","Singapore","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Water/Binary/sgp_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54168,702,"SGP","Singapore","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SGP/ESA_CCI_Water/DST/sgp_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54169,703,"SVK","Slovakia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Water/Binary/svk_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54170,703,"SVK","Slovakia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SVK/ESA_CCI_Water/DST/svk_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54171,704,"VNM","Vietnam","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Water/Binary/vnm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54172,704,"VNM","Vietnam","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VNM/ESA_CCI_Water/DST/vnm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54173,705,"SVN","Slovenia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Water/Binary/svn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54174,705,"SVN","Slovenia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SVN/ESA_CCI_Water/DST/svn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54175,706,"SOM","Somalia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Water/Binary/som_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54176,706,"SOM","Somalia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SOM/ESA_CCI_Water/DST/som_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54177,710,"ZAF","South Africa","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Water/Binary/zaf_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54178,710,"ZAF","South Africa","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ZAF/ESA_CCI_Water/DST/zaf_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54179,716,"ZWE","Zimbabwe","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Water/Binary/zwe_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54180,716,"ZWE","Zimbabwe","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ZWE/ESA_CCI_Water/DST/zwe_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54181,724,"ESP","Spain","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Water/Binary/esp_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54182,724,"ESP","Spain","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ESP/ESA_CCI_Water/DST/esp_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54183,728,"SSD","South Sudan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Water/Binary/ssd_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54184,728,"SSD","South Sudan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SSD/ESA_CCI_Water/DST/ssd_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54185,729,"SDN","Sudan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Water/Binary/sdn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54186,729,"SDN","Sudan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SDN/ESA_CCI_Water/DST/sdn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54187,732,"ESH","Western Sahara","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Water/Binary/esh_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54188,732,"ESH","Western Sahara","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ESH/ESA_CCI_Water/DST/esh_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54189,740,"SUR","Suriname","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Water/Binary/sur_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54190,740,"SUR","Suriname","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SUR/ESA_CCI_Water/DST/sur_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54191,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Water/Binary/sjm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54192,744,"SJM","Svalbard and Jan Mayen Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SJM/ESA_CCI_Water/DST/sjm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54193,748,"SWZ","Swaziland","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Water/Binary/swz_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54194,748,"SWZ","Swaziland","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SWZ/ESA_CCI_Water/DST/swz_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54195,752,"SWE","Sweden","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Water/Binary/swe_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54196,752,"SWE","Sweden","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SWE/ESA_CCI_Water/DST/swe_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54197,756,"CHE","Switzerland","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Water/Binary/che_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54198,756,"CHE","Switzerland","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/CHE/ESA_CCI_Water/DST/che_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54199,760,"SYR","Syria","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Water/Binary/syr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54200,760,"SYR","Syria","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SYR/ESA_CCI_Water/DST/syr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54201,762,"TJK","Tajikistan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Water/Binary/tjk_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54202,762,"TJK","Tajikistan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TJK/ESA_CCI_Water/DST/tjk_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54203,764,"THA","Thailand","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Water/Binary/tha_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54204,764,"THA","Thailand","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/THA/ESA_CCI_Water/DST/tha_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54205,768,"TGO","Togo","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Water/Binary/tgo_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54206,768,"TGO","Togo","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TGO/ESA_CCI_Water/DST/tgo_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54207,772,"TKL","Tokelau","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Water/Binary/tkl_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54208,772,"TKL","Tokelau","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TKL/ESA_CCI_Water/DST/tkl_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54209,776,"TON","Tonga","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Water/Binary/ton_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54210,776,"TON","Tonga","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TON/ESA_CCI_Water/DST/ton_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54211,780,"TTO","Trinidad and Tobago","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Water/Binary/tto_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54212,780,"TTO","Trinidad and Tobago","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TTO/ESA_CCI_Water/DST/tto_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54213,784,"ARE","United Arab Emirates","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Water/Binary/are_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54214,784,"ARE","United Arab Emirates","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ARE/ESA_CCI_Water/DST/are_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54215,788,"TUN","Tunisia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Water/Binary/tun_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54216,788,"TUN","Tunisia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TUN/ESA_CCI_Water/DST/tun_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54217,792,"TUR","Turkey","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Water/Binary/tur_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54218,792,"TUR","Turkey","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TUR/ESA_CCI_Water/DST/tur_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54219,795,"TKM","Turkmenistan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Water/Binary/tkm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54220,795,"TKM","Turkmenistan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TKM/ESA_CCI_Water/DST/tkm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54221,796,"TCA","Turks and Caicos Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Water/Binary/tca_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54222,796,"TCA","Turks and Caicos Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TCA/ESA_CCI_Water/DST/tca_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54223,798,"TUV","Tuvalu","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Water/Binary/tuv_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54224,798,"TUV","Tuvalu","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TUV/ESA_CCI_Water/DST/tuv_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54225,800,"UGA","Uganda","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Water/Binary/uga_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54226,800,"UGA","Uganda","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/UGA/ESA_CCI_Water/DST/uga_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54227,804,"UKR","Ukraine","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Water/Binary/ukr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54228,804,"UKR","Ukraine","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/UKR/ESA_CCI_Water/DST/ukr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54229,807,"MKD","Macedonia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Water/Binary/mkd_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54230,807,"MKD","Macedonia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/MKD/ESA_CCI_Water/DST/mkd_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54231,818,"EGY","Egypt","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Water/Binary/egy_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54232,818,"EGY","Egypt","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/EGY/ESA_CCI_Water/DST/egy_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54233,826,"GBR","United Kingdom","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Water/Binary/gbr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54234,826,"GBR","United Kingdom","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GBR/ESA_CCI_Water/DST/gbr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54235,831,"GGY","Guernsey","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Water/Binary/ggy_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54236,831,"GGY","Guernsey","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/GGY/ESA_CCI_Water/DST/ggy_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54237,832,"JEY","Jersey","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Water/Binary/jey_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54238,832,"JEY","Jersey","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/JEY/ESA_CCI_Water/DST/jey_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54239,833,"IMN","Isle of Man","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Water/Binary/imn_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54240,833,"IMN","Isle of Man","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/IMN/ESA_CCI_Water/DST/imn_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54241,834,"TZA","Tanzania","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Water/Binary/tza_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54242,834,"TZA","Tanzania","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/TZA/ESA_CCI_Water/DST/tza_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54243,854,"BFA","Burkina Faso","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Water/Binary/bfa_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54244,854,"BFA","Burkina Faso","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/BFA/ESA_CCI_Water/DST/bfa_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54245,858,"URY","Uruguay","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Water/Binary/ury_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54246,858,"URY","Uruguay","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/URY/ESA_CCI_Water/DST/ury_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54247,860,"UZB","Uzbekistan","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Water/Binary/uzb_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54248,860,"UZB","Uzbekistan","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/UZB/ESA_CCI_Water/DST/uzb_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54249,862,"VEN","Venezuela","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Water/Binary/ven_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54250,862,"VEN","Venezuela","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/VEN/ESA_CCI_Water/DST/ven_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54251,876,"WLF","Wallis and Futuna","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Water/Binary/wlf_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54252,876,"WLF","Wallis and Futuna","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/WLF/ESA_CCI_Water/DST/wlf_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54253,882,"WSM","Samoa","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Water/Binary/wsm_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54254,882,"WSM","Samoa","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/WSM/ESA_CCI_Water/DST/wsm_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54255,887,"YEM","Yemen","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Water/Binary/yem_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54256,887,"YEM","Yemen","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/YEM/ESA_CCI_Water/DST/yem_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54257,894,"ZMB","Zambia","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Water/Binary/zmb_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54258,894,"ZMB","Zambia","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/ZMB/ESA_CCI_Water/DST/zmb_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54259,900,"KOS","Kosovo","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Water/Binary/kos_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54260,900,"KOS","Kosovo","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/KOS/ESA_CCI_Water/DST/kos_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54261,901,"SPR","Spratly Islands","esaccilc_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Water/Binary/spr_esaccilc_water_100m_2000_2012.tif","ESA-CCI-LC inland waterbodies 2000-2012"
54262,901,"SPR","Spratly Islands","esaccilc_dst_water_100m_2000_2012","GIS/Covariates/Global_2000_2020/SPR/ESA_CCI_Water/DST/spr_esaccilc_dst_water_100m_2000_2012.tif","Distance to ESA-CCI-LC inland waterbody 2000-2012"
54263,643,"RUS","Russia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/RUS/L0/rus_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54264,643,"RUS","Russia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/RUS/Subnational/rus_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54265,360,"IDN","Indonesia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/IDN/L0/idn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54266,360,"IDN","Indonesia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/IDN/Subnational/idn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54267,840,"USA","United States","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/USA/L0/usa_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54268,840,"USA","United States","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/USA/Subnational/usa_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54269,850,"VIR","Virgin_Islands_U_S","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/VIR/L0/vir_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54270,850,"VIR","Virgin_Islands_U_S","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/VIR/Subnational/vir_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54271,304,"GRL","Greenland","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GRL/L0/grl_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54272,304,"GRL","Greenland","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GRL/Subnational/grl_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54273,156,"CHN","China","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CHN/L0/chn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54274,156,"CHN","China","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CHN/Subnational/chn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54275,36,"AUS","Australia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/AUS/L0/aus_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54276,36,"AUS","Australia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/AUS/Subnational/aus_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54277,76,"BRA","Brazil","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BRA/L0/bra_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54278,76,"BRA","Brazil","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BRA/Subnational/bra_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54279,124,"CAN","Canada","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CAN/L0/can_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54280,124,"CAN","Canada","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CAN/Subnational/can_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54281,152,"CHL","Chile","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CHL/L0/chl_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54282,152,"CHL","Chile","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CHL/Subnational/chl_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54283,4,"AFG","Afghanistan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/AFG/L0/afg_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54284,4,"AFG","Afghanistan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/AFG/Subnational/afg_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54285,8,"ALB","Albania","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ALB/L0/alb_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54286,8,"ALB","Albania","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ALB/Subnational/alb_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54287,10,"ATA","Antarctica","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ATA/L0/ata_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54288,10,"ATA","Antarctica","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ATA/Subnational/ata_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54289,12,"DZA","Algeria","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/DZA/L0/dza_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54290,12,"DZA","Algeria","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/DZA/Subnational/dza_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54291,16,"ASM","American Samoa","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ASM/L0/asm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54292,16,"ASM","American Samoa","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ASM/Subnational/asm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54293,20,"AND","Andorra","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/AND/L0/and_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54294,20,"AND","Andorra","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/AND/Subnational/and_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54295,24,"AGO","Angola","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/AGO/L0/ago_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54296,24,"AGO","Angola","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/AGO/Subnational/ago_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54297,28,"ATG","Antigua and Barbuda","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ATG/L0/atg_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54298,28,"ATG","Antigua and Barbuda","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ATG/Subnational/atg_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54299,31,"AZE","Azerbaijan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/AZE/L0/aze_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54300,31,"AZE","Azerbaijan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/AZE/Subnational/aze_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54301,32,"ARG","Argentina","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ARG/L0/arg_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54302,32,"ARG","Argentina","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ARG/Subnational/arg_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54303,40,"AUT","Austria","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/AUT/L0/aut_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54304,40,"AUT","Austria","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/AUT/Subnational/aut_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54305,44,"BHS","Bahamas","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BHS/L0/bhs_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54306,44,"BHS","Bahamas","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BHS/Subnational/bhs_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54307,48,"BHR","Bahrain","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BHR/L0/bhr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54308,48,"BHR","Bahrain","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BHR/Subnational/bhr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54309,50,"BGD","Bangladesh","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BGD/L0/bgd_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54310,50,"BGD","Bangladesh","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BGD/Subnational/bgd_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54311,51,"ARM","Armenia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ARM/L0/arm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54312,51,"ARM","Armenia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ARM/Subnational/arm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54313,52,"BRB","Barbados","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BRB/L0/brb_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54314,52,"BRB","Barbados","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BRB/Subnational/brb_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54315,56,"BEL","Belgium","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BEL/L0/bel_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54316,56,"BEL","Belgium","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BEL/Subnational/bel_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54317,60,"BMU","Bermuda","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BMU/L0/bmu_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54318,60,"BMU","Bermuda","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BMU/Subnational/bmu_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54319,64,"BTN","Bhutan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BTN/L0/btn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54320,64,"BTN","Bhutan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BTN/Subnational/btn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54321,68,"BOL","Bolivia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BOL/L0/bol_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54322,68,"BOL","Bolivia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BOL/Subnational/bol_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54323,70,"BIH","Bosnia and Herzegovina","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BIH/L0/bih_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54324,70,"BIH","Bosnia and Herzegovina","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BIH/Subnational/bih_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54325,72,"BWA","Botswana","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BWA/L0/bwa_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54326,72,"BWA","Botswana","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BWA/Subnational/bwa_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54327,74,"BVT","Bouvet Island","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BVT/L0/bvt_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54328,74,"BVT","Bouvet Island","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BVT/Subnational/bvt_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54329,84,"BLZ","Belize","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BLZ/L0/blz_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54330,84,"BLZ","Belize","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BLZ/Subnational/blz_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54331,86,"IOT","British Indian Ocean Territory","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/IOT/L0/iot_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54332,86,"IOT","British Indian Ocean Territory","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/IOT/Subnational/iot_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54333,90,"SLB","Solomon Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SLB/L0/slb_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54334,90,"SLB","Solomon Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SLB/Subnational/slb_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54335,92,"VGB","British Virgin Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/VGB/L0/vgb_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54336,92,"VGB","British Virgin Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/VGB/Subnational/vgb_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54337,96,"BRN","Brunei","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BRN/L0/brn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54338,96,"BRN","Brunei","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BRN/Subnational/brn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54339,100,"BGR","Bulgaria","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BGR/L0/bgr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54340,100,"BGR","Bulgaria","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BGR/Subnational/bgr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54341,104,"MMR","Myanmar","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MMR/L0/mmr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54342,104,"MMR","Myanmar","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MMR/Subnational/mmr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54343,108,"BDI","Burundi","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BDI/L0/bdi_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54344,108,"BDI","Burundi","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BDI/Subnational/bdi_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54345,112,"BLR","Belarus","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BLR/L0/blr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54346,112,"BLR","Belarus","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BLR/Subnational/blr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54347,116,"KHM","Cambodia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/KHM/L0/khm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54348,116,"KHM","Cambodia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/KHM/Subnational/khm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54349,120,"CMR","Cameroon","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CMR/L0/cmr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54350,120,"CMR","Cameroon","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CMR/Subnational/cmr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54351,132,"CPV","Cape Verde","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CPV/L0/cpv_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54352,132,"CPV","Cape Verde","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CPV/Subnational/cpv_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54353,136,"CYM","Cayman Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CYM/L0/cym_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54354,136,"CYM","Cayman Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CYM/Subnational/cym_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54355,140,"CAF","Central African Republic","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CAF/L0/caf_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54356,140,"CAF","Central African Republic","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CAF/Subnational/caf_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54357,144,"LKA","Sri Lanka","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LKA/L0/lka_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54358,144,"LKA","Sri Lanka","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LKA/Subnational/lka_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54359,148,"TCD","Chad","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TCD/L0/tcd_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54360,148,"TCD","Chad","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TCD/Subnational/tcd_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54361,158,"TWN","Taiwan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TWN/L0/twn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54362,158,"TWN","Taiwan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TWN/Subnational/twn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54363,170,"COL","Colombia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/COL/L0/col_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54364,170,"COL","Colombia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/COL/Subnational/col_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54365,174,"COM","Comoros","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/COM/L0/com_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54366,174,"COM","Comoros","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/COM/Subnational/com_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54367,175,"MYT","Mayotte","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MYT/L0/myt_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54368,175,"MYT","Mayotte","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MYT/Subnational/myt_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54369,178,"COG","Republic of Congo","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/COG/L0/cog_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54370,178,"COG","Republic of Congo","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/COG/Subnational/cog_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54371,180,"COD","Democratic Republic of the Congo","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/COD/L0/cod_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54372,180,"COD","Democratic Republic of the Congo","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/COD/Subnational/cod_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54373,184,"COK","Cook Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/COK/L0/cok_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54374,184,"COK","Cook Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/COK/Subnational/cok_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54375,188,"CRI","Costa Rica","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CRI/L0/cri_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54376,188,"CRI","Costa Rica","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CRI/Subnational/cri_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54377,191,"HRV","Croatia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/HRV/L0/hrv_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54378,191,"HRV","Croatia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/HRV/Subnational/hrv_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54379,192,"CUB","Cuba","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CUB/L0/cub_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54380,192,"CUB","Cuba","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CUB/Subnational/cub_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54381,196,"CYP","Cyprus","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CYP/L0/cyp_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54382,196,"CYP","Cyprus","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CYP/Subnational/cyp_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54383,203,"CZE","Czech Republic","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CZE/L0/cze_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54384,203,"CZE","Czech Republic","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CZE/Subnational/cze_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54385,204,"BEN","Benin","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BEN/L0/ben_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54386,204,"BEN","Benin","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BEN/Subnational/ben_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54387,208,"DNK","Denmark","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/DNK/L0/dnk_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54388,208,"DNK","Denmark","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/DNK/Subnational/dnk_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54389,212,"DMA","Dominica","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/DMA/L0/dma_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54390,212,"DMA","Dominica","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/DMA/Subnational/dma_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54391,214,"DOM","Dominican Republic","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/DOM/L0/dom_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54392,214,"DOM","Dominican Republic","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/DOM/Subnational/dom_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54393,218,"ECU","Ecuador","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ECU/L0/ecu_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54394,218,"ECU","Ecuador","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ECU/Subnational/ecu_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54395,222,"SLV","El Salvador","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SLV/L0/slv_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54396,222,"SLV","El Salvador","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SLV/Subnational/slv_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54397,226,"GNQ","Equatorial Guinea","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GNQ/L0/gnq_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54398,226,"GNQ","Equatorial Guinea","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GNQ/Subnational/gnq_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54399,231,"ETH","Ethiopia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ETH/L0/eth_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54400,231,"ETH","Ethiopia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ETH/Subnational/eth_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54401,232,"ERI","Eritrea","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ERI/L0/eri_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54402,232,"ERI","Eritrea","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ERI/Subnational/eri_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54403,233,"EST","Estonia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/EST/L0/est_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54404,233,"EST","Estonia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/EST/Subnational/est_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54405,234,"FRO","Faroe Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/FRO/L0/fro_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54406,234,"FRO","Faroe Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/FRO/Subnational/fro_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54407,238,"FLK","Falkland Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/FLK/L0/flk_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54408,238,"FLK","Falkland Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/FLK/Subnational/flk_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54409,239,"SGS","South Georgia and the South Sandwich Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SGS/L0/sgs_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54410,239,"SGS","South Georgia and the South Sandwich Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SGS/Subnational/sgs_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54411,242,"FJI","Fiji","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/FJI/L0/fji_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54412,242,"FJI","Fiji","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/FJI/Subnational/fji_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54413,246,"FIN","Finland","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/FIN/L0/fin_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54414,246,"FIN","Finland","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/FIN/Subnational/fin_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54415,248,"ALA","Aland Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ALA/L0/ala_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54416,248,"ALA","Aland Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ALA/Subnational/ala_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54417,250,"FRA","France","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/FRA/L0/fra_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54418,250,"FRA","France","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/FRA/Subnational/fra_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54419,254,"GUF","French Guiana","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GUF/L0/guf_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54420,254,"GUF","French Guiana","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GUF/Subnational/guf_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54421,258,"PYF","French Polynesia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PYF/L0/pyf_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54422,258,"PYF","French Polynesia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PYF/Subnational/pyf_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54423,260,"ATF","French Southern Territories","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ATF/L0/atf_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54424,260,"ATF","French Southern Territories","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ATF/Subnational/atf_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54425,262,"DJI","Djibouti","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/DJI/L0/dji_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54426,262,"DJI","Djibouti","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/DJI/Subnational/dji_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54427,266,"GAB","Gabon","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GAB/L0/gab_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54428,266,"GAB","Gabon","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GAB/Subnational/gab_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54429,268,"GEO","Georgia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GEO/L0/geo_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54430,268,"GEO","Georgia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GEO/Subnational/geo_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54431,270,"GMB","Gambia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GMB/L0/gmb_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54432,270,"GMB","Gambia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GMB/Subnational/gmb_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54433,275,"PSE","Palestina","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PSE/L0/pse_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54434,275,"PSE","Palestina","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PSE/Subnational/pse_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54435,276,"DEU","Germany","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/DEU/L0/deu_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54436,276,"DEU","Germany","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/DEU/Subnational/deu_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54437,288,"GHA","Ghana","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GHA/L0/gha_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54438,288,"GHA","Ghana","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GHA/Subnational/gha_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54439,292,"GIB","Gibraltar","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GIB/L0/gib_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54440,292,"GIB","Gibraltar","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GIB/Subnational/gib_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54441,296,"KIR","Kiribati","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/KIR/L0/kir_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54442,296,"KIR","Kiribati","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/KIR/Subnational/kir_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54443,300,"GRC","Greece","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GRC/L0/grc_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54444,300,"GRC","Greece","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GRC/Subnational/grc_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54445,308,"GRD","Grenada","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GRD/L0/grd_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54446,308,"GRD","Grenada","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GRD/Subnational/grd_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54447,312,"GLP","Guadeloupe","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GLP/L0/glp_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54448,312,"GLP","Guadeloupe","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GLP/Subnational/glp_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54449,316,"GUM","Guam","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GUM/L0/gum_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54450,316,"GUM","Guam","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GUM/Subnational/gum_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54451,320,"GTM","Guatemala","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GTM/L0/gtm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54452,320,"GTM","Guatemala","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GTM/Subnational/gtm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54453,324,"GIN","Guinea","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GIN/L0/gin_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54454,324,"GIN","Guinea","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GIN/Subnational/gin_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54455,328,"GUY","Guyana","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GUY/L0/guy_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54456,328,"GUY","Guyana","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GUY/Subnational/guy_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54457,332,"HTI","Haiti","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/HTI/L0/hti_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54458,332,"HTI","Haiti","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/HTI/Subnational/hti_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54459,334,"HMD","Heard Island and McDonald Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/HMD/L0/hmd_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54460,334,"HMD","Heard Island and McDonald Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/HMD/Subnational/hmd_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54461,336,"VAT","Vatican City","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/VAT/L0/vat_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54462,336,"VAT","Vatican City","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/VAT/Subnational/vat_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54463,340,"HND","Honduras","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/HND/L0/hnd_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54464,340,"HND","Honduras","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/HND/Subnational/hnd_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54465,344,"HKG","Hong Kong","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/HKG/L0/hkg_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54466,344,"HKG","Hong Kong","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/HKG/Subnational/hkg_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54467,348,"HUN","Hungary","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/HUN/L0/hun_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54468,348,"HUN","Hungary","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/HUN/Subnational/hun_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54469,352,"ISL","Iceland","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ISL/L0/isl_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54470,352,"ISL","Iceland","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ISL/Subnational/isl_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54471,356,"IND","India","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/IND/L0/ind_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54472,356,"IND","India","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/IND/Subnational/ind_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54473,364,"IRN","Iran","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/IRN/L0/irn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54474,364,"IRN","Iran","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/IRN/Subnational/irn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54475,368,"IRQ","Iraq","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/IRQ/L0/irq_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54476,368,"IRQ","Iraq","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/IRQ/Subnational/irq_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54477,372,"IRL","Ireland","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/IRL/L0/irl_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54478,372,"IRL","Ireland","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/IRL/Subnational/irl_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54479,376,"ISR","Israel","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ISR/L0/isr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54480,376,"ISR","Israel","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ISR/Subnational/isr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54481,380,"ITA","Italy","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ITA/L0/ita_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54482,380,"ITA","Italy","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ITA/Subnational/ita_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54483,384,"CIV","CIte dIvoire","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CIV/L0/civ_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54484,384,"CIV","CIte dIvoire","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CIV/Subnational/civ_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54485,388,"JAM","Jamaica","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/JAM/L0/jam_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54486,388,"JAM","Jamaica","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/JAM/Subnational/jam_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54487,392,"JPN","Japan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/JPN/L0/jpn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54488,392,"JPN","Japan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/JPN/Subnational/jpn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54489,398,"KAZ","Kazakhstan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/KAZ/L0/kaz_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54490,398,"KAZ","Kazakhstan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/KAZ/Subnational/kaz_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54491,400,"JOR","Jordan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/JOR/L0/jor_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54492,400,"JOR","Jordan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/JOR/Subnational/jor_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54493,404,"KEN","Kenya","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/KEN/L0/ken_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54494,404,"KEN","Kenya","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/KEN/Subnational/ken_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54495,408,"PRK","North Korea","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PRK/L0/prk_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54496,408,"PRK","North Korea","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PRK/Subnational/prk_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54497,410,"KOR","South Korea","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/KOR/L0/kor_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54498,410,"KOR","South Korea","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/KOR/Subnational/kor_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54499,414,"KWT","Kuwait","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/KWT/L0/kwt_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54500,414,"KWT","Kuwait","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/KWT/Subnational/kwt_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54501,417,"KGZ","Kyrgyzstan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/KGZ/L0/kgz_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54502,417,"KGZ","Kyrgyzstan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/KGZ/Subnational/kgz_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54503,418,"LAO","Laos","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LAO/L0/lao_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54504,418,"LAO","Laos","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LAO/Subnational/lao_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54505,422,"LBN","Lebanon","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LBN/L0/lbn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54506,422,"LBN","Lebanon","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LBN/Subnational/lbn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54507,426,"LSO","Lesotho","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LSO/L0/lso_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54508,426,"LSO","Lesotho","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LSO/Subnational/lso_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54509,428,"LVA","Latvia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LVA/L0/lva_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54510,428,"LVA","Latvia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LVA/Subnational/lva_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54511,430,"LBR","Liberia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LBR/L0/lbr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54512,430,"LBR","Liberia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LBR/Subnational/lbr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54513,434,"LBY","Libya","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LBY/L0/lby_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54514,434,"LBY","Libya","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LBY/Subnational/lby_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54515,438,"LIE","Liechtenstein","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LIE/L0/lie_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54516,438,"LIE","Liechtenstein","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LIE/Subnational/lie_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54517,440,"LTU","Lithuania","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LTU/L0/ltu_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54518,440,"LTU","Lithuania","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LTU/Subnational/ltu_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54519,442,"LUX","Luxembourg","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LUX/L0/lux_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54520,442,"LUX","Luxembourg","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LUX/Subnational/lux_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54521,446,"MAC","Macao","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MAC/L0/mac_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54522,446,"MAC","Macao","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MAC/Subnational/mac_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54523,450,"MDG","Madagascar","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MDG/L0/mdg_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54524,450,"MDG","Madagascar","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MDG/Subnational/mdg_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54525,454,"MWI","Malawi","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MWI/L0/mwi_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54526,454,"MWI","Malawi","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MWI/Subnational/mwi_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54527,458,"MYS","Malaysia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MYS/L0/mys_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54528,458,"MYS","Malaysia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MYS/Subnational/mys_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54529,462,"MDV","Maldives","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MDV/L0/mdv_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54530,462,"MDV","Maldives","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MDV/Subnational/mdv_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54531,466,"MLI","Mali","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MLI/L0/mli_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54532,466,"MLI","Mali","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MLI/Subnational/mli_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54533,470,"MLT","Malta","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MLT/L0/mlt_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54534,470,"MLT","Malta","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MLT/Subnational/mlt_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54535,474,"MTQ","Martinique","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MTQ/L0/mtq_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54536,474,"MTQ","Martinique","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MTQ/Subnational/mtq_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54537,478,"MRT","Mauritania","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MRT/L0/mrt_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54538,478,"MRT","Mauritania","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MRT/Subnational/mrt_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54539,480,"MUS","Mauritius","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MUS/L0/mus_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54540,480,"MUS","Mauritius","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MUS/Subnational/mus_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54541,484,"MEX","Mexico","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MEX/L0/mex_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54542,484,"MEX","Mexico","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MEX/Subnational/mex_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54543,492,"MCO","Monaco","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MCO/L0/mco_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54544,492,"MCO","Monaco","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MCO/Subnational/mco_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54545,496,"MNG","Mongolia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MNG/L0/mng_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54546,496,"MNG","Mongolia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MNG/Subnational/mng_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54547,498,"MDA","Moldova","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MDA/L0/mda_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54548,498,"MDA","Moldova","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MDA/Subnational/mda_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54549,499,"MNE","Montenegro","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MNE/L0/mne_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54550,499,"MNE","Montenegro","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MNE/Subnational/mne_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54551,500,"MSR","Montserrat","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MSR/L0/msr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54552,500,"MSR","Montserrat","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MSR/Subnational/msr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54553,504,"MAR","Morocco","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MAR/L0/mar_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54554,504,"MAR","Morocco","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MAR/Subnational/mar_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54555,508,"MOZ","Mozambique","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MOZ/L0/moz_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54556,508,"MOZ","Mozambique","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MOZ/Subnational/moz_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54557,512,"OMN","Oman","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/OMN/L0/omn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54558,512,"OMN","Oman","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/OMN/Subnational/omn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54559,516,"NAM","Namibia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NAM/L0/nam_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54560,516,"NAM","Namibia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NAM/Subnational/nam_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54561,520,"NRU","Nauru","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NRU/L0/nru_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54562,520,"NRU","Nauru","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NRU/Subnational/nru_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54563,524,"NPL","Nepal","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NPL/L0/npl_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54564,524,"NPL","Nepal","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NPL/Subnational/npl_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54565,528,"NLD","Netherlands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NLD/L0/nld_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54566,528,"NLD","Netherlands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NLD/Subnational/nld_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54567,531,"CUW","Curacao","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CUW/L0/cuw_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54568,531,"CUW","Curacao","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CUW/Subnational/cuw_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54569,533,"ABW","Aruba","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ABW/L0/abw_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54570,533,"ABW","Aruba","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ABW/Subnational/abw_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54571,534,"SXM","Sint Maarten (Dutch part)","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SXM/L0/sxm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54572,534,"SXM","Sint Maarten (Dutch part)","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SXM/Subnational/sxm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54573,535,"BES","Bonaire, Sint Eustatius and Saba","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BES/L0/bes_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54574,535,"BES","Bonaire, Sint Eustatius and Saba","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BES/Subnational/bes_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54575,540,"NCL","New Caledonia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NCL/L0/ncl_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54576,540,"NCL","New Caledonia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NCL/Subnational/ncl_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54577,548,"VUT","Vanuatu","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/VUT/L0/vut_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54578,548,"VUT","Vanuatu","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/VUT/Subnational/vut_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54579,554,"NZL","New Zealand","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NZL/L0/nzl_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54580,554,"NZL","New Zealand","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NZL/Subnational/nzl_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54581,558,"NIC","Nicaragua","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NIC/L0/nic_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54582,558,"NIC","Nicaragua","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NIC/Subnational/nic_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54583,562,"NER","Niger","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NER/L0/ner_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54584,562,"NER","Niger","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NER/Subnational/ner_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54585,566,"NGA","Nigeria","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NGA/L0/nga_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54586,566,"NGA","Nigeria","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NGA/Subnational/nga_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54587,570,"NIU","Niue","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NIU/L0/niu_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54588,570,"NIU","Niue","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NIU/Subnational/niu_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54589,574,"NFK","Norfolk Island","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NFK/L0/nfk_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54590,574,"NFK","Norfolk Island","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NFK/Subnational/nfk_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54591,578,"NOR","Norway","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/NOR/L0/nor_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54592,578,"NOR","Norway","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/NOR/Subnational/nor_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54593,580,"MNP","Northern Mariana Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MNP/L0/mnp_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54594,580,"MNP","Northern Mariana Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MNP/Subnational/mnp_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54595,581,"UMI","United States Minor Outlying Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/UMI/L0/umi_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54596,581,"UMI","United States Minor Outlying Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/UMI/Subnational/umi_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54597,583,"FSM","Micronesia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/FSM/L0/fsm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54598,583,"FSM","Micronesia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/FSM/Subnational/fsm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54599,584,"MHL","Marshall Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MHL/L0/mhl_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54600,584,"MHL","Marshall Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MHL/Subnational/mhl_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54601,585,"PLW","Palau","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PLW/L0/plw_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54602,585,"PLW","Palau","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PLW/Subnational/plw_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54603,586,"PAK","Pakistan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PAK/L0/pak_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54604,586,"PAK","Pakistan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PAK/Subnational/pak_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54605,591,"PAN","Panama","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PAN/L0/pan_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54606,591,"PAN","Panama","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PAN/Subnational/pan_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54607,598,"PNG","Papua New Guinea","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PNG/L0/png_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54608,598,"PNG","Papua New Guinea","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PNG/Subnational/png_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54609,600,"PRY","Paraguay","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PRY/L0/pry_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54610,600,"PRY","Paraguay","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PRY/Subnational/pry_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54611,604,"PER","Peru","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PER/L0/per_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54612,604,"PER","Peru","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PER/Subnational/per_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54613,608,"PHL","Philippines","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PHL/L0/phl_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54614,608,"PHL","Philippines","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PHL/Subnational/phl_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54615,612,"PCN","Pitcairn Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PCN/L0/pcn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54616,612,"PCN","Pitcairn Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PCN/Subnational/pcn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54617,616,"POL","Poland","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/POL/L0/pol_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54618,616,"POL","Poland","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/POL/Subnational/pol_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54619,620,"PRT","Portugal","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PRT/L0/prt_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54620,620,"PRT","Portugal","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PRT/Subnational/prt_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54621,624,"GNB","Guinea-Bissau","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GNB/L0/gnb_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54622,624,"GNB","Guinea-Bissau","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GNB/Subnational/gnb_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54623,626,"TLS","East Timor","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TLS/L0/tls_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54624,626,"TLS","East Timor","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TLS/Subnational/tls_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54625,630,"PRI","Puerto Rico","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/PRI/L0/pri_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54626,630,"PRI","Puerto Rico","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/PRI/Subnational/pri_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54627,634,"QAT","Qatar","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/QAT/L0/qat_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54628,634,"QAT","Qatar","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/QAT/Subnational/qat_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54629,638,"REU","Reunion","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/REU/L0/reu_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54630,638,"REU","Reunion","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/REU/Subnational/reu_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54631,642,"ROU","Romania","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ROU/L0/rou_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54632,642,"ROU","Romania","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ROU/Subnational/rou_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54633,646,"RWA","Rwanda","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/RWA/L0/rwa_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54634,646,"RWA","Rwanda","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/RWA/Subnational/rwa_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54635,652,"BLM","Saint Barthelemy","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BLM/L0/blm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54636,652,"BLM","Saint Barthelemy","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BLM/Subnational/blm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54637,654,"SHN","Saint Helena","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SHN/L0/shn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54638,654,"SHN","Saint Helena","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SHN/Subnational/shn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54639,659,"KNA","Saint Kitts and Nevis","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/KNA/L0/kna_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54640,659,"KNA","Saint Kitts and Nevis","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/KNA/Subnational/kna_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54641,660,"AIA","Anguilla","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/AIA/L0/aia_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54642,660,"AIA","Anguilla","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/AIA/Subnational/aia_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54643,662,"LCA","Saint Lucia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/LCA/L0/lca_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54644,662,"LCA","Saint Lucia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/LCA/Subnational/lca_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54645,663,"MAF","Saint Martin (French part)","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MAF/L0/maf_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54646,663,"MAF","Saint Martin (French part)","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MAF/Subnational/maf_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54647,666,"SPM","Saint Pierre and Miquelon","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SPM/L0/spm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54648,666,"SPM","Saint Pierre and Miquelon","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SPM/Subnational/spm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54649,670,"VCT","Saint Vincent and the Grenadines","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/VCT/L0/vct_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54650,670,"VCT","Saint Vincent and the Grenadines","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/VCT/Subnational/vct_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54651,674,"SMR","San Marino","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SMR/L0/smr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54652,674,"SMR","San Marino","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SMR/Subnational/smr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54653,678,"STP","Sao Tome and Principe","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/STP/L0/stp_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54654,678,"STP","Sao Tome and Principe","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/STP/Subnational/stp_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54655,682,"SAU","Saudi Arabia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SAU/L0/sau_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54656,682,"SAU","Saudi Arabia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SAU/Subnational/sau_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54657,686,"SEN","Senegal","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SEN/L0/sen_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54658,686,"SEN","Senegal","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SEN/Subnational/sen_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54659,688,"SRB","Serbia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SRB/L0/srb_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54660,688,"SRB","Serbia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SRB/Subnational/srb_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54661,690,"SYC","Seychelles","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SYC/L0/syc_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54662,690,"SYC","Seychelles","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SYC/Subnational/syc_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54663,694,"SLE","Sierra Leone","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SLE/L0/sle_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54664,694,"SLE","Sierra Leone","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SLE/Subnational/sle_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54665,702,"SGP","Singapore","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SGP/L0/sgp_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54666,702,"SGP","Singapore","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SGP/Subnational/sgp_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54667,703,"SVK","Slovakia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SVK/L0/svk_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54668,703,"SVK","Slovakia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SVK/Subnational/svk_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54669,704,"VNM","Vietnam","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/VNM/L0/vnm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54670,704,"VNM","Vietnam","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/VNM/Subnational/vnm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54671,705,"SVN","Slovenia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SVN/L0/svn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54672,705,"SVN","Slovenia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SVN/Subnational/svn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54673,706,"SOM","Somalia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SOM/L0/som_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54674,706,"SOM","Somalia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SOM/Subnational/som_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54675,710,"ZAF","South Africa","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ZAF/L0/zaf_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54676,710,"ZAF","South Africa","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ZAF/Subnational/zaf_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54677,716,"ZWE","Zimbabwe","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ZWE/L0/zwe_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54678,716,"ZWE","Zimbabwe","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ZWE/Subnational/zwe_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54679,724,"ESP","Spain","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ESP/L0/esp_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54680,724,"ESP","Spain","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ESP/Subnational/esp_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54681,728,"SSD","South Sudan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SSD/L0/ssd_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54682,728,"SSD","South Sudan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SSD/Subnational/ssd_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54683,729,"SDN","Sudan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SDN/L0/sdn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54684,729,"SDN","Sudan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SDN/Subnational/sdn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54685,732,"ESH","Western Sahara","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ESH/L0/esh_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54686,732,"ESH","Western Sahara","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ESH/Subnational/esh_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54687,740,"SUR","Suriname","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SUR/L0/sur_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54688,740,"SUR","Suriname","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SUR/Subnational/sur_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54689,744,"SJM","Svalbard and Jan Mayen Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SJM/L0/sjm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54690,744,"SJM","Svalbard and Jan Mayen Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SJM/Subnational/sjm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54691,748,"SWZ","Swaziland","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SWZ/L0/swz_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54692,748,"SWZ","Swaziland","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SWZ/Subnational/swz_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54693,752,"SWE","Sweden","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SWE/L0/swe_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54694,752,"SWE","Sweden","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SWE/Subnational/swe_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54695,756,"CHE","Switzerland","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/CHE/L0/che_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54696,756,"CHE","Switzerland","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/CHE/Subnational/che_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54697,760,"SYR","Syria","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SYR/L0/syr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54698,760,"SYR","Syria","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SYR/Subnational/syr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54699,762,"TJK","Tajikistan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TJK/L0/tjk_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54700,762,"TJK","Tajikistan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TJK/Subnational/tjk_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54701,764,"THA","Thailand","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/THA/L0/tha_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54702,764,"THA","Thailand","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/THA/Subnational/tha_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54703,768,"TGO","Togo","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TGO/L0/tgo_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54704,768,"TGO","Togo","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TGO/Subnational/tgo_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54705,772,"TKL","Tokelau","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TKL/L0/tkl_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54706,772,"TKL","Tokelau","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TKL/Subnational/tkl_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54707,776,"TON","Tonga","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TON/L0/ton_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54708,776,"TON","Tonga","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TON/Subnational/ton_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54709,780,"TTO","Trinidad and Tobago","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TTO/L0/tto_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54710,780,"TTO","Trinidad and Tobago","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TTO/Subnational/tto_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54711,784,"ARE","United Arab Emirates","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ARE/L0/are_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54712,784,"ARE","United Arab Emirates","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ARE/Subnational/are_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54713,788,"TUN","Tunisia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TUN/L0/tun_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54714,788,"TUN","Tunisia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TUN/Subnational/tun_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54715,792,"TUR","Turkey","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TUR/L0/tur_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54716,792,"TUR","Turkey","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TUR/Subnational/tur_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54717,795,"TKM","Turkmenistan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TKM/L0/tkm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54718,795,"TKM","Turkmenistan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TKM/Subnational/tkm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54719,796,"TCA","Turks and Caicos Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TCA/L0/tca_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54720,796,"TCA","Turks and Caicos Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TCA/Subnational/tca_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54721,798,"TUV","Tuvalu","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TUV/L0/tuv_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54722,798,"TUV","Tuvalu","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TUV/Subnational/tuv_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54723,800,"UGA","Uganda","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/UGA/L0/uga_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54724,800,"UGA","Uganda","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/UGA/Subnational/uga_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54725,804,"UKR","Ukraine","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/UKR/L0/ukr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54726,804,"UKR","Ukraine","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/UKR/Subnational/ukr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54727,807,"MKD","Macedonia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/MKD/L0/mkd_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54728,807,"MKD","Macedonia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/MKD/Subnational/mkd_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54729,818,"EGY","Egypt","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/EGY/L0/egy_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54730,818,"EGY","Egypt","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/EGY/Subnational/egy_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54731,826,"GBR","United Kingdom","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GBR/L0/gbr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54732,826,"GBR","United Kingdom","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GBR/Subnational/gbr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54733,831,"GGY","Guernsey","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/GGY/L0/ggy_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54734,831,"GGY","Guernsey","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/GGY/Subnational/ggy_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54735,832,"JEY","Jersey","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/JEY/L0/jey_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54736,832,"JEY","Jersey","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/JEY/Subnational/jey_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54737,833,"IMN","Isle of Man","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/IMN/L0/imn_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54738,833,"IMN","Isle of Man","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/IMN/Subnational/imn_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54739,834,"TZA","Tanzania","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/TZA/L0/tza_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54740,834,"TZA","Tanzania","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/TZA/Subnational/tza_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54741,854,"BFA","Burkina Faso","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/BFA/L0/bfa_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54742,854,"BFA","Burkina Faso","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/BFA/Subnational/bfa_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54743,858,"URY","Uruguay","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/URY/L0/ury_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54744,858,"URY","Uruguay","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/URY/Subnational/ury_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54745,860,"UZB","Uzbekistan","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/UZB/L0/uzb_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54746,860,"UZB","Uzbekistan","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/UZB/Subnational/uzb_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54747,862,"VEN","Venezuela","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/VEN/L0/ven_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54748,862,"VEN","Venezuela","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/VEN/Subnational/ven_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54749,876,"WLF","Wallis and Futuna","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/WLF/L0/wlf_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54750,876,"WLF","Wallis and Futuna","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/WLF/Subnational/wlf_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54751,882,"WSM","Samoa","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/WSM/L0/wsm_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54752,882,"WSM","Samoa","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/WSM/Subnational/wsm_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54753,887,"YEM","Yemen","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/YEM/L0/yem_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54754,887,"YEM","Yemen","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/YEM/Subnational/yem_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54755,894,"ZMB","Zambia","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/ZMB/L0/zmb_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54756,894,"ZMB","Zambia","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/ZMB/Subnational/zmb_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54757,900,"KOS","Kosovo","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/KOS/L0/kos_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54758,900,"KOS","Kosovo","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/KOS/Subnational/kos_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54759,901,"SPR","Spratly Islands","level0_100m_2000_2020","GIS/Mastergrid/Global_2000_2020/SPR/L0/spr_level0_100m_2000_2020.tif","Countries, territories, and dependencies 2000-2020"
54760,901,"SPR","Spratly Islands","subnational_admin_2000_2020","GIS/Mastergrid/Global_2000_2020/SPR/Subnational/spr_subnational_admin_2000_2020.tif","Subnational administrative units 2000-2020"
54761,643,"RUS","Russia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/RUS/OSM/DST/rus_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54762,643,"RUS","Russia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/RUS/OSM/DST/rus_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54763,643,"RUS","Russia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/RUS/OSM/DST/rus_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54764,360,"IDN","Indonesia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/IDN/OSM/DST/idn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54765,360,"IDN","Indonesia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/IDN/OSM/DST/idn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54766,360,"IDN","Indonesia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/IDN/OSM/DST/idn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54767,840,"USA","United States","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/USA/OSM/DST/usa_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54768,840,"USA","United States","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/USA/OSM/DST/usa_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54769,840,"USA","United States","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/USA/OSM/DST/usa_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54770,850,"VIR","Virgin_Islands_U_S","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/VIR/OSM/DST/vir_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54771,850,"VIR","Virgin_Islands_U_S","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/VIR/OSM/DST/vir_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54772,850,"VIR","Virgin_Islands_U_S","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/VIR/OSM/DST/vir_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54773,304,"GRL","Greenland","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GRL/OSM/DST/grl_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54774,304,"GRL","Greenland","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GRL/OSM/DST/grl_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54775,304,"GRL","Greenland","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GRL/OSM/DST/grl_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54776,156,"CHN","China","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CHN/OSM/DST/chn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54777,156,"CHN","China","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CHN/OSM/DST/chn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54778,156,"CHN","China","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CHN/OSM/DST/chn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54779,36,"AUS","Australia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/AUS/OSM/DST/aus_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54780,36,"AUS","Australia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/AUS/OSM/DST/aus_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54781,36,"AUS","Australia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/AUS/OSM/DST/aus_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54782,76,"BRA","Brazil","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BRA/OSM/DST/bra_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54783,76,"BRA","Brazil","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BRA/OSM/DST/bra_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54784,76,"BRA","Brazil","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BRA/OSM/DST/bra_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54785,124,"CAN","Canada","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CAN/OSM/DST/can_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54786,124,"CAN","Canada","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CAN/OSM/DST/can_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54787,124,"CAN","Canada","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CAN/OSM/DST/can_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54788,152,"CHL","Chile","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CHL/OSM/DST/chl_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54789,152,"CHL","Chile","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CHL/OSM/DST/chl_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54790,152,"CHL","Chile","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CHL/OSM/DST/chl_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54791,4,"AFG","Afghanistan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/AFG/OSM/DST/afg_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54792,4,"AFG","Afghanistan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/AFG/OSM/DST/afg_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54793,4,"AFG","Afghanistan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/AFG/OSM/DST/afg_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54794,8,"ALB","Albania","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ALB/OSM/DST/alb_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54795,8,"ALB","Albania","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ALB/OSM/DST/alb_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54796,8,"ALB","Albania","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ALB/OSM/DST/alb_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54797,10,"ATA","Antarctica","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ATA/OSM/DST/ata_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54798,10,"ATA","Antarctica","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ATA/OSM/DST/ata_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54799,10,"ATA","Antarctica","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ATA/OSM/DST/ata_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54800,12,"DZA","Algeria","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/DZA/OSM/DST/dza_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54801,12,"DZA","Algeria","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/DZA/OSM/DST/dza_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54802,12,"DZA","Algeria","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/DZA/OSM/DST/dza_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54803,16,"ASM","American Samoa","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ASM/OSM/DST/asm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54804,16,"ASM","American Samoa","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ASM/OSM/DST/asm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54805,16,"ASM","American Samoa","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ASM/OSM/DST/asm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54806,20,"AND","Andorra","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/AND/OSM/DST/and_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54807,20,"AND","Andorra","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/AND/OSM/DST/and_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54808,20,"AND","Andorra","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/AND/OSM/DST/and_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54809,24,"AGO","Angola","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/AGO/OSM/DST/ago_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54810,24,"AGO","Angola","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/AGO/OSM/DST/ago_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54811,24,"AGO","Angola","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/AGO/OSM/DST/ago_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54812,28,"ATG","Antigua and Barbuda","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ATG/OSM/DST/atg_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54813,28,"ATG","Antigua and Barbuda","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ATG/OSM/DST/atg_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54814,28,"ATG","Antigua and Barbuda","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ATG/OSM/DST/atg_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54815,31,"AZE","Azerbaijan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/AZE/OSM/DST/aze_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54816,31,"AZE","Azerbaijan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/AZE/OSM/DST/aze_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54817,31,"AZE","Azerbaijan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/AZE/OSM/DST/aze_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54818,32,"ARG","Argentina","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ARG/OSM/DST/arg_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54819,32,"ARG","Argentina","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ARG/OSM/DST/arg_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54820,32,"ARG","Argentina","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ARG/OSM/DST/arg_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54821,40,"AUT","Austria","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/AUT/OSM/DST/aut_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54822,40,"AUT","Austria","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/AUT/OSM/DST/aut_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54823,40,"AUT","Austria","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/AUT/OSM/DST/aut_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54824,44,"BHS","Bahamas","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BHS/OSM/DST/bhs_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54825,44,"BHS","Bahamas","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BHS/OSM/DST/bhs_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54826,44,"BHS","Bahamas","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BHS/OSM/DST/bhs_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54827,48,"BHR","Bahrain","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BHR/OSM/DST/bhr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54828,48,"BHR","Bahrain","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BHR/OSM/DST/bhr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54829,48,"BHR","Bahrain","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BHR/OSM/DST/bhr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54830,50,"BGD","Bangladesh","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BGD/OSM/DST/bgd_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54831,50,"BGD","Bangladesh","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BGD/OSM/DST/bgd_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54832,50,"BGD","Bangladesh","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BGD/OSM/DST/bgd_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54833,51,"ARM","Armenia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ARM/OSM/DST/arm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54834,51,"ARM","Armenia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ARM/OSM/DST/arm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54835,51,"ARM","Armenia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ARM/OSM/DST/arm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54836,52,"BRB","Barbados","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BRB/OSM/DST/brb_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54837,52,"BRB","Barbados","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BRB/OSM/DST/brb_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54838,52,"BRB","Barbados","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BRB/OSM/DST/brb_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54839,56,"BEL","Belgium","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BEL/OSM/DST/bel_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54840,56,"BEL","Belgium","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BEL/OSM/DST/bel_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54841,56,"BEL","Belgium","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BEL/OSM/DST/bel_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54842,60,"BMU","Bermuda","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BMU/OSM/DST/bmu_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54843,60,"BMU","Bermuda","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BMU/OSM/DST/bmu_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54844,60,"BMU","Bermuda","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BMU/OSM/DST/bmu_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54845,64,"BTN","Bhutan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BTN/OSM/DST/btn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54846,64,"BTN","Bhutan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BTN/OSM/DST/btn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54847,64,"BTN","Bhutan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BTN/OSM/DST/btn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54848,68,"BOL","Bolivia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BOL/OSM/DST/bol_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54849,68,"BOL","Bolivia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BOL/OSM/DST/bol_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54850,68,"BOL","Bolivia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BOL/OSM/DST/bol_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54851,70,"BIH","Bosnia and Herzegovina","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BIH/OSM/DST/bih_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54852,70,"BIH","Bosnia and Herzegovina","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BIH/OSM/DST/bih_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54853,70,"BIH","Bosnia and Herzegovina","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BIH/OSM/DST/bih_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54854,72,"BWA","Botswana","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BWA/OSM/DST/bwa_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54855,72,"BWA","Botswana","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BWA/OSM/DST/bwa_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54856,72,"BWA","Botswana","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BWA/OSM/DST/bwa_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54857,74,"BVT","Bouvet Island","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BVT/OSM/DST/bvt_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54858,74,"BVT","Bouvet Island","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BVT/OSM/DST/bvt_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54859,74,"BVT","Bouvet Island","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BVT/OSM/DST/bvt_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54860,84,"BLZ","Belize","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BLZ/OSM/DST/blz_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54861,84,"BLZ","Belize","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BLZ/OSM/DST/blz_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54862,84,"BLZ","Belize","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BLZ/OSM/DST/blz_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54863,86,"IOT","British Indian Ocean Territory","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/IOT/OSM/DST/iot_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54864,86,"IOT","British Indian Ocean Territory","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/IOT/OSM/DST/iot_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54865,86,"IOT","British Indian Ocean Territory","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/IOT/OSM/DST/iot_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54866,90,"SLB","Solomon Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SLB/OSM/DST/slb_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54867,90,"SLB","Solomon Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SLB/OSM/DST/slb_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54868,90,"SLB","Solomon Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SLB/OSM/DST/slb_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54869,92,"VGB","British Virgin Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/VGB/OSM/DST/vgb_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54870,92,"VGB","British Virgin Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/VGB/OSM/DST/vgb_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54871,92,"VGB","British Virgin Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/VGB/OSM/DST/vgb_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54872,96,"BRN","Brunei","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BRN/OSM/DST/brn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54873,96,"BRN","Brunei","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BRN/OSM/DST/brn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54874,96,"BRN","Brunei","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BRN/OSM/DST/brn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54875,100,"BGR","Bulgaria","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BGR/OSM/DST/bgr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54876,100,"BGR","Bulgaria","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BGR/OSM/DST/bgr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54877,100,"BGR","Bulgaria","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BGR/OSM/DST/bgr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54878,104,"MMR","Myanmar","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MMR/OSM/DST/mmr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54879,104,"MMR","Myanmar","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MMR/OSM/DST/mmr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54880,104,"MMR","Myanmar","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MMR/OSM/DST/mmr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54881,108,"BDI","Burundi","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BDI/OSM/DST/bdi_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54882,108,"BDI","Burundi","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BDI/OSM/DST/bdi_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54883,108,"BDI","Burundi","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BDI/OSM/DST/bdi_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54884,112,"BLR","Belarus","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BLR/OSM/DST/blr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54885,112,"BLR","Belarus","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BLR/OSM/DST/blr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54886,112,"BLR","Belarus","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BLR/OSM/DST/blr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54887,116,"KHM","Cambodia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/KHM/OSM/DST/khm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54888,116,"KHM","Cambodia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/KHM/OSM/DST/khm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54889,116,"KHM","Cambodia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/KHM/OSM/DST/khm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54890,120,"CMR","Cameroon","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CMR/OSM/DST/cmr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54891,120,"CMR","Cameroon","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CMR/OSM/DST/cmr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54892,120,"CMR","Cameroon","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CMR/OSM/DST/cmr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54893,132,"CPV","Cape Verde","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CPV/OSM/DST/cpv_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54894,132,"CPV","Cape Verde","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CPV/OSM/DST/cpv_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54895,132,"CPV","Cape Verde","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CPV/OSM/DST/cpv_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54896,136,"CYM","Cayman Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CYM/OSM/DST/cym_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54897,136,"CYM","Cayman Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CYM/OSM/DST/cym_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54898,136,"CYM","Cayman Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CYM/OSM/DST/cym_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54899,140,"CAF","Central African Republic","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CAF/OSM/DST/caf_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54900,140,"CAF","Central African Republic","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CAF/OSM/DST/caf_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54901,140,"CAF","Central African Republic","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CAF/OSM/DST/caf_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54902,144,"LKA","Sri Lanka","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LKA/OSM/DST/lka_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54903,144,"LKA","Sri Lanka","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LKA/OSM/DST/lka_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54904,144,"LKA","Sri Lanka","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LKA/OSM/DST/lka_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54905,148,"TCD","Chad","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TCD/OSM/DST/tcd_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54906,148,"TCD","Chad","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TCD/OSM/DST/tcd_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54907,148,"TCD","Chad","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TCD/OSM/DST/tcd_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54908,158,"TWN","Taiwan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TWN/OSM/DST/twn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54909,158,"TWN","Taiwan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TWN/OSM/DST/twn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54910,158,"TWN","Taiwan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TWN/OSM/DST/twn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54911,170,"COL","Colombia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/COL/OSM/DST/col_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54912,170,"COL","Colombia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/COL/OSM/DST/col_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54913,170,"COL","Colombia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/COL/OSM/DST/col_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54914,174,"COM","Comoros","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/COM/OSM/DST/com_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54915,174,"COM","Comoros","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/COM/OSM/DST/com_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54916,174,"COM","Comoros","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/COM/OSM/DST/com_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54917,175,"MYT","Mayotte","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MYT/OSM/DST/myt_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54918,175,"MYT","Mayotte","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MYT/OSM/DST/myt_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54919,175,"MYT","Mayotte","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MYT/OSM/DST/myt_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54920,178,"COG","Republic of Congo","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/COG/OSM/DST/cog_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54921,178,"COG","Republic of Congo","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/COG/OSM/DST/cog_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54922,178,"COG","Republic of Congo","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/COG/OSM/DST/cog_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54923,180,"COD","Democratic Republic of the Congo","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/COD/OSM/DST/cod_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54924,180,"COD","Democratic Republic of the Congo","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/COD/OSM/DST/cod_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54925,180,"COD","Democratic Republic of the Congo","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/COD/OSM/DST/cod_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54926,184,"COK","Cook Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/COK/OSM/DST/cok_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54927,184,"COK","Cook Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/COK/OSM/DST/cok_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54928,184,"COK","Cook Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/COK/OSM/DST/cok_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54929,188,"CRI","Costa Rica","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CRI/OSM/DST/cri_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54930,188,"CRI","Costa Rica","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CRI/OSM/DST/cri_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54931,188,"CRI","Costa Rica","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CRI/OSM/DST/cri_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54932,191,"HRV","Croatia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/HRV/OSM/DST/hrv_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54933,191,"HRV","Croatia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/HRV/OSM/DST/hrv_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54934,191,"HRV","Croatia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/HRV/OSM/DST/hrv_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54935,192,"CUB","Cuba","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CUB/OSM/DST/cub_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54936,192,"CUB","Cuba","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CUB/OSM/DST/cub_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54937,192,"CUB","Cuba","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CUB/OSM/DST/cub_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54938,196,"CYP","Cyprus","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CYP/OSM/DST/cyp_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54939,196,"CYP","Cyprus","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CYP/OSM/DST/cyp_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54940,196,"CYP","Cyprus","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CYP/OSM/DST/cyp_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54941,203,"CZE","Czech Republic","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CZE/OSM/DST/cze_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54942,203,"CZE","Czech Republic","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CZE/OSM/DST/cze_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54943,203,"CZE","Czech Republic","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CZE/OSM/DST/cze_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54944,204,"BEN","Benin","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BEN/OSM/DST/ben_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54945,204,"BEN","Benin","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BEN/OSM/DST/ben_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54946,204,"BEN","Benin","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BEN/OSM/DST/ben_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54947,208,"DNK","Denmark","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/DNK/OSM/DST/dnk_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54948,208,"DNK","Denmark","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/DNK/OSM/DST/dnk_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54949,208,"DNK","Denmark","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/DNK/OSM/DST/dnk_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54950,212,"DMA","Dominica","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/DMA/OSM/DST/dma_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54951,212,"DMA","Dominica","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/DMA/OSM/DST/dma_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54952,212,"DMA","Dominica","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/DMA/OSM/DST/dma_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54953,214,"DOM","Dominican Republic","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/DOM/OSM/DST/dom_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54954,214,"DOM","Dominican Republic","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/DOM/OSM/DST/dom_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54955,214,"DOM","Dominican Republic","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/DOM/OSM/DST/dom_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54956,218,"ECU","Ecuador","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ECU/OSM/DST/ecu_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54957,218,"ECU","Ecuador","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ECU/OSM/DST/ecu_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54958,218,"ECU","Ecuador","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ECU/OSM/DST/ecu_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54959,222,"SLV","El Salvador","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SLV/OSM/DST/slv_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54960,222,"SLV","El Salvador","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SLV/OSM/DST/slv_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54961,222,"SLV","El Salvador","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SLV/OSM/DST/slv_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54962,226,"GNQ","Equatorial Guinea","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GNQ/OSM/DST/gnq_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54963,226,"GNQ","Equatorial Guinea","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GNQ/OSM/DST/gnq_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54964,226,"GNQ","Equatorial Guinea","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GNQ/OSM/DST/gnq_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54965,231,"ETH","Ethiopia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ETH/OSM/DST/eth_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54966,231,"ETH","Ethiopia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ETH/OSM/DST/eth_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54967,231,"ETH","Ethiopia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ETH/OSM/DST/eth_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54968,232,"ERI","Eritrea","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ERI/OSM/DST/eri_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54969,232,"ERI","Eritrea","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ERI/OSM/DST/eri_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54970,232,"ERI","Eritrea","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ERI/OSM/DST/eri_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54971,233,"EST","Estonia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/EST/OSM/DST/est_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54972,233,"EST","Estonia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/EST/OSM/DST/est_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54973,233,"EST","Estonia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/EST/OSM/DST/est_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54974,234,"FRO","Faroe Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/FRO/OSM/DST/fro_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54975,234,"FRO","Faroe Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/FRO/OSM/DST/fro_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54976,234,"FRO","Faroe Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/FRO/OSM/DST/fro_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54977,238,"FLK","Falkland Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/FLK/OSM/DST/flk_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54978,238,"FLK","Falkland Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/FLK/OSM/DST/flk_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54979,238,"FLK","Falkland Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/FLK/OSM/DST/flk_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54980,239,"SGS","South Georgia and the South Sandwich Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SGS/OSM/DST/sgs_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54981,239,"SGS","South Georgia and the South Sandwich Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SGS/OSM/DST/sgs_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54982,239,"SGS","South Georgia and the South Sandwich Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SGS/OSM/DST/sgs_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54983,242,"FJI","Fiji","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/FJI/OSM/DST/fji_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54984,242,"FJI","Fiji","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/FJI/OSM/DST/fji_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54985,242,"FJI","Fiji","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/FJI/OSM/DST/fji_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54986,246,"FIN","Finland","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/FIN/OSM/DST/fin_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54987,246,"FIN","Finland","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/FIN/OSM/DST/fin_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54988,246,"FIN","Finland","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/FIN/OSM/DST/fin_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54989,248,"ALA","Aland Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ALA/OSM/DST/ala_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54990,248,"ALA","Aland Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ALA/OSM/DST/ala_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54991,248,"ALA","Aland Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ALA/OSM/DST/ala_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54992,250,"FRA","France","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/FRA/OSM/DST/fra_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54993,250,"FRA","France","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/FRA/OSM/DST/fra_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54994,250,"FRA","France","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/FRA/OSM/DST/fra_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54995,254,"GUF","French Guiana","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GUF/OSM/DST/guf_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54996,254,"GUF","French Guiana","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GUF/OSM/DST/guf_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
54997,254,"GUF","French Guiana","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GUF/OSM/DST/guf_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
54998,258,"PYF","French Polynesia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PYF/OSM/DST/pyf_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
54999,258,"PYF","French Polynesia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PYF/OSM/DST/pyf_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55000,258,"PYF","French Polynesia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PYF/OSM/DST/pyf_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55001,260,"ATF","French Southern Territories","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ATF/OSM/DST/atf_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55002,260,"ATF","French Southern Territories","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ATF/OSM/DST/atf_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55003,260,"ATF","French Southern Territories","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ATF/OSM/DST/atf_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55004,262,"DJI","Djibouti","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/DJI/OSM/DST/dji_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55005,262,"DJI","Djibouti","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/DJI/OSM/DST/dji_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55006,262,"DJI","Djibouti","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/DJI/OSM/DST/dji_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55007,266,"GAB","Gabon","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GAB/OSM/DST/gab_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55008,266,"GAB","Gabon","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GAB/OSM/DST/gab_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55009,266,"GAB","Gabon","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GAB/OSM/DST/gab_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55010,268,"GEO","Georgia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GEO/OSM/DST/geo_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55011,268,"GEO","Georgia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GEO/OSM/DST/geo_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55012,268,"GEO","Georgia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GEO/OSM/DST/geo_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55013,270,"GMB","Gambia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GMB/OSM/DST/gmb_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55014,270,"GMB","Gambia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GMB/OSM/DST/gmb_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55015,270,"GMB","Gambia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GMB/OSM/DST/gmb_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55016,275,"PSE","Palestina","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PSE/OSM/DST/pse_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55017,275,"PSE","Palestina","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PSE/OSM/DST/pse_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55018,275,"PSE","Palestina","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PSE/OSM/DST/pse_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55019,276,"DEU","Germany","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/DEU/OSM/DST/deu_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55020,276,"DEU","Germany","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/DEU/OSM/DST/deu_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55021,276,"DEU","Germany","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/DEU/OSM/DST/deu_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55022,288,"GHA","Ghana","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GHA/OSM/DST/gha_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55023,288,"GHA","Ghana","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GHA/OSM/DST/gha_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55024,288,"GHA","Ghana","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GHA/OSM/DST/gha_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55025,292,"GIB","Gibraltar","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GIB/OSM/DST/gib_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55026,292,"GIB","Gibraltar","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GIB/OSM/DST/gib_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55027,292,"GIB","Gibraltar","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GIB/OSM/DST/gib_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55028,296,"KIR","Kiribati","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/KIR/OSM/DST/kir_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55029,296,"KIR","Kiribati","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/KIR/OSM/DST/kir_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55030,296,"KIR","Kiribati","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/KIR/OSM/DST/kir_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55031,300,"GRC","Greece","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GRC/OSM/DST/grc_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55032,300,"GRC","Greece","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GRC/OSM/DST/grc_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55033,300,"GRC","Greece","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GRC/OSM/DST/grc_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55034,308,"GRD","Grenada","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GRD/OSM/DST/grd_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55035,308,"GRD","Grenada","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GRD/OSM/DST/grd_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55036,308,"GRD","Grenada","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GRD/OSM/DST/grd_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55037,312,"GLP","Guadeloupe","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GLP/OSM/DST/glp_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55038,312,"GLP","Guadeloupe","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GLP/OSM/DST/glp_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55039,312,"GLP","Guadeloupe","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GLP/OSM/DST/glp_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55040,316,"GUM","Guam","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GUM/OSM/DST/gum_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55041,316,"GUM","Guam","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GUM/OSM/DST/gum_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55042,316,"GUM","Guam","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GUM/OSM/DST/gum_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55043,320,"GTM","Guatemala","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GTM/OSM/DST/gtm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55044,320,"GTM","Guatemala","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GTM/OSM/DST/gtm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55045,320,"GTM","Guatemala","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GTM/OSM/DST/gtm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55046,324,"GIN","Guinea","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GIN/OSM/DST/gin_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55047,324,"GIN","Guinea","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GIN/OSM/DST/gin_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55048,324,"GIN","Guinea","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GIN/OSM/DST/gin_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55049,328,"GUY","Guyana","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GUY/OSM/DST/guy_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55050,328,"GUY","Guyana","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GUY/OSM/DST/guy_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55051,328,"GUY","Guyana","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GUY/OSM/DST/guy_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55052,332,"HTI","Haiti","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/HTI/OSM/DST/hti_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55053,332,"HTI","Haiti","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/HTI/OSM/DST/hti_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55054,332,"HTI","Haiti","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/HTI/OSM/DST/hti_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55055,334,"HMD","Heard Island and McDonald Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/HMD/OSM/DST/hmd_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55056,334,"HMD","Heard Island and McDonald Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/HMD/OSM/DST/hmd_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55057,334,"HMD","Heard Island and McDonald Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/HMD/OSM/DST/hmd_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55058,336,"VAT","Vatican City","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/VAT/OSM/DST/vat_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55059,336,"VAT","Vatican City","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/VAT/OSM/DST/vat_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55060,336,"VAT","Vatican City","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/VAT/OSM/DST/vat_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55061,340,"HND","Honduras","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/HND/OSM/DST/hnd_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55062,340,"HND","Honduras","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/HND/OSM/DST/hnd_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55063,340,"HND","Honduras","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/HND/OSM/DST/hnd_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55064,344,"HKG","Hong Kong","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/HKG/OSM/DST/hkg_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55065,344,"HKG","Hong Kong","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/HKG/OSM/DST/hkg_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55066,344,"HKG","Hong Kong","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/HKG/OSM/DST/hkg_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55067,348,"HUN","Hungary","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/HUN/OSM/DST/hun_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55068,348,"HUN","Hungary","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/HUN/OSM/DST/hun_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55069,348,"HUN","Hungary","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/HUN/OSM/DST/hun_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55070,352,"ISL","Iceland","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ISL/OSM/DST/isl_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55071,352,"ISL","Iceland","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ISL/OSM/DST/isl_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55072,352,"ISL","Iceland","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ISL/OSM/DST/isl_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55073,356,"IND","India","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/IND/OSM/DST/ind_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55074,356,"IND","India","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/IND/OSM/DST/ind_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55075,356,"IND","India","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/IND/OSM/DST/ind_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55076,364,"IRN","Iran","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/IRN/OSM/DST/irn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55077,364,"IRN","Iran","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/IRN/OSM/DST/irn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55078,364,"IRN","Iran","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/IRN/OSM/DST/irn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55079,368,"IRQ","Iraq","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/IRQ/OSM/DST/irq_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55080,368,"IRQ","Iraq","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/IRQ/OSM/DST/irq_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55081,368,"IRQ","Iraq","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/IRQ/OSM/DST/irq_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55082,372,"IRL","Ireland","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/IRL/OSM/DST/irl_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55083,372,"IRL","Ireland","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/IRL/OSM/DST/irl_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55084,372,"IRL","Ireland","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/IRL/OSM/DST/irl_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55085,376,"ISR","Israel","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ISR/OSM/DST/isr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55086,376,"ISR","Israel","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ISR/OSM/DST/isr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55087,376,"ISR","Israel","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ISR/OSM/DST/isr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55088,380,"ITA","Italy","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ITA/OSM/DST/ita_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55089,380,"ITA","Italy","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ITA/OSM/DST/ita_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55090,380,"ITA","Italy","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ITA/OSM/DST/ita_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55091,384,"CIV","CIte dIvoire","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CIV/OSM/DST/civ_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55092,384,"CIV","CIte dIvoire","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CIV/OSM/DST/civ_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55093,384,"CIV","CIte dIvoire","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CIV/OSM/DST/civ_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55094,388,"JAM","Jamaica","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/JAM/OSM/DST/jam_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55095,388,"JAM","Jamaica","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/JAM/OSM/DST/jam_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55096,388,"JAM","Jamaica","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/JAM/OSM/DST/jam_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55097,392,"JPN","Japan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/JPN/OSM/DST/jpn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55098,392,"JPN","Japan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/JPN/OSM/DST/jpn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55099,392,"JPN","Japan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/JPN/OSM/DST/jpn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55100,398,"KAZ","Kazakhstan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/KAZ/OSM/DST/kaz_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55101,398,"KAZ","Kazakhstan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/KAZ/OSM/DST/kaz_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55102,398,"KAZ","Kazakhstan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/KAZ/OSM/DST/kaz_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55103,400,"JOR","Jordan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/JOR/OSM/DST/jor_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55104,400,"JOR","Jordan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/JOR/OSM/DST/jor_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55105,400,"JOR","Jordan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/JOR/OSM/DST/jor_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55106,404,"KEN","Kenya","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/KEN/OSM/DST/ken_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55107,404,"KEN","Kenya","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/KEN/OSM/DST/ken_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55108,404,"KEN","Kenya","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/KEN/OSM/DST/ken_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55109,408,"PRK","North Korea","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PRK/OSM/DST/prk_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55110,408,"PRK","North Korea","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PRK/OSM/DST/prk_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55111,408,"PRK","North Korea","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PRK/OSM/DST/prk_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55112,410,"KOR","South Korea","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/KOR/OSM/DST/kor_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55113,410,"KOR","South Korea","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/KOR/OSM/DST/kor_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55114,410,"KOR","South Korea","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/KOR/OSM/DST/kor_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55115,414,"KWT","Kuwait","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/KWT/OSM/DST/kwt_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55116,414,"KWT","Kuwait","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/KWT/OSM/DST/kwt_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55117,414,"KWT","Kuwait","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/KWT/OSM/DST/kwt_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55118,417,"KGZ","Kyrgyzstan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/KGZ/OSM/DST/kgz_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55119,417,"KGZ","Kyrgyzstan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/KGZ/OSM/DST/kgz_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55120,417,"KGZ","Kyrgyzstan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/KGZ/OSM/DST/kgz_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55121,418,"LAO","Laos","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LAO/OSM/DST/lao_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55122,418,"LAO","Laos","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LAO/OSM/DST/lao_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55123,418,"LAO","Laos","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LAO/OSM/DST/lao_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55124,422,"LBN","Lebanon","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LBN/OSM/DST/lbn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55125,422,"LBN","Lebanon","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LBN/OSM/DST/lbn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55126,422,"LBN","Lebanon","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LBN/OSM/DST/lbn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55127,426,"LSO","Lesotho","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LSO/OSM/DST/lso_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55128,426,"LSO","Lesotho","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LSO/OSM/DST/lso_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55129,426,"LSO","Lesotho","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LSO/OSM/DST/lso_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55130,428,"LVA","Latvia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LVA/OSM/DST/lva_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55131,428,"LVA","Latvia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LVA/OSM/DST/lva_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55132,428,"LVA","Latvia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LVA/OSM/DST/lva_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55133,430,"LBR","Liberia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LBR/OSM/DST/lbr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55134,430,"LBR","Liberia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LBR/OSM/DST/lbr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55135,430,"LBR","Liberia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LBR/OSM/DST/lbr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55136,434,"LBY","Libya","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LBY/OSM/DST/lby_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55137,434,"LBY","Libya","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LBY/OSM/DST/lby_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55138,434,"LBY","Libya","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LBY/OSM/DST/lby_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55139,438,"LIE","Liechtenstein","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LIE/OSM/DST/lie_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55140,438,"LIE","Liechtenstein","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LIE/OSM/DST/lie_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55141,438,"LIE","Liechtenstein","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LIE/OSM/DST/lie_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55142,440,"LTU","Lithuania","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LTU/OSM/DST/ltu_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55143,440,"LTU","Lithuania","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LTU/OSM/DST/ltu_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55144,440,"LTU","Lithuania","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LTU/OSM/DST/ltu_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55145,442,"LUX","Luxembourg","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LUX/OSM/DST/lux_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55146,442,"LUX","Luxembourg","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LUX/OSM/DST/lux_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55147,442,"LUX","Luxembourg","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LUX/OSM/DST/lux_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55148,446,"MAC","Macao","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MAC/OSM/DST/mac_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55149,446,"MAC","Macao","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MAC/OSM/DST/mac_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55150,446,"MAC","Macao","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MAC/OSM/DST/mac_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55151,450,"MDG","Madagascar","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MDG/OSM/DST/mdg_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55152,450,"MDG","Madagascar","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MDG/OSM/DST/mdg_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55153,450,"MDG","Madagascar","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MDG/OSM/DST/mdg_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55154,454,"MWI","Malawi","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MWI/OSM/DST/mwi_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55155,454,"MWI","Malawi","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MWI/OSM/DST/mwi_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55156,454,"MWI","Malawi","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MWI/OSM/DST/mwi_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55157,458,"MYS","Malaysia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MYS/OSM/DST/mys_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55158,458,"MYS","Malaysia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MYS/OSM/DST/mys_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55159,458,"MYS","Malaysia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MYS/OSM/DST/mys_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55160,462,"MDV","Maldives","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MDV/OSM/DST/mdv_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55161,462,"MDV","Maldives","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MDV/OSM/DST/mdv_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55162,462,"MDV","Maldives","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MDV/OSM/DST/mdv_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55163,466,"MLI","Mali","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MLI/OSM/DST/mli_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55164,466,"MLI","Mali","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MLI/OSM/DST/mli_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55165,466,"MLI","Mali","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MLI/OSM/DST/mli_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55166,470,"MLT","Malta","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MLT/OSM/DST/mlt_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55167,470,"MLT","Malta","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MLT/OSM/DST/mlt_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55168,470,"MLT","Malta","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MLT/OSM/DST/mlt_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55169,474,"MTQ","Martinique","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MTQ/OSM/DST/mtq_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55170,474,"MTQ","Martinique","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MTQ/OSM/DST/mtq_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55171,474,"MTQ","Martinique","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MTQ/OSM/DST/mtq_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55172,478,"MRT","Mauritania","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MRT/OSM/DST/mrt_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55173,478,"MRT","Mauritania","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MRT/OSM/DST/mrt_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55174,478,"MRT","Mauritania","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MRT/OSM/DST/mrt_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55175,480,"MUS","Mauritius","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MUS/OSM/DST/mus_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55176,480,"MUS","Mauritius","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MUS/OSM/DST/mus_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55177,480,"MUS","Mauritius","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MUS/OSM/DST/mus_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55178,484,"MEX","Mexico","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MEX/OSM/DST/mex_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55179,484,"MEX","Mexico","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MEX/OSM/DST/mex_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55180,484,"MEX","Mexico","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MEX/OSM/DST/mex_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55181,492,"MCO","Monaco","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MCO/OSM/DST/mco_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55182,492,"MCO","Monaco","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MCO/OSM/DST/mco_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55183,492,"MCO","Monaco","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MCO/OSM/DST/mco_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55184,496,"MNG","Mongolia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MNG/OSM/DST/mng_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55185,496,"MNG","Mongolia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MNG/OSM/DST/mng_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55186,496,"MNG","Mongolia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MNG/OSM/DST/mng_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55187,498,"MDA","Moldova","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MDA/OSM/DST/mda_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55188,498,"MDA","Moldova","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MDA/OSM/DST/mda_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55189,498,"MDA","Moldova","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MDA/OSM/DST/mda_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55190,499,"MNE","Montenegro","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MNE/OSM/DST/mne_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55191,499,"MNE","Montenegro","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MNE/OSM/DST/mne_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55192,499,"MNE","Montenegro","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MNE/OSM/DST/mne_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55193,500,"MSR","Montserrat","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MSR/OSM/DST/msr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55194,500,"MSR","Montserrat","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MSR/OSM/DST/msr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55195,500,"MSR","Montserrat","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MSR/OSM/DST/msr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55196,504,"MAR","Morocco","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MAR/OSM/DST/mar_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55197,504,"MAR","Morocco","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MAR/OSM/DST/mar_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55198,504,"MAR","Morocco","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MAR/OSM/DST/mar_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55199,508,"MOZ","Mozambique","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MOZ/OSM/DST/moz_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55200,508,"MOZ","Mozambique","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MOZ/OSM/DST/moz_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55201,508,"MOZ","Mozambique","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MOZ/OSM/DST/moz_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55202,512,"OMN","Oman","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/OMN/OSM/DST/omn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55203,512,"OMN","Oman","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/OMN/OSM/DST/omn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55204,512,"OMN","Oman","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/OMN/OSM/DST/omn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55205,516,"NAM","Namibia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NAM/OSM/DST/nam_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55206,516,"NAM","Namibia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NAM/OSM/DST/nam_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55207,516,"NAM","Namibia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NAM/OSM/DST/nam_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55208,520,"NRU","Nauru","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NRU/OSM/DST/nru_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55209,520,"NRU","Nauru","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NRU/OSM/DST/nru_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55210,520,"NRU","Nauru","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NRU/OSM/DST/nru_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55211,524,"NPL","Nepal","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NPL/OSM/DST/npl_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55212,524,"NPL","Nepal","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NPL/OSM/DST/npl_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55213,524,"NPL","Nepal","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NPL/OSM/DST/npl_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55214,528,"NLD","Netherlands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NLD/OSM/DST/nld_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55215,528,"NLD","Netherlands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NLD/OSM/DST/nld_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55216,528,"NLD","Netherlands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NLD/OSM/DST/nld_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55217,531,"CUW","Curacao","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CUW/OSM/DST/cuw_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55218,531,"CUW","Curacao","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CUW/OSM/DST/cuw_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55219,531,"CUW","Curacao","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CUW/OSM/DST/cuw_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55220,533,"ABW","Aruba","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ABW/OSM/DST/abw_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55221,533,"ABW","Aruba","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ABW/OSM/DST/abw_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55222,533,"ABW","Aruba","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ABW/OSM/DST/abw_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55223,534,"SXM","Sint Maarten (Dutch part)","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SXM/OSM/DST/sxm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55224,534,"SXM","Sint Maarten (Dutch part)","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SXM/OSM/DST/sxm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55225,534,"SXM","Sint Maarten (Dutch part)","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SXM/OSM/DST/sxm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55226,535,"BES","Bonaire, Sint Eustatius and Saba","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BES/OSM/DST/bes_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55227,535,"BES","Bonaire, Sint Eustatius and Saba","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BES/OSM/DST/bes_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55228,535,"BES","Bonaire, Sint Eustatius and Saba","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BES/OSM/DST/bes_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55229,540,"NCL","New Caledonia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NCL/OSM/DST/ncl_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55230,540,"NCL","New Caledonia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NCL/OSM/DST/ncl_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55231,540,"NCL","New Caledonia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NCL/OSM/DST/ncl_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55232,548,"VUT","Vanuatu","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/VUT/OSM/DST/vut_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55233,548,"VUT","Vanuatu","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/VUT/OSM/DST/vut_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55234,548,"VUT","Vanuatu","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/VUT/OSM/DST/vut_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55235,554,"NZL","New Zealand","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NZL/OSM/DST/nzl_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55236,554,"NZL","New Zealand","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NZL/OSM/DST/nzl_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55237,554,"NZL","New Zealand","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NZL/OSM/DST/nzl_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55238,558,"NIC","Nicaragua","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NIC/OSM/DST/nic_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55239,558,"NIC","Nicaragua","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NIC/OSM/DST/nic_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55240,558,"NIC","Nicaragua","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NIC/OSM/DST/nic_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55241,562,"NER","Niger","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NER/OSM/DST/ner_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55242,562,"NER","Niger","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NER/OSM/DST/ner_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55243,562,"NER","Niger","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NER/OSM/DST/ner_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55244,566,"NGA","Nigeria","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NGA/OSM/DST/nga_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55245,566,"NGA","Nigeria","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NGA/OSM/DST/nga_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55246,566,"NGA","Nigeria","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NGA/OSM/DST/nga_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55247,570,"NIU","Niue","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NIU/OSM/DST/niu_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55248,570,"NIU","Niue","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NIU/OSM/DST/niu_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55249,570,"NIU","Niue","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NIU/OSM/DST/niu_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55250,574,"NFK","Norfolk Island","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NFK/OSM/DST/nfk_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55251,574,"NFK","Norfolk Island","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NFK/OSM/DST/nfk_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55252,574,"NFK","Norfolk Island","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NFK/OSM/DST/nfk_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55253,578,"NOR","Norway","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/NOR/OSM/DST/nor_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55254,578,"NOR","Norway","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/NOR/OSM/DST/nor_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55255,578,"NOR","Norway","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/NOR/OSM/DST/nor_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55256,580,"MNP","Northern Mariana Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MNP/OSM/DST/mnp_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55257,580,"MNP","Northern Mariana Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MNP/OSM/DST/mnp_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55258,580,"MNP","Northern Mariana Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MNP/OSM/DST/mnp_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55259,581,"UMI","United States Minor Outlying Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/UMI/OSM/DST/umi_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55260,581,"UMI","United States Minor Outlying Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/UMI/OSM/DST/umi_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55261,581,"UMI","United States Minor Outlying Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/UMI/OSM/DST/umi_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55262,583,"FSM","Micronesia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/FSM/OSM/DST/fsm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55263,583,"FSM","Micronesia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/FSM/OSM/DST/fsm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55264,583,"FSM","Micronesia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/FSM/OSM/DST/fsm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55265,584,"MHL","Marshall Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MHL/OSM/DST/mhl_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55266,584,"MHL","Marshall Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MHL/OSM/DST/mhl_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55267,584,"MHL","Marshall Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MHL/OSM/DST/mhl_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55268,585,"PLW","Palau","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PLW/OSM/DST/plw_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55269,585,"PLW","Palau","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PLW/OSM/DST/plw_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55270,585,"PLW","Palau","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PLW/OSM/DST/plw_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55271,586,"PAK","Pakistan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PAK/OSM/DST/pak_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55272,586,"PAK","Pakistan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PAK/OSM/DST/pak_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55273,586,"PAK","Pakistan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PAK/OSM/DST/pak_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55274,591,"PAN","Panama","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PAN/OSM/DST/pan_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55275,591,"PAN","Panama","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PAN/OSM/DST/pan_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55276,591,"PAN","Panama","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PAN/OSM/DST/pan_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55277,598,"PNG","Papua New Guinea","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PNG/OSM/DST/png_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55278,598,"PNG","Papua New Guinea","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PNG/OSM/DST/png_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55279,598,"PNG","Papua New Guinea","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PNG/OSM/DST/png_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55280,600,"PRY","Paraguay","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PRY/OSM/DST/pry_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55281,600,"PRY","Paraguay","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PRY/OSM/DST/pry_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55282,600,"PRY","Paraguay","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PRY/OSM/DST/pry_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55283,604,"PER","Peru","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PER/OSM/DST/per_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55284,604,"PER","Peru","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PER/OSM/DST/per_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55285,604,"PER","Peru","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PER/OSM/DST/per_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55286,608,"PHL","Philippines","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PHL/OSM/DST/phl_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55287,608,"PHL","Philippines","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PHL/OSM/DST/phl_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55288,608,"PHL","Philippines","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PHL/OSM/DST/phl_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55289,612,"PCN","Pitcairn Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PCN/OSM/DST/pcn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55290,612,"PCN","Pitcairn Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PCN/OSM/DST/pcn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55291,612,"PCN","Pitcairn Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PCN/OSM/DST/pcn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55292,616,"POL","Poland","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/POL/OSM/DST/pol_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55293,616,"POL","Poland","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/POL/OSM/DST/pol_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55294,616,"POL","Poland","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/POL/OSM/DST/pol_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55295,620,"PRT","Portugal","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PRT/OSM/DST/prt_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55296,620,"PRT","Portugal","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PRT/OSM/DST/prt_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55297,620,"PRT","Portugal","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PRT/OSM/DST/prt_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55298,624,"GNB","Guinea-Bissau","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GNB/OSM/DST/gnb_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55299,624,"GNB","Guinea-Bissau","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GNB/OSM/DST/gnb_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55300,624,"GNB","Guinea-Bissau","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GNB/OSM/DST/gnb_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55301,626,"TLS","East Timor","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TLS/OSM/DST/tls_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55302,626,"TLS","East Timor","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TLS/OSM/DST/tls_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55303,626,"TLS","East Timor","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TLS/OSM/DST/tls_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55304,630,"PRI","Puerto Rico","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/PRI/OSM/DST/pri_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55305,630,"PRI","Puerto Rico","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/PRI/OSM/DST/pri_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55306,630,"PRI","Puerto Rico","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/PRI/OSM/DST/pri_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55307,634,"QAT","Qatar","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/QAT/OSM/DST/qat_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55308,634,"QAT","Qatar","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/QAT/OSM/DST/qat_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55309,634,"QAT","Qatar","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/QAT/OSM/DST/qat_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55310,638,"REU","Reunion","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/REU/OSM/DST/reu_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55311,638,"REU","Reunion","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/REU/OSM/DST/reu_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55312,638,"REU","Reunion","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/REU/OSM/DST/reu_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55313,642,"ROU","Romania","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ROU/OSM/DST/rou_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55314,642,"ROU","Romania","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ROU/OSM/DST/rou_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55315,642,"ROU","Romania","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ROU/OSM/DST/rou_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55316,646,"RWA","Rwanda","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/RWA/OSM/DST/rwa_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55317,646,"RWA","Rwanda","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/RWA/OSM/DST/rwa_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55318,646,"RWA","Rwanda","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/RWA/OSM/DST/rwa_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55319,652,"BLM","Saint Barthelemy","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BLM/OSM/DST/blm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55320,652,"BLM","Saint Barthelemy","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BLM/OSM/DST/blm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55321,652,"BLM","Saint Barthelemy","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BLM/OSM/DST/blm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55322,654,"SHN","Saint Helena","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SHN/OSM/DST/shn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55323,654,"SHN","Saint Helena","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SHN/OSM/DST/shn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55324,654,"SHN","Saint Helena","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SHN/OSM/DST/shn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55325,659,"KNA","Saint Kitts and Nevis","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/KNA/OSM/DST/kna_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55326,659,"KNA","Saint Kitts and Nevis","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/KNA/OSM/DST/kna_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55327,659,"KNA","Saint Kitts and Nevis","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/KNA/OSM/DST/kna_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55328,660,"AIA","Anguilla","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/AIA/OSM/DST/aia_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55329,660,"AIA","Anguilla","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/AIA/OSM/DST/aia_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55330,660,"AIA","Anguilla","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/AIA/OSM/DST/aia_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55331,662,"LCA","Saint Lucia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/LCA/OSM/DST/lca_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55332,662,"LCA","Saint Lucia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/LCA/OSM/DST/lca_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55333,662,"LCA","Saint Lucia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/LCA/OSM/DST/lca_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55334,663,"MAF","Saint Martin (French part)","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MAF/OSM/DST/maf_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55335,663,"MAF","Saint Martin (French part)","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MAF/OSM/DST/maf_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55336,663,"MAF","Saint Martin (French part)","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MAF/OSM/DST/maf_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55337,666,"SPM","Saint Pierre and Miquelon","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SPM/OSM/DST/spm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55338,666,"SPM","Saint Pierre and Miquelon","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SPM/OSM/DST/spm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55339,666,"SPM","Saint Pierre and Miquelon","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SPM/OSM/DST/spm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55340,670,"VCT","Saint Vincent and the Grenadines","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/VCT/OSM/DST/vct_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55341,670,"VCT","Saint Vincent and the Grenadines","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/VCT/OSM/DST/vct_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55342,670,"VCT","Saint Vincent and the Grenadines","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/VCT/OSM/DST/vct_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55343,674,"SMR","San Marino","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SMR/OSM/DST/smr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55344,674,"SMR","San Marino","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SMR/OSM/DST/smr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55345,674,"SMR","San Marino","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SMR/OSM/DST/smr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55346,678,"STP","Sao Tome and Principe","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/STP/OSM/DST/stp_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55347,678,"STP","Sao Tome and Principe","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/STP/OSM/DST/stp_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55348,678,"STP","Sao Tome and Principe","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/STP/OSM/DST/stp_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55349,682,"SAU","Saudi Arabia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SAU/OSM/DST/sau_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55350,682,"SAU","Saudi Arabia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SAU/OSM/DST/sau_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55351,682,"SAU","Saudi Arabia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SAU/OSM/DST/sau_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55352,686,"SEN","Senegal","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SEN/OSM/DST/sen_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55353,686,"SEN","Senegal","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SEN/OSM/DST/sen_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55354,686,"SEN","Senegal","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SEN/OSM/DST/sen_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55355,688,"SRB","Serbia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SRB/OSM/DST/srb_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55356,688,"SRB","Serbia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SRB/OSM/DST/srb_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55357,688,"SRB","Serbia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SRB/OSM/DST/srb_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55358,690,"SYC","Seychelles","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SYC/OSM/DST/syc_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55359,690,"SYC","Seychelles","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SYC/OSM/DST/syc_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55360,690,"SYC","Seychelles","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SYC/OSM/DST/syc_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55361,694,"SLE","Sierra Leone","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SLE/OSM/DST/sle_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55362,694,"SLE","Sierra Leone","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SLE/OSM/DST/sle_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55363,694,"SLE","Sierra Leone","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SLE/OSM/DST/sle_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55364,702,"SGP","Singapore","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SGP/OSM/DST/sgp_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55365,702,"SGP","Singapore","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SGP/OSM/DST/sgp_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55366,702,"SGP","Singapore","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SGP/OSM/DST/sgp_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55367,703,"SVK","Slovakia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SVK/OSM/DST/svk_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55368,703,"SVK","Slovakia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SVK/OSM/DST/svk_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55369,703,"SVK","Slovakia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SVK/OSM/DST/svk_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55370,704,"VNM","Vietnam","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/VNM/OSM/DST/vnm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55371,704,"VNM","Vietnam","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/VNM/OSM/DST/vnm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55372,704,"VNM","Vietnam","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/VNM/OSM/DST/vnm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55373,705,"SVN","Slovenia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SVN/OSM/DST/svn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55374,705,"SVN","Slovenia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SVN/OSM/DST/svn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55375,705,"SVN","Slovenia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SVN/OSM/DST/svn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55376,706,"SOM","Somalia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SOM/OSM/DST/som_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55377,706,"SOM","Somalia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SOM/OSM/DST/som_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55378,706,"SOM","Somalia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SOM/OSM/DST/som_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55379,710,"ZAF","South Africa","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ZAF/OSM/DST/zaf_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55380,710,"ZAF","South Africa","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ZAF/OSM/DST/zaf_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55381,710,"ZAF","South Africa","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ZAF/OSM/DST/zaf_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55382,716,"ZWE","Zimbabwe","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ZWE/OSM/DST/zwe_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55383,716,"ZWE","Zimbabwe","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ZWE/OSM/DST/zwe_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55384,716,"ZWE","Zimbabwe","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ZWE/OSM/DST/zwe_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55385,724,"ESP","Spain","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ESP/OSM/DST/esp_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55386,724,"ESP","Spain","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ESP/OSM/DST/esp_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55387,724,"ESP","Spain","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ESP/OSM/DST/esp_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55388,728,"SSD","South Sudan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SSD/OSM/DST/ssd_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55389,728,"SSD","South Sudan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SSD/OSM/DST/ssd_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55390,728,"SSD","South Sudan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SSD/OSM/DST/ssd_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55391,729,"SDN","Sudan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SDN/OSM/DST/sdn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55392,729,"SDN","Sudan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SDN/OSM/DST/sdn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55393,729,"SDN","Sudan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SDN/OSM/DST/sdn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55394,732,"ESH","Western Sahara","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ESH/OSM/DST/esh_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55395,732,"ESH","Western Sahara","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ESH/OSM/DST/esh_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55396,732,"ESH","Western Sahara","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ESH/OSM/DST/esh_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55397,740,"SUR","Suriname","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SUR/OSM/DST/sur_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55398,740,"SUR","Suriname","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SUR/OSM/DST/sur_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55399,740,"SUR","Suriname","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SUR/OSM/DST/sur_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55400,744,"SJM","Svalbard and Jan Mayen Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SJM/OSM/DST/sjm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55401,744,"SJM","Svalbard and Jan Mayen Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SJM/OSM/DST/sjm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55402,744,"SJM","Svalbard and Jan Mayen Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SJM/OSM/DST/sjm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55403,748,"SWZ","Swaziland","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SWZ/OSM/DST/swz_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55404,748,"SWZ","Swaziland","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SWZ/OSM/DST/swz_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55405,748,"SWZ","Swaziland","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SWZ/OSM/DST/swz_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55406,752,"SWE","Sweden","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SWE/OSM/DST/swe_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55407,752,"SWE","Sweden","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SWE/OSM/DST/swe_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55408,752,"SWE","Sweden","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SWE/OSM/DST/swe_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55409,756,"CHE","Switzerland","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/CHE/OSM/DST/che_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55410,756,"CHE","Switzerland","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/CHE/OSM/DST/che_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55411,756,"CHE","Switzerland","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/CHE/OSM/DST/che_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55412,760,"SYR","Syria","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SYR/OSM/DST/syr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55413,760,"SYR","Syria","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SYR/OSM/DST/syr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55414,760,"SYR","Syria","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SYR/OSM/DST/syr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55415,762,"TJK","Tajikistan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TJK/OSM/DST/tjk_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55416,762,"TJK","Tajikistan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TJK/OSM/DST/tjk_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55417,762,"TJK","Tajikistan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TJK/OSM/DST/tjk_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55418,764,"THA","Thailand","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/THA/OSM/DST/tha_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55419,764,"THA","Thailand","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/THA/OSM/DST/tha_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55420,764,"THA","Thailand","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/THA/OSM/DST/tha_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55421,768,"TGO","Togo","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TGO/OSM/DST/tgo_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55422,768,"TGO","Togo","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TGO/OSM/DST/tgo_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55423,768,"TGO","Togo","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TGO/OSM/DST/tgo_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55424,772,"TKL","Tokelau","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TKL/OSM/DST/tkl_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55425,772,"TKL","Tokelau","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TKL/OSM/DST/tkl_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55426,772,"TKL","Tokelau","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TKL/OSM/DST/tkl_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55427,776,"TON","Tonga","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TON/OSM/DST/ton_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55428,776,"TON","Tonga","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TON/OSM/DST/ton_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55429,776,"TON","Tonga","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TON/OSM/DST/ton_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55430,780,"TTO","Trinidad and Tobago","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TTO/OSM/DST/tto_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55431,780,"TTO","Trinidad and Tobago","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TTO/OSM/DST/tto_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55432,780,"TTO","Trinidad and Tobago","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TTO/OSM/DST/tto_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55433,784,"ARE","United Arab Emirates","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ARE/OSM/DST/are_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55434,784,"ARE","United Arab Emirates","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ARE/OSM/DST/are_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55435,784,"ARE","United Arab Emirates","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ARE/OSM/DST/are_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55436,788,"TUN","Tunisia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TUN/OSM/DST/tun_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55437,788,"TUN","Tunisia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TUN/OSM/DST/tun_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55438,788,"TUN","Tunisia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TUN/OSM/DST/tun_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55439,792,"TUR","Turkey","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TUR/OSM/DST/tur_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55440,792,"TUR","Turkey","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TUR/OSM/DST/tur_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55441,792,"TUR","Turkey","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TUR/OSM/DST/tur_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55442,795,"TKM","Turkmenistan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TKM/OSM/DST/tkm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55443,795,"TKM","Turkmenistan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TKM/OSM/DST/tkm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55444,795,"TKM","Turkmenistan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TKM/OSM/DST/tkm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55445,796,"TCA","Turks and Caicos Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TCA/OSM/DST/tca_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55446,796,"TCA","Turks and Caicos Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TCA/OSM/DST/tca_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55447,796,"TCA","Turks and Caicos Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TCA/OSM/DST/tca_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55448,798,"TUV","Tuvalu","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TUV/OSM/DST/tuv_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55449,798,"TUV","Tuvalu","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TUV/OSM/DST/tuv_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55450,798,"TUV","Tuvalu","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TUV/OSM/DST/tuv_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55451,800,"UGA","Uganda","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/UGA/OSM/DST/uga_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55452,800,"UGA","Uganda","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/UGA/OSM/DST/uga_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55453,800,"UGA","Uganda","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/UGA/OSM/DST/uga_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55454,804,"UKR","Ukraine","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/UKR/OSM/DST/ukr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55455,804,"UKR","Ukraine","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/UKR/OSM/DST/ukr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55456,804,"UKR","Ukraine","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/UKR/OSM/DST/ukr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55457,807,"MKD","Macedonia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/MKD/OSM/DST/mkd_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55458,807,"MKD","Macedonia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/MKD/OSM/DST/mkd_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55459,807,"MKD","Macedonia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/MKD/OSM/DST/mkd_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55460,818,"EGY","Egypt","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/EGY/OSM/DST/egy_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55461,818,"EGY","Egypt","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/EGY/OSM/DST/egy_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55462,818,"EGY","Egypt","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/EGY/OSM/DST/egy_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55463,826,"GBR","United Kingdom","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GBR/OSM/DST/gbr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55464,826,"GBR","United Kingdom","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GBR/OSM/DST/gbr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55465,826,"GBR","United Kingdom","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GBR/OSM/DST/gbr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55466,831,"GGY","Guernsey","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/GGY/OSM/DST/ggy_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55467,831,"GGY","Guernsey","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/GGY/OSM/DST/ggy_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55468,831,"GGY","Guernsey","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/GGY/OSM/DST/ggy_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55469,832,"JEY","Jersey","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/JEY/OSM/DST/jey_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55470,832,"JEY","Jersey","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/JEY/OSM/DST/jey_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55471,832,"JEY","Jersey","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/JEY/OSM/DST/jey_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55472,833,"IMN","Isle of Man","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/IMN/OSM/DST/imn_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55473,833,"IMN","Isle of Man","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/IMN/OSM/DST/imn_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55474,833,"IMN","Isle of Man","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/IMN/OSM/DST/imn_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55475,834,"TZA","Tanzania","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/TZA/OSM/DST/tza_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55476,834,"TZA","Tanzania","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/TZA/OSM/DST/tza_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55477,834,"TZA","Tanzania","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/TZA/OSM/DST/tza_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55478,854,"BFA","Burkina Faso","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/BFA/OSM/DST/bfa_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55479,854,"BFA","Burkina Faso","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/BFA/OSM/DST/bfa_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55480,854,"BFA","Burkina Faso","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/BFA/OSM/DST/bfa_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55481,858,"URY","Uruguay","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/URY/OSM/DST/ury_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55482,858,"URY","Uruguay","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/URY/OSM/DST/ury_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55483,858,"URY","Uruguay","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/URY/OSM/DST/ury_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55484,860,"UZB","Uzbekistan","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/UZB/OSM/DST/uzb_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55485,860,"UZB","Uzbekistan","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/UZB/OSM/DST/uzb_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55486,860,"UZB","Uzbekistan","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/UZB/OSM/DST/uzb_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55487,862,"VEN","Venezuela","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/VEN/OSM/DST/ven_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55488,862,"VEN","Venezuela","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/VEN/OSM/DST/ven_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55489,862,"VEN","Venezuela","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/VEN/OSM/DST/ven_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55490,876,"WLF","Wallis and Futuna","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/WLF/OSM/DST/wlf_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55491,876,"WLF","Wallis and Futuna","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/WLF/OSM/DST/wlf_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55492,876,"WLF","Wallis and Futuna","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/WLF/OSM/DST/wlf_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55493,882,"WSM","Samoa","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/WSM/OSM/DST/wsm_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55494,882,"WSM","Samoa","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/WSM/OSM/DST/wsm_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55495,882,"WSM","Samoa","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/WSM/OSM/DST/wsm_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55496,887,"YEM","Yemen","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/YEM/OSM/DST/yem_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55497,887,"YEM","Yemen","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/YEM/OSM/DST/yem_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55498,887,"YEM","Yemen","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/YEM/OSM/DST/yem_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55499,894,"ZMB","Zambia","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/ZMB/OSM/DST/zmb_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55500,894,"ZMB","Zambia","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/ZMB/OSM/DST/zmb_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55501,894,"ZMB","Zambia","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/ZMB/OSM/DST/zmb_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55502,900,"KOS","Kosovo","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/KOS/OSM/DST/kos_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55503,900,"KOS","Kosovo","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/KOS/OSM/DST/kos_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55504,900,"KOS","Kosovo","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/KOS/OSM/DST/kos_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55505,901,"SPR","Spratly Islands","osm_dst_roadintersec_100m_2016","GIS/Covariates/Global_2000_2020/SPR/OSM/DST/spr_osm_dst_roadintersec_100m_2016.tif","Distance to OSM major road intersections 2016"
55506,901,"SPR","Spratly Islands","osm_dst_waterway_100m_2016","GIS/Covariates/Global_2000_2020/SPR/OSM/DST/spr_osm_dst_waterway_100m_2016.tif","Distance to OSM major waterways 2016"
55507,901,"SPR","Spratly Islands","osm_dst_road_100m_2016","GIS/Covariates/Global_2000_2020/SPR/OSM/DST/spr_osm_dst_road_100m_2016.tif","Distance to OSM major roads 2016"
55508,643,"RUS","Russia","px_area_100m","GIS/Pixel_area/Global_2000_2020/RUS/rus_px_area_100m.tif","Grid-cell surface areas"
55509,360,"IDN","Indonesia","px_area_100m","GIS/Pixel_area/Global_2000_2020/IDN/idn_px_area_100m.tif","Grid-cell surface areas"
55510,840,"USA","United States","px_area_100m","GIS/Pixel_area/Global_2000_2020/USA/usa_px_area_100m.tif","Grid-cell surface areas"
55511,850,"VIR","Virgin_Islands_U_S","px_area_100m","GIS/Pixel_area/Global_2000_2020/VIR/vir_px_area_100m.tif","Grid-cell surface areas"
55512,304,"GRL","Greenland","px_area_100m","GIS/Pixel_area/Global_2000_2020/GRL/grl_px_area_100m.tif","Grid-cell surface areas"
55513,156,"CHN","China","px_area_100m","GIS/Pixel_area/Global_2000_2020/CHN/chn_px_area_100m.tif","Grid-cell surface areas"
55514,36,"AUS","Australia","px_area_100m","GIS/Pixel_area/Global_2000_2020/AUS/aus_px_area_100m.tif","Grid-cell surface areas"
55515,76,"BRA","Brazil","px_area_100m","GIS/Pixel_area/Global_2000_2020/BRA/bra_px_area_100m.tif","Grid-cell surface areas"
55516,124,"CAN","Canada","px_area_100m","GIS/Pixel_area/Global_2000_2020/CAN/can_px_area_100m.tif","Grid-cell surface areas"
55517,152,"CHL","Chile","px_area_100m","GIS/Pixel_area/Global_2000_2020/CHL/chl_px_area_100m.tif","Grid-cell surface areas"
55518,4,"AFG","Afghanistan","px_area_100m","GIS/Pixel_area/Global_2000_2020/AFG/afg_px_area_100m.tif","Grid-cell surface areas"
55519,8,"ALB","Albania","px_area_100m","GIS/Pixel_area/Global_2000_2020/ALB/alb_px_area_100m.tif","Grid-cell surface areas"
55520,10,"ATA","Antarctica","px_area_100m","GIS/Pixel_area/Global_2000_2020/ATA/ata_px_area_100m.tif","Grid-cell surface areas"
55521,12,"DZA","Algeria","px_area_100m","GIS/Pixel_area/Global_2000_2020/DZA/dza_px_area_100m.tif","Grid-cell surface areas"
55522,16,"ASM","American Samoa","px_area_100m","GIS/Pixel_area/Global_2000_2020/ASM/asm_px_area_100m.tif","Grid-cell surface areas"
55523,20,"AND","Andorra","px_area_100m","GIS/Pixel_area/Global_2000_2020/AND/and_px_area_100m.tif","Grid-cell surface areas"
55524,24,"AGO","Angola","px_area_100m","GIS/Pixel_area/Global_2000_2020/AGO/ago_px_area_100m.tif","Grid-cell surface areas"
55525,28,"ATG","Antigua and Barbuda","px_area_100m","GIS/Pixel_area/Global_2000_2020/ATG/atg_px_area_100m.tif","Grid-cell surface areas"
55526,31,"AZE","Azerbaijan","px_area_100m","GIS/Pixel_area/Global_2000_2020/AZE/aze_px_area_100m.tif","Grid-cell surface areas"
55527,32,"ARG","Argentina","px_area_100m","GIS/Pixel_area/Global_2000_2020/ARG/arg_px_area_100m.tif","Grid-cell surface areas"
55528,40,"AUT","Austria","px_area_100m","GIS/Pixel_area/Global_2000_2020/AUT/aut_px_area_100m.tif","Grid-cell surface areas"
55529,44,"BHS","Bahamas","px_area_100m","GIS/Pixel_area/Global_2000_2020/BHS/bhs_px_area_100m.tif","Grid-cell surface areas"
55530,48,"BHR","Bahrain","px_area_100m","GIS/Pixel_area/Global_2000_2020/BHR/bhr_px_area_100m.tif","Grid-cell surface areas"
55531,50,"BGD","Bangladesh","px_area_100m","GIS/Pixel_area/Global_2000_2020/BGD/bgd_px_area_100m.tif","Grid-cell surface areas"
55532,51,"ARM","Armenia","px_area_100m","GIS/Pixel_area/Global_2000_2020/ARM/arm_px_area_100m.tif","Grid-cell surface areas"
55533,52,"BRB","Barbados","px_area_100m","GIS/Pixel_area/Global_2000_2020/BRB/brb_px_area_100m.tif","Grid-cell surface areas"
55534,56,"BEL","Belgium","px_area_100m","GIS/Pixel_area/Global_2000_2020/BEL/bel_px_area_100m.tif","Grid-cell surface areas"
55535,60,"BMU","Bermuda","px_area_100m","GIS/Pixel_area/Global_2000_2020/BMU/bmu_px_area_100m.tif","Grid-cell surface areas"
55536,64,"BTN","Bhutan","px_area_100m","GIS/Pixel_area/Global_2000_2020/BTN/btn_px_area_100m.tif","Grid-cell surface areas"
55537,68,"BOL","Bolivia","px_area_100m","GIS/Pixel_area/Global_2000_2020/BOL/bol_px_area_100m.tif","Grid-cell surface areas"
55538,70,"BIH","Bosnia and Herzegovina","px_area_100m","GIS/Pixel_area/Global_2000_2020/BIH/bih_px_area_100m.tif","Grid-cell surface areas"
55539,72,"BWA","Botswana","px_area_100m","GIS/Pixel_area/Global_2000_2020/BWA/bwa_px_area_100m.tif","Grid-cell surface areas"
55540,74,"BVT","Bouvet Island","px_area_100m","GIS/Pixel_area/Global_2000_2020/BVT/bvt_px_area_100m.tif","Grid-cell surface areas"
55541,84,"BLZ","Belize","px_area_100m","GIS/Pixel_area/Global_2000_2020/BLZ/blz_px_area_100m.tif","Grid-cell surface areas"
55542,86,"IOT","British Indian Ocean Territory","px_area_100m","GIS/Pixel_area/Global_2000_2020/IOT/iot_px_area_100m.tif","Grid-cell surface areas"
55543,90,"SLB","Solomon Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/SLB/slb_px_area_100m.tif","Grid-cell surface areas"
55544,92,"VGB","British Virgin Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/VGB/vgb_px_area_100m.tif","Grid-cell surface areas"
55545,96,"BRN","Brunei","px_area_100m","GIS/Pixel_area/Global_2000_2020/BRN/brn_px_area_100m.tif","Grid-cell surface areas"
55546,100,"BGR","Bulgaria","px_area_100m","GIS/Pixel_area/Global_2000_2020/BGR/bgr_px_area_100m.tif","Grid-cell surface areas"
55547,104,"MMR","Myanmar","px_area_100m","GIS/Pixel_area/Global_2000_2020/MMR/mmr_px_area_100m.tif","Grid-cell surface areas"
55548,108,"BDI","Burundi","px_area_100m","GIS/Pixel_area/Global_2000_2020/BDI/bdi_px_area_100m.tif","Grid-cell surface areas"
55549,112,"BLR","Belarus","px_area_100m","GIS/Pixel_area/Global_2000_2020/BLR/blr_px_area_100m.tif","Grid-cell surface areas"
55550,116,"KHM","Cambodia","px_area_100m","GIS/Pixel_area/Global_2000_2020/KHM/khm_px_area_100m.tif","Grid-cell surface areas"
55551,120,"CMR","Cameroon","px_area_100m","GIS/Pixel_area/Global_2000_2020/CMR/cmr_px_area_100m.tif","Grid-cell surface areas"
55552,132,"CPV","Cape Verde","px_area_100m","GIS/Pixel_area/Global_2000_2020/CPV/cpv_px_area_100m.tif","Grid-cell surface areas"
55553,136,"CYM","Cayman Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/CYM/cym_px_area_100m.tif","Grid-cell surface areas"
55554,140,"CAF","Central African Republic","px_area_100m","GIS/Pixel_area/Global_2000_2020/CAF/caf_px_area_100m.tif","Grid-cell surface areas"
55555,144,"LKA","Sri Lanka","px_area_100m","GIS/Pixel_area/Global_2000_2020/LKA/lka_px_area_100m.tif","Grid-cell surface areas"
55556,148,"TCD","Chad","px_area_100m","GIS/Pixel_area/Global_2000_2020/TCD/tcd_px_area_100m.tif","Grid-cell surface areas"
55557,158,"TWN","Taiwan","px_area_100m","GIS/Pixel_area/Global_2000_2020/TWN/twn_px_area_100m.tif","Grid-cell surface areas"
55558,170,"COL","Colombia","px_area_100m","GIS/Pixel_area/Global_2000_2020/COL/col_px_area_100m.tif","Grid-cell surface areas"
55559,174,"COM","Comoros","px_area_100m","GIS/Pixel_area/Global_2000_2020/COM/com_px_area_100m.tif","Grid-cell surface areas"
55560,175,"MYT","Mayotte","px_area_100m","GIS/Pixel_area/Global_2000_2020/MYT/myt_px_area_100m.tif","Grid-cell surface areas"
55561,178,"COG","Republic of Congo","px_area_100m","GIS/Pixel_area/Global_2000_2020/COG/cog_px_area_100m.tif","Grid-cell surface areas"
55562,180,"COD","Democratic Republic of the Congo","px_area_100m","GIS/Pixel_area/Global_2000_2020/COD/cod_px_area_100m.tif","Grid-cell surface areas"
55563,184,"COK","Cook Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/COK/cok_px_area_100m.tif","Grid-cell surface areas"
55564,188,"CRI","Costa Rica","px_area_100m","GIS/Pixel_area/Global_2000_2020/CRI/cri_px_area_100m.tif","Grid-cell surface areas"
55565,191,"HRV","Croatia","px_area_100m","GIS/Pixel_area/Global_2000_2020/HRV/hrv_px_area_100m.tif","Grid-cell surface areas"
55566,192,"CUB","Cuba","px_area_100m","GIS/Pixel_area/Global_2000_2020/CUB/cub_px_area_100m.tif","Grid-cell surface areas"
55567,196,"CYP","Cyprus","px_area_100m","GIS/Pixel_area/Global_2000_2020/CYP/cyp_px_area_100m.tif","Grid-cell surface areas"
55568,203,"CZE","Czech Republic","px_area_100m","GIS/Pixel_area/Global_2000_2020/CZE/cze_px_area_100m.tif","Grid-cell surface areas"
55569,204,"BEN","Benin","px_area_100m","GIS/Pixel_area/Global_2000_2020/BEN/ben_px_area_100m.tif","Grid-cell surface areas"
55570,208,"DNK","Denmark","px_area_100m","GIS/Pixel_area/Global_2000_2020/DNK/dnk_px_area_100m.tif","Grid-cell surface areas"
55571,212,"DMA","Dominica","px_area_100m","GIS/Pixel_area/Global_2000_2020/DMA/dma_px_area_100m.tif","Grid-cell surface areas"
55572,214,"DOM","Dominican Republic","px_area_100m","GIS/Pixel_area/Global_2000_2020/DOM/dom_px_area_100m.tif","Grid-cell surface areas"
55573,218,"ECU","Ecuador","px_area_100m","GIS/Pixel_area/Global_2000_2020/ECU/ecu_px_area_100m.tif","Grid-cell surface areas"
55574,222,"SLV","El Salvador","px_area_100m","GIS/Pixel_area/Global_2000_2020/SLV/slv_px_area_100m.tif","Grid-cell surface areas"
55575,226,"GNQ","Equatorial Guinea","px_area_100m","GIS/Pixel_area/Global_2000_2020/GNQ/gnq_px_area_100m.tif","Grid-cell surface areas"
55576,231,"ETH","Ethiopia","px_area_100m","GIS/Pixel_area/Global_2000_2020/ETH/eth_px_area_100m.tif","Grid-cell surface areas"
55577,232,"ERI","Eritrea","px_area_100m","GIS/Pixel_area/Global_2000_2020/ERI/eri_px_area_100m.tif","Grid-cell surface areas"
55578,233,"EST","Estonia","px_area_100m","GIS/Pixel_area/Global_2000_2020/EST/est_px_area_100m.tif","Grid-cell surface areas"
55579,234,"FRO","Faroe Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/FRO/fro_px_area_100m.tif","Grid-cell surface areas"
55580,238,"FLK","Falkland Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/FLK/flk_px_area_100m.tif","Grid-cell surface areas"
55581,239,"SGS","South Georgia and the South Sandwich Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/SGS/sgs_px_area_100m.tif","Grid-cell surface areas"
55582,242,"FJI","Fiji","px_area_100m","GIS/Pixel_area/Global_2000_2020/FJI/fji_px_area_100m.tif","Grid-cell surface areas"
55583,246,"FIN","Finland","px_area_100m","GIS/Pixel_area/Global_2000_2020/FIN/fin_px_area_100m.tif","Grid-cell surface areas"
55584,248,"ALA","Aland Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/ALA/ala_px_area_100m.tif","Grid-cell surface areas"
55585,250,"FRA","France","px_area_100m","GIS/Pixel_area/Global_2000_2020/FRA/fra_px_area_100m.tif","Grid-cell surface areas"
55586,254,"GUF","French Guiana","px_area_100m","GIS/Pixel_area/Global_2000_2020/GUF/guf_px_area_100m.tif","Grid-cell surface areas"
55587,258,"PYF","French Polynesia","px_area_100m","GIS/Pixel_area/Global_2000_2020/PYF/pyf_px_area_100m.tif","Grid-cell surface areas"
55588,260,"ATF","French Southern Territories","px_area_100m","GIS/Pixel_area/Global_2000_2020/ATF/atf_px_area_100m.tif","Grid-cell surface areas"
55589,262,"DJI","Djibouti","px_area_100m","GIS/Pixel_area/Global_2000_2020/DJI/dji_px_area_100m.tif","Grid-cell surface areas"
55590,266,"GAB","Gabon","px_area_100m","GIS/Pixel_area/Global_2000_2020/GAB/gab_px_area_100m.tif","Grid-cell surface areas"
55591,268,"GEO","Georgia","px_area_100m","GIS/Pixel_area/Global_2000_2020/GEO/geo_px_area_100m.tif","Grid-cell surface areas"
55592,270,"GMB","Gambia","px_area_100m","GIS/Pixel_area/Global_2000_2020/GMB/gmb_px_area_100m.tif","Grid-cell surface areas"
55593,275,"PSE","Palestina","px_area_100m","GIS/Pixel_area/Global_2000_2020/PSE/pse_px_area_100m.tif","Grid-cell surface areas"
55594,276,"DEU","Germany","px_area_100m","GIS/Pixel_area/Global_2000_2020/DEU/deu_px_area_100m.tif","Grid-cell surface areas"
55595,288,"GHA","Ghana","px_area_100m","GIS/Pixel_area/Global_2000_2020/GHA/gha_px_area_100m.tif","Grid-cell surface areas"
55596,292,"GIB","Gibraltar","px_area_100m","GIS/Pixel_area/Global_2000_2020/GIB/gib_px_area_100m.tif","Grid-cell surface areas"
55597,296,"KIR","Kiribati","px_area_100m","GIS/Pixel_area/Global_2000_2020/KIR/kir_px_area_100m.tif","Grid-cell surface areas"
55598,300,"GRC","Greece","px_area_100m","GIS/Pixel_area/Global_2000_2020/GRC/grc_px_area_100m.tif","Grid-cell surface areas"
55599,308,"GRD","Grenada","px_area_100m","GIS/Pixel_area/Global_2000_2020/GRD/grd_px_area_100m.tif","Grid-cell surface areas"
55600,312,"GLP","Guadeloupe","px_area_100m","GIS/Pixel_area/Global_2000_2020/GLP/glp_px_area_100m.tif","Grid-cell surface areas"
55601,316,"GUM","Guam","px_area_100m","GIS/Pixel_area/Global_2000_2020/GUM/gum_px_area_100m.tif","Grid-cell surface areas"
55602,320,"GTM","Guatemala","px_area_100m","GIS/Pixel_area/Global_2000_2020/GTM/gtm_px_area_100m.tif","Grid-cell surface areas"
55603,324,"GIN","Guinea","px_area_100m","GIS/Pixel_area/Global_2000_2020/GIN/gin_px_area_100m.tif","Grid-cell surface areas"
55604,328,"GUY","Guyana","px_area_100m","GIS/Pixel_area/Global_2000_2020/GUY/guy_px_area_100m.tif","Grid-cell surface areas"
55605,332,"HTI","Haiti","px_area_100m","GIS/Pixel_area/Global_2000_2020/HTI/hti_px_area_100m.tif","Grid-cell surface areas"
55606,334,"HMD","Heard Island and McDonald Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/HMD/hmd_px_area_100m.tif","Grid-cell surface areas"
55607,336,"VAT","Vatican City","px_area_100m","GIS/Pixel_area/Global_2000_2020/VAT/vat_px_area_100m.tif","Grid-cell surface areas"
55608,340,"HND","Honduras","px_area_100m","GIS/Pixel_area/Global_2000_2020/HND/hnd_px_area_100m.tif","Grid-cell surface areas"
55609,344,"HKG","Hong Kong","px_area_100m","GIS/Pixel_area/Global_2000_2020/HKG/hkg_px_area_100m.tif","Grid-cell surface areas"
55610,348,"HUN","Hungary","px_area_100m","GIS/Pixel_area/Global_2000_2020/HUN/hun_px_area_100m.tif","Grid-cell surface areas"
55611,352,"ISL","Iceland","px_area_100m","GIS/Pixel_area/Global_2000_2020/ISL/isl_px_area_100m.tif","Grid-cell surface areas"
55612,356,"IND","India","px_area_100m","GIS/Pixel_area/Global_2000_2020/IND/ind_px_area_100m.tif","Grid-cell surface areas"
55613,364,"IRN","Iran","px_area_100m","GIS/Pixel_area/Global_2000_2020/IRN/irn_px_area_100m.tif","Grid-cell surface areas"
55614,368,"IRQ","Iraq","px_area_100m","GIS/Pixel_area/Global_2000_2020/IRQ/irq_px_area_100m.tif","Grid-cell surface areas"
55615,372,"IRL","Ireland","px_area_100m","GIS/Pixel_area/Global_2000_2020/IRL/irl_px_area_100m.tif","Grid-cell surface areas"
55616,376,"ISR","Israel","px_area_100m","GIS/Pixel_area/Global_2000_2020/ISR/isr_px_area_100m.tif","Grid-cell surface areas"
55617,380,"ITA","Italy","px_area_100m","GIS/Pixel_area/Global_2000_2020/ITA/ita_px_area_100m.tif","Grid-cell surface areas"
55618,384,"CIV","CIte dIvoire","px_area_100m","GIS/Pixel_area/Global_2000_2020/CIV/civ_px_area_100m.tif","Grid-cell surface areas"
55619,388,"JAM","Jamaica","px_area_100m","GIS/Pixel_area/Global_2000_2020/JAM/jam_px_area_100m.tif","Grid-cell surface areas"
55620,392,"JPN","Japan","px_area_100m","GIS/Pixel_area/Global_2000_2020/JPN/jpn_px_area_100m.tif","Grid-cell surface areas"
55621,398,"KAZ","Kazakhstan","px_area_100m","GIS/Pixel_area/Global_2000_2020/KAZ/kaz_px_area_100m.tif","Grid-cell surface areas"
55622,400,"JOR","Jordan","px_area_100m","GIS/Pixel_area/Global_2000_2020/JOR/jor_px_area_100m.tif","Grid-cell surface areas"
55623,404,"KEN","Kenya","px_area_100m","GIS/Pixel_area/Global_2000_2020/KEN/ken_px_area_100m.tif","Grid-cell surface areas"
55624,408,"PRK","North Korea","px_area_100m","GIS/Pixel_area/Global_2000_2020/PRK/prk_px_area_100m.tif","Grid-cell surface areas"
55625,410,"KOR","South Korea","px_area_100m","GIS/Pixel_area/Global_2000_2020/KOR/kor_px_area_100m.tif","Grid-cell surface areas"
55626,414,"KWT","Kuwait","px_area_100m","GIS/Pixel_area/Global_2000_2020/KWT/kwt_px_area_100m.tif","Grid-cell surface areas"
55627,417,"KGZ","Kyrgyzstan","px_area_100m","GIS/Pixel_area/Global_2000_2020/KGZ/kgz_px_area_100m.tif","Grid-cell surface areas"
55628,418,"LAO","Laos","px_area_100m","GIS/Pixel_area/Global_2000_2020/LAO/lao_px_area_100m.tif","Grid-cell surface areas"
55629,422,"LBN","Lebanon","px_area_100m","GIS/Pixel_area/Global_2000_2020/LBN/lbn_px_area_100m.tif","Grid-cell surface areas"
55630,426,"LSO","Lesotho","px_area_100m","GIS/Pixel_area/Global_2000_2020/LSO/lso_px_area_100m.tif","Grid-cell surface areas"
55631,428,"LVA","Latvia","px_area_100m","GIS/Pixel_area/Global_2000_2020/LVA/lva_px_area_100m.tif","Grid-cell surface areas"
55632,430,"LBR","Liberia","px_area_100m","GIS/Pixel_area/Global_2000_2020/LBR/lbr_px_area_100m.tif","Grid-cell surface areas"
55633,434,"LBY","Libya","px_area_100m","GIS/Pixel_area/Global_2000_2020/LBY/lby_px_area_100m.tif","Grid-cell surface areas"
55634,438,"LIE","Liechtenstein","px_area_100m","GIS/Pixel_area/Global_2000_2020/LIE/lie_px_area_100m.tif","Grid-cell surface areas"
55635,440,"LTU","Lithuania","px_area_100m","GIS/Pixel_area/Global_2000_2020/LTU/ltu_px_area_100m.tif","Grid-cell surface areas"
55636,442,"LUX","Luxembourg","px_area_100m","GIS/Pixel_area/Global_2000_2020/LUX/lux_px_area_100m.tif","Grid-cell surface areas"
55637,446,"MAC","Macao","px_area_100m","GIS/Pixel_area/Global_2000_2020/MAC/mac_px_area_100m.tif","Grid-cell surface areas"
55638,450,"MDG","Madagascar","px_area_100m","GIS/Pixel_area/Global_2000_2020/MDG/mdg_px_area_100m.tif","Grid-cell surface areas"
55639,454,"MWI","Malawi","px_area_100m","GIS/Pixel_area/Global_2000_2020/MWI/mwi_px_area_100m.tif","Grid-cell surface areas"
55640,458,"MYS","Malaysia","px_area_100m","GIS/Pixel_area/Global_2000_2020/MYS/mys_px_area_100m.tif","Grid-cell surface areas"
55641,462,"MDV","Maldives","px_area_100m","GIS/Pixel_area/Global_2000_2020/MDV/mdv_px_area_100m.tif","Grid-cell surface areas"
55642,466,"MLI","Mali","px_area_100m","GIS/Pixel_area/Global_2000_2020/MLI/mli_px_area_100m.tif","Grid-cell surface areas"
55643,470,"MLT","Malta","px_area_100m","GIS/Pixel_area/Global_2000_2020/MLT/mlt_px_area_100m.tif","Grid-cell surface areas"
55644,474,"MTQ","Martinique","px_area_100m","GIS/Pixel_area/Global_2000_2020/MTQ/mtq_px_area_100m.tif","Grid-cell surface areas"
55645,478,"MRT","Mauritania","px_area_100m","GIS/Pixel_area/Global_2000_2020/MRT/mrt_px_area_100m.tif","Grid-cell surface areas"
55646,480,"MUS","Mauritius","px_area_100m","GIS/Pixel_area/Global_2000_2020/MUS/mus_px_area_100m.tif","Grid-cell surface areas"
55647,484,"MEX","Mexico","px_area_100m","GIS/Pixel_area/Global_2000_2020/MEX/mex_px_area_100m.tif","Grid-cell surface areas"
55648,492,"MCO","Monaco","px_area_100m","GIS/Pixel_area/Global_2000_2020/MCO/mco_px_area_100m.tif","Grid-cell surface areas"
55649,496,"MNG","Mongolia","px_area_100m","GIS/Pixel_area/Global_2000_2020/MNG/mng_px_area_100m.tif","Grid-cell surface areas"
55650,498,"MDA","Moldova","px_area_100m","GIS/Pixel_area/Global_2000_2020/MDA/mda_px_area_100m.tif","Grid-cell surface areas"
55651,499,"MNE","Montenegro","px_area_100m","GIS/Pixel_area/Global_2000_2020/MNE/mne_px_area_100m.tif","Grid-cell surface areas"
55652,500,"MSR","Montserrat","px_area_100m","GIS/Pixel_area/Global_2000_2020/MSR/msr_px_area_100m.tif","Grid-cell surface areas"
55653,504,"MAR","Morocco","px_area_100m","GIS/Pixel_area/Global_2000_2020/MAR/mar_px_area_100m.tif","Grid-cell surface areas"
55654,508,"MOZ","Mozambique","px_area_100m","GIS/Pixel_area/Global_2000_2020/MOZ/moz_px_area_100m.tif","Grid-cell surface areas"
55655,512,"OMN","Oman","px_area_100m","GIS/Pixel_area/Global_2000_2020/OMN/omn_px_area_100m.tif","Grid-cell surface areas"
55656,516,"NAM","Namibia","px_area_100m","GIS/Pixel_area/Global_2000_2020/NAM/nam_px_area_100m.tif","Grid-cell surface areas"
55657,520,"NRU","Nauru","px_area_100m","GIS/Pixel_area/Global_2000_2020/NRU/nru_px_area_100m.tif","Grid-cell surface areas"
55658,524,"NPL","Nepal","px_area_100m","GIS/Pixel_area/Global_2000_2020/NPL/npl_px_area_100m.tif","Grid-cell surface areas"
55659,528,"NLD","Netherlands","px_area_100m","GIS/Pixel_area/Global_2000_2020/NLD/nld_px_area_100m.tif","Grid-cell surface areas"
55660,531,"CUW","Curacao","px_area_100m","GIS/Pixel_area/Global_2000_2020/CUW/cuw_px_area_100m.tif","Grid-cell surface areas"
55661,533,"ABW","Aruba","px_area_100m","GIS/Pixel_area/Global_2000_2020/ABW/abw_px_area_100m.tif","Grid-cell surface areas"
55662,534,"SXM","Sint Maarten (Dutch part)","px_area_100m","GIS/Pixel_area/Global_2000_2020/SXM/sxm_px_area_100m.tif","Grid-cell surface areas"
55663,535,"BES","Bonaire, Sint Eustatius and Saba","px_area_100m","GIS/Pixel_area/Global_2000_2020/BES/bes_px_area_100m.tif","Grid-cell surface areas"
55664,540,"NCL","New Caledonia","px_area_100m","GIS/Pixel_area/Global_2000_2020/NCL/ncl_px_area_100m.tif","Grid-cell surface areas"
55665,548,"VUT","Vanuatu","px_area_100m","GIS/Pixel_area/Global_2000_2020/VUT/vut_px_area_100m.tif","Grid-cell surface areas"
55666,554,"NZL","New Zealand","px_area_100m","GIS/Pixel_area/Global_2000_2020/NZL/nzl_px_area_100m.tif","Grid-cell surface areas"
55667,558,"NIC","Nicaragua","px_area_100m","GIS/Pixel_area/Global_2000_2020/NIC/nic_px_area_100m.tif","Grid-cell surface areas"
55668,562,"NER","Niger","px_area_100m","GIS/Pixel_area/Global_2000_2020/NER/ner_px_area_100m.tif","Grid-cell surface areas"
55669,566,"NGA","Nigeria","px_area_100m","GIS/Pixel_area/Global_2000_2020/NGA/nga_px_area_100m.tif","Grid-cell surface areas"
55670,570,"NIU","Niue","px_area_100m","GIS/Pixel_area/Global_2000_2020/NIU/niu_px_area_100m.tif","Grid-cell surface areas"
55671,574,"NFK","Norfolk Island","px_area_100m","GIS/Pixel_area/Global_2000_2020/NFK/nfk_px_area_100m.tif","Grid-cell surface areas"
55672,578,"NOR","Norway","px_area_100m","GIS/Pixel_area/Global_2000_2020/NOR/nor_px_area_100m.tif","Grid-cell surface areas"
55673,580,"MNP","Northern Mariana Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/MNP/mnp_px_area_100m.tif","Grid-cell surface areas"
55674,581,"UMI","United States Minor Outlying Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/UMI/umi_px_area_100m.tif","Grid-cell surface areas"
55675,583,"FSM","Micronesia","px_area_100m","GIS/Pixel_area/Global_2000_2020/FSM/fsm_px_area_100m.tif","Grid-cell surface areas"
55676,584,"MHL","Marshall Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/MHL/mhl_px_area_100m.tif","Grid-cell surface areas"
55677,585,"PLW","Palau","px_area_100m","GIS/Pixel_area/Global_2000_2020/PLW/plw_px_area_100m.tif","Grid-cell surface areas"
55678,586,"PAK","Pakistan","px_area_100m","GIS/Pixel_area/Global_2000_2020/PAK/pak_px_area_100m.tif","Grid-cell surface areas"
55679,591,"PAN","Panama","px_area_100m","GIS/Pixel_area/Global_2000_2020/PAN/pan_px_area_100m.tif","Grid-cell surface areas"
55680,598,"PNG","Papua New Guinea","px_area_100m","GIS/Pixel_area/Global_2000_2020/PNG/png_px_area_100m.tif","Grid-cell surface areas"
55681,600,"PRY","Paraguay","px_area_100m","GIS/Pixel_area/Global_2000_2020/PRY/pry_px_area_100m.tif","Grid-cell surface areas"
55682,604,"PER","Peru","px_area_100m","GIS/Pixel_area/Global_2000_2020/PER/per_px_area_100m.tif","Grid-cell surface areas"
55683,608,"PHL","Philippines","px_area_100m","GIS/Pixel_area/Global_2000_2020/PHL/phl_px_area_100m.tif","Grid-cell surface areas"
55684,612,"PCN","Pitcairn Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/PCN/pcn_px_area_100m.tif","Grid-cell surface areas"
55685,616,"POL","Poland","px_area_100m","GIS/Pixel_area/Global_2000_2020/POL/pol_px_area_100m.tif","Grid-cell surface areas"
55686,620,"PRT","Portugal","px_area_100m","GIS/Pixel_area/Global_2000_2020/PRT/prt_px_area_100m.tif","Grid-cell surface areas"
55687,624,"GNB","Guinea-Bissau","px_area_100m","GIS/Pixel_area/Global_2000_2020/GNB/gnb_px_area_100m.tif","Grid-cell surface areas"
55688,626,"TLS","East Timor","px_area_100m","GIS/Pixel_area/Global_2000_2020/TLS/tls_px_area_100m.tif","Grid-cell surface areas"
55689,630,"PRI","Puerto Rico","px_area_100m","GIS/Pixel_area/Global_2000_2020/PRI/pri_px_area_100m.tif","Grid-cell surface areas"
55690,634,"QAT","Qatar","px_area_100m","GIS/Pixel_area/Global_2000_2020/QAT/qat_px_area_100m.tif","Grid-cell surface areas"
55691,638,"REU","Reunion","px_area_100m","GIS/Pixel_area/Global_2000_2020/REU/reu_px_area_100m.tif","Grid-cell surface areas"
55692,642,"ROU","Romania","px_area_100m","GIS/Pixel_area/Global_2000_2020/ROU/rou_px_area_100m.tif","Grid-cell surface areas"
55693,646,"RWA","Rwanda","px_area_100m","GIS/Pixel_area/Global_2000_2020/RWA/rwa_px_area_100m.tif","Grid-cell surface areas"
55694,652,"BLM","Saint Barthelemy","px_area_100m","GIS/Pixel_area/Global_2000_2020/BLM/blm_px_area_100m.tif","Grid-cell surface areas"
55695,654,"SHN","Saint Helena","px_area_100m","GIS/Pixel_area/Global_2000_2020/SHN/shn_px_area_100m.tif","Grid-cell surface areas"
55696,659,"KNA","Saint Kitts and Nevis","px_area_100m","GIS/Pixel_area/Global_2000_2020/KNA/kna_px_area_100m.tif","Grid-cell surface areas"
55697,660,"AIA","Anguilla","px_area_100m","GIS/Pixel_area/Global_2000_2020/AIA/aia_px_area_100m.tif","Grid-cell surface areas"
55698,662,"LCA","Saint Lucia","px_area_100m","GIS/Pixel_area/Global_2000_2020/LCA/lca_px_area_100m.tif","Grid-cell surface areas"
55699,663,"MAF","Saint Martin (French part)","px_area_100m","GIS/Pixel_area/Global_2000_2020/MAF/maf_px_area_100m.tif","Grid-cell surface areas"
55700,666,"SPM","Saint Pierre and Miquelon","px_area_100m","GIS/Pixel_area/Global_2000_2020/SPM/spm_px_area_100m.tif","Grid-cell surface areas"
55701,670,"VCT","Saint Vincent and the Grenadines","px_area_100m","GIS/Pixel_area/Global_2000_2020/VCT/vct_px_area_100m.tif","Grid-cell surface areas"
55702,674,"SMR","San Marino","px_area_100m","GIS/Pixel_area/Global_2000_2020/SMR/smr_px_area_100m.tif","Grid-cell surface areas"
55703,678,"STP","Sao Tome and Principe","px_area_100m","GIS/Pixel_area/Global_2000_2020/STP/stp_px_area_100m.tif","Grid-cell surface areas"
55704,682,"SAU","Saudi Arabia","px_area_100m","GIS/Pixel_area/Global_2000_2020/SAU/sau_px_area_100m.tif","Grid-cell surface areas"
55705,686,"SEN","Senegal","px_area_100m","GIS/Pixel_area/Global_2000_2020/SEN/sen_px_area_100m.tif","Grid-cell surface areas"
55706,688,"SRB","Serbia","px_area_100m","GIS/Pixel_area/Global_2000_2020/SRB/srb_px_area_100m.tif","Grid-cell surface areas"
55707,690,"SYC","Seychelles","px_area_100m","GIS/Pixel_area/Global_2000_2020/SYC/syc_px_area_100m.tif","Grid-cell surface areas"
55708,694,"SLE","Sierra Leone","px_area_100m","GIS/Pixel_area/Global_2000_2020/SLE/sle_px_area_100m.tif","Grid-cell surface areas"
55709,702,"SGP","Singapore","px_area_100m","GIS/Pixel_area/Global_2000_2020/SGP/sgp_px_area_100m.tif","Grid-cell surface areas"
55710,703,"SVK","Slovakia","px_area_100m","GIS/Pixel_area/Global_2000_2020/SVK/svk_px_area_100m.tif","Grid-cell surface areas"
55711,704,"VNM","Vietnam","px_area_100m","GIS/Pixel_area/Global_2000_2020/VNM/vnm_px_area_100m.tif","Grid-cell surface areas"
55712,705,"SVN","Slovenia","px_area_100m","GIS/Pixel_area/Global_2000_2020/SVN/svn_px_area_100m.tif","Grid-cell surface areas"
55713,706,"SOM","Somalia","px_area_100m","GIS/Pixel_area/Global_2000_2020/SOM/som_px_area_100m.tif","Grid-cell surface areas"
55714,710,"ZAF","South Africa","px_area_100m","GIS/Pixel_area/Global_2000_2020/ZAF/zaf_px_area_100m.tif","Grid-cell surface areas"
55715,716,"ZWE","Zimbabwe","px_area_100m","GIS/Pixel_area/Global_2000_2020/ZWE/zwe_px_area_100m.tif","Grid-cell surface areas"
55716,724,"ESP","Spain","px_area_100m","GIS/Pixel_area/Global_2000_2020/ESP/esp_px_area_100m.tif","Grid-cell surface areas"
55717,728,"SSD","South Sudan","px_area_100m","GIS/Pixel_area/Global_2000_2020/SSD/ssd_px_area_100m.tif","Grid-cell surface areas"
55718,729,"SDN","Sudan","px_area_100m","GIS/Pixel_area/Global_2000_2020/SDN/sdn_px_area_100m.tif","Grid-cell surface areas"
55719,732,"ESH","Western Sahara","px_area_100m","GIS/Pixel_area/Global_2000_2020/ESH/esh_px_area_100m.tif","Grid-cell surface areas"
55720,740,"SUR","Suriname","px_area_100m","GIS/Pixel_area/Global_2000_2020/SUR/sur_px_area_100m.tif","Grid-cell surface areas"
55721,744,"SJM","Svalbard and Jan Mayen Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/SJM/sjm_px_area_100m.tif","Grid-cell surface areas"
55722,748,"SWZ","Swaziland","px_area_100m","GIS/Pixel_area/Global_2000_2020/SWZ/swz_px_area_100m.tif","Grid-cell surface areas"
55723,752,"SWE","Sweden","px_area_100m","GIS/Pixel_area/Global_2000_2020/SWE/swe_px_area_100m.tif","Grid-cell surface areas"
55724,756,"CHE","Switzerland","px_area_100m","GIS/Pixel_area/Global_2000_2020/CHE/che_px_area_100m.tif","Grid-cell surface areas"
55725,760,"SYR","Syria","px_area_100m","GIS/Pixel_area/Global_2000_2020/SYR/syr_px_area_100m.tif","Grid-cell surface areas"
55726,762,"TJK","Tajikistan","px_area_100m","GIS/Pixel_area/Global_2000_2020/TJK/tjk_px_area_100m.tif","Grid-cell surface areas"
55727,764,"THA","Thailand","px_area_100m","GIS/Pixel_area/Global_2000_2020/THA/tha_px_area_100m.tif","Grid-cell surface areas"
55728,768,"TGO","Togo","px_area_100m","GIS/Pixel_area/Global_2000_2020/TGO/tgo_px_area_100m.tif","Grid-cell surface areas"
55729,772,"TKL","Tokelau","px_area_100m","GIS/Pixel_area/Global_2000_2020/TKL/tkl_px_area_100m.tif","Grid-cell surface areas"
55730,776,"TON","Tonga","px_area_100m","GIS/Pixel_area/Global_2000_2020/TON/ton_px_area_100m.tif","Grid-cell surface areas"
55731,780,"TTO","Trinidad and Tobago","px_area_100m","GIS/Pixel_area/Global_2000_2020/TTO/tto_px_area_100m.tif","Grid-cell surface areas"
55732,784,"ARE","United Arab Emirates","px_area_100m","GIS/Pixel_area/Global_2000_2020/ARE/are_px_area_100m.tif","Grid-cell surface areas"
55733,788,"TUN","Tunisia","px_area_100m","GIS/Pixel_area/Global_2000_2020/TUN/tun_px_area_100m.tif","Grid-cell surface areas"
55734,792,"TUR","Turkey","px_area_100m","GIS/Pixel_area/Global_2000_2020/TUR/tur_px_area_100m.tif","Grid-cell surface areas"
55735,795,"TKM","Turkmenistan","px_area_100m","GIS/Pixel_area/Global_2000_2020/TKM/tkm_px_area_100m.tif","Grid-cell surface areas"
55736,796,"TCA","Turks and Caicos Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/TCA/tca_px_area_100m.tif","Grid-cell surface areas"
55737,798,"TUV","Tuvalu","px_area_100m","GIS/Pixel_area/Global_2000_2020/TUV/tuv_px_area_100m.tif","Grid-cell surface areas"
55738,800,"UGA","Uganda","px_area_100m","GIS/Pixel_area/Global_2000_2020/UGA/uga_px_area_100m.tif","Grid-cell surface areas"
55739,804,"UKR","Ukraine","px_area_100m","GIS/Pixel_area/Global_2000_2020/UKR/ukr_px_area_100m.tif","Grid-cell surface areas"
55740,807,"MKD","Macedonia","px_area_100m","GIS/Pixel_area/Global_2000_2020/MKD/mkd_px_area_100m.tif","Grid-cell surface areas"
55741,818,"EGY","Egypt","px_area_100m","GIS/Pixel_area/Global_2000_2020/EGY/egy_px_area_100m.tif","Grid-cell surface areas"
55742,826,"GBR","United Kingdom","px_area_100m","GIS/Pixel_area/Global_2000_2020/GBR/gbr_px_area_100m.tif","Grid-cell surface areas"
55743,831,"GGY","Guernsey","px_area_100m","GIS/Pixel_area/Global_2000_2020/GGY/ggy_px_area_100m.tif","Grid-cell surface areas"
55744,832,"JEY","Jersey","px_area_100m","GIS/Pixel_area/Global_2000_2020/JEY/jey_px_area_100m.tif","Grid-cell surface areas"
55745,833,"IMN","Isle of Man","px_area_100m","GIS/Pixel_area/Global_2000_2020/IMN/imn_px_area_100m.tif","Grid-cell surface areas"
55746,834,"TZA","Tanzania","px_area_100m","GIS/Pixel_area/Global_2000_2020/TZA/tza_px_area_100m.tif","Grid-cell surface areas"
55747,854,"BFA","Burkina Faso","px_area_100m","GIS/Pixel_area/Global_2000_2020/BFA/bfa_px_area_100m.tif","Grid-cell surface areas"
55748,858,"URY","Uruguay","px_area_100m","GIS/Pixel_area/Global_2000_2020/URY/ury_px_area_100m.tif","Grid-cell surface areas"
55749,860,"UZB","Uzbekistan","px_area_100m","GIS/Pixel_area/Global_2000_2020/UZB/uzb_px_area_100m.tif","Grid-cell surface areas"
55750,862,"VEN","Venezuela","px_area_100m","GIS/Pixel_area/Global_2000_2020/VEN/ven_px_area_100m.tif","Grid-cell surface areas"
55751,876,"WLF","Wallis and Futuna","px_area_100m","GIS/Pixel_area/Global_2000_2020/WLF/wlf_px_area_100m.tif","Grid-cell surface areas"
55752,882,"WSM","Samoa","px_area_100m","GIS/Pixel_area/Global_2000_2020/WSM/wsm_px_area_100m.tif","Grid-cell surface areas"
55753,887,"YEM","Yemen","px_area_100m","GIS/Pixel_area/Global_2000_2020/YEM/yem_px_area_100m.tif","Grid-cell surface areas"
55754,894,"ZMB","Zambia","px_area_100m","GIS/Pixel_area/Global_2000_2020/ZMB/zmb_px_area_100m.tif","Grid-cell surface areas"
55755,900,"KOS","Kosovo","px_area_100m","GIS/Pixel_area/Global_2000_2020/KOS/kos_px_area_100m.tif","Grid-cell surface areas"
55756,901,"SPR","Spratly Islands","px_area_100m","GIS/Pixel_area/Global_2000_2020/SPR/spr_px_area_100m.tif","Grid-cell surface areas"
55757,643,"RUS","Russia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2000/Binary/rus_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55758,643,"RUS","Russia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2000/DTE/rus_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55759,643,"RUS","Russia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2012/Binary/rus_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55760,643,"RUS","Russia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2012/DTE/rus_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55761,643,"RUS","Russia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2014/Binary/rus_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55762,643,"RUS","Russia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2014/DTE/rus_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55763,643,"RUS","Russia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2000/PRP/rus_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55764,643,"RUS","Russia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2000/PRP/rus_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55765,643,"RUS","Russia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2000/PRP/rus_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55766,643,"RUS","Russia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2000/PRP/rus_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55767,643,"RUS","Russia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2012/PRP/rus_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55768,643,"RUS","Russia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2012/PRP/rus_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55769,643,"RUS","Russia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2012/PRP/rus_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55770,643,"RUS","Russia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2012/PRP/rus_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55771,643,"RUS","Russia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2014/PRP/rus_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55772,643,"RUS","Russia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2014/PRP/rus_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55773,643,"RUS","Russia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2014/PRP/rus_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55774,643,"RUS","Russia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/RUS/BuiltSettlement/2014/PRP/rus_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55775,360,"IDN","Indonesia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2000/Binary/idn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55776,360,"IDN","Indonesia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2000/DTE/idn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55777,360,"IDN","Indonesia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2012/Binary/idn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55778,360,"IDN","Indonesia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2012/DTE/idn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55779,360,"IDN","Indonesia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2014/Binary/idn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55780,360,"IDN","Indonesia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2014/DTE/idn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55781,360,"IDN","Indonesia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2000/PRP/idn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55782,360,"IDN","Indonesia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2000/PRP/idn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55783,360,"IDN","Indonesia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2000/PRP/idn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55784,360,"IDN","Indonesia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2000/PRP/idn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55785,360,"IDN","Indonesia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2012/PRP/idn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55786,360,"IDN","Indonesia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2012/PRP/idn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55787,360,"IDN","Indonesia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2012/PRP/idn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55788,360,"IDN","Indonesia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2012/PRP/idn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55789,360,"IDN","Indonesia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2014/PRP/idn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55790,360,"IDN","Indonesia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2014/PRP/idn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55791,360,"IDN","Indonesia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2014/PRP/idn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55792,360,"IDN","Indonesia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/IDN/BuiltSettlement/2014/PRP/idn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55793,840,"USA","United States","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2000/Binary/usa_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55794,840,"USA","United States","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2000/DTE/usa_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55795,840,"USA","United States","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2012/Binary/usa_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55796,840,"USA","United States","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2012/DTE/usa_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55797,840,"USA","United States","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2014/Binary/usa_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55798,840,"USA","United States","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2014/DTE/usa_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55799,840,"USA","United States","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2000/PRP/usa_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55800,840,"USA","United States","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2000/PRP/usa_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55801,840,"USA","United States","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2000/PRP/usa_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55802,840,"USA","United States","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2000/PRP/usa_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55803,840,"USA","United States","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2012/PRP/usa_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55804,840,"USA","United States","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2012/PRP/usa_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55805,840,"USA","United States","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2012/PRP/usa_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55806,840,"USA","United States","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2012/PRP/usa_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55807,840,"USA","United States","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2014/PRP/usa_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55808,840,"USA","United States","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2014/PRP/usa_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55809,840,"USA","United States","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2014/PRP/usa_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55810,840,"USA","United States","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/USA/BuiltSettlement/2014/PRP/usa_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55811,850,"VIR","Virgin_Islands_U_S","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2000/Binary/vir_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55812,850,"VIR","Virgin_Islands_U_S","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2000/DTE/vir_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55813,850,"VIR","Virgin_Islands_U_S","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2012/Binary/vir_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55814,850,"VIR","Virgin_Islands_U_S","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2012/DTE/vir_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55815,850,"VIR","Virgin_Islands_U_S","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2014/Binary/vir_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55816,850,"VIR","Virgin_Islands_U_S","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2014/DTE/vir_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55817,850,"VIR","Virgin_Islands_U_S","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2000/PRP/vir_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55818,850,"VIR","Virgin_Islands_U_S","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2000/PRP/vir_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55819,850,"VIR","Virgin_Islands_U_S","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2000/PRP/vir_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55820,850,"VIR","Virgin_Islands_U_S","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2000/PRP/vir_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55821,850,"VIR","Virgin_Islands_U_S","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2012/PRP/vir_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55822,850,"VIR","Virgin_Islands_U_S","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2012/PRP/vir_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55823,850,"VIR","Virgin_Islands_U_S","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2012/PRP/vir_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55824,850,"VIR","Virgin_Islands_U_S","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2012/PRP/vir_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55825,850,"VIR","Virgin_Islands_U_S","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2014/PRP/vir_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55826,850,"VIR","Virgin_Islands_U_S","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2014/PRP/vir_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55827,850,"VIR","Virgin_Islands_U_S","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2014/PRP/vir_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55828,850,"VIR","Virgin_Islands_U_S","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/VIR/BuiltSettlement/2014/PRP/vir_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55829,304,"GRL","Greenland","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2000/Binary/grl_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55830,304,"GRL","Greenland","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2000/DTE/grl_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55831,304,"GRL","Greenland","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2012/Binary/grl_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55832,304,"GRL","Greenland","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2012/DTE/grl_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55833,304,"GRL","Greenland","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2014/Binary/grl_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55834,304,"GRL","Greenland","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2014/DTE/grl_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55835,304,"GRL","Greenland","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2000/PRP/grl_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55836,304,"GRL","Greenland","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2000/PRP/grl_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55837,304,"GRL","Greenland","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2000/PRP/grl_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55838,304,"GRL","Greenland","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2000/PRP/grl_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55839,304,"GRL","Greenland","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2012/PRP/grl_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55840,304,"GRL","Greenland","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2012/PRP/grl_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55841,304,"GRL","Greenland","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2012/PRP/grl_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55842,304,"GRL","Greenland","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2012/PRP/grl_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55843,304,"GRL","Greenland","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2014/PRP/grl_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55844,304,"GRL","Greenland","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2014/PRP/grl_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55845,304,"GRL","Greenland","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2014/PRP/grl_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55846,304,"GRL","Greenland","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GRL/BuiltSettlement/2014/PRP/grl_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55847,156,"CHN","China","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2000/Binary/chn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55848,156,"CHN","China","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2000/DTE/chn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55849,156,"CHN","China","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2012/Binary/chn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55850,156,"CHN","China","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2012/DTE/chn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55851,156,"CHN","China","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2014/Binary/chn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55852,156,"CHN","China","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2014/DTE/chn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55853,156,"CHN","China","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2000/PRP/chn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55854,156,"CHN","China","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2000/PRP/chn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55855,156,"CHN","China","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2000/PRP/chn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55856,156,"CHN","China","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2000/PRP/chn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55857,156,"CHN","China","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2012/PRP/chn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55858,156,"CHN","China","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2012/PRP/chn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55859,156,"CHN","China","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2012/PRP/chn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55860,156,"CHN","China","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2012/PRP/chn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55861,156,"CHN","China","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2014/PRP/chn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55862,156,"CHN","China","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2014/PRP/chn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55863,156,"CHN","China","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2014/PRP/chn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55864,156,"CHN","China","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CHN/BuiltSettlement/2014/PRP/chn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55865,36,"AUS","Australia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2000/Binary/aus_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55866,36,"AUS","Australia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2000/DTE/aus_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55867,36,"AUS","Australia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2012/Binary/aus_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55868,36,"AUS","Australia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2012/DTE/aus_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55869,36,"AUS","Australia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2014/Binary/aus_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55870,36,"AUS","Australia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2014/DTE/aus_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55871,36,"AUS","Australia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2000/PRP/aus_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55872,36,"AUS","Australia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2000/PRP/aus_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55873,36,"AUS","Australia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2000/PRP/aus_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55874,36,"AUS","Australia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2000/PRP/aus_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55875,36,"AUS","Australia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2012/PRP/aus_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55876,36,"AUS","Australia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2012/PRP/aus_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55877,36,"AUS","Australia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2012/PRP/aus_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55878,36,"AUS","Australia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2012/PRP/aus_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55879,36,"AUS","Australia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2014/PRP/aus_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55880,36,"AUS","Australia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2014/PRP/aus_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55881,36,"AUS","Australia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2014/PRP/aus_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55882,36,"AUS","Australia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/AUS/BuiltSettlement/2014/PRP/aus_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55883,76,"BRA","Brazil","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2000/Binary/bra_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55884,76,"BRA","Brazil","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2000/DTE/bra_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55885,76,"BRA","Brazil","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2012/Binary/bra_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55886,76,"BRA","Brazil","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2012/DTE/bra_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55887,76,"BRA","Brazil","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2014/Binary/bra_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55888,76,"BRA","Brazil","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2014/DTE/bra_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55889,76,"BRA","Brazil","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2000/PRP/bra_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55890,76,"BRA","Brazil","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2000/PRP/bra_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55891,76,"BRA","Brazil","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2000/PRP/bra_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55892,76,"BRA","Brazil","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2000/PRP/bra_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55893,76,"BRA","Brazil","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2012/PRP/bra_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55894,76,"BRA","Brazil","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2012/PRP/bra_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55895,76,"BRA","Brazil","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2012/PRP/bra_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55896,76,"BRA","Brazil","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2012/PRP/bra_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55897,76,"BRA","Brazil","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2014/PRP/bra_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55898,76,"BRA","Brazil","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2014/PRP/bra_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55899,76,"BRA","Brazil","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2014/PRP/bra_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55900,76,"BRA","Brazil","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BRA/BuiltSettlement/2014/PRP/bra_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55901,124,"CAN","Canada","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2000/Binary/can_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55902,124,"CAN","Canada","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2000/DTE/can_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55903,124,"CAN","Canada","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2012/Binary/can_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55904,124,"CAN","Canada","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2012/DTE/can_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55905,124,"CAN","Canada","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2014/Binary/can_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55906,124,"CAN","Canada","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2014/DTE/can_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55907,124,"CAN","Canada","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2000/PRP/can_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55908,124,"CAN","Canada","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2000/PRP/can_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55909,124,"CAN","Canada","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2000/PRP/can_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55910,124,"CAN","Canada","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2000/PRP/can_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55911,124,"CAN","Canada","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2012/PRP/can_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55912,124,"CAN","Canada","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2012/PRP/can_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55913,124,"CAN","Canada","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2012/PRP/can_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55914,124,"CAN","Canada","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2012/PRP/can_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55915,124,"CAN","Canada","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2014/PRP/can_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55916,124,"CAN","Canada","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2014/PRP/can_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55917,124,"CAN","Canada","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2014/PRP/can_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55918,124,"CAN","Canada","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CAN/BuiltSettlement/2014/PRP/can_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55919,152,"CHL","Chile","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2000/Binary/chl_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55920,152,"CHL","Chile","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2000/DTE/chl_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55921,152,"CHL","Chile","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2012/Binary/chl_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55922,152,"CHL","Chile","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2012/DTE/chl_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55923,152,"CHL","Chile","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2014/Binary/chl_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55924,152,"CHL","Chile","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2014/DTE/chl_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55925,152,"CHL","Chile","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2000/PRP/chl_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55926,152,"CHL","Chile","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2000/PRP/chl_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55927,152,"CHL","Chile","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2000/PRP/chl_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55928,152,"CHL","Chile","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2000/PRP/chl_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55929,152,"CHL","Chile","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2012/PRP/chl_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55930,152,"CHL","Chile","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2012/PRP/chl_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55931,152,"CHL","Chile","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2012/PRP/chl_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55932,152,"CHL","Chile","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2012/PRP/chl_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55933,152,"CHL","Chile","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2014/PRP/chl_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55934,152,"CHL","Chile","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2014/PRP/chl_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55935,152,"CHL","Chile","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2014/PRP/chl_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55936,152,"CHL","Chile","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CHL/BuiltSettlement/2014/PRP/chl_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55937,4,"AFG","Afghanistan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2000/Binary/afg_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55938,4,"AFG","Afghanistan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2000/DTE/afg_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55939,4,"AFG","Afghanistan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2012/Binary/afg_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55940,4,"AFG","Afghanistan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2012/DTE/afg_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55941,4,"AFG","Afghanistan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2014/Binary/afg_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55942,4,"AFG","Afghanistan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2014/DTE/afg_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55943,4,"AFG","Afghanistan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2000/PRP/afg_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55944,4,"AFG","Afghanistan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2000/PRP/afg_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55945,4,"AFG","Afghanistan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2000/PRP/afg_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55946,4,"AFG","Afghanistan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2000/PRP/afg_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55947,4,"AFG","Afghanistan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2012/PRP/afg_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55948,4,"AFG","Afghanistan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2012/PRP/afg_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55949,4,"AFG","Afghanistan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2012/PRP/afg_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55950,4,"AFG","Afghanistan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2012/PRP/afg_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55951,4,"AFG","Afghanistan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2014/PRP/afg_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55952,4,"AFG","Afghanistan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2014/PRP/afg_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55953,4,"AFG","Afghanistan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2014/PRP/afg_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55954,4,"AFG","Afghanistan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/AFG/BuiltSettlement/2014/PRP/afg_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55955,8,"ALB","Albania","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2000/Binary/alb_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55956,8,"ALB","Albania","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2000/DTE/alb_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55957,8,"ALB","Albania","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2012/Binary/alb_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55958,8,"ALB","Albania","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2012/DTE/alb_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55959,8,"ALB","Albania","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2014/Binary/alb_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55960,8,"ALB","Albania","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2014/DTE/alb_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55961,8,"ALB","Albania","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2000/PRP/alb_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55962,8,"ALB","Albania","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2000/PRP/alb_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55963,8,"ALB","Albania","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2000/PRP/alb_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55964,8,"ALB","Albania","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2000/PRP/alb_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55965,8,"ALB","Albania","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2012/PRP/alb_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55966,8,"ALB","Albania","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2012/PRP/alb_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55967,8,"ALB","Albania","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2012/PRP/alb_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55968,8,"ALB","Albania","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2012/PRP/alb_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55969,8,"ALB","Albania","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2014/PRP/alb_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55970,8,"ALB","Albania","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2014/PRP/alb_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55971,8,"ALB","Albania","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2014/PRP/alb_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55972,8,"ALB","Albania","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ALB/BuiltSettlement/2014/PRP/alb_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55973,10,"ATA","Antarctica","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2000/Binary/ata_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55974,10,"ATA","Antarctica","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2000/DTE/ata_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55975,10,"ATA","Antarctica","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2012/Binary/ata_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55976,10,"ATA","Antarctica","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2012/DTE/ata_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55977,10,"ATA","Antarctica","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2014/Binary/ata_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55978,10,"ATA","Antarctica","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2014/DTE/ata_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55979,10,"ATA","Antarctica","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2000/PRP/ata_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55980,10,"ATA","Antarctica","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2000/PRP/ata_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55981,10,"ATA","Antarctica","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2000/PRP/ata_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
55982,10,"ATA","Antarctica","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2000/PRP/ata_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
55983,10,"ATA","Antarctica","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2012/PRP/ata_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
55984,10,"ATA","Antarctica","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2012/PRP/ata_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
55985,10,"ATA","Antarctica","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2012/PRP/ata_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
55986,10,"ATA","Antarctica","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2012/PRP/ata_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
55987,10,"ATA","Antarctica","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2014/PRP/ata_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
55988,10,"ATA","Antarctica","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2014/PRP/ata_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
55989,10,"ATA","Antarctica","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2014/PRP/ata_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
55990,10,"ATA","Antarctica","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ATA/BuiltSettlement/2014/PRP/ata_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
55991,12,"DZA","Algeria","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2000/Binary/dza_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
55992,12,"DZA","Algeria","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2000/DTE/dza_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
55993,12,"DZA","Algeria","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2012/Binary/dza_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
55994,12,"DZA","Algeria","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2012/DTE/dza_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
55995,12,"DZA","Algeria","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2014/Binary/dza_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
55996,12,"DZA","Algeria","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2014/DTE/dza_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
55997,12,"DZA","Algeria","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2000/PRP/dza_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
55998,12,"DZA","Algeria","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2000/PRP/dza_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
55999,12,"DZA","Algeria","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2000/PRP/dza_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56000,12,"DZA","Algeria","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2000/PRP/dza_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56001,12,"DZA","Algeria","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2012/PRP/dza_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56002,12,"DZA","Algeria","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2012/PRP/dza_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56003,12,"DZA","Algeria","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2012/PRP/dza_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56004,12,"DZA","Algeria","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2012/PRP/dza_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56005,12,"DZA","Algeria","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2014/PRP/dza_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56006,12,"DZA","Algeria","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2014/PRP/dza_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56007,12,"DZA","Algeria","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2014/PRP/dza_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56008,12,"DZA","Algeria","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/DZA/BuiltSettlement/2014/PRP/dza_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56009,16,"ASM","American Samoa","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2000/Binary/asm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56010,16,"ASM","American Samoa","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2000/DTE/asm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56011,16,"ASM","American Samoa","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2012/Binary/asm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56012,16,"ASM","American Samoa","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2012/DTE/asm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56013,16,"ASM","American Samoa","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2014/Binary/asm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56014,16,"ASM","American Samoa","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2014/DTE/asm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56015,16,"ASM","American Samoa","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2000/PRP/asm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56016,16,"ASM","American Samoa","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2000/PRP/asm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56017,16,"ASM","American Samoa","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2000/PRP/asm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56018,16,"ASM","American Samoa","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2000/PRP/asm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56019,16,"ASM","American Samoa","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2012/PRP/asm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56020,16,"ASM","American Samoa","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2012/PRP/asm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56021,16,"ASM","American Samoa","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2012/PRP/asm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56022,16,"ASM","American Samoa","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2012/PRP/asm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56023,16,"ASM","American Samoa","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2014/PRP/asm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56024,16,"ASM","American Samoa","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2014/PRP/asm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56025,16,"ASM","American Samoa","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2014/PRP/asm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56026,16,"ASM","American Samoa","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ASM/BuiltSettlement/2014/PRP/asm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56027,20,"AND","Andorra","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2000/Binary/and_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56028,20,"AND","Andorra","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2000/DTE/and_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56029,20,"AND","Andorra","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2012/Binary/and_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56030,20,"AND","Andorra","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2012/DTE/and_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56031,20,"AND","Andorra","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2014/Binary/and_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56032,20,"AND","Andorra","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2014/DTE/and_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56033,20,"AND","Andorra","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2000/PRP/and_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56034,20,"AND","Andorra","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2000/PRP/and_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56035,20,"AND","Andorra","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2000/PRP/and_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56036,20,"AND","Andorra","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2000/PRP/and_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56037,20,"AND","Andorra","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2012/PRP/and_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56038,20,"AND","Andorra","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2012/PRP/and_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56039,20,"AND","Andorra","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2012/PRP/and_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56040,20,"AND","Andorra","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2012/PRP/and_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56041,20,"AND","Andorra","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2014/PRP/and_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56042,20,"AND","Andorra","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2014/PRP/and_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56043,20,"AND","Andorra","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2014/PRP/and_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56044,20,"AND","Andorra","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/AND/BuiltSettlement/2014/PRP/and_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56045,24,"AGO","Angola","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2000/Binary/ago_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56046,24,"AGO","Angola","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2000/DTE/ago_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56047,24,"AGO","Angola","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2012/Binary/ago_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56048,24,"AGO","Angola","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2012/DTE/ago_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56049,24,"AGO","Angola","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2014/Binary/ago_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56050,24,"AGO","Angola","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2014/DTE/ago_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56051,24,"AGO","Angola","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2000/PRP/ago_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56052,24,"AGO","Angola","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2000/PRP/ago_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56053,24,"AGO","Angola","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2000/PRP/ago_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56054,24,"AGO","Angola","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2000/PRP/ago_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56055,24,"AGO","Angola","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2012/PRP/ago_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56056,24,"AGO","Angola","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2012/PRP/ago_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56057,24,"AGO","Angola","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2012/PRP/ago_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56058,24,"AGO","Angola","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2012/PRP/ago_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56059,24,"AGO","Angola","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2014/PRP/ago_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56060,24,"AGO","Angola","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2014/PRP/ago_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56061,24,"AGO","Angola","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2014/PRP/ago_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56062,24,"AGO","Angola","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/AGO/BuiltSettlement/2014/PRP/ago_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56063,28,"ATG","Antigua and Barbuda","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2000/Binary/atg_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56064,28,"ATG","Antigua and Barbuda","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2000/DTE/atg_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56065,28,"ATG","Antigua and Barbuda","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2012/Binary/atg_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56066,28,"ATG","Antigua and Barbuda","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2012/DTE/atg_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56067,28,"ATG","Antigua and Barbuda","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2014/Binary/atg_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56068,28,"ATG","Antigua and Barbuda","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2014/DTE/atg_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56069,28,"ATG","Antigua and Barbuda","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2000/PRP/atg_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56070,28,"ATG","Antigua and Barbuda","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2000/PRP/atg_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56071,28,"ATG","Antigua and Barbuda","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2000/PRP/atg_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56072,28,"ATG","Antigua and Barbuda","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2000/PRP/atg_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56073,28,"ATG","Antigua and Barbuda","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2012/PRP/atg_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56074,28,"ATG","Antigua and Barbuda","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2012/PRP/atg_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56075,28,"ATG","Antigua and Barbuda","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2012/PRP/atg_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56076,28,"ATG","Antigua and Barbuda","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2012/PRP/atg_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56077,28,"ATG","Antigua and Barbuda","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2014/PRP/atg_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56078,28,"ATG","Antigua and Barbuda","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2014/PRP/atg_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56079,28,"ATG","Antigua and Barbuda","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2014/PRP/atg_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56080,28,"ATG","Antigua and Barbuda","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ATG/BuiltSettlement/2014/PRP/atg_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56081,31,"AZE","Azerbaijan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2000/Binary/aze_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56082,31,"AZE","Azerbaijan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2000/DTE/aze_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56083,31,"AZE","Azerbaijan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2012/Binary/aze_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56084,31,"AZE","Azerbaijan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2012/DTE/aze_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56085,31,"AZE","Azerbaijan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2014/Binary/aze_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56086,31,"AZE","Azerbaijan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2014/DTE/aze_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56087,31,"AZE","Azerbaijan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2000/PRP/aze_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56088,31,"AZE","Azerbaijan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2000/PRP/aze_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56089,31,"AZE","Azerbaijan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2000/PRP/aze_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56090,31,"AZE","Azerbaijan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2000/PRP/aze_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56091,31,"AZE","Azerbaijan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2012/PRP/aze_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56092,31,"AZE","Azerbaijan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2012/PRP/aze_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56093,31,"AZE","Azerbaijan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2012/PRP/aze_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56094,31,"AZE","Azerbaijan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2012/PRP/aze_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56095,31,"AZE","Azerbaijan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2014/PRP/aze_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56096,31,"AZE","Azerbaijan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2014/PRP/aze_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56097,31,"AZE","Azerbaijan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2014/PRP/aze_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56098,31,"AZE","Azerbaijan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/AZE/BuiltSettlement/2014/PRP/aze_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56099,32,"ARG","Argentina","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2000/Binary/arg_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56100,32,"ARG","Argentina","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2000/DTE/arg_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56101,32,"ARG","Argentina","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2012/Binary/arg_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56102,32,"ARG","Argentina","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2012/DTE/arg_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56103,32,"ARG","Argentina","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2014/Binary/arg_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56104,32,"ARG","Argentina","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2014/DTE/arg_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56105,32,"ARG","Argentina","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2000/PRP/arg_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56106,32,"ARG","Argentina","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2000/PRP/arg_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56107,32,"ARG","Argentina","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2000/PRP/arg_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56108,32,"ARG","Argentina","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2000/PRP/arg_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56109,32,"ARG","Argentina","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2012/PRP/arg_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56110,32,"ARG","Argentina","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2012/PRP/arg_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56111,32,"ARG","Argentina","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2012/PRP/arg_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56112,32,"ARG","Argentina","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2012/PRP/arg_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56113,32,"ARG","Argentina","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2014/PRP/arg_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56114,32,"ARG","Argentina","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2014/PRP/arg_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56115,32,"ARG","Argentina","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2014/PRP/arg_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56116,32,"ARG","Argentina","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ARG/BuiltSettlement/2014/PRP/arg_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56117,40,"AUT","Austria","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2000/Binary/aut_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56118,40,"AUT","Austria","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2000/DTE/aut_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56119,40,"AUT","Austria","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2012/Binary/aut_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56120,40,"AUT","Austria","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2012/DTE/aut_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56121,40,"AUT","Austria","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2014/Binary/aut_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56122,40,"AUT","Austria","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2014/DTE/aut_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56123,40,"AUT","Austria","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2000/PRP/aut_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56124,40,"AUT","Austria","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2000/PRP/aut_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56125,40,"AUT","Austria","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2000/PRP/aut_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56126,40,"AUT","Austria","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2000/PRP/aut_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56127,40,"AUT","Austria","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2012/PRP/aut_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56128,40,"AUT","Austria","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2012/PRP/aut_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56129,40,"AUT","Austria","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2012/PRP/aut_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56130,40,"AUT","Austria","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2012/PRP/aut_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56131,40,"AUT","Austria","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2014/PRP/aut_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56132,40,"AUT","Austria","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2014/PRP/aut_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56133,40,"AUT","Austria","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2014/PRP/aut_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56134,40,"AUT","Austria","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/AUT/BuiltSettlement/2014/PRP/aut_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56135,44,"BHS","Bahamas","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2000/Binary/bhs_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56136,44,"BHS","Bahamas","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2000/DTE/bhs_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56137,44,"BHS","Bahamas","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2012/Binary/bhs_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56138,44,"BHS","Bahamas","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2012/DTE/bhs_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56139,44,"BHS","Bahamas","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2014/Binary/bhs_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56140,44,"BHS","Bahamas","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2014/DTE/bhs_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56141,44,"BHS","Bahamas","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2000/PRP/bhs_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56142,44,"BHS","Bahamas","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2000/PRP/bhs_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56143,44,"BHS","Bahamas","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2000/PRP/bhs_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56144,44,"BHS","Bahamas","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2000/PRP/bhs_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56145,44,"BHS","Bahamas","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2012/PRP/bhs_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56146,44,"BHS","Bahamas","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2012/PRP/bhs_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56147,44,"BHS","Bahamas","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2012/PRP/bhs_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56148,44,"BHS","Bahamas","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2012/PRP/bhs_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56149,44,"BHS","Bahamas","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2014/PRP/bhs_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56150,44,"BHS","Bahamas","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2014/PRP/bhs_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56151,44,"BHS","Bahamas","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2014/PRP/bhs_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56152,44,"BHS","Bahamas","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BHS/BuiltSettlement/2014/PRP/bhs_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56153,48,"BHR","Bahrain","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2000/Binary/bhr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56154,48,"BHR","Bahrain","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2000/DTE/bhr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56155,48,"BHR","Bahrain","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2012/Binary/bhr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56156,48,"BHR","Bahrain","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2012/DTE/bhr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56157,48,"BHR","Bahrain","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2014/Binary/bhr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56158,48,"BHR","Bahrain","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2014/DTE/bhr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56159,48,"BHR","Bahrain","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2000/PRP/bhr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56160,48,"BHR","Bahrain","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2000/PRP/bhr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56161,48,"BHR","Bahrain","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2000/PRP/bhr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56162,48,"BHR","Bahrain","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2000/PRP/bhr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56163,48,"BHR","Bahrain","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2012/PRP/bhr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56164,48,"BHR","Bahrain","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2012/PRP/bhr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56165,48,"BHR","Bahrain","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2012/PRP/bhr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56166,48,"BHR","Bahrain","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2012/PRP/bhr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56167,48,"BHR","Bahrain","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2014/PRP/bhr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56168,48,"BHR","Bahrain","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2014/PRP/bhr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56169,48,"BHR","Bahrain","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2014/PRP/bhr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56170,48,"BHR","Bahrain","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BHR/BuiltSettlement/2014/PRP/bhr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56171,50,"BGD","Bangladesh","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2000/Binary/bgd_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56172,50,"BGD","Bangladesh","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2000/DTE/bgd_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56173,50,"BGD","Bangladesh","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2012/Binary/bgd_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56174,50,"BGD","Bangladesh","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2012/DTE/bgd_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56175,50,"BGD","Bangladesh","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2014/Binary/bgd_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56176,50,"BGD","Bangladesh","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2014/DTE/bgd_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56177,50,"BGD","Bangladesh","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2000/PRP/bgd_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56178,50,"BGD","Bangladesh","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2000/PRP/bgd_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56179,50,"BGD","Bangladesh","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2000/PRP/bgd_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56180,50,"BGD","Bangladesh","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2000/PRP/bgd_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56181,50,"BGD","Bangladesh","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2012/PRP/bgd_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56182,50,"BGD","Bangladesh","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2012/PRP/bgd_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56183,50,"BGD","Bangladesh","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2012/PRP/bgd_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56184,50,"BGD","Bangladesh","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2012/PRP/bgd_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56185,50,"BGD","Bangladesh","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2014/PRP/bgd_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56186,50,"BGD","Bangladesh","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2014/PRP/bgd_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56187,50,"BGD","Bangladesh","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2014/PRP/bgd_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56188,50,"BGD","Bangladesh","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BGD/BuiltSettlement/2014/PRP/bgd_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56189,51,"ARM","Armenia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2000/Binary/arm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56190,51,"ARM","Armenia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2000/DTE/arm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56191,51,"ARM","Armenia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2012/Binary/arm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56192,51,"ARM","Armenia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2012/DTE/arm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56193,51,"ARM","Armenia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2014/Binary/arm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56194,51,"ARM","Armenia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2014/DTE/arm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56195,51,"ARM","Armenia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2000/PRP/arm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56196,51,"ARM","Armenia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2000/PRP/arm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56197,51,"ARM","Armenia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2000/PRP/arm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56198,51,"ARM","Armenia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2000/PRP/arm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56199,51,"ARM","Armenia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2012/PRP/arm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56200,51,"ARM","Armenia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2012/PRP/arm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56201,51,"ARM","Armenia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2012/PRP/arm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56202,51,"ARM","Armenia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2012/PRP/arm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56203,51,"ARM","Armenia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2014/PRP/arm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56204,51,"ARM","Armenia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2014/PRP/arm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56205,51,"ARM","Armenia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2014/PRP/arm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56206,51,"ARM","Armenia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ARM/BuiltSettlement/2014/PRP/arm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56207,52,"BRB","Barbados","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2000/Binary/brb_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56208,52,"BRB","Barbados","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2000/DTE/brb_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56209,52,"BRB","Barbados","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2012/Binary/brb_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56210,52,"BRB","Barbados","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2012/DTE/brb_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56211,52,"BRB","Barbados","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2014/Binary/brb_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56212,52,"BRB","Barbados","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2014/DTE/brb_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56213,52,"BRB","Barbados","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2000/PRP/brb_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56214,52,"BRB","Barbados","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2000/PRP/brb_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56215,52,"BRB","Barbados","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2000/PRP/brb_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56216,52,"BRB","Barbados","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2000/PRP/brb_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56217,52,"BRB","Barbados","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2012/PRP/brb_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56218,52,"BRB","Barbados","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2012/PRP/brb_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56219,52,"BRB","Barbados","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2012/PRP/brb_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56220,52,"BRB","Barbados","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2012/PRP/brb_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56221,52,"BRB","Barbados","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2014/PRP/brb_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56222,52,"BRB","Barbados","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2014/PRP/brb_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56223,52,"BRB","Barbados","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2014/PRP/brb_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56224,52,"BRB","Barbados","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BRB/BuiltSettlement/2014/PRP/brb_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56225,56,"BEL","Belgium","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2000/Binary/bel_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56226,56,"BEL","Belgium","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2000/DTE/bel_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56227,56,"BEL","Belgium","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2012/Binary/bel_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56228,56,"BEL","Belgium","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2012/DTE/bel_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56229,56,"BEL","Belgium","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2014/Binary/bel_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56230,56,"BEL","Belgium","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2014/DTE/bel_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56231,56,"BEL","Belgium","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2000/PRP/bel_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56232,56,"BEL","Belgium","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2000/PRP/bel_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56233,56,"BEL","Belgium","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2000/PRP/bel_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56234,56,"BEL","Belgium","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2000/PRP/bel_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56235,56,"BEL","Belgium","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2012/PRP/bel_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56236,56,"BEL","Belgium","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2012/PRP/bel_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56237,56,"BEL","Belgium","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2012/PRP/bel_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56238,56,"BEL","Belgium","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2012/PRP/bel_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56239,56,"BEL","Belgium","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2014/PRP/bel_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56240,56,"BEL","Belgium","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2014/PRP/bel_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56241,56,"BEL","Belgium","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2014/PRP/bel_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56242,56,"BEL","Belgium","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BEL/BuiltSettlement/2014/PRP/bel_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56243,60,"BMU","Bermuda","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2000/Binary/bmu_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56244,60,"BMU","Bermuda","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2000/DTE/bmu_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56245,60,"BMU","Bermuda","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2012/Binary/bmu_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56246,60,"BMU","Bermuda","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2012/DTE/bmu_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56247,60,"BMU","Bermuda","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2014/Binary/bmu_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56248,60,"BMU","Bermuda","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2014/DTE/bmu_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56249,60,"BMU","Bermuda","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2000/PRP/bmu_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56250,60,"BMU","Bermuda","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2000/PRP/bmu_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56251,60,"BMU","Bermuda","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2000/PRP/bmu_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56252,60,"BMU","Bermuda","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2000/PRP/bmu_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56253,60,"BMU","Bermuda","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2012/PRP/bmu_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56254,60,"BMU","Bermuda","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2012/PRP/bmu_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56255,60,"BMU","Bermuda","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2012/PRP/bmu_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56256,60,"BMU","Bermuda","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2012/PRP/bmu_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56257,60,"BMU","Bermuda","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2014/PRP/bmu_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56258,60,"BMU","Bermuda","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2014/PRP/bmu_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56259,60,"BMU","Bermuda","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2014/PRP/bmu_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56260,60,"BMU","Bermuda","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BMU/BuiltSettlement/2014/PRP/bmu_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56261,64,"BTN","Bhutan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2000/Binary/btn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56262,64,"BTN","Bhutan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2000/DTE/btn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56263,64,"BTN","Bhutan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2012/Binary/btn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56264,64,"BTN","Bhutan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2012/DTE/btn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56265,64,"BTN","Bhutan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2014/Binary/btn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56266,64,"BTN","Bhutan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2014/DTE/btn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56267,64,"BTN","Bhutan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2000/PRP/btn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56268,64,"BTN","Bhutan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2000/PRP/btn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56269,64,"BTN","Bhutan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2000/PRP/btn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56270,64,"BTN","Bhutan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2000/PRP/btn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56271,64,"BTN","Bhutan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2012/PRP/btn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56272,64,"BTN","Bhutan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2012/PRP/btn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56273,64,"BTN","Bhutan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2012/PRP/btn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56274,64,"BTN","Bhutan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2012/PRP/btn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56275,64,"BTN","Bhutan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2014/PRP/btn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56276,64,"BTN","Bhutan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2014/PRP/btn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56277,64,"BTN","Bhutan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2014/PRP/btn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56278,64,"BTN","Bhutan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BTN/BuiltSettlement/2014/PRP/btn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56279,68,"BOL","Bolivia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2000/Binary/bol_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56280,68,"BOL","Bolivia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2000/DTE/bol_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56281,68,"BOL","Bolivia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2012/Binary/bol_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56282,68,"BOL","Bolivia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2012/DTE/bol_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56283,68,"BOL","Bolivia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2014/Binary/bol_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56284,68,"BOL","Bolivia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2014/DTE/bol_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56285,68,"BOL","Bolivia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2000/PRP/bol_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56286,68,"BOL","Bolivia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2000/PRP/bol_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56287,68,"BOL","Bolivia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2000/PRP/bol_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56288,68,"BOL","Bolivia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2000/PRP/bol_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56289,68,"BOL","Bolivia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2012/PRP/bol_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56290,68,"BOL","Bolivia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2012/PRP/bol_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56291,68,"BOL","Bolivia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2012/PRP/bol_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56292,68,"BOL","Bolivia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2012/PRP/bol_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56293,68,"BOL","Bolivia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2014/PRP/bol_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56294,68,"BOL","Bolivia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2014/PRP/bol_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56295,68,"BOL","Bolivia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2014/PRP/bol_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56296,68,"BOL","Bolivia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BOL/BuiltSettlement/2014/PRP/bol_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56297,70,"BIH","Bosnia and Herzegovina","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2000/Binary/bih_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56298,70,"BIH","Bosnia and Herzegovina","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2000/DTE/bih_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56299,70,"BIH","Bosnia and Herzegovina","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2012/Binary/bih_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56300,70,"BIH","Bosnia and Herzegovina","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2012/DTE/bih_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56301,70,"BIH","Bosnia and Herzegovina","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2014/Binary/bih_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56302,70,"BIH","Bosnia and Herzegovina","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2014/DTE/bih_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56303,70,"BIH","Bosnia and Herzegovina","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2000/PRP/bih_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56304,70,"BIH","Bosnia and Herzegovina","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2000/PRP/bih_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56305,70,"BIH","Bosnia and Herzegovina","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2000/PRP/bih_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56306,70,"BIH","Bosnia and Herzegovina","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2000/PRP/bih_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56307,70,"BIH","Bosnia and Herzegovina","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2012/PRP/bih_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56308,70,"BIH","Bosnia and Herzegovina","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2012/PRP/bih_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56309,70,"BIH","Bosnia and Herzegovina","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2012/PRP/bih_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56310,70,"BIH","Bosnia and Herzegovina","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2012/PRP/bih_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56311,70,"BIH","Bosnia and Herzegovina","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2014/PRP/bih_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56312,70,"BIH","Bosnia and Herzegovina","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2014/PRP/bih_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56313,70,"BIH","Bosnia and Herzegovina","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2014/PRP/bih_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56314,70,"BIH","Bosnia and Herzegovina","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BIH/BuiltSettlement/2014/PRP/bih_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56315,72,"BWA","Botswana","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2000/Binary/bwa_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56316,72,"BWA","Botswana","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2000/DTE/bwa_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56317,72,"BWA","Botswana","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2012/Binary/bwa_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56318,72,"BWA","Botswana","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2012/DTE/bwa_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56319,72,"BWA","Botswana","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2014/Binary/bwa_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56320,72,"BWA","Botswana","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2014/DTE/bwa_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56321,72,"BWA","Botswana","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2000/PRP/bwa_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56322,72,"BWA","Botswana","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2000/PRP/bwa_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56323,72,"BWA","Botswana","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2000/PRP/bwa_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56324,72,"BWA","Botswana","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2000/PRP/bwa_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56325,72,"BWA","Botswana","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2012/PRP/bwa_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56326,72,"BWA","Botswana","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2012/PRP/bwa_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56327,72,"BWA","Botswana","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2012/PRP/bwa_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56328,72,"BWA","Botswana","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2012/PRP/bwa_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56329,72,"BWA","Botswana","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2014/PRP/bwa_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56330,72,"BWA","Botswana","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2014/PRP/bwa_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56331,72,"BWA","Botswana","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2014/PRP/bwa_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56332,72,"BWA","Botswana","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BWA/BuiltSettlement/2014/PRP/bwa_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56333,74,"BVT","Bouvet Island","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2000/Binary/bvt_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56334,74,"BVT","Bouvet Island","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2000/DTE/bvt_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56335,74,"BVT","Bouvet Island","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2012/Binary/bvt_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56336,74,"BVT","Bouvet Island","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2012/DTE/bvt_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56337,74,"BVT","Bouvet Island","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2014/Binary/bvt_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56338,74,"BVT","Bouvet Island","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2014/DTE/bvt_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56339,74,"BVT","Bouvet Island","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2000/PRP/bvt_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56340,74,"BVT","Bouvet Island","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2000/PRP/bvt_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56341,74,"BVT","Bouvet Island","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2000/PRP/bvt_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56342,74,"BVT","Bouvet Island","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2000/PRP/bvt_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56343,74,"BVT","Bouvet Island","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2012/PRP/bvt_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56344,74,"BVT","Bouvet Island","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2012/PRP/bvt_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56345,74,"BVT","Bouvet Island","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2012/PRP/bvt_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56346,74,"BVT","Bouvet Island","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2012/PRP/bvt_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56347,74,"BVT","Bouvet Island","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2014/PRP/bvt_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56348,74,"BVT","Bouvet Island","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2014/PRP/bvt_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56349,74,"BVT","Bouvet Island","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2014/PRP/bvt_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56350,74,"BVT","Bouvet Island","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BVT/BuiltSettlement/2014/PRP/bvt_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56351,84,"BLZ","Belize","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2000/Binary/blz_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56352,84,"BLZ","Belize","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2000/DTE/blz_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56353,84,"BLZ","Belize","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2012/Binary/blz_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56354,84,"BLZ","Belize","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2012/DTE/blz_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56355,84,"BLZ","Belize","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2014/Binary/blz_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56356,84,"BLZ","Belize","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2014/DTE/blz_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56357,84,"BLZ","Belize","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2000/PRP/blz_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56358,84,"BLZ","Belize","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2000/PRP/blz_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56359,84,"BLZ","Belize","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2000/PRP/blz_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56360,84,"BLZ","Belize","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2000/PRP/blz_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56361,84,"BLZ","Belize","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2012/PRP/blz_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56362,84,"BLZ","Belize","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2012/PRP/blz_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56363,84,"BLZ","Belize","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2012/PRP/blz_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56364,84,"BLZ","Belize","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2012/PRP/blz_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56365,84,"BLZ","Belize","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2014/PRP/blz_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56366,84,"BLZ","Belize","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2014/PRP/blz_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56367,84,"BLZ","Belize","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2014/PRP/blz_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56368,84,"BLZ","Belize","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/BuiltSettlement/2014/PRP/blz_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56369,86,"IOT","British Indian Ocean Territory","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2000/Binary/iot_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56370,86,"IOT","British Indian Ocean Territory","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2000/DTE/iot_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56371,86,"IOT","British Indian Ocean Territory","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2012/Binary/iot_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56372,86,"IOT","British Indian Ocean Territory","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2012/DTE/iot_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56373,86,"IOT","British Indian Ocean Territory","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2014/Binary/iot_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56374,86,"IOT","British Indian Ocean Territory","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2014/DTE/iot_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56375,86,"IOT","British Indian Ocean Territory","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2000/PRP/iot_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56376,86,"IOT","British Indian Ocean Territory","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2000/PRP/iot_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56377,86,"IOT","British Indian Ocean Territory","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2000/PRP/iot_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56378,86,"IOT","British Indian Ocean Territory","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2000/PRP/iot_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56379,86,"IOT","British Indian Ocean Territory","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2012/PRP/iot_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56380,86,"IOT","British Indian Ocean Territory","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2012/PRP/iot_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56381,86,"IOT","British Indian Ocean Territory","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2012/PRP/iot_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56382,86,"IOT","British Indian Ocean Territory","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2012/PRP/iot_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56383,86,"IOT","British Indian Ocean Territory","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2014/PRP/iot_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56384,86,"IOT","British Indian Ocean Territory","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2014/PRP/iot_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56385,86,"IOT","British Indian Ocean Territory","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2014/PRP/iot_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56386,86,"IOT","British Indian Ocean Territory","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/IOT/BuiltSettlement/2014/PRP/iot_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56387,90,"SLB","Solomon Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2000/Binary/slb_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56388,90,"SLB","Solomon Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2000/DTE/slb_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56389,90,"SLB","Solomon Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2012/Binary/slb_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56390,90,"SLB","Solomon Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2012/DTE/slb_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56391,90,"SLB","Solomon Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2014/Binary/slb_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56392,90,"SLB","Solomon Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2014/DTE/slb_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56393,90,"SLB","Solomon Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2000/PRP/slb_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56394,90,"SLB","Solomon Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2000/PRP/slb_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56395,90,"SLB","Solomon Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2000/PRP/slb_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56396,90,"SLB","Solomon Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2000/PRP/slb_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56397,90,"SLB","Solomon Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2012/PRP/slb_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56398,90,"SLB","Solomon Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2012/PRP/slb_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56399,90,"SLB","Solomon Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2012/PRP/slb_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56400,90,"SLB","Solomon Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2012/PRP/slb_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56401,90,"SLB","Solomon Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2014/PRP/slb_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56402,90,"SLB","Solomon Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2014/PRP/slb_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56403,90,"SLB","Solomon Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2014/PRP/slb_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56404,90,"SLB","Solomon Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SLB/BuiltSettlement/2014/PRP/slb_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56405,92,"VGB","British Virgin Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2000/Binary/vgb_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56406,92,"VGB","British Virgin Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2000/DTE/vgb_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56407,92,"VGB","British Virgin Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2012/Binary/vgb_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56408,92,"VGB","British Virgin Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2012/DTE/vgb_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56409,92,"VGB","British Virgin Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2014/Binary/vgb_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56410,92,"VGB","British Virgin Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2014/DTE/vgb_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56411,92,"VGB","British Virgin Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2000/PRP/vgb_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56412,92,"VGB","British Virgin Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2000/PRP/vgb_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56413,92,"VGB","British Virgin Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2000/PRP/vgb_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56414,92,"VGB","British Virgin Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2000/PRP/vgb_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56415,92,"VGB","British Virgin Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2012/PRP/vgb_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56416,92,"VGB","British Virgin Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2012/PRP/vgb_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56417,92,"VGB","British Virgin Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2012/PRP/vgb_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56418,92,"VGB","British Virgin Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2012/PRP/vgb_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56419,92,"VGB","British Virgin Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2014/PRP/vgb_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56420,92,"VGB","British Virgin Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2014/PRP/vgb_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56421,92,"VGB","British Virgin Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2014/PRP/vgb_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56422,92,"VGB","British Virgin Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/VGB/BuiltSettlement/2014/PRP/vgb_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56423,96,"BRN","Brunei","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2000/Binary/brn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56424,96,"BRN","Brunei","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2000/DTE/brn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56425,96,"BRN","Brunei","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2012/Binary/brn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56426,96,"BRN","Brunei","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2012/DTE/brn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56427,96,"BRN","Brunei","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2014/Binary/brn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56428,96,"BRN","Brunei","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2014/DTE/brn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56429,96,"BRN","Brunei","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2000/PRP/brn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56430,96,"BRN","Brunei","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2000/PRP/brn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56431,96,"BRN","Brunei","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2000/PRP/brn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56432,96,"BRN","Brunei","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2000/PRP/brn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56433,96,"BRN","Brunei","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2012/PRP/brn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56434,96,"BRN","Brunei","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2012/PRP/brn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56435,96,"BRN","Brunei","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2012/PRP/brn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56436,96,"BRN","Brunei","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2012/PRP/brn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56437,96,"BRN","Brunei","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2014/PRP/brn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56438,96,"BRN","Brunei","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2014/PRP/brn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56439,96,"BRN","Brunei","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2014/PRP/brn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56440,96,"BRN","Brunei","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BRN/BuiltSettlement/2014/PRP/brn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56441,100,"BGR","Bulgaria","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2000/Binary/bgr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56442,100,"BGR","Bulgaria","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2000/DTE/bgr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56443,100,"BGR","Bulgaria","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2012/Binary/bgr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56444,100,"BGR","Bulgaria","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2012/DTE/bgr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56445,100,"BGR","Bulgaria","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2014/Binary/bgr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56446,100,"BGR","Bulgaria","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2014/DTE/bgr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56447,100,"BGR","Bulgaria","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2000/PRP/bgr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56448,100,"BGR","Bulgaria","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2000/PRP/bgr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56449,100,"BGR","Bulgaria","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2000/PRP/bgr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56450,100,"BGR","Bulgaria","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2000/PRP/bgr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56451,100,"BGR","Bulgaria","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2012/PRP/bgr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56452,100,"BGR","Bulgaria","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2012/PRP/bgr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56453,100,"BGR","Bulgaria","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2012/PRP/bgr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56454,100,"BGR","Bulgaria","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2012/PRP/bgr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56455,100,"BGR","Bulgaria","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2014/PRP/bgr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56456,100,"BGR","Bulgaria","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2014/PRP/bgr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56457,100,"BGR","Bulgaria","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2014/PRP/bgr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56458,100,"BGR","Bulgaria","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BGR/BuiltSettlement/2014/PRP/bgr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56459,104,"MMR","Myanmar","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2000/Binary/mmr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56460,104,"MMR","Myanmar","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2000/DTE/mmr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56461,104,"MMR","Myanmar","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2012/Binary/mmr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56462,104,"MMR","Myanmar","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2012/DTE/mmr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56463,104,"MMR","Myanmar","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2014/Binary/mmr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56464,104,"MMR","Myanmar","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2014/DTE/mmr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56465,104,"MMR","Myanmar","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2000/PRP/mmr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56466,104,"MMR","Myanmar","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2000/PRP/mmr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56467,104,"MMR","Myanmar","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2000/PRP/mmr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56468,104,"MMR","Myanmar","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2000/PRP/mmr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56469,104,"MMR","Myanmar","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2012/PRP/mmr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56470,104,"MMR","Myanmar","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2012/PRP/mmr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56471,104,"MMR","Myanmar","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2012/PRP/mmr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56472,104,"MMR","Myanmar","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2012/PRP/mmr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56473,104,"MMR","Myanmar","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2014/PRP/mmr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56474,104,"MMR","Myanmar","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2014/PRP/mmr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56475,104,"MMR","Myanmar","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2014/PRP/mmr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56476,104,"MMR","Myanmar","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MMR/BuiltSettlement/2014/PRP/mmr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56477,108,"BDI","Burundi","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2000/Binary/bdi_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56478,108,"BDI","Burundi","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2000/DTE/bdi_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56479,108,"BDI","Burundi","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2012/Binary/bdi_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56480,108,"BDI","Burundi","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2012/DTE/bdi_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56481,108,"BDI","Burundi","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2014/Binary/bdi_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56482,108,"BDI","Burundi","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2014/DTE/bdi_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56483,108,"BDI","Burundi","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2000/PRP/bdi_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56484,108,"BDI","Burundi","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2000/PRP/bdi_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56485,108,"BDI","Burundi","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2000/PRP/bdi_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56486,108,"BDI","Burundi","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2000/PRP/bdi_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56487,108,"BDI","Burundi","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2012/PRP/bdi_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56488,108,"BDI","Burundi","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2012/PRP/bdi_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56489,108,"BDI","Burundi","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2012/PRP/bdi_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56490,108,"BDI","Burundi","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2012/PRP/bdi_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56491,108,"BDI","Burundi","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2014/PRP/bdi_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56492,108,"BDI","Burundi","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2014/PRP/bdi_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56493,108,"BDI","Burundi","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2014/PRP/bdi_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56494,108,"BDI","Burundi","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BDI/BuiltSettlement/2014/PRP/bdi_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56495,112,"BLR","Belarus","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2000/Binary/blr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56496,112,"BLR","Belarus","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2000/DTE/blr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56497,112,"BLR","Belarus","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2012/Binary/blr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56498,112,"BLR","Belarus","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2012/DTE/blr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56499,112,"BLR","Belarus","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2014/Binary/blr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56500,112,"BLR","Belarus","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2014/DTE/blr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56501,112,"BLR","Belarus","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2000/PRP/blr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56502,112,"BLR","Belarus","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2000/PRP/blr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56503,112,"BLR","Belarus","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2000/PRP/blr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56504,112,"BLR","Belarus","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2000/PRP/blr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56505,112,"BLR","Belarus","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2012/PRP/blr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56506,112,"BLR","Belarus","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2012/PRP/blr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56507,112,"BLR","Belarus","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2012/PRP/blr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56508,112,"BLR","Belarus","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2012/PRP/blr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56509,112,"BLR","Belarus","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2014/PRP/blr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56510,112,"BLR","Belarus","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2014/PRP/blr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56511,112,"BLR","Belarus","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2014/PRP/blr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56512,112,"BLR","Belarus","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BLR/BuiltSettlement/2014/PRP/blr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56513,116,"KHM","Cambodia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2000/Binary/khm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56514,116,"KHM","Cambodia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2000/DTE/khm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56515,116,"KHM","Cambodia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2012/Binary/khm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56516,116,"KHM","Cambodia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2012/DTE/khm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56517,116,"KHM","Cambodia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2014/Binary/khm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56518,116,"KHM","Cambodia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2014/DTE/khm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56519,116,"KHM","Cambodia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2000/PRP/khm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56520,116,"KHM","Cambodia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2000/PRP/khm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56521,116,"KHM","Cambodia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2000/PRP/khm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56522,116,"KHM","Cambodia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2000/PRP/khm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56523,116,"KHM","Cambodia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2012/PRP/khm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56524,116,"KHM","Cambodia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2012/PRP/khm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56525,116,"KHM","Cambodia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2012/PRP/khm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56526,116,"KHM","Cambodia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2012/PRP/khm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56527,116,"KHM","Cambodia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2014/PRP/khm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56528,116,"KHM","Cambodia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2014/PRP/khm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56529,116,"KHM","Cambodia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2014/PRP/khm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56530,116,"KHM","Cambodia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/KHM/BuiltSettlement/2014/PRP/khm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56531,120,"CMR","Cameroon","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2000/Binary/cmr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56532,120,"CMR","Cameroon","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2000/DTE/cmr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56533,120,"CMR","Cameroon","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2012/Binary/cmr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56534,120,"CMR","Cameroon","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2012/DTE/cmr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56535,120,"CMR","Cameroon","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2014/Binary/cmr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56536,120,"CMR","Cameroon","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2014/DTE/cmr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56537,120,"CMR","Cameroon","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2000/PRP/cmr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56538,120,"CMR","Cameroon","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2000/PRP/cmr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56539,120,"CMR","Cameroon","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2000/PRP/cmr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56540,120,"CMR","Cameroon","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2000/PRP/cmr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56541,120,"CMR","Cameroon","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2012/PRP/cmr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56542,120,"CMR","Cameroon","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2012/PRP/cmr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56543,120,"CMR","Cameroon","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2012/PRP/cmr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56544,120,"CMR","Cameroon","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2012/PRP/cmr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56545,120,"CMR","Cameroon","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2014/PRP/cmr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56546,120,"CMR","Cameroon","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2014/PRP/cmr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56547,120,"CMR","Cameroon","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2014/PRP/cmr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56548,120,"CMR","Cameroon","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CMR/BuiltSettlement/2014/PRP/cmr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56549,132,"CPV","Cape Verde","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2000/Binary/cpv_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56550,132,"CPV","Cape Verde","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2000/DTE/cpv_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56551,132,"CPV","Cape Verde","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2012/Binary/cpv_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56552,132,"CPV","Cape Verde","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2012/DTE/cpv_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56553,132,"CPV","Cape Verde","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2014/Binary/cpv_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56554,132,"CPV","Cape Verde","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2014/DTE/cpv_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56555,132,"CPV","Cape Verde","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2000/PRP/cpv_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56556,132,"CPV","Cape Verde","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2000/PRP/cpv_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56557,132,"CPV","Cape Verde","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2000/PRP/cpv_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56558,132,"CPV","Cape Verde","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2000/PRP/cpv_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56559,132,"CPV","Cape Verde","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2012/PRP/cpv_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56560,132,"CPV","Cape Verde","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2012/PRP/cpv_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56561,132,"CPV","Cape Verde","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2012/PRP/cpv_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56562,132,"CPV","Cape Verde","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2012/PRP/cpv_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56563,132,"CPV","Cape Verde","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2014/PRP/cpv_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56564,132,"CPV","Cape Verde","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2014/PRP/cpv_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56565,132,"CPV","Cape Verde","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2014/PRP/cpv_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56566,132,"CPV","Cape Verde","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CPV/BuiltSettlement/2014/PRP/cpv_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56567,136,"CYM","Cayman Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2000/Binary/cym_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56568,136,"CYM","Cayman Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2000/DTE/cym_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56569,136,"CYM","Cayman Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2012/Binary/cym_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56570,136,"CYM","Cayman Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2012/DTE/cym_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56571,136,"CYM","Cayman Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2014/Binary/cym_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56572,136,"CYM","Cayman Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2014/DTE/cym_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56573,136,"CYM","Cayman Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2000/PRP/cym_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56574,136,"CYM","Cayman Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2000/PRP/cym_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56575,136,"CYM","Cayman Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2000/PRP/cym_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56576,136,"CYM","Cayman Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2000/PRP/cym_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56577,136,"CYM","Cayman Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2012/PRP/cym_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56578,136,"CYM","Cayman Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2012/PRP/cym_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56579,136,"CYM","Cayman Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2012/PRP/cym_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56580,136,"CYM","Cayman Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2012/PRP/cym_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56581,136,"CYM","Cayman Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2014/PRP/cym_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56582,136,"CYM","Cayman Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2014/PRP/cym_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56583,136,"CYM","Cayman Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2014/PRP/cym_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56584,136,"CYM","Cayman Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CYM/BuiltSettlement/2014/PRP/cym_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56585,140,"CAF","Central African Republic","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2000/Binary/caf_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56586,140,"CAF","Central African Republic","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2000/DTE/caf_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56587,140,"CAF","Central African Republic","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2012/Binary/caf_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56588,140,"CAF","Central African Republic","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2012/DTE/caf_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56589,140,"CAF","Central African Republic","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2014/Binary/caf_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56590,140,"CAF","Central African Republic","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2014/DTE/caf_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56591,140,"CAF","Central African Republic","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2000/PRP/caf_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56592,140,"CAF","Central African Republic","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2000/PRP/caf_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56593,140,"CAF","Central African Republic","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2000/PRP/caf_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56594,140,"CAF","Central African Republic","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2000/PRP/caf_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56595,140,"CAF","Central African Republic","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2012/PRP/caf_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56596,140,"CAF","Central African Republic","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2012/PRP/caf_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56597,140,"CAF","Central African Republic","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2012/PRP/caf_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56598,140,"CAF","Central African Republic","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2012/PRP/caf_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56599,140,"CAF","Central African Republic","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2014/PRP/caf_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56600,140,"CAF","Central African Republic","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2014/PRP/caf_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56601,140,"CAF","Central African Republic","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2014/PRP/caf_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56602,140,"CAF","Central African Republic","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CAF/BuiltSettlement/2014/PRP/caf_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56603,144,"LKA","Sri Lanka","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2000/Binary/lka_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56604,144,"LKA","Sri Lanka","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2000/DTE/lka_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56605,144,"LKA","Sri Lanka","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2012/Binary/lka_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56606,144,"LKA","Sri Lanka","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2012/DTE/lka_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56607,144,"LKA","Sri Lanka","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2014/Binary/lka_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56608,144,"LKA","Sri Lanka","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2014/DTE/lka_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56609,144,"LKA","Sri Lanka","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2000/PRP/lka_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56610,144,"LKA","Sri Lanka","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2000/PRP/lka_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56611,144,"LKA","Sri Lanka","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2000/PRP/lka_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56612,144,"LKA","Sri Lanka","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2000/PRP/lka_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56613,144,"LKA","Sri Lanka","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2012/PRP/lka_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56614,144,"LKA","Sri Lanka","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2012/PRP/lka_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56615,144,"LKA","Sri Lanka","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2012/PRP/lka_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56616,144,"LKA","Sri Lanka","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2012/PRP/lka_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56617,144,"LKA","Sri Lanka","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2014/PRP/lka_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56618,144,"LKA","Sri Lanka","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2014/PRP/lka_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56619,144,"LKA","Sri Lanka","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2014/PRP/lka_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56620,144,"LKA","Sri Lanka","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LKA/BuiltSettlement/2014/PRP/lka_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56621,148,"TCD","Chad","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2000/Binary/tcd_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56622,148,"TCD","Chad","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2000/DTE/tcd_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56623,148,"TCD","Chad","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2012/Binary/tcd_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56624,148,"TCD","Chad","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2012/DTE/tcd_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56625,148,"TCD","Chad","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2014/Binary/tcd_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56626,148,"TCD","Chad","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2014/DTE/tcd_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56627,148,"TCD","Chad","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2000/PRP/tcd_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56628,148,"TCD","Chad","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2000/PRP/tcd_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56629,148,"TCD","Chad","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2000/PRP/tcd_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56630,148,"TCD","Chad","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2000/PRP/tcd_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56631,148,"TCD","Chad","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2012/PRP/tcd_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56632,148,"TCD","Chad","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2012/PRP/tcd_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56633,148,"TCD","Chad","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2012/PRP/tcd_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56634,148,"TCD","Chad","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2012/PRP/tcd_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56635,148,"TCD","Chad","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2014/PRP/tcd_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56636,148,"TCD","Chad","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2014/PRP/tcd_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56637,148,"TCD","Chad","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2014/PRP/tcd_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56638,148,"TCD","Chad","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TCD/BuiltSettlement/2014/PRP/tcd_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56639,158,"TWN","Taiwan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2000/Binary/twn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56640,158,"TWN","Taiwan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2000/DTE/twn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56641,158,"TWN","Taiwan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2012/Binary/twn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56642,158,"TWN","Taiwan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2012/DTE/twn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56643,158,"TWN","Taiwan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2014/Binary/twn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56644,158,"TWN","Taiwan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2014/DTE/twn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56645,158,"TWN","Taiwan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2000/PRP/twn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56646,158,"TWN","Taiwan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2000/PRP/twn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56647,158,"TWN","Taiwan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2000/PRP/twn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56648,158,"TWN","Taiwan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2000/PRP/twn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56649,158,"TWN","Taiwan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2012/PRP/twn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56650,158,"TWN","Taiwan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2012/PRP/twn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56651,158,"TWN","Taiwan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2012/PRP/twn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56652,158,"TWN","Taiwan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2012/PRP/twn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56653,158,"TWN","Taiwan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2014/PRP/twn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56654,158,"TWN","Taiwan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2014/PRP/twn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56655,158,"TWN","Taiwan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2014/PRP/twn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56656,158,"TWN","Taiwan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TWN/BuiltSettlement/2014/PRP/twn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56657,170,"COL","Colombia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2000/Binary/col_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56658,170,"COL","Colombia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2000/DTE/col_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56659,170,"COL","Colombia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2012/Binary/col_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56660,170,"COL","Colombia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2012/DTE/col_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56661,170,"COL","Colombia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2014/Binary/col_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56662,170,"COL","Colombia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2014/DTE/col_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56663,170,"COL","Colombia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2000/PRP/col_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56664,170,"COL","Colombia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2000/PRP/col_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56665,170,"COL","Colombia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2000/PRP/col_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56666,170,"COL","Colombia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2000/PRP/col_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56667,170,"COL","Colombia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2012/PRP/col_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56668,170,"COL","Colombia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2012/PRP/col_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56669,170,"COL","Colombia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2012/PRP/col_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56670,170,"COL","Colombia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2012/PRP/col_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56671,170,"COL","Colombia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2014/PRP/col_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56672,170,"COL","Colombia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2014/PRP/col_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56673,170,"COL","Colombia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2014/PRP/col_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56674,170,"COL","Colombia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/COL/BuiltSettlement/2014/PRP/col_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56675,174,"COM","Comoros","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2000/Binary/com_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56676,174,"COM","Comoros","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2000/DTE/com_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56677,174,"COM","Comoros","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2012/Binary/com_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56678,174,"COM","Comoros","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2012/DTE/com_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56679,174,"COM","Comoros","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2014/Binary/com_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56680,174,"COM","Comoros","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2014/DTE/com_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56681,174,"COM","Comoros","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2000/PRP/com_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56682,174,"COM","Comoros","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2000/PRP/com_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56683,174,"COM","Comoros","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2000/PRP/com_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56684,174,"COM","Comoros","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2000/PRP/com_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56685,174,"COM","Comoros","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2012/PRP/com_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56686,174,"COM","Comoros","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2012/PRP/com_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56687,174,"COM","Comoros","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2012/PRP/com_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56688,174,"COM","Comoros","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2012/PRP/com_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56689,174,"COM","Comoros","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2014/PRP/com_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56690,174,"COM","Comoros","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2014/PRP/com_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56691,174,"COM","Comoros","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2014/PRP/com_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56692,174,"COM","Comoros","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/COM/BuiltSettlement/2014/PRP/com_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56693,175,"MYT","Mayotte","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2000/Binary/myt_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56694,175,"MYT","Mayotte","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2000/DTE/myt_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56695,175,"MYT","Mayotte","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2012/Binary/myt_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56696,175,"MYT","Mayotte","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2012/DTE/myt_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56697,175,"MYT","Mayotte","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2014/Binary/myt_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56698,175,"MYT","Mayotte","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2014/DTE/myt_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56699,175,"MYT","Mayotte","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2000/PRP/myt_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56700,175,"MYT","Mayotte","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2000/PRP/myt_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56701,175,"MYT","Mayotte","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2000/PRP/myt_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56702,175,"MYT","Mayotte","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2000/PRP/myt_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56703,175,"MYT","Mayotte","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2012/PRP/myt_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56704,175,"MYT","Mayotte","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2012/PRP/myt_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56705,175,"MYT","Mayotte","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2012/PRP/myt_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56706,175,"MYT","Mayotte","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2012/PRP/myt_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56707,175,"MYT","Mayotte","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2014/PRP/myt_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56708,175,"MYT","Mayotte","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2014/PRP/myt_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56709,175,"MYT","Mayotte","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2014/PRP/myt_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56710,175,"MYT","Mayotte","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MYT/BuiltSettlement/2014/PRP/myt_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56711,178,"COG","Republic of Congo","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2000/Binary/cog_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56712,178,"COG","Republic of Congo","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2000/DTE/cog_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56713,178,"COG","Republic of Congo","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2012/Binary/cog_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56714,178,"COG","Republic of Congo","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2012/DTE/cog_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56715,178,"COG","Republic of Congo","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2014/Binary/cog_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56716,178,"COG","Republic of Congo","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2014/DTE/cog_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56717,178,"COG","Republic of Congo","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2000/PRP/cog_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56718,178,"COG","Republic of Congo","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2000/PRP/cog_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56719,178,"COG","Republic of Congo","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2000/PRP/cog_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56720,178,"COG","Republic of Congo","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2000/PRP/cog_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56721,178,"COG","Republic of Congo","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2012/PRP/cog_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56722,178,"COG","Republic of Congo","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2012/PRP/cog_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56723,178,"COG","Republic of Congo","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2012/PRP/cog_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56724,178,"COG","Republic of Congo","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2012/PRP/cog_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56725,178,"COG","Republic of Congo","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2014/PRP/cog_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56726,178,"COG","Republic of Congo","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2014/PRP/cog_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56727,178,"COG","Republic of Congo","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2014/PRP/cog_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56728,178,"COG","Republic of Congo","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/COG/BuiltSettlement/2014/PRP/cog_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56729,180,"COD","Democratic Republic of the Congo","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2000/Binary/cod_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56730,180,"COD","Democratic Republic of the Congo","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2000/DTE/cod_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56731,180,"COD","Democratic Republic of the Congo","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2012/Binary/cod_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56732,180,"COD","Democratic Republic of the Congo","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2012/DTE/cod_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56733,180,"COD","Democratic Republic of the Congo","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2014/Binary/cod_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56734,180,"COD","Democratic Republic of the Congo","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2014/DTE/cod_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56735,180,"COD","Democratic Republic of the Congo","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2000/PRP/cod_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56736,180,"COD","Democratic Republic of the Congo","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2000/PRP/cod_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56737,180,"COD","Democratic Republic of the Congo","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2000/PRP/cod_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56738,180,"COD","Democratic Republic of the Congo","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2000/PRP/cod_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56739,180,"COD","Democratic Republic of the Congo","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2012/PRP/cod_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56740,180,"COD","Democratic Republic of the Congo","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2012/PRP/cod_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56741,180,"COD","Democratic Republic of the Congo","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2012/PRP/cod_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56742,180,"COD","Democratic Republic of the Congo","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2012/PRP/cod_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56743,180,"COD","Democratic Republic of the Congo","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2014/PRP/cod_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56744,180,"COD","Democratic Republic of the Congo","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2014/PRP/cod_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56745,180,"COD","Democratic Republic of the Congo","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2014/PRP/cod_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56746,180,"COD","Democratic Republic of the Congo","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/COD/BuiltSettlement/2014/PRP/cod_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56747,184,"COK","Cook Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2000/Binary/cok_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56748,184,"COK","Cook Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2000/DTE/cok_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56749,184,"COK","Cook Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2012/Binary/cok_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56750,184,"COK","Cook Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2012/DTE/cok_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56751,184,"COK","Cook Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2014/Binary/cok_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56752,184,"COK","Cook Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2014/DTE/cok_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56753,184,"COK","Cook Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2000/PRP/cok_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56754,184,"COK","Cook Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2000/PRP/cok_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56755,184,"COK","Cook Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2000/PRP/cok_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56756,184,"COK","Cook Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2000/PRP/cok_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56757,184,"COK","Cook Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2012/PRP/cok_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56758,184,"COK","Cook Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2012/PRP/cok_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56759,184,"COK","Cook Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2012/PRP/cok_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56760,184,"COK","Cook Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2012/PRP/cok_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56761,184,"COK","Cook Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2014/PRP/cok_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56762,184,"COK","Cook Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2014/PRP/cok_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56763,184,"COK","Cook Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2014/PRP/cok_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56764,184,"COK","Cook Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/COK/BuiltSettlement/2014/PRP/cok_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56765,188,"CRI","Costa Rica","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2000/Binary/cri_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56766,188,"CRI","Costa Rica","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2000/DTE/cri_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56767,188,"CRI","Costa Rica","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2012/Binary/cri_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56768,188,"CRI","Costa Rica","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2012/DTE/cri_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56769,188,"CRI","Costa Rica","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2014/Binary/cri_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56770,188,"CRI","Costa Rica","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2014/DTE/cri_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56771,188,"CRI","Costa Rica","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2000/PRP/cri_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56772,188,"CRI","Costa Rica","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2000/PRP/cri_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56773,188,"CRI","Costa Rica","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2000/PRP/cri_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56774,188,"CRI","Costa Rica","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2000/PRP/cri_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56775,188,"CRI","Costa Rica","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2012/PRP/cri_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56776,188,"CRI","Costa Rica","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2012/PRP/cri_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56777,188,"CRI","Costa Rica","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2012/PRP/cri_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56778,188,"CRI","Costa Rica","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2012/PRP/cri_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56779,188,"CRI","Costa Rica","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2014/PRP/cri_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56780,188,"CRI","Costa Rica","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2014/PRP/cri_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56781,188,"CRI","Costa Rica","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2014/PRP/cri_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56782,188,"CRI","Costa Rica","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CRI/BuiltSettlement/2014/PRP/cri_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56783,191,"HRV","Croatia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2000/Binary/hrv_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56784,191,"HRV","Croatia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2000/DTE/hrv_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56785,191,"HRV","Croatia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2012/Binary/hrv_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56786,191,"HRV","Croatia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2012/DTE/hrv_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56787,191,"HRV","Croatia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2014/Binary/hrv_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56788,191,"HRV","Croatia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2014/DTE/hrv_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56789,191,"HRV","Croatia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2000/PRP/hrv_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56790,191,"HRV","Croatia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2000/PRP/hrv_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56791,191,"HRV","Croatia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2000/PRP/hrv_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56792,191,"HRV","Croatia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2000/PRP/hrv_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56793,191,"HRV","Croatia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2012/PRP/hrv_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56794,191,"HRV","Croatia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2012/PRP/hrv_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56795,191,"HRV","Croatia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2012/PRP/hrv_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56796,191,"HRV","Croatia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2012/PRP/hrv_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56797,191,"HRV","Croatia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2014/PRP/hrv_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56798,191,"HRV","Croatia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2014/PRP/hrv_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56799,191,"HRV","Croatia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2014/PRP/hrv_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56800,191,"HRV","Croatia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/HRV/BuiltSettlement/2014/PRP/hrv_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56801,192,"CUB","Cuba","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2000/Binary/cub_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56802,192,"CUB","Cuba","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2000/DTE/cub_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56803,192,"CUB","Cuba","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2012/Binary/cub_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56804,192,"CUB","Cuba","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2012/DTE/cub_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56805,192,"CUB","Cuba","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2014/Binary/cub_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56806,192,"CUB","Cuba","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2014/DTE/cub_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56807,192,"CUB","Cuba","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2000/PRP/cub_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56808,192,"CUB","Cuba","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2000/PRP/cub_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56809,192,"CUB","Cuba","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2000/PRP/cub_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56810,192,"CUB","Cuba","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2000/PRP/cub_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56811,192,"CUB","Cuba","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2012/PRP/cub_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56812,192,"CUB","Cuba","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2012/PRP/cub_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56813,192,"CUB","Cuba","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2012/PRP/cub_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56814,192,"CUB","Cuba","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2012/PRP/cub_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56815,192,"CUB","Cuba","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2014/PRP/cub_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56816,192,"CUB","Cuba","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2014/PRP/cub_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56817,192,"CUB","Cuba","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2014/PRP/cub_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56818,192,"CUB","Cuba","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CUB/BuiltSettlement/2014/PRP/cub_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56819,196,"CYP","Cyprus","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2000/Binary/cyp_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56820,196,"CYP","Cyprus","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2000/DTE/cyp_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56821,196,"CYP","Cyprus","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2012/Binary/cyp_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56822,196,"CYP","Cyprus","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2012/DTE/cyp_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56823,196,"CYP","Cyprus","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2014/Binary/cyp_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56824,196,"CYP","Cyprus","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2014/DTE/cyp_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56825,196,"CYP","Cyprus","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2000/PRP/cyp_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56826,196,"CYP","Cyprus","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2000/PRP/cyp_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56827,196,"CYP","Cyprus","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2000/PRP/cyp_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56828,196,"CYP","Cyprus","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2000/PRP/cyp_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56829,196,"CYP","Cyprus","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2012/PRP/cyp_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56830,196,"CYP","Cyprus","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2012/PRP/cyp_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56831,196,"CYP","Cyprus","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2012/PRP/cyp_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56832,196,"CYP","Cyprus","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2012/PRP/cyp_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56833,196,"CYP","Cyprus","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2014/PRP/cyp_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56834,196,"CYP","Cyprus","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2014/PRP/cyp_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56835,196,"CYP","Cyprus","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2014/PRP/cyp_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56836,196,"CYP","Cyprus","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CYP/BuiltSettlement/2014/PRP/cyp_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56837,203,"CZE","Czech Republic","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2000/Binary/cze_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56838,203,"CZE","Czech Republic","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2000/DTE/cze_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56839,203,"CZE","Czech Republic","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2012/Binary/cze_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56840,203,"CZE","Czech Republic","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2012/DTE/cze_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56841,203,"CZE","Czech Republic","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2014/Binary/cze_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56842,203,"CZE","Czech Republic","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2014/DTE/cze_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56843,203,"CZE","Czech Republic","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2000/PRP/cze_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56844,203,"CZE","Czech Republic","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2000/PRP/cze_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56845,203,"CZE","Czech Republic","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2000/PRP/cze_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56846,203,"CZE","Czech Republic","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2000/PRP/cze_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56847,203,"CZE","Czech Republic","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2012/PRP/cze_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56848,203,"CZE","Czech Republic","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2012/PRP/cze_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56849,203,"CZE","Czech Republic","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2012/PRP/cze_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56850,203,"CZE","Czech Republic","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2012/PRP/cze_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56851,203,"CZE","Czech Republic","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2014/PRP/cze_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56852,203,"CZE","Czech Republic","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2014/PRP/cze_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56853,203,"CZE","Czech Republic","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2014/PRP/cze_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56854,203,"CZE","Czech Republic","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CZE/BuiltSettlement/2014/PRP/cze_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56855,204,"BEN","Benin","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2000/Binary/ben_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56856,204,"BEN","Benin","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2000/DTE/ben_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56857,204,"BEN","Benin","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2012/Binary/ben_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56858,204,"BEN","Benin","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2012/DTE/ben_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56859,204,"BEN","Benin","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2014/Binary/ben_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56860,204,"BEN","Benin","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2014/DTE/ben_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56861,204,"BEN","Benin","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2000/PRP/ben_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56862,204,"BEN","Benin","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2000/PRP/ben_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56863,204,"BEN","Benin","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2000/PRP/ben_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56864,204,"BEN","Benin","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2000/PRP/ben_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56865,204,"BEN","Benin","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2012/PRP/ben_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56866,204,"BEN","Benin","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2012/PRP/ben_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56867,204,"BEN","Benin","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2012/PRP/ben_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56868,204,"BEN","Benin","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2012/PRP/ben_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56869,204,"BEN","Benin","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2014/PRP/ben_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56870,204,"BEN","Benin","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2014/PRP/ben_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56871,204,"BEN","Benin","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2014/PRP/ben_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56872,204,"BEN","Benin","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BEN/BuiltSettlement/2014/PRP/ben_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56873,208,"DNK","Denmark","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2000/Binary/dnk_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56874,208,"DNK","Denmark","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2000/DTE/dnk_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56875,208,"DNK","Denmark","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2012/Binary/dnk_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56876,208,"DNK","Denmark","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2012/DTE/dnk_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56877,208,"DNK","Denmark","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2014/Binary/dnk_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56878,208,"DNK","Denmark","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2014/DTE/dnk_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56879,208,"DNK","Denmark","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2000/PRP/dnk_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56880,208,"DNK","Denmark","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2000/PRP/dnk_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56881,208,"DNK","Denmark","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2000/PRP/dnk_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56882,208,"DNK","Denmark","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2000/PRP/dnk_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56883,208,"DNK","Denmark","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2012/PRP/dnk_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56884,208,"DNK","Denmark","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2012/PRP/dnk_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56885,208,"DNK","Denmark","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2012/PRP/dnk_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56886,208,"DNK","Denmark","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2012/PRP/dnk_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56887,208,"DNK","Denmark","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2014/PRP/dnk_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56888,208,"DNK","Denmark","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2014/PRP/dnk_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56889,208,"DNK","Denmark","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2014/PRP/dnk_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56890,208,"DNK","Denmark","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/DNK/BuiltSettlement/2014/PRP/dnk_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56891,212,"DMA","Dominica","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2000/Binary/dma_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56892,212,"DMA","Dominica","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2000/DTE/dma_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56893,212,"DMA","Dominica","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2012/Binary/dma_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56894,212,"DMA","Dominica","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2012/DTE/dma_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56895,212,"DMA","Dominica","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2014/Binary/dma_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56896,212,"DMA","Dominica","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2014/DTE/dma_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56897,212,"DMA","Dominica","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2000/PRP/dma_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56898,212,"DMA","Dominica","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2000/PRP/dma_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56899,212,"DMA","Dominica","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2000/PRP/dma_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56900,212,"DMA","Dominica","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2000/PRP/dma_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56901,212,"DMA","Dominica","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2012/PRP/dma_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56902,212,"DMA","Dominica","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2012/PRP/dma_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56903,212,"DMA","Dominica","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2012/PRP/dma_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56904,212,"DMA","Dominica","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2012/PRP/dma_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56905,212,"DMA","Dominica","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2014/PRP/dma_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56906,212,"DMA","Dominica","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2014/PRP/dma_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56907,212,"DMA","Dominica","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2014/PRP/dma_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56908,212,"DMA","Dominica","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/DMA/BuiltSettlement/2014/PRP/dma_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56909,214,"DOM","Dominican Republic","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2000/Binary/dom_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56910,214,"DOM","Dominican Republic","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2000/DTE/dom_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56911,214,"DOM","Dominican Republic","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2012/Binary/dom_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56912,214,"DOM","Dominican Republic","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2012/DTE/dom_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56913,214,"DOM","Dominican Republic","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2014/Binary/dom_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56914,214,"DOM","Dominican Republic","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2014/DTE/dom_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56915,214,"DOM","Dominican Republic","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2000/PRP/dom_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56916,214,"DOM","Dominican Republic","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2000/PRP/dom_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56917,214,"DOM","Dominican Republic","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2000/PRP/dom_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56918,214,"DOM","Dominican Republic","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2000/PRP/dom_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56919,214,"DOM","Dominican Republic","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2012/PRP/dom_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56920,214,"DOM","Dominican Republic","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2012/PRP/dom_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56921,214,"DOM","Dominican Republic","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2012/PRP/dom_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56922,214,"DOM","Dominican Republic","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2012/PRP/dom_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56923,214,"DOM","Dominican Republic","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2014/PRP/dom_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56924,214,"DOM","Dominican Republic","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2014/PRP/dom_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56925,214,"DOM","Dominican Republic","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2014/PRP/dom_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56926,214,"DOM","Dominican Republic","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/DOM/BuiltSettlement/2014/PRP/dom_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56927,218,"ECU","Ecuador","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2000/Binary/ecu_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56928,218,"ECU","Ecuador","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2000/DTE/ecu_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56929,218,"ECU","Ecuador","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2012/Binary/ecu_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56930,218,"ECU","Ecuador","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2012/DTE/ecu_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56931,218,"ECU","Ecuador","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2014/Binary/ecu_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56932,218,"ECU","Ecuador","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2014/DTE/ecu_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56933,218,"ECU","Ecuador","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2000/PRP/ecu_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56934,218,"ECU","Ecuador","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2000/PRP/ecu_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56935,218,"ECU","Ecuador","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2000/PRP/ecu_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56936,218,"ECU","Ecuador","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2000/PRP/ecu_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56937,218,"ECU","Ecuador","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2012/PRP/ecu_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56938,218,"ECU","Ecuador","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2012/PRP/ecu_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56939,218,"ECU","Ecuador","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2012/PRP/ecu_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56940,218,"ECU","Ecuador","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2012/PRP/ecu_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56941,218,"ECU","Ecuador","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2014/PRP/ecu_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56942,218,"ECU","Ecuador","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2014/PRP/ecu_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56943,218,"ECU","Ecuador","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2014/PRP/ecu_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56944,218,"ECU","Ecuador","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ECU/BuiltSettlement/2014/PRP/ecu_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56945,222,"SLV","El Salvador","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2000/Binary/slv_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56946,222,"SLV","El Salvador","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2000/DTE/slv_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56947,222,"SLV","El Salvador","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2012/Binary/slv_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56948,222,"SLV","El Salvador","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2012/DTE/slv_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56949,222,"SLV","El Salvador","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2014/Binary/slv_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56950,222,"SLV","El Salvador","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2014/DTE/slv_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56951,222,"SLV","El Salvador","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2000/PRP/slv_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56952,222,"SLV","El Salvador","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2000/PRP/slv_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56953,222,"SLV","El Salvador","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2000/PRP/slv_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56954,222,"SLV","El Salvador","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2000/PRP/slv_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56955,222,"SLV","El Salvador","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2012/PRP/slv_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56956,222,"SLV","El Salvador","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2012/PRP/slv_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56957,222,"SLV","El Salvador","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2012/PRP/slv_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56958,222,"SLV","El Salvador","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2012/PRP/slv_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56959,222,"SLV","El Salvador","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2014/PRP/slv_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56960,222,"SLV","El Salvador","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2014/PRP/slv_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56961,222,"SLV","El Salvador","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2014/PRP/slv_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56962,222,"SLV","El Salvador","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SLV/BuiltSettlement/2014/PRP/slv_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56963,226,"GNQ","Equatorial Guinea","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2000/Binary/gnq_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56964,226,"GNQ","Equatorial Guinea","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2000/DTE/gnq_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56965,226,"GNQ","Equatorial Guinea","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2012/Binary/gnq_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56966,226,"GNQ","Equatorial Guinea","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2012/DTE/gnq_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56967,226,"GNQ","Equatorial Guinea","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2014/Binary/gnq_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56968,226,"GNQ","Equatorial Guinea","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2014/DTE/gnq_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56969,226,"GNQ","Equatorial Guinea","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2000/PRP/gnq_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56970,226,"GNQ","Equatorial Guinea","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2000/PRP/gnq_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56971,226,"GNQ","Equatorial Guinea","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2000/PRP/gnq_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56972,226,"GNQ","Equatorial Guinea","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2000/PRP/gnq_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56973,226,"GNQ","Equatorial Guinea","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2012/PRP/gnq_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56974,226,"GNQ","Equatorial Guinea","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2012/PRP/gnq_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56975,226,"GNQ","Equatorial Guinea","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2012/PRP/gnq_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56976,226,"GNQ","Equatorial Guinea","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2012/PRP/gnq_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56977,226,"GNQ","Equatorial Guinea","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2014/PRP/gnq_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56978,226,"GNQ","Equatorial Guinea","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2014/PRP/gnq_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56979,226,"GNQ","Equatorial Guinea","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2014/PRP/gnq_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56980,226,"GNQ","Equatorial Guinea","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/BuiltSettlement/2014/PRP/gnq_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56981,231,"ETH","Ethiopia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2000/Binary/eth_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
56982,231,"ETH","Ethiopia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2000/DTE/eth_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
56983,231,"ETH","Ethiopia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2012/Binary/eth_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
56984,231,"ETH","Ethiopia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2012/DTE/eth_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
56985,231,"ETH","Ethiopia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2014/Binary/eth_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
56986,231,"ETH","Ethiopia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2014/DTE/eth_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
56987,231,"ETH","Ethiopia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2000/PRP/eth_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
56988,231,"ETH","Ethiopia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2000/PRP/eth_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
56989,231,"ETH","Ethiopia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2000/PRP/eth_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
56990,231,"ETH","Ethiopia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2000/PRP/eth_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
56991,231,"ETH","Ethiopia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2012/PRP/eth_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
56992,231,"ETH","Ethiopia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2012/PRP/eth_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
56993,231,"ETH","Ethiopia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2012/PRP/eth_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
56994,231,"ETH","Ethiopia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2012/PRP/eth_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
56995,231,"ETH","Ethiopia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2014/PRP/eth_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
56996,231,"ETH","Ethiopia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2014/PRP/eth_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
56997,231,"ETH","Ethiopia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2014/PRP/eth_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
56998,231,"ETH","Ethiopia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ETH/BuiltSettlement/2014/PRP/eth_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
56999,232,"ERI","Eritrea","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2000/Binary/eri_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57000,232,"ERI","Eritrea","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2000/DTE/eri_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57001,232,"ERI","Eritrea","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2012/Binary/eri_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57002,232,"ERI","Eritrea","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2012/DTE/eri_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57003,232,"ERI","Eritrea","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2014/Binary/eri_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57004,232,"ERI","Eritrea","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2014/DTE/eri_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57005,232,"ERI","Eritrea","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2000/PRP/eri_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57006,232,"ERI","Eritrea","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2000/PRP/eri_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57007,232,"ERI","Eritrea","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2000/PRP/eri_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57008,232,"ERI","Eritrea","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2000/PRP/eri_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57009,232,"ERI","Eritrea","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2012/PRP/eri_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57010,232,"ERI","Eritrea","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2012/PRP/eri_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57011,232,"ERI","Eritrea","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2012/PRP/eri_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57012,232,"ERI","Eritrea","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2012/PRP/eri_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57013,232,"ERI","Eritrea","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2014/PRP/eri_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57014,232,"ERI","Eritrea","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2014/PRP/eri_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57015,232,"ERI","Eritrea","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2014/PRP/eri_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57016,232,"ERI","Eritrea","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ERI/BuiltSettlement/2014/PRP/eri_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57017,233,"EST","Estonia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2000/Binary/est_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57018,233,"EST","Estonia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2000/DTE/est_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57019,233,"EST","Estonia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2012/Binary/est_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57020,233,"EST","Estonia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2012/DTE/est_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57021,233,"EST","Estonia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2014/Binary/est_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57022,233,"EST","Estonia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2014/DTE/est_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57023,233,"EST","Estonia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2000/PRP/est_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57024,233,"EST","Estonia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2000/PRP/est_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57025,233,"EST","Estonia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2000/PRP/est_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57026,233,"EST","Estonia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2000/PRP/est_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57027,233,"EST","Estonia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2012/PRP/est_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57028,233,"EST","Estonia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2012/PRP/est_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57029,233,"EST","Estonia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2012/PRP/est_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57030,233,"EST","Estonia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2012/PRP/est_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57031,233,"EST","Estonia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2014/PRP/est_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57032,233,"EST","Estonia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2014/PRP/est_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57033,233,"EST","Estonia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2014/PRP/est_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57034,233,"EST","Estonia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/EST/BuiltSettlement/2014/PRP/est_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57035,234,"FRO","Faroe Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2000/Binary/fro_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57036,234,"FRO","Faroe Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2000/DTE/fro_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57037,234,"FRO","Faroe Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2012/Binary/fro_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57038,234,"FRO","Faroe Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2012/DTE/fro_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57039,234,"FRO","Faroe Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2014/Binary/fro_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57040,234,"FRO","Faroe Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2014/DTE/fro_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57041,234,"FRO","Faroe Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2000/PRP/fro_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57042,234,"FRO","Faroe Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2000/PRP/fro_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57043,234,"FRO","Faroe Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2000/PRP/fro_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57044,234,"FRO","Faroe Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2000/PRP/fro_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57045,234,"FRO","Faroe Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2012/PRP/fro_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57046,234,"FRO","Faroe Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2012/PRP/fro_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57047,234,"FRO","Faroe Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2012/PRP/fro_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57048,234,"FRO","Faroe Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2012/PRP/fro_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57049,234,"FRO","Faroe Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2014/PRP/fro_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57050,234,"FRO","Faroe Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2014/PRP/fro_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57051,234,"FRO","Faroe Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2014/PRP/fro_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57052,234,"FRO","Faroe Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/FRO/BuiltSettlement/2014/PRP/fro_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57053,238,"FLK","Falkland Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2000/Binary/flk_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57054,238,"FLK","Falkland Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2000/DTE/flk_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57055,238,"FLK","Falkland Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2012/Binary/flk_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57056,238,"FLK","Falkland Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2012/DTE/flk_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57057,238,"FLK","Falkland Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2014/Binary/flk_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57058,238,"FLK","Falkland Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2014/DTE/flk_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57059,238,"FLK","Falkland Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2000/PRP/flk_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57060,238,"FLK","Falkland Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2000/PRP/flk_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57061,238,"FLK","Falkland Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2000/PRP/flk_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57062,238,"FLK","Falkland Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2000/PRP/flk_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57063,238,"FLK","Falkland Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2012/PRP/flk_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57064,238,"FLK","Falkland Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2012/PRP/flk_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57065,238,"FLK","Falkland Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2012/PRP/flk_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57066,238,"FLK","Falkland Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2012/PRP/flk_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57067,238,"FLK","Falkland Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2014/PRP/flk_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57068,238,"FLK","Falkland Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2014/PRP/flk_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57069,238,"FLK","Falkland Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2014/PRP/flk_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57070,238,"FLK","Falkland Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/FLK/BuiltSettlement/2014/PRP/flk_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57071,239,"SGS","South Georgia and the South Sandwich Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2000/Binary/sgs_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57072,239,"SGS","South Georgia and the South Sandwich Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2000/DTE/sgs_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57073,239,"SGS","South Georgia and the South Sandwich Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2012/Binary/sgs_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57074,239,"SGS","South Georgia and the South Sandwich Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2012/DTE/sgs_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57075,239,"SGS","South Georgia and the South Sandwich Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2014/Binary/sgs_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57076,239,"SGS","South Georgia and the South Sandwich Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2014/DTE/sgs_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57077,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2000/PRP/sgs_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57078,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2000/PRP/sgs_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57079,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2000/PRP/sgs_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57080,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2000/PRP/sgs_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57081,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2012/PRP/sgs_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57082,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2012/PRP/sgs_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57083,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2012/PRP/sgs_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57084,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2012/PRP/sgs_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57085,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2014/PRP/sgs_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57086,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2014/PRP/sgs_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57087,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2014/PRP/sgs_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57088,239,"SGS","South Georgia and the South Sandwich Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SGS/BuiltSettlement/2014/PRP/sgs_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57089,242,"FJI","Fiji","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2000/Binary/fji_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57090,242,"FJI","Fiji","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2000/DTE/fji_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57091,242,"FJI","Fiji","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2012/Binary/fji_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57092,242,"FJI","Fiji","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2012/DTE/fji_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57093,242,"FJI","Fiji","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2014/Binary/fji_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57094,242,"FJI","Fiji","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2014/DTE/fji_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57095,242,"FJI","Fiji","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2000/PRP/fji_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57096,242,"FJI","Fiji","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2000/PRP/fji_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57097,242,"FJI","Fiji","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2000/PRP/fji_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57098,242,"FJI","Fiji","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2000/PRP/fji_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57099,242,"FJI","Fiji","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2012/PRP/fji_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57100,242,"FJI","Fiji","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2012/PRP/fji_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57101,242,"FJI","Fiji","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2012/PRP/fji_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57102,242,"FJI","Fiji","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2012/PRP/fji_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57103,242,"FJI","Fiji","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2014/PRP/fji_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57104,242,"FJI","Fiji","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2014/PRP/fji_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57105,242,"FJI","Fiji","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2014/PRP/fji_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57106,242,"FJI","Fiji","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/FJI/BuiltSettlement/2014/PRP/fji_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57107,246,"FIN","Finland","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2000/Binary/fin_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57108,246,"FIN","Finland","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2000/DTE/fin_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57109,246,"FIN","Finland","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2012/Binary/fin_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57110,246,"FIN","Finland","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2012/DTE/fin_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57111,246,"FIN","Finland","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2014/Binary/fin_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57112,246,"FIN","Finland","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2014/DTE/fin_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57113,246,"FIN","Finland","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2000/PRP/fin_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57114,246,"FIN","Finland","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2000/PRP/fin_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57115,246,"FIN","Finland","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2000/PRP/fin_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57116,246,"FIN","Finland","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2000/PRP/fin_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57117,246,"FIN","Finland","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2012/PRP/fin_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57118,246,"FIN","Finland","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2012/PRP/fin_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57119,246,"FIN","Finland","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2012/PRP/fin_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57120,246,"FIN","Finland","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2012/PRP/fin_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57121,246,"FIN","Finland","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2014/PRP/fin_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57122,246,"FIN","Finland","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2014/PRP/fin_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57123,246,"FIN","Finland","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2014/PRP/fin_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57124,246,"FIN","Finland","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/FIN/BuiltSettlement/2014/PRP/fin_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57125,248,"ALA","Aland Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2000/Binary/ala_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57126,248,"ALA","Aland Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2000/DTE/ala_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57127,248,"ALA","Aland Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2012/Binary/ala_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57128,248,"ALA","Aland Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2012/DTE/ala_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57129,248,"ALA","Aland Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2014/Binary/ala_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57130,248,"ALA","Aland Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2014/DTE/ala_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57131,248,"ALA","Aland Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2000/PRP/ala_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57132,248,"ALA","Aland Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2000/PRP/ala_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57133,248,"ALA","Aland Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2000/PRP/ala_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57134,248,"ALA","Aland Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2000/PRP/ala_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57135,248,"ALA","Aland Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2012/PRP/ala_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57136,248,"ALA","Aland Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2012/PRP/ala_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57137,248,"ALA","Aland Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2012/PRP/ala_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57138,248,"ALA","Aland Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2012/PRP/ala_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57139,248,"ALA","Aland Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2014/PRP/ala_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57140,248,"ALA","Aland Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2014/PRP/ala_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57141,248,"ALA","Aland Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2014/PRP/ala_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57142,248,"ALA","Aland Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ALA/BuiltSettlement/2014/PRP/ala_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57143,250,"FRA","France","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2000/Binary/fra_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57144,250,"FRA","France","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2000/DTE/fra_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57145,250,"FRA","France","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2012/Binary/fra_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57146,250,"FRA","France","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2012/DTE/fra_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57147,250,"FRA","France","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2014/Binary/fra_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57148,250,"FRA","France","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2014/DTE/fra_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57149,250,"FRA","France","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2000/PRP/fra_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57150,250,"FRA","France","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2000/PRP/fra_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57151,250,"FRA","France","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2000/PRP/fra_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57152,250,"FRA","France","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2000/PRP/fra_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57153,250,"FRA","France","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2012/PRP/fra_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57154,250,"FRA","France","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2012/PRP/fra_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57155,250,"FRA","France","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2012/PRP/fra_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57156,250,"FRA","France","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2012/PRP/fra_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57157,250,"FRA","France","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2014/PRP/fra_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57158,250,"FRA","France","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2014/PRP/fra_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57159,250,"FRA","France","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2014/PRP/fra_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57160,250,"FRA","France","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/FRA/BuiltSettlement/2014/PRP/fra_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57161,254,"GUF","French Guiana","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2000/Binary/guf_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57162,254,"GUF","French Guiana","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2000/DTE/guf_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57163,254,"GUF","French Guiana","ghslesaccilc100m_2012","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2012/Binary/guf_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57164,254,"GUF","French Guiana","dst_ghslesaccilc100m_2012","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2012/DTE/guf_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57165,254,"GUF","French Guiana","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2014/Binary/guf_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57166,254,"GUF","French Guiana","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2014/DTE/guf_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57167,254,"GUF","French Guiana","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2000/PRP/guf_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57168,254,"GUF","French Guiana","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2000/PRP/guf_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57169,254,"GUF","French Guiana","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2000/PRP/guf_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57170,254,"GUF","French Guiana","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2000/PRP/guf_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57171,254,"GUF","French Guiana","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2012/PRP/guf_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57172,254,"GUF","French Guiana","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2012/PRP/guf_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57173,254,"GUF","French Guiana","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2012/PRP/guf_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57174,254,"GUF","French Guiana","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2012/PRP/guf_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57175,254,"GUF","French Guiana","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2014/PRP/guf_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57176,254,"GUF","French Guiana","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2014/PRP/guf_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57177,254,"GUF","French Guiana","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2014/PRP/guf_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57178,254,"GUF","French Guiana","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GUF/BuiltSettlement/2014/PRP/guf_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57179,258,"PYF","French Polynesia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2000/Binary/pyf_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57180,258,"PYF","French Polynesia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2000/DTE/pyf_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57181,258,"PYF","French Polynesia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2012/Binary/pyf_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57182,258,"PYF","French Polynesia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2012/DTE/pyf_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57183,258,"PYF","French Polynesia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2014/Binary/pyf_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57184,258,"PYF","French Polynesia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2014/DTE/pyf_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57185,258,"PYF","French Polynesia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2000/PRP/pyf_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57186,258,"PYF","French Polynesia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2000/PRP/pyf_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57187,258,"PYF","French Polynesia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2000/PRP/pyf_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57188,258,"PYF","French Polynesia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2000/PRP/pyf_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57189,258,"PYF","French Polynesia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2012/PRP/pyf_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57190,258,"PYF","French Polynesia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2012/PRP/pyf_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57191,258,"PYF","French Polynesia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2012/PRP/pyf_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57192,258,"PYF","French Polynesia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2012/PRP/pyf_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57193,258,"PYF","French Polynesia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2014/PRP/pyf_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57194,258,"PYF","French Polynesia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2014/PRP/pyf_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57195,258,"PYF","French Polynesia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2014/PRP/pyf_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57196,258,"PYF","French Polynesia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PYF/BuiltSettlement/2014/PRP/pyf_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57197,260,"ATF","French Southern Territories","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2000/Binary/atf_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57198,260,"ATF","French Southern Territories","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2000/DTE/atf_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57199,260,"ATF","French Southern Territories","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2012/Binary/atf_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57200,260,"ATF","French Southern Territories","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2012/DTE/atf_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57201,260,"ATF","French Southern Territories","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2014/Binary/atf_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57202,260,"ATF","French Southern Territories","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2014/DTE/atf_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57203,260,"ATF","French Southern Territories","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2000/PRP/atf_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57204,260,"ATF","French Southern Territories","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2000/PRP/atf_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57205,260,"ATF","French Southern Territories","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2000/PRP/atf_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57206,260,"ATF","French Southern Territories","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2000/PRP/atf_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57207,260,"ATF","French Southern Territories","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2012/PRP/atf_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57208,260,"ATF","French Southern Territories","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2012/PRP/atf_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57209,260,"ATF","French Southern Territories","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2012/PRP/atf_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57210,260,"ATF","French Southern Territories","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2012/PRP/atf_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57211,260,"ATF","French Southern Territories","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2014/PRP/atf_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57212,260,"ATF","French Southern Territories","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2014/PRP/atf_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57213,260,"ATF","French Southern Territories","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2014/PRP/atf_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57214,260,"ATF","French Southern Territories","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ATF/BuiltSettlement/2014/PRP/atf_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57215,262,"DJI","Djibouti","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2000/Binary/dji_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57216,262,"DJI","Djibouti","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2000/DTE/dji_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57217,262,"DJI","Djibouti","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2012/Binary/dji_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57218,262,"DJI","Djibouti","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2012/DTE/dji_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57219,262,"DJI","Djibouti","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2014/Binary/dji_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57220,262,"DJI","Djibouti","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2014/DTE/dji_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57221,262,"DJI","Djibouti","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2000/PRP/dji_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57222,262,"DJI","Djibouti","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2000/PRP/dji_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57223,262,"DJI","Djibouti","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2000/PRP/dji_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57224,262,"DJI","Djibouti","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2000/PRP/dji_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57225,262,"DJI","Djibouti","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2012/PRP/dji_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57226,262,"DJI","Djibouti","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2012/PRP/dji_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57227,262,"DJI","Djibouti","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2012/PRP/dji_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57228,262,"DJI","Djibouti","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2012/PRP/dji_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57229,262,"DJI","Djibouti","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2014/PRP/dji_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57230,262,"DJI","Djibouti","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2014/PRP/dji_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57231,262,"DJI","Djibouti","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2014/PRP/dji_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57232,262,"DJI","Djibouti","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/DJI/BuiltSettlement/2014/PRP/dji_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57233,266,"GAB","Gabon","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2000/Binary/gab_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57234,266,"GAB","Gabon","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2000/DTE/gab_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57235,266,"GAB","Gabon","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2012/Binary/gab_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57236,266,"GAB","Gabon","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2012/DTE/gab_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57237,266,"GAB","Gabon","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2014/Binary/gab_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57238,266,"GAB","Gabon","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2014/DTE/gab_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57239,266,"GAB","Gabon","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2000/PRP/gab_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57240,266,"GAB","Gabon","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2000/PRP/gab_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57241,266,"GAB","Gabon","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2000/PRP/gab_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57242,266,"GAB","Gabon","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2000/PRP/gab_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57243,266,"GAB","Gabon","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2012/PRP/gab_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57244,266,"GAB","Gabon","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2012/PRP/gab_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57245,266,"GAB","Gabon","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2012/PRP/gab_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57246,266,"GAB","Gabon","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2012/PRP/gab_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57247,266,"GAB","Gabon","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2014/PRP/gab_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57248,266,"GAB","Gabon","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2014/PRP/gab_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57249,266,"GAB","Gabon","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2014/PRP/gab_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57250,266,"GAB","Gabon","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GAB/BuiltSettlement/2014/PRP/gab_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57251,268,"GEO","Georgia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2000/Binary/geo_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57252,268,"GEO","Georgia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2000/DTE/geo_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57253,268,"GEO","Georgia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2012/Binary/geo_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57254,268,"GEO","Georgia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2012/DTE/geo_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57255,268,"GEO","Georgia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2014/Binary/geo_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57256,268,"GEO","Georgia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2014/DTE/geo_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57257,268,"GEO","Georgia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2000/PRP/geo_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57258,268,"GEO","Georgia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2000/PRP/geo_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57259,268,"GEO","Georgia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2000/PRP/geo_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57260,268,"GEO","Georgia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2000/PRP/geo_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57261,268,"GEO","Georgia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2012/PRP/geo_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57262,268,"GEO","Georgia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2012/PRP/geo_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57263,268,"GEO","Georgia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2012/PRP/geo_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57264,268,"GEO","Georgia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2012/PRP/geo_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57265,268,"GEO","Georgia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2014/PRP/geo_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57266,268,"GEO","Georgia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2014/PRP/geo_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57267,268,"GEO","Georgia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2014/PRP/geo_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57268,268,"GEO","Georgia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GEO/BuiltSettlement/2014/PRP/geo_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57269,270,"GMB","Gambia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2000/Binary/gmb_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57270,270,"GMB","Gambia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2000/DTE/gmb_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57271,270,"GMB","Gambia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2012/Binary/gmb_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57272,270,"GMB","Gambia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2012/DTE/gmb_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57273,270,"GMB","Gambia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2014/Binary/gmb_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57274,270,"GMB","Gambia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2014/DTE/gmb_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57275,270,"GMB","Gambia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2000/PRP/gmb_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57276,270,"GMB","Gambia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2000/PRP/gmb_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57277,270,"GMB","Gambia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2000/PRP/gmb_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57278,270,"GMB","Gambia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2000/PRP/gmb_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57279,270,"GMB","Gambia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2012/PRP/gmb_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57280,270,"GMB","Gambia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2012/PRP/gmb_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57281,270,"GMB","Gambia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2012/PRP/gmb_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57282,270,"GMB","Gambia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2012/PRP/gmb_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57283,270,"GMB","Gambia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2014/PRP/gmb_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57284,270,"GMB","Gambia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2014/PRP/gmb_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57285,270,"GMB","Gambia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2014/PRP/gmb_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57286,270,"GMB","Gambia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GMB/BuiltSettlement/2014/PRP/gmb_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57287,275,"PSE","Palestina","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2000/Binary/pse_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57288,275,"PSE","Palestina","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2000/DTE/pse_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57289,275,"PSE","Palestina","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2012/Binary/pse_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57290,275,"PSE","Palestina","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2012/DTE/pse_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57291,275,"PSE","Palestina","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2014/Binary/pse_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57292,275,"PSE","Palestina","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2014/DTE/pse_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57293,275,"PSE","Palestina","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2000/PRP/pse_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57294,275,"PSE","Palestina","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2000/PRP/pse_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57295,275,"PSE","Palestina","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2000/PRP/pse_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57296,275,"PSE","Palestina","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2000/PRP/pse_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57297,275,"PSE","Palestina","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2012/PRP/pse_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57298,275,"PSE","Palestina","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2012/PRP/pse_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57299,275,"PSE","Palestina","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2012/PRP/pse_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57300,275,"PSE","Palestina","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2012/PRP/pse_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57301,275,"PSE","Palestina","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2014/PRP/pse_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57302,275,"PSE","Palestina","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2014/PRP/pse_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57303,275,"PSE","Palestina","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2014/PRP/pse_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57304,275,"PSE","Palestina","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PSE/BuiltSettlement/2014/PRP/pse_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57305,276,"DEU","Germany","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2000/Binary/deu_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57306,276,"DEU","Germany","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2000/DTE/deu_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57307,276,"DEU","Germany","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2012/Binary/deu_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57308,276,"DEU","Germany","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2012/DTE/deu_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57309,276,"DEU","Germany","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2014/Binary/deu_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57310,276,"DEU","Germany","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2014/DTE/deu_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57311,276,"DEU","Germany","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2000/PRP/deu_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57312,276,"DEU","Germany","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2000/PRP/deu_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57313,276,"DEU","Germany","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2000/PRP/deu_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57314,276,"DEU","Germany","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2000/PRP/deu_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57315,276,"DEU","Germany","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2012/PRP/deu_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57316,276,"DEU","Germany","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2012/PRP/deu_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57317,276,"DEU","Germany","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2012/PRP/deu_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57318,276,"DEU","Germany","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2012/PRP/deu_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57319,276,"DEU","Germany","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2014/PRP/deu_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57320,276,"DEU","Germany","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2014/PRP/deu_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57321,276,"DEU","Germany","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2014/PRP/deu_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57322,276,"DEU","Germany","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/DEU/BuiltSettlement/2014/PRP/deu_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57323,288,"GHA","Ghana","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2000/Binary/gha_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57324,288,"GHA","Ghana","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2000/DTE/gha_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57325,288,"GHA","Ghana","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2012/Binary/gha_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57326,288,"GHA","Ghana","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2012/DTE/gha_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57327,288,"GHA","Ghana","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2014/Binary/gha_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57328,288,"GHA","Ghana","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2014/DTE/gha_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57329,288,"GHA","Ghana","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2000/PRP/gha_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57330,288,"GHA","Ghana","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2000/PRP/gha_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57331,288,"GHA","Ghana","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2000/PRP/gha_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57332,288,"GHA","Ghana","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2000/PRP/gha_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57333,288,"GHA","Ghana","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2012/PRP/gha_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57334,288,"GHA","Ghana","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2012/PRP/gha_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57335,288,"GHA","Ghana","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2012/PRP/gha_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57336,288,"GHA","Ghana","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2012/PRP/gha_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57337,288,"GHA","Ghana","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2014/PRP/gha_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57338,288,"GHA","Ghana","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2014/PRP/gha_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57339,288,"GHA","Ghana","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2014/PRP/gha_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57340,288,"GHA","Ghana","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GHA/BuiltSettlement/2014/PRP/gha_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57341,292,"GIB","Gibraltar","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2000/Binary/gib_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57342,292,"GIB","Gibraltar","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2000/DTE/gib_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57343,292,"GIB","Gibraltar","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2012/Binary/gib_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57344,292,"GIB","Gibraltar","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2012/DTE/gib_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57345,292,"GIB","Gibraltar","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2014/Binary/gib_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57346,292,"GIB","Gibraltar","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2014/DTE/gib_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57347,292,"GIB","Gibraltar","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2000/PRP/gib_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57348,292,"GIB","Gibraltar","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2000/PRP/gib_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57349,292,"GIB","Gibraltar","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2000/PRP/gib_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57350,292,"GIB","Gibraltar","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2000/PRP/gib_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57351,292,"GIB","Gibraltar","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2012/PRP/gib_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57352,292,"GIB","Gibraltar","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2012/PRP/gib_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57353,292,"GIB","Gibraltar","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2012/PRP/gib_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57354,292,"GIB","Gibraltar","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2012/PRP/gib_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57355,292,"GIB","Gibraltar","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2014/PRP/gib_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57356,292,"GIB","Gibraltar","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2014/PRP/gib_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57357,292,"GIB","Gibraltar","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2014/PRP/gib_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57358,292,"GIB","Gibraltar","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GIB/BuiltSettlement/2014/PRP/gib_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57359,296,"KIR","Kiribati","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2000/Binary/kir_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57360,296,"KIR","Kiribati","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2000/DTE/kir_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57361,296,"KIR","Kiribati","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2012/Binary/kir_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57362,296,"KIR","Kiribati","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2012/DTE/kir_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57363,296,"KIR","Kiribati","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2014/Binary/kir_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57364,296,"KIR","Kiribati","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2014/DTE/kir_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57365,296,"KIR","Kiribati","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2000/PRP/kir_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57366,296,"KIR","Kiribati","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2000/PRP/kir_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57367,296,"KIR","Kiribati","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2000/PRP/kir_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57368,296,"KIR","Kiribati","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2000/PRP/kir_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57369,296,"KIR","Kiribati","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2012/PRP/kir_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57370,296,"KIR","Kiribati","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2012/PRP/kir_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57371,296,"KIR","Kiribati","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2012/PRP/kir_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57372,296,"KIR","Kiribati","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2012/PRP/kir_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57373,296,"KIR","Kiribati","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2014/PRP/kir_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57374,296,"KIR","Kiribati","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2014/PRP/kir_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57375,296,"KIR","Kiribati","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2014/PRP/kir_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57376,296,"KIR","Kiribati","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/KIR/BuiltSettlement/2014/PRP/kir_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57377,300,"GRC","Greece","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2000/Binary/grc_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57378,300,"GRC","Greece","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2000/DTE/grc_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57379,300,"GRC","Greece","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2012/Binary/grc_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57380,300,"GRC","Greece","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2012/DTE/grc_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57381,300,"GRC","Greece","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2014/Binary/grc_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57382,300,"GRC","Greece","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2014/DTE/grc_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57383,300,"GRC","Greece","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2000/PRP/grc_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57384,300,"GRC","Greece","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2000/PRP/grc_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57385,300,"GRC","Greece","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2000/PRP/grc_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57386,300,"GRC","Greece","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2000/PRP/grc_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57387,300,"GRC","Greece","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2012/PRP/grc_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57388,300,"GRC","Greece","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2012/PRP/grc_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57389,300,"GRC","Greece","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2012/PRP/grc_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57390,300,"GRC","Greece","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2012/PRP/grc_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57391,300,"GRC","Greece","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2014/PRP/grc_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57392,300,"GRC","Greece","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2014/PRP/grc_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57393,300,"GRC","Greece","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2014/PRP/grc_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57394,300,"GRC","Greece","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GRC/BuiltSettlement/2014/PRP/grc_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57395,308,"GRD","Grenada","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2000/Binary/grd_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57396,308,"GRD","Grenada","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2000/DTE/grd_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57397,308,"GRD","Grenada","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2012/Binary/grd_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57398,308,"GRD","Grenada","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2012/DTE/grd_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57399,308,"GRD","Grenada","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2014/Binary/grd_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57400,308,"GRD","Grenada","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2014/DTE/grd_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57401,308,"GRD","Grenada","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2000/PRP/grd_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57402,308,"GRD","Grenada","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2000/PRP/grd_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57403,308,"GRD","Grenada","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2000/PRP/grd_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57404,308,"GRD","Grenada","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2000/PRP/grd_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57405,308,"GRD","Grenada","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2012/PRP/grd_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57406,308,"GRD","Grenada","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2012/PRP/grd_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57407,308,"GRD","Grenada","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2012/PRP/grd_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57408,308,"GRD","Grenada","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2012/PRP/grd_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57409,308,"GRD","Grenada","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2014/PRP/grd_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57410,308,"GRD","Grenada","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2014/PRP/grd_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57411,308,"GRD","Grenada","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2014/PRP/grd_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57412,308,"GRD","Grenada","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GRD/BuiltSettlement/2014/PRP/grd_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57413,312,"GLP","Guadeloupe","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2000/Binary/glp_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57414,312,"GLP","Guadeloupe","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2000/DTE/glp_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57415,312,"GLP","Guadeloupe","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2012/Binary/glp_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57416,312,"GLP","Guadeloupe","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2012/DTE/glp_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57417,312,"GLP","Guadeloupe","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2014/Binary/glp_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57418,312,"GLP","Guadeloupe","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2014/DTE/glp_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57419,312,"GLP","Guadeloupe","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2000/PRP/glp_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57420,312,"GLP","Guadeloupe","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2000/PRP/glp_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57421,312,"GLP","Guadeloupe","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2000/PRP/glp_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57422,312,"GLP","Guadeloupe","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2000/PRP/glp_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57423,312,"GLP","Guadeloupe","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2012/PRP/glp_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57424,312,"GLP","Guadeloupe","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2012/PRP/glp_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57425,312,"GLP","Guadeloupe","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2012/PRP/glp_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57426,312,"GLP","Guadeloupe","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2012/PRP/glp_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57427,312,"GLP","Guadeloupe","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2014/PRP/glp_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57428,312,"GLP","Guadeloupe","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2014/PRP/glp_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57429,312,"GLP","Guadeloupe","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2014/PRP/glp_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57430,312,"GLP","Guadeloupe","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GLP/BuiltSettlement/2014/PRP/glp_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57431,316,"GUM","Guam","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2000/Binary/gum_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57432,316,"GUM","Guam","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2000/DTE/gum_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57433,316,"GUM","Guam","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2012/Binary/gum_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57434,316,"GUM","Guam","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2012/DTE/gum_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57435,316,"GUM","Guam","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2014/Binary/gum_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57436,316,"GUM","Guam","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2014/DTE/gum_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57437,316,"GUM","Guam","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2000/PRP/gum_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57438,316,"GUM","Guam","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2000/PRP/gum_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57439,316,"GUM","Guam","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2000/PRP/gum_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57440,316,"GUM","Guam","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2000/PRP/gum_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57441,316,"GUM","Guam","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2012/PRP/gum_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57442,316,"GUM","Guam","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2012/PRP/gum_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57443,316,"GUM","Guam","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2012/PRP/gum_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57444,316,"GUM","Guam","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2012/PRP/gum_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57445,316,"GUM","Guam","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2014/PRP/gum_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57446,316,"GUM","Guam","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2014/PRP/gum_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57447,316,"GUM","Guam","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2014/PRP/gum_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57448,316,"GUM","Guam","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GUM/BuiltSettlement/2014/PRP/gum_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57449,320,"GTM","Guatemala","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2000/Binary/gtm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57450,320,"GTM","Guatemala","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2000/DTE/gtm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57451,320,"GTM","Guatemala","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2012/Binary/gtm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57452,320,"GTM","Guatemala","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2012/DTE/gtm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57453,320,"GTM","Guatemala","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2014/Binary/gtm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57454,320,"GTM","Guatemala","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2014/DTE/gtm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57455,320,"GTM","Guatemala","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2000/PRP/gtm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57456,320,"GTM","Guatemala","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2000/PRP/gtm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57457,320,"GTM","Guatemala","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2000/PRP/gtm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57458,320,"GTM","Guatemala","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2000/PRP/gtm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57459,320,"GTM","Guatemala","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2012/PRP/gtm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57460,320,"GTM","Guatemala","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2012/PRP/gtm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57461,320,"GTM","Guatemala","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2012/PRP/gtm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57462,320,"GTM","Guatemala","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2012/PRP/gtm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57463,320,"GTM","Guatemala","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2014/PRP/gtm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57464,320,"GTM","Guatemala","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2014/PRP/gtm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57465,320,"GTM","Guatemala","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2014/PRP/gtm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57466,320,"GTM","Guatemala","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GTM/BuiltSettlement/2014/PRP/gtm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57467,324,"GIN","Guinea","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2000/Binary/gin_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57468,324,"GIN","Guinea","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2000/DTE/gin_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57469,324,"GIN","Guinea","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2012/Binary/gin_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57470,324,"GIN","Guinea","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2012/DTE/gin_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57471,324,"GIN","Guinea","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2014/Binary/gin_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57472,324,"GIN","Guinea","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2014/DTE/gin_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57473,324,"GIN","Guinea","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2000/PRP/gin_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57474,324,"GIN","Guinea","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2000/PRP/gin_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57475,324,"GIN","Guinea","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2000/PRP/gin_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57476,324,"GIN","Guinea","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2000/PRP/gin_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57477,324,"GIN","Guinea","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2012/PRP/gin_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57478,324,"GIN","Guinea","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2012/PRP/gin_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57479,324,"GIN","Guinea","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2012/PRP/gin_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57480,324,"GIN","Guinea","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2012/PRP/gin_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57481,324,"GIN","Guinea","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2014/PRP/gin_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57482,324,"GIN","Guinea","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2014/PRP/gin_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57483,324,"GIN","Guinea","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2014/PRP/gin_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57484,324,"GIN","Guinea","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GIN/BuiltSettlement/2014/PRP/gin_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57485,328,"GUY","Guyana","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2000/Binary/guy_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57486,328,"GUY","Guyana","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2000/DTE/guy_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57487,328,"GUY","Guyana","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2012/Binary/guy_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57488,328,"GUY","Guyana","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2012/DTE/guy_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57489,328,"GUY","Guyana","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2014/Binary/guy_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57490,328,"GUY","Guyana","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2014/DTE/guy_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57491,328,"GUY","Guyana","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2000/PRP/guy_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57492,328,"GUY","Guyana","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2000/PRP/guy_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57493,328,"GUY","Guyana","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2000/PRP/guy_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57494,328,"GUY","Guyana","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2000/PRP/guy_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57495,328,"GUY","Guyana","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2012/PRP/guy_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57496,328,"GUY","Guyana","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2012/PRP/guy_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57497,328,"GUY","Guyana","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2012/PRP/guy_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57498,328,"GUY","Guyana","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2012/PRP/guy_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57499,328,"GUY","Guyana","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2014/PRP/guy_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57500,328,"GUY","Guyana","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2014/PRP/guy_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57501,328,"GUY","Guyana","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2014/PRP/guy_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57502,328,"GUY","Guyana","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GUY/BuiltSettlement/2014/PRP/guy_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57503,332,"HTI","Haiti","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2000/Binary/hti_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57504,332,"HTI","Haiti","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2000/DTE/hti_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57505,332,"HTI","Haiti","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2012/Binary/hti_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57506,332,"HTI","Haiti","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2012/DTE/hti_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57507,332,"HTI","Haiti","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2014/Binary/hti_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57508,332,"HTI","Haiti","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2014/DTE/hti_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57509,332,"HTI","Haiti","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2000/PRP/hti_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57510,332,"HTI","Haiti","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2000/PRP/hti_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57511,332,"HTI","Haiti","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2000/PRP/hti_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57512,332,"HTI","Haiti","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2000/PRP/hti_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57513,332,"HTI","Haiti","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2012/PRP/hti_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57514,332,"HTI","Haiti","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2012/PRP/hti_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57515,332,"HTI","Haiti","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2012/PRP/hti_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57516,332,"HTI","Haiti","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2012/PRP/hti_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57517,332,"HTI","Haiti","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2014/PRP/hti_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57518,332,"HTI","Haiti","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2014/PRP/hti_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57519,332,"HTI","Haiti","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2014/PRP/hti_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57520,332,"HTI","Haiti","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/HTI/BuiltSettlement/2014/PRP/hti_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57521,334,"HMD","Heard Island and McDonald Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2000/Binary/hmd_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57522,334,"HMD","Heard Island and McDonald Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2000/DTE/hmd_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57523,334,"HMD","Heard Island and McDonald Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2012/Binary/hmd_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57524,334,"HMD","Heard Island and McDonald Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2012/DTE/hmd_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57525,334,"HMD","Heard Island and McDonald Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2014/Binary/hmd_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57526,334,"HMD","Heard Island and McDonald Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2014/DTE/hmd_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57527,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2000/PRP/hmd_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57528,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2000/PRP/hmd_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57529,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2000/PRP/hmd_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57530,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2000/PRP/hmd_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57531,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2012/PRP/hmd_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57532,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2012/PRP/hmd_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57533,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2012/PRP/hmd_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57534,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2012/PRP/hmd_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57535,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2014/PRP/hmd_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57536,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2014/PRP/hmd_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57537,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2014/PRP/hmd_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57538,334,"HMD","Heard Island and McDonald Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/HMD/BuiltSettlement/2014/PRP/hmd_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57539,336,"VAT","Vatican City","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2000/Binary/vat_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57540,336,"VAT","Vatican City","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2000/DTE/vat_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57541,336,"VAT","Vatican City","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2012/Binary/vat_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57542,336,"VAT","Vatican City","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2012/DTE/vat_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57543,336,"VAT","Vatican City","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2014/Binary/vat_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57544,336,"VAT","Vatican City","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2014/DTE/vat_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57545,336,"VAT","Vatican City","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2000/PRP/vat_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57546,336,"VAT","Vatican City","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2000/PRP/vat_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57547,336,"VAT","Vatican City","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2000/PRP/vat_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57548,336,"VAT","Vatican City","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2000/PRP/vat_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57549,336,"VAT","Vatican City","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2012/PRP/vat_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57550,336,"VAT","Vatican City","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2012/PRP/vat_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57551,336,"VAT","Vatican City","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2012/PRP/vat_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57552,336,"VAT","Vatican City","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2012/PRP/vat_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57553,336,"VAT","Vatican City","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2014/PRP/vat_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57554,336,"VAT","Vatican City","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2014/PRP/vat_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57555,336,"VAT","Vatican City","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2014/PRP/vat_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57556,336,"VAT","Vatican City","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/VAT/BuiltSettlement/2014/PRP/vat_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57557,340,"HND","Honduras","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2000/Binary/hnd_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57558,340,"HND","Honduras","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2000/DTE/hnd_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57559,340,"HND","Honduras","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2012/Binary/hnd_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57560,340,"HND","Honduras","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2012/DTE/hnd_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57561,340,"HND","Honduras","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2014/Binary/hnd_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57562,340,"HND","Honduras","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2014/DTE/hnd_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57563,340,"HND","Honduras","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2000/PRP/hnd_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57564,340,"HND","Honduras","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2000/PRP/hnd_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57565,340,"HND","Honduras","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2000/PRP/hnd_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57566,340,"HND","Honduras","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2000/PRP/hnd_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57567,340,"HND","Honduras","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2012/PRP/hnd_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57568,340,"HND","Honduras","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2012/PRP/hnd_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57569,340,"HND","Honduras","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2012/PRP/hnd_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57570,340,"HND","Honduras","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2012/PRP/hnd_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57571,340,"HND","Honduras","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2014/PRP/hnd_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57572,340,"HND","Honduras","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2014/PRP/hnd_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57573,340,"HND","Honduras","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2014/PRP/hnd_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57574,340,"HND","Honduras","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/HND/BuiltSettlement/2014/PRP/hnd_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57575,344,"HKG","Hong Kong","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2000/Binary/hkg_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57576,344,"HKG","Hong Kong","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2000/DTE/hkg_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57577,344,"HKG","Hong Kong","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2012/Binary/hkg_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57578,344,"HKG","Hong Kong","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2012/DTE/hkg_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57579,344,"HKG","Hong Kong","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2014/Binary/hkg_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57580,344,"HKG","Hong Kong","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2014/DTE/hkg_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57581,344,"HKG","Hong Kong","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2000/PRP/hkg_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57582,344,"HKG","Hong Kong","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2000/PRP/hkg_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57583,344,"HKG","Hong Kong","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2000/PRP/hkg_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57584,344,"HKG","Hong Kong","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2000/PRP/hkg_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57585,344,"HKG","Hong Kong","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2012/PRP/hkg_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57586,344,"HKG","Hong Kong","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2012/PRP/hkg_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57587,344,"HKG","Hong Kong","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2012/PRP/hkg_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57588,344,"HKG","Hong Kong","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2012/PRP/hkg_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57589,344,"HKG","Hong Kong","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2014/PRP/hkg_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57590,344,"HKG","Hong Kong","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2014/PRP/hkg_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57591,344,"HKG","Hong Kong","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2014/PRP/hkg_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57592,344,"HKG","Hong Kong","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/HKG/BuiltSettlement/2014/PRP/hkg_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57593,348,"HUN","Hungary","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2000/Binary/hun_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57594,348,"HUN","Hungary","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2000/DTE/hun_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57595,348,"HUN","Hungary","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2012/Binary/hun_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57596,348,"HUN","Hungary","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2012/DTE/hun_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57597,348,"HUN","Hungary","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2014/Binary/hun_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57598,348,"HUN","Hungary","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2014/DTE/hun_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57599,348,"HUN","Hungary","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2000/PRP/hun_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57600,348,"HUN","Hungary","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2000/PRP/hun_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57601,348,"HUN","Hungary","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2000/PRP/hun_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57602,348,"HUN","Hungary","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2000/PRP/hun_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57603,348,"HUN","Hungary","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2012/PRP/hun_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57604,348,"HUN","Hungary","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2012/PRP/hun_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57605,348,"HUN","Hungary","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2012/PRP/hun_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57606,348,"HUN","Hungary","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2012/PRP/hun_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57607,348,"HUN","Hungary","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2014/PRP/hun_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57608,348,"HUN","Hungary","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2014/PRP/hun_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57609,348,"HUN","Hungary","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2014/PRP/hun_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57610,348,"HUN","Hungary","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/HUN/BuiltSettlement/2014/PRP/hun_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57611,352,"ISL","Iceland","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2000/Binary/isl_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57612,352,"ISL","Iceland","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2000/DTE/isl_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57613,352,"ISL","Iceland","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2012/Binary/isl_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57614,352,"ISL","Iceland","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2012/DTE/isl_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57615,352,"ISL","Iceland","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2014/Binary/isl_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57616,352,"ISL","Iceland","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2014/DTE/isl_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57617,352,"ISL","Iceland","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2000/PRP/isl_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57618,352,"ISL","Iceland","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2000/PRP/isl_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57619,352,"ISL","Iceland","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2000/PRP/isl_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57620,352,"ISL","Iceland","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2000/PRP/isl_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57621,352,"ISL","Iceland","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2012/PRP/isl_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57622,352,"ISL","Iceland","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2012/PRP/isl_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57623,352,"ISL","Iceland","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2012/PRP/isl_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57624,352,"ISL","Iceland","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2012/PRP/isl_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57625,352,"ISL","Iceland","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2014/PRP/isl_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57626,352,"ISL","Iceland","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2014/PRP/isl_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57627,352,"ISL","Iceland","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2014/PRP/isl_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57628,352,"ISL","Iceland","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ISL/BuiltSettlement/2014/PRP/isl_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57629,356,"IND","India","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2000/Binary/ind_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57630,356,"IND","India","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2000/DTE/ind_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57631,356,"IND","India","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2012/Binary/ind_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57632,356,"IND","India","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2012/DTE/ind_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57633,356,"IND","India","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2014/Binary/ind_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57634,356,"IND","India","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2014/DTE/ind_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57635,356,"IND","India","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2000/PRP/ind_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57636,356,"IND","India","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2000/PRP/ind_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57637,356,"IND","India","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2000/PRP/ind_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57638,356,"IND","India","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2000/PRP/ind_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57639,356,"IND","India","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2012/PRP/ind_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57640,356,"IND","India","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2012/PRP/ind_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57641,356,"IND","India","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2012/PRP/ind_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57642,356,"IND","India","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2012/PRP/ind_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57643,356,"IND","India","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2014/PRP/ind_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57644,356,"IND","India","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2014/PRP/ind_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57645,356,"IND","India","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2014/PRP/ind_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57646,356,"IND","India","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/IND/BuiltSettlement/2014/PRP/ind_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57647,364,"IRN","Iran","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2000/Binary/irn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57648,364,"IRN","Iran","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2000/DTE/irn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57649,364,"IRN","Iran","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2012/Binary/irn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57650,364,"IRN","Iran","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2012/DTE/irn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57651,364,"IRN","Iran","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2014/Binary/irn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57652,364,"IRN","Iran","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2014/DTE/irn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57653,364,"IRN","Iran","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2000/PRP/irn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57654,364,"IRN","Iran","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2000/PRP/irn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57655,364,"IRN","Iran","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2000/PRP/irn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57656,364,"IRN","Iran","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2000/PRP/irn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57657,364,"IRN","Iran","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2012/PRP/irn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57658,364,"IRN","Iran","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2012/PRP/irn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57659,364,"IRN","Iran","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2012/PRP/irn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57660,364,"IRN","Iran","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2012/PRP/irn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57661,364,"IRN","Iran","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2014/PRP/irn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57662,364,"IRN","Iran","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2014/PRP/irn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57663,364,"IRN","Iran","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2014/PRP/irn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57664,364,"IRN","Iran","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/IRN/BuiltSettlement/2014/PRP/irn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57665,368,"IRQ","Iraq","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2000/Binary/irq_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57666,368,"IRQ","Iraq","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2000/DTE/irq_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57667,368,"IRQ","Iraq","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2012/Binary/irq_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57668,368,"IRQ","Iraq","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2012/DTE/irq_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57669,368,"IRQ","Iraq","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2014/Binary/irq_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57670,368,"IRQ","Iraq","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2014/DTE/irq_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57671,368,"IRQ","Iraq","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2000/PRP/irq_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57672,368,"IRQ","Iraq","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2000/PRP/irq_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57673,368,"IRQ","Iraq","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2000/PRP/irq_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57674,368,"IRQ","Iraq","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2000/PRP/irq_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57675,368,"IRQ","Iraq","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2012/PRP/irq_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57676,368,"IRQ","Iraq","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2012/PRP/irq_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57677,368,"IRQ","Iraq","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2012/PRP/irq_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57678,368,"IRQ","Iraq","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2012/PRP/irq_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57679,368,"IRQ","Iraq","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2014/PRP/irq_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57680,368,"IRQ","Iraq","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2014/PRP/irq_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57681,368,"IRQ","Iraq","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2014/PRP/irq_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57682,368,"IRQ","Iraq","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/BuiltSettlement/2014/PRP/irq_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57683,372,"IRL","Ireland","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2000/Binary/irl_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57684,372,"IRL","Ireland","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2000/DTE/irl_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57685,372,"IRL","Ireland","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2012/Binary/irl_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57686,372,"IRL","Ireland","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2012/DTE/irl_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57687,372,"IRL","Ireland","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2014/Binary/irl_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57688,372,"IRL","Ireland","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2014/DTE/irl_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57689,372,"IRL","Ireland","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2000/PRP/irl_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57690,372,"IRL","Ireland","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2000/PRP/irl_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57691,372,"IRL","Ireland","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2000/PRP/irl_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57692,372,"IRL","Ireland","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2000/PRP/irl_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57693,372,"IRL","Ireland","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2012/PRP/irl_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57694,372,"IRL","Ireland","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2012/PRP/irl_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57695,372,"IRL","Ireland","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2012/PRP/irl_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57696,372,"IRL","Ireland","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2012/PRP/irl_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57697,372,"IRL","Ireland","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2014/PRP/irl_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57698,372,"IRL","Ireland","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2014/PRP/irl_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57699,372,"IRL","Ireland","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2014/PRP/irl_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57700,372,"IRL","Ireland","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/IRL/BuiltSettlement/2014/PRP/irl_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57701,376,"ISR","Israel","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2000/Binary/isr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57702,376,"ISR","Israel","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2000/DTE/isr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57703,376,"ISR","Israel","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2012/Binary/isr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57704,376,"ISR","Israel","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2012/DTE/isr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57705,376,"ISR","Israel","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2014/Binary/isr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57706,376,"ISR","Israel","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2014/DTE/isr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57707,376,"ISR","Israel","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2000/PRP/isr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57708,376,"ISR","Israel","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2000/PRP/isr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57709,376,"ISR","Israel","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2000/PRP/isr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57710,376,"ISR","Israel","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2000/PRP/isr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57711,376,"ISR","Israel","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2012/PRP/isr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57712,376,"ISR","Israel","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2012/PRP/isr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57713,376,"ISR","Israel","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2012/PRP/isr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57714,376,"ISR","Israel","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2012/PRP/isr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57715,376,"ISR","Israel","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2014/PRP/isr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57716,376,"ISR","Israel","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2014/PRP/isr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57717,376,"ISR","Israel","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2014/PRP/isr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57718,376,"ISR","Israel","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ISR/BuiltSettlement/2014/PRP/isr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57719,380,"ITA","Italy","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2000/Binary/ita_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57720,380,"ITA","Italy","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2000/DTE/ita_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57721,380,"ITA","Italy","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2012/Binary/ita_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57722,380,"ITA","Italy","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2012/DTE/ita_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57723,380,"ITA","Italy","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2014/Binary/ita_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57724,380,"ITA","Italy","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2014/DTE/ita_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57725,380,"ITA","Italy","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2000/PRP/ita_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57726,380,"ITA","Italy","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2000/PRP/ita_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57727,380,"ITA","Italy","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2000/PRP/ita_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57728,380,"ITA","Italy","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2000/PRP/ita_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57729,380,"ITA","Italy","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2012/PRP/ita_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57730,380,"ITA","Italy","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2012/PRP/ita_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57731,380,"ITA","Italy","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2012/PRP/ita_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57732,380,"ITA","Italy","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2012/PRP/ita_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57733,380,"ITA","Italy","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2014/PRP/ita_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57734,380,"ITA","Italy","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2014/PRP/ita_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57735,380,"ITA","Italy","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2014/PRP/ita_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57736,380,"ITA","Italy","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ITA/BuiltSettlement/2014/PRP/ita_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57737,384,"CIV","CIte dIvoire","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2000/Binary/civ_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57738,384,"CIV","CIte dIvoire","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2000/DTE/civ_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57739,384,"CIV","CIte dIvoire","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2012/Binary/civ_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57740,384,"CIV","CIte dIvoire","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2012/DTE/civ_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57741,384,"CIV","CIte dIvoire","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2014/Binary/civ_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57742,384,"CIV","CIte dIvoire","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2014/DTE/civ_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57743,384,"CIV","CIte dIvoire","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2000/PRP/civ_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57744,384,"CIV","CIte dIvoire","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2000/PRP/civ_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57745,384,"CIV","CIte dIvoire","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2000/PRP/civ_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57746,384,"CIV","CIte dIvoire","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2000/PRP/civ_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57747,384,"CIV","CIte dIvoire","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2012/PRP/civ_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57748,384,"CIV","CIte dIvoire","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2012/PRP/civ_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57749,384,"CIV","CIte dIvoire","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2012/PRP/civ_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57750,384,"CIV","CIte dIvoire","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2012/PRP/civ_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57751,384,"CIV","CIte dIvoire","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2014/PRP/civ_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57752,384,"CIV","CIte dIvoire","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2014/PRP/civ_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57753,384,"CIV","CIte dIvoire","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2014/PRP/civ_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57754,384,"CIV","CIte dIvoire","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CIV/BuiltSettlement/2014/PRP/civ_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57755,388,"JAM","Jamaica","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2000/Binary/jam_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57756,388,"JAM","Jamaica","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2000/DTE/jam_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57757,388,"JAM","Jamaica","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2012/Binary/jam_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57758,388,"JAM","Jamaica","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2012/DTE/jam_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57759,388,"JAM","Jamaica","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2014/Binary/jam_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57760,388,"JAM","Jamaica","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2014/DTE/jam_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57761,388,"JAM","Jamaica","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2000/PRP/jam_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57762,388,"JAM","Jamaica","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2000/PRP/jam_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57763,388,"JAM","Jamaica","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2000/PRP/jam_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57764,388,"JAM","Jamaica","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2000/PRP/jam_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57765,388,"JAM","Jamaica","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2012/PRP/jam_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57766,388,"JAM","Jamaica","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2012/PRP/jam_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57767,388,"JAM","Jamaica","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2012/PRP/jam_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57768,388,"JAM","Jamaica","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2012/PRP/jam_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57769,388,"JAM","Jamaica","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2014/PRP/jam_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57770,388,"JAM","Jamaica","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2014/PRP/jam_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57771,388,"JAM","Jamaica","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2014/PRP/jam_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57772,388,"JAM","Jamaica","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/JAM/BuiltSettlement/2014/PRP/jam_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57773,392,"JPN","Japan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2000/Binary/jpn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57774,392,"JPN","Japan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2000/DTE/jpn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57775,392,"JPN","Japan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2012/Binary/jpn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57776,392,"JPN","Japan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2012/DTE/jpn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57777,392,"JPN","Japan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2014/Binary/jpn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57778,392,"JPN","Japan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2014/DTE/jpn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57779,392,"JPN","Japan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2000/PRP/jpn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57780,392,"JPN","Japan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2000/PRP/jpn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57781,392,"JPN","Japan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2000/PRP/jpn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57782,392,"JPN","Japan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2000/PRP/jpn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57783,392,"JPN","Japan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2012/PRP/jpn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57784,392,"JPN","Japan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2012/PRP/jpn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57785,392,"JPN","Japan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2012/PRP/jpn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57786,392,"JPN","Japan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2012/PRP/jpn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57787,392,"JPN","Japan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2014/PRP/jpn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57788,392,"JPN","Japan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2014/PRP/jpn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57789,392,"JPN","Japan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2014/PRP/jpn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57790,392,"JPN","Japan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/JPN/BuiltSettlement/2014/PRP/jpn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57791,398,"KAZ","Kazakhstan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2000/Binary/kaz_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57792,398,"KAZ","Kazakhstan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2000/DTE/kaz_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57793,398,"KAZ","Kazakhstan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2012/Binary/kaz_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57794,398,"KAZ","Kazakhstan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2012/DTE/kaz_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57795,398,"KAZ","Kazakhstan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2014/Binary/kaz_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57796,398,"KAZ","Kazakhstan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2014/DTE/kaz_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57797,398,"KAZ","Kazakhstan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2000/PRP/kaz_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57798,398,"KAZ","Kazakhstan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2000/PRP/kaz_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57799,398,"KAZ","Kazakhstan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2000/PRP/kaz_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57800,398,"KAZ","Kazakhstan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2000/PRP/kaz_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57801,398,"KAZ","Kazakhstan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2012/PRP/kaz_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57802,398,"KAZ","Kazakhstan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2012/PRP/kaz_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57803,398,"KAZ","Kazakhstan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2012/PRP/kaz_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57804,398,"KAZ","Kazakhstan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2012/PRP/kaz_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57805,398,"KAZ","Kazakhstan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2014/PRP/kaz_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57806,398,"KAZ","Kazakhstan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2014/PRP/kaz_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57807,398,"KAZ","Kazakhstan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2014/PRP/kaz_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57808,398,"KAZ","Kazakhstan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/BuiltSettlement/2014/PRP/kaz_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57809,400,"JOR","Jordan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2000/Binary/jor_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57810,400,"JOR","Jordan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2000/DTE/jor_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57811,400,"JOR","Jordan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2012/Binary/jor_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57812,400,"JOR","Jordan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2012/DTE/jor_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57813,400,"JOR","Jordan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2014/Binary/jor_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57814,400,"JOR","Jordan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2014/DTE/jor_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57815,400,"JOR","Jordan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2000/PRP/jor_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57816,400,"JOR","Jordan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2000/PRP/jor_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57817,400,"JOR","Jordan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2000/PRP/jor_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57818,400,"JOR","Jordan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2000/PRP/jor_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57819,400,"JOR","Jordan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2012/PRP/jor_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57820,400,"JOR","Jordan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2012/PRP/jor_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57821,400,"JOR","Jordan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2012/PRP/jor_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57822,400,"JOR","Jordan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2012/PRP/jor_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57823,400,"JOR","Jordan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2014/PRP/jor_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57824,400,"JOR","Jordan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2014/PRP/jor_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57825,400,"JOR","Jordan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2014/PRP/jor_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57826,400,"JOR","Jordan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/JOR/BuiltSettlement/2014/PRP/jor_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57827,404,"KEN","Kenya","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2000/Binary/ken_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57828,404,"KEN","Kenya","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2000/DTE/ken_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57829,404,"KEN","Kenya","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2012/Binary/ken_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57830,404,"KEN","Kenya","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2012/DTE/ken_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57831,404,"KEN","Kenya","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2014/Binary/ken_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57832,404,"KEN","Kenya","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2014/DTE/ken_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57833,404,"KEN","Kenya","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2000/PRP/ken_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57834,404,"KEN","Kenya","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2000/PRP/ken_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57835,404,"KEN","Kenya","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2000/PRP/ken_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57836,404,"KEN","Kenya","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2000/PRP/ken_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57837,404,"KEN","Kenya","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2012/PRP/ken_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57838,404,"KEN","Kenya","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2012/PRP/ken_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57839,404,"KEN","Kenya","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2012/PRP/ken_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57840,404,"KEN","Kenya","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2012/PRP/ken_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57841,404,"KEN","Kenya","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2014/PRP/ken_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57842,404,"KEN","Kenya","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2014/PRP/ken_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57843,404,"KEN","Kenya","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2014/PRP/ken_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57844,404,"KEN","Kenya","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/KEN/BuiltSettlement/2014/PRP/ken_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57845,408,"PRK","North Korea","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2000/Binary/prk_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57846,408,"PRK","North Korea","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2000/DTE/prk_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57847,408,"PRK","North Korea","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2012/Binary/prk_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57848,408,"PRK","North Korea","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2012/DTE/prk_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57849,408,"PRK","North Korea","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2014/Binary/prk_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57850,408,"PRK","North Korea","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2014/DTE/prk_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57851,408,"PRK","North Korea","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2000/PRP/prk_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57852,408,"PRK","North Korea","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2000/PRP/prk_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57853,408,"PRK","North Korea","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2000/PRP/prk_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57854,408,"PRK","North Korea","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2000/PRP/prk_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57855,408,"PRK","North Korea","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2012/PRP/prk_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57856,408,"PRK","North Korea","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2012/PRP/prk_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57857,408,"PRK","North Korea","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2012/PRP/prk_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57858,408,"PRK","North Korea","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2012/PRP/prk_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57859,408,"PRK","North Korea","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2014/PRP/prk_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57860,408,"PRK","North Korea","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2014/PRP/prk_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57861,408,"PRK","North Korea","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2014/PRP/prk_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57862,408,"PRK","North Korea","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PRK/BuiltSettlement/2014/PRP/prk_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57863,410,"KOR","South Korea","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2000/Binary/kor_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57864,410,"KOR","South Korea","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2000/DTE/kor_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57865,410,"KOR","South Korea","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2012/Binary/kor_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57866,410,"KOR","South Korea","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2012/DTE/kor_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57867,410,"KOR","South Korea","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2014/Binary/kor_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57868,410,"KOR","South Korea","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2014/DTE/kor_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57869,410,"KOR","South Korea","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2000/PRP/kor_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57870,410,"KOR","South Korea","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2000/PRP/kor_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57871,410,"KOR","South Korea","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2000/PRP/kor_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57872,410,"KOR","South Korea","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2000/PRP/kor_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57873,410,"KOR","South Korea","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2012/PRP/kor_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57874,410,"KOR","South Korea","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2012/PRP/kor_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57875,410,"KOR","South Korea","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2012/PRP/kor_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57876,410,"KOR","South Korea","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2012/PRP/kor_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57877,410,"KOR","South Korea","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2014/PRP/kor_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57878,410,"KOR","South Korea","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2014/PRP/kor_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57879,410,"KOR","South Korea","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2014/PRP/kor_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57880,410,"KOR","South Korea","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/KOR/BuiltSettlement/2014/PRP/kor_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57881,414,"KWT","Kuwait","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2000/Binary/kwt_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57882,414,"KWT","Kuwait","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2000/DTE/kwt_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57883,414,"KWT","Kuwait","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2012/Binary/kwt_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57884,414,"KWT","Kuwait","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2012/DTE/kwt_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57885,414,"KWT","Kuwait","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2014/Binary/kwt_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57886,414,"KWT","Kuwait","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2014/DTE/kwt_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57887,414,"KWT","Kuwait","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2000/PRP/kwt_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57888,414,"KWT","Kuwait","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2000/PRP/kwt_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57889,414,"KWT","Kuwait","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2000/PRP/kwt_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57890,414,"KWT","Kuwait","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2000/PRP/kwt_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57891,414,"KWT","Kuwait","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2012/PRP/kwt_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57892,414,"KWT","Kuwait","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2012/PRP/kwt_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57893,414,"KWT","Kuwait","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2012/PRP/kwt_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57894,414,"KWT","Kuwait","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2012/PRP/kwt_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57895,414,"KWT","Kuwait","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2014/PRP/kwt_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57896,414,"KWT","Kuwait","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2014/PRP/kwt_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57897,414,"KWT","Kuwait","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2014/PRP/kwt_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57898,414,"KWT","Kuwait","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/KWT/BuiltSettlement/2014/PRP/kwt_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57899,417,"KGZ","Kyrgyzstan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2000/Binary/kgz_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57900,417,"KGZ","Kyrgyzstan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2000/DTE/kgz_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57901,417,"KGZ","Kyrgyzstan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2012/Binary/kgz_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57902,417,"KGZ","Kyrgyzstan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2012/DTE/kgz_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57903,417,"KGZ","Kyrgyzstan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2014/Binary/kgz_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57904,417,"KGZ","Kyrgyzstan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2014/DTE/kgz_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57905,417,"KGZ","Kyrgyzstan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2000/PRP/kgz_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57906,417,"KGZ","Kyrgyzstan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2000/PRP/kgz_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57907,417,"KGZ","Kyrgyzstan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2000/PRP/kgz_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57908,417,"KGZ","Kyrgyzstan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2000/PRP/kgz_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57909,417,"KGZ","Kyrgyzstan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2012/PRP/kgz_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57910,417,"KGZ","Kyrgyzstan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2012/PRP/kgz_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57911,417,"KGZ","Kyrgyzstan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2012/PRP/kgz_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57912,417,"KGZ","Kyrgyzstan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2012/PRP/kgz_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57913,417,"KGZ","Kyrgyzstan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2014/PRP/kgz_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57914,417,"KGZ","Kyrgyzstan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2014/PRP/kgz_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57915,417,"KGZ","Kyrgyzstan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2014/PRP/kgz_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57916,417,"KGZ","Kyrgyzstan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/BuiltSettlement/2014/PRP/kgz_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57917,418,"LAO","Laos","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2000/Binary/lao_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57918,418,"LAO","Laos","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2000/DTE/lao_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57919,418,"LAO","Laos","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2012/Binary/lao_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57920,418,"LAO","Laos","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2012/DTE/lao_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57921,418,"LAO","Laos","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2014/Binary/lao_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57922,418,"LAO","Laos","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2014/DTE/lao_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57923,418,"LAO","Laos","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2000/PRP/lao_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57924,418,"LAO","Laos","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2000/PRP/lao_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57925,418,"LAO","Laos","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2000/PRP/lao_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57926,418,"LAO","Laos","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2000/PRP/lao_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57927,418,"LAO","Laos","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2012/PRP/lao_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57928,418,"LAO","Laos","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2012/PRP/lao_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57929,418,"LAO","Laos","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2012/PRP/lao_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57930,418,"LAO","Laos","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2012/PRP/lao_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57931,418,"LAO","Laos","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2014/PRP/lao_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57932,418,"LAO","Laos","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2014/PRP/lao_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57933,418,"LAO","Laos","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2014/PRP/lao_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57934,418,"LAO","Laos","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LAO/BuiltSettlement/2014/PRP/lao_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57935,422,"LBN","Lebanon","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2000/Binary/lbn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57936,422,"LBN","Lebanon","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2000/DTE/lbn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57937,422,"LBN","Lebanon","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2012/Binary/lbn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57938,422,"LBN","Lebanon","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2012/DTE/lbn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57939,422,"LBN","Lebanon","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2014/Binary/lbn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57940,422,"LBN","Lebanon","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2014/DTE/lbn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57941,422,"LBN","Lebanon","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2000/PRP/lbn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57942,422,"LBN","Lebanon","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2000/PRP/lbn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57943,422,"LBN","Lebanon","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2000/PRP/lbn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57944,422,"LBN","Lebanon","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2000/PRP/lbn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57945,422,"LBN","Lebanon","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2012/PRP/lbn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57946,422,"LBN","Lebanon","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2012/PRP/lbn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57947,422,"LBN","Lebanon","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2012/PRP/lbn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57948,422,"LBN","Lebanon","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2012/PRP/lbn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57949,422,"LBN","Lebanon","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2014/PRP/lbn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57950,422,"LBN","Lebanon","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2014/PRP/lbn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57951,422,"LBN","Lebanon","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2014/PRP/lbn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57952,422,"LBN","Lebanon","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LBN/BuiltSettlement/2014/PRP/lbn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57953,426,"LSO","Lesotho","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2000/Binary/lso_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57954,426,"LSO","Lesotho","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2000/DTE/lso_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57955,426,"LSO","Lesotho","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2012/Binary/lso_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57956,426,"LSO","Lesotho","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2012/DTE/lso_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57957,426,"LSO","Lesotho","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2014/Binary/lso_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57958,426,"LSO","Lesotho","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2014/DTE/lso_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57959,426,"LSO","Lesotho","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2000/PRP/lso_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57960,426,"LSO","Lesotho","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2000/PRP/lso_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57961,426,"LSO","Lesotho","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2000/PRP/lso_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57962,426,"LSO","Lesotho","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2000/PRP/lso_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57963,426,"LSO","Lesotho","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2012/PRP/lso_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57964,426,"LSO","Lesotho","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2012/PRP/lso_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57965,426,"LSO","Lesotho","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2012/PRP/lso_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57966,426,"LSO","Lesotho","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2012/PRP/lso_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57967,426,"LSO","Lesotho","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2014/PRP/lso_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57968,426,"LSO","Lesotho","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2014/PRP/lso_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57969,426,"LSO","Lesotho","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2014/PRP/lso_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57970,426,"LSO","Lesotho","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LSO/BuiltSettlement/2014/PRP/lso_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57971,428,"LVA","Latvia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2000/Binary/lva_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57972,428,"LVA","Latvia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2000/DTE/lva_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57973,428,"LVA","Latvia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2012/Binary/lva_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57974,428,"LVA","Latvia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2012/DTE/lva_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57975,428,"LVA","Latvia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2014/Binary/lva_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57976,428,"LVA","Latvia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2014/DTE/lva_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57977,428,"LVA","Latvia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2000/PRP/lva_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57978,428,"LVA","Latvia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2000/PRP/lva_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57979,428,"LVA","Latvia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2000/PRP/lva_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57980,428,"LVA","Latvia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2000/PRP/lva_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57981,428,"LVA","Latvia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2012/PRP/lva_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
57982,428,"LVA","Latvia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2012/PRP/lva_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
57983,428,"LVA","Latvia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2012/PRP/lva_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
57984,428,"LVA","Latvia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2012/PRP/lva_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
57985,428,"LVA","Latvia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2014/PRP/lva_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
57986,428,"LVA","Latvia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2014/PRP/lva_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
57987,428,"LVA","Latvia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2014/PRP/lva_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
57988,428,"LVA","Latvia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LVA/BuiltSettlement/2014/PRP/lva_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
57989,430,"LBR","Liberia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2000/Binary/lbr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
57990,430,"LBR","Liberia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2000/DTE/lbr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
57991,430,"LBR","Liberia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2012/Binary/lbr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
57992,430,"LBR","Liberia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2012/DTE/lbr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
57993,430,"LBR","Liberia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2014/Binary/lbr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
57994,430,"LBR","Liberia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2014/DTE/lbr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
57995,430,"LBR","Liberia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2000/PRP/lbr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
57996,430,"LBR","Liberia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2000/PRP/lbr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
57997,430,"LBR","Liberia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2000/PRP/lbr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
57998,430,"LBR","Liberia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2000/PRP/lbr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
57999,430,"LBR","Liberia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2012/PRP/lbr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58000,430,"LBR","Liberia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2012/PRP/lbr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58001,430,"LBR","Liberia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2012/PRP/lbr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58002,430,"LBR","Liberia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2012/PRP/lbr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58003,430,"LBR","Liberia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2014/PRP/lbr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58004,430,"LBR","Liberia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2014/PRP/lbr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58005,430,"LBR","Liberia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2014/PRP/lbr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58006,430,"LBR","Liberia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LBR/BuiltSettlement/2014/PRP/lbr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58007,434,"LBY","Libya","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2000/Binary/lby_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58008,434,"LBY","Libya","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2000/DTE/lby_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58009,434,"LBY","Libya","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2012/Binary/lby_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58010,434,"LBY","Libya","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2012/DTE/lby_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58011,434,"LBY","Libya","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2014/Binary/lby_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58012,434,"LBY","Libya","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2014/DTE/lby_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58013,434,"LBY","Libya","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2000/PRP/lby_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58014,434,"LBY","Libya","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2000/PRP/lby_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58015,434,"LBY","Libya","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2000/PRP/lby_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58016,434,"LBY","Libya","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2000/PRP/lby_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58017,434,"LBY","Libya","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2012/PRP/lby_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58018,434,"LBY","Libya","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2012/PRP/lby_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58019,434,"LBY","Libya","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2012/PRP/lby_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58020,434,"LBY","Libya","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2012/PRP/lby_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58021,434,"LBY","Libya","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2014/PRP/lby_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58022,434,"LBY","Libya","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2014/PRP/lby_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58023,434,"LBY","Libya","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2014/PRP/lby_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58024,434,"LBY","Libya","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LBY/BuiltSettlement/2014/PRP/lby_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58025,438,"LIE","Liechtenstein","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2000/Binary/lie_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58026,438,"LIE","Liechtenstein","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2000/DTE/lie_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58027,438,"LIE","Liechtenstein","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2012/Binary/lie_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58028,438,"LIE","Liechtenstein","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2012/DTE/lie_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58029,438,"LIE","Liechtenstein","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2014/Binary/lie_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58030,438,"LIE","Liechtenstein","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2014/DTE/lie_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58031,438,"LIE","Liechtenstein","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2000/PRP/lie_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58032,438,"LIE","Liechtenstein","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2000/PRP/lie_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58033,438,"LIE","Liechtenstein","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2000/PRP/lie_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58034,438,"LIE","Liechtenstein","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2000/PRP/lie_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58035,438,"LIE","Liechtenstein","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2012/PRP/lie_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58036,438,"LIE","Liechtenstein","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2012/PRP/lie_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58037,438,"LIE","Liechtenstein","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2012/PRP/lie_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58038,438,"LIE","Liechtenstein","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2012/PRP/lie_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58039,438,"LIE","Liechtenstein","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2014/PRP/lie_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58040,438,"LIE","Liechtenstein","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2014/PRP/lie_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58041,438,"LIE","Liechtenstein","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2014/PRP/lie_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58042,438,"LIE","Liechtenstein","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LIE/BuiltSettlement/2014/PRP/lie_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58043,440,"LTU","Lithuania","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2000/Binary/ltu_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58044,440,"LTU","Lithuania","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2000/DTE/ltu_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58045,440,"LTU","Lithuania","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2012/Binary/ltu_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58046,440,"LTU","Lithuania","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2012/DTE/ltu_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58047,440,"LTU","Lithuania","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2014/Binary/ltu_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58048,440,"LTU","Lithuania","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2014/DTE/ltu_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58049,440,"LTU","Lithuania","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2000/PRP/ltu_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58050,440,"LTU","Lithuania","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2000/PRP/ltu_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58051,440,"LTU","Lithuania","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2000/PRP/ltu_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58052,440,"LTU","Lithuania","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2000/PRP/ltu_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58053,440,"LTU","Lithuania","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2012/PRP/ltu_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58054,440,"LTU","Lithuania","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2012/PRP/ltu_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58055,440,"LTU","Lithuania","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2012/PRP/ltu_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58056,440,"LTU","Lithuania","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2012/PRP/ltu_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58057,440,"LTU","Lithuania","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2014/PRP/ltu_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58058,440,"LTU","Lithuania","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2014/PRP/ltu_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58059,440,"LTU","Lithuania","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2014/PRP/ltu_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58060,440,"LTU","Lithuania","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LTU/BuiltSettlement/2014/PRP/ltu_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58061,442,"LUX","Luxembourg","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2000/Binary/lux_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58062,442,"LUX","Luxembourg","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2000/DTE/lux_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58063,442,"LUX","Luxembourg","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2012/Binary/lux_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58064,442,"LUX","Luxembourg","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2012/DTE/lux_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58065,442,"LUX","Luxembourg","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2014/Binary/lux_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58066,442,"LUX","Luxembourg","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2014/DTE/lux_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58067,442,"LUX","Luxembourg","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2000/PRP/lux_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58068,442,"LUX","Luxembourg","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2000/PRP/lux_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58069,442,"LUX","Luxembourg","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2000/PRP/lux_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58070,442,"LUX","Luxembourg","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2000/PRP/lux_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58071,442,"LUX","Luxembourg","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2012/PRP/lux_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58072,442,"LUX","Luxembourg","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2012/PRP/lux_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58073,442,"LUX","Luxembourg","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2012/PRP/lux_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58074,442,"LUX","Luxembourg","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2012/PRP/lux_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58075,442,"LUX","Luxembourg","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2014/PRP/lux_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58076,442,"LUX","Luxembourg","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2014/PRP/lux_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58077,442,"LUX","Luxembourg","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2014/PRP/lux_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58078,442,"LUX","Luxembourg","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LUX/BuiltSettlement/2014/PRP/lux_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58079,446,"MAC","Macao","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2000/Binary/mac_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58080,446,"MAC","Macao","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2000/DTE/mac_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58081,446,"MAC","Macao","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2012/Binary/mac_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58082,446,"MAC","Macao","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2012/DTE/mac_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58083,446,"MAC","Macao","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2014/Binary/mac_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58084,446,"MAC","Macao","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2014/DTE/mac_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58085,446,"MAC","Macao","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2000/PRP/mac_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58086,446,"MAC","Macao","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2000/PRP/mac_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58087,446,"MAC","Macao","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2000/PRP/mac_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58088,446,"MAC","Macao","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2000/PRP/mac_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58089,446,"MAC","Macao","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2012/PRP/mac_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58090,446,"MAC","Macao","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2012/PRP/mac_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58091,446,"MAC","Macao","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2012/PRP/mac_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58092,446,"MAC","Macao","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2012/PRP/mac_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58093,446,"MAC","Macao","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2014/PRP/mac_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58094,446,"MAC","Macao","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2014/PRP/mac_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58095,446,"MAC","Macao","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2014/PRP/mac_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58096,446,"MAC","Macao","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MAC/BuiltSettlement/2014/PRP/mac_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58097,450,"MDG","Madagascar","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2000/Binary/mdg_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58098,450,"MDG","Madagascar","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2000/DTE/mdg_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58099,450,"MDG","Madagascar","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2012/Binary/mdg_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58100,450,"MDG","Madagascar","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2012/DTE/mdg_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58101,450,"MDG","Madagascar","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2014/Binary/mdg_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58102,450,"MDG","Madagascar","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2014/DTE/mdg_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58103,450,"MDG","Madagascar","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2000/PRP/mdg_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58104,450,"MDG","Madagascar","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2000/PRP/mdg_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58105,450,"MDG","Madagascar","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2000/PRP/mdg_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58106,450,"MDG","Madagascar","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2000/PRP/mdg_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58107,450,"MDG","Madagascar","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2012/PRP/mdg_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58108,450,"MDG","Madagascar","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2012/PRP/mdg_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58109,450,"MDG","Madagascar","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2012/PRP/mdg_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58110,450,"MDG","Madagascar","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2012/PRP/mdg_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58111,450,"MDG","Madagascar","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2014/PRP/mdg_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58112,450,"MDG","Madagascar","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2014/PRP/mdg_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58113,450,"MDG","Madagascar","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2014/PRP/mdg_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58114,450,"MDG","Madagascar","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MDG/BuiltSettlement/2014/PRP/mdg_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58115,454,"MWI","Malawi","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2000/Binary/mwi_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58116,454,"MWI","Malawi","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2000/DTE/mwi_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58117,454,"MWI","Malawi","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2012/Binary/mwi_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58118,454,"MWI","Malawi","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2012/DTE/mwi_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58119,454,"MWI","Malawi","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2014/Binary/mwi_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58120,454,"MWI","Malawi","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2014/DTE/mwi_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58121,454,"MWI","Malawi","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2000/PRP/mwi_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58122,454,"MWI","Malawi","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2000/PRP/mwi_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58123,454,"MWI","Malawi","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2000/PRP/mwi_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58124,454,"MWI","Malawi","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2000/PRP/mwi_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58125,454,"MWI","Malawi","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2012/PRP/mwi_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58126,454,"MWI","Malawi","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2012/PRP/mwi_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58127,454,"MWI","Malawi","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2012/PRP/mwi_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58128,454,"MWI","Malawi","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2012/PRP/mwi_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58129,454,"MWI","Malawi","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2014/PRP/mwi_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58130,454,"MWI","Malawi","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2014/PRP/mwi_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58131,454,"MWI","Malawi","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2014/PRP/mwi_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58132,454,"MWI","Malawi","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MWI/BuiltSettlement/2014/PRP/mwi_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58133,458,"MYS","Malaysia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2000/Binary/mys_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58134,458,"MYS","Malaysia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2000/DTE/mys_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58135,458,"MYS","Malaysia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2012/Binary/mys_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58136,458,"MYS","Malaysia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2012/DTE/mys_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58137,458,"MYS","Malaysia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2014/Binary/mys_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58138,458,"MYS","Malaysia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2014/DTE/mys_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58139,458,"MYS","Malaysia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2000/PRP/mys_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58140,458,"MYS","Malaysia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2000/PRP/mys_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58141,458,"MYS","Malaysia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2000/PRP/mys_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58142,458,"MYS","Malaysia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2000/PRP/mys_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58143,458,"MYS","Malaysia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2012/PRP/mys_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58144,458,"MYS","Malaysia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2012/PRP/mys_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58145,458,"MYS","Malaysia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2012/PRP/mys_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58146,458,"MYS","Malaysia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2012/PRP/mys_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58147,458,"MYS","Malaysia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2014/PRP/mys_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58148,458,"MYS","Malaysia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2014/PRP/mys_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58149,458,"MYS","Malaysia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2014/PRP/mys_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58150,458,"MYS","Malaysia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MYS/BuiltSettlement/2014/PRP/mys_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58151,462,"MDV","Maldives","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2000/Binary/mdv_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58152,462,"MDV","Maldives","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2000/DTE/mdv_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58153,462,"MDV","Maldives","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2012/Binary/mdv_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58154,462,"MDV","Maldives","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2012/DTE/mdv_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58155,462,"MDV","Maldives","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2014/Binary/mdv_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58156,462,"MDV","Maldives","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2014/DTE/mdv_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58157,462,"MDV","Maldives","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2000/PRP/mdv_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58158,462,"MDV","Maldives","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2000/PRP/mdv_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58159,462,"MDV","Maldives","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2000/PRP/mdv_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58160,462,"MDV","Maldives","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2000/PRP/mdv_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58161,462,"MDV","Maldives","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2012/PRP/mdv_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58162,462,"MDV","Maldives","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2012/PRP/mdv_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58163,462,"MDV","Maldives","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2012/PRP/mdv_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58164,462,"MDV","Maldives","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2012/PRP/mdv_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58165,462,"MDV","Maldives","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2014/PRP/mdv_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58166,462,"MDV","Maldives","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2014/PRP/mdv_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58167,462,"MDV","Maldives","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2014/PRP/mdv_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58168,462,"MDV","Maldives","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MDV/BuiltSettlement/2014/PRP/mdv_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58169,466,"MLI","Mali","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2000/Binary/mli_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58170,466,"MLI","Mali","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2000/DTE/mli_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58171,466,"MLI","Mali","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2012/Binary/mli_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58172,466,"MLI","Mali","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2012/DTE/mli_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58173,466,"MLI","Mali","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2014/Binary/mli_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58174,466,"MLI","Mali","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2014/DTE/mli_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58175,466,"MLI","Mali","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2000/PRP/mli_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58176,466,"MLI","Mali","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2000/PRP/mli_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58177,466,"MLI","Mali","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2000/PRP/mli_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58178,466,"MLI","Mali","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2000/PRP/mli_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58179,466,"MLI","Mali","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2012/PRP/mli_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58180,466,"MLI","Mali","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2012/PRP/mli_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58181,466,"MLI","Mali","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2012/PRP/mli_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58182,466,"MLI","Mali","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2012/PRP/mli_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58183,466,"MLI","Mali","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2014/PRP/mli_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58184,466,"MLI","Mali","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2014/PRP/mli_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58185,466,"MLI","Mali","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2014/PRP/mli_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58186,466,"MLI","Mali","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MLI/BuiltSettlement/2014/PRP/mli_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58187,470,"MLT","Malta","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2000/Binary/mlt_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58188,470,"MLT","Malta","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2000/DTE/mlt_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58189,470,"MLT","Malta","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2012/Binary/mlt_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58190,470,"MLT","Malta","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2012/DTE/mlt_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58191,470,"MLT","Malta","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2014/Binary/mlt_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58192,470,"MLT","Malta","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2014/DTE/mlt_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58193,470,"MLT","Malta","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2000/PRP/mlt_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58194,470,"MLT","Malta","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2000/PRP/mlt_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58195,470,"MLT","Malta","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2000/PRP/mlt_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58196,470,"MLT","Malta","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2000/PRP/mlt_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58197,470,"MLT","Malta","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2012/PRP/mlt_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58198,470,"MLT","Malta","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2012/PRP/mlt_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58199,470,"MLT","Malta","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2012/PRP/mlt_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58200,470,"MLT","Malta","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2012/PRP/mlt_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58201,470,"MLT","Malta","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2014/PRP/mlt_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58202,470,"MLT","Malta","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2014/PRP/mlt_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58203,470,"MLT","Malta","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2014/PRP/mlt_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58204,470,"MLT","Malta","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MLT/BuiltSettlement/2014/PRP/mlt_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58205,474,"MTQ","Martinique","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2000/Binary/mtq_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58206,474,"MTQ","Martinique","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2000/DTE/mtq_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58207,474,"MTQ","Martinique","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2012/Binary/mtq_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58208,474,"MTQ","Martinique","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2012/DTE/mtq_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58209,474,"MTQ","Martinique","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2014/Binary/mtq_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58210,474,"MTQ","Martinique","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2014/DTE/mtq_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58211,474,"MTQ","Martinique","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2000/PRP/mtq_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58212,474,"MTQ","Martinique","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2000/PRP/mtq_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58213,474,"MTQ","Martinique","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2000/PRP/mtq_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58214,474,"MTQ","Martinique","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2000/PRP/mtq_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58215,474,"MTQ","Martinique","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2012/PRP/mtq_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58216,474,"MTQ","Martinique","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2012/PRP/mtq_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58217,474,"MTQ","Martinique","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2012/PRP/mtq_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58218,474,"MTQ","Martinique","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2012/PRP/mtq_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58219,474,"MTQ","Martinique","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2014/PRP/mtq_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58220,474,"MTQ","Martinique","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2014/PRP/mtq_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58221,474,"MTQ","Martinique","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2014/PRP/mtq_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58222,474,"MTQ","Martinique","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/BuiltSettlement/2014/PRP/mtq_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58223,478,"MRT","Mauritania","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2000/Binary/mrt_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58224,478,"MRT","Mauritania","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2000/DTE/mrt_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58225,478,"MRT","Mauritania","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2012/Binary/mrt_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58226,478,"MRT","Mauritania","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2012/DTE/mrt_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58227,478,"MRT","Mauritania","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2014/Binary/mrt_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58228,478,"MRT","Mauritania","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2014/DTE/mrt_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58229,478,"MRT","Mauritania","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2000/PRP/mrt_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58230,478,"MRT","Mauritania","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2000/PRP/mrt_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58231,478,"MRT","Mauritania","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2000/PRP/mrt_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58232,478,"MRT","Mauritania","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2000/PRP/mrt_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58233,478,"MRT","Mauritania","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2012/PRP/mrt_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58234,478,"MRT","Mauritania","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2012/PRP/mrt_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58235,478,"MRT","Mauritania","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2012/PRP/mrt_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58236,478,"MRT","Mauritania","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2012/PRP/mrt_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58237,478,"MRT","Mauritania","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2014/PRP/mrt_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58238,478,"MRT","Mauritania","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2014/PRP/mrt_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58239,478,"MRT","Mauritania","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2014/PRP/mrt_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58240,478,"MRT","Mauritania","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MRT/BuiltSettlement/2014/PRP/mrt_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58241,480,"MUS","Mauritius","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2000/Binary/mus_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58242,480,"MUS","Mauritius","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2000/DTE/mus_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58243,480,"MUS","Mauritius","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2012/Binary/mus_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58244,480,"MUS","Mauritius","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2012/DTE/mus_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58245,480,"MUS","Mauritius","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2014/Binary/mus_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58246,480,"MUS","Mauritius","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2014/DTE/mus_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58247,480,"MUS","Mauritius","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2000/PRP/mus_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58248,480,"MUS","Mauritius","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2000/PRP/mus_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58249,480,"MUS","Mauritius","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2000/PRP/mus_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58250,480,"MUS","Mauritius","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2000/PRP/mus_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58251,480,"MUS","Mauritius","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2012/PRP/mus_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58252,480,"MUS","Mauritius","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2012/PRP/mus_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58253,480,"MUS","Mauritius","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2012/PRP/mus_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58254,480,"MUS","Mauritius","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2012/PRP/mus_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58255,480,"MUS","Mauritius","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2014/PRP/mus_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58256,480,"MUS","Mauritius","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2014/PRP/mus_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58257,480,"MUS","Mauritius","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2014/PRP/mus_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58258,480,"MUS","Mauritius","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MUS/BuiltSettlement/2014/PRP/mus_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58259,484,"MEX","Mexico","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2000/Binary/mex_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58260,484,"MEX","Mexico","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2000/DTE/mex_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58261,484,"MEX","Mexico","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2012/Binary/mex_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58262,484,"MEX","Mexico","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2012/DTE/mex_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58263,484,"MEX","Mexico","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2014/Binary/mex_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58264,484,"MEX","Mexico","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2014/DTE/mex_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58265,484,"MEX","Mexico","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2000/PRP/mex_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58266,484,"MEX","Mexico","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2000/PRP/mex_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58267,484,"MEX","Mexico","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2000/PRP/mex_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58268,484,"MEX","Mexico","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2000/PRP/mex_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58269,484,"MEX","Mexico","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2012/PRP/mex_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58270,484,"MEX","Mexico","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2012/PRP/mex_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58271,484,"MEX","Mexico","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2012/PRP/mex_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58272,484,"MEX","Mexico","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2012/PRP/mex_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58273,484,"MEX","Mexico","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2014/PRP/mex_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58274,484,"MEX","Mexico","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2014/PRP/mex_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58275,484,"MEX","Mexico","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2014/PRP/mex_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58276,484,"MEX","Mexico","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MEX/BuiltSettlement/2014/PRP/mex_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58277,492,"MCO","Monaco","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2000/Binary/mco_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58278,492,"MCO","Monaco","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2000/DTE/mco_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58279,492,"MCO","Monaco","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2012/Binary/mco_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58280,492,"MCO","Monaco","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2012/DTE/mco_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58281,492,"MCO","Monaco","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2014/Binary/mco_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58282,492,"MCO","Monaco","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2014/DTE/mco_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58283,492,"MCO","Monaco","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2000/PRP/mco_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58284,492,"MCO","Monaco","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2000/PRP/mco_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58285,492,"MCO","Monaco","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2000/PRP/mco_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58286,492,"MCO","Monaco","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2000/PRP/mco_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58287,492,"MCO","Monaco","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2012/PRP/mco_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58288,492,"MCO","Monaco","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2012/PRP/mco_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58289,492,"MCO","Monaco","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2012/PRP/mco_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58290,492,"MCO","Monaco","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2012/PRP/mco_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58291,492,"MCO","Monaco","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2014/PRP/mco_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58292,492,"MCO","Monaco","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2014/PRP/mco_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58293,492,"MCO","Monaco","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2014/PRP/mco_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58294,492,"MCO","Monaco","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MCO/BuiltSettlement/2014/PRP/mco_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58295,496,"MNG","Mongolia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2000/Binary/mng_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58296,496,"MNG","Mongolia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2000/DTE/mng_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58297,496,"MNG","Mongolia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2012/Binary/mng_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58298,496,"MNG","Mongolia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2012/DTE/mng_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58299,496,"MNG","Mongolia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2014/Binary/mng_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58300,496,"MNG","Mongolia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2014/DTE/mng_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58301,496,"MNG","Mongolia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2000/PRP/mng_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58302,496,"MNG","Mongolia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2000/PRP/mng_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58303,496,"MNG","Mongolia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2000/PRP/mng_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58304,496,"MNG","Mongolia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2000/PRP/mng_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58305,496,"MNG","Mongolia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2012/PRP/mng_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58306,496,"MNG","Mongolia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2012/PRP/mng_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58307,496,"MNG","Mongolia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2012/PRP/mng_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58308,496,"MNG","Mongolia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2012/PRP/mng_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58309,496,"MNG","Mongolia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2014/PRP/mng_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58310,496,"MNG","Mongolia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2014/PRP/mng_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58311,496,"MNG","Mongolia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2014/PRP/mng_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58312,496,"MNG","Mongolia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MNG/BuiltSettlement/2014/PRP/mng_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58313,498,"MDA","Moldova","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2000/Binary/mda_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58314,498,"MDA","Moldova","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2000/DTE/mda_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58315,498,"MDA","Moldova","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2012/Binary/mda_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58316,498,"MDA","Moldova","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2012/DTE/mda_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58317,498,"MDA","Moldova","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2014/Binary/mda_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58318,498,"MDA","Moldova","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2014/DTE/mda_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58319,498,"MDA","Moldova","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2000/PRP/mda_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58320,498,"MDA","Moldova","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2000/PRP/mda_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58321,498,"MDA","Moldova","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2000/PRP/mda_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58322,498,"MDA","Moldova","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2000/PRP/mda_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58323,498,"MDA","Moldova","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2012/PRP/mda_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58324,498,"MDA","Moldova","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2012/PRP/mda_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58325,498,"MDA","Moldova","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2012/PRP/mda_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58326,498,"MDA","Moldova","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2012/PRP/mda_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58327,498,"MDA","Moldova","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2014/PRP/mda_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58328,498,"MDA","Moldova","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2014/PRP/mda_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58329,498,"MDA","Moldova","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2014/PRP/mda_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58330,498,"MDA","Moldova","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MDA/BuiltSettlement/2014/PRP/mda_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58331,499,"MNE","Montenegro","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2000/Binary/mne_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58332,499,"MNE","Montenegro","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2000/DTE/mne_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58333,499,"MNE","Montenegro","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2012/Binary/mne_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58334,499,"MNE","Montenegro","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2012/DTE/mne_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58335,499,"MNE","Montenegro","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2014/Binary/mne_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58336,499,"MNE","Montenegro","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2014/DTE/mne_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58337,499,"MNE","Montenegro","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2000/PRP/mne_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58338,499,"MNE","Montenegro","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2000/PRP/mne_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58339,499,"MNE","Montenegro","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2000/PRP/mne_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58340,499,"MNE","Montenegro","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2000/PRP/mne_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58341,499,"MNE","Montenegro","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2012/PRP/mne_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58342,499,"MNE","Montenegro","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2012/PRP/mne_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58343,499,"MNE","Montenegro","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2012/PRP/mne_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58344,499,"MNE","Montenegro","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2012/PRP/mne_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58345,499,"MNE","Montenegro","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2014/PRP/mne_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58346,499,"MNE","Montenegro","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2014/PRP/mne_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58347,499,"MNE","Montenegro","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2014/PRP/mne_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58348,499,"MNE","Montenegro","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MNE/BuiltSettlement/2014/PRP/mne_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58349,500,"MSR","Montserrat","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2000/Binary/msr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58350,500,"MSR","Montserrat","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2000/DTE/msr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58351,500,"MSR","Montserrat","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2012/Binary/msr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58352,500,"MSR","Montserrat","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2012/DTE/msr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58353,500,"MSR","Montserrat","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2014/Binary/msr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58354,500,"MSR","Montserrat","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2014/DTE/msr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58355,500,"MSR","Montserrat","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2000/PRP/msr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58356,500,"MSR","Montserrat","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2000/PRP/msr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58357,500,"MSR","Montserrat","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2000/PRP/msr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58358,500,"MSR","Montserrat","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2000/PRP/msr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58359,500,"MSR","Montserrat","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2012/PRP/msr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58360,500,"MSR","Montserrat","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2012/PRP/msr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58361,500,"MSR","Montserrat","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2012/PRP/msr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58362,500,"MSR","Montserrat","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2012/PRP/msr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58363,500,"MSR","Montserrat","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2014/PRP/msr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58364,500,"MSR","Montserrat","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2014/PRP/msr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58365,500,"MSR","Montserrat","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2014/PRP/msr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58366,500,"MSR","Montserrat","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MSR/BuiltSettlement/2014/PRP/msr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58367,504,"MAR","Morocco","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2000/Binary/mar_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58368,504,"MAR","Morocco","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2000/DTE/mar_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58369,504,"MAR","Morocco","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2012/Binary/mar_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58370,504,"MAR","Morocco","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2012/DTE/mar_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58371,504,"MAR","Morocco","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2014/Binary/mar_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58372,504,"MAR","Morocco","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2014/DTE/mar_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58373,504,"MAR","Morocco","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2000/PRP/mar_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58374,504,"MAR","Morocco","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2000/PRP/mar_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58375,504,"MAR","Morocco","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2000/PRP/mar_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58376,504,"MAR","Morocco","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2000/PRP/mar_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58377,504,"MAR","Morocco","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2012/PRP/mar_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58378,504,"MAR","Morocco","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2012/PRP/mar_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58379,504,"MAR","Morocco","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2012/PRP/mar_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58380,504,"MAR","Morocco","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2012/PRP/mar_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58381,504,"MAR","Morocco","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2014/PRP/mar_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58382,504,"MAR","Morocco","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2014/PRP/mar_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58383,504,"MAR","Morocco","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2014/PRP/mar_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58384,504,"MAR","Morocco","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MAR/BuiltSettlement/2014/PRP/mar_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58385,508,"MOZ","Mozambique","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2000/Binary/moz_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58386,508,"MOZ","Mozambique","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2000/DTE/moz_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58387,508,"MOZ","Mozambique","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2012/Binary/moz_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58388,508,"MOZ","Mozambique","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2012/DTE/moz_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58389,508,"MOZ","Mozambique","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2014/Binary/moz_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58390,508,"MOZ","Mozambique","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2014/DTE/moz_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58391,508,"MOZ","Mozambique","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2000/PRP/moz_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58392,508,"MOZ","Mozambique","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2000/PRP/moz_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58393,508,"MOZ","Mozambique","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2000/PRP/moz_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58394,508,"MOZ","Mozambique","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2000/PRP/moz_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58395,508,"MOZ","Mozambique","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2012/PRP/moz_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58396,508,"MOZ","Mozambique","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2012/PRP/moz_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58397,508,"MOZ","Mozambique","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2012/PRP/moz_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58398,508,"MOZ","Mozambique","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2012/PRP/moz_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58399,508,"MOZ","Mozambique","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2014/PRP/moz_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58400,508,"MOZ","Mozambique","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2014/PRP/moz_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58401,508,"MOZ","Mozambique","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2014/PRP/moz_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58402,508,"MOZ","Mozambique","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/BuiltSettlement/2014/PRP/moz_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58403,512,"OMN","Oman","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2000/Binary/omn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58404,512,"OMN","Oman","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2000/DTE/omn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58405,512,"OMN","Oman","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2012/Binary/omn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58406,512,"OMN","Oman","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2012/DTE/omn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58407,512,"OMN","Oman","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2014/Binary/omn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58408,512,"OMN","Oman","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2014/DTE/omn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58409,512,"OMN","Oman","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2000/PRP/omn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58410,512,"OMN","Oman","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2000/PRP/omn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58411,512,"OMN","Oman","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2000/PRP/omn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58412,512,"OMN","Oman","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2000/PRP/omn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58413,512,"OMN","Oman","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2012/PRP/omn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58414,512,"OMN","Oman","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2012/PRP/omn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58415,512,"OMN","Oman","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2012/PRP/omn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58416,512,"OMN","Oman","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2012/PRP/omn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58417,512,"OMN","Oman","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2014/PRP/omn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58418,512,"OMN","Oman","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2014/PRP/omn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58419,512,"OMN","Oman","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2014/PRP/omn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58420,512,"OMN","Oman","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/OMN/BuiltSettlement/2014/PRP/omn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58421,516,"NAM","Namibia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2000/Binary/nam_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58422,516,"NAM","Namibia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2000/DTE/nam_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58423,516,"NAM","Namibia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2012/Binary/nam_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58424,516,"NAM","Namibia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2012/DTE/nam_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58425,516,"NAM","Namibia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2014/Binary/nam_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58426,516,"NAM","Namibia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2014/DTE/nam_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58427,516,"NAM","Namibia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2000/PRP/nam_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58428,516,"NAM","Namibia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2000/PRP/nam_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58429,516,"NAM","Namibia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2000/PRP/nam_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58430,516,"NAM","Namibia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2000/PRP/nam_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58431,516,"NAM","Namibia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2012/PRP/nam_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58432,516,"NAM","Namibia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2012/PRP/nam_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58433,516,"NAM","Namibia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2012/PRP/nam_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58434,516,"NAM","Namibia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2012/PRP/nam_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58435,516,"NAM","Namibia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2014/PRP/nam_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58436,516,"NAM","Namibia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2014/PRP/nam_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58437,516,"NAM","Namibia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2014/PRP/nam_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58438,516,"NAM","Namibia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NAM/BuiltSettlement/2014/PRP/nam_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58439,520,"NRU","Nauru","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2000/Binary/nru_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58440,520,"NRU","Nauru","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2000/DTE/nru_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58441,520,"NRU","Nauru","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2012/Binary/nru_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58442,520,"NRU","Nauru","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2012/DTE/nru_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58443,520,"NRU","Nauru","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2014/Binary/nru_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58444,520,"NRU","Nauru","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2014/DTE/nru_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58445,520,"NRU","Nauru","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2000/PRP/nru_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58446,520,"NRU","Nauru","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2000/PRP/nru_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58447,520,"NRU","Nauru","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2000/PRP/nru_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58448,520,"NRU","Nauru","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2000/PRP/nru_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58449,520,"NRU","Nauru","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2012/PRP/nru_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58450,520,"NRU","Nauru","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2012/PRP/nru_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58451,520,"NRU","Nauru","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2012/PRP/nru_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58452,520,"NRU","Nauru","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2012/PRP/nru_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58453,520,"NRU","Nauru","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2014/PRP/nru_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58454,520,"NRU","Nauru","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2014/PRP/nru_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58455,520,"NRU","Nauru","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2014/PRP/nru_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58456,520,"NRU","Nauru","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NRU/BuiltSettlement/2014/PRP/nru_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58457,524,"NPL","Nepal","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2000/Binary/npl_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58458,524,"NPL","Nepal","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2000/DTE/npl_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58459,524,"NPL","Nepal","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2012/Binary/npl_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58460,524,"NPL","Nepal","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2012/DTE/npl_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58461,524,"NPL","Nepal","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2014/Binary/npl_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58462,524,"NPL","Nepal","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2014/DTE/npl_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58463,524,"NPL","Nepal","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2000/PRP/npl_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58464,524,"NPL","Nepal","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2000/PRP/npl_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58465,524,"NPL","Nepal","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2000/PRP/npl_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58466,524,"NPL","Nepal","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2000/PRP/npl_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58467,524,"NPL","Nepal","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2012/PRP/npl_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58468,524,"NPL","Nepal","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2012/PRP/npl_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58469,524,"NPL","Nepal","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2012/PRP/npl_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58470,524,"NPL","Nepal","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2012/PRP/npl_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58471,524,"NPL","Nepal","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2014/PRP/npl_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58472,524,"NPL","Nepal","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2014/PRP/npl_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58473,524,"NPL","Nepal","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2014/PRP/npl_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58474,524,"NPL","Nepal","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NPL/BuiltSettlement/2014/PRP/npl_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58475,528,"NLD","Netherlands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2000/Binary/nld_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58476,528,"NLD","Netherlands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2000/DTE/nld_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58477,528,"NLD","Netherlands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2012/Binary/nld_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58478,528,"NLD","Netherlands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2012/DTE/nld_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58479,528,"NLD","Netherlands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2014/Binary/nld_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58480,528,"NLD","Netherlands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2014/DTE/nld_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58481,528,"NLD","Netherlands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2000/PRP/nld_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58482,528,"NLD","Netherlands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2000/PRP/nld_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58483,528,"NLD","Netherlands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2000/PRP/nld_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58484,528,"NLD","Netherlands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2000/PRP/nld_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58485,528,"NLD","Netherlands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2012/PRP/nld_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58486,528,"NLD","Netherlands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2012/PRP/nld_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58487,528,"NLD","Netherlands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2012/PRP/nld_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58488,528,"NLD","Netherlands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2012/PRP/nld_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58489,528,"NLD","Netherlands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2014/PRP/nld_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58490,528,"NLD","Netherlands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2014/PRP/nld_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58491,528,"NLD","Netherlands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2014/PRP/nld_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58492,528,"NLD","Netherlands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NLD/BuiltSettlement/2014/PRP/nld_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58493,531,"CUW","Curacao","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2000/Binary/cuw_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58494,531,"CUW","Curacao","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2000/DTE/cuw_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58495,531,"CUW","Curacao","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2012/Binary/cuw_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58496,531,"CUW","Curacao","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2012/DTE/cuw_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58497,531,"CUW","Curacao","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2014/Binary/cuw_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58498,531,"CUW","Curacao","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2014/DTE/cuw_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58499,531,"CUW","Curacao","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2000/PRP/cuw_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58500,531,"CUW","Curacao","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2000/PRP/cuw_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58501,531,"CUW","Curacao","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2000/PRP/cuw_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58502,531,"CUW","Curacao","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2000/PRP/cuw_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58503,531,"CUW","Curacao","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2012/PRP/cuw_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58504,531,"CUW","Curacao","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2012/PRP/cuw_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58505,531,"CUW","Curacao","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2012/PRP/cuw_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58506,531,"CUW","Curacao","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2012/PRP/cuw_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58507,531,"CUW","Curacao","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2014/PRP/cuw_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58508,531,"CUW","Curacao","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2014/PRP/cuw_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58509,531,"CUW","Curacao","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2014/PRP/cuw_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58510,531,"CUW","Curacao","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CUW/BuiltSettlement/2014/PRP/cuw_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58511,533,"ABW","Aruba","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2000/Binary/abw_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58512,533,"ABW","Aruba","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2000/DTE/abw_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58513,533,"ABW","Aruba","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2012/Binary/abw_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58514,533,"ABW","Aruba","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2012/DTE/abw_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58515,533,"ABW","Aruba","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2014/Binary/abw_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58516,533,"ABW","Aruba","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2014/DTE/abw_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58517,533,"ABW","Aruba","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2000/PRP/abw_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58518,533,"ABW","Aruba","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2000/PRP/abw_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58519,533,"ABW","Aruba","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2000/PRP/abw_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58520,533,"ABW","Aruba","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2000/PRP/abw_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58521,533,"ABW","Aruba","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2012/PRP/abw_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58522,533,"ABW","Aruba","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2012/PRP/abw_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58523,533,"ABW","Aruba","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2012/PRP/abw_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58524,533,"ABW","Aruba","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2012/PRP/abw_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58525,533,"ABW","Aruba","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2014/PRP/abw_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58526,533,"ABW","Aruba","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2014/PRP/abw_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58527,533,"ABW","Aruba","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2014/PRP/abw_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58528,533,"ABW","Aruba","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ABW/BuiltSettlement/2014/PRP/abw_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58529,534,"SXM","Sint Maarten (Dutch part)","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2000/Binary/sxm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58530,534,"SXM","Sint Maarten (Dutch part)","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2000/DTE/sxm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58531,534,"SXM","Sint Maarten (Dutch part)","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2012/Binary/sxm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58532,534,"SXM","Sint Maarten (Dutch part)","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2012/DTE/sxm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58533,534,"SXM","Sint Maarten (Dutch part)","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2014/Binary/sxm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58534,534,"SXM","Sint Maarten (Dutch part)","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2014/DTE/sxm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58535,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2000/PRP/sxm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58536,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2000/PRP/sxm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58537,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2000/PRP/sxm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58538,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2000/PRP/sxm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58539,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2012/PRP/sxm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58540,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2012/PRP/sxm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58541,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2012/PRP/sxm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58542,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2012/PRP/sxm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58543,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2014/PRP/sxm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58544,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2014/PRP/sxm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58545,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2014/PRP/sxm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58546,534,"SXM","Sint Maarten (Dutch part)","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SXM/BuiltSettlement/2014/PRP/sxm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58547,535,"BES","Bonaire, Sint Eustatius and Saba","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2000/Binary/bes_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58548,535,"BES","Bonaire, Sint Eustatius and Saba","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2000/DTE/bes_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58549,535,"BES","Bonaire, Sint Eustatius and Saba","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2012/Binary/bes_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58550,535,"BES","Bonaire, Sint Eustatius and Saba","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2012/DTE/bes_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58551,535,"BES","Bonaire, Sint Eustatius and Saba","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2014/Binary/bes_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58552,535,"BES","Bonaire, Sint Eustatius and Saba","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2014/DTE/bes_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58553,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2000/PRP/bes_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58554,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2000/PRP/bes_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58555,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2000/PRP/bes_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58556,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2000/PRP/bes_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58557,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2012/PRP/bes_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58558,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2012/PRP/bes_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58559,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2012/PRP/bes_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58560,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2012/PRP/bes_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58561,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2014/PRP/bes_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58562,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2014/PRP/bes_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58563,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2014/PRP/bes_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58564,535,"BES","Bonaire, Sint Eustatius and Saba","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BES/BuiltSettlement/2014/PRP/bes_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58565,540,"NCL","New Caledonia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2000/Binary/ncl_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58566,540,"NCL","New Caledonia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2000/DTE/ncl_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58567,540,"NCL","New Caledonia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2012/Binary/ncl_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58568,540,"NCL","New Caledonia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2012/DTE/ncl_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58569,540,"NCL","New Caledonia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2014/Binary/ncl_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58570,540,"NCL","New Caledonia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2014/DTE/ncl_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58571,540,"NCL","New Caledonia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2000/PRP/ncl_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58572,540,"NCL","New Caledonia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2000/PRP/ncl_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58573,540,"NCL","New Caledonia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2000/PRP/ncl_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58574,540,"NCL","New Caledonia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2000/PRP/ncl_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58575,540,"NCL","New Caledonia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2012/PRP/ncl_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58576,540,"NCL","New Caledonia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2012/PRP/ncl_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58577,540,"NCL","New Caledonia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2012/PRP/ncl_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58578,540,"NCL","New Caledonia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2012/PRP/ncl_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58579,540,"NCL","New Caledonia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2014/PRP/ncl_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58580,540,"NCL","New Caledonia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2014/PRP/ncl_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58581,540,"NCL","New Caledonia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2014/PRP/ncl_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58582,540,"NCL","New Caledonia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NCL/BuiltSettlement/2014/PRP/ncl_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58583,548,"VUT","Vanuatu","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2000/Binary/vut_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58584,548,"VUT","Vanuatu","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2000/DTE/vut_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58585,548,"VUT","Vanuatu","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2012/Binary/vut_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58586,548,"VUT","Vanuatu","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2012/DTE/vut_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58587,548,"VUT","Vanuatu","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2014/Binary/vut_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58588,548,"VUT","Vanuatu","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2014/DTE/vut_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58589,548,"VUT","Vanuatu","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2000/PRP/vut_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58590,548,"VUT","Vanuatu","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2000/PRP/vut_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58591,548,"VUT","Vanuatu","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2000/PRP/vut_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58592,548,"VUT","Vanuatu","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2000/PRP/vut_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58593,548,"VUT","Vanuatu","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2012/PRP/vut_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58594,548,"VUT","Vanuatu","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2012/PRP/vut_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58595,548,"VUT","Vanuatu","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2012/PRP/vut_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58596,548,"VUT","Vanuatu","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2012/PRP/vut_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58597,548,"VUT","Vanuatu","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2014/PRP/vut_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58598,548,"VUT","Vanuatu","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2014/PRP/vut_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58599,548,"VUT","Vanuatu","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2014/PRP/vut_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58600,548,"VUT","Vanuatu","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/VUT/BuiltSettlement/2014/PRP/vut_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58601,554,"NZL","New Zealand","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2000/Binary/nzl_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58602,554,"NZL","New Zealand","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2000/DTE/nzl_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58603,554,"NZL","New Zealand","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2012/Binary/nzl_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58604,554,"NZL","New Zealand","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2012/DTE/nzl_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58605,554,"NZL","New Zealand","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2014/Binary/nzl_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58606,554,"NZL","New Zealand","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2014/DTE/nzl_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58607,554,"NZL","New Zealand","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2000/PRP/nzl_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58608,554,"NZL","New Zealand","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2000/PRP/nzl_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58609,554,"NZL","New Zealand","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2000/PRP/nzl_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58610,554,"NZL","New Zealand","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2000/PRP/nzl_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58611,554,"NZL","New Zealand","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2012/PRP/nzl_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58612,554,"NZL","New Zealand","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2012/PRP/nzl_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58613,554,"NZL","New Zealand","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2012/PRP/nzl_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58614,554,"NZL","New Zealand","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2012/PRP/nzl_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58615,554,"NZL","New Zealand","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2014/PRP/nzl_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58616,554,"NZL","New Zealand","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2014/PRP/nzl_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58617,554,"NZL","New Zealand","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2014/PRP/nzl_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58618,554,"NZL","New Zealand","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NZL/BuiltSettlement/2014/PRP/nzl_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58619,558,"NIC","Nicaragua","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2000/Binary/nic_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58620,558,"NIC","Nicaragua","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2000/DTE/nic_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58621,558,"NIC","Nicaragua","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2012/Binary/nic_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58622,558,"NIC","Nicaragua","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2012/DTE/nic_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58623,558,"NIC","Nicaragua","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2014/Binary/nic_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58624,558,"NIC","Nicaragua","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2014/DTE/nic_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58625,558,"NIC","Nicaragua","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2000/PRP/nic_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58626,558,"NIC","Nicaragua","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2000/PRP/nic_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58627,558,"NIC","Nicaragua","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2000/PRP/nic_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58628,558,"NIC","Nicaragua","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2000/PRP/nic_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58629,558,"NIC","Nicaragua","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2012/PRP/nic_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58630,558,"NIC","Nicaragua","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2012/PRP/nic_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58631,558,"NIC","Nicaragua","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2012/PRP/nic_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58632,558,"NIC","Nicaragua","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2012/PRP/nic_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58633,558,"NIC","Nicaragua","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2014/PRP/nic_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58634,558,"NIC","Nicaragua","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2014/PRP/nic_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58635,558,"NIC","Nicaragua","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2014/PRP/nic_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58636,558,"NIC","Nicaragua","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NIC/BuiltSettlement/2014/PRP/nic_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58637,562,"NER","Niger","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2000/Binary/ner_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58638,562,"NER","Niger","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2000/DTE/ner_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58639,562,"NER","Niger","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2012/Binary/ner_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58640,562,"NER","Niger","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2012/DTE/ner_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58641,562,"NER","Niger","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2014/Binary/ner_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58642,562,"NER","Niger","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2014/DTE/ner_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58643,562,"NER","Niger","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2000/PRP/ner_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58644,562,"NER","Niger","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2000/PRP/ner_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58645,562,"NER","Niger","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2000/PRP/ner_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58646,562,"NER","Niger","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2000/PRP/ner_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58647,562,"NER","Niger","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2012/PRP/ner_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58648,562,"NER","Niger","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2012/PRP/ner_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58649,562,"NER","Niger","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2012/PRP/ner_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58650,562,"NER","Niger","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2012/PRP/ner_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58651,562,"NER","Niger","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2014/PRP/ner_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58652,562,"NER","Niger","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2014/PRP/ner_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58653,562,"NER","Niger","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2014/PRP/ner_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58654,562,"NER","Niger","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NER/BuiltSettlement/2014/PRP/ner_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58655,566,"NGA","Nigeria","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2000/Binary/nga_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58656,566,"NGA","Nigeria","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2000/DTE/nga_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58657,566,"NGA","Nigeria","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2012/Binary/nga_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58658,566,"NGA","Nigeria","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2012/DTE/nga_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58659,566,"NGA","Nigeria","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2014/Binary/nga_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58660,566,"NGA","Nigeria","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2014/DTE/nga_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58661,566,"NGA","Nigeria","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2000/PRP/nga_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58662,566,"NGA","Nigeria","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2000/PRP/nga_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58663,566,"NGA","Nigeria","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2000/PRP/nga_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58664,566,"NGA","Nigeria","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2000/PRP/nga_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58665,566,"NGA","Nigeria","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2012/PRP/nga_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58666,566,"NGA","Nigeria","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2012/PRP/nga_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58667,566,"NGA","Nigeria","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2012/PRP/nga_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58668,566,"NGA","Nigeria","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2012/PRP/nga_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58669,566,"NGA","Nigeria","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2014/PRP/nga_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58670,566,"NGA","Nigeria","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2014/PRP/nga_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58671,566,"NGA","Nigeria","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2014/PRP/nga_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58672,566,"NGA","Nigeria","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NGA/BuiltSettlement/2014/PRP/nga_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58673,570,"NIU","Niue","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2000/Binary/niu_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58674,570,"NIU","Niue","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2000/DTE/niu_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58675,570,"NIU","Niue","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2012/Binary/niu_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58676,570,"NIU","Niue","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2012/DTE/niu_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58677,570,"NIU","Niue","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2014/Binary/niu_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58678,570,"NIU","Niue","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2014/DTE/niu_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58679,570,"NIU","Niue","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2000/PRP/niu_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58680,570,"NIU","Niue","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2000/PRP/niu_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58681,570,"NIU","Niue","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2000/PRP/niu_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58682,570,"NIU","Niue","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2000/PRP/niu_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58683,570,"NIU","Niue","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2012/PRP/niu_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58684,570,"NIU","Niue","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2012/PRP/niu_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58685,570,"NIU","Niue","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2012/PRP/niu_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58686,570,"NIU","Niue","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2012/PRP/niu_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58687,570,"NIU","Niue","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2014/PRP/niu_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58688,570,"NIU","Niue","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2014/PRP/niu_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58689,570,"NIU","Niue","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2014/PRP/niu_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58690,570,"NIU","Niue","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NIU/BuiltSettlement/2014/PRP/niu_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58691,574,"NFK","Norfolk Island","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2000/Binary/nfk_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58692,574,"NFK","Norfolk Island","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2000/DTE/nfk_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58693,574,"NFK","Norfolk Island","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2012/Binary/nfk_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58694,574,"NFK","Norfolk Island","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2012/DTE/nfk_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58695,574,"NFK","Norfolk Island","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2014/Binary/nfk_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58696,574,"NFK","Norfolk Island","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2014/DTE/nfk_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58697,574,"NFK","Norfolk Island","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2000/PRP/nfk_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58698,574,"NFK","Norfolk Island","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2000/PRP/nfk_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58699,574,"NFK","Norfolk Island","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2000/PRP/nfk_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58700,574,"NFK","Norfolk Island","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2000/PRP/nfk_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58701,574,"NFK","Norfolk Island","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2012/PRP/nfk_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58702,574,"NFK","Norfolk Island","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2012/PRP/nfk_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58703,574,"NFK","Norfolk Island","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2012/PRP/nfk_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58704,574,"NFK","Norfolk Island","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2012/PRP/nfk_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58705,574,"NFK","Norfolk Island","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2014/PRP/nfk_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58706,574,"NFK","Norfolk Island","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2014/PRP/nfk_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58707,574,"NFK","Norfolk Island","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2014/PRP/nfk_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58708,574,"NFK","Norfolk Island","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NFK/BuiltSettlement/2014/PRP/nfk_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58709,578,"NOR","Norway","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2000/Binary/nor_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58710,578,"NOR","Norway","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2000/DTE/nor_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58711,578,"NOR","Norway","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2012/Binary/nor_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58712,578,"NOR","Norway","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2012/DTE/nor_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58713,578,"NOR","Norway","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2014/Binary/nor_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58714,578,"NOR","Norway","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2014/DTE/nor_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58715,578,"NOR","Norway","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2000/PRP/nor_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58716,578,"NOR","Norway","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2000/PRP/nor_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58717,578,"NOR","Norway","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2000/PRP/nor_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58718,578,"NOR","Norway","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2000/PRP/nor_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58719,578,"NOR","Norway","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2012/PRP/nor_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58720,578,"NOR","Norway","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2012/PRP/nor_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58721,578,"NOR","Norway","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2012/PRP/nor_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58722,578,"NOR","Norway","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2012/PRP/nor_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58723,578,"NOR","Norway","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2014/PRP/nor_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58724,578,"NOR","Norway","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2014/PRP/nor_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58725,578,"NOR","Norway","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2014/PRP/nor_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58726,578,"NOR","Norway","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/NOR/BuiltSettlement/2014/PRP/nor_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58727,580,"MNP","Northern Mariana Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2000/Binary/mnp_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58728,580,"MNP","Northern Mariana Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2000/DTE/mnp_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58729,580,"MNP","Northern Mariana Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2012/Binary/mnp_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58730,580,"MNP","Northern Mariana Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2012/DTE/mnp_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58731,580,"MNP","Northern Mariana Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2014/Binary/mnp_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58732,580,"MNP","Northern Mariana Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2014/DTE/mnp_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58733,580,"MNP","Northern Mariana Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2000/PRP/mnp_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58734,580,"MNP","Northern Mariana Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2000/PRP/mnp_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58735,580,"MNP","Northern Mariana Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2000/PRP/mnp_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58736,580,"MNP","Northern Mariana Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2000/PRP/mnp_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58737,580,"MNP","Northern Mariana Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2012/PRP/mnp_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58738,580,"MNP","Northern Mariana Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2012/PRP/mnp_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58739,580,"MNP","Northern Mariana Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2012/PRP/mnp_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58740,580,"MNP","Northern Mariana Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2012/PRP/mnp_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58741,580,"MNP","Northern Mariana Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2014/PRP/mnp_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58742,580,"MNP","Northern Mariana Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2014/PRP/mnp_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58743,580,"MNP","Northern Mariana Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2014/PRP/mnp_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58744,580,"MNP","Northern Mariana Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MNP/BuiltSettlement/2014/PRP/mnp_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58745,581,"UMI","United States Minor Outlying Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2000/Binary/umi_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58746,581,"UMI","United States Minor Outlying Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2000/DTE/umi_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58747,581,"UMI","United States Minor Outlying Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2012/Binary/umi_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58748,581,"UMI","United States Minor Outlying Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2012/DTE/umi_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58749,581,"UMI","United States Minor Outlying Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2014/Binary/umi_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58750,581,"UMI","United States Minor Outlying Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2014/DTE/umi_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58751,581,"UMI","United States Minor Outlying Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2000/PRP/umi_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58752,581,"UMI","United States Minor Outlying Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2000/PRP/umi_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58753,581,"UMI","United States Minor Outlying Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2000/PRP/umi_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58754,581,"UMI","United States Minor Outlying Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2000/PRP/umi_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58755,581,"UMI","United States Minor Outlying Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2012/PRP/umi_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58756,581,"UMI","United States Minor Outlying Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2012/PRP/umi_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58757,581,"UMI","United States Minor Outlying Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2012/PRP/umi_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58758,581,"UMI","United States Minor Outlying Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2012/PRP/umi_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58759,581,"UMI","United States Minor Outlying Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2014/PRP/umi_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58760,581,"UMI","United States Minor Outlying Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2014/PRP/umi_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58761,581,"UMI","United States Minor Outlying Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2014/PRP/umi_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58762,581,"UMI","United States Minor Outlying Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/UMI/BuiltSettlement/2014/PRP/umi_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58763,583,"FSM","Micronesia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2000/Binary/fsm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58764,583,"FSM","Micronesia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2000/DTE/fsm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58765,583,"FSM","Micronesia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2012/Binary/fsm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58766,583,"FSM","Micronesia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2012/DTE/fsm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58767,583,"FSM","Micronesia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2014/Binary/fsm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58768,583,"FSM","Micronesia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2014/DTE/fsm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58769,583,"FSM","Micronesia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2000/PRP/fsm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58770,583,"FSM","Micronesia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2000/PRP/fsm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58771,583,"FSM","Micronesia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2000/PRP/fsm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58772,583,"FSM","Micronesia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2000/PRP/fsm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58773,583,"FSM","Micronesia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2012/PRP/fsm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58774,583,"FSM","Micronesia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2012/PRP/fsm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58775,583,"FSM","Micronesia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2012/PRP/fsm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58776,583,"FSM","Micronesia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2012/PRP/fsm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58777,583,"FSM","Micronesia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2014/PRP/fsm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58778,583,"FSM","Micronesia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2014/PRP/fsm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58779,583,"FSM","Micronesia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2014/PRP/fsm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58780,583,"FSM","Micronesia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/FSM/BuiltSettlement/2014/PRP/fsm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58781,584,"MHL","Marshall Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2000/Binary/mhl_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58782,584,"MHL","Marshall Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2000/DTE/mhl_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58783,584,"MHL","Marshall Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2012/Binary/mhl_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58784,584,"MHL","Marshall Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2012/DTE/mhl_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58785,584,"MHL","Marshall Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2014/Binary/mhl_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58786,584,"MHL","Marshall Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2014/DTE/mhl_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58787,584,"MHL","Marshall Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2000/PRP/mhl_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58788,584,"MHL","Marshall Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2000/PRP/mhl_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58789,584,"MHL","Marshall Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2000/PRP/mhl_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58790,584,"MHL","Marshall Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2000/PRP/mhl_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58791,584,"MHL","Marshall Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2012/PRP/mhl_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58792,584,"MHL","Marshall Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2012/PRP/mhl_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58793,584,"MHL","Marshall Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2012/PRP/mhl_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58794,584,"MHL","Marshall Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2012/PRP/mhl_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58795,584,"MHL","Marshall Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2014/PRP/mhl_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58796,584,"MHL","Marshall Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2014/PRP/mhl_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58797,584,"MHL","Marshall Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2014/PRP/mhl_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58798,584,"MHL","Marshall Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MHL/BuiltSettlement/2014/PRP/mhl_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58799,585,"PLW","Palau","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2000/Binary/plw_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58800,585,"PLW","Palau","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2000/DTE/plw_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58801,585,"PLW","Palau","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2012/Binary/plw_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58802,585,"PLW","Palau","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2012/DTE/plw_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58803,585,"PLW","Palau","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2014/Binary/plw_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58804,585,"PLW","Palau","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2014/DTE/plw_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58805,585,"PLW","Palau","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2000/PRP/plw_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58806,585,"PLW","Palau","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2000/PRP/plw_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58807,585,"PLW","Palau","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2000/PRP/plw_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58808,585,"PLW","Palau","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2000/PRP/plw_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58809,585,"PLW","Palau","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2012/PRP/plw_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58810,585,"PLW","Palau","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2012/PRP/plw_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58811,585,"PLW","Palau","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2012/PRP/plw_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58812,585,"PLW","Palau","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2012/PRP/plw_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58813,585,"PLW","Palau","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2014/PRP/plw_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58814,585,"PLW","Palau","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2014/PRP/plw_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58815,585,"PLW","Palau","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2014/PRP/plw_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58816,585,"PLW","Palau","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PLW/BuiltSettlement/2014/PRP/plw_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58817,586,"PAK","Pakistan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2000/Binary/pak_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58818,586,"PAK","Pakistan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2000/DTE/pak_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58819,586,"PAK","Pakistan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2012/Binary/pak_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58820,586,"PAK","Pakistan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2012/DTE/pak_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58821,586,"PAK","Pakistan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2014/Binary/pak_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58822,586,"PAK","Pakistan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2014/DTE/pak_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58823,586,"PAK","Pakistan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2000/PRP/pak_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58824,586,"PAK","Pakistan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2000/PRP/pak_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58825,586,"PAK","Pakistan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2000/PRP/pak_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58826,586,"PAK","Pakistan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2000/PRP/pak_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58827,586,"PAK","Pakistan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2012/PRP/pak_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58828,586,"PAK","Pakistan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2012/PRP/pak_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58829,586,"PAK","Pakistan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2012/PRP/pak_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58830,586,"PAK","Pakistan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2012/PRP/pak_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58831,586,"PAK","Pakistan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2014/PRP/pak_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58832,586,"PAK","Pakistan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2014/PRP/pak_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58833,586,"PAK","Pakistan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2014/PRP/pak_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58834,586,"PAK","Pakistan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PAK/BuiltSettlement/2014/PRP/pak_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58835,591,"PAN","Panama","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2000/Binary/pan_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58836,591,"PAN","Panama","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2000/DTE/pan_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58837,591,"PAN","Panama","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2012/Binary/pan_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58838,591,"PAN","Panama","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2012/DTE/pan_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58839,591,"PAN","Panama","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2014/Binary/pan_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58840,591,"PAN","Panama","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2014/DTE/pan_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58841,591,"PAN","Panama","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2000/PRP/pan_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58842,591,"PAN","Panama","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2000/PRP/pan_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58843,591,"PAN","Panama","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2000/PRP/pan_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58844,591,"PAN","Panama","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2000/PRP/pan_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58845,591,"PAN","Panama","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2012/PRP/pan_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58846,591,"PAN","Panama","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2012/PRP/pan_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58847,591,"PAN","Panama","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2012/PRP/pan_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58848,591,"PAN","Panama","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2012/PRP/pan_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58849,591,"PAN","Panama","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2014/PRP/pan_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58850,591,"PAN","Panama","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2014/PRP/pan_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58851,591,"PAN","Panama","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2014/PRP/pan_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58852,591,"PAN","Panama","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PAN/BuiltSettlement/2014/PRP/pan_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58853,598,"PNG","Papua New Guinea","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2000/Binary/png_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58854,598,"PNG","Papua New Guinea","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2000/DTE/png_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58855,598,"PNG","Papua New Guinea","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2012/Binary/png_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58856,598,"PNG","Papua New Guinea","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2012/DTE/png_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58857,598,"PNG","Papua New Guinea","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2014/Binary/png_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58858,598,"PNG","Papua New Guinea","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2014/DTE/png_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58859,598,"PNG","Papua New Guinea","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2000/PRP/png_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58860,598,"PNG","Papua New Guinea","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2000/PRP/png_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58861,598,"PNG","Papua New Guinea","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2000/PRP/png_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58862,598,"PNG","Papua New Guinea","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2000/PRP/png_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58863,598,"PNG","Papua New Guinea","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2012/PRP/png_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58864,598,"PNG","Papua New Guinea","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2012/PRP/png_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58865,598,"PNG","Papua New Guinea","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2012/PRP/png_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58866,598,"PNG","Papua New Guinea","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2012/PRP/png_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58867,598,"PNG","Papua New Guinea","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2014/PRP/png_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58868,598,"PNG","Papua New Guinea","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2014/PRP/png_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58869,598,"PNG","Papua New Guinea","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2014/PRP/png_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58870,598,"PNG","Papua New Guinea","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PNG/BuiltSettlement/2014/PRP/png_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58871,600,"PRY","Paraguay","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2000/Binary/pry_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58872,600,"PRY","Paraguay","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2000/DTE/pry_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58873,600,"PRY","Paraguay","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2012/Binary/pry_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58874,600,"PRY","Paraguay","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2012/DTE/pry_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58875,600,"PRY","Paraguay","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2014/Binary/pry_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58876,600,"PRY","Paraguay","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2014/DTE/pry_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58877,600,"PRY","Paraguay","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2000/PRP/pry_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58878,600,"PRY","Paraguay","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2000/PRP/pry_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58879,600,"PRY","Paraguay","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2000/PRP/pry_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58880,600,"PRY","Paraguay","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2000/PRP/pry_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58881,600,"PRY","Paraguay","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2012/PRP/pry_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58882,600,"PRY","Paraguay","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2012/PRP/pry_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58883,600,"PRY","Paraguay","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2012/PRP/pry_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58884,600,"PRY","Paraguay","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2012/PRP/pry_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58885,600,"PRY","Paraguay","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2014/PRP/pry_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58886,600,"PRY","Paraguay","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2014/PRP/pry_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58887,600,"PRY","Paraguay","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2014/PRP/pry_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58888,600,"PRY","Paraguay","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PRY/BuiltSettlement/2014/PRP/pry_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58889,604,"PER","Peru","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2000/Binary/per_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58890,604,"PER","Peru","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2000/DTE/per_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58891,604,"PER","Peru","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2012/Binary/per_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58892,604,"PER","Peru","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2012/DTE/per_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58893,604,"PER","Peru","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2014/Binary/per_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58894,604,"PER","Peru","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2014/DTE/per_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58895,604,"PER","Peru","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2000/PRP/per_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58896,604,"PER","Peru","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2000/PRP/per_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58897,604,"PER","Peru","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2000/PRP/per_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58898,604,"PER","Peru","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2000/PRP/per_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58899,604,"PER","Peru","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2012/PRP/per_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58900,604,"PER","Peru","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2012/PRP/per_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58901,604,"PER","Peru","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2012/PRP/per_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58902,604,"PER","Peru","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2012/PRP/per_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58903,604,"PER","Peru","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2014/PRP/per_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58904,604,"PER","Peru","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2014/PRP/per_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58905,604,"PER","Peru","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2014/PRP/per_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58906,604,"PER","Peru","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PER/BuiltSettlement/2014/PRP/per_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58907,608,"PHL","Philippines","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2000/Binary/phl_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58908,608,"PHL","Philippines","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2000/DTE/phl_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58909,608,"PHL","Philippines","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2012/Binary/phl_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58910,608,"PHL","Philippines","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2012/DTE/phl_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58911,608,"PHL","Philippines","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2014/Binary/phl_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58912,608,"PHL","Philippines","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2014/DTE/phl_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58913,608,"PHL","Philippines","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2000/PRP/phl_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58914,608,"PHL","Philippines","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2000/PRP/phl_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58915,608,"PHL","Philippines","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2000/PRP/phl_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58916,608,"PHL","Philippines","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2000/PRP/phl_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58917,608,"PHL","Philippines","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2012/PRP/phl_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58918,608,"PHL","Philippines","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2012/PRP/phl_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58919,608,"PHL","Philippines","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2012/PRP/phl_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58920,608,"PHL","Philippines","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2012/PRP/phl_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58921,608,"PHL","Philippines","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2014/PRP/phl_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58922,608,"PHL","Philippines","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2014/PRP/phl_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58923,608,"PHL","Philippines","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2014/PRP/phl_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58924,608,"PHL","Philippines","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PHL/BuiltSettlement/2014/PRP/phl_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58925,612,"PCN","Pitcairn Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2000/Binary/pcn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58926,612,"PCN","Pitcairn Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2000/DTE/pcn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58927,612,"PCN","Pitcairn Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2012/Binary/pcn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58928,612,"PCN","Pitcairn Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2012/DTE/pcn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58929,612,"PCN","Pitcairn Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2014/Binary/pcn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58930,612,"PCN","Pitcairn Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2014/DTE/pcn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58931,612,"PCN","Pitcairn Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2000/PRP/pcn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58932,612,"PCN","Pitcairn Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2000/PRP/pcn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58933,612,"PCN","Pitcairn Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2000/PRP/pcn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58934,612,"PCN","Pitcairn Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2000/PRP/pcn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58935,612,"PCN","Pitcairn Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2012/PRP/pcn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58936,612,"PCN","Pitcairn Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2012/PRP/pcn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58937,612,"PCN","Pitcairn Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2012/PRP/pcn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58938,612,"PCN","Pitcairn Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2012/PRP/pcn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58939,612,"PCN","Pitcairn Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2014/PRP/pcn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58940,612,"PCN","Pitcairn Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2014/PRP/pcn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58941,612,"PCN","Pitcairn Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2014/PRP/pcn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58942,612,"PCN","Pitcairn Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PCN/BuiltSettlement/2014/PRP/pcn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58943,616,"POL","Poland","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2000/Binary/pol_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58944,616,"POL","Poland","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2000/DTE/pol_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58945,616,"POL","Poland","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2012/Binary/pol_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58946,616,"POL","Poland","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2012/DTE/pol_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58947,616,"POL","Poland","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2014/Binary/pol_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58948,616,"POL","Poland","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2014/DTE/pol_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58949,616,"POL","Poland","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2000/PRP/pol_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58950,616,"POL","Poland","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2000/PRP/pol_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58951,616,"POL","Poland","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2000/PRP/pol_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58952,616,"POL","Poland","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2000/PRP/pol_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58953,616,"POL","Poland","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2012/PRP/pol_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58954,616,"POL","Poland","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2012/PRP/pol_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58955,616,"POL","Poland","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2012/PRP/pol_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58956,616,"POL","Poland","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2012/PRP/pol_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58957,616,"POL","Poland","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2014/PRP/pol_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58958,616,"POL","Poland","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2014/PRP/pol_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58959,616,"POL","Poland","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2014/PRP/pol_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58960,616,"POL","Poland","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/POL/BuiltSettlement/2014/PRP/pol_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58961,620,"PRT","Portugal","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2000/Binary/prt_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58962,620,"PRT","Portugal","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2000/DTE/prt_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58963,620,"PRT","Portugal","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2012/Binary/prt_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58964,620,"PRT","Portugal","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2012/DTE/prt_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58965,620,"PRT","Portugal","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2014/Binary/prt_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58966,620,"PRT","Portugal","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2014/DTE/prt_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58967,620,"PRT","Portugal","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2000/PRP/prt_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58968,620,"PRT","Portugal","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2000/PRP/prt_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58969,620,"PRT","Portugal","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2000/PRP/prt_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58970,620,"PRT","Portugal","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2000/PRP/prt_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58971,620,"PRT","Portugal","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2012/PRP/prt_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58972,620,"PRT","Portugal","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2012/PRP/prt_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58973,620,"PRT","Portugal","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2012/PRP/prt_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58974,620,"PRT","Portugal","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2012/PRP/prt_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58975,620,"PRT","Portugal","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2014/PRP/prt_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58976,620,"PRT","Portugal","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2014/PRP/prt_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58977,620,"PRT","Portugal","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2014/PRP/prt_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58978,620,"PRT","Portugal","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PRT/BuiltSettlement/2014/PRP/prt_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58979,624,"GNB","Guinea-Bissau","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2000/Binary/gnb_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58980,624,"GNB","Guinea-Bissau","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2000/DTE/gnb_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58981,624,"GNB","Guinea-Bissau","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2012/Binary/gnb_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
58982,624,"GNB","Guinea-Bissau","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2012/DTE/gnb_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
58983,624,"GNB","Guinea-Bissau","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2014/Binary/gnb_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
58984,624,"GNB","Guinea-Bissau","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2014/DTE/gnb_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
58985,624,"GNB","Guinea-Bissau","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2000/PRP/gnb_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
58986,624,"GNB","Guinea-Bissau","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2000/PRP/gnb_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
58987,624,"GNB","Guinea-Bissau","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2000/PRP/gnb_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
58988,624,"GNB","Guinea-Bissau","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2000/PRP/gnb_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
58989,624,"GNB","Guinea-Bissau","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2012/PRP/gnb_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
58990,624,"GNB","Guinea-Bissau","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2012/PRP/gnb_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
58991,624,"GNB","Guinea-Bissau","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2012/PRP/gnb_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
58992,624,"GNB","Guinea-Bissau","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2012/PRP/gnb_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
58993,624,"GNB","Guinea-Bissau","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2014/PRP/gnb_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
58994,624,"GNB","Guinea-Bissau","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2014/PRP/gnb_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
58995,624,"GNB","Guinea-Bissau","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2014/PRP/gnb_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
58996,624,"GNB","Guinea-Bissau","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GNB/BuiltSettlement/2014/PRP/gnb_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
58997,626,"TLS","East Timor","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2000/Binary/tls_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
58998,626,"TLS","East Timor","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2000/DTE/tls_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
58999,626,"TLS","East Timor","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2012/Binary/tls_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59000,626,"TLS","East Timor","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2012/DTE/tls_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59001,626,"TLS","East Timor","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2014/Binary/tls_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59002,626,"TLS","East Timor","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2014/DTE/tls_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59003,626,"TLS","East Timor","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2000/PRP/tls_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59004,626,"TLS","East Timor","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2000/PRP/tls_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59005,626,"TLS","East Timor","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2000/PRP/tls_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59006,626,"TLS","East Timor","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2000/PRP/tls_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59007,626,"TLS","East Timor","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2012/PRP/tls_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59008,626,"TLS","East Timor","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2012/PRP/tls_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59009,626,"TLS","East Timor","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2012/PRP/tls_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59010,626,"TLS","East Timor","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2012/PRP/tls_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59011,626,"TLS","East Timor","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2014/PRP/tls_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59012,626,"TLS","East Timor","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2014/PRP/tls_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59013,626,"TLS","East Timor","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2014/PRP/tls_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59014,626,"TLS","East Timor","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TLS/BuiltSettlement/2014/PRP/tls_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59015,630,"PRI","Puerto Rico","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2000/Binary/pri_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59016,630,"PRI","Puerto Rico","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2000/DTE/pri_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59017,630,"PRI","Puerto Rico","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2012/Binary/pri_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59018,630,"PRI","Puerto Rico","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2012/DTE/pri_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59019,630,"PRI","Puerto Rico","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2014/Binary/pri_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59020,630,"PRI","Puerto Rico","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2014/DTE/pri_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59021,630,"PRI","Puerto Rico","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2000/PRP/pri_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59022,630,"PRI","Puerto Rico","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2000/PRP/pri_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59023,630,"PRI","Puerto Rico","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2000/PRP/pri_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59024,630,"PRI","Puerto Rico","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2000/PRP/pri_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59025,630,"PRI","Puerto Rico","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2012/PRP/pri_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59026,630,"PRI","Puerto Rico","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2012/PRP/pri_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59027,630,"PRI","Puerto Rico","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2012/PRP/pri_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59028,630,"PRI","Puerto Rico","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2012/PRP/pri_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59029,630,"PRI","Puerto Rico","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2014/PRP/pri_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59030,630,"PRI","Puerto Rico","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2014/PRP/pri_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59031,630,"PRI","Puerto Rico","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2014/PRP/pri_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59032,630,"PRI","Puerto Rico","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/PRI/BuiltSettlement/2014/PRP/pri_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59033,634,"QAT","Qatar","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2000/Binary/qat_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59034,634,"QAT","Qatar","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2000/DTE/qat_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59035,634,"QAT","Qatar","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2012/Binary/qat_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59036,634,"QAT","Qatar","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2012/DTE/qat_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59037,634,"QAT","Qatar","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2014/Binary/qat_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59038,634,"QAT","Qatar","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2014/DTE/qat_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59039,634,"QAT","Qatar","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2000/PRP/qat_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59040,634,"QAT","Qatar","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2000/PRP/qat_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59041,634,"QAT","Qatar","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2000/PRP/qat_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59042,634,"QAT","Qatar","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2000/PRP/qat_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59043,634,"QAT","Qatar","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2012/PRP/qat_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59044,634,"QAT","Qatar","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2012/PRP/qat_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59045,634,"QAT","Qatar","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2012/PRP/qat_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59046,634,"QAT","Qatar","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2012/PRP/qat_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59047,634,"QAT","Qatar","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2014/PRP/qat_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59048,634,"QAT","Qatar","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2014/PRP/qat_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59049,634,"QAT","Qatar","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2014/PRP/qat_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59050,634,"QAT","Qatar","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/QAT/BuiltSettlement/2014/PRP/qat_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59051,638,"REU","Reunion","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2000/Binary/reu_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59052,638,"REU","Reunion","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2000/DTE/reu_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59053,638,"REU","Reunion","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2012/Binary/reu_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59054,638,"REU","Reunion","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2012/DTE/reu_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59055,638,"REU","Reunion","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2014/Binary/reu_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59056,638,"REU","Reunion","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2014/DTE/reu_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59057,638,"REU","Reunion","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2000/PRP/reu_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59058,638,"REU","Reunion","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2000/PRP/reu_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59059,638,"REU","Reunion","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2000/PRP/reu_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59060,638,"REU","Reunion","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2000/PRP/reu_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59061,638,"REU","Reunion","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2012/PRP/reu_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59062,638,"REU","Reunion","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2012/PRP/reu_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59063,638,"REU","Reunion","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2012/PRP/reu_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59064,638,"REU","Reunion","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2012/PRP/reu_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59065,638,"REU","Reunion","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2014/PRP/reu_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59066,638,"REU","Reunion","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2014/PRP/reu_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59067,638,"REU","Reunion","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2014/PRP/reu_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59068,638,"REU","Reunion","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/REU/BuiltSettlement/2014/PRP/reu_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59069,642,"ROU","Romania","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2000/Binary/rou_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59070,642,"ROU","Romania","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2000/DTE/rou_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59071,642,"ROU","Romania","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2012/Binary/rou_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59072,642,"ROU","Romania","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2012/DTE/rou_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59073,642,"ROU","Romania","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2014/Binary/rou_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59074,642,"ROU","Romania","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2014/DTE/rou_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59075,642,"ROU","Romania","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2000/PRP/rou_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59076,642,"ROU","Romania","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2000/PRP/rou_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59077,642,"ROU","Romania","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2000/PRP/rou_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59078,642,"ROU","Romania","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2000/PRP/rou_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59079,642,"ROU","Romania","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2012/PRP/rou_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59080,642,"ROU","Romania","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2012/PRP/rou_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59081,642,"ROU","Romania","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2012/PRP/rou_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59082,642,"ROU","Romania","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2012/PRP/rou_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59083,642,"ROU","Romania","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2014/PRP/rou_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59084,642,"ROU","Romania","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2014/PRP/rou_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59085,642,"ROU","Romania","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2014/PRP/rou_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59086,642,"ROU","Romania","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ROU/BuiltSettlement/2014/PRP/rou_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59087,646,"RWA","Rwanda","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2000/Binary/rwa_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59088,646,"RWA","Rwanda","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2000/DTE/rwa_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59089,646,"RWA","Rwanda","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2012/Binary/rwa_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59090,646,"RWA","Rwanda","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2012/DTE/rwa_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59091,646,"RWA","Rwanda","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2014/Binary/rwa_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59092,646,"RWA","Rwanda","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2014/DTE/rwa_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59093,646,"RWA","Rwanda","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2000/PRP/rwa_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59094,646,"RWA","Rwanda","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2000/PRP/rwa_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59095,646,"RWA","Rwanda","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2000/PRP/rwa_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59096,646,"RWA","Rwanda","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2000/PRP/rwa_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59097,646,"RWA","Rwanda","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2012/PRP/rwa_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59098,646,"RWA","Rwanda","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2012/PRP/rwa_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59099,646,"RWA","Rwanda","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2012/PRP/rwa_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59100,646,"RWA","Rwanda","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2012/PRP/rwa_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59101,646,"RWA","Rwanda","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2014/PRP/rwa_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59102,646,"RWA","Rwanda","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2014/PRP/rwa_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59103,646,"RWA","Rwanda","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2014/PRP/rwa_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59104,646,"RWA","Rwanda","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/RWA/BuiltSettlement/2014/PRP/rwa_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59105,652,"BLM","Saint Barthelemy","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2000/Binary/blm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59106,652,"BLM","Saint Barthelemy","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2000/DTE/blm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59107,652,"BLM","Saint Barthelemy","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2012/Binary/blm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59108,652,"BLM","Saint Barthelemy","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2012/DTE/blm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59109,652,"BLM","Saint Barthelemy","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2014/Binary/blm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59110,652,"BLM","Saint Barthelemy","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2014/DTE/blm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59111,652,"BLM","Saint Barthelemy","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2000/PRP/blm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59112,652,"BLM","Saint Barthelemy","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2000/PRP/blm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59113,652,"BLM","Saint Barthelemy","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2000/PRP/blm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59114,652,"BLM","Saint Barthelemy","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2000/PRP/blm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59115,652,"BLM","Saint Barthelemy","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2012/PRP/blm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59116,652,"BLM","Saint Barthelemy","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2012/PRP/blm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59117,652,"BLM","Saint Barthelemy","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2012/PRP/blm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59118,652,"BLM","Saint Barthelemy","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2012/PRP/blm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59119,652,"BLM","Saint Barthelemy","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2014/PRP/blm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59120,652,"BLM","Saint Barthelemy","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2014/PRP/blm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59121,652,"BLM","Saint Barthelemy","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2014/PRP/blm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59122,652,"BLM","Saint Barthelemy","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BLM/BuiltSettlement/2014/PRP/blm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59123,654,"SHN","Saint Helena","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2000/Binary/shn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59124,654,"SHN","Saint Helena","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2000/DTE/shn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59125,654,"SHN","Saint Helena","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2012/Binary/shn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59126,654,"SHN","Saint Helena","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2012/DTE/shn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59127,654,"SHN","Saint Helena","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2014/Binary/shn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59128,654,"SHN","Saint Helena","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2014/DTE/shn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59129,654,"SHN","Saint Helena","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2000/PRP/shn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59130,654,"SHN","Saint Helena","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2000/PRP/shn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59131,654,"SHN","Saint Helena","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2000/PRP/shn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59132,654,"SHN","Saint Helena","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2000/PRP/shn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59133,654,"SHN","Saint Helena","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2012/PRP/shn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59134,654,"SHN","Saint Helena","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2012/PRP/shn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59135,654,"SHN","Saint Helena","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2012/PRP/shn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59136,654,"SHN","Saint Helena","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2012/PRP/shn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59137,654,"SHN","Saint Helena","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2014/PRP/shn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59138,654,"SHN","Saint Helena","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2014/PRP/shn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59139,654,"SHN","Saint Helena","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2014/PRP/shn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59140,654,"SHN","Saint Helena","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SHN/BuiltSettlement/2014/PRP/shn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59141,659,"KNA","Saint Kitts and Nevis","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2000/Binary/kna_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59142,659,"KNA","Saint Kitts and Nevis","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2000/DTE/kna_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59143,659,"KNA","Saint Kitts and Nevis","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2012/Binary/kna_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59144,659,"KNA","Saint Kitts and Nevis","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2012/DTE/kna_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59145,659,"KNA","Saint Kitts and Nevis","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2014/Binary/kna_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59146,659,"KNA","Saint Kitts and Nevis","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2014/DTE/kna_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59147,659,"KNA","Saint Kitts and Nevis","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2000/PRP/kna_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59148,659,"KNA","Saint Kitts and Nevis","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2000/PRP/kna_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59149,659,"KNA","Saint Kitts and Nevis","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2000/PRP/kna_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59150,659,"KNA","Saint Kitts and Nevis","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2000/PRP/kna_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59151,659,"KNA","Saint Kitts and Nevis","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2012/PRP/kna_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59152,659,"KNA","Saint Kitts and Nevis","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2012/PRP/kna_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59153,659,"KNA","Saint Kitts and Nevis","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2012/PRP/kna_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59154,659,"KNA","Saint Kitts and Nevis","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2012/PRP/kna_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59155,659,"KNA","Saint Kitts and Nevis","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2014/PRP/kna_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59156,659,"KNA","Saint Kitts and Nevis","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2014/PRP/kna_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59157,659,"KNA","Saint Kitts and Nevis","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2014/PRP/kna_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59158,659,"KNA","Saint Kitts and Nevis","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/KNA/BuiltSettlement/2014/PRP/kna_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59159,660,"AIA","Anguilla","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2000/Binary/aia_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59160,660,"AIA","Anguilla","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2000/DTE/aia_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59161,660,"AIA","Anguilla","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2012/Binary/aia_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59162,660,"AIA","Anguilla","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2012/DTE/aia_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59163,660,"AIA","Anguilla","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2014/Binary/aia_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59164,660,"AIA","Anguilla","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2014/DTE/aia_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59165,660,"AIA","Anguilla","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2000/PRP/aia_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59166,660,"AIA","Anguilla","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2000/PRP/aia_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59167,660,"AIA","Anguilla","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2000/PRP/aia_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59168,660,"AIA","Anguilla","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2000/PRP/aia_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59169,660,"AIA","Anguilla","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2012/PRP/aia_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59170,660,"AIA","Anguilla","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2012/PRP/aia_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59171,660,"AIA","Anguilla","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2012/PRP/aia_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59172,660,"AIA","Anguilla","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2012/PRP/aia_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59173,660,"AIA","Anguilla","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2014/PRP/aia_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59174,660,"AIA","Anguilla","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2014/PRP/aia_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59175,660,"AIA","Anguilla","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2014/PRP/aia_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59176,660,"AIA","Anguilla","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/AIA/BuiltSettlement/2014/PRP/aia_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59177,662,"LCA","Saint Lucia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2000/Binary/lca_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59178,662,"LCA","Saint Lucia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2000/DTE/lca_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59179,662,"LCA","Saint Lucia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2012/Binary/lca_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59180,662,"LCA","Saint Lucia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2012/DTE/lca_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59181,662,"LCA","Saint Lucia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2014/Binary/lca_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59182,662,"LCA","Saint Lucia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2014/DTE/lca_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59183,662,"LCA","Saint Lucia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2000/PRP/lca_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59184,662,"LCA","Saint Lucia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2000/PRP/lca_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59185,662,"LCA","Saint Lucia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2000/PRP/lca_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59186,662,"LCA","Saint Lucia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2000/PRP/lca_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59187,662,"LCA","Saint Lucia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2012/PRP/lca_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59188,662,"LCA","Saint Lucia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2012/PRP/lca_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59189,662,"LCA","Saint Lucia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2012/PRP/lca_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59190,662,"LCA","Saint Lucia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2012/PRP/lca_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59191,662,"LCA","Saint Lucia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2014/PRP/lca_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59192,662,"LCA","Saint Lucia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2014/PRP/lca_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59193,662,"LCA","Saint Lucia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2014/PRP/lca_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59194,662,"LCA","Saint Lucia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/LCA/BuiltSettlement/2014/PRP/lca_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59195,663,"MAF","Saint Martin (French part)","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2000/Binary/maf_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59196,663,"MAF","Saint Martin (French part)","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2000/DTE/maf_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59197,663,"MAF","Saint Martin (French part)","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2012/Binary/maf_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59198,663,"MAF","Saint Martin (French part)","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2012/DTE/maf_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59199,663,"MAF","Saint Martin (French part)","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2014/Binary/maf_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59200,663,"MAF","Saint Martin (French part)","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2014/DTE/maf_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59201,663,"MAF","Saint Martin (French part)","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2000/PRP/maf_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59202,663,"MAF","Saint Martin (French part)","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2000/PRP/maf_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59203,663,"MAF","Saint Martin (French part)","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2000/PRP/maf_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59204,663,"MAF","Saint Martin (French part)","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2000/PRP/maf_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59205,663,"MAF","Saint Martin (French part)","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2012/PRP/maf_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59206,663,"MAF","Saint Martin (French part)","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2012/PRP/maf_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59207,663,"MAF","Saint Martin (French part)","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2012/PRP/maf_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59208,663,"MAF","Saint Martin (French part)","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2012/PRP/maf_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59209,663,"MAF","Saint Martin (French part)","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2014/PRP/maf_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59210,663,"MAF","Saint Martin (French part)","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2014/PRP/maf_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59211,663,"MAF","Saint Martin (French part)","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2014/PRP/maf_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59212,663,"MAF","Saint Martin (French part)","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MAF/BuiltSettlement/2014/PRP/maf_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59213,666,"SPM","Saint Pierre and Miquelon","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2000/Binary/spm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59214,666,"SPM","Saint Pierre and Miquelon","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2000/DTE/spm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59215,666,"SPM","Saint Pierre and Miquelon","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2012/Binary/spm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59216,666,"SPM","Saint Pierre and Miquelon","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2012/DTE/spm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59217,666,"SPM","Saint Pierre and Miquelon","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2014/Binary/spm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59218,666,"SPM","Saint Pierre and Miquelon","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2014/DTE/spm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59219,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2000/PRP/spm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59220,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2000/PRP/spm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59221,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2000/PRP/spm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59222,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2000/PRP/spm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59223,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2012/PRP/spm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59224,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2012/PRP/spm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59225,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2012/PRP/spm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59226,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2012/PRP/spm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59227,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2014/PRP/spm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59228,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2014/PRP/spm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59229,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2014/PRP/spm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59230,666,"SPM","Saint Pierre and Miquelon","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SPM/BuiltSettlement/2014/PRP/spm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59231,670,"VCT","Saint Vincent and the Grenadines","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2000/Binary/vct_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59232,670,"VCT","Saint Vincent and the Grenadines","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2000/DTE/vct_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59233,670,"VCT","Saint Vincent and the Grenadines","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2012/Binary/vct_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59234,670,"VCT","Saint Vincent and the Grenadines","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2012/DTE/vct_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59235,670,"VCT","Saint Vincent and the Grenadines","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2014/Binary/vct_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59236,670,"VCT","Saint Vincent and the Grenadines","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2014/DTE/vct_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59237,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2000/PRP/vct_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59238,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2000/PRP/vct_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59239,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2000/PRP/vct_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59240,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2000/PRP/vct_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59241,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2012/PRP/vct_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59242,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2012/PRP/vct_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59243,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2012/PRP/vct_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59244,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2012/PRP/vct_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59245,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2014/PRP/vct_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59246,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2014/PRP/vct_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59247,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2014/PRP/vct_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59248,670,"VCT","Saint Vincent and the Grenadines","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/VCT/BuiltSettlement/2014/PRP/vct_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59249,674,"SMR","San Marino","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2000/Binary/smr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59250,674,"SMR","San Marino","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2000/DTE/smr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59251,674,"SMR","San Marino","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2012/Binary/smr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59252,674,"SMR","San Marino","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2012/DTE/smr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59253,674,"SMR","San Marino","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2014/Binary/smr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59254,674,"SMR","San Marino","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2014/DTE/smr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59255,674,"SMR","San Marino","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2000/PRP/smr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59256,674,"SMR","San Marino","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2000/PRP/smr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59257,674,"SMR","San Marino","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2000/PRP/smr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59258,674,"SMR","San Marino","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2000/PRP/smr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59259,674,"SMR","San Marino","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2012/PRP/smr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59260,674,"SMR","San Marino","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2012/PRP/smr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59261,674,"SMR","San Marino","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2012/PRP/smr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59262,674,"SMR","San Marino","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2012/PRP/smr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59263,674,"SMR","San Marino","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2014/PRP/smr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59264,674,"SMR","San Marino","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2014/PRP/smr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59265,674,"SMR","San Marino","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2014/PRP/smr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59266,674,"SMR","San Marino","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SMR/BuiltSettlement/2014/PRP/smr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59267,678,"STP","Sao Tome and Principe","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2000/Binary/stp_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59268,678,"STP","Sao Tome and Principe","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2000/DTE/stp_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59269,678,"STP","Sao Tome and Principe","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2012/Binary/stp_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59270,678,"STP","Sao Tome and Principe","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2012/DTE/stp_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59271,678,"STP","Sao Tome and Principe","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2014/Binary/stp_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59272,678,"STP","Sao Tome and Principe","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2014/DTE/stp_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59273,678,"STP","Sao Tome and Principe","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2000/PRP/stp_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59274,678,"STP","Sao Tome and Principe","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2000/PRP/stp_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59275,678,"STP","Sao Tome and Principe","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2000/PRP/stp_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59276,678,"STP","Sao Tome and Principe","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2000/PRP/stp_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59277,678,"STP","Sao Tome and Principe","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2012/PRP/stp_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59278,678,"STP","Sao Tome and Principe","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2012/PRP/stp_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59279,678,"STP","Sao Tome and Principe","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2012/PRP/stp_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59280,678,"STP","Sao Tome and Principe","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2012/PRP/stp_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59281,678,"STP","Sao Tome and Principe","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2014/PRP/stp_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59282,678,"STP","Sao Tome and Principe","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2014/PRP/stp_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59283,678,"STP","Sao Tome and Principe","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2014/PRP/stp_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59284,678,"STP","Sao Tome and Principe","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/STP/BuiltSettlement/2014/PRP/stp_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59285,682,"SAU","Saudi Arabia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2000/Binary/sau_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59286,682,"SAU","Saudi Arabia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2000/DTE/sau_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59287,682,"SAU","Saudi Arabia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2012/Binary/sau_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59288,682,"SAU","Saudi Arabia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2012/DTE/sau_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59289,682,"SAU","Saudi Arabia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2014/Binary/sau_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59290,682,"SAU","Saudi Arabia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2014/DTE/sau_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59291,682,"SAU","Saudi Arabia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2000/PRP/sau_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59292,682,"SAU","Saudi Arabia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2000/PRP/sau_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59293,682,"SAU","Saudi Arabia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2000/PRP/sau_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59294,682,"SAU","Saudi Arabia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2000/PRP/sau_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59295,682,"SAU","Saudi Arabia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2012/PRP/sau_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59296,682,"SAU","Saudi Arabia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2012/PRP/sau_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59297,682,"SAU","Saudi Arabia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2012/PRP/sau_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59298,682,"SAU","Saudi Arabia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2012/PRP/sau_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59299,682,"SAU","Saudi Arabia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2014/PRP/sau_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59300,682,"SAU","Saudi Arabia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2014/PRP/sau_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59301,682,"SAU","Saudi Arabia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2014/PRP/sau_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59302,682,"SAU","Saudi Arabia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SAU/BuiltSettlement/2014/PRP/sau_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59303,686,"SEN","Senegal","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2000/Binary/sen_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59304,686,"SEN","Senegal","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2000/DTE/sen_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59305,686,"SEN","Senegal","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2012/Binary/sen_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59306,686,"SEN","Senegal","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2012/DTE/sen_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59307,686,"SEN","Senegal","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2014/Binary/sen_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59308,686,"SEN","Senegal","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2014/DTE/sen_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59309,686,"SEN","Senegal","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2000/PRP/sen_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59310,686,"SEN","Senegal","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2000/PRP/sen_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59311,686,"SEN","Senegal","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2000/PRP/sen_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59312,686,"SEN","Senegal","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2000/PRP/sen_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59313,686,"SEN","Senegal","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2012/PRP/sen_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59314,686,"SEN","Senegal","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2012/PRP/sen_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59315,686,"SEN","Senegal","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2012/PRP/sen_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59316,686,"SEN","Senegal","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2012/PRP/sen_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59317,686,"SEN","Senegal","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2014/PRP/sen_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59318,686,"SEN","Senegal","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2014/PRP/sen_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59319,686,"SEN","Senegal","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2014/PRP/sen_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59320,686,"SEN","Senegal","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SEN/BuiltSettlement/2014/PRP/sen_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59321,688,"SRB","Serbia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2000/Binary/srb_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59322,688,"SRB","Serbia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2000/DTE/srb_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59323,688,"SRB","Serbia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2012/Binary/srb_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59324,688,"SRB","Serbia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2012/DTE/srb_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59325,688,"SRB","Serbia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2014/Binary/srb_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59326,688,"SRB","Serbia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2014/DTE/srb_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59327,688,"SRB","Serbia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2000/PRP/srb_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59328,688,"SRB","Serbia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2000/PRP/srb_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59329,688,"SRB","Serbia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2000/PRP/srb_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59330,688,"SRB","Serbia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2000/PRP/srb_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59331,688,"SRB","Serbia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2012/PRP/srb_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59332,688,"SRB","Serbia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2012/PRP/srb_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59333,688,"SRB","Serbia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2012/PRP/srb_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59334,688,"SRB","Serbia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2012/PRP/srb_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59335,688,"SRB","Serbia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2014/PRP/srb_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59336,688,"SRB","Serbia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2014/PRP/srb_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59337,688,"SRB","Serbia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2014/PRP/srb_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59338,688,"SRB","Serbia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SRB/BuiltSettlement/2014/PRP/srb_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59339,690,"SYC","Seychelles","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2000/Binary/syc_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59340,690,"SYC","Seychelles","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2000/DTE/syc_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59341,690,"SYC","Seychelles","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2012/Binary/syc_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59342,690,"SYC","Seychelles","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2012/DTE/syc_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59343,690,"SYC","Seychelles","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2014/Binary/syc_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59344,690,"SYC","Seychelles","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2014/DTE/syc_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59345,690,"SYC","Seychelles","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2000/PRP/syc_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59346,690,"SYC","Seychelles","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2000/PRP/syc_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59347,690,"SYC","Seychelles","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2000/PRP/syc_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59348,690,"SYC","Seychelles","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2000/PRP/syc_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59349,690,"SYC","Seychelles","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2012/PRP/syc_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59350,690,"SYC","Seychelles","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2012/PRP/syc_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59351,690,"SYC","Seychelles","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2012/PRP/syc_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59352,690,"SYC","Seychelles","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2012/PRP/syc_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59353,690,"SYC","Seychelles","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2014/PRP/syc_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59354,690,"SYC","Seychelles","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2014/PRP/syc_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59355,690,"SYC","Seychelles","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2014/PRP/syc_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59356,690,"SYC","Seychelles","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SYC/BuiltSettlement/2014/PRP/syc_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59357,694,"SLE","Sierra Leone","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2000/Binary/sle_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59358,694,"SLE","Sierra Leone","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2000/DTE/sle_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59359,694,"SLE","Sierra Leone","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2012/Binary/sle_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59360,694,"SLE","Sierra Leone","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2012/DTE/sle_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59361,694,"SLE","Sierra Leone","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2014/Binary/sle_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59362,694,"SLE","Sierra Leone","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2014/DTE/sle_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59363,694,"SLE","Sierra Leone","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2000/PRP/sle_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59364,694,"SLE","Sierra Leone","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2000/PRP/sle_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59365,694,"SLE","Sierra Leone","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2000/PRP/sle_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59366,694,"SLE","Sierra Leone","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2000/PRP/sle_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59367,694,"SLE","Sierra Leone","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2012/PRP/sle_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59368,694,"SLE","Sierra Leone","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2012/PRP/sle_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59369,694,"SLE","Sierra Leone","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2012/PRP/sle_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59370,694,"SLE","Sierra Leone","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2012/PRP/sle_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59371,694,"SLE","Sierra Leone","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2014/PRP/sle_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59372,694,"SLE","Sierra Leone","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2014/PRP/sle_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59373,694,"SLE","Sierra Leone","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2014/PRP/sle_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59374,694,"SLE","Sierra Leone","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SLE/BuiltSettlement/2014/PRP/sle_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59375,702,"SGP","Singapore","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2000/Binary/sgp_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59376,702,"SGP","Singapore","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2000/DTE/sgp_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59377,702,"SGP","Singapore","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2012/Binary/sgp_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59378,702,"SGP","Singapore","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2012/DTE/sgp_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59379,702,"SGP","Singapore","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2014/Binary/sgp_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59380,702,"SGP","Singapore","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2014/DTE/sgp_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59381,702,"SGP","Singapore","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2000/PRP/sgp_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59382,702,"SGP","Singapore","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2000/PRP/sgp_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59383,702,"SGP","Singapore","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2000/PRP/sgp_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59384,702,"SGP","Singapore","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2000/PRP/sgp_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59385,702,"SGP","Singapore","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2012/PRP/sgp_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59386,702,"SGP","Singapore","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2012/PRP/sgp_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59387,702,"SGP","Singapore","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2012/PRP/sgp_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59388,702,"SGP","Singapore","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2012/PRP/sgp_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59389,702,"SGP","Singapore","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2014/PRP/sgp_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59390,702,"SGP","Singapore","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2014/PRP/sgp_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59391,702,"SGP","Singapore","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2014/PRP/sgp_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59392,702,"SGP","Singapore","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SGP/BuiltSettlement/2014/PRP/sgp_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59393,703,"SVK","Slovakia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2000/Binary/svk_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59394,703,"SVK","Slovakia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2000/DTE/svk_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59395,703,"SVK","Slovakia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2012/Binary/svk_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59396,703,"SVK","Slovakia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2012/DTE/svk_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59397,703,"SVK","Slovakia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2014/Binary/svk_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59398,703,"SVK","Slovakia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2014/DTE/svk_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59399,703,"SVK","Slovakia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2000/PRP/svk_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59400,703,"SVK","Slovakia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2000/PRP/svk_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59401,703,"SVK","Slovakia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2000/PRP/svk_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59402,703,"SVK","Slovakia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2000/PRP/svk_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59403,703,"SVK","Slovakia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2012/PRP/svk_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59404,703,"SVK","Slovakia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2012/PRP/svk_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59405,703,"SVK","Slovakia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2012/PRP/svk_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59406,703,"SVK","Slovakia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2012/PRP/svk_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59407,703,"SVK","Slovakia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2014/PRP/svk_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59408,703,"SVK","Slovakia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2014/PRP/svk_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59409,703,"SVK","Slovakia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2014/PRP/svk_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59410,703,"SVK","Slovakia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SVK/BuiltSettlement/2014/PRP/svk_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59411,704,"VNM","Vietnam","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2000/Binary/vnm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59412,704,"VNM","Vietnam","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2000/DTE/vnm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59413,704,"VNM","Vietnam","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2012/Binary/vnm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59414,704,"VNM","Vietnam","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2012/DTE/vnm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59415,704,"VNM","Vietnam","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2014/Binary/vnm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59416,704,"VNM","Vietnam","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2014/DTE/vnm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59417,704,"VNM","Vietnam","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2000/PRP/vnm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59418,704,"VNM","Vietnam","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2000/PRP/vnm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59419,704,"VNM","Vietnam","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2000/PRP/vnm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59420,704,"VNM","Vietnam","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2000/PRP/vnm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59421,704,"VNM","Vietnam","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2012/PRP/vnm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59422,704,"VNM","Vietnam","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2012/PRP/vnm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59423,704,"VNM","Vietnam","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2012/PRP/vnm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59424,704,"VNM","Vietnam","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2012/PRP/vnm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59425,704,"VNM","Vietnam","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2014/PRP/vnm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59426,704,"VNM","Vietnam","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2014/PRP/vnm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59427,704,"VNM","Vietnam","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2014/PRP/vnm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59428,704,"VNM","Vietnam","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/VNM/BuiltSettlement/2014/PRP/vnm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59429,705,"SVN","Slovenia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2000/Binary/svn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59430,705,"SVN","Slovenia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2000/DTE/svn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59431,705,"SVN","Slovenia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2012/Binary/svn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59432,705,"SVN","Slovenia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2012/DTE/svn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59433,705,"SVN","Slovenia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2014/Binary/svn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59434,705,"SVN","Slovenia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2014/DTE/svn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59435,705,"SVN","Slovenia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2000/PRP/svn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59436,705,"SVN","Slovenia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2000/PRP/svn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59437,705,"SVN","Slovenia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2000/PRP/svn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59438,705,"SVN","Slovenia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2000/PRP/svn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59439,705,"SVN","Slovenia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2012/PRP/svn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59440,705,"SVN","Slovenia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2012/PRP/svn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59441,705,"SVN","Slovenia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2012/PRP/svn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59442,705,"SVN","Slovenia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2012/PRP/svn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59443,705,"SVN","Slovenia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2014/PRP/svn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59444,705,"SVN","Slovenia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2014/PRP/svn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59445,705,"SVN","Slovenia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2014/PRP/svn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59446,705,"SVN","Slovenia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SVN/BuiltSettlement/2014/PRP/svn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59447,706,"SOM","Somalia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2000/Binary/som_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59448,706,"SOM","Somalia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2000/DTE/som_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59449,706,"SOM","Somalia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2012/Binary/som_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59450,706,"SOM","Somalia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2012/DTE/som_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59451,706,"SOM","Somalia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2014/Binary/som_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59452,706,"SOM","Somalia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2014/DTE/som_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59453,706,"SOM","Somalia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2000/PRP/som_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59454,706,"SOM","Somalia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2000/PRP/som_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59455,706,"SOM","Somalia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2000/PRP/som_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59456,706,"SOM","Somalia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2000/PRP/som_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59457,706,"SOM","Somalia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2012/PRP/som_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59458,706,"SOM","Somalia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2012/PRP/som_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59459,706,"SOM","Somalia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2012/PRP/som_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59460,706,"SOM","Somalia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2012/PRP/som_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59461,706,"SOM","Somalia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2014/PRP/som_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59462,706,"SOM","Somalia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2014/PRP/som_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59463,706,"SOM","Somalia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2014/PRP/som_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59464,706,"SOM","Somalia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SOM/BuiltSettlement/2014/PRP/som_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59465,710,"ZAF","South Africa","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2000/Binary/zaf_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59466,710,"ZAF","South Africa","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2000/DTE/zaf_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59467,710,"ZAF","South Africa","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2012/Binary/zaf_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59468,710,"ZAF","South Africa","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2012/DTE/zaf_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59469,710,"ZAF","South Africa","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2014/Binary/zaf_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59470,710,"ZAF","South Africa","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2014/DTE/zaf_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59471,710,"ZAF","South Africa","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2000/PRP/zaf_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59472,710,"ZAF","South Africa","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2000/PRP/zaf_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59473,710,"ZAF","South Africa","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2000/PRP/zaf_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59474,710,"ZAF","South Africa","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2000/PRP/zaf_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59475,710,"ZAF","South Africa","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2012/PRP/zaf_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59476,710,"ZAF","South Africa","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2012/PRP/zaf_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59477,710,"ZAF","South Africa","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2012/PRP/zaf_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59478,710,"ZAF","South Africa","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2012/PRP/zaf_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59479,710,"ZAF","South Africa","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2014/PRP/zaf_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59480,710,"ZAF","South Africa","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2014/PRP/zaf_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59481,710,"ZAF","South Africa","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2014/PRP/zaf_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59482,710,"ZAF","South Africa","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/BuiltSettlement/2014/PRP/zaf_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59483,716,"ZWE","Zimbabwe","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2000/Binary/zwe_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59484,716,"ZWE","Zimbabwe","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2000/DTE/zwe_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59485,716,"ZWE","Zimbabwe","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2012/Binary/zwe_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59486,716,"ZWE","Zimbabwe","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2012/DTE/zwe_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59487,716,"ZWE","Zimbabwe","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2014/Binary/zwe_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59488,716,"ZWE","Zimbabwe","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2014/DTE/zwe_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59489,716,"ZWE","Zimbabwe","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2000/PRP/zwe_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59490,716,"ZWE","Zimbabwe","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2000/PRP/zwe_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59491,716,"ZWE","Zimbabwe","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2000/PRP/zwe_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59492,716,"ZWE","Zimbabwe","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2000/PRP/zwe_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59493,716,"ZWE","Zimbabwe","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2012/PRP/zwe_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59494,716,"ZWE","Zimbabwe","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2012/PRP/zwe_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59495,716,"ZWE","Zimbabwe","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2012/PRP/zwe_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59496,716,"ZWE","Zimbabwe","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2012/PRP/zwe_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59497,716,"ZWE","Zimbabwe","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2014/PRP/zwe_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59498,716,"ZWE","Zimbabwe","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2014/PRP/zwe_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59499,716,"ZWE","Zimbabwe","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2014/PRP/zwe_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59500,716,"ZWE","Zimbabwe","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/BuiltSettlement/2014/PRP/zwe_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59501,724,"ESP","Spain","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2000/Binary/esp_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59502,724,"ESP","Spain","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2000/DTE/esp_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59503,724,"ESP","Spain","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2012/Binary/esp_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59504,724,"ESP","Spain","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2012/DTE/esp_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59505,724,"ESP","Spain","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2014/Binary/esp_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59506,724,"ESP","Spain","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2014/DTE/esp_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59507,724,"ESP","Spain","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2000/PRP/esp_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59508,724,"ESP","Spain","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2000/PRP/esp_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59509,724,"ESP","Spain","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2000/PRP/esp_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59510,724,"ESP","Spain","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2000/PRP/esp_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59511,724,"ESP","Spain","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2012/PRP/esp_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59512,724,"ESP","Spain","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2012/PRP/esp_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59513,724,"ESP","Spain","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2012/PRP/esp_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59514,724,"ESP","Spain","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2012/PRP/esp_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59515,724,"ESP","Spain","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2014/PRP/esp_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59516,724,"ESP","Spain","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2014/PRP/esp_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59517,724,"ESP","Spain","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2014/PRP/esp_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59518,724,"ESP","Spain","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ESP/BuiltSettlement/2014/PRP/esp_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59519,728,"SSD","South Sudan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2000/Binary/ssd_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59520,728,"SSD","South Sudan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2000/DTE/ssd_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59521,728,"SSD","South Sudan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2012/Binary/ssd_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59522,728,"SSD","South Sudan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2012/DTE/ssd_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59523,728,"SSD","South Sudan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2014/Binary/ssd_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59524,728,"SSD","South Sudan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2014/DTE/ssd_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59525,728,"SSD","South Sudan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2000/PRP/ssd_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59526,728,"SSD","South Sudan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2000/PRP/ssd_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59527,728,"SSD","South Sudan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2000/PRP/ssd_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59528,728,"SSD","South Sudan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2000/PRP/ssd_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59529,728,"SSD","South Sudan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2012/PRP/ssd_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59530,728,"SSD","South Sudan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2012/PRP/ssd_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59531,728,"SSD","South Sudan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2012/PRP/ssd_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59532,728,"SSD","South Sudan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2012/PRP/ssd_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59533,728,"SSD","South Sudan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2014/PRP/ssd_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59534,728,"SSD","South Sudan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2014/PRP/ssd_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59535,728,"SSD","South Sudan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2014/PRP/ssd_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59536,728,"SSD","South Sudan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SSD/BuiltSettlement/2014/PRP/ssd_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59537,729,"SDN","Sudan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2000/Binary/sdn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59538,729,"SDN","Sudan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2000/DTE/sdn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59539,729,"SDN","Sudan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2012/Binary/sdn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59540,729,"SDN","Sudan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2012/DTE/sdn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59541,729,"SDN","Sudan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2014/Binary/sdn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59542,729,"SDN","Sudan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2014/DTE/sdn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59543,729,"SDN","Sudan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2000/PRP/sdn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59544,729,"SDN","Sudan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2000/PRP/sdn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59545,729,"SDN","Sudan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2000/PRP/sdn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59546,729,"SDN","Sudan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2000/PRP/sdn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59547,729,"SDN","Sudan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2012/PRP/sdn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59548,729,"SDN","Sudan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2012/PRP/sdn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59549,729,"SDN","Sudan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2012/PRP/sdn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59550,729,"SDN","Sudan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2012/PRP/sdn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59551,729,"SDN","Sudan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2014/PRP/sdn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59552,729,"SDN","Sudan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2014/PRP/sdn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59553,729,"SDN","Sudan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2014/PRP/sdn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59554,729,"SDN","Sudan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SDN/BuiltSettlement/2014/PRP/sdn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59555,732,"ESH","Western Sahara","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2000/Binary/esh_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59556,732,"ESH","Western Sahara","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2000/DTE/esh_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59557,732,"ESH","Western Sahara","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2012/Binary/esh_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59558,732,"ESH","Western Sahara","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2012/DTE/esh_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59559,732,"ESH","Western Sahara","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2014/Binary/esh_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59560,732,"ESH","Western Sahara","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2014/DTE/esh_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59561,732,"ESH","Western Sahara","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2000/PRP/esh_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59562,732,"ESH","Western Sahara","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2000/PRP/esh_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59563,732,"ESH","Western Sahara","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2000/PRP/esh_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59564,732,"ESH","Western Sahara","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2000/PRP/esh_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59565,732,"ESH","Western Sahara","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2012/PRP/esh_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59566,732,"ESH","Western Sahara","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2012/PRP/esh_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59567,732,"ESH","Western Sahara","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2012/PRP/esh_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59568,732,"ESH","Western Sahara","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2012/PRP/esh_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59569,732,"ESH","Western Sahara","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2014/PRP/esh_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59570,732,"ESH","Western Sahara","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2014/PRP/esh_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59571,732,"ESH","Western Sahara","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2014/PRP/esh_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59572,732,"ESH","Western Sahara","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ESH/BuiltSettlement/2014/PRP/esh_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59573,740,"SUR","Suriname","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2000/Binary/sur_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59574,740,"SUR","Suriname","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2000/DTE/sur_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59575,740,"SUR","Suriname","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2012/Binary/sur_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59576,740,"SUR","Suriname","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2012/DTE/sur_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59577,740,"SUR","Suriname","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2014/Binary/sur_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59578,740,"SUR","Suriname","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2014/DTE/sur_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59579,740,"SUR","Suriname","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2000/PRP/sur_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59580,740,"SUR","Suriname","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2000/PRP/sur_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59581,740,"SUR","Suriname","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2000/PRP/sur_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59582,740,"SUR","Suriname","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2000/PRP/sur_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59583,740,"SUR","Suriname","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2012/PRP/sur_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59584,740,"SUR","Suriname","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2012/PRP/sur_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59585,740,"SUR","Suriname","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2012/PRP/sur_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59586,740,"SUR","Suriname","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2012/PRP/sur_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59587,740,"SUR","Suriname","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2014/PRP/sur_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59588,740,"SUR","Suriname","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2014/PRP/sur_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59589,740,"SUR","Suriname","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2014/PRP/sur_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59590,740,"SUR","Suriname","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SUR/BuiltSettlement/2014/PRP/sur_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59591,744,"SJM","Svalbard and Jan Mayen Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2000/Binary/sjm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59592,744,"SJM","Svalbard and Jan Mayen Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2000/DTE/sjm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59593,744,"SJM","Svalbard and Jan Mayen Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2012/Binary/sjm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59594,744,"SJM","Svalbard and Jan Mayen Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2012/DTE/sjm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59595,744,"SJM","Svalbard and Jan Mayen Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2014/Binary/sjm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59596,744,"SJM","Svalbard and Jan Mayen Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2014/DTE/sjm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59597,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2000/PRP/sjm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59598,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2000/PRP/sjm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59599,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2000/PRP/sjm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59600,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2000/PRP/sjm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59601,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2012/PRP/sjm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59602,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2012/PRP/sjm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59603,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2012/PRP/sjm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59604,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2012/PRP/sjm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59605,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2014/PRP/sjm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59606,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2014/PRP/sjm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59607,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2014/PRP/sjm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59608,744,"SJM","Svalbard and Jan Mayen Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SJM/BuiltSettlement/2014/PRP/sjm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59609,748,"SWZ","Swaziland","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2000/Binary/swz_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59610,748,"SWZ","Swaziland","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2000/DTE/swz_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59611,748,"SWZ","Swaziland","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2012/Binary/swz_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59612,748,"SWZ","Swaziland","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2012/DTE/swz_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59613,748,"SWZ","Swaziland","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2014/Binary/swz_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59614,748,"SWZ","Swaziland","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2014/DTE/swz_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59615,748,"SWZ","Swaziland","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2000/PRP/swz_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59616,748,"SWZ","Swaziland","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2000/PRP/swz_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59617,748,"SWZ","Swaziland","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2000/PRP/swz_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59618,748,"SWZ","Swaziland","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2000/PRP/swz_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59619,748,"SWZ","Swaziland","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2012/PRP/swz_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59620,748,"SWZ","Swaziland","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2012/PRP/swz_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59621,748,"SWZ","Swaziland","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2012/PRP/swz_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59622,748,"SWZ","Swaziland","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2012/PRP/swz_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59623,748,"SWZ","Swaziland","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2014/PRP/swz_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59624,748,"SWZ","Swaziland","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2014/PRP/swz_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59625,748,"SWZ","Swaziland","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2014/PRP/swz_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59626,748,"SWZ","Swaziland","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/BuiltSettlement/2014/PRP/swz_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59627,752,"SWE","Sweden","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2000/Binary/swe_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59628,752,"SWE","Sweden","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2000/DTE/swe_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59629,752,"SWE","Sweden","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2012/Binary/swe_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59630,752,"SWE","Sweden","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2012/DTE/swe_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59631,752,"SWE","Sweden","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2014/Binary/swe_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59632,752,"SWE","Sweden","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2014/DTE/swe_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59633,752,"SWE","Sweden","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2000/PRP/swe_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59634,752,"SWE","Sweden","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2000/PRP/swe_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59635,752,"SWE","Sweden","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2000/PRP/swe_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59636,752,"SWE","Sweden","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2000/PRP/swe_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59637,752,"SWE","Sweden","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2012/PRP/swe_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59638,752,"SWE","Sweden","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2012/PRP/swe_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59639,752,"SWE","Sweden","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2012/PRP/swe_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59640,752,"SWE","Sweden","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2012/PRP/swe_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59641,752,"SWE","Sweden","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2014/PRP/swe_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59642,752,"SWE","Sweden","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2014/PRP/swe_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59643,752,"SWE","Sweden","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2014/PRP/swe_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59644,752,"SWE","Sweden","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SWE/BuiltSettlement/2014/PRP/swe_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59645,756,"CHE","Switzerland","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2000/Binary/che_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59646,756,"CHE","Switzerland","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2000/DTE/che_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59647,756,"CHE","Switzerland","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2012/Binary/che_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59648,756,"CHE","Switzerland","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2012/DTE/che_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59649,756,"CHE","Switzerland","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2014/Binary/che_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59650,756,"CHE","Switzerland","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2014/DTE/che_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59651,756,"CHE","Switzerland","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2000/PRP/che_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59652,756,"CHE","Switzerland","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2000/PRP/che_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59653,756,"CHE","Switzerland","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2000/PRP/che_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59654,756,"CHE","Switzerland","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2000/PRP/che_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59655,756,"CHE","Switzerland","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2012/PRP/che_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59656,756,"CHE","Switzerland","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2012/PRP/che_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59657,756,"CHE","Switzerland","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2012/PRP/che_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59658,756,"CHE","Switzerland","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2012/PRP/che_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59659,756,"CHE","Switzerland","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2014/PRP/che_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59660,756,"CHE","Switzerland","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2014/PRP/che_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59661,756,"CHE","Switzerland","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2014/PRP/che_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59662,756,"CHE","Switzerland","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/CHE/BuiltSettlement/2014/PRP/che_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59663,760,"SYR","Syria","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2000/Binary/syr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59664,760,"SYR","Syria","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2000/DTE/syr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59665,760,"SYR","Syria","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2012/Binary/syr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59666,760,"SYR","Syria","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2012/DTE/syr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59667,760,"SYR","Syria","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2014/Binary/syr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59668,760,"SYR","Syria","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2014/DTE/syr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59669,760,"SYR","Syria","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2000/PRP/syr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59670,760,"SYR","Syria","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2000/PRP/syr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59671,760,"SYR","Syria","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2000/PRP/syr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59672,760,"SYR","Syria","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2000/PRP/syr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59673,760,"SYR","Syria","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2012/PRP/syr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59674,760,"SYR","Syria","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2012/PRP/syr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59675,760,"SYR","Syria","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2012/PRP/syr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59676,760,"SYR","Syria","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2012/PRP/syr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59677,760,"SYR","Syria","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2014/PRP/syr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59678,760,"SYR","Syria","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2014/PRP/syr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59679,760,"SYR","Syria","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2014/PRP/syr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59680,760,"SYR","Syria","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SYR/BuiltSettlement/2014/PRP/syr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59681,762,"TJK","Tajikistan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2000/Binary/tjk_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59682,762,"TJK","Tajikistan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2000/DTE/tjk_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59683,762,"TJK","Tajikistan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2012/Binary/tjk_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59684,762,"TJK","Tajikistan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2012/DTE/tjk_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59685,762,"TJK","Tajikistan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2014/Binary/tjk_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59686,762,"TJK","Tajikistan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2014/DTE/tjk_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59687,762,"TJK","Tajikistan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2000/PRP/tjk_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59688,762,"TJK","Tajikistan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2000/PRP/tjk_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59689,762,"TJK","Tajikistan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2000/PRP/tjk_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59690,762,"TJK","Tajikistan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2000/PRP/tjk_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59691,762,"TJK","Tajikistan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2012/PRP/tjk_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59692,762,"TJK","Tajikistan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2012/PRP/tjk_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59693,762,"TJK","Tajikistan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2012/PRP/tjk_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59694,762,"TJK","Tajikistan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2012/PRP/tjk_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59695,762,"TJK","Tajikistan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2014/PRP/tjk_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59696,762,"TJK","Tajikistan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2014/PRP/tjk_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59697,762,"TJK","Tajikistan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2014/PRP/tjk_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59698,762,"TJK","Tajikistan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TJK/BuiltSettlement/2014/PRP/tjk_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59699,764,"THA","Thailand","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2000/Binary/tha_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59700,764,"THA","Thailand","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2000/DTE/tha_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59701,764,"THA","Thailand","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2012/Binary/tha_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59702,764,"THA","Thailand","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2012/DTE/tha_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59703,764,"THA","Thailand","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2014/Binary/tha_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59704,764,"THA","Thailand","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2014/DTE/tha_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59705,764,"THA","Thailand","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2000/PRP/tha_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59706,764,"THA","Thailand","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2000/PRP/tha_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59707,764,"THA","Thailand","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2000/PRP/tha_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59708,764,"THA","Thailand","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2000/PRP/tha_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59709,764,"THA","Thailand","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2012/PRP/tha_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59710,764,"THA","Thailand","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2012/PRP/tha_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59711,764,"THA","Thailand","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2012/PRP/tha_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59712,764,"THA","Thailand","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2012/PRP/tha_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59713,764,"THA","Thailand","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2014/PRP/tha_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59714,764,"THA","Thailand","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2014/PRP/tha_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59715,764,"THA","Thailand","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2014/PRP/tha_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59716,764,"THA","Thailand","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/THA/BuiltSettlement/2014/PRP/tha_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59717,768,"TGO","Togo","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2000/Binary/tgo_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59718,768,"TGO","Togo","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2000/DTE/tgo_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59719,768,"TGO","Togo","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2012/Binary/tgo_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59720,768,"TGO","Togo","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2012/DTE/tgo_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59721,768,"TGO","Togo","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2014/Binary/tgo_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59722,768,"TGO","Togo","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2014/DTE/tgo_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59723,768,"TGO","Togo","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2000/PRP/tgo_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59724,768,"TGO","Togo","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2000/PRP/tgo_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59725,768,"TGO","Togo","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2000/PRP/tgo_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59726,768,"TGO","Togo","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2000/PRP/tgo_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59727,768,"TGO","Togo","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2012/PRP/tgo_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59728,768,"TGO","Togo","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2012/PRP/tgo_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59729,768,"TGO","Togo","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2012/PRP/tgo_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59730,768,"TGO","Togo","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2012/PRP/tgo_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59731,768,"TGO","Togo","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2014/PRP/tgo_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59732,768,"TGO","Togo","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2014/PRP/tgo_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59733,768,"TGO","Togo","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2014/PRP/tgo_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59734,768,"TGO","Togo","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TGO/BuiltSettlement/2014/PRP/tgo_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59735,772,"TKL","Tokelau","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2000/Binary/tkl_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59736,772,"TKL","Tokelau","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2000/DTE/tkl_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59737,772,"TKL","Tokelau","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2012/Binary/tkl_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59738,772,"TKL","Tokelau","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2012/DTE/tkl_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59739,772,"TKL","Tokelau","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2014/Binary/tkl_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59740,772,"TKL","Tokelau","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2014/DTE/tkl_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59741,772,"TKL","Tokelau","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2000/PRP/tkl_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59742,772,"TKL","Tokelau","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2000/PRP/tkl_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59743,772,"TKL","Tokelau","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2000/PRP/tkl_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59744,772,"TKL","Tokelau","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2000/PRP/tkl_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59745,772,"TKL","Tokelau","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2012/PRP/tkl_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59746,772,"TKL","Tokelau","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2012/PRP/tkl_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59747,772,"TKL","Tokelau","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2012/PRP/tkl_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59748,772,"TKL","Tokelau","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2012/PRP/tkl_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59749,772,"TKL","Tokelau","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2014/PRP/tkl_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59750,772,"TKL","Tokelau","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2014/PRP/tkl_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59751,772,"TKL","Tokelau","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2014/PRP/tkl_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59752,772,"TKL","Tokelau","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TKL/BuiltSettlement/2014/PRP/tkl_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59753,776,"TON","Tonga","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2000/Binary/ton_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59754,776,"TON","Tonga","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2000/DTE/ton_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59755,776,"TON","Tonga","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2012/Binary/ton_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59756,776,"TON","Tonga","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2012/DTE/ton_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59757,776,"TON","Tonga","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2014/Binary/ton_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59758,776,"TON","Tonga","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2014/DTE/ton_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59759,776,"TON","Tonga","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2000/PRP/ton_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59760,776,"TON","Tonga","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2000/PRP/ton_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59761,776,"TON","Tonga","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2000/PRP/ton_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59762,776,"TON","Tonga","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2000/PRP/ton_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59763,776,"TON","Tonga","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2012/PRP/ton_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59764,776,"TON","Tonga","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2012/PRP/ton_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59765,776,"TON","Tonga","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2012/PRP/ton_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59766,776,"TON","Tonga","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2012/PRP/ton_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59767,776,"TON","Tonga","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2014/PRP/ton_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59768,776,"TON","Tonga","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2014/PRP/ton_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59769,776,"TON","Tonga","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2014/PRP/ton_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59770,776,"TON","Tonga","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TON/BuiltSettlement/2014/PRP/ton_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59771,780,"TTO","Trinidad and Tobago","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2000/Binary/tto_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59772,780,"TTO","Trinidad and Tobago","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2000/DTE/tto_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59773,780,"TTO","Trinidad and Tobago","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2012/Binary/tto_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59774,780,"TTO","Trinidad and Tobago","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2012/DTE/tto_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59775,780,"TTO","Trinidad and Tobago","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2014/Binary/tto_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59776,780,"TTO","Trinidad and Tobago","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2014/DTE/tto_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59777,780,"TTO","Trinidad and Tobago","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2000/PRP/tto_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59778,780,"TTO","Trinidad and Tobago","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2000/PRP/tto_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59779,780,"TTO","Trinidad and Tobago","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2000/PRP/tto_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59780,780,"TTO","Trinidad and Tobago","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2000/PRP/tto_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59781,780,"TTO","Trinidad and Tobago","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2012/PRP/tto_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59782,780,"TTO","Trinidad and Tobago","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2012/PRP/tto_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59783,780,"TTO","Trinidad and Tobago","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2012/PRP/tto_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59784,780,"TTO","Trinidad and Tobago","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2012/PRP/tto_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59785,780,"TTO","Trinidad and Tobago","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2014/PRP/tto_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59786,780,"TTO","Trinidad and Tobago","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2014/PRP/tto_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59787,780,"TTO","Trinidad and Tobago","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2014/PRP/tto_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59788,780,"TTO","Trinidad and Tobago","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TTO/BuiltSettlement/2014/PRP/tto_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59789,784,"ARE","United Arab Emirates","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2000/Binary/are_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59790,784,"ARE","United Arab Emirates","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2000/DTE/are_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59791,784,"ARE","United Arab Emirates","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2012/Binary/are_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59792,784,"ARE","United Arab Emirates","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2012/DTE/are_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59793,784,"ARE","United Arab Emirates","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2014/Binary/are_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59794,784,"ARE","United Arab Emirates","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2014/DTE/are_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59795,784,"ARE","United Arab Emirates","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2000/PRP/are_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59796,784,"ARE","United Arab Emirates","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2000/PRP/are_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59797,784,"ARE","United Arab Emirates","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2000/PRP/are_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59798,784,"ARE","United Arab Emirates","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2000/PRP/are_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59799,784,"ARE","United Arab Emirates","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2012/PRP/are_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59800,784,"ARE","United Arab Emirates","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2012/PRP/are_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59801,784,"ARE","United Arab Emirates","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2012/PRP/are_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59802,784,"ARE","United Arab Emirates","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2012/PRP/are_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59803,784,"ARE","United Arab Emirates","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2014/PRP/are_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59804,784,"ARE","United Arab Emirates","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2014/PRP/are_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59805,784,"ARE","United Arab Emirates","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2014/PRP/are_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59806,784,"ARE","United Arab Emirates","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ARE/BuiltSettlement/2014/PRP/are_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59807,788,"TUN","Tunisia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2000/Binary/tun_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59808,788,"TUN","Tunisia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2000/DTE/tun_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59809,788,"TUN","Tunisia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2012/Binary/tun_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59810,788,"TUN","Tunisia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2012/DTE/tun_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59811,788,"TUN","Tunisia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2014/Binary/tun_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59812,788,"TUN","Tunisia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2014/DTE/tun_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59813,788,"TUN","Tunisia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2000/PRP/tun_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59814,788,"TUN","Tunisia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2000/PRP/tun_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59815,788,"TUN","Tunisia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2000/PRP/tun_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59816,788,"TUN","Tunisia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2000/PRP/tun_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59817,788,"TUN","Tunisia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2012/PRP/tun_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59818,788,"TUN","Tunisia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2012/PRP/tun_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59819,788,"TUN","Tunisia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2012/PRP/tun_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59820,788,"TUN","Tunisia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2012/PRP/tun_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59821,788,"TUN","Tunisia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2014/PRP/tun_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59822,788,"TUN","Tunisia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2014/PRP/tun_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59823,788,"TUN","Tunisia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2014/PRP/tun_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59824,788,"TUN","Tunisia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TUN/BuiltSettlement/2014/PRP/tun_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59825,792,"TUR","Turkey","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2000/Binary/tur_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59826,792,"TUR","Turkey","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2000/DTE/tur_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59827,792,"TUR","Turkey","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2012/Binary/tur_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59828,792,"TUR","Turkey","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2012/DTE/tur_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59829,792,"TUR","Turkey","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2014/Binary/tur_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59830,792,"TUR","Turkey","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2014/DTE/tur_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59831,792,"TUR","Turkey","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2000/PRP/tur_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59832,792,"TUR","Turkey","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2000/PRP/tur_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59833,792,"TUR","Turkey","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2000/PRP/tur_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59834,792,"TUR","Turkey","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2000/PRP/tur_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59835,792,"TUR","Turkey","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2012/PRP/tur_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59836,792,"TUR","Turkey","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2012/PRP/tur_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59837,792,"TUR","Turkey","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2012/PRP/tur_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59838,792,"TUR","Turkey","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2012/PRP/tur_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59839,792,"TUR","Turkey","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2014/PRP/tur_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59840,792,"TUR","Turkey","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2014/PRP/tur_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59841,792,"TUR","Turkey","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2014/PRP/tur_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59842,792,"TUR","Turkey","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TUR/BuiltSettlement/2014/PRP/tur_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59843,795,"TKM","Turkmenistan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2000/Binary/tkm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59844,795,"TKM","Turkmenistan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2000/DTE/tkm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59845,795,"TKM","Turkmenistan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2012/Binary/tkm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59846,795,"TKM","Turkmenistan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2012/DTE/tkm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59847,795,"TKM","Turkmenistan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2014/Binary/tkm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59848,795,"TKM","Turkmenistan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2014/DTE/tkm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59849,795,"TKM","Turkmenistan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2000/PRP/tkm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59850,795,"TKM","Turkmenistan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2000/PRP/tkm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59851,795,"TKM","Turkmenistan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2000/PRP/tkm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59852,795,"TKM","Turkmenistan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2000/PRP/tkm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59853,795,"TKM","Turkmenistan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2012/PRP/tkm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59854,795,"TKM","Turkmenistan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2012/PRP/tkm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59855,795,"TKM","Turkmenistan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2012/PRP/tkm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59856,795,"TKM","Turkmenistan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2012/PRP/tkm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59857,795,"TKM","Turkmenistan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2014/PRP/tkm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59858,795,"TKM","Turkmenistan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2014/PRP/tkm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59859,795,"TKM","Turkmenistan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2014/PRP/tkm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59860,795,"TKM","Turkmenistan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TKM/BuiltSettlement/2014/PRP/tkm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59861,796,"TCA","Turks and Caicos Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2000/Binary/tca_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59862,796,"TCA","Turks and Caicos Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2000/DTE/tca_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59863,796,"TCA","Turks and Caicos Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2012/Binary/tca_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59864,796,"TCA","Turks and Caicos Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2012/DTE/tca_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59865,796,"TCA","Turks and Caicos Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2014/Binary/tca_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59866,796,"TCA","Turks and Caicos Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2014/DTE/tca_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59867,796,"TCA","Turks and Caicos Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2000/PRP/tca_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59868,796,"TCA","Turks and Caicos Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2000/PRP/tca_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59869,796,"TCA","Turks and Caicos Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2000/PRP/tca_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59870,796,"TCA","Turks and Caicos Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2000/PRP/tca_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59871,796,"TCA","Turks and Caicos Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2012/PRP/tca_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59872,796,"TCA","Turks and Caicos Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2012/PRP/tca_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59873,796,"TCA","Turks and Caicos Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2012/PRP/tca_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59874,796,"TCA","Turks and Caicos Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2012/PRP/tca_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59875,796,"TCA","Turks and Caicos Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2014/PRP/tca_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59876,796,"TCA","Turks and Caicos Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2014/PRP/tca_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59877,796,"TCA","Turks and Caicos Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2014/PRP/tca_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59878,796,"TCA","Turks and Caicos Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TCA/BuiltSettlement/2014/PRP/tca_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59879,798,"TUV","Tuvalu","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2000/Binary/tuv_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59880,798,"TUV","Tuvalu","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2000/DTE/tuv_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59881,798,"TUV","Tuvalu","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2012/Binary/tuv_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59882,798,"TUV","Tuvalu","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2012/DTE/tuv_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59883,798,"TUV","Tuvalu","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2014/Binary/tuv_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59884,798,"TUV","Tuvalu","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2014/DTE/tuv_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59885,798,"TUV","Tuvalu","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2000/PRP/tuv_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59886,798,"TUV","Tuvalu","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2000/PRP/tuv_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59887,798,"TUV","Tuvalu","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2000/PRP/tuv_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59888,798,"TUV","Tuvalu","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2000/PRP/tuv_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59889,798,"TUV","Tuvalu","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2012/PRP/tuv_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59890,798,"TUV","Tuvalu","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2012/PRP/tuv_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59891,798,"TUV","Tuvalu","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2012/PRP/tuv_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59892,798,"TUV","Tuvalu","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2012/PRP/tuv_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59893,798,"TUV","Tuvalu","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2014/PRP/tuv_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59894,798,"TUV","Tuvalu","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2014/PRP/tuv_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59895,798,"TUV","Tuvalu","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2014/PRP/tuv_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59896,798,"TUV","Tuvalu","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TUV/BuiltSettlement/2014/PRP/tuv_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59897,800,"UGA","Uganda","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2000/Binary/uga_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59898,800,"UGA","Uganda","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2000/DTE/uga_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59899,800,"UGA","Uganda","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2012/Binary/uga_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59900,800,"UGA","Uganda","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2012/DTE/uga_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59901,800,"UGA","Uganda","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2014/Binary/uga_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59902,800,"UGA","Uganda","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2014/DTE/uga_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59903,800,"UGA","Uganda","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2000/PRP/uga_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59904,800,"UGA","Uganda","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2000/PRP/uga_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59905,800,"UGA","Uganda","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2000/PRP/uga_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59906,800,"UGA","Uganda","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2000/PRP/uga_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59907,800,"UGA","Uganda","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2012/PRP/uga_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59908,800,"UGA","Uganda","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2012/PRP/uga_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59909,800,"UGA","Uganda","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2012/PRP/uga_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59910,800,"UGA","Uganda","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2012/PRP/uga_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59911,800,"UGA","Uganda","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2014/PRP/uga_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59912,800,"UGA","Uganda","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2014/PRP/uga_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59913,800,"UGA","Uganda","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2014/PRP/uga_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59914,800,"UGA","Uganda","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/UGA/BuiltSettlement/2014/PRP/uga_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59915,804,"UKR","Ukraine","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2000/Binary/ukr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59916,804,"UKR","Ukraine","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2000/DTE/ukr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59917,804,"UKR","Ukraine","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2012/Binary/ukr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59918,804,"UKR","Ukraine","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2012/DTE/ukr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59919,804,"UKR","Ukraine","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2014/Binary/ukr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59920,804,"UKR","Ukraine","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2014/DTE/ukr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59921,804,"UKR","Ukraine","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2000/PRP/ukr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59922,804,"UKR","Ukraine","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2000/PRP/ukr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59923,804,"UKR","Ukraine","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2000/PRP/ukr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59924,804,"UKR","Ukraine","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2000/PRP/ukr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59925,804,"UKR","Ukraine","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2012/PRP/ukr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59926,804,"UKR","Ukraine","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2012/PRP/ukr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59927,804,"UKR","Ukraine","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2012/PRP/ukr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59928,804,"UKR","Ukraine","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2012/PRP/ukr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59929,804,"UKR","Ukraine","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2014/PRP/ukr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59930,804,"UKR","Ukraine","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2014/PRP/ukr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59931,804,"UKR","Ukraine","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2014/PRP/ukr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59932,804,"UKR","Ukraine","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/UKR/BuiltSettlement/2014/PRP/ukr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59933,807,"MKD","Macedonia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2000/Binary/mkd_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59934,807,"MKD","Macedonia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2000/DTE/mkd_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59935,807,"MKD","Macedonia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2012/Binary/mkd_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59936,807,"MKD","Macedonia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2012/DTE/mkd_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59937,807,"MKD","Macedonia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2014/Binary/mkd_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59938,807,"MKD","Macedonia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2014/DTE/mkd_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59939,807,"MKD","Macedonia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2000/PRP/mkd_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59940,807,"MKD","Macedonia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2000/PRP/mkd_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59941,807,"MKD","Macedonia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2000/PRP/mkd_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59942,807,"MKD","Macedonia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2000/PRP/mkd_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59943,807,"MKD","Macedonia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2012/PRP/mkd_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59944,807,"MKD","Macedonia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2012/PRP/mkd_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59945,807,"MKD","Macedonia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2012/PRP/mkd_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59946,807,"MKD","Macedonia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2012/PRP/mkd_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59947,807,"MKD","Macedonia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2014/PRP/mkd_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59948,807,"MKD","Macedonia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2014/PRP/mkd_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59949,807,"MKD","Macedonia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2014/PRP/mkd_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59950,807,"MKD","Macedonia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/MKD/BuiltSettlement/2014/PRP/mkd_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59951,818,"EGY","Egypt","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2000/Binary/egy_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59952,818,"EGY","Egypt","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2000/DTE/egy_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59953,818,"EGY","Egypt","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2012/Binary/egy_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59954,818,"EGY","Egypt","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2012/DTE/egy_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59955,818,"EGY","Egypt","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2014/Binary/egy_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59956,818,"EGY","Egypt","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2014/DTE/egy_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59957,818,"EGY","Egypt","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2000/PRP/egy_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59958,818,"EGY","Egypt","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2000/PRP/egy_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59959,818,"EGY","Egypt","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2000/PRP/egy_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59960,818,"EGY","Egypt","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2000/PRP/egy_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59961,818,"EGY","Egypt","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2012/PRP/egy_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59962,818,"EGY","Egypt","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2012/PRP/egy_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59963,818,"EGY","Egypt","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2012/PRP/egy_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59964,818,"EGY","Egypt","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2012/PRP/egy_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59965,818,"EGY","Egypt","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2014/PRP/egy_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59966,818,"EGY","Egypt","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2014/PRP/egy_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59967,818,"EGY","Egypt","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2014/PRP/egy_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59968,818,"EGY","Egypt","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/EGY/BuiltSettlement/2014/PRP/egy_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59969,826,"GBR","United Kingdom","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2000/Binary/gbr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59970,826,"GBR","United Kingdom","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2000/DTE/gbr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59971,826,"GBR","United Kingdom","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2012/Binary/gbr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59972,826,"GBR","United Kingdom","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2012/DTE/gbr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59973,826,"GBR","United Kingdom","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2014/Binary/gbr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59974,826,"GBR","United Kingdom","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2014/DTE/gbr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59975,826,"GBR","United Kingdom","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2000/PRP/gbr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59976,826,"GBR","United Kingdom","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2000/PRP/gbr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59977,826,"GBR","United Kingdom","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2000/PRP/gbr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59978,826,"GBR","United Kingdom","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2000/PRP/gbr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59979,826,"GBR","United Kingdom","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2012/PRP/gbr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59980,826,"GBR","United Kingdom","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2012/PRP/gbr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59981,826,"GBR","United Kingdom","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2012/PRP/gbr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
59982,826,"GBR","United Kingdom","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2012/PRP/gbr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
59983,826,"GBR","United Kingdom","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2014/PRP/gbr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
59984,826,"GBR","United Kingdom","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2014/PRP/gbr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
59985,826,"GBR","United Kingdom","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2014/PRP/gbr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
59986,826,"GBR","United Kingdom","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GBR/BuiltSettlement/2014/PRP/gbr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
59987,831,"GGY","Guernsey","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2000/Binary/ggy_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
59988,831,"GGY","Guernsey","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2000/DTE/ggy_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
59989,831,"GGY","Guernsey","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2012/Binary/ggy_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
59990,831,"GGY","Guernsey","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2012/DTE/ggy_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
59991,831,"GGY","Guernsey","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2014/Binary/ggy_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
59992,831,"GGY","Guernsey","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2014/DTE/ggy_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
59993,831,"GGY","Guernsey","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2000/PRP/ggy_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
59994,831,"GGY","Guernsey","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2000/PRP/ggy_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
59995,831,"GGY","Guernsey","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2000/PRP/ggy_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
59996,831,"GGY","Guernsey","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2000/PRP/ggy_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
59997,831,"GGY","Guernsey","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2012/PRP/ggy_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
59998,831,"GGY","Guernsey","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2012/PRP/ggy_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
59999,831,"GGY","Guernsey","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2012/PRP/ggy_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60000,831,"GGY","Guernsey","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2012/PRP/ggy_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60001,831,"GGY","Guernsey","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2014/PRP/ggy_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60002,831,"GGY","Guernsey","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2014/PRP/ggy_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60003,831,"GGY","Guernsey","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2014/PRP/ggy_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60004,831,"GGY","Guernsey","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/GGY/BuiltSettlement/2014/PRP/ggy_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60005,832,"JEY","Jersey","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2000/Binary/jey_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60006,832,"JEY","Jersey","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2000/DTE/jey_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60007,832,"JEY","Jersey","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2012/Binary/jey_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60008,832,"JEY","Jersey","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2012/DTE/jey_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60009,832,"JEY","Jersey","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2014/Binary/jey_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60010,832,"JEY","Jersey","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2014/DTE/jey_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60011,832,"JEY","Jersey","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2000/PRP/jey_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60012,832,"JEY","Jersey","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2000/PRP/jey_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60013,832,"JEY","Jersey","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2000/PRP/jey_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60014,832,"JEY","Jersey","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2000/PRP/jey_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60015,832,"JEY","Jersey","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2012/PRP/jey_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60016,832,"JEY","Jersey","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2012/PRP/jey_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60017,832,"JEY","Jersey","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2012/PRP/jey_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60018,832,"JEY","Jersey","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2012/PRP/jey_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60019,832,"JEY","Jersey","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2014/PRP/jey_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60020,832,"JEY","Jersey","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2014/PRP/jey_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60021,832,"JEY","Jersey","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2014/PRP/jey_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60022,832,"JEY","Jersey","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/JEY/BuiltSettlement/2014/PRP/jey_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60023,833,"IMN","Isle of Man","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2000/Binary/imn_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60024,833,"IMN","Isle of Man","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2000/DTE/imn_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60025,833,"IMN","Isle of Man","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2012/Binary/imn_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60026,833,"IMN","Isle of Man","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2012/DTE/imn_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60027,833,"IMN","Isle of Man","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2014/Binary/imn_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60028,833,"IMN","Isle of Man","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2014/DTE/imn_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60029,833,"IMN","Isle of Man","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2000/PRP/imn_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60030,833,"IMN","Isle of Man","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2000/PRP/imn_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60031,833,"IMN","Isle of Man","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2000/PRP/imn_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60032,833,"IMN","Isle of Man","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2000/PRP/imn_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60033,833,"IMN","Isle of Man","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2012/PRP/imn_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60034,833,"IMN","Isle of Man","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2012/PRP/imn_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60035,833,"IMN","Isle of Man","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2012/PRP/imn_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60036,833,"IMN","Isle of Man","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2012/PRP/imn_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60037,833,"IMN","Isle of Man","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2014/PRP/imn_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60038,833,"IMN","Isle of Man","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2014/PRP/imn_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60039,833,"IMN","Isle of Man","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2014/PRP/imn_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60040,833,"IMN","Isle of Man","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/IMN/BuiltSettlement/2014/PRP/imn_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60041,834,"TZA","Tanzania","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2000/Binary/tza_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60042,834,"TZA","Tanzania","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2000/DTE/tza_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60043,834,"TZA","Tanzania","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2012/Binary/tza_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60044,834,"TZA","Tanzania","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2012/DTE/tza_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60045,834,"TZA","Tanzania","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2014/Binary/tza_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60046,834,"TZA","Tanzania","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2014/DTE/tza_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60047,834,"TZA","Tanzania","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2000/PRP/tza_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60048,834,"TZA","Tanzania","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2000/PRP/tza_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60049,834,"TZA","Tanzania","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2000/PRP/tza_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60050,834,"TZA","Tanzania","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2000/PRP/tza_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60051,834,"TZA","Tanzania","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2012/PRP/tza_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60052,834,"TZA","Tanzania","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2012/PRP/tza_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60053,834,"TZA","Tanzania","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2012/PRP/tza_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60054,834,"TZA","Tanzania","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2012/PRP/tza_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60055,834,"TZA","Tanzania","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2014/PRP/tza_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60056,834,"TZA","Tanzania","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2014/PRP/tza_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60057,834,"TZA","Tanzania","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2014/PRP/tza_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60058,834,"TZA","Tanzania","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/TZA/BuiltSettlement/2014/PRP/tza_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60059,854,"BFA","Burkina Faso","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2000/Binary/bfa_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60060,854,"BFA","Burkina Faso","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2000/DTE/bfa_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60061,854,"BFA","Burkina Faso","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2012/Binary/bfa_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60062,854,"BFA","Burkina Faso","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2012/DTE/bfa_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60063,854,"BFA","Burkina Faso","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2014/Binary/bfa_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60064,854,"BFA","Burkina Faso","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2014/DTE/bfa_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60065,854,"BFA","Burkina Faso","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2000/PRP/bfa_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60066,854,"BFA","Burkina Faso","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2000/PRP/bfa_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60067,854,"BFA","Burkina Faso","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2000/PRP/bfa_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60068,854,"BFA","Burkina Faso","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2000/PRP/bfa_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60069,854,"BFA","Burkina Faso","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2012/PRP/bfa_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60070,854,"BFA","Burkina Faso","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2012/PRP/bfa_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60071,854,"BFA","Burkina Faso","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2012/PRP/bfa_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60072,854,"BFA","Burkina Faso","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2012/PRP/bfa_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60073,854,"BFA","Burkina Faso","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2014/PRP/bfa_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60074,854,"BFA","Burkina Faso","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2014/PRP/bfa_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60075,854,"BFA","Burkina Faso","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2014/PRP/bfa_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60076,854,"BFA","Burkina Faso","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/BFA/BuiltSettlement/2014/PRP/bfa_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60077,858,"URY","Uruguay","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2000/Binary/ury_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60078,858,"URY","Uruguay","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2000/DTE/ury_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60079,858,"URY","Uruguay","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2012/Binary/ury_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60080,858,"URY","Uruguay","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2012/DTE/ury_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60081,858,"URY","Uruguay","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2014/Binary/ury_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60082,858,"URY","Uruguay","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2014/DTE/ury_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60083,858,"URY","Uruguay","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2000/PRP/ury_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60084,858,"URY","Uruguay","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2000/PRP/ury_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60085,858,"URY","Uruguay","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2000/PRP/ury_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60086,858,"URY","Uruguay","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2000/PRP/ury_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60087,858,"URY","Uruguay","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2012/PRP/ury_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60088,858,"URY","Uruguay","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2012/PRP/ury_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60089,858,"URY","Uruguay","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2012/PRP/ury_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60090,858,"URY","Uruguay","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2012/PRP/ury_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60091,858,"URY","Uruguay","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2014/PRP/ury_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60092,858,"URY","Uruguay","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2014/PRP/ury_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60093,858,"URY","Uruguay","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2014/PRP/ury_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60094,858,"URY","Uruguay","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/URY/BuiltSettlement/2014/PRP/ury_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60095,860,"UZB","Uzbekistan","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2000/Binary/uzb_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60096,860,"UZB","Uzbekistan","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2000/DTE/uzb_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60097,860,"UZB","Uzbekistan","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2012/Binary/uzb_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60098,860,"UZB","Uzbekistan","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2012/DTE/uzb_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60099,860,"UZB","Uzbekistan","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2014/Binary/uzb_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60100,860,"UZB","Uzbekistan","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2014/DTE/uzb_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60101,860,"UZB","Uzbekistan","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2000/PRP/uzb_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60102,860,"UZB","Uzbekistan","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2000/PRP/uzb_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60103,860,"UZB","Uzbekistan","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2000/PRP/uzb_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60104,860,"UZB","Uzbekistan","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2000/PRP/uzb_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60105,860,"UZB","Uzbekistan","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2012/PRP/uzb_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60106,860,"UZB","Uzbekistan","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2012/PRP/uzb_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60107,860,"UZB","Uzbekistan","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2012/PRP/uzb_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60108,860,"UZB","Uzbekistan","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2012/PRP/uzb_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60109,860,"UZB","Uzbekistan","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2014/PRP/uzb_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60110,860,"UZB","Uzbekistan","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2014/PRP/uzb_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60111,860,"UZB","Uzbekistan","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2014/PRP/uzb_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60112,860,"UZB","Uzbekistan","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/UZB/BuiltSettlement/2014/PRP/uzb_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60113,862,"VEN","Venezuela","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2000/Binary/ven_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60114,862,"VEN","Venezuela","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2000/DTE/ven_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60115,862,"VEN","Venezuela","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2012/Binary/ven_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60116,862,"VEN","Venezuela","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2012/DTE/ven_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60117,862,"VEN","Venezuela","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2014/Binary/ven_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60118,862,"VEN","Venezuela","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2014/DTE/ven_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60119,862,"VEN","Venezuela","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2000/PRP/ven_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60120,862,"VEN","Venezuela","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2000/PRP/ven_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60121,862,"VEN","Venezuela","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2000/PRP/ven_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60122,862,"VEN","Venezuela","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2000/PRP/ven_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60123,862,"VEN","Venezuela","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2012/PRP/ven_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60124,862,"VEN","Venezuela","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2012/PRP/ven_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60125,862,"VEN","Venezuela","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2012/PRP/ven_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60126,862,"VEN","Venezuela","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2012/PRP/ven_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60127,862,"VEN","Venezuela","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2014/PRP/ven_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60128,862,"VEN","Venezuela","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2014/PRP/ven_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60129,862,"VEN","Venezuela","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2014/PRP/ven_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60130,862,"VEN","Venezuela","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/VEN/BuiltSettlement/2014/PRP/ven_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60131,876,"WLF","Wallis and Futuna","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2000/Binary/wlf_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60132,876,"WLF","Wallis and Futuna","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2000/DTE/wlf_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60133,876,"WLF","Wallis and Futuna","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2012/Binary/wlf_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60134,876,"WLF","Wallis and Futuna","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2012/DTE/wlf_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60135,876,"WLF","Wallis and Futuna","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2014/Binary/wlf_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60136,876,"WLF","Wallis and Futuna","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2014/DTE/wlf_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60137,876,"WLF","Wallis and Futuna","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2000/PRP/wlf_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60138,876,"WLF","Wallis and Futuna","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2000/PRP/wlf_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60139,876,"WLF","Wallis and Futuna","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2000/PRP/wlf_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60140,876,"WLF","Wallis and Futuna","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2000/PRP/wlf_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60141,876,"WLF","Wallis and Futuna","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2012/PRP/wlf_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60142,876,"WLF","Wallis and Futuna","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2012/PRP/wlf_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60143,876,"WLF","Wallis and Futuna","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2012/PRP/wlf_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60144,876,"WLF","Wallis and Futuna","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2012/PRP/wlf_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60145,876,"WLF","Wallis and Futuna","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2014/PRP/wlf_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60146,876,"WLF","Wallis and Futuna","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2014/PRP/wlf_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60147,876,"WLF","Wallis and Futuna","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2014/PRP/wlf_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60148,876,"WLF","Wallis and Futuna","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/WLF/BuiltSettlement/2014/PRP/wlf_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60149,882,"WSM","Samoa","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2000/Binary/wsm_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60150,882,"WSM","Samoa","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2000/DTE/wsm_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60151,882,"WSM","Samoa","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2012/Binary/wsm_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60152,882,"WSM","Samoa","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2012/DTE/wsm_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60153,882,"WSM","Samoa","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2014/Binary/wsm_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60154,882,"WSM","Samoa","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2014/DTE/wsm_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60155,882,"WSM","Samoa","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2000/PRP/wsm_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60156,882,"WSM","Samoa","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2000/PRP/wsm_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60157,882,"WSM","Samoa","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2000/PRP/wsm_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60158,882,"WSM","Samoa","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2000/PRP/wsm_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60159,882,"WSM","Samoa","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2012/PRP/wsm_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60160,882,"WSM","Samoa","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2012/PRP/wsm_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60161,882,"WSM","Samoa","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2012/PRP/wsm_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60162,882,"WSM","Samoa","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2012/PRP/wsm_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60163,882,"WSM","Samoa","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2014/PRP/wsm_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60164,882,"WSM","Samoa","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2014/PRP/wsm_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60165,882,"WSM","Samoa","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2014/PRP/wsm_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60166,882,"WSM","Samoa","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/WSM/BuiltSettlement/2014/PRP/wsm_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60167,887,"YEM","Yemen","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2000/Binary/yem_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60168,887,"YEM","Yemen","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2000/DTE/yem_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60169,887,"YEM","Yemen","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2012/Binary/yem_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60170,887,"YEM","Yemen","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2012/DTE/yem_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60171,887,"YEM","Yemen","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2014/Binary/yem_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60172,887,"YEM","Yemen","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2014/DTE/yem_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60173,887,"YEM","Yemen","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2000/PRP/yem_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60174,887,"YEM","Yemen","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2000/PRP/yem_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60175,887,"YEM","Yemen","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2000/PRP/yem_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60176,887,"YEM","Yemen","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2000/PRP/yem_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60177,887,"YEM","Yemen","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2012/PRP/yem_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60178,887,"YEM","Yemen","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2012/PRP/yem_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60179,887,"YEM","Yemen","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2012/PRP/yem_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60180,887,"YEM","Yemen","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2012/PRP/yem_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60181,887,"YEM","Yemen","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2014/PRP/yem_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60182,887,"YEM","Yemen","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2014/PRP/yem_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60183,887,"YEM","Yemen","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2014/PRP/yem_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60184,887,"YEM","Yemen","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/YEM/BuiltSettlement/2014/PRP/yem_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60185,894,"ZMB","Zambia","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2000/Binary/zmb_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60186,894,"ZMB","Zambia","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2000/DTE/zmb_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60187,894,"ZMB","Zambia","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2012/Binary/zmb_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60188,894,"ZMB","Zambia","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2012/DTE/zmb_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60189,894,"ZMB","Zambia","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2014/Binary/zmb_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60190,894,"ZMB","Zambia","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2014/DTE/zmb_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60191,894,"ZMB","Zambia","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2000/PRP/zmb_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60192,894,"ZMB","Zambia","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2000/PRP/zmb_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60193,894,"ZMB","Zambia","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2000/PRP/zmb_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60194,894,"ZMB","Zambia","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2000/PRP/zmb_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60195,894,"ZMB","Zambia","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2012/PRP/zmb_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60196,894,"ZMB","Zambia","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2012/PRP/zmb_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60197,894,"ZMB","Zambia","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2012/PRP/zmb_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60198,894,"ZMB","Zambia","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2012/PRP/zmb_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60199,894,"ZMB","Zambia","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2014/PRP/zmb_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60200,894,"ZMB","Zambia","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2014/PRP/zmb_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60201,894,"ZMB","Zambia","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2014/PRP/zmb_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60202,894,"ZMB","Zambia","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/BuiltSettlement/2014/PRP/zmb_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60203,900,"KOS","Kosovo","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2000/Binary/kos_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60204,900,"KOS","Kosovo","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2000/DTE/kos_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60205,900,"KOS","Kosovo","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2012/Binary/kos_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60206,900,"KOS","Kosovo","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2012/DTE/kos_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60207,900,"KOS","Kosovo","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2014/Binary/kos_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60208,900,"KOS","Kosovo","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2014/DTE/kos_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60209,900,"KOS","Kosovo","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2000/PRP/kos_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60210,900,"KOS","Kosovo","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2000/PRP/kos_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60211,900,"KOS","Kosovo","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2000/PRP/kos_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60212,900,"KOS","Kosovo","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2000/PRP/kos_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60213,900,"KOS","Kosovo","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2012/PRP/kos_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60214,900,"KOS","Kosovo","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2012/PRP/kos_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60215,900,"KOS","Kosovo","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2012/PRP/kos_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60216,900,"KOS","Kosovo","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2012/PRP/kos_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60217,900,"KOS","Kosovo","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2014/PRP/kos_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60218,900,"KOS","Kosovo","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2014/PRP/kos_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60219,900,"KOS","Kosovo","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2014/PRP/kos_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60220,900,"KOS","Kosovo","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/KOS/BuiltSettlement/2014/PRP/kos_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60221,901,"SPR","Spratly Islands","ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2000/Binary/spr_ghslesaccilc_100m_2000.tif","GHSL+ESA-CCI-LC built-settlement areas 2000"
60222,901,"SPR","Spratly Islands","dst_ghslesaccilc_100m_2000","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2000/DTE/spr_dst_ghslesaccilc_100m_2000.tif","Distance to GHSL+ESA-CCI-LC built-settlement area edges 2000"
60223,901,"SPR","Spratly Islands","ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2012/Binary/spr_ghslesaccilcguf_100m_2012.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2012"
60224,901,"SPR","Spratly Islands","dst_ghslesaccilcguf_100m_2012","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2012/DTE/spr_dst_ghslesaccilcguf_100m_2012.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2012"
60225,901,"SPR","Spratly Islands","ghslesaccilcgufghsl_100m_2014","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2014/Binary/spr_ghslesaccilcgufghsl_100m_2014.tif","GHSL+ESA-CCI-LC+GUF built-settlement areas 2014"
60226,901,"SPR","Spratly Islands","dst_ghslesaccilcgufghsll_100m_2014","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2014/DTE/spr_dst_ghslesaccilcgufghsll_100m_2014.tif","Distance to GHSL+ESA-CCI-LC+GUF built-settlement area edges 2014"
60227,901,"SPR","Spratly Islands","urbpx_prp_1_100m_2000","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2000/PRP/spr_urbpx_prp_1_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 1 grid-cell radius 2000"
60228,901,"SPR","Spratly Islands","urbpx_prp_5_100m_2000","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2000/PRP/spr_urbpx_prp_5_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 5 grid-cell radius 2000"
60229,901,"SPR","Spratly Islands","urbpx_prp_10_100m_2000","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2000/PRP/spr_urbpx_prp_10_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 10 grid-cell radius 2000"
60230,901,"SPR","Spratly Islands","urbpx_prp_15_100m_2000","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2000/PRP/spr_urbpx_prp_15_100m_2000.tif","Proportion of GHSL+ESA-CCI-LC built-settlement grid-cells with 15 grid-cell radius 2000"
60231,901,"SPR","Spratly Islands","urbpx_prp_1_100m_2012","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2012/PRP/spr_urbpx_prp_1_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2012"
60232,901,"SPR","Spratly Islands","urbpx_prp_5_100m_2012","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2012/PRP/spr_urbpx_prp_5_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2012"
60233,901,"SPR","Spratly Islands","urbpx_prp_10_100m_2012","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2012/PRP/spr_urbpx_prp_10_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2012"
60234,901,"SPR","Spratly Islands","urbpx_prp_15_100m_2012","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2012/PRP/spr_urbpx_prp_15_100m_2012.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2012"
60235,901,"SPR","Spratly Islands","urbpx_prp_1_100m_2014","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2014/PRP/spr_urbpx_prp_1_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 1 grid-cell radius 2014"
60236,901,"SPR","Spratly Islands","urbpx_prp_5_100m_2014","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2014/PRP/spr_urbpx_prp_5_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 5 grid-cell radius 2014"
60237,901,"SPR","Spratly Islands","urbpx_prp_10_100m_2014","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2014/PRP/spr_urbpx_prp_10_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 10 grid-cell radius 2014"
60238,901,"SPR","Spratly Islands","urbpx_prp_15_100m_2014","GIS/Covariates/Global_2000_2020/SPR/BuiltSettlement/2014/PRP/spr_urbpx_prp_15_100m_2014.tif","Proportion of GHSL+ESA-CCI-LC+GUF built-settlement grid-cells with 15 grid-cell radius 2014"
60239,643,"RUS","Russia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/RUS/Slope/rus_srtm_slope_100m.tif","SRTM slope 2000"
60240,360,"IDN","Indonesia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/IDN/Slope/idn_srtm_slope_100m.tif","SRTM slope 2000"
60241,840,"USA","United States","srtm_slope_100m","GIS/Covariates/Global_2000_2020/USA/Slope/usa_srtm_slope_100m.tif","SRTM slope 2000"
60242,850,"VIR","Virgin_Islands_U_S","srtm_slope_100m","GIS/Covariates/Global_2000_2020/VIR/Slope/vir_srtm_slope_100m.tif","SRTM slope 2000"
60243,304,"GRL","Greenland","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GRL/Slope/grl_srtm_slope_100m.tif","SRTM slope 2000"
60244,156,"CHN","China","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CHN/Slope/chn_srtm_slope_100m.tif","SRTM slope 2000"
60245,36,"AUS","Australia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/AUS/Slope/aus_srtm_slope_100m.tif","SRTM slope 2000"
60246,76,"BRA","Brazil","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BRA/Slope/bra_srtm_slope_100m.tif","SRTM slope 2000"
60247,124,"CAN","Canada","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CAN/Slope/can_srtm_slope_100m.tif","SRTM slope 2000"
60248,152,"CHL","Chile","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CHL/Slope/chl_srtm_slope_100m.tif","SRTM slope 2000"
60249,4,"AFG","Afghanistan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/AFG/Slope/afg_srtm_slope_100m.tif","SRTM slope 2000"
60250,8,"ALB","Albania","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ALB/Slope/alb_srtm_slope_100m.tif","SRTM slope 2000"
60251,10,"ATA","Antarctica","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ATA/Slope/ata_srtm_slope_100m.tif","SRTM slope 2000"
60252,12,"DZA","Algeria","srtm_slope_100m","GIS/Covariates/Global_2000_2020/DZA/Slope/dza_srtm_slope_100m.tif","SRTM slope 2000"
60253,16,"ASM","American Samoa","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ASM/Slope/asm_srtm_slope_100m.tif","SRTM slope 2000"
60254,20,"AND","Andorra","srtm_slope_100m","GIS/Covariates/Global_2000_2020/AND/Slope/and_srtm_slope_100m.tif","SRTM slope 2000"
60255,24,"AGO","Angola","srtm_slope_100m","GIS/Covariates/Global_2000_2020/AGO/Slope/ago_srtm_slope_100m.tif","SRTM slope 2000"
60256,28,"ATG","Antigua and Barbuda","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ATG/Slope/atg_srtm_slope_100m.tif","SRTM slope 2000"
60257,31,"AZE","Azerbaijan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/AZE/Slope/aze_srtm_slope_100m.tif","SRTM slope 2000"
60258,32,"ARG","Argentina","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ARG/Slope/arg_srtm_slope_100m.tif","SRTM slope 2000"
60259,40,"AUT","Austria","srtm_slope_100m","GIS/Covariates/Global_2000_2020/AUT/Slope/aut_srtm_slope_100m.tif","SRTM slope 2000"
60260,44,"BHS","Bahamas","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BHS/Slope/bhs_srtm_slope_100m.tif","SRTM slope 2000"
60261,48,"BHR","Bahrain","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BHR/Slope/bhr_srtm_slope_100m.tif","SRTM slope 2000"
60262,50,"BGD","Bangladesh","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BGD/Slope/bgd_srtm_slope_100m.tif","SRTM slope 2000"
60263,51,"ARM","Armenia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ARM/Slope/arm_srtm_slope_100m.tif","SRTM slope 2000"
60264,52,"BRB","Barbados","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BRB/Slope/brb_srtm_slope_100m.tif","SRTM slope 2000"
60265,56,"BEL","Belgium","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BEL/Slope/bel_srtm_slope_100m.tif","SRTM slope 2000"
60266,60,"BMU","Bermuda","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BMU/Slope/bmu_srtm_slope_100m.tif","SRTM slope 2000"
60267,64,"BTN","Bhutan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BTN/Slope/btn_srtm_slope_100m.tif","SRTM slope 2000"
60268,68,"BOL","Bolivia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BOL/Slope/bol_srtm_slope_100m.tif","SRTM slope 2000"
60269,70,"BIH","Bosnia and Herzegovina","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BIH/Slope/bih_srtm_slope_100m.tif","SRTM slope 2000"
60270,72,"BWA","Botswana","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BWA/Slope/bwa_srtm_slope_100m.tif","SRTM slope 2000"
60271,74,"BVT","Bouvet Island","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BVT/Slope/bvt_srtm_slope_100m.tif","SRTM slope 2000"
60272,84,"BLZ","Belize","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BLZ/Slope/blz_srtm_slope_100m.tif","SRTM slope 2000"
60273,86,"IOT","British Indian Ocean Territory","srtm_slope_100m","GIS/Covariates/Global_2000_2020/IOT/Slope/iot_srtm_slope_100m.tif","SRTM slope 2000"
60274,90,"SLB","Solomon Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SLB/Slope/slb_srtm_slope_100m.tif","SRTM slope 2000"
60275,92,"VGB","British Virgin Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/VGB/Slope/vgb_srtm_slope_100m.tif","SRTM slope 2000"
60276,96,"BRN","Brunei","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BRN/Slope/brn_srtm_slope_100m.tif","SRTM slope 2000"
60277,100,"BGR","Bulgaria","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BGR/Slope/bgr_srtm_slope_100m.tif","SRTM slope 2000"
60278,104,"MMR","Myanmar","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MMR/Slope/mmr_srtm_slope_100m.tif","SRTM slope 2000"
60279,108,"BDI","Burundi","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BDI/Slope/bdi_srtm_slope_100m.tif","SRTM slope 2000"
60280,112,"BLR","Belarus","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BLR/Slope/blr_srtm_slope_100m.tif","SRTM slope 2000"
60281,116,"KHM","Cambodia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/KHM/Slope/khm_srtm_slope_100m.tif","SRTM slope 2000"
60282,120,"CMR","Cameroon","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CMR/Slope/cmr_srtm_slope_100m.tif","SRTM slope 2000"
60283,132,"CPV","Cape Verde","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CPV/Slope/cpv_srtm_slope_100m.tif","SRTM slope 2000"
60284,136,"CYM","Cayman Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CYM/Slope/cym_srtm_slope_100m.tif","SRTM slope 2000"
60285,140,"CAF","Central African Republic","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CAF/Slope/caf_srtm_slope_100m.tif","SRTM slope 2000"
60286,144,"LKA","Sri Lanka","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LKA/Slope/lka_srtm_slope_100m.tif","SRTM slope 2000"
60287,148,"TCD","Chad","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TCD/Slope/tcd_srtm_slope_100m.tif","SRTM slope 2000"
60288,158,"TWN","Taiwan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TWN/Slope/twn_srtm_slope_100m.tif","SRTM slope 2000"
60289,170,"COL","Colombia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/COL/Slope/col_srtm_slope_100m.tif","SRTM slope 2000"
60290,174,"COM","Comoros","srtm_slope_100m","GIS/Covariates/Global_2000_2020/COM/Slope/com_srtm_slope_100m.tif","SRTM slope 2000"
60291,175,"MYT","Mayotte","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MYT/Slope/myt_srtm_slope_100m.tif","SRTM slope 2000"
60292,178,"COG","Republic of Congo","srtm_slope_100m","GIS/Covariates/Global_2000_2020/COG/Slope/cog_srtm_slope_100m.tif","SRTM slope 2000"
60293,180,"COD","Democratic Republic of the Congo","srtm_slope_100m","GIS/Covariates/Global_2000_2020/COD/Slope/cod_srtm_slope_100m.tif","SRTM slope 2000"
60294,184,"COK","Cook Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/COK/Slope/cok_srtm_slope_100m.tif","SRTM slope 2000"
60295,188,"CRI","Costa Rica","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CRI/Slope/cri_srtm_slope_100m.tif","SRTM slope 2000"
60296,191,"HRV","Croatia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/HRV/Slope/hrv_srtm_slope_100m.tif","SRTM slope 2000"
60297,192,"CUB","Cuba","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CUB/Slope/cub_srtm_slope_100m.tif","SRTM slope 2000"
60298,196,"CYP","Cyprus","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CYP/Slope/cyp_srtm_slope_100m.tif","SRTM slope 2000"
60299,203,"CZE","Czech Republic","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CZE/Slope/cze_srtm_slope_100m.tif","SRTM slope 2000"
60300,204,"BEN","Benin","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BEN/Slope/ben_srtm_slope_100m.tif","SRTM slope 2000"
60301,208,"DNK","Denmark","srtm_slope_100m","GIS/Covariates/Global_2000_2020/DNK/Slope/dnk_srtm_slope_100m.tif","SRTM slope 2000"
60302,212,"DMA","Dominica","srtm_slope_100m","GIS/Covariates/Global_2000_2020/DMA/Slope/dma_srtm_slope_100m.tif","SRTM slope 2000"
60303,214,"DOM","Dominican Republic","srtm_slope_100m","GIS/Covariates/Global_2000_2020/DOM/Slope/dom_srtm_slope_100m.tif","SRTM slope 2000"
60304,218,"ECU","Ecuador","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ECU/Slope/ecu_srtm_slope_100m.tif","SRTM slope 2000"
60305,222,"SLV","El Salvador","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SLV/Slope/slv_srtm_slope_100m.tif","SRTM slope 2000"
60306,226,"GNQ","Equatorial Guinea","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GNQ/Slope/gnq_srtm_slope_100m.tif","SRTM slope 2000"
60307,231,"ETH","Ethiopia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ETH/Slope/eth_srtm_slope_100m.tif","SRTM slope 2000"
60308,232,"ERI","Eritrea","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ERI/Slope/eri_srtm_slope_100m.tif","SRTM slope 2000"
60309,233,"EST","Estonia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/EST/Slope/est_srtm_slope_100m.tif","SRTM slope 2000"
60310,234,"FRO","Faroe Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/FRO/Slope/fro_srtm_slope_100m.tif","SRTM slope 2000"
60311,238,"FLK","Falkland Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/FLK/Slope/flk_srtm_slope_100m.tif","SRTM slope 2000"
60312,239,"SGS","South Georgia and the South Sandwich Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SGS/Slope/sgs_srtm_slope_100m.tif","SRTM slope 2000"
60313,242,"FJI","Fiji","srtm_slope_100m","GIS/Covariates/Global_2000_2020/FJI/Slope/fji_srtm_slope_100m.tif","SRTM slope 2000"
60314,246,"FIN","Finland","srtm_slope_100m","GIS/Covariates/Global_2000_2020/FIN/Slope/fin_srtm_slope_100m.tif","SRTM slope 2000"
60315,248,"ALA","Aland Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ALA/Slope/ala_srtm_slope_100m.tif","SRTM slope 2000"
60316,250,"FRA","France","srtm_slope_100m","GIS/Covariates/Global_2000_2020/FRA/Slope/fra_srtm_slope_100m.tif","SRTM slope 2000"
60317,254,"GUF","French Guiana","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GUF/Slope/guf_srtm_slope_100m.tif","SRTM slope 2000"
60318,258,"PYF","French Polynesia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PYF/Slope/pyf_srtm_slope_100m.tif","SRTM slope 2000"
60319,260,"ATF","French Southern Territories","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ATF/Slope/atf_srtm_slope_100m.tif","SRTM slope 2000"
60320,262,"DJI","Djibouti","srtm_slope_100m","GIS/Covariates/Global_2000_2020/DJI/Slope/dji_srtm_slope_100m.tif","SRTM slope 2000"
60321,266,"GAB","Gabon","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GAB/Slope/gab_srtm_slope_100m.tif","SRTM slope 2000"
60322,268,"GEO","Georgia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GEO/Slope/geo_srtm_slope_100m.tif","SRTM slope 2000"
60323,270,"GMB","Gambia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GMB/Slope/gmb_srtm_slope_100m.tif","SRTM slope 2000"
60324,275,"PSE","Palestina","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PSE/Slope/pse_srtm_slope_100m.tif","SRTM slope 2000"
60325,276,"DEU","Germany","srtm_slope_100m","GIS/Covariates/Global_2000_2020/DEU/Slope/deu_srtm_slope_100m.tif","SRTM slope 2000"
60326,288,"GHA","Ghana","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GHA/Slope/gha_srtm_slope_100m.tif","SRTM slope 2000"
60327,292,"GIB","Gibraltar","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GIB/Slope/gib_srtm_slope_100m.tif","SRTM slope 2000"
60328,296,"KIR","Kiribati","srtm_slope_100m","GIS/Covariates/Global_2000_2020/KIR/Slope/kir_srtm_slope_100m.tif","SRTM slope 2000"
60329,300,"GRC","Greece","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GRC/Slope/grc_srtm_slope_100m.tif","SRTM slope 2000"
60330,308,"GRD","Grenada","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GRD/Slope/grd_srtm_slope_100m.tif","SRTM slope 2000"
60331,312,"GLP","Guadeloupe","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GLP/Slope/glp_srtm_slope_100m.tif","SRTM slope 2000"
60332,316,"GUM","Guam","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GUM/Slope/gum_srtm_slope_100m.tif","SRTM slope 2000"
60333,320,"GTM","Guatemala","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GTM/Slope/gtm_srtm_slope_100m.tif","SRTM slope 2000"
60334,324,"GIN","Guinea","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GIN/Slope/gin_srtm_slope_100m.tif","SRTM slope 2000"
60335,328,"GUY","Guyana","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GUY/Slope/guy_srtm_slope_100m.tif","SRTM slope 2000"
60336,332,"HTI","Haiti","srtm_slope_100m","GIS/Covariates/Global_2000_2020/HTI/Slope/hti_srtm_slope_100m.tif","SRTM slope 2000"
60337,334,"HMD","Heard Island and McDonald Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/HMD/Slope/hmd_srtm_slope_100m.tif","SRTM slope 2000"
60338,336,"VAT","Vatican City","srtm_slope_100m","GIS/Covariates/Global_2000_2020/VAT/Slope/vat_srtm_slope_100m.tif","SRTM slope 2000"
60339,340,"HND","Honduras","srtm_slope_100m","GIS/Covariates/Global_2000_2020/HND/Slope/hnd_srtm_slope_100m.tif","SRTM slope 2000"
60340,344,"HKG","Hong Kong","srtm_slope_100m","GIS/Covariates/Global_2000_2020/HKG/Slope/hkg_srtm_slope_100m.tif","SRTM slope 2000"
60341,348,"HUN","Hungary","srtm_slope_100m","GIS/Covariates/Global_2000_2020/HUN/Slope/hun_srtm_slope_100m.tif","SRTM slope 2000"
60342,352,"ISL","Iceland","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ISL/Slope/isl_srtm_slope_100m.tif","SRTM slope 2000"
60343,356,"IND","India","srtm_slope_100m","GIS/Covariates/Global_2000_2020/IND/Slope/ind_srtm_slope_100m.tif","SRTM slope 2000"
60344,364,"IRN","Iran","srtm_slope_100m","GIS/Covariates/Global_2000_2020/IRN/Slope/irn_srtm_slope_100m.tif","SRTM slope 2000"
60345,368,"IRQ","Iraq","srtm_slope_100m","GIS/Covariates/Global_2000_2020/IRQ/Slope/irq_srtm_slope_100m.tif","SRTM slope 2000"
60346,372,"IRL","Ireland","srtm_slope_100m","GIS/Covariates/Global_2000_2020/IRL/Slope/irl_srtm_slope_100m.tif","SRTM slope 2000"
60347,376,"ISR","Israel","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ISR/Slope/isr_srtm_slope_100m.tif","SRTM slope 2000"
60348,380,"ITA","Italy","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ITA/Slope/ita_srtm_slope_100m.tif","SRTM slope 2000"
60349,384,"CIV","CIte dIvoire","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CIV/Slope/civ_srtm_slope_100m.tif","SRTM slope 2000"
60350,388,"JAM","Jamaica","srtm_slope_100m","GIS/Covariates/Global_2000_2020/JAM/Slope/jam_srtm_slope_100m.tif","SRTM slope 2000"
60351,392,"JPN","Japan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/JPN/Slope/jpn_srtm_slope_100m.tif","SRTM slope 2000"
60352,398,"KAZ","Kazakhstan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/KAZ/Slope/kaz_srtm_slope_100m.tif","SRTM slope 2000"
60353,400,"JOR","Jordan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/JOR/Slope/jor_srtm_slope_100m.tif","SRTM slope 2000"
60354,404,"KEN","Kenya","srtm_slope_100m","GIS/Covariates/Global_2000_2020/KEN/Slope/ken_srtm_slope_100m.tif","SRTM slope 2000"
60355,408,"PRK","North Korea","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PRK/Slope/prk_srtm_slope_100m.tif","SRTM slope 2000"
60356,410,"KOR","South Korea","srtm_slope_100m","GIS/Covariates/Global_2000_2020/KOR/Slope/kor_srtm_slope_100m.tif","SRTM slope 2000"
60357,414,"KWT","Kuwait","srtm_slope_100m","GIS/Covariates/Global_2000_2020/KWT/Slope/kwt_srtm_slope_100m.tif","SRTM slope 2000"
60358,417,"KGZ","Kyrgyzstan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/KGZ/Slope/kgz_srtm_slope_100m.tif","SRTM slope 2000"
60359,418,"LAO","Laos","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LAO/Slope/lao_srtm_slope_100m.tif","SRTM slope 2000"
60360,422,"LBN","Lebanon","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LBN/Slope/lbn_srtm_slope_100m.tif","SRTM slope 2000"
60361,426,"LSO","Lesotho","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LSO/Slope/lso_srtm_slope_100m.tif","SRTM slope 2000"
60362,428,"LVA","Latvia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LVA/Slope/lva_srtm_slope_100m.tif","SRTM slope 2000"
60363,430,"LBR","Liberia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LBR/Slope/lbr_srtm_slope_100m.tif","SRTM slope 2000"
60364,434,"LBY","Libya","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LBY/Slope/lby_srtm_slope_100m.tif","SRTM slope 2000"
60365,438,"LIE","Liechtenstein","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LIE/Slope/lie_srtm_slope_100m.tif","SRTM slope 2000"
60366,440,"LTU","Lithuania","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LTU/Slope/ltu_srtm_slope_100m.tif","SRTM slope 2000"
60367,442,"LUX","Luxembourg","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LUX/Slope/lux_srtm_slope_100m.tif","SRTM slope 2000"
60368,446,"MAC","Macao","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MAC/Slope/mac_srtm_slope_100m.tif","SRTM slope 2000"
60369,450,"MDG","Madagascar","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MDG/Slope/mdg_srtm_slope_100m.tif","SRTM slope 2000"
60370,454,"MWI","Malawi","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MWI/Slope/mwi_srtm_slope_100m.tif","SRTM slope 2000"
60371,458,"MYS","Malaysia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MYS/Slope/mys_srtm_slope_100m.tif","SRTM slope 2000"
60372,462,"MDV","Maldives","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MDV/Slope/mdv_srtm_slope_100m.tif","SRTM slope 2000"
60373,466,"MLI","Mali","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MLI/Slope/mli_srtm_slope_100m.tif","SRTM slope 2000"
60374,470,"MLT","Malta","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MLT/Slope/mlt_srtm_slope_100m.tif","SRTM slope 2000"
60375,474,"MTQ","Martinique","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MTQ/Slope/mtq_srtm_slope_100m.tif","SRTM slope 2000"
60376,478,"MRT","Mauritania","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MRT/Slope/mrt_srtm_slope_100m.tif","SRTM slope 2000"
60377,480,"MUS","Mauritius","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MUS/Slope/mus_srtm_slope_100m.tif","SRTM slope 2000"
60378,484,"MEX","Mexico","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MEX/Slope/mex_srtm_slope_100m.tif","SRTM slope 2000"
60379,492,"MCO","Monaco","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MCO/Slope/mco_srtm_slope_100m.tif","SRTM slope 2000"
60380,496,"MNG","Mongolia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MNG/Slope/mng_srtm_slope_100m.tif","SRTM slope 2000"
60381,498,"MDA","Moldova","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MDA/Slope/mda_srtm_slope_100m.tif","SRTM slope 2000"
60382,499,"MNE","Montenegro","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MNE/Slope/mne_srtm_slope_100m.tif","SRTM slope 2000"
60383,500,"MSR","Montserrat","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MSR/Slope/msr_srtm_slope_100m.tif","SRTM slope 2000"
60384,504,"MAR","Morocco","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MAR/Slope/mar_srtm_slope_100m.tif","SRTM slope 2000"
60385,508,"MOZ","Mozambique","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MOZ/Slope/moz_srtm_slope_100m.tif","SRTM slope 2000"
60386,512,"OMN","Oman","srtm_slope_100m","GIS/Covariates/Global_2000_2020/OMN/Slope/omn_srtm_slope_100m.tif","SRTM slope 2000"
60387,516,"NAM","Namibia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NAM/Slope/nam_srtm_slope_100m.tif","SRTM slope 2000"
60388,520,"NRU","Nauru","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NRU/Slope/nru_srtm_slope_100m.tif","SRTM slope 2000"
60389,524,"NPL","Nepal","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NPL/Slope/npl_srtm_slope_100m.tif","SRTM slope 2000"
60390,528,"NLD","Netherlands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NLD/Slope/nld_srtm_slope_100m.tif","SRTM slope 2000"
60391,531,"CUW","Curacao","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CUW/Slope/cuw_srtm_slope_100m.tif","SRTM slope 2000"
60392,533,"ABW","Aruba","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ABW/Slope/abw_srtm_slope_100m.tif","SRTM slope 2000"
60393,534,"SXM","Sint Maarten (Dutch part)","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SXM/Slope/sxm_srtm_slope_100m.tif","SRTM slope 2000"
60394,535,"BES","Bonaire, Sint Eustatius and Saba","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BES/Slope/bes_srtm_slope_100m.tif","SRTM slope 2000"
60395,540,"NCL","New Caledonia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NCL/Slope/ncl_srtm_slope_100m.tif","SRTM slope 2000"
60396,548,"VUT","Vanuatu","srtm_slope_100m","GIS/Covariates/Global_2000_2020/VUT/Slope/vut_srtm_slope_100m.tif","SRTM slope 2000"
60397,554,"NZL","New Zealand","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NZL/Slope/nzl_srtm_slope_100m.tif","SRTM slope 2000"
60398,558,"NIC","Nicaragua","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NIC/Slope/nic_srtm_slope_100m.tif","SRTM slope 2000"
60399,562,"NER","Niger","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NER/Slope/ner_srtm_slope_100m.tif","SRTM slope 2000"
60400,566,"NGA","Nigeria","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NGA/Slope/nga_srtm_slope_100m.tif","SRTM slope 2000"
60401,570,"NIU","Niue","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NIU/Slope/niu_srtm_slope_100m.tif","SRTM slope 2000"
60402,574,"NFK","Norfolk Island","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NFK/Slope/nfk_srtm_slope_100m.tif","SRTM slope 2000"
60403,578,"NOR","Norway","srtm_slope_100m","GIS/Covariates/Global_2000_2020/NOR/Slope/nor_srtm_slope_100m.tif","SRTM slope 2000"
60404,580,"MNP","Northern Mariana Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MNP/Slope/mnp_srtm_slope_100m.tif","SRTM slope 2000"
60405,581,"UMI","United States Minor Outlying Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/UMI/Slope/umi_srtm_slope_100m.tif","SRTM slope 2000"
60406,583,"FSM","Micronesia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/FSM/Slope/fsm_srtm_slope_100m.tif","SRTM slope 2000"
60407,584,"MHL","Marshall Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MHL/Slope/mhl_srtm_slope_100m.tif","SRTM slope 2000"
60408,585,"PLW","Palau","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PLW/Slope/plw_srtm_slope_100m.tif","SRTM slope 2000"
60409,586,"PAK","Pakistan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PAK/Slope/pak_srtm_slope_100m.tif","SRTM slope 2000"
60410,591,"PAN","Panama","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PAN/Slope/pan_srtm_slope_100m.tif","SRTM slope 2000"
60411,598,"PNG","Papua New Guinea","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PNG/Slope/png_srtm_slope_100m.tif","SRTM slope 2000"
60412,600,"PRY","Paraguay","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PRY/Slope/pry_srtm_slope_100m.tif","SRTM slope 2000"
60413,604,"PER","Peru","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PER/Slope/per_srtm_slope_100m.tif","SRTM slope 2000"
60414,608,"PHL","Philippines","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PHL/Slope/phl_srtm_slope_100m.tif","SRTM slope 2000"
60415,612,"PCN","Pitcairn Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PCN/Slope/pcn_srtm_slope_100m.tif","SRTM slope 2000"
60416,616,"POL","Poland","srtm_slope_100m","GIS/Covariates/Global_2000_2020/POL/Slope/pol_srtm_slope_100m.tif","SRTM slope 2000"
60417,620,"PRT","Portugal","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PRT/Slope/prt_srtm_slope_100m.tif","SRTM slope 2000"
60418,624,"GNB","Guinea-Bissau","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GNB/Slope/gnb_srtm_slope_100m.tif","SRTM slope 2000"
60419,626,"TLS","East Timor","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TLS/Slope/tls_srtm_slope_100m.tif","SRTM slope 2000"
60420,630,"PRI","Puerto Rico","srtm_slope_100m","GIS/Covariates/Global_2000_2020/PRI/Slope/pri_srtm_slope_100m.tif","SRTM slope 2000"
60421,634,"QAT","Qatar","srtm_slope_100m","GIS/Covariates/Global_2000_2020/QAT/Slope/qat_srtm_slope_100m.tif","SRTM slope 2000"
60422,638,"REU","Reunion","srtm_slope_100m","GIS/Covariates/Global_2000_2020/REU/Slope/reu_srtm_slope_100m.tif","SRTM slope 2000"
60423,642,"ROU","Romania","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ROU/Slope/rou_srtm_slope_100m.tif","SRTM slope 2000"
60424,646,"RWA","Rwanda","srtm_slope_100m","GIS/Covariates/Global_2000_2020/RWA/Slope/rwa_srtm_slope_100m.tif","SRTM slope 2000"
60425,652,"BLM","Saint Barthelemy","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BLM/Slope/blm_srtm_slope_100m.tif","SRTM slope 2000"
60426,654,"SHN","Saint Helena","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SHN/Slope/shn_srtm_slope_100m.tif","SRTM slope 2000"
60427,659,"KNA","Saint Kitts and Nevis","srtm_slope_100m","GIS/Covariates/Global_2000_2020/KNA/Slope/kna_srtm_slope_100m.tif","SRTM slope 2000"
60428,660,"AIA","Anguilla","srtm_slope_100m","GIS/Covariates/Global_2000_2020/AIA/Slope/aia_srtm_slope_100m.tif","SRTM slope 2000"
60429,662,"LCA","Saint Lucia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/LCA/Slope/lca_srtm_slope_100m.tif","SRTM slope 2000"
60430,663,"MAF","Saint Martin (French part)","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MAF/Slope/maf_srtm_slope_100m.tif","SRTM slope 2000"
60431,666,"SPM","Saint Pierre and Miquelon","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SPM/Slope/spm_srtm_slope_100m.tif","SRTM slope 2000"
60432,670,"VCT","Saint Vincent and the Grenadines","srtm_slope_100m","GIS/Covariates/Global_2000_2020/VCT/Slope/vct_srtm_slope_100m.tif","SRTM slope 2000"
60433,674,"SMR","San Marino","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SMR/Slope/smr_srtm_slope_100m.tif","SRTM slope 2000"
60434,678,"STP","Sao Tome and Principe","srtm_slope_100m","GIS/Covariates/Global_2000_2020/STP/Slope/stp_srtm_slope_100m.tif","SRTM slope 2000"
60435,682,"SAU","Saudi Arabia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SAU/Slope/sau_srtm_slope_100m.tif","SRTM slope 2000"
60436,686,"SEN","Senegal","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SEN/Slope/sen_srtm_slope_100m.tif","SRTM slope 2000"
60437,688,"SRB","Serbia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SRB/Slope/srb_srtm_slope_100m.tif","SRTM slope 2000"
60438,690,"SYC","Seychelles","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SYC/Slope/syc_srtm_slope_100m.tif","SRTM slope 2000"
60439,694,"SLE","Sierra Leone","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SLE/Slope/sle_srtm_slope_100m.tif","SRTM slope 2000"
60440,702,"SGP","Singapore","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SGP/Slope/sgp_srtm_slope_100m.tif","SRTM slope 2000"
60441,703,"SVK","Slovakia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SVK/Slope/svk_srtm_slope_100m.tif","SRTM slope 2000"
60442,704,"VNM","Vietnam","srtm_slope_100m","GIS/Covariates/Global_2000_2020/VNM/Slope/vnm_srtm_slope_100m.tif","SRTM slope 2000"
60443,705,"SVN","Slovenia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SVN/Slope/svn_srtm_slope_100m.tif","SRTM slope 2000"
60444,706,"SOM","Somalia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SOM/Slope/som_srtm_slope_100m.tif","SRTM slope 2000"
60445,710,"ZAF","South Africa","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ZAF/Slope/zaf_srtm_slope_100m.tif","SRTM slope 2000"
60446,716,"ZWE","Zimbabwe","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ZWE/Slope/zwe_srtm_slope_100m.tif","SRTM slope 2000"
60447,724,"ESP","Spain","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ESP/Slope/esp_srtm_slope_100m.tif","SRTM slope 2000"
60448,728,"SSD","South Sudan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SSD/Slope/ssd_srtm_slope_100m.tif","SRTM slope 2000"
60449,729,"SDN","Sudan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SDN/Slope/sdn_srtm_slope_100m.tif","SRTM slope 2000"
60450,732,"ESH","Western Sahara","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ESH/Slope/esh_srtm_slope_100m.tif","SRTM slope 2000"
60451,740,"SUR","Suriname","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SUR/Slope/sur_srtm_slope_100m.tif","SRTM slope 2000"
60452,744,"SJM","Svalbard and Jan Mayen Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SJM/Slope/sjm_srtm_slope_100m.tif","SRTM slope 2000"
60453,748,"SWZ","Swaziland","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SWZ/Slope/swz_srtm_slope_100m.tif","SRTM slope 2000"
60454,752,"SWE","Sweden","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SWE/Slope/swe_srtm_slope_100m.tif","SRTM slope 2000"
60455,756,"CHE","Switzerland","srtm_slope_100m","GIS/Covariates/Global_2000_2020/CHE/Slope/che_srtm_slope_100m.tif","SRTM slope 2000"
60456,760,"SYR","Syria","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SYR/Slope/syr_srtm_slope_100m.tif","SRTM slope 2000"
60457,762,"TJK","Tajikistan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TJK/Slope/tjk_srtm_slope_100m.tif","SRTM slope 2000"
60458,764,"THA","Thailand","srtm_slope_100m","GIS/Covariates/Global_2000_2020/THA/Slope/tha_srtm_slope_100m.tif","SRTM slope 2000"
60459,768,"TGO","Togo","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TGO/Slope/tgo_srtm_slope_100m.tif","SRTM slope 2000"
60460,772,"TKL","Tokelau","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TKL/Slope/tkl_srtm_slope_100m.tif","SRTM slope 2000"
60461,776,"TON","Tonga","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TON/Slope/ton_srtm_slope_100m.tif","SRTM slope 2000"
60462,780,"TTO","Trinidad and Tobago","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TTO/Slope/tto_srtm_slope_100m.tif","SRTM slope 2000"
60463,784,"ARE","United Arab Emirates","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ARE/Slope/are_srtm_slope_100m.tif","SRTM slope 2000"
60464,788,"TUN","Tunisia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TUN/Slope/tun_srtm_slope_100m.tif","SRTM slope 2000"
60465,792,"TUR","Turkey","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TUR/Slope/tur_srtm_slope_100m.tif","SRTM slope 2000"
60466,795,"TKM","Turkmenistan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TKM/Slope/tkm_srtm_slope_100m.tif","SRTM slope 2000"
60467,796,"TCA","Turks and Caicos Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TCA/Slope/tca_srtm_slope_100m.tif","SRTM slope 2000"
60468,798,"TUV","Tuvalu","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TUV/Slope/tuv_srtm_slope_100m.tif","SRTM slope 2000"
60469,800,"UGA","Uganda","srtm_slope_100m","GIS/Covariates/Global_2000_2020/UGA/Slope/uga_srtm_slope_100m.tif","SRTM slope 2000"
60470,804,"UKR","Ukraine","srtm_slope_100m","GIS/Covariates/Global_2000_2020/UKR/Slope/ukr_srtm_slope_100m.tif","SRTM slope 2000"
60471,807,"MKD","Macedonia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/MKD/Slope/mkd_srtm_slope_100m.tif","SRTM slope 2000"
60472,818,"EGY","Egypt","srtm_slope_100m","GIS/Covariates/Global_2000_2020/EGY/Slope/egy_srtm_slope_100m.tif","SRTM slope 2000"
60473,826,"GBR","United Kingdom","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GBR/Slope/gbr_srtm_slope_100m.tif","SRTM slope 2000"
60474,831,"GGY","Guernsey","srtm_slope_100m","GIS/Covariates/Global_2000_2020/GGY/Slope/ggy_srtm_slope_100m.tif","SRTM slope 2000"
60475,832,"JEY","Jersey","srtm_slope_100m","GIS/Covariates/Global_2000_2020/JEY/Slope/jey_srtm_slope_100m.tif","SRTM slope 2000"
60476,833,"IMN","Isle of Man","srtm_slope_100m","GIS/Covariates/Global_2000_2020/IMN/Slope/imn_srtm_slope_100m.tif","SRTM slope 2000"
60477,834,"TZA","Tanzania","srtm_slope_100m","GIS/Covariates/Global_2000_2020/TZA/Slope/tza_srtm_slope_100m.tif","SRTM slope 2000"
60478,854,"BFA","Burkina Faso","srtm_slope_100m","GIS/Covariates/Global_2000_2020/BFA/Slope/bfa_srtm_slope_100m.tif","SRTM slope 2000"
60479,858,"URY","Uruguay","srtm_slope_100m","GIS/Covariates/Global_2000_2020/URY/Slope/ury_srtm_slope_100m.tif","SRTM slope 2000"
60480,860,"UZB","Uzbekistan","srtm_slope_100m","GIS/Covariates/Global_2000_2020/UZB/Slope/uzb_srtm_slope_100m.tif","SRTM slope 2000"
60481,862,"VEN","Venezuela","srtm_slope_100m","GIS/Covariates/Global_2000_2020/VEN/Slope/ven_srtm_slope_100m.tif","SRTM slope 2000"
60482,876,"WLF","Wallis and Futuna","srtm_slope_100m","GIS/Covariates/Global_2000_2020/WLF/Slope/wlf_srtm_slope_100m.tif","SRTM slope 2000"
60483,882,"WSM","Samoa","srtm_slope_100m","GIS/Covariates/Global_2000_2020/WSM/Slope/wsm_srtm_slope_100m.tif","SRTM slope 2000"
60484,887,"YEM","Yemen","srtm_slope_100m","GIS/Covariates/Global_2000_2020/YEM/Slope/yem_srtm_slope_100m.tif","SRTM slope 2000"
60485,894,"ZMB","Zambia","srtm_slope_100m","GIS/Covariates/Global_2000_2020/ZMB/Slope/zmb_srtm_slope_100m.tif","SRTM slope 2000"
60486,900,"KOS","Kosovo","srtm_slope_100m","GIS/Covariates/Global_2000_2020/KOS/Slope/kos_srtm_slope_100m.tif","SRTM slope 2000"
60487,901,"SPR","Spratly Islands","srtm_slope_100m","GIS/Covariates/Global_2000_2020/SPR/Slope/spr_srtm_slope_100m.tif","SRTM slope 2000"
60488,643,"RUS","Russia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/RUS/Topo/rus_srtm_topo_100m.tif","SRTM elevation 2000"
60489,360,"IDN","Indonesia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/IDN/Topo/idn_srtm_topo_100m.tif","SRTM elevation 2000"
60490,840,"USA","United States","srtm_topo_100m","GIS/Covariates/Global_2000_2020/USA/Topo/usa_srtm_topo_100m.tif","SRTM elevation 2000"
60491,850,"VIR","Virgin_Islands_U_S","srtm_topo_100m","GIS/Covariates/Global_2000_2020/VIR/Topo/vir_srtm_topo_100m.tif","SRTM elevation 2000"
60492,304,"GRL","Greenland","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GRL/Topo/grl_srtm_topo_100m.tif","SRTM elevation 2000"
60493,156,"CHN","China","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CHN/Topo/chn_srtm_topo_100m.tif","SRTM elevation 2000"
60494,36,"AUS","Australia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/AUS/Topo/aus_srtm_topo_100m.tif","SRTM elevation 2000"
60495,76,"BRA","Brazil","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BRA/Topo/bra_srtm_topo_100m.tif","SRTM elevation 2000"
60496,124,"CAN","Canada","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CAN/Topo/can_srtm_topo_100m.tif","SRTM elevation 2000"
60497,152,"CHL","Chile","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CHL/Topo/chl_srtm_topo_100m.tif","SRTM elevation 2000"
60498,4,"AFG","Afghanistan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/AFG/Topo/afg_srtm_topo_100m.tif","SRTM elevation 2000"
60499,8,"ALB","Albania","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ALB/Topo/alb_srtm_topo_100m.tif","SRTM elevation 2000"
60500,10,"ATA","Antarctica","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ATA/Topo/ata_srtm_topo_100m.tif","SRTM elevation 2000"
60501,12,"DZA","Algeria","srtm_topo_100m","GIS/Covariates/Global_2000_2020/DZA/Topo/dza_srtm_topo_100m.tif","SRTM elevation 2000"
60502,16,"ASM","American Samoa","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ASM/Topo/asm_srtm_topo_100m.tif","SRTM elevation 2000"
60503,20,"AND","Andorra","srtm_topo_100m","GIS/Covariates/Global_2000_2020/AND/Topo/and_srtm_topo_100m.tif","SRTM elevation 2000"
60504,24,"AGO","Angola","srtm_topo_100m","GIS/Covariates/Global_2000_2020/AGO/Topo/ago_srtm_topo_100m.tif","SRTM elevation 2000"
60505,28,"ATG","Antigua and Barbuda","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ATG/Topo/atg_srtm_topo_100m.tif","SRTM elevation 2000"
60506,31,"AZE","Azerbaijan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/AZE/Topo/aze_srtm_topo_100m.tif","SRTM elevation 2000"
60507,32,"ARG","Argentina","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ARG/Topo/arg_srtm_topo_100m.tif","SRTM elevation 2000"
60508,40,"AUT","Austria","srtm_topo_100m","GIS/Covariates/Global_2000_2020/AUT/Topo/aut_srtm_topo_100m.tif","SRTM elevation 2000"
60509,44,"BHS","Bahamas","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BHS/Topo/bhs_srtm_topo_100m.tif","SRTM elevation 2000"
60510,48,"BHR","Bahrain","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BHR/Topo/bhr_srtm_topo_100m.tif","SRTM elevation 2000"
60511,50,"BGD","Bangladesh","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BGD/Topo/bgd_srtm_topo_100m.tif","SRTM elevation 2000"
60512,51,"ARM","Armenia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ARM/Topo/arm_srtm_topo_100m.tif","SRTM elevation 2000"
60513,52,"BRB","Barbados","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BRB/Topo/brb_srtm_topo_100m.tif","SRTM elevation 2000"
60514,56,"BEL","Belgium","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BEL/Topo/bel_srtm_topo_100m.tif","SRTM elevation 2000"
60515,60,"BMU","Bermuda","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BMU/Topo/bmu_srtm_topo_100m.tif","SRTM elevation 2000"
60516,64,"BTN","Bhutan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BTN/Topo/btn_srtm_topo_100m.tif","SRTM elevation 2000"
60517,68,"BOL","Bolivia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BOL/Topo/bol_srtm_topo_100m.tif","SRTM elevation 2000"
60518,70,"BIH","Bosnia and Herzegovina","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BIH/Topo/bih_srtm_topo_100m.tif","SRTM elevation 2000"
60519,72,"BWA","Botswana","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BWA/Topo/bwa_srtm_topo_100m.tif","SRTM elevation 2000"
60520,74,"BVT","Bouvet Island","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BVT/Topo/bvt_srtm_topo_100m.tif","SRTM elevation 2000"
60521,84,"BLZ","Belize","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BLZ/Topo/blz_srtm_topo_100m.tif","SRTM elevation 2000"
60522,86,"IOT","British Indian Ocean Territory","srtm_topo_100m","GIS/Covariates/Global_2000_2020/IOT/Topo/iot_srtm_topo_100m.tif","SRTM elevation 2000"
60523,90,"SLB","Solomon Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SLB/Topo/slb_srtm_topo_100m.tif","SRTM elevation 2000"
60524,92,"VGB","British Virgin Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/VGB/Topo/vgb_srtm_topo_100m.tif","SRTM elevation 2000"
60525,96,"BRN","Brunei","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BRN/Topo/brn_srtm_topo_100m.tif","SRTM elevation 2000"
60526,100,"BGR","Bulgaria","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BGR/Topo/bgr_srtm_topo_100m.tif","SRTM elevation 2000"
60527,104,"MMR","Myanmar","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MMR/Topo/mmr_srtm_topo_100m.tif","SRTM elevation 2000"
60528,108,"BDI","Burundi","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BDI/Topo/bdi_srtm_topo_100m.tif","SRTM elevation 2000"
60529,112,"BLR","Belarus","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BLR/Topo/blr_srtm_topo_100m.tif","SRTM elevation 2000"
60530,116,"KHM","Cambodia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/KHM/Topo/khm_srtm_topo_100m.tif","SRTM elevation 2000"
60531,120,"CMR","Cameroon","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CMR/Topo/cmr_srtm_topo_100m.tif","SRTM elevation 2000"
60532,132,"CPV","Cape Verde","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CPV/Topo/cpv_srtm_topo_100m.tif","SRTM elevation 2000"
60533,136,"CYM","Cayman Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CYM/Topo/cym_srtm_topo_100m.tif","SRTM elevation 2000"
60534,140,"CAF","Central African Republic","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CAF/Topo/caf_srtm_topo_100m.tif","SRTM elevation 2000"
60535,144,"LKA","Sri Lanka","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LKA/Topo/lka_srtm_topo_100m.tif","SRTM elevation 2000"
60536,148,"TCD","Chad","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TCD/Topo/tcd_srtm_topo_100m.tif","SRTM elevation 2000"
60537,158,"TWN","Taiwan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TWN/Topo/twn_srtm_topo_100m.tif","SRTM elevation 2000"
60538,170,"COL","Colombia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/COL/Topo/col_srtm_topo_100m.tif","SRTM elevation 2000"
60539,174,"COM","Comoros","srtm_topo_100m","GIS/Covariates/Global_2000_2020/COM/Topo/com_srtm_topo_100m.tif","SRTM elevation 2000"
60540,175,"MYT","Mayotte","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MYT/Topo/myt_srtm_topo_100m.tif","SRTM elevation 2000"
60541,178,"COG","Republic of Congo","srtm_topo_100m","GIS/Covariates/Global_2000_2020/COG/Topo/cog_srtm_topo_100m.tif","SRTM elevation 2000"
60542,180,"COD","Democratic Republic of the Congo","srtm_topo_100m","GIS/Covariates/Global_2000_2020/COD/Topo/cod_srtm_topo_100m.tif","SRTM elevation 2000"
60543,184,"COK","Cook Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/COK/Topo/cok_srtm_topo_100m.tif","SRTM elevation 2000"
60544,188,"CRI","Costa Rica","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CRI/Topo/cri_srtm_topo_100m.tif","SRTM elevation 2000"
60545,191,"HRV","Croatia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/HRV/Topo/hrv_srtm_topo_100m.tif","SRTM elevation 2000"
60546,192,"CUB","Cuba","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CUB/Topo/cub_srtm_topo_100m.tif","SRTM elevation 2000"
60547,196,"CYP","Cyprus","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CYP/Topo/cyp_srtm_topo_100m.tif","SRTM elevation 2000"
60548,203,"CZE","Czech Republic","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CZE/Topo/cze_srtm_topo_100m.tif","SRTM elevation 2000"
60549,204,"BEN","Benin","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BEN/Topo/ben_srtm_topo_100m.tif","SRTM elevation 2000"
60550,208,"DNK","Denmark","srtm_topo_100m","GIS/Covariates/Global_2000_2020/DNK/Topo/dnk_srtm_topo_100m.tif","SRTM elevation 2000"
60551,212,"DMA","Dominica","srtm_topo_100m","GIS/Covariates/Global_2000_2020/DMA/Topo/dma_srtm_topo_100m.tif","SRTM elevation 2000"
60552,214,"DOM","Dominican Republic","srtm_topo_100m","GIS/Covariates/Global_2000_2020/DOM/Topo/dom_srtm_topo_100m.tif","SRTM elevation 2000"
60553,218,"ECU","Ecuador","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ECU/Topo/ecu_srtm_topo_100m.tif","SRTM elevation 2000"
60554,222,"SLV","El Salvador","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SLV/Topo/slv_srtm_topo_100m.tif","SRTM elevation 2000"
60555,226,"GNQ","Equatorial Guinea","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GNQ/Topo/gnq_srtm_topo_100m.tif","SRTM elevation 2000"
60556,231,"ETH","Ethiopia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ETH/Topo/eth_srtm_topo_100m.tif","SRTM elevation 2000"
60557,232,"ERI","Eritrea","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ERI/Topo/eri_srtm_topo_100m.tif","SRTM elevation 2000"
60558,233,"EST","Estonia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/EST/Topo/est_srtm_topo_100m.tif","SRTM elevation 2000"
60559,234,"FRO","Faroe Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/FRO/Topo/fro_srtm_topo_100m.tif","SRTM elevation 2000"
60560,238,"FLK","Falkland Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/FLK/Topo/flk_srtm_topo_100m.tif","SRTM elevation 2000"
60561,239,"SGS","South Georgia and the South Sandwich Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SGS/Topo/sgs_srtm_topo_100m.tif","SRTM elevation 2000"
60562,242,"FJI","Fiji","srtm_topo_100m","GIS/Covariates/Global_2000_2020/FJI/Topo/fji_srtm_topo_100m.tif","SRTM elevation 2000"
60563,246,"FIN","Finland","srtm_topo_100m","GIS/Covariates/Global_2000_2020/FIN/Topo/fin_srtm_topo_100m.tif","SRTM elevation 2000"
60564,248,"ALA","Aland Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ALA/Topo/ala_srtm_topo_100m.tif","SRTM elevation 2000"
60565,250,"FRA","France","srtm_topo_100m","GIS/Covariates/Global_2000_2020/FRA/Topo/fra_srtm_topo_100m.tif","SRTM elevation 2000"
60566,254,"GUF","French Guiana","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GUF/Topo/guf_srtm_topo_100m.tif","SRTM elevation 2000"
60567,258,"PYF","French Polynesia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PYF/Topo/pyf_srtm_topo_100m.tif","SRTM elevation 2000"
60568,260,"ATF","French Southern Territories","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ATF/Topo/atf_srtm_topo_100m.tif","SRTM elevation 2000"
60569,262,"DJI","Djibouti","srtm_topo_100m","GIS/Covariates/Global_2000_2020/DJI/Topo/dji_srtm_topo_100m.tif","SRTM elevation 2000"
60570,266,"GAB","Gabon","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GAB/Topo/gab_srtm_topo_100m.tif","SRTM elevation 2000"
60571,268,"GEO","Georgia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GEO/Topo/geo_srtm_topo_100m.tif","SRTM elevation 2000"
60572,270,"GMB","Gambia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GMB/Topo/gmb_srtm_topo_100m.tif","SRTM elevation 2000"
60573,275,"PSE","Palestina","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PSE/Topo/pse_srtm_topo_100m.tif","SRTM elevation 2000"
60574,276,"DEU","Germany","srtm_topo_100m","GIS/Covariates/Global_2000_2020/DEU/Topo/deu_srtm_topo_100m.tif","SRTM elevation 2000"
60575,288,"GHA","Ghana","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GHA/Topo/gha_srtm_topo_100m.tif","SRTM elevation 2000"
60576,292,"GIB","Gibraltar","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GIB/Topo/gib_srtm_topo_100m.tif","SRTM elevation 2000"
60577,296,"KIR","Kiribati","srtm_topo_100m","GIS/Covariates/Global_2000_2020/KIR/Topo/kir_srtm_topo_100m.tif","SRTM elevation 2000"
60578,300,"GRC","Greece","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GRC/Topo/grc_srtm_topo_100m.tif","SRTM elevation 2000"
60579,308,"GRD","Grenada","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GRD/Topo/grd_srtm_topo_100m.tif","SRTM elevation 2000"
60580,312,"GLP","Guadeloupe","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GLP/Topo/glp_srtm_topo_100m.tif","SRTM elevation 2000"
60581,316,"GUM","Guam","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GUM/Topo/gum_srtm_topo_100m.tif","SRTM elevation 2000"
60582,320,"GTM","Guatemala","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GTM/Topo/gtm_srtm_topo_100m.tif","SRTM elevation 2000"
60583,324,"GIN","Guinea","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GIN/Topo/gin_srtm_topo_100m.tif","SRTM elevation 2000"
60584,328,"GUY","Guyana","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GUY/Topo/guy_srtm_topo_100m.tif","SRTM elevation 2000"
60585,332,"HTI","Haiti","srtm_topo_100m","GIS/Covariates/Global_2000_2020/HTI/Topo/hti_srtm_topo_100m.tif","SRTM elevation 2000"
60586,334,"HMD","Heard Island and McDonald Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/HMD/Topo/hmd_srtm_topo_100m.tif","SRTM elevation 2000"
60587,336,"VAT","Vatican City","srtm_topo_100m","GIS/Covariates/Global_2000_2020/VAT/Topo/vat_srtm_topo_100m.tif","SRTM elevation 2000"
60588,340,"HND","Honduras","srtm_topo_100m","GIS/Covariates/Global_2000_2020/HND/Topo/hnd_srtm_topo_100m.tif","SRTM elevation 2000"
60589,344,"HKG","Hong Kong","srtm_topo_100m","GIS/Covariates/Global_2000_2020/HKG/Topo/hkg_srtm_topo_100m.tif","SRTM elevation 2000"
60590,348,"HUN","Hungary","srtm_topo_100m","GIS/Covariates/Global_2000_2020/HUN/Topo/hun_srtm_topo_100m.tif","SRTM elevation 2000"
60591,352,"ISL","Iceland","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ISL/Topo/isl_srtm_topo_100m.tif","SRTM elevation 2000"
60592,356,"IND","India","srtm_topo_100m","GIS/Covariates/Global_2000_2020/IND/Topo/ind_srtm_topo_100m.tif","SRTM elevation 2000"
60593,364,"IRN","Iran","srtm_topo_100m","GIS/Covariates/Global_2000_2020/IRN/Topo/irn_srtm_topo_100m.tif","SRTM elevation 2000"
60594,368,"IRQ","Iraq","srtm_topo_100m","GIS/Covariates/Global_2000_2020/IRQ/Topo/irq_srtm_topo_100m.tif","SRTM elevation 2000"
60595,372,"IRL","Ireland","srtm_topo_100m","GIS/Covariates/Global_2000_2020/IRL/Topo/irl_srtm_topo_100m.tif","SRTM elevation 2000"
60596,376,"ISR","Israel","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ISR/Topo/isr_srtm_topo_100m.tif","SRTM elevation 2000"
60597,380,"ITA","Italy","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ITA/Topo/ita_srtm_topo_100m.tif","SRTM elevation 2000"
60598,384,"CIV","CIte dIvoire","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CIV/Topo/civ_srtm_topo_100m.tif","SRTM elevation 2000"
60599,388,"JAM","Jamaica","srtm_topo_100m","GIS/Covariates/Global_2000_2020/JAM/Topo/jam_srtm_topo_100m.tif","SRTM elevation 2000"
60600,392,"JPN","Japan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/JPN/Topo/jpn_srtm_topo_100m.tif","SRTM elevation 2000"
60601,398,"KAZ","Kazakhstan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/KAZ/Topo/kaz_srtm_topo_100m.tif","SRTM elevation 2000"
60602,400,"JOR","Jordan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/JOR/Topo/jor_srtm_topo_100m.tif","SRTM elevation 2000"
60603,404,"KEN","Kenya","srtm_topo_100m","GIS/Covariates/Global_2000_2020/KEN/Topo/ken_srtm_topo_100m.tif","SRTM elevation 2000"
60604,408,"PRK","North Korea","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PRK/Topo/prk_srtm_topo_100m.tif","SRTM elevation 2000"
60605,410,"KOR","South Korea","srtm_topo_100m","GIS/Covariates/Global_2000_2020/KOR/Topo/kor_srtm_topo_100m.tif","SRTM elevation 2000"
60606,414,"KWT","Kuwait","srtm_topo_100m","GIS/Covariates/Global_2000_2020/KWT/Topo/kwt_srtm_topo_100m.tif","SRTM elevation 2000"
60607,417,"KGZ","Kyrgyzstan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/KGZ/Topo/kgz_srtm_topo_100m.tif","SRTM elevation 2000"
60608,418,"LAO","Laos","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LAO/Topo/lao_srtm_topo_100m.tif","SRTM elevation 2000"
60609,422,"LBN","Lebanon","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LBN/Topo/lbn_srtm_topo_100m.tif","SRTM elevation 2000"
60610,426,"LSO","Lesotho","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LSO/Topo/lso_srtm_topo_100m.tif","SRTM elevation 2000"
60611,428,"LVA","Latvia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LVA/Topo/lva_srtm_topo_100m.tif","SRTM elevation 2000"
60612,430,"LBR","Liberia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LBR/Topo/lbr_srtm_topo_100m.tif","SRTM elevation 2000"
60613,434,"LBY","Libya","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LBY/Topo/lby_srtm_topo_100m.tif","SRTM elevation 2000"
60614,438,"LIE","Liechtenstein","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LIE/Topo/lie_srtm_topo_100m.tif","SRTM elevation 2000"
60615,440,"LTU","Lithuania","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LTU/Topo/ltu_srtm_topo_100m.tif","SRTM elevation 2000"
60616,442,"LUX","Luxembourg","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LUX/Topo/lux_srtm_topo_100m.tif","SRTM elevation 2000"
60617,446,"MAC","Macao","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MAC/Topo/mac_srtm_topo_100m.tif","SRTM elevation 2000"
60618,450,"MDG","Madagascar","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MDG/Topo/mdg_srtm_topo_100m.tif","SRTM elevation 2000"
60619,454,"MWI","Malawi","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MWI/Topo/mwi_srtm_topo_100m.tif","SRTM elevation 2000"
60620,458,"MYS","Malaysia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MYS/Topo/mys_srtm_topo_100m.tif","SRTM elevation 2000"
60621,462,"MDV","Maldives","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MDV/Topo/mdv_srtm_topo_100m.tif","SRTM elevation 2000"
60622,466,"MLI","Mali","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MLI/Topo/mli_srtm_topo_100m.tif","SRTM elevation 2000"
60623,470,"MLT","Malta","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MLT/Topo/mlt_srtm_topo_100m.tif","SRTM elevation 2000"
60624,474,"MTQ","Martinique","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MTQ/Topo/mtq_srtm_topo_100m.tif","SRTM elevation 2000"
60625,478,"MRT","Mauritania","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MRT/Topo/mrt_srtm_topo_100m.tif","SRTM elevation 2000"
60626,480,"MUS","Mauritius","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MUS/Topo/mus_srtm_topo_100m.tif","SRTM elevation 2000"
60627,484,"MEX","Mexico","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MEX/Topo/mex_srtm_topo_100m.tif","SRTM elevation 2000"
60628,492,"MCO","Monaco","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MCO/Topo/mco_srtm_topo_100m.tif","SRTM elevation 2000"
60629,496,"MNG","Mongolia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MNG/Topo/mng_srtm_topo_100m.tif","SRTM elevation 2000"
60630,498,"MDA","Moldova","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MDA/Topo/mda_srtm_topo_100m.tif","SRTM elevation 2000"
60631,499,"MNE","Montenegro","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MNE/Topo/mne_srtm_topo_100m.tif","SRTM elevation 2000"
60632,500,"MSR","Montserrat","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MSR/Topo/msr_srtm_topo_100m.tif","SRTM elevation 2000"
60633,504,"MAR","Morocco","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MAR/Topo/mar_srtm_topo_100m.tif","SRTM elevation 2000"
60634,508,"MOZ","Mozambique","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MOZ/Topo/moz_srtm_topo_100m.tif","SRTM elevation 2000"
60635,512,"OMN","Oman","srtm_topo_100m","GIS/Covariates/Global_2000_2020/OMN/Topo/omn_srtm_topo_100m.tif","SRTM elevation 2000"
60636,516,"NAM","Namibia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NAM/Topo/nam_srtm_topo_100m.tif","SRTM elevation 2000"
60637,520,"NRU","Nauru","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NRU/Topo/nru_srtm_topo_100m.tif","SRTM elevation 2000"
60638,524,"NPL","Nepal","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NPL/Topo/npl_srtm_topo_100m.tif","SRTM elevation 2000"
60639,528,"NLD","Netherlands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NLD/Topo/nld_srtm_topo_100m.tif","SRTM elevation 2000"
60640,531,"CUW","Curacao","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CUW/Topo/cuw_srtm_topo_100m.tif","SRTM elevation 2000"
60641,533,"ABW","Aruba","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ABW/Topo/abw_srtm_topo_100m.tif","SRTM elevation 2000"
60642,534,"SXM","Sint Maarten (Dutch part)","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SXM/Topo/sxm_srtm_topo_100m.tif","SRTM elevation 2000"
60643,535,"BES","Bonaire, Sint Eustatius and Saba","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BES/Topo/bes_srtm_topo_100m.tif","SRTM elevation 2000"
60644,540,"NCL","New Caledonia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NCL/Topo/ncl_srtm_topo_100m.tif","SRTM elevation 2000"
60645,548,"VUT","Vanuatu","srtm_topo_100m","GIS/Covariates/Global_2000_2020/VUT/Topo/vut_srtm_topo_100m.tif","SRTM elevation 2000"
60646,554,"NZL","New Zealand","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NZL/Topo/nzl_srtm_topo_100m.tif","SRTM elevation 2000"
60647,558,"NIC","Nicaragua","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NIC/Topo/nic_srtm_topo_100m.tif","SRTM elevation 2000"
60648,562,"NER","Niger","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NER/Topo/ner_srtm_topo_100m.tif","SRTM elevation 2000"
60649,566,"NGA","Nigeria","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NGA/Topo/nga_srtm_topo_100m.tif","SRTM elevation 2000"
60650,570,"NIU","Niue","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NIU/Topo/niu_srtm_topo_100m.tif","SRTM elevation 2000"
60651,574,"NFK","Norfolk Island","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NFK/Topo/nfk_srtm_topo_100m.tif","SRTM elevation 2000"
60652,578,"NOR","Norway","srtm_topo_100m","GIS/Covariates/Global_2000_2020/NOR/Topo/nor_srtm_topo_100m.tif","SRTM elevation 2000"
60653,580,"MNP","Northern Mariana Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MNP/Topo/mnp_srtm_topo_100m.tif","SRTM elevation 2000"
60654,581,"UMI","United States Minor Outlying Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/UMI/Topo/umi_srtm_topo_100m.tif","SRTM elevation 2000"
60655,583,"FSM","Micronesia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/FSM/Topo/fsm_srtm_topo_100m.tif","SRTM elevation 2000"
60656,584,"MHL","Marshall Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MHL/Topo/mhl_srtm_topo_100m.tif","SRTM elevation 2000"
60657,585,"PLW","Palau","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PLW/Topo/plw_srtm_topo_100m.tif","SRTM elevation 2000"
60658,586,"PAK","Pakistan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PAK/Topo/pak_srtm_topo_100m.tif","SRTM elevation 2000"
60659,591,"PAN","Panama","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PAN/Topo/pan_srtm_topo_100m.tif","SRTM elevation 2000"
60660,598,"PNG","Papua New Guinea","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PNG/Topo/png_srtm_topo_100m.tif","SRTM elevation 2000"
60661,600,"PRY","Paraguay","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PRY/Topo/pry_srtm_topo_100m.tif","SRTM elevation 2000"
60662,604,"PER","Peru","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PER/Topo/per_srtm_topo_100m.tif","SRTM elevation 2000"
60663,608,"PHL","Philippines","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PHL/Topo/phl_srtm_topo_100m.tif","SRTM elevation 2000"
60664,612,"PCN","Pitcairn Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PCN/Topo/pcn_srtm_topo_100m.tif","SRTM elevation 2000"
60665,616,"POL","Poland","srtm_topo_100m","GIS/Covariates/Global_2000_2020/POL/Topo/pol_srtm_topo_100m.tif","SRTM elevation 2000"
60666,620,"PRT","Portugal","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PRT/Topo/prt_srtm_topo_100m.tif","SRTM elevation 2000"
60667,624,"GNB","Guinea-Bissau","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GNB/Topo/gnb_srtm_topo_100m.tif","SRTM elevation 2000"
60668,626,"TLS","East Timor","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TLS/Topo/tls_srtm_topo_100m.tif","SRTM elevation 2000"
60669,630,"PRI","Puerto Rico","srtm_topo_100m","GIS/Covariates/Global_2000_2020/PRI/Topo/pri_srtm_topo_100m.tif","SRTM elevation 2000"
60670,634,"QAT","Qatar","srtm_topo_100m","GIS/Covariates/Global_2000_2020/QAT/Topo/qat_srtm_topo_100m.tif","SRTM elevation 2000"
60671,638,"REU","Reunion","srtm_topo_100m","GIS/Covariates/Global_2000_2020/REU/Topo/reu_srtm_topo_100m.tif","SRTM elevation 2000"
60672,642,"ROU","Romania","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ROU/Topo/rou_srtm_topo_100m.tif","SRTM elevation 2000"
60673,646,"RWA","Rwanda","srtm_topo_100m","GIS/Covariates/Global_2000_2020/RWA/Topo/rwa_srtm_topo_100m.tif","SRTM elevation 2000"
60674,652,"BLM","Saint Barthelemy","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BLM/Topo/blm_srtm_topo_100m.tif","SRTM elevation 2000"
60675,654,"SHN","Saint Helena","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SHN/Topo/shn_srtm_topo_100m.tif","SRTM elevation 2000"
60676,659,"KNA","Saint Kitts and Nevis","srtm_topo_100m","GIS/Covariates/Global_2000_2020/KNA/Topo/kna_srtm_topo_100m.tif","SRTM elevation 2000"
60677,660,"AIA","Anguilla","srtm_topo_100m","GIS/Covariates/Global_2000_2020/AIA/Topo/aia_srtm_topo_100m.tif","SRTM elevation 2000"
60678,662,"LCA","Saint Lucia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/LCA/Topo/lca_srtm_topo_100m.tif","SRTM elevation 2000"
60679,663,"MAF","Saint Martin (French part)","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MAF/Topo/maf_srtm_topo_100m.tif","SRTM elevation 2000"
60680,666,"SPM","Saint Pierre and Miquelon","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SPM/Topo/spm_srtm_topo_100m.tif","SRTM elevation 2000"
60681,670,"VCT","Saint Vincent and the Grenadines","srtm_topo_100m","GIS/Covariates/Global_2000_2020/VCT/Topo/vct_srtm_topo_100m.tif","SRTM elevation 2000"
60682,674,"SMR","San Marino","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SMR/Topo/smr_srtm_topo_100m.tif","SRTM elevation 2000"
60683,678,"STP","Sao Tome and Principe","srtm_topo_100m","GIS/Covariates/Global_2000_2020/STP/Topo/stp_srtm_topo_100m.tif","SRTM elevation 2000"
60684,682,"SAU","Saudi Arabia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SAU/Topo/sau_srtm_topo_100m.tif","SRTM elevation 2000"
60685,686,"SEN","Senegal","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SEN/Topo/sen_srtm_topo_100m.tif","SRTM elevation 2000"
60686,688,"SRB","Serbia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SRB/Topo/srb_srtm_topo_100m.tif","SRTM elevation 2000"
60687,690,"SYC","Seychelles","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SYC/Topo/syc_srtm_topo_100m.tif","SRTM elevation 2000"
60688,694,"SLE","Sierra Leone","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SLE/Topo/sle_srtm_topo_100m.tif","SRTM elevation 2000"
60689,702,"SGP","Singapore","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SGP/Topo/sgp_srtm_topo_100m.tif","SRTM elevation 2000"
60690,703,"SVK","Slovakia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SVK/Topo/svk_srtm_topo_100m.tif","SRTM elevation 2000"
60691,704,"VNM","Vietnam","srtm_topo_100m","GIS/Covariates/Global_2000_2020/VNM/Topo/vnm_srtm_topo_100m.tif","SRTM elevation 2000"
60692,705,"SVN","Slovenia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SVN/Topo/svn_srtm_topo_100m.tif","SRTM elevation 2000"
60693,706,"SOM","Somalia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SOM/Topo/som_srtm_topo_100m.tif","SRTM elevation 2000"
60694,710,"ZAF","South Africa","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ZAF/Topo/zaf_srtm_topo_100m.tif","SRTM elevation 2000"
60695,716,"ZWE","Zimbabwe","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ZWE/Topo/zwe_srtm_topo_100m.tif","SRTM elevation 2000"
60696,724,"ESP","Spain","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ESP/Topo/esp_srtm_topo_100m.tif","SRTM elevation 2000"
60697,728,"SSD","South Sudan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SSD/Topo/ssd_srtm_topo_100m.tif","SRTM elevation 2000"
60698,729,"SDN","Sudan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SDN/Topo/sdn_srtm_topo_100m.tif","SRTM elevation 2000"
60699,732,"ESH","Western Sahara","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ESH/Topo/esh_srtm_topo_100m.tif","SRTM elevation 2000"
60700,740,"SUR","Suriname","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SUR/Topo/sur_srtm_topo_100m.tif","SRTM elevation 2000"
60701,744,"SJM","Svalbard and Jan Mayen Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SJM/Topo/sjm_srtm_topo_100m.tif","SRTM elevation 2000"
60702,748,"SWZ","Swaziland","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SWZ/Topo/swz_srtm_topo_100m.tif","SRTM elevation 2000"
60703,752,"SWE","Sweden","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SWE/Topo/swe_srtm_topo_100m.tif","SRTM elevation 2000"
60704,756,"CHE","Switzerland","srtm_topo_100m","GIS/Covariates/Global_2000_2020/CHE/Topo/che_srtm_topo_100m.tif","SRTM elevation 2000"
60705,760,"SYR","Syria","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SYR/Topo/syr_srtm_topo_100m.tif","SRTM elevation 2000"
60706,762,"TJK","Tajikistan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TJK/Topo/tjk_srtm_topo_100m.tif","SRTM elevation 2000"
60707,764,"THA","Thailand","srtm_topo_100m","GIS/Covariates/Global_2000_2020/THA/Topo/tha_srtm_topo_100m.tif","SRTM elevation 2000"
60708,768,"TGO","Togo","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TGO/Topo/tgo_srtm_topo_100m.tif","SRTM elevation 2000"
60709,772,"TKL","Tokelau","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TKL/Topo/tkl_srtm_topo_100m.tif","SRTM elevation 2000"
60710,776,"TON","Tonga","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TON/Topo/ton_srtm_topo_100m.tif","SRTM elevation 2000"
60711,780,"TTO","Trinidad and Tobago","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TTO/Topo/tto_srtm_topo_100m.tif","SRTM elevation 2000"
60712,784,"ARE","United Arab Emirates","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ARE/Topo/are_srtm_topo_100m.tif","SRTM elevation 2000"
60713,788,"TUN","Tunisia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TUN/Topo/tun_srtm_topo_100m.tif","SRTM elevation 2000"
60714,792,"TUR","Turkey","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TUR/Topo/tur_srtm_topo_100m.tif","SRTM elevation 2000"
60715,795,"TKM","Turkmenistan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TKM/Topo/tkm_srtm_topo_100m.tif","SRTM elevation 2000"
60716,796,"TCA","Turks and Caicos Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TCA/Topo/tca_srtm_topo_100m.tif","SRTM elevation 2000"
60717,798,"TUV","Tuvalu","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TUV/Topo/tuv_srtm_topo_100m.tif","SRTM elevation 2000"
60718,800,"UGA","Uganda","srtm_topo_100m","GIS/Covariates/Global_2000_2020/UGA/Topo/uga_srtm_topo_100m.tif","SRTM elevation 2000"
60719,804,"UKR","Ukraine","srtm_topo_100m","GIS/Covariates/Global_2000_2020/UKR/Topo/ukr_srtm_topo_100m.tif","SRTM elevation 2000"
60720,807,"MKD","Macedonia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/MKD/Topo/mkd_srtm_topo_100m.tif","SRTM elevation 2000"
60721,818,"EGY","Egypt","srtm_topo_100m","GIS/Covariates/Global_2000_2020/EGY/Topo/egy_srtm_topo_100m.tif","SRTM elevation 2000"
60722,826,"GBR","United Kingdom","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GBR/Topo/gbr_srtm_topo_100m.tif","SRTM elevation 2000"
60723,831,"GGY","Guernsey","srtm_topo_100m","GIS/Covariates/Global_2000_2020/GGY/Topo/ggy_srtm_topo_100m.tif","SRTM elevation 2000"
60724,832,"JEY","Jersey","srtm_topo_100m","GIS/Covariates/Global_2000_2020/JEY/Topo/jey_srtm_topo_100m.tif","SRTM elevation 2000"
60725,833,"IMN","Isle of Man","srtm_topo_100m","GIS/Covariates/Global_2000_2020/IMN/Topo/imn_srtm_topo_100m.tif","SRTM elevation 2000"
60726,834,"TZA","Tanzania","srtm_topo_100m","GIS/Covariates/Global_2000_2020/TZA/Topo/tza_srtm_topo_100m.tif","SRTM elevation 2000"
60727,854,"BFA","Burkina Faso","srtm_topo_100m","GIS/Covariates/Global_2000_2020/BFA/Topo/bfa_srtm_topo_100m.tif","SRTM elevation 2000"
60728,858,"URY","Uruguay","srtm_topo_100m","GIS/Covariates/Global_2000_2020/URY/Topo/ury_srtm_topo_100m.tif","SRTM elevation 2000"
60729,860,"UZB","Uzbekistan","srtm_topo_100m","GIS/Covariates/Global_2000_2020/UZB/Topo/uzb_srtm_topo_100m.tif","SRTM elevation 2000"
60730,862,"VEN","Venezuela","srtm_topo_100m","GIS/Covariates/Global_2000_2020/VEN/Topo/ven_srtm_topo_100m.tif","SRTM elevation 2000"
60731,876,"WLF","Wallis and Futuna","srtm_topo_100m","GIS/Covariates/Global_2000_2020/WLF/Topo/wlf_srtm_topo_100m.tif","SRTM elevation 2000"
60732,882,"WSM","Samoa","srtm_topo_100m","GIS/Covariates/Global_2000_2020/WSM/Topo/wsm_srtm_topo_100m.tif","SRTM elevation 2000"
60733,887,"YEM","Yemen","srtm_topo_100m","GIS/Covariates/Global_2000_2020/YEM/Topo/yem_srtm_topo_100m.tif","SRTM elevation 2000"
60734,894,"ZMB","Zambia","srtm_topo_100m","GIS/Covariates/Global_2000_2020/ZMB/Topo/zmb_srtm_topo_100m.tif","SRTM elevation 2000"
60735,900,"KOS","Kosovo","srtm_topo_100m","GIS/Covariates/Global_2000_2020/KOS/Topo/kos_srtm_topo_100m.tif","SRTM elevation 2000"
60736,901,"SPR","Spratly Islands","srtm_topo_100m","GIS/Covariates/Global_2000_2020/SPR/Topo/spr_srtm_topo_100m.tif","SRTM elevation 2000"
60737,643,"RUS","Russia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/RUS/VIIRS/rus_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60738,643,"RUS","Russia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/RUS/VIIRS/rus_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60739,643,"RUS","Russia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/RUS/VIIRS/rus_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60740,643,"RUS","Russia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/RUS/VIIRS/rus_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60741,643,"RUS","Russia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/RUS/VIIRS/rus_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60742,360,"IDN","Indonesia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/IDN/VIIRS/idn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60743,360,"IDN","Indonesia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/IDN/VIIRS/idn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60744,360,"IDN","Indonesia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/IDN/VIIRS/idn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60745,360,"IDN","Indonesia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/IDN/VIIRS/idn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60746,360,"IDN","Indonesia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/IDN/VIIRS/idn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60747,840,"USA","United States","viirs_100m_2012","GIS/Covariates/Global_2000_2020/USA/VIIRS/usa_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60748,840,"USA","United States","viirs_100m_2013","GIS/Covariates/Global_2000_2020/USA/VIIRS/usa_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60749,840,"USA","United States","viirs_100m_2014","GIS/Covariates/Global_2000_2020/USA/VIIRS/usa_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60750,840,"USA","United States","viirs_100m_2015","GIS/Covariates/Global_2000_2020/USA/VIIRS/usa_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60751,840,"USA","United States","viirs_100m_2016","GIS/Covariates/Global_2000_2020/USA/VIIRS/usa_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60752,850,"VIR","Virgin_Islands_U_S","viirs_100m_2012","GIS/Covariates/Global_2000_2020/VIR/VIIRS/vir_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60753,850,"VIR","Virgin_Islands_U_S","viirs_100m_2013","GIS/Covariates/Global_2000_2020/VIR/VIIRS/vir_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60754,850,"VIR","Virgin_Islands_U_S","viirs_100m_2014","GIS/Covariates/Global_2000_2020/VIR/VIIRS/vir_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60755,850,"VIR","Virgin_Islands_U_S","viirs_100m_2015","GIS/Covariates/Global_2000_2020/VIR/VIIRS/vir_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60756,850,"VIR","Virgin_Islands_U_S","viirs_100m_2016","GIS/Covariates/Global_2000_2020/VIR/VIIRS/vir_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60757,304,"GRL","Greenland","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GRL/VIIRS/grl_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60758,304,"GRL","Greenland","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GRL/VIIRS/grl_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60759,304,"GRL","Greenland","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GRL/VIIRS/grl_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60760,304,"GRL","Greenland","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GRL/VIIRS/grl_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60761,304,"GRL","Greenland","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GRL/VIIRS/grl_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60762,156,"CHN","China","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CHN/VIIRS/chn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60763,156,"CHN","China","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CHN/VIIRS/chn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60764,156,"CHN","China","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CHN/VIIRS/chn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60765,156,"CHN","China","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CHN/VIIRS/chn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60766,156,"CHN","China","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CHN/VIIRS/chn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60767,36,"AUS","Australia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/AUS/VIIRS/aus_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60768,36,"AUS","Australia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/AUS/VIIRS/aus_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60769,36,"AUS","Australia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/AUS/VIIRS/aus_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60770,36,"AUS","Australia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/AUS/VIIRS/aus_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60771,36,"AUS","Australia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/AUS/VIIRS/aus_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60772,76,"BRA","Brazil","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BRA/VIIRS/bra_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60773,76,"BRA","Brazil","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BRA/VIIRS/bra_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60774,76,"BRA","Brazil","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BRA/VIIRS/bra_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60775,76,"BRA","Brazil","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BRA/VIIRS/bra_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60776,76,"BRA","Brazil","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BRA/VIIRS/bra_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60777,124,"CAN","Canada","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CAN/VIIRS/can_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60778,124,"CAN","Canada","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CAN/VIIRS/can_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60779,124,"CAN","Canada","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CAN/VIIRS/can_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60780,124,"CAN","Canada","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CAN/VIIRS/can_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60781,124,"CAN","Canada","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CAN/VIIRS/can_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60782,152,"CHL","Chile","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CHL/VIIRS/chl_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60783,152,"CHL","Chile","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CHL/VIIRS/chl_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60784,152,"CHL","Chile","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CHL/VIIRS/chl_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60785,152,"CHL","Chile","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CHL/VIIRS/chl_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60786,152,"CHL","Chile","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CHL/VIIRS/chl_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60787,4,"AFG","Afghanistan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/AFG/VIIRS/afg_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60788,4,"AFG","Afghanistan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/AFG/VIIRS/afg_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60789,4,"AFG","Afghanistan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/AFG/VIIRS/afg_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60790,4,"AFG","Afghanistan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/AFG/VIIRS/afg_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60791,4,"AFG","Afghanistan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/AFG/VIIRS/afg_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60792,8,"ALB","Albania","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ALB/VIIRS/alb_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60793,8,"ALB","Albania","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ALB/VIIRS/alb_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60794,8,"ALB","Albania","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ALB/VIIRS/alb_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60795,8,"ALB","Albania","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ALB/VIIRS/alb_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60796,8,"ALB","Albania","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ALB/VIIRS/alb_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60797,10,"ATA","Antarctica","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ATA/VIIRS/ata_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60798,10,"ATA","Antarctica","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ATA/VIIRS/ata_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60799,10,"ATA","Antarctica","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ATA/VIIRS/ata_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60800,10,"ATA","Antarctica","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ATA/VIIRS/ata_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60801,10,"ATA","Antarctica","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ATA/VIIRS/ata_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60802,12,"DZA","Algeria","viirs_100m_2012","GIS/Covariates/Global_2000_2020/DZA/VIIRS/dza_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60803,12,"DZA","Algeria","viirs_100m_2013","GIS/Covariates/Global_2000_2020/DZA/VIIRS/dza_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60804,12,"DZA","Algeria","viirs_100m_2014","GIS/Covariates/Global_2000_2020/DZA/VIIRS/dza_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60805,12,"DZA","Algeria","viirs_100m_2015","GIS/Covariates/Global_2000_2020/DZA/VIIRS/dza_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60806,12,"DZA","Algeria","viirs_100m_2016","GIS/Covariates/Global_2000_2020/DZA/VIIRS/dza_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60807,16,"ASM","American Samoa","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ASM/VIIRS/asm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60808,16,"ASM","American Samoa","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ASM/VIIRS/asm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60809,16,"ASM","American Samoa","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ASM/VIIRS/asm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60810,16,"ASM","American Samoa","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ASM/VIIRS/asm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60811,16,"ASM","American Samoa","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ASM/VIIRS/asm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60812,20,"AND","Andorra","viirs_100m_2012","GIS/Covariates/Global_2000_2020/AND/VIIRS/and_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60813,20,"AND","Andorra","viirs_100m_2013","GIS/Covariates/Global_2000_2020/AND/VIIRS/and_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60814,20,"AND","Andorra","viirs_100m_2014","GIS/Covariates/Global_2000_2020/AND/VIIRS/and_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60815,20,"AND","Andorra","viirs_100m_2015","GIS/Covariates/Global_2000_2020/AND/VIIRS/and_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60816,20,"AND","Andorra","viirs_100m_2016","GIS/Covariates/Global_2000_2020/AND/VIIRS/and_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60817,24,"AGO","Angola","viirs_100m_2012","GIS/Covariates/Global_2000_2020/AGO/VIIRS/ago_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60818,24,"AGO","Angola","viirs_100m_2013","GIS/Covariates/Global_2000_2020/AGO/VIIRS/ago_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60819,24,"AGO","Angola","viirs_100m_2014","GIS/Covariates/Global_2000_2020/AGO/VIIRS/ago_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60820,24,"AGO","Angola","viirs_100m_2015","GIS/Covariates/Global_2000_2020/AGO/VIIRS/ago_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60821,24,"AGO","Angola","viirs_100m_2016","GIS/Covariates/Global_2000_2020/AGO/VIIRS/ago_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60822,28,"ATG","Antigua and Barbuda","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ATG/VIIRS/atg_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60823,28,"ATG","Antigua and Barbuda","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ATG/VIIRS/atg_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60824,28,"ATG","Antigua and Barbuda","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ATG/VIIRS/atg_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60825,28,"ATG","Antigua and Barbuda","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ATG/VIIRS/atg_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60826,28,"ATG","Antigua and Barbuda","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ATG/VIIRS/atg_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60827,31,"AZE","Azerbaijan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/AZE/VIIRS/aze_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60828,31,"AZE","Azerbaijan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/AZE/VIIRS/aze_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60829,31,"AZE","Azerbaijan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/AZE/VIIRS/aze_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60830,31,"AZE","Azerbaijan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/AZE/VIIRS/aze_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60831,31,"AZE","Azerbaijan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/AZE/VIIRS/aze_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60832,32,"ARG","Argentina","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ARG/VIIRS/arg_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60833,32,"ARG","Argentina","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ARG/VIIRS/arg_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60834,32,"ARG","Argentina","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ARG/VIIRS/arg_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60835,32,"ARG","Argentina","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ARG/VIIRS/arg_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60836,32,"ARG","Argentina","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ARG/VIIRS/arg_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60837,40,"AUT","Austria","viirs_100m_2012","GIS/Covariates/Global_2000_2020/AUT/VIIRS/aut_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60838,40,"AUT","Austria","viirs_100m_2013","GIS/Covariates/Global_2000_2020/AUT/VIIRS/aut_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60839,40,"AUT","Austria","viirs_100m_2014","GIS/Covariates/Global_2000_2020/AUT/VIIRS/aut_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60840,40,"AUT","Austria","viirs_100m_2015","GIS/Covariates/Global_2000_2020/AUT/VIIRS/aut_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60841,40,"AUT","Austria","viirs_100m_2016","GIS/Covariates/Global_2000_2020/AUT/VIIRS/aut_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60842,44,"BHS","Bahamas","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BHS/VIIRS/bhs_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60843,44,"BHS","Bahamas","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BHS/VIIRS/bhs_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60844,44,"BHS","Bahamas","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BHS/VIIRS/bhs_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60845,44,"BHS","Bahamas","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BHS/VIIRS/bhs_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60846,44,"BHS","Bahamas","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BHS/VIIRS/bhs_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60847,48,"BHR","Bahrain","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BHR/VIIRS/bhr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60848,48,"BHR","Bahrain","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BHR/VIIRS/bhr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60849,48,"BHR","Bahrain","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BHR/VIIRS/bhr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60850,48,"BHR","Bahrain","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BHR/VIIRS/bhr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60851,48,"BHR","Bahrain","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BHR/VIIRS/bhr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60852,50,"BGD","Bangladesh","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BGD/VIIRS/bgd_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60853,50,"BGD","Bangladesh","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BGD/VIIRS/bgd_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60854,50,"BGD","Bangladesh","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BGD/VIIRS/bgd_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60855,50,"BGD","Bangladesh","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BGD/VIIRS/bgd_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60856,50,"BGD","Bangladesh","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BGD/VIIRS/bgd_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60857,51,"ARM","Armenia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ARM/VIIRS/arm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60858,51,"ARM","Armenia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ARM/VIIRS/arm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60859,51,"ARM","Armenia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ARM/VIIRS/arm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60860,51,"ARM","Armenia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ARM/VIIRS/arm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60861,51,"ARM","Armenia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ARM/VIIRS/arm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60862,52,"BRB","Barbados","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BRB/VIIRS/brb_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60863,52,"BRB","Barbados","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BRB/VIIRS/brb_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60864,52,"BRB","Barbados","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BRB/VIIRS/brb_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60865,52,"BRB","Barbados","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BRB/VIIRS/brb_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60866,52,"BRB","Barbados","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BRB/VIIRS/brb_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60867,56,"BEL","Belgium","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BEL/VIIRS/bel_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60868,56,"BEL","Belgium","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BEL/VIIRS/bel_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60869,56,"BEL","Belgium","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BEL/VIIRS/bel_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60870,56,"BEL","Belgium","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BEL/VIIRS/bel_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60871,56,"BEL","Belgium","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BEL/VIIRS/bel_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60872,60,"BMU","Bermuda","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BMU/VIIRS/bmu_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60873,60,"BMU","Bermuda","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BMU/VIIRS/bmu_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60874,60,"BMU","Bermuda","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BMU/VIIRS/bmu_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60875,60,"BMU","Bermuda","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BMU/VIIRS/bmu_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60876,60,"BMU","Bermuda","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BMU/VIIRS/bmu_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60877,64,"BTN","Bhutan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BTN/VIIRS/btn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60878,64,"BTN","Bhutan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BTN/VIIRS/btn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60879,64,"BTN","Bhutan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BTN/VIIRS/btn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60880,64,"BTN","Bhutan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BTN/VIIRS/btn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60881,64,"BTN","Bhutan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BTN/VIIRS/btn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60882,68,"BOL","Bolivia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BOL/VIIRS/bol_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60883,68,"BOL","Bolivia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BOL/VIIRS/bol_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60884,68,"BOL","Bolivia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BOL/VIIRS/bol_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60885,68,"BOL","Bolivia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BOL/VIIRS/bol_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60886,68,"BOL","Bolivia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BOL/VIIRS/bol_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60887,70,"BIH","Bosnia and Herzegovina","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BIH/VIIRS/bih_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60888,70,"BIH","Bosnia and Herzegovina","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BIH/VIIRS/bih_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60889,70,"BIH","Bosnia and Herzegovina","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BIH/VIIRS/bih_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60890,70,"BIH","Bosnia and Herzegovina","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BIH/VIIRS/bih_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60891,70,"BIH","Bosnia and Herzegovina","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BIH/VIIRS/bih_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60892,72,"BWA","Botswana","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BWA/VIIRS/bwa_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60893,72,"BWA","Botswana","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BWA/VIIRS/bwa_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60894,72,"BWA","Botswana","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BWA/VIIRS/bwa_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60895,72,"BWA","Botswana","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BWA/VIIRS/bwa_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60896,72,"BWA","Botswana","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BWA/VIIRS/bwa_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60897,74,"BVT","Bouvet Island","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BVT/VIIRS/bvt_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60898,74,"BVT","Bouvet Island","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BVT/VIIRS/bvt_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60899,74,"BVT","Bouvet Island","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BVT/VIIRS/bvt_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60900,74,"BVT","Bouvet Island","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BVT/VIIRS/bvt_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60901,74,"BVT","Bouvet Island","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BVT/VIIRS/bvt_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60902,84,"BLZ","Belize","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BLZ/VIIRS/blz_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60903,84,"BLZ","Belize","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BLZ/VIIRS/blz_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60904,84,"BLZ","Belize","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BLZ/VIIRS/blz_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60905,84,"BLZ","Belize","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BLZ/VIIRS/blz_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60906,84,"BLZ","Belize","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BLZ/VIIRS/blz_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60907,86,"IOT","British Indian Ocean Territory","viirs_100m_2012","GIS/Covariates/Global_2000_2020/IOT/VIIRS/iot_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60908,86,"IOT","British Indian Ocean Territory","viirs_100m_2013","GIS/Covariates/Global_2000_2020/IOT/VIIRS/iot_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60909,86,"IOT","British Indian Ocean Territory","viirs_100m_2014","GIS/Covariates/Global_2000_2020/IOT/VIIRS/iot_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60910,86,"IOT","British Indian Ocean Territory","viirs_100m_2015","GIS/Covariates/Global_2000_2020/IOT/VIIRS/iot_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60911,86,"IOT","British Indian Ocean Territory","viirs_100m_2016","GIS/Covariates/Global_2000_2020/IOT/VIIRS/iot_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60912,90,"SLB","Solomon Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SLB/VIIRS/slb_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60913,90,"SLB","Solomon Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SLB/VIIRS/slb_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60914,90,"SLB","Solomon Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SLB/VIIRS/slb_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60915,90,"SLB","Solomon Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SLB/VIIRS/slb_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60916,90,"SLB","Solomon Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SLB/VIIRS/slb_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60917,92,"VGB","British Virgin Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/VGB/VIIRS/vgb_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60918,92,"VGB","British Virgin Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/VGB/VIIRS/vgb_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60919,92,"VGB","British Virgin Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/VGB/VIIRS/vgb_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60920,92,"VGB","British Virgin Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/VGB/VIIRS/vgb_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60921,92,"VGB","British Virgin Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/VGB/VIIRS/vgb_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60922,96,"BRN","Brunei","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BRN/VIIRS/brn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60923,96,"BRN","Brunei","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BRN/VIIRS/brn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60924,96,"BRN","Brunei","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BRN/VIIRS/brn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60925,96,"BRN","Brunei","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BRN/VIIRS/brn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60926,96,"BRN","Brunei","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BRN/VIIRS/brn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60927,100,"BGR","Bulgaria","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BGR/VIIRS/bgr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60928,100,"BGR","Bulgaria","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BGR/VIIRS/bgr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60929,100,"BGR","Bulgaria","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BGR/VIIRS/bgr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60930,100,"BGR","Bulgaria","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BGR/VIIRS/bgr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60931,100,"BGR","Bulgaria","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BGR/VIIRS/bgr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60932,104,"MMR","Myanmar","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MMR/VIIRS/mmr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60933,104,"MMR","Myanmar","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MMR/VIIRS/mmr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60934,104,"MMR","Myanmar","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MMR/VIIRS/mmr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60935,104,"MMR","Myanmar","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MMR/VIIRS/mmr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60936,104,"MMR","Myanmar","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MMR/VIIRS/mmr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60937,108,"BDI","Burundi","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BDI/VIIRS/bdi_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60938,108,"BDI","Burundi","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BDI/VIIRS/bdi_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60939,108,"BDI","Burundi","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BDI/VIIRS/bdi_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60940,108,"BDI","Burundi","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BDI/VIIRS/bdi_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60941,108,"BDI","Burundi","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BDI/VIIRS/bdi_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60942,112,"BLR","Belarus","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BLR/VIIRS/blr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60943,112,"BLR","Belarus","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BLR/VIIRS/blr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60944,112,"BLR","Belarus","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BLR/VIIRS/blr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60945,112,"BLR","Belarus","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BLR/VIIRS/blr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60946,112,"BLR","Belarus","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BLR/VIIRS/blr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60947,116,"KHM","Cambodia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/KHM/VIIRS/khm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60948,116,"KHM","Cambodia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/KHM/VIIRS/khm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60949,116,"KHM","Cambodia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/KHM/VIIRS/khm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60950,116,"KHM","Cambodia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/KHM/VIIRS/khm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60951,116,"KHM","Cambodia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/KHM/VIIRS/khm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60952,120,"CMR","Cameroon","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CMR/VIIRS/cmr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60953,120,"CMR","Cameroon","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CMR/VIIRS/cmr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60954,120,"CMR","Cameroon","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CMR/VIIRS/cmr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60955,120,"CMR","Cameroon","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CMR/VIIRS/cmr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60956,120,"CMR","Cameroon","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CMR/VIIRS/cmr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60957,132,"CPV","Cape Verde","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CPV/VIIRS/cpv_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60958,132,"CPV","Cape Verde","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CPV/VIIRS/cpv_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60959,132,"CPV","Cape Verde","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CPV/VIIRS/cpv_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60960,132,"CPV","Cape Verde","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CPV/VIIRS/cpv_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60961,132,"CPV","Cape Verde","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CPV/VIIRS/cpv_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60962,136,"CYM","Cayman Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CYM/VIIRS/cym_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60963,136,"CYM","Cayman Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CYM/VIIRS/cym_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60964,136,"CYM","Cayman Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CYM/VIIRS/cym_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60965,136,"CYM","Cayman Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CYM/VIIRS/cym_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60966,136,"CYM","Cayman Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CYM/VIIRS/cym_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60967,140,"CAF","Central African Republic","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CAF/VIIRS/caf_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60968,140,"CAF","Central African Republic","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CAF/VIIRS/caf_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60969,140,"CAF","Central African Republic","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CAF/VIIRS/caf_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60970,140,"CAF","Central African Republic","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CAF/VIIRS/caf_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60971,140,"CAF","Central African Republic","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CAF/VIIRS/caf_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60972,144,"LKA","Sri Lanka","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LKA/VIIRS/lka_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60973,144,"LKA","Sri Lanka","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LKA/VIIRS/lka_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60974,144,"LKA","Sri Lanka","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LKA/VIIRS/lka_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60975,144,"LKA","Sri Lanka","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LKA/VIIRS/lka_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60976,144,"LKA","Sri Lanka","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LKA/VIIRS/lka_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60977,148,"TCD","Chad","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TCD/VIIRS/tcd_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60978,148,"TCD","Chad","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TCD/VIIRS/tcd_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60979,148,"TCD","Chad","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TCD/VIIRS/tcd_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60980,148,"TCD","Chad","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TCD/VIIRS/tcd_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60981,148,"TCD","Chad","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TCD/VIIRS/tcd_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60982,158,"TWN","Taiwan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TWN/VIIRS/twn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60983,158,"TWN","Taiwan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TWN/VIIRS/twn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60984,158,"TWN","Taiwan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TWN/VIIRS/twn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60985,158,"TWN","Taiwan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TWN/VIIRS/twn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60986,158,"TWN","Taiwan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TWN/VIIRS/twn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60987,170,"COL","Colombia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/COL/VIIRS/col_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60988,170,"COL","Colombia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/COL/VIIRS/col_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60989,170,"COL","Colombia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/COL/VIIRS/col_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60990,170,"COL","Colombia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/COL/VIIRS/col_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60991,170,"COL","Colombia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/COL/VIIRS/col_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60992,174,"COM","Comoros","viirs_100m_2012","GIS/Covariates/Global_2000_2020/COM/VIIRS/com_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60993,174,"COM","Comoros","viirs_100m_2013","GIS/Covariates/Global_2000_2020/COM/VIIRS/com_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60994,174,"COM","Comoros","viirs_100m_2014","GIS/Covariates/Global_2000_2020/COM/VIIRS/com_viirs_100m_2014.tif","VIIRS night-time lights 2014"
60995,174,"COM","Comoros","viirs_100m_2015","GIS/Covariates/Global_2000_2020/COM/VIIRS/com_viirs_100m_2015.tif","VIIRS night-time lights 2015"
60996,174,"COM","Comoros","viirs_100m_2016","GIS/Covariates/Global_2000_2020/COM/VIIRS/com_viirs_100m_2016.tif","VIIRS night-time lights 2016"
60997,175,"MYT","Mayotte","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MYT/VIIRS/myt_viirs_100m_2012.tif","VIIRS night-time lights 2012"
60998,175,"MYT","Mayotte","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MYT/VIIRS/myt_viirs_100m_2013.tif","VIIRS night-time lights 2013"
60999,175,"MYT","Mayotte","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MYT/VIIRS/myt_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61000,175,"MYT","Mayotte","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MYT/VIIRS/myt_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61001,175,"MYT","Mayotte","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MYT/VIIRS/myt_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61002,178,"COG","Republic of Congo","viirs_100m_2012","GIS/Covariates/Global_2000_2020/COG/VIIRS/cog_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61003,178,"COG","Republic of Congo","viirs_100m_2013","GIS/Covariates/Global_2000_2020/COG/VIIRS/cog_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61004,178,"COG","Republic of Congo","viirs_100m_2014","GIS/Covariates/Global_2000_2020/COG/VIIRS/cog_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61005,178,"COG","Republic of Congo","viirs_100m_2015","GIS/Covariates/Global_2000_2020/COG/VIIRS/cog_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61006,178,"COG","Republic of Congo","viirs_100m_2016","GIS/Covariates/Global_2000_2020/COG/VIIRS/cog_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61007,180,"COD","Democratic Republic of the Congo","viirs_100m_2012","GIS/Covariates/Global_2000_2020/COD/VIIRS/cod_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61008,180,"COD","Democratic Republic of the Congo","viirs_100m_2013","GIS/Covariates/Global_2000_2020/COD/VIIRS/cod_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61009,180,"COD","Democratic Republic of the Congo","viirs_100m_2014","GIS/Covariates/Global_2000_2020/COD/VIIRS/cod_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61010,180,"COD","Democratic Republic of the Congo","viirs_100m_2015","GIS/Covariates/Global_2000_2020/COD/VIIRS/cod_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61011,180,"COD","Democratic Republic of the Congo","viirs_100m_2016","GIS/Covariates/Global_2000_2020/COD/VIIRS/cod_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61012,184,"COK","Cook Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/COK/VIIRS/cok_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61013,184,"COK","Cook Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/COK/VIIRS/cok_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61014,184,"COK","Cook Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/COK/VIIRS/cok_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61015,184,"COK","Cook Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/COK/VIIRS/cok_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61016,184,"COK","Cook Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/COK/VIIRS/cok_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61017,188,"CRI","Costa Rica","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CRI/VIIRS/cri_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61018,188,"CRI","Costa Rica","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CRI/VIIRS/cri_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61019,188,"CRI","Costa Rica","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CRI/VIIRS/cri_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61020,188,"CRI","Costa Rica","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CRI/VIIRS/cri_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61021,188,"CRI","Costa Rica","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CRI/VIIRS/cri_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61022,191,"HRV","Croatia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/HRV/VIIRS/hrv_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61023,191,"HRV","Croatia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/HRV/VIIRS/hrv_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61024,191,"HRV","Croatia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/HRV/VIIRS/hrv_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61025,191,"HRV","Croatia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/HRV/VIIRS/hrv_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61026,191,"HRV","Croatia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/HRV/VIIRS/hrv_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61027,192,"CUB","Cuba","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CUB/VIIRS/cub_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61028,192,"CUB","Cuba","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CUB/VIIRS/cub_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61029,192,"CUB","Cuba","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CUB/VIIRS/cub_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61030,192,"CUB","Cuba","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CUB/VIIRS/cub_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61031,192,"CUB","Cuba","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CUB/VIIRS/cub_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61032,196,"CYP","Cyprus","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CYP/VIIRS/cyp_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61033,196,"CYP","Cyprus","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CYP/VIIRS/cyp_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61034,196,"CYP","Cyprus","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CYP/VIIRS/cyp_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61035,196,"CYP","Cyprus","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CYP/VIIRS/cyp_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61036,196,"CYP","Cyprus","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CYP/VIIRS/cyp_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61037,203,"CZE","Czech Republic","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CZE/VIIRS/cze_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61038,203,"CZE","Czech Republic","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CZE/VIIRS/cze_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61039,203,"CZE","Czech Republic","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CZE/VIIRS/cze_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61040,203,"CZE","Czech Republic","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CZE/VIIRS/cze_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61041,203,"CZE","Czech Republic","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CZE/VIIRS/cze_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61042,204,"BEN","Benin","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BEN/VIIRS/ben_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61043,204,"BEN","Benin","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BEN/VIIRS/ben_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61044,204,"BEN","Benin","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BEN/VIIRS/ben_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61045,204,"BEN","Benin","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BEN/VIIRS/ben_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61046,204,"BEN","Benin","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BEN/VIIRS/ben_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61047,208,"DNK","Denmark","viirs_100m_2012","GIS/Covariates/Global_2000_2020/DNK/VIIRS/dnk_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61048,208,"DNK","Denmark","viirs_100m_2013","GIS/Covariates/Global_2000_2020/DNK/VIIRS/dnk_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61049,208,"DNK","Denmark","viirs_100m_2014","GIS/Covariates/Global_2000_2020/DNK/VIIRS/dnk_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61050,208,"DNK","Denmark","viirs_100m_2015","GIS/Covariates/Global_2000_2020/DNK/VIIRS/dnk_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61051,208,"DNK","Denmark","viirs_100m_2016","GIS/Covariates/Global_2000_2020/DNK/VIIRS/dnk_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61052,212,"DMA","Dominica","viirs_100m_2012","GIS/Covariates/Global_2000_2020/DMA/VIIRS/dma_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61053,212,"DMA","Dominica","viirs_100m_2013","GIS/Covariates/Global_2000_2020/DMA/VIIRS/dma_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61054,212,"DMA","Dominica","viirs_100m_2014","GIS/Covariates/Global_2000_2020/DMA/VIIRS/dma_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61055,212,"DMA","Dominica","viirs_100m_2015","GIS/Covariates/Global_2000_2020/DMA/VIIRS/dma_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61056,212,"DMA","Dominica","viirs_100m_2016","GIS/Covariates/Global_2000_2020/DMA/VIIRS/dma_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61057,214,"DOM","Dominican Republic","viirs_100m_2012","GIS/Covariates/Global_2000_2020/DOM/VIIRS/dom_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61058,214,"DOM","Dominican Republic","viirs_100m_2013","GIS/Covariates/Global_2000_2020/DOM/VIIRS/dom_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61059,214,"DOM","Dominican Republic","viirs_100m_2014","GIS/Covariates/Global_2000_2020/DOM/VIIRS/dom_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61060,214,"DOM","Dominican Republic","viirs_100m_2015","GIS/Covariates/Global_2000_2020/DOM/VIIRS/dom_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61061,214,"DOM","Dominican Republic","viirs_100m_2016","GIS/Covariates/Global_2000_2020/DOM/VIIRS/dom_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61062,218,"ECU","Ecuador","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ECU/VIIRS/ecu_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61063,218,"ECU","Ecuador","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ECU/VIIRS/ecu_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61064,218,"ECU","Ecuador","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ECU/VIIRS/ecu_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61065,218,"ECU","Ecuador","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ECU/VIIRS/ecu_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61066,218,"ECU","Ecuador","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ECU/VIIRS/ecu_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61067,222,"SLV","El Salvador","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SLV/VIIRS/slv_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61068,222,"SLV","El Salvador","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SLV/VIIRS/slv_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61069,222,"SLV","El Salvador","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SLV/VIIRS/slv_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61070,222,"SLV","El Salvador","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SLV/VIIRS/slv_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61071,222,"SLV","El Salvador","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SLV/VIIRS/slv_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61072,226,"GNQ","Equatorial Guinea","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GNQ/VIIRS/gnq_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61073,226,"GNQ","Equatorial Guinea","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GNQ/VIIRS/gnq_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61074,226,"GNQ","Equatorial Guinea","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GNQ/VIIRS/gnq_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61075,226,"GNQ","Equatorial Guinea","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GNQ/VIIRS/gnq_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61076,226,"GNQ","Equatorial Guinea","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GNQ/VIIRS/gnq_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61077,231,"ETH","Ethiopia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ETH/VIIRS/eth_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61078,231,"ETH","Ethiopia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ETH/VIIRS/eth_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61079,231,"ETH","Ethiopia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ETH/VIIRS/eth_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61080,231,"ETH","Ethiopia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ETH/VIIRS/eth_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61081,231,"ETH","Ethiopia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ETH/VIIRS/eth_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61082,232,"ERI","Eritrea","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ERI/VIIRS/eri_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61083,232,"ERI","Eritrea","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ERI/VIIRS/eri_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61084,232,"ERI","Eritrea","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ERI/VIIRS/eri_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61085,232,"ERI","Eritrea","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ERI/VIIRS/eri_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61086,232,"ERI","Eritrea","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ERI/VIIRS/eri_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61087,233,"EST","Estonia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/EST/VIIRS/est_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61088,233,"EST","Estonia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/EST/VIIRS/est_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61089,233,"EST","Estonia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/EST/VIIRS/est_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61090,233,"EST","Estonia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/EST/VIIRS/est_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61091,233,"EST","Estonia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/EST/VIIRS/est_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61092,234,"FRO","Faroe Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/FRO/VIIRS/fro_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61093,234,"FRO","Faroe Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/FRO/VIIRS/fro_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61094,234,"FRO","Faroe Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/FRO/VIIRS/fro_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61095,234,"FRO","Faroe Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/FRO/VIIRS/fro_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61096,234,"FRO","Faroe Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/FRO/VIIRS/fro_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61097,238,"FLK","Falkland Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/FLK/VIIRS/flk_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61098,238,"FLK","Falkland Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/FLK/VIIRS/flk_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61099,238,"FLK","Falkland Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/FLK/VIIRS/flk_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61100,238,"FLK","Falkland Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/FLK/VIIRS/flk_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61101,238,"FLK","Falkland Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/FLK/VIIRS/flk_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61102,239,"SGS","South Georgia and the South Sandwich Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SGS/VIIRS/sgs_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61103,239,"SGS","South Georgia and the South Sandwich Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SGS/VIIRS/sgs_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61104,239,"SGS","South Georgia and the South Sandwich Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SGS/VIIRS/sgs_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61105,239,"SGS","South Georgia and the South Sandwich Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SGS/VIIRS/sgs_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61106,239,"SGS","South Georgia and the South Sandwich Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SGS/VIIRS/sgs_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61107,242,"FJI","Fiji","viirs_100m_2012","GIS/Covariates/Global_2000_2020/FJI/VIIRS/fji_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61108,242,"FJI","Fiji","viirs_100m_2013","GIS/Covariates/Global_2000_2020/FJI/VIIRS/fji_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61109,242,"FJI","Fiji","viirs_100m_2014","GIS/Covariates/Global_2000_2020/FJI/VIIRS/fji_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61110,242,"FJI","Fiji","viirs_100m_2015","GIS/Covariates/Global_2000_2020/FJI/VIIRS/fji_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61111,242,"FJI","Fiji","viirs_100m_2016","GIS/Covariates/Global_2000_2020/FJI/VIIRS/fji_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61112,246,"FIN","Finland","viirs_100m_2012","GIS/Covariates/Global_2000_2020/FIN/VIIRS/fin_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61113,246,"FIN","Finland","viirs_100m_2013","GIS/Covariates/Global_2000_2020/FIN/VIIRS/fin_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61114,246,"FIN","Finland","viirs_100m_2014","GIS/Covariates/Global_2000_2020/FIN/VIIRS/fin_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61115,246,"FIN","Finland","viirs_100m_2015","GIS/Covariates/Global_2000_2020/FIN/VIIRS/fin_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61116,246,"FIN","Finland","viirs_100m_2016","GIS/Covariates/Global_2000_2020/FIN/VIIRS/fin_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61117,248,"ALA","Aland Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ALA/VIIRS/ala_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61118,248,"ALA","Aland Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ALA/VIIRS/ala_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61119,248,"ALA","Aland Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ALA/VIIRS/ala_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61120,248,"ALA","Aland Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ALA/VIIRS/ala_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61121,248,"ALA","Aland Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ALA/VIIRS/ala_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61122,250,"FRA","France","viirs_100m_2012","GIS/Covariates/Global_2000_2020/FRA/VIIRS/fra_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61123,250,"FRA","France","viirs_100m_2013","GIS/Covariates/Global_2000_2020/FRA/VIIRS/fra_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61124,250,"FRA","France","viirs_100m_2014","GIS/Covariates/Global_2000_2020/FRA/VIIRS/fra_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61125,250,"FRA","France","viirs_100m_2015","GIS/Covariates/Global_2000_2020/FRA/VIIRS/fra_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61126,250,"FRA","France","viirs_100m_2016","GIS/Covariates/Global_2000_2020/FRA/VIIRS/fra_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61127,254,"GUF","French Guiana","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GUF/VIIRS/guf_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61128,254,"GUF","French Guiana","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GUF/VIIRS/guf_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61129,254,"GUF","French Guiana","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GUF/VIIRS/guf_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61130,254,"GUF","French Guiana","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GUF/VIIRS/guf_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61131,254,"GUF","French Guiana","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GUF/VIIRS/guf_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61132,258,"PYF","French Polynesia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PYF/VIIRS/pyf_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61133,258,"PYF","French Polynesia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PYF/VIIRS/pyf_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61134,258,"PYF","French Polynesia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PYF/VIIRS/pyf_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61135,258,"PYF","French Polynesia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PYF/VIIRS/pyf_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61136,258,"PYF","French Polynesia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PYF/VIIRS/pyf_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61137,260,"ATF","French Southern Territories","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ATF/VIIRS/atf_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61138,260,"ATF","French Southern Territories","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ATF/VIIRS/atf_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61139,260,"ATF","French Southern Territories","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ATF/VIIRS/atf_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61140,260,"ATF","French Southern Territories","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ATF/VIIRS/atf_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61141,260,"ATF","French Southern Territories","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ATF/VIIRS/atf_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61142,262,"DJI","Djibouti","viirs_100m_2012","GIS/Covariates/Global_2000_2020/DJI/VIIRS/dji_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61143,262,"DJI","Djibouti","viirs_100m_2013","GIS/Covariates/Global_2000_2020/DJI/VIIRS/dji_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61144,262,"DJI","Djibouti","viirs_100m_2014","GIS/Covariates/Global_2000_2020/DJI/VIIRS/dji_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61145,262,"DJI","Djibouti","viirs_100m_2015","GIS/Covariates/Global_2000_2020/DJI/VIIRS/dji_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61146,262,"DJI","Djibouti","viirs_100m_2016","GIS/Covariates/Global_2000_2020/DJI/VIIRS/dji_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61147,266,"GAB","Gabon","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GAB/VIIRS/gab_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61148,266,"GAB","Gabon","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GAB/VIIRS/gab_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61149,266,"GAB","Gabon","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GAB/VIIRS/gab_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61150,266,"GAB","Gabon","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GAB/VIIRS/gab_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61151,266,"GAB","Gabon","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GAB/VIIRS/gab_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61152,268,"GEO","Georgia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GEO/VIIRS/geo_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61153,268,"GEO","Georgia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GEO/VIIRS/geo_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61154,268,"GEO","Georgia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GEO/VIIRS/geo_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61155,268,"GEO","Georgia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GEO/VIIRS/geo_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61156,268,"GEO","Georgia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GEO/VIIRS/geo_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61157,270,"GMB","Gambia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GMB/VIIRS/gmb_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61158,270,"GMB","Gambia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GMB/VIIRS/gmb_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61159,270,"GMB","Gambia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GMB/VIIRS/gmb_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61160,270,"GMB","Gambia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GMB/VIIRS/gmb_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61161,270,"GMB","Gambia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GMB/VIIRS/gmb_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61162,275,"PSE","Palestina","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PSE/VIIRS/pse_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61163,275,"PSE","Palestina","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PSE/VIIRS/pse_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61164,275,"PSE","Palestina","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PSE/VIIRS/pse_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61165,275,"PSE","Palestina","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PSE/VIIRS/pse_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61166,275,"PSE","Palestina","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PSE/VIIRS/pse_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61167,276,"DEU","Germany","viirs_100m_2012","GIS/Covariates/Global_2000_2020/DEU/VIIRS/deu_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61168,276,"DEU","Germany","viirs_100m_2013","GIS/Covariates/Global_2000_2020/DEU/VIIRS/deu_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61169,276,"DEU","Germany","viirs_100m_2014","GIS/Covariates/Global_2000_2020/DEU/VIIRS/deu_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61170,276,"DEU","Germany","viirs_100m_2015","GIS/Covariates/Global_2000_2020/DEU/VIIRS/deu_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61171,276,"DEU","Germany","viirs_100m_2016","GIS/Covariates/Global_2000_2020/DEU/VIIRS/deu_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61172,288,"GHA","Ghana","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GHA/VIIRS/gha_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61173,288,"GHA","Ghana","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GHA/VIIRS/gha_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61174,288,"GHA","Ghana","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GHA/VIIRS/gha_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61175,288,"GHA","Ghana","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GHA/VIIRS/gha_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61176,288,"GHA","Ghana","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GHA/VIIRS/gha_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61177,292,"GIB","Gibraltar","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GIB/VIIRS/gib_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61178,292,"GIB","Gibraltar","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GIB/VIIRS/gib_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61179,292,"GIB","Gibraltar","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GIB/VIIRS/gib_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61180,292,"GIB","Gibraltar","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GIB/VIIRS/gib_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61181,292,"GIB","Gibraltar","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GIB/VIIRS/gib_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61182,296,"KIR","Kiribati","viirs_100m_2012","GIS/Covariates/Global_2000_2020/KIR/VIIRS/kir_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61183,296,"KIR","Kiribati","viirs_100m_2013","GIS/Covariates/Global_2000_2020/KIR/VIIRS/kir_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61184,296,"KIR","Kiribati","viirs_100m_2014","GIS/Covariates/Global_2000_2020/KIR/VIIRS/kir_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61185,296,"KIR","Kiribati","viirs_100m_2015","GIS/Covariates/Global_2000_2020/KIR/VIIRS/kir_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61186,296,"KIR","Kiribati","viirs_100m_2016","GIS/Covariates/Global_2000_2020/KIR/VIIRS/kir_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61187,300,"GRC","Greece","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GRC/VIIRS/grc_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61188,300,"GRC","Greece","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GRC/VIIRS/grc_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61189,300,"GRC","Greece","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GRC/VIIRS/grc_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61190,300,"GRC","Greece","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GRC/VIIRS/grc_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61191,300,"GRC","Greece","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GRC/VIIRS/grc_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61192,308,"GRD","Grenada","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GRD/VIIRS/grd_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61193,308,"GRD","Grenada","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GRD/VIIRS/grd_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61194,308,"GRD","Grenada","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GRD/VIIRS/grd_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61195,308,"GRD","Grenada","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GRD/VIIRS/grd_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61196,308,"GRD","Grenada","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GRD/VIIRS/grd_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61197,312,"GLP","Guadeloupe","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GLP/VIIRS/glp_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61198,312,"GLP","Guadeloupe","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GLP/VIIRS/glp_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61199,312,"GLP","Guadeloupe","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GLP/VIIRS/glp_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61200,312,"GLP","Guadeloupe","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GLP/VIIRS/glp_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61201,312,"GLP","Guadeloupe","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GLP/VIIRS/glp_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61202,316,"GUM","Guam","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GUM/VIIRS/gum_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61203,316,"GUM","Guam","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GUM/VIIRS/gum_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61204,316,"GUM","Guam","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GUM/VIIRS/gum_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61205,316,"GUM","Guam","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GUM/VIIRS/gum_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61206,316,"GUM","Guam","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GUM/VIIRS/gum_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61207,320,"GTM","Guatemala","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GTM/VIIRS/gtm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61208,320,"GTM","Guatemala","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GTM/VIIRS/gtm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61209,320,"GTM","Guatemala","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GTM/VIIRS/gtm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61210,320,"GTM","Guatemala","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GTM/VIIRS/gtm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61211,320,"GTM","Guatemala","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GTM/VIIRS/gtm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61212,324,"GIN","Guinea","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GIN/VIIRS/gin_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61213,324,"GIN","Guinea","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GIN/VIIRS/gin_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61214,324,"GIN","Guinea","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GIN/VIIRS/gin_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61215,324,"GIN","Guinea","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GIN/VIIRS/gin_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61216,324,"GIN","Guinea","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GIN/VIIRS/gin_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61217,328,"GUY","Guyana","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GUY/VIIRS/guy_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61218,328,"GUY","Guyana","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GUY/VIIRS/guy_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61219,328,"GUY","Guyana","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GUY/VIIRS/guy_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61220,328,"GUY","Guyana","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GUY/VIIRS/guy_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61221,328,"GUY","Guyana","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GUY/VIIRS/guy_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61222,332,"HTI","Haiti","viirs_100m_2012","GIS/Covariates/Global_2000_2020/HTI/VIIRS/hti_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61223,332,"HTI","Haiti","viirs_100m_2013","GIS/Covariates/Global_2000_2020/HTI/VIIRS/hti_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61224,332,"HTI","Haiti","viirs_100m_2014","GIS/Covariates/Global_2000_2020/HTI/VIIRS/hti_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61225,332,"HTI","Haiti","viirs_100m_2015","GIS/Covariates/Global_2000_2020/HTI/VIIRS/hti_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61226,332,"HTI","Haiti","viirs_100m_2016","GIS/Covariates/Global_2000_2020/HTI/VIIRS/hti_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61227,334,"HMD","Heard Island and McDonald Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/HMD/VIIRS/hmd_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61228,334,"HMD","Heard Island and McDonald Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/HMD/VIIRS/hmd_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61229,334,"HMD","Heard Island and McDonald Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/HMD/VIIRS/hmd_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61230,334,"HMD","Heard Island and McDonald Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/HMD/VIIRS/hmd_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61231,334,"HMD","Heard Island and McDonald Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/HMD/VIIRS/hmd_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61232,336,"VAT","Vatican City","viirs_100m_2012","GIS/Covariates/Global_2000_2020/VAT/VIIRS/vat_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61233,336,"VAT","Vatican City","viirs_100m_2013","GIS/Covariates/Global_2000_2020/VAT/VIIRS/vat_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61234,336,"VAT","Vatican City","viirs_100m_2014","GIS/Covariates/Global_2000_2020/VAT/VIIRS/vat_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61235,336,"VAT","Vatican City","viirs_100m_2015","GIS/Covariates/Global_2000_2020/VAT/VIIRS/vat_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61236,336,"VAT","Vatican City","viirs_100m_2016","GIS/Covariates/Global_2000_2020/VAT/VIIRS/vat_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61237,340,"HND","Honduras","viirs_100m_2012","GIS/Covariates/Global_2000_2020/HND/VIIRS/hnd_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61238,340,"HND","Honduras","viirs_100m_2013","GIS/Covariates/Global_2000_2020/HND/VIIRS/hnd_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61239,340,"HND","Honduras","viirs_100m_2014","GIS/Covariates/Global_2000_2020/HND/VIIRS/hnd_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61240,340,"HND","Honduras","viirs_100m_2015","GIS/Covariates/Global_2000_2020/HND/VIIRS/hnd_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61241,340,"HND","Honduras","viirs_100m_2016","GIS/Covariates/Global_2000_2020/HND/VIIRS/hnd_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61242,344,"HKG","Hong Kong","viirs_100m_2012","GIS/Covariates/Global_2000_2020/HKG/VIIRS/hkg_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61243,344,"HKG","Hong Kong","viirs_100m_2013","GIS/Covariates/Global_2000_2020/HKG/VIIRS/hkg_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61244,344,"HKG","Hong Kong","viirs_100m_2014","GIS/Covariates/Global_2000_2020/HKG/VIIRS/hkg_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61245,344,"HKG","Hong Kong","viirs_100m_2015","GIS/Covariates/Global_2000_2020/HKG/VIIRS/hkg_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61246,344,"HKG","Hong Kong","viirs_100m_2016","GIS/Covariates/Global_2000_2020/HKG/VIIRS/hkg_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61247,348,"HUN","Hungary","viirs_100m_2012","GIS/Covariates/Global_2000_2020/HUN/VIIRS/hun_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61248,348,"HUN","Hungary","viirs_100m_2013","GIS/Covariates/Global_2000_2020/HUN/VIIRS/hun_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61249,348,"HUN","Hungary","viirs_100m_2014","GIS/Covariates/Global_2000_2020/HUN/VIIRS/hun_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61250,348,"HUN","Hungary","viirs_100m_2015","GIS/Covariates/Global_2000_2020/HUN/VIIRS/hun_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61251,348,"HUN","Hungary","viirs_100m_2016","GIS/Covariates/Global_2000_2020/HUN/VIIRS/hun_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61252,352,"ISL","Iceland","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ISL/VIIRS/isl_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61253,352,"ISL","Iceland","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ISL/VIIRS/isl_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61254,352,"ISL","Iceland","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ISL/VIIRS/isl_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61255,352,"ISL","Iceland","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ISL/VIIRS/isl_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61256,352,"ISL","Iceland","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ISL/VIIRS/isl_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61257,356,"IND","India","viirs_100m_2012","GIS/Covariates/Global_2000_2020/IND/VIIRS/ind_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61258,356,"IND","India","viirs_100m_2013","GIS/Covariates/Global_2000_2020/IND/VIIRS/ind_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61259,356,"IND","India","viirs_100m_2014","GIS/Covariates/Global_2000_2020/IND/VIIRS/ind_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61260,356,"IND","India","viirs_100m_2015","GIS/Covariates/Global_2000_2020/IND/VIIRS/ind_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61261,356,"IND","India","viirs_100m_2016","GIS/Covariates/Global_2000_2020/IND/VIIRS/ind_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61262,364,"IRN","Iran","viirs_100m_2012","GIS/Covariates/Global_2000_2020/IRN/VIIRS/irn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61263,364,"IRN","Iran","viirs_100m_2013","GIS/Covariates/Global_2000_2020/IRN/VIIRS/irn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61264,364,"IRN","Iran","viirs_100m_2014","GIS/Covariates/Global_2000_2020/IRN/VIIRS/irn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61265,364,"IRN","Iran","viirs_100m_2015","GIS/Covariates/Global_2000_2020/IRN/VIIRS/irn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61266,364,"IRN","Iran","viirs_100m_2016","GIS/Covariates/Global_2000_2020/IRN/VIIRS/irn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61267,368,"IRQ","Iraq","viirs_100m_2012","GIS/Covariates/Global_2000_2020/IRQ/VIIRS/irq_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61268,368,"IRQ","Iraq","viirs_100m_2013","GIS/Covariates/Global_2000_2020/IRQ/VIIRS/irq_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61269,368,"IRQ","Iraq","viirs_100m_2014","GIS/Covariates/Global_2000_2020/IRQ/VIIRS/irq_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61270,368,"IRQ","Iraq","viirs_100m_2015","GIS/Covariates/Global_2000_2020/IRQ/VIIRS/irq_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61271,368,"IRQ","Iraq","viirs_100m_2016","GIS/Covariates/Global_2000_2020/IRQ/VIIRS/irq_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61272,372,"IRL","Ireland","viirs_100m_2012","GIS/Covariates/Global_2000_2020/IRL/VIIRS/irl_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61273,372,"IRL","Ireland","viirs_100m_2013","GIS/Covariates/Global_2000_2020/IRL/VIIRS/irl_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61274,372,"IRL","Ireland","viirs_100m_2014","GIS/Covariates/Global_2000_2020/IRL/VIIRS/irl_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61275,372,"IRL","Ireland","viirs_100m_2015","GIS/Covariates/Global_2000_2020/IRL/VIIRS/irl_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61276,372,"IRL","Ireland","viirs_100m_2016","GIS/Covariates/Global_2000_2020/IRL/VIIRS/irl_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61277,376,"ISR","Israel","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ISR/VIIRS/isr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61278,376,"ISR","Israel","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ISR/VIIRS/isr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61279,376,"ISR","Israel","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ISR/VIIRS/isr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61280,376,"ISR","Israel","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ISR/VIIRS/isr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61281,376,"ISR","Israel","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ISR/VIIRS/isr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61282,380,"ITA","Italy","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ITA/VIIRS/ita_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61283,380,"ITA","Italy","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ITA/VIIRS/ita_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61284,380,"ITA","Italy","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ITA/VIIRS/ita_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61285,380,"ITA","Italy","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ITA/VIIRS/ita_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61286,380,"ITA","Italy","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ITA/VIIRS/ita_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61287,384,"CIV","CIte dIvoire","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CIV/VIIRS/civ_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61288,384,"CIV","CIte dIvoire","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CIV/VIIRS/civ_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61289,384,"CIV","CIte dIvoire","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CIV/VIIRS/civ_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61290,384,"CIV","CIte dIvoire","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CIV/VIIRS/civ_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61291,384,"CIV","CIte dIvoire","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CIV/VIIRS/civ_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61292,388,"JAM","Jamaica","viirs_100m_2012","GIS/Covariates/Global_2000_2020/JAM/VIIRS/jam_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61293,388,"JAM","Jamaica","viirs_100m_2013","GIS/Covariates/Global_2000_2020/JAM/VIIRS/jam_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61294,388,"JAM","Jamaica","viirs_100m_2014","GIS/Covariates/Global_2000_2020/JAM/VIIRS/jam_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61295,388,"JAM","Jamaica","viirs_100m_2015","GIS/Covariates/Global_2000_2020/JAM/VIIRS/jam_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61296,388,"JAM","Jamaica","viirs_100m_2016","GIS/Covariates/Global_2000_2020/JAM/VIIRS/jam_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61297,392,"JPN","Japan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/JPN/VIIRS/jpn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61298,392,"JPN","Japan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/JPN/VIIRS/jpn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61299,392,"JPN","Japan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/JPN/VIIRS/jpn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61300,392,"JPN","Japan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/JPN/VIIRS/jpn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61301,392,"JPN","Japan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/JPN/VIIRS/jpn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61302,398,"KAZ","Kazakhstan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/KAZ/VIIRS/kaz_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61303,398,"KAZ","Kazakhstan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/KAZ/VIIRS/kaz_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61304,398,"KAZ","Kazakhstan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/KAZ/VIIRS/kaz_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61305,398,"KAZ","Kazakhstan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/KAZ/VIIRS/kaz_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61306,398,"KAZ","Kazakhstan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/KAZ/VIIRS/kaz_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61307,400,"JOR","Jordan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/JOR/VIIRS/jor_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61308,400,"JOR","Jordan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/JOR/VIIRS/jor_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61309,400,"JOR","Jordan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/JOR/VIIRS/jor_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61310,400,"JOR","Jordan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/JOR/VIIRS/jor_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61311,400,"JOR","Jordan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/JOR/VIIRS/jor_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61312,404,"KEN","Kenya","viirs_100m_2012","GIS/Covariates/Global_2000_2020/KEN/VIIRS/ken_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61313,404,"KEN","Kenya","viirs_100m_2013","GIS/Covariates/Global_2000_2020/KEN/VIIRS/ken_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61314,404,"KEN","Kenya","viirs_100m_2014","GIS/Covariates/Global_2000_2020/KEN/VIIRS/ken_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61315,404,"KEN","Kenya","viirs_100m_2015","GIS/Covariates/Global_2000_2020/KEN/VIIRS/ken_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61316,404,"KEN","Kenya","viirs_100m_2016","GIS/Covariates/Global_2000_2020/KEN/VIIRS/ken_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61317,408,"PRK","North Korea","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PRK/VIIRS/prk_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61318,408,"PRK","North Korea","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PRK/VIIRS/prk_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61319,408,"PRK","North Korea","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PRK/VIIRS/prk_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61320,408,"PRK","North Korea","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PRK/VIIRS/prk_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61321,408,"PRK","North Korea","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PRK/VIIRS/prk_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61322,410,"KOR","South Korea","viirs_100m_2012","GIS/Covariates/Global_2000_2020/KOR/VIIRS/kor_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61323,410,"KOR","South Korea","viirs_100m_2013","GIS/Covariates/Global_2000_2020/KOR/VIIRS/kor_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61324,410,"KOR","South Korea","viirs_100m_2014","GIS/Covariates/Global_2000_2020/KOR/VIIRS/kor_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61325,410,"KOR","South Korea","viirs_100m_2015","GIS/Covariates/Global_2000_2020/KOR/VIIRS/kor_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61326,410,"KOR","South Korea","viirs_100m_2016","GIS/Covariates/Global_2000_2020/KOR/VIIRS/kor_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61327,414,"KWT","Kuwait","viirs_100m_2012","GIS/Covariates/Global_2000_2020/KWT/VIIRS/kwt_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61328,414,"KWT","Kuwait","viirs_100m_2013","GIS/Covariates/Global_2000_2020/KWT/VIIRS/kwt_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61329,414,"KWT","Kuwait","viirs_100m_2014","GIS/Covariates/Global_2000_2020/KWT/VIIRS/kwt_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61330,414,"KWT","Kuwait","viirs_100m_2015","GIS/Covariates/Global_2000_2020/KWT/VIIRS/kwt_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61331,414,"KWT","Kuwait","viirs_100m_2016","GIS/Covariates/Global_2000_2020/KWT/VIIRS/kwt_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61332,417,"KGZ","Kyrgyzstan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/KGZ/VIIRS/kgz_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61333,417,"KGZ","Kyrgyzstan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/KGZ/VIIRS/kgz_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61334,417,"KGZ","Kyrgyzstan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/KGZ/VIIRS/kgz_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61335,417,"KGZ","Kyrgyzstan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/KGZ/VIIRS/kgz_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61336,417,"KGZ","Kyrgyzstan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/KGZ/VIIRS/kgz_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61337,418,"LAO","Laos","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LAO/VIIRS/lao_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61338,418,"LAO","Laos","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LAO/VIIRS/lao_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61339,418,"LAO","Laos","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LAO/VIIRS/lao_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61340,418,"LAO","Laos","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LAO/VIIRS/lao_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61341,418,"LAO","Laos","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LAO/VIIRS/lao_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61342,422,"LBN","Lebanon","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LBN/VIIRS/lbn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61343,422,"LBN","Lebanon","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LBN/VIIRS/lbn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61344,422,"LBN","Lebanon","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LBN/VIIRS/lbn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61345,422,"LBN","Lebanon","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LBN/VIIRS/lbn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61346,422,"LBN","Lebanon","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LBN/VIIRS/lbn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61347,426,"LSO","Lesotho","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LSO/VIIRS/lso_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61348,426,"LSO","Lesotho","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LSO/VIIRS/lso_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61349,426,"LSO","Lesotho","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LSO/VIIRS/lso_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61350,426,"LSO","Lesotho","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LSO/VIIRS/lso_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61351,426,"LSO","Lesotho","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LSO/VIIRS/lso_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61352,428,"LVA","Latvia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LVA/VIIRS/lva_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61353,428,"LVA","Latvia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LVA/VIIRS/lva_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61354,428,"LVA","Latvia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LVA/VIIRS/lva_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61355,428,"LVA","Latvia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LVA/VIIRS/lva_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61356,428,"LVA","Latvia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LVA/VIIRS/lva_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61357,430,"LBR","Liberia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LBR/VIIRS/lbr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61358,430,"LBR","Liberia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LBR/VIIRS/lbr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61359,430,"LBR","Liberia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LBR/VIIRS/lbr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61360,430,"LBR","Liberia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LBR/VIIRS/lbr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61361,430,"LBR","Liberia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LBR/VIIRS/lbr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61362,434,"LBY","Libya","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LBY/VIIRS/lby_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61363,434,"LBY","Libya","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LBY/VIIRS/lby_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61364,434,"LBY","Libya","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LBY/VIIRS/lby_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61365,434,"LBY","Libya","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LBY/VIIRS/lby_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61366,434,"LBY","Libya","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LBY/VIIRS/lby_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61367,438,"LIE","Liechtenstein","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LIE/VIIRS/lie_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61368,438,"LIE","Liechtenstein","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LIE/VIIRS/lie_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61369,438,"LIE","Liechtenstein","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LIE/VIIRS/lie_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61370,438,"LIE","Liechtenstein","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LIE/VIIRS/lie_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61371,438,"LIE","Liechtenstein","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LIE/VIIRS/lie_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61372,440,"LTU","Lithuania","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LTU/VIIRS/ltu_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61373,440,"LTU","Lithuania","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LTU/VIIRS/ltu_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61374,440,"LTU","Lithuania","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LTU/VIIRS/ltu_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61375,440,"LTU","Lithuania","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LTU/VIIRS/ltu_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61376,440,"LTU","Lithuania","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LTU/VIIRS/ltu_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61377,442,"LUX","Luxembourg","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LUX/VIIRS/lux_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61378,442,"LUX","Luxembourg","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LUX/VIIRS/lux_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61379,442,"LUX","Luxembourg","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LUX/VIIRS/lux_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61380,442,"LUX","Luxembourg","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LUX/VIIRS/lux_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61381,442,"LUX","Luxembourg","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LUX/VIIRS/lux_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61382,446,"MAC","Macao","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MAC/VIIRS/mac_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61383,446,"MAC","Macao","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MAC/VIIRS/mac_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61384,446,"MAC","Macao","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MAC/VIIRS/mac_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61385,446,"MAC","Macao","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MAC/VIIRS/mac_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61386,446,"MAC","Macao","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MAC/VIIRS/mac_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61387,450,"MDG","Madagascar","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MDG/VIIRS/mdg_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61388,450,"MDG","Madagascar","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MDG/VIIRS/mdg_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61389,450,"MDG","Madagascar","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MDG/VIIRS/mdg_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61390,450,"MDG","Madagascar","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MDG/VIIRS/mdg_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61391,450,"MDG","Madagascar","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MDG/VIIRS/mdg_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61392,454,"MWI","Malawi","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MWI/VIIRS/mwi_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61393,454,"MWI","Malawi","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MWI/VIIRS/mwi_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61394,454,"MWI","Malawi","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MWI/VIIRS/mwi_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61395,454,"MWI","Malawi","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MWI/VIIRS/mwi_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61396,454,"MWI","Malawi","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MWI/VIIRS/mwi_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61397,458,"MYS","Malaysia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MYS/VIIRS/mys_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61398,458,"MYS","Malaysia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MYS/VIIRS/mys_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61399,458,"MYS","Malaysia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MYS/VIIRS/mys_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61400,458,"MYS","Malaysia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MYS/VIIRS/mys_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61401,458,"MYS","Malaysia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MYS/VIIRS/mys_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61402,462,"MDV","Maldives","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MDV/VIIRS/mdv_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61403,462,"MDV","Maldives","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MDV/VIIRS/mdv_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61404,462,"MDV","Maldives","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MDV/VIIRS/mdv_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61405,462,"MDV","Maldives","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MDV/VIIRS/mdv_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61406,462,"MDV","Maldives","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MDV/VIIRS/mdv_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61407,466,"MLI","Mali","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MLI/VIIRS/mli_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61408,466,"MLI","Mali","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MLI/VIIRS/mli_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61409,466,"MLI","Mali","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MLI/VIIRS/mli_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61410,466,"MLI","Mali","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MLI/VIIRS/mli_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61411,466,"MLI","Mali","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MLI/VIIRS/mli_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61412,470,"MLT","Malta","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MLT/VIIRS/mlt_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61413,470,"MLT","Malta","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MLT/VIIRS/mlt_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61414,470,"MLT","Malta","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MLT/VIIRS/mlt_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61415,470,"MLT","Malta","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MLT/VIIRS/mlt_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61416,470,"MLT","Malta","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MLT/VIIRS/mlt_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61417,474,"MTQ","Martinique","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MTQ/VIIRS/mtq_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61418,474,"MTQ","Martinique","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MTQ/VIIRS/mtq_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61419,474,"MTQ","Martinique","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MTQ/VIIRS/mtq_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61420,474,"MTQ","Martinique","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MTQ/VIIRS/mtq_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61421,474,"MTQ","Martinique","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MTQ/VIIRS/mtq_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61422,478,"MRT","Mauritania","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MRT/VIIRS/mrt_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61423,478,"MRT","Mauritania","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MRT/VIIRS/mrt_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61424,478,"MRT","Mauritania","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MRT/VIIRS/mrt_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61425,478,"MRT","Mauritania","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MRT/VIIRS/mrt_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61426,478,"MRT","Mauritania","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MRT/VIIRS/mrt_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61427,480,"MUS","Mauritius","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MUS/VIIRS/mus_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61428,480,"MUS","Mauritius","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MUS/VIIRS/mus_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61429,480,"MUS","Mauritius","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MUS/VIIRS/mus_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61430,480,"MUS","Mauritius","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MUS/VIIRS/mus_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61431,480,"MUS","Mauritius","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MUS/VIIRS/mus_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61432,484,"MEX","Mexico","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MEX/VIIRS/mex_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61433,484,"MEX","Mexico","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MEX/VIIRS/mex_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61434,484,"MEX","Mexico","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MEX/VIIRS/mex_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61435,484,"MEX","Mexico","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MEX/VIIRS/mex_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61436,484,"MEX","Mexico","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MEX/VIIRS/mex_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61437,492,"MCO","Monaco","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MCO/VIIRS/mco_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61438,492,"MCO","Monaco","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MCO/VIIRS/mco_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61439,492,"MCO","Monaco","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MCO/VIIRS/mco_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61440,492,"MCO","Monaco","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MCO/VIIRS/mco_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61441,492,"MCO","Monaco","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MCO/VIIRS/mco_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61442,496,"MNG","Mongolia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MNG/VIIRS/mng_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61443,496,"MNG","Mongolia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MNG/VIIRS/mng_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61444,496,"MNG","Mongolia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MNG/VIIRS/mng_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61445,496,"MNG","Mongolia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MNG/VIIRS/mng_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61446,496,"MNG","Mongolia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MNG/VIIRS/mng_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61447,498,"MDA","Moldova","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MDA/VIIRS/mda_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61448,498,"MDA","Moldova","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MDA/VIIRS/mda_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61449,498,"MDA","Moldova","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MDA/VIIRS/mda_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61450,498,"MDA","Moldova","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MDA/VIIRS/mda_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61451,498,"MDA","Moldova","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MDA/VIIRS/mda_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61452,499,"MNE","Montenegro","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MNE/VIIRS/mne_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61453,499,"MNE","Montenegro","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MNE/VIIRS/mne_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61454,499,"MNE","Montenegro","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MNE/VIIRS/mne_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61455,499,"MNE","Montenegro","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MNE/VIIRS/mne_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61456,499,"MNE","Montenegro","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MNE/VIIRS/mne_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61457,500,"MSR","Montserrat","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MSR/VIIRS/msr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61458,500,"MSR","Montserrat","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MSR/VIIRS/msr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61459,500,"MSR","Montserrat","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MSR/VIIRS/msr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61460,500,"MSR","Montserrat","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MSR/VIIRS/msr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61461,500,"MSR","Montserrat","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MSR/VIIRS/msr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61462,504,"MAR","Morocco","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MAR/VIIRS/mar_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61463,504,"MAR","Morocco","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MAR/VIIRS/mar_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61464,504,"MAR","Morocco","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MAR/VIIRS/mar_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61465,504,"MAR","Morocco","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MAR/VIIRS/mar_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61466,504,"MAR","Morocco","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MAR/VIIRS/mar_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61467,508,"MOZ","Mozambique","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MOZ/VIIRS/moz_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61468,508,"MOZ","Mozambique","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MOZ/VIIRS/moz_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61469,508,"MOZ","Mozambique","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MOZ/VIIRS/moz_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61470,508,"MOZ","Mozambique","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MOZ/VIIRS/moz_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61471,508,"MOZ","Mozambique","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MOZ/VIIRS/moz_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61472,512,"OMN","Oman","viirs_100m_2012","GIS/Covariates/Global_2000_2020/OMN/VIIRS/omn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61473,512,"OMN","Oman","viirs_100m_2013","GIS/Covariates/Global_2000_2020/OMN/VIIRS/omn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61474,512,"OMN","Oman","viirs_100m_2014","GIS/Covariates/Global_2000_2020/OMN/VIIRS/omn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61475,512,"OMN","Oman","viirs_100m_2015","GIS/Covariates/Global_2000_2020/OMN/VIIRS/omn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61476,512,"OMN","Oman","viirs_100m_2016","GIS/Covariates/Global_2000_2020/OMN/VIIRS/omn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61477,516,"NAM","Namibia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NAM/VIIRS/nam_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61478,516,"NAM","Namibia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NAM/VIIRS/nam_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61479,516,"NAM","Namibia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NAM/VIIRS/nam_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61480,516,"NAM","Namibia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NAM/VIIRS/nam_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61481,516,"NAM","Namibia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NAM/VIIRS/nam_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61482,520,"NRU","Nauru","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NRU/VIIRS/nru_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61483,520,"NRU","Nauru","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NRU/VIIRS/nru_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61484,520,"NRU","Nauru","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NRU/VIIRS/nru_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61485,520,"NRU","Nauru","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NRU/VIIRS/nru_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61486,520,"NRU","Nauru","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NRU/VIIRS/nru_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61487,524,"NPL","Nepal","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NPL/VIIRS/npl_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61488,524,"NPL","Nepal","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NPL/VIIRS/npl_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61489,524,"NPL","Nepal","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NPL/VIIRS/npl_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61490,524,"NPL","Nepal","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NPL/VIIRS/npl_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61491,524,"NPL","Nepal","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NPL/VIIRS/npl_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61492,528,"NLD","Netherlands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NLD/VIIRS/nld_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61493,528,"NLD","Netherlands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NLD/VIIRS/nld_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61494,528,"NLD","Netherlands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NLD/VIIRS/nld_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61495,528,"NLD","Netherlands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NLD/VIIRS/nld_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61496,528,"NLD","Netherlands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NLD/VIIRS/nld_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61497,531,"CUW","Curacao","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CUW/VIIRS/cuw_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61498,531,"CUW","Curacao","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CUW/VIIRS/cuw_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61499,531,"CUW","Curacao","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CUW/VIIRS/cuw_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61500,531,"CUW","Curacao","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CUW/VIIRS/cuw_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61501,531,"CUW","Curacao","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CUW/VIIRS/cuw_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61502,533,"ABW","Aruba","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ABW/VIIRS/abw_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61503,533,"ABW","Aruba","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ABW/VIIRS/abw_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61504,533,"ABW","Aruba","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ABW/VIIRS/abw_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61505,533,"ABW","Aruba","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ABW/VIIRS/abw_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61506,533,"ABW","Aruba","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ABW/VIIRS/abw_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61507,534,"SXM","Sint Maarten (Dutch part)","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SXM/VIIRS/sxm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61508,534,"SXM","Sint Maarten (Dutch part)","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SXM/VIIRS/sxm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61509,534,"SXM","Sint Maarten (Dutch part)","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SXM/VIIRS/sxm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61510,534,"SXM","Sint Maarten (Dutch part)","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SXM/VIIRS/sxm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61511,534,"SXM","Sint Maarten (Dutch part)","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SXM/VIIRS/sxm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61512,535,"BES","Bonaire, Sint Eustatius and Saba","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BES/VIIRS/bes_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61513,535,"BES","Bonaire, Sint Eustatius and Saba","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BES/VIIRS/bes_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61514,535,"BES","Bonaire, Sint Eustatius and Saba","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BES/VIIRS/bes_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61515,535,"BES","Bonaire, Sint Eustatius and Saba","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BES/VIIRS/bes_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61516,535,"BES","Bonaire, Sint Eustatius and Saba","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BES/VIIRS/bes_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61517,540,"NCL","New Caledonia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NCL/VIIRS/ncl_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61518,540,"NCL","New Caledonia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NCL/VIIRS/ncl_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61519,540,"NCL","New Caledonia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NCL/VIIRS/ncl_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61520,540,"NCL","New Caledonia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NCL/VIIRS/ncl_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61521,540,"NCL","New Caledonia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NCL/VIIRS/ncl_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61522,548,"VUT","Vanuatu","viirs_100m_2012","GIS/Covariates/Global_2000_2020/VUT/VIIRS/vut_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61523,548,"VUT","Vanuatu","viirs_100m_2013","GIS/Covariates/Global_2000_2020/VUT/VIIRS/vut_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61524,548,"VUT","Vanuatu","viirs_100m_2014","GIS/Covariates/Global_2000_2020/VUT/VIIRS/vut_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61525,548,"VUT","Vanuatu","viirs_100m_2015","GIS/Covariates/Global_2000_2020/VUT/VIIRS/vut_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61526,548,"VUT","Vanuatu","viirs_100m_2016","GIS/Covariates/Global_2000_2020/VUT/VIIRS/vut_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61527,554,"NZL","New Zealand","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NZL/VIIRS/nzl_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61528,554,"NZL","New Zealand","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NZL/VIIRS/nzl_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61529,554,"NZL","New Zealand","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NZL/VIIRS/nzl_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61530,554,"NZL","New Zealand","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NZL/VIIRS/nzl_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61531,554,"NZL","New Zealand","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NZL/VIIRS/nzl_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61532,558,"NIC","Nicaragua","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NIC/VIIRS/nic_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61533,558,"NIC","Nicaragua","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NIC/VIIRS/nic_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61534,558,"NIC","Nicaragua","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NIC/VIIRS/nic_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61535,558,"NIC","Nicaragua","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NIC/VIIRS/nic_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61536,558,"NIC","Nicaragua","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NIC/VIIRS/nic_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61537,562,"NER","Niger","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NER/VIIRS/ner_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61538,562,"NER","Niger","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NER/VIIRS/ner_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61539,562,"NER","Niger","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NER/VIIRS/ner_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61540,562,"NER","Niger","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NER/VIIRS/ner_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61541,562,"NER","Niger","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NER/VIIRS/ner_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61542,566,"NGA","Nigeria","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NGA/VIIRS/nga_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61543,566,"NGA","Nigeria","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NGA/VIIRS/nga_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61544,566,"NGA","Nigeria","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NGA/VIIRS/nga_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61545,566,"NGA","Nigeria","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NGA/VIIRS/nga_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61546,566,"NGA","Nigeria","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NGA/VIIRS/nga_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61547,570,"NIU","Niue","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NIU/VIIRS/niu_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61548,570,"NIU","Niue","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NIU/VIIRS/niu_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61549,570,"NIU","Niue","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NIU/VIIRS/niu_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61550,570,"NIU","Niue","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NIU/VIIRS/niu_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61551,570,"NIU","Niue","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NIU/VIIRS/niu_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61552,574,"NFK","Norfolk Island","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NFK/VIIRS/nfk_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61553,574,"NFK","Norfolk Island","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NFK/VIIRS/nfk_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61554,574,"NFK","Norfolk Island","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NFK/VIIRS/nfk_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61555,574,"NFK","Norfolk Island","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NFK/VIIRS/nfk_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61556,574,"NFK","Norfolk Island","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NFK/VIIRS/nfk_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61557,578,"NOR","Norway","viirs_100m_2012","GIS/Covariates/Global_2000_2020/NOR/VIIRS/nor_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61558,578,"NOR","Norway","viirs_100m_2013","GIS/Covariates/Global_2000_2020/NOR/VIIRS/nor_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61559,578,"NOR","Norway","viirs_100m_2014","GIS/Covariates/Global_2000_2020/NOR/VIIRS/nor_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61560,578,"NOR","Norway","viirs_100m_2015","GIS/Covariates/Global_2000_2020/NOR/VIIRS/nor_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61561,578,"NOR","Norway","viirs_100m_2016","GIS/Covariates/Global_2000_2020/NOR/VIIRS/nor_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61562,580,"MNP","Northern Mariana Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MNP/VIIRS/mnp_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61563,580,"MNP","Northern Mariana Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MNP/VIIRS/mnp_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61564,580,"MNP","Northern Mariana Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MNP/VIIRS/mnp_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61565,580,"MNP","Northern Mariana Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MNP/VIIRS/mnp_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61566,580,"MNP","Northern Mariana Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MNP/VIIRS/mnp_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61567,581,"UMI","United States Minor Outlying Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/UMI/VIIRS/umi_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61568,581,"UMI","United States Minor Outlying Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/UMI/VIIRS/umi_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61569,581,"UMI","United States Minor Outlying Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/UMI/VIIRS/umi_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61570,581,"UMI","United States Minor Outlying Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/UMI/VIIRS/umi_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61571,581,"UMI","United States Minor Outlying Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/UMI/VIIRS/umi_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61572,583,"FSM","Micronesia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/FSM/VIIRS/fsm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61573,583,"FSM","Micronesia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/FSM/VIIRS/fsm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61574,583,"FSM","Micronesia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/FSM/VIIRS/fsm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61575,583,"FSM","Micronesia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/FSM/VIIRS/fsm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61576,583,"FSM","Micronesia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/FSM/VIIRS/fsm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61577,584,"MHL","Marshall Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MHL/VIIRS/mhl_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61578,584,"MHL","Marshall Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MHL/VIIRS/mhl_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61579,584,"MHL","Marshall Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MHL/VIIRS/mhl_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61580,584,"MHL","Marshall Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MHL/VIIRS/mhl_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61581,584,"MHL","Marshall Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MHL/VIIRS/mhl_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61582,585,"PLW","Palau","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PLW/VIIRS/plw_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61583,585,"PLW","Palau","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PLW/VIIRS/plw_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61584,585,"PLW","Palau","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PLW/VIIRS/plw_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61585,585,"PLW","Palau","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PLW/VIIRS/plw_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61586,585,"PLW","Palau","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PLW/VIIRS/plw_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61587,586,"PAK","Pakistan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PAK/VIIRS/pak_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61588,586,"PAK","Pakistan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PAK/VIIRS/pak_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61589,586,"PAK","Pakistan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PAK/VIIRS/pak_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61590,586,"PAK","Pakistan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PAK/VIIRS/pak_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61591,586,"PAK","Pakistan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PAK/VIIRS/pak_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61592,591,"PAN","Panama","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PAN/VIIRS/pan_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61593,591,"PAN","Panama","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PAN/VIIRS/pan_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61594,591,"PAN","Panama","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PAN/VIIRS/pan_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61595,591,"PAN","Panama","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PAN/VIIRS/pan_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61596,591,"PAN","Panama","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PAN/VIIRS/pan_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61597,598,"PNG","Papua New Guinea","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PNG/VIIRS/png_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61598,598,"PNG","Papua New Guinea","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PNG/VIIRS/png_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61599,598,"PNG","Papua New Guinea","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PNG/VIIRS/png_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61600,598,"PNG","Papua New Guinea","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PNG/VIIRS/png_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61601,598,"PNG","Papua New Guinea","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PNG/VIIRS/png_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61602,600,"PRY","Paraguay","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PRY/VIIRS/pry_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61603,600,"PRY","Paraguay","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PRY/VIIRS/pry_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61604,600,"PRY","Paraguay","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PRY/VIIRS/pry_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61605,600,"PRY","Paraguay","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PRY/VIIRS/pry_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61606,600,"PRY","Paraguay","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PRY/VIIRS/pry_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61607,604,"PER","Peru","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PER/VIIRS/per_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61608,604,"PER","Peru","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PER/VIIRS/per_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61609,604,"PER","Peru","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PER/VIIRS/per_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61610,604,"PER","Peru","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PER/VIIRS/per_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61611,604,"PER","Peru","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PER/VIIRS/per_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61612,608,"PHL","Philippines","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PHL/VIIRS/phl_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61613,608,"PHL","Philippines","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PHL/VIIRS/phl_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61614,608,"PHL","Philippines","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PHL/VIIRS/phl_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61615,608,"PHL","Philippines","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PHL/VIIRS/phl_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61616,608,"PHL","Philippines","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PHL/VIIRS/phl_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61617,612,"PCN","Pitcairn Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PCN/VIIRS/pcn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61618,612,"PCN","Pitcairn Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PCN/VIIRS/pcn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61619,612,"PCN","Pitcairn Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PCN/VIIRS/pcn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61620,612,"PCN","Pitcairn Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PCN/VIIRS/pcn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61621,612,"PCN","Pitcairn Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PCN/VIIRS/pcn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61622,616,"POL","Poland","viirs_100m_2012","GIS/Covariates/Global_2000_2020/POL/VIIRS/pol_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61623,616,"POL","Poland","viirs_100m_2013","GIS/Covariates/Global_2000_2020/POL/VIIRS/pol_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61624,616,"POL","Poland","viirs_100m_2014","GIS/Covariates/Global_2000_2020/POL/VIIRS/pol_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61625,616,"POL","Poland","viirs_100m_2015","GIS/Covariates/Global_2000_2020/POL/VIIRS/pol_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61626,616,"POL","Poland","viirs_100m_2016","GIS/Covariates/Global_2000_2020/POL/VIIRS/pol_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61627,620,"PRT","Portugal","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PRT/VIIRS/prt_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61628,620,"PRT","Portugal","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PRT/VIIRS/prt_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61629,620,"PRT","Portugal","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PRT/VIIRS/prt_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61630,620,"PRT","Portugal","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PRT/VIIRS/prt_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61631,620,"PRT","Portugal","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PRT/VIIRS/prt_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61632,624,"GNB","Guinea-Bissau","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GNB/VIIRS/gnb_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61633,624,"GNB","Guinea-Bissau","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GNB/VIIRS/gnb_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61634,624,"GNB","Guinea-Bissau","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GNB/VIIRS/gnb_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61635,624,"GNB","Guinea-Bissau","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GNB/VIIRS/gnb_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61636,624,"GNB","Guinea-Bissau","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GNB/VIIRS/gnb_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61637,626,"TLS","East Timor","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TLS/VIIRS/tls_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61638,626,"TLS","East Timor","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TLS/VIIRS/tls_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61639,626,"TLS","East Timor","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TLS/VIIRS/tls_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61640,626,"TLS","East Timor","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TLS/VIIRS/tls_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61641,626,"TLS","East Timor","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TLS/VIIRS/tls_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61642,630,"PRI","Puerto Rico","viirs_100m_2012","GIS/Covariates/Global_2000_2020/PRI/VIIRS/pri_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61643,630,"PRI","Puerto Rico","viirs_100m_2013","GIS/Covariates/Global_2000_2020/PRI/VIIRS/pri_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61644,630,"PRI","Puerto Rico","viirs_100m_2014","GIS/Covariates/Global_2000_2020/PRI/VIIRS/pri_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61645,630,"PRI","Puerto Rico","viirs_100m_2015","GIS/Covariates/Global_2000_2020/PRI/VIIRS/pri_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61646,630,"PRI","Puerto Rico","viirs_100m_2016","GIS/Covariates/Global_2000_2020/PRI/VIIRS/pri_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61647,634,"QAT","Qatar","viirs_100m_2012","GIS/Covariates/Global_2000_2020/QAT/VIIRS/qat_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61648,634,"QAT","Qatar","viirs_100m_2013","GIS/Covariates/Global_2000_2020/QAT/VIIRS/qat_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61649,634,"QAT","Qatar","viirs_100m_2014","GIS/Covariates/Global_2000_2020/QAT/VIIRS/qat_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61650,634,"QAT","Qatar","viirs_100m_2015","GIS/Covariates/Global_2000_2020/QAT/VIIRS/qat_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61651,634,"QAT","Qatar","viirs_100m_2016","GIS/Covariates/Global_2000_2020/QAT/VIIRS/qat_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61652,638,"REU","Reunion","viirs_100m_2012","GIS/Covariates/Global_2000_2020/REU/VIIRS/reu_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61653,638,"REU","Reunion","viirs_100m_2013","GIS/Covariates/Global_2000_2020/REU/VIIRS/reu_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61654,638,"REU","Reunion","viirs_100m_2014","GIS/Covariates/Global_2000_2020/REU/VIIRS/reu_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61655,638,"REU","Reunion","viirs_100m_2015","GIS/Covariates/Global_2000_2020/REU/VIIRS/reu_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61656,638,"REU","Reunion","viirs_100m_2016","GIS/Covariates/Global_2000_2020/REU/VIIRS/reu_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61657,642,"ROU","Romania","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ROU/VIIRS/rou_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61658,642,"ROU","Romania","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ROU/VIIRS/rou_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61659,642,"ROU","Romania","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ROU/VIIRS/rou_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61660,642,"ROU","Romania","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ROU/VIIRS/rou_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61661,642,"ROU","Romania","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ROU/VIIRS/rou_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61662,646,"RWA","Rwanda","viirs_100m_2012","GIS/Covariates/Global_2000_2020/RWA/VIIRS/rwa_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61663,646,"RWA","Rwanda","viirs_100m_2013","GIS/Covariates/Global_2000_2020/RWA/VIIRS/rwa_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61664,646,"RWA","Rwanda","viirs_100m_2014","GIS/Covariates/Global_2000_2020/RWA/VIIRS/rwa_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61665,646,"RWA","Rwanda","viirs_100m_2015","GIS/Covariates/Global_2000_2020/RWA/VIIRS/rwa_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61666,646,"RWA","Rwanda","viirs_100m_2016","GIS/Covariates/Global_2000_2020/RWA/VIIRS/rwa_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61667,652,"BLM","Saint Barthelemy","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BLM/VIIRS/blm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61668,652,"BLM","Saint Barthelemy","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BLM/VIIRS/blm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61669,652,"BLM","Saint Barthelemy","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BLM/VIIRS/blm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61670,652,"BLM","Saint Barthelemy","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BLM/VIIRS/blm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61671,652,"BLM","Saint Barthelemy","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BLM/VIIRS/blm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61672,654,"SHN","Saint Helena","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SHN/VIIRS/shn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61673,654,"SHN","Saint Helena","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SHN/VIIRS/shn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61674,654,"SHN","Saint Helena","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SHN/VIIRS/shn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61675,654,"SHN","Saint Helena","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SHN/VIIRS/shn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61676,654,"SHN","Saint Helena","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SHN/VIIRS/shn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61677,659,"KNA","Saint Kitts and Nevis","viirs_100m_2012","GIS/Covariates/Global_2000_2020/KNA/VIIRS/kna_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61678,659,"KNA","Saint Kitts and Nevis","viirs_100m_2013","GIS/Covariates/Global_2000_2020/KNA/VIIRS/kna_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61679,659,"KNA","Saint Kitts and Nevis","viirs_100m_2014","GIS/Covariates/Global_2000_2020/KNA/VIIRS/kna_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61680,659,"KNA","Saint Kitts and Nevis","viirs_100m_2015","GIS/Covariates/Global_2000_2020/KNA/VIIRS/kna_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61681,659,"KNA","Saint Kitts and Nevis","viirs_100m_2016","GIS/Covariates/Global_2000_2020/KNA/VIIRS/kna_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61682,660,"AIA","Anguilla","viirs_100m_2012","GIS/Covariates/Global_2000_2020/AIA/VIIRS/aia_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61683,660,"AIA","Anguilla","viirs_100m_2013","GIS/Covariates/Global_2000_2020/AIA/VIIRS/aia_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61684,660,"AIA","Anguilla","viirs_100m_2014","GIS/Covariates/Global_2000_2020/AIA/VIIRS/aia_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61685,660,"AIA","Anguilla","viirs_100m_2015","GIS/Covariates/Global_2000_2020/AIA/VIIRS/aia_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61686,660,"AIA","Anguilla","viirs_100m_2016","GIS/Covariates/Global_2000_2020/AIA/VIIRS/aia_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61687,662,"LCA","Saint Lucia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/LCA/VIIRS/lca_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61688,662,"LCA","Saint Lucia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/LCA/VIIRS/lca_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61689,662,"LCA","Saint Lucia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/LCA/VIIRS/lca_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61690,662,"LCA","Saint Lucia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/LCA/VIIRS/lca_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61691,662,"LCA","Saint Lucia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/LCA/VIIRS/lca_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61692,663,"MAF","Saint Martin (French part)","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MAF/VIIRS/maf_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61693,663,"MAF","Saint Martin (French part)","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MAF/VIIRS/maf_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61694,663,"MAF","Saint Martin (French part)","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MAF/VIIRS/maf_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61695,663,"MAF","Saint Martin (French part)","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MAF/VIIRS/maf_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61696,663,"MAF","Saint Martin (French part)","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MAF/VIIRS/maf_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61697,666,"SPM","Saint Pierre and Miquelon","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SPM/VIIRS/spm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61698,666,"SPM","Saint Pierre and Miquelon","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SPM/VIIRS/spm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61699,666,"SPM","Saint Pierre and Miquelon","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SPM/VIIRS/spm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61700,666,"SPM","Saint Pierre and Miquelon","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SPM/VIIRS/spm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61701,666,"SPM","Saint Pierre and Miquelon","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SPM/VIIRS/spm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61702,670,"VCT","Saint Vincent and the Grenadines","viirs_100m_2012","GIS/Covariates/Global_2000_2020/VCT/VIIRS/vct_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61703,670,"VCT","Saint Vincent and the Grenadines","viirs_100m_2013","GIS/Covariates/Global_2000_2020/VCT/VIIRS/vct_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61704,670,"VCT","Saint Vincent and the Grenadines","viirs_100m_2014","GIS/Covariates/Global_2000_2020/VCT/VIIRS/vct_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61705,670,"VCT","Saint Vincent and the Grenadines","viirs_100m_2015","GIS/Covariates/Global_2000_2020/VCT/VIIRS/vct_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61706,670,"VCT","Saint Vincent and the Grenadines","viirs_100m_2016","GIS/Covariates/Global_2000_2020/VCT/VIIRS/vct_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61707,674,"SMR","San Marino","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SMR/VIIRS/smr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61708,674,"SMR","San Marino","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SMR/VIIRS/smr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61709,674,"SMR","San Marino","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SMR/VIIRS/smr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61710,674,"SMR","San Marino","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SMR/VIIRS/smr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61711,674,"SMR","San Marino","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SMR/VIIRS/smr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61712,678,"STP","Sao Tome and Principe","viirs_100m_2012","GIS/Covariates/Global_2000_2020/STP/VIIRS/stp_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61713,678,"STP","Sao Tome and Principe","viirs_100m_2013","GIS/Covariates/Global_2000_2020/STP/VIIRS/stp_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61714,678,"STP","Sao Tome and Principe","viirs_100m_2014","GIS/Covariates/Global_2000_2020/STP/VIIRS/stp_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61715,678,"STP","Sao Tome and Principe","viirs_100m_2015","GIS/Covariates/Global_2000_2020/STP/VIIRS/stp_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61716,678,"STP","Sao Tome and Principe","viirs_100m_2016","GIS/Covariates/Global_2000_2020/STP/VIIRS/stp_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61717,682,"SAU","Saudi Arabia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SAU/VIIRS/sau_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61718,682,"SAU","Saudi Arabia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SAU/VIIRS/sau_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61719,682,"SAU","Saudi Arabia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SAU/VIIRS/sau_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61720,682,"SAU","Saudi Arabia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SAU/VIIRS/sau_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61721,682,"SAU","Saudi Arabia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SAU/VIIRS/sau_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61722,686,"SEN","Senegal","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SEN/VIIRS/sen_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61723,686,"SEN","Senegal","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SEN/VIIRS/sen_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61724,686,"SEN","Senegal","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SEN/VIIRS/sen_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61725,686,"SEN","Senegal","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SEN/VIIRS/sen_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61726,686,"SEN","Senegal","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SEN/VIIRS/sen_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61727,688,"SRB","Serbia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SRB/VIIRS/srb_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61728,688,"SRB","Serbia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SRB/VIIRS/srb_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61729,688,"SRB","Serbia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SRB/VIIRS/srb_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61730,688,"SRB","Serbia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SRB/VIIRS/srb_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61731,688,"SRB","Serbia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SRB/VIIRS/srb_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61732,690,"SYC","Seychelles","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SYC/VIIRS/syc_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61733,690,"SYC","Seychelles","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SYC/VIIRS/syc_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61734,690,"SYC","Seychelles","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SYC/VIIRS/syc_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61735,690,"SYC","Seychelles","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SYC/VIIRS/syc_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61736,690,"SYC","Seychelles","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SYC/VIIRS/syc_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61737,694,"SLE","Sierra Leone","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SLE/VIIRS/sle_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61738,694,"SLE","Sierra Leone","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SLE/VIIRS/sle_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61739,694,"SLE","Sierra Leone","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SLE/VIIRS/sle_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61740,694,"SLE","Sierra Leone","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SLE/VIIRS/sle_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61741,694,"SLE","Sierra Leone","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SLE/VIIRS/sle_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61742,702,"SGP","Singapore","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SGP/VIIRS/sgp_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61743,702,"SGP","Singapore","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SGP/VIIRS/sgp_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61744,702,"SGP","Singapore","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SGP/VIIRS/sgp_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61745,702,"SGP","Singapore","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SGP/VIIRS/sgp_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61746,702,"SGP","Singapore","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SGP/VIIRS/sgp_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61747,703,"SVK","Slovakia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SVK/VIIRS/svk_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61748,703,"SVK","Slovakia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SVK/VIIRS/svk_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61749,703,"SVK","Slovakia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SVK/VIIRS/svk_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61750,703,"SVK","Slovakia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SVK/VIIRS/svk_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61751,703,"SVK","Slovakia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SVK/VIIRS/svk_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61752,704,"VNM","Vietnam","viirs_100m_2012","GIS/Covariates/Global_2000_2020/VNM/VIIRS/vnm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61753,704,"VNM","Vietnam","viirs_100m_2013","GIS/Covariates/Global_2000_2020/VNM/VIIRS/vnm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61754,704,"VNM","Vietnam","viirs_100m_2014","GIS/Covariates/Global_2000_2020/VNM/VIIRS/vnm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61755,704,"VNM","Vietnam","viirs_100m_2015","GIS/Covariates/Global_2000_2020/VNM/VIIRS/vnm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61756,704,"VNM","Vietnam","viirs_100m_2016","GIS/Covariates/Global_2000_2020/VNM/VIIRS/vnm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61757,705,"SVN","Slovenia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SVN/VIIRS/svn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61758,705,"SVN","Slovenia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SVN/VIIRS/svn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61759,705,"SVN","Slovenia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SVN/VIIRS/svn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61760,705,"SVN","Slovenia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SVN/VIIRS/svn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61761,705,"SVN","Slovenia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SVN/VIIRS/svn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61762,706,"SOM","Somalia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SOM/VIIRS/som_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61763,706,"SOM","Somalia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SOM/VIIRS/som_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61764,706,"SOM","Somalia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SOM/VIIRS/som_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61765,706,"SOM","Somalia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SOM/VIIRS/som_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61766,706,"SOM","Somalia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SOM/VIIRS/som_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61767,710,"ZAF","South Africa","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ZAF/VIIRS/zaf_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61768,710,"ZAF","South Africa","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ZAF/VIIRS/zaf_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61769,710,"ZAF","South Africa","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ZAF/VIIRS/zaf_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61770,710,"ZAF","South Africa","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ZAF/VIIRS/zaf_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61771,710,"ZAF","South Africa","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ZAF/VIIRS/zaf_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61772,716,"ZWE","Zimbabwe","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ZWE/VIIRS/zwe_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61773,716,"ZWE","Zimbabwe","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ZWE/VIIRS/zwe_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61774,716,"ZWE","Zimbabwe","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ZWE/VIIRS/zwe_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61775,716,"ZWE","Zimbabwe","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ZWE/VIIRS/zwe_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61776,716,"ZWE","Zimbabwe","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ZWE/VIIRS/zwe_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61777,724,"ESP","Spain","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ESP/VIIRS/esp_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61778,724,"ESP","Spain","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ESP/VIIRS/esp_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61779,724,"ESP","Spain","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ESP/VIIRS/esp_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61780,724,"ESP","Spain","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ESP/VIIRS/esp_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61781,724,"ESP","Spain","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ESP/VIIRS/esp_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61782,728,"SSD","South Sudan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SSD/VIIRS/ssd_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61783,728,"SSD","South Sudan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SSD/VIIRS/ssd_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61784,728,"SSD","South Sudan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SSD/VIIRS/ssd_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61785,728,"SSD","South Sudan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SSD/VIIRS/ssd_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61786,728,"SSD","South Sudan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SSD/VIIRS/ssd_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61787,729,"SDN","Sudan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SDN/VIIRS/sdn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61788,729,"SDN","Sudan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SDN/VIIRS/sdn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61789,729,"SDN","Sudan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SDN/VIIRS/sdn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61790,729,"SDN","Sudan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SDN/VIIRS/sdn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61791,729,"SDN","Sudan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SDN/VIIRS/sdn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61792,732,"ESH","Western Sahara","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ESH/VIIRS/esh_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61793,732,"ESH","Western Sahara","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ESH/VIIRS/esh_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61794,732,"ESH","Western Sahara","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ESH/VIIRS/esh_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61795,732,"ESH","Western Sahara","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ESH/VIIRS/esh_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61796,732,"ESH","Western Sahara","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ESH/VIIRS/esh_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61797,740,"SUR","Suriname","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SUR/VIIRS/sur_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61798,740,"SUR","Suriname","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SUR/VIIRS/sur_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61799,740,"SUR","Suriname","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SUR/VIIRS/sur_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61800,740,"SUR","Suriname","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SUR/VIIRS/sur_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61801,740,"SUR","Suriname","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SUR/VIIRS/sur_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61802,744,"SJM","Svalbard and Jan Mayen Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SJM/VIIRS/sjm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61803,744,"SJM","Svalbard and Jan Mayen Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SJM/VIIRS/sjm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61804,744,"SJM","Svalbard and Jan Mayen Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SJM/VIIRS/sjm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61805,744,"SJM","Svalbard and Jan Mayen Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SJM/VIIRS/sjm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61806,744,"SJM","Svalbard and Jan Mayen Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SJM/VIIRS/sjm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61807,748,"SWZ","Swaziland","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SWZ/VIIRS/swz_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61808,748,"SWZ","Swaziland","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SWZ/VIIRS/swz_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61809,748,"SWZ","Swaziland","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SWZ/VIIRS/swz_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61810,748,"SWZ","Swaziland","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SWZ/VIIRS/swz_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61811,748,"SWZ","Swaziland","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SWZ/VIIRS/swz_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61812,752,"SWE","Sweden","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SWE/VIIRS/swe_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61813,752,"SWE","Sweden","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SWE/VIIRS/swe_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61814,752,"SWE","Sweden","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SWE/VIIRS/swe_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61815,752,"SWE","Sweden","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SWE/VIIRS/swe_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61816,752,"SWE","Sweden","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SWE/VIIRS/swe_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61817,756,"CHE","Switzerland","viirs_100m_2012","GIS/Covariates/Global_2000_2020/CHE/VIIRS/che_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61818,756,"CHE","Switzerland","viirs_100m_2013","GIS/Covariates/Global_2000_2020/CHE/VIIRS/che_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61819,756,"CHE","Switzerland","viirs_100m_2014","GIS/Covariates/Global_2000_2020/CHE/VIIRS/che_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61820,756,"CHE","Switzerland","viirs_100m_2015","GIS/Covariates/Global_2000_2020/CHE/VIIRS/che_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61821,756,"CHE","Switzerland","viirs_100m_2016","GIS/Covariates/Global_2000_2020/CHE/VIIRS/che_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61822,760,"SYR","Syria","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SYR/VIIRS/syr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61823,760,"SYR","Syria","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SYR/VIIRS/syr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61824,760,"SYR","Syria","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SYR/VIIRS/syr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61825,760,"SYR","Syria","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SYR/VIIRS/syr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61826,760,"SYR","Syria","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SYR/VIIRS/syr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61827,762,"TJK","Tajikistan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TJK/VIIRS/tjk_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61828,762,"TJK","Tajikistan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TJK/VIIRS/tjk_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61829,762,"TJK","Tajikistan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TJK/VIIRS/tjk_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61830,762,"TJK","Tajikistan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TJK/VIIRS/tjk_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61831,762,"TJK","Tajikistan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TJK/VIIRS/tjk_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61832,764,"THA","Thailand","viirs_100m_2012","GIS/Covariates/Global_2000_2020/THA/VIIRS/tha_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61833,764,"THA","Thailand","viirs_100m_2013","GIS/Covariates/Global_2000_2020/THA/VIIRS/tha_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61834,764,"THA","Thailand","viirs_100m_2014","GIS/Covariates/Global_2000_2020/THA/VIIRS/tha_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61835,764,"THA","Thailand","viirs_100m_2015","GIS/Covariates/Global_2000_2020/THA/VIIRS/tha_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61836,764,"THA","Thailand","viirs_100m_2016","GIS/Covariates/Global_2000_2020/THA/VIIRS/tha_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61837,768,"TGO","Togo","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TGO/VIIRS/tgo_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61838,768,"TGO","Togo","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TGO/VIIRS/tgo_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61839,768,"TGO","Togo","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TGO/VIIRS/tgo_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61840,768,"TGO","Togo","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TGO/VIIRS/tgo_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61841,768,"TGO","Togo","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TGO/VIIRS/tgo_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61842,772,"TKL","Tokelau","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TKL/VIIRS/tkl_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61843,772,"TKL","Tokelau","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TKL/VIIRS/tkl_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61844,772,"TKL","Tokelau","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TKL/VIIRS/tkl_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61845,772,"TKL","Tokelau","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TKL/VIIRS/tkl_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61846,772,"TKL","Tokelau","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TKL/VIIRS/tkl_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61847,776,"TON","Tonga","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TON/VIIRS/ton_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61848,776,"TON","Tonga","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TON/VIIRS/ton_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61849,776,"TON","Tonga","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TON/VIIRS/ton_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61850,776,"TON","Tonga","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TON/VIIRS/ton_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61851,776,"TON","Tonga","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TON/VIIRS/ton_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61852,780,"TTO","Trinidad and Tobago","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TTO/VIIRS/tto_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61853,780,"TTO","Trinidad and Tobago","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TTO/VIIRS/tto_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61854,780,"TTO","Trinidad and Tobago","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TTO/VIIRS/tto_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61855,780,"TTO","Trinidad and Tobago","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TTO/VIIRS/tto_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61856,780,"TTO","Trinidad and Tobago","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TTO/VIIRS/tto_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61857,784,"ARE","United Arab Emirates","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ARE/VIIRS/are_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61858,784,"ARE","United Arab Emirates","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ARE/VIIRS/are_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61859,784,"ARE","United Arab Emirates","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ARE/VIIRS/are_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61860,784,"ARE","United Arab Emirates","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ARE/VIIRS/are_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61861,784,"ARE","United Arab Emirates","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ARE/VIIRS/are_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61862,788,"TUN","Tunisia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TUN/VIIRS/tun_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61863,788,"TUN","Tunisia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TUN/VIIRS/tun_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61864,788,"TUN","Tunisia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TUN/VIIRS/tun_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61865,788,"TUN","Tunisia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TUN/VIIRS/tun_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61866,788,"TUN","Tunisia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TUN/VIIRS/tun_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61867,792,"TUR","Turkey","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TUR/VIIRS/tur_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61868,792,"TUR","Turkey","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TUR/VIIRS/tur_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61869,792,"TUR","Turkey","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TUR/VIIRS/tur_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61870,792,"TUR","Turkey","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TUR/VIIRS/tur_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61871,792,"TUR","Turkey","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TUR/VIIRS/tur_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61872,795,"TKM","Turkmenistan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TKM/VIIRS/tkm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61873,795,"TKM","Turkmenistan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TKM/VIIRS/tkm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61874,795,"TKM","Turkmenistan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TKM/VIIRS/tkm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61875,795,"TKM","Turkmenistan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TKM/VIIRS/tkm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61876,795,"TKM","Turkmenistan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TKM/VIIRS/tkm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61877,796,"TCA","Turks and Caicos Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TCA/VIIRS/tca_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61878,796,"TCA","Turks and Caicos Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TCA/VIIRS/tca_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61879,796,"TCA","Turks and Caicos Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TCA/VIIRS/tca_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61880,796,"TCA","Turks and Caicos Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TCA/VIIRS/tca_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61881,796,"TCA","Turks and Caicos Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TCA/VIIRS/tca_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61882,798,"TUV","Tuvalu","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TUV/VIIRS/tuv_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61883,798,"TUV","Tuvalu","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TUV/VIIRS/tuv_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61884,798,"TUV","Tuvalu","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TUV/VIIRS/tuv_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61885,798,"TUV","Tuvalu","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TUV/VIIRS/tuv_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61886,798,"TUV","Tuvalu","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TUV/VIIRS/tuv_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61887,800,"UGA","Uganda","viirs_100m_2012","GIS/Covariates/Global_2000_2020/UGA/VIIRS/uga_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61888,800,"UGA","Uganda","viirs_100m_2013","GIS/Covariates/Global_2000_2020/UGA/VIIRS/uga_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61889,800,"UGA","Uganda","viirs_100m_2014","GIS/Covariates/Global_2000_2020/UGA/VIIRS/uga_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61890,800,"UGA","Uganda","viirs_100m_2015","GIS/Covariates/Global_2000_2020/UGA/VIIRS/uga_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61891,800,"UGA","Uganda","viirs_100m_2016","GIS/Covariates/Global_2000_2020/UGA/VIIRS/uga_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61892,804,"UKR","Ukraine","viirs_100m_2012","GIS/Covariates/Global_2000_2020/UKR/VIIRS/ukr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61893,804,"UKR","Ukraine","viirs_100m_2013","GIS/Covariates/Global_2000_2020/UKR/VIIRS/ukr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61894,804,"UKR","Ukraine","viirs_100m_2014","GIS/Covariates/Global_2000_2020/UKR/VIIRS/ukr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61895,804,"UKR","Ukraine","viirs_100m_2015","GIS/Covariates/Global_2000_2020/UKR/VIIRS/ukr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61896,804,"UKR","Ukraine","viirs_100m_2016","GIS/Covariates/Global_2000_2020/UKR/VIIRS/ukr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61897,807,"MKD","Macedonia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/MKD/VIIRS/mkd_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61898,807,"MKD","Macedonia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/MKD/VIIRS/mkd_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61899,807,"MKD","Macedonia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/MKD/VIIRS/mkd_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61900,807,"MKD","Macedonia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/MKD/VIIRS/mkd_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61901,807,"MKD","Macedonia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/MKD/VIIRS/mkd_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61902,818,"EGY","Egypt","viirs_100m_2012","GIS/Covariates/Global_2000_2020/EGY/VIIRS/egy_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61903,818,"EGY","Egypt","viirs_100m_2013","GIS/Covariates/Global_2000_2020/EGY/VIIRS/egy_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61904,818,"EGY","Egypt","viirs_100m_2014","GIS/Covariates/Global_2000_2020/EGY/VIIRS/egy_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61905,818,"EGY","Egypt","viirs_100m_2015","GIS/Covariates/Global_2000_2020/EGY/VIIRS/egy_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61906,818,"EGY","Egypt","viirs_100m_2016","GIS/Covariates/Global_2000_2020/EGY/VIIRS/egy_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61907,826,"GBR","United Kingdom","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GBR/VIIRS/gbr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61908,826,"GBR","United Kingdom","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GBR/VIIRS/gbr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61909,826,"GBR","United Kingdom","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GBR/VIIRS/gbr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61910,826,"GBR","United Kingdom","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GBR/VIIRS/gbr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61911,826,"GBR","United Kingdom","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GBR/VIIRS/gbr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61912,831,"GGY","Guernsey","viirs_100m_2012","GIS/Covariates/Global_2000_2020/GGY/VIIRS/ggy_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61913,831,"GGY","Guernsey","viirs_100m_2013","GIS/Covariates/Global_2000_2020/GGY/VIIRS/ggy_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61914,831,"GGY","Guernsey","viirs_100m_2014","GIS/Covariates/Global_2000_2020/GGY/VIIRS/ggy_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61915,831,"GGY","Guernsey","viirs_100m_2015","GIS/Covariates/Global_2000_2020/GGY/VIIRS/ggy_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61916,831,"GGY","Guernsey","viirs_100m_2016","GIS/Covariates/Global_2000_2020/GGY/VIIRS/ggy_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61917,832,"JEY","Jersey","viirs_100m_2012","GIS/Covariates/Global_2000_2020/JEY/VIIRS/jey_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61918,832,"JEY","Jersey","viirs_100m_2013","GIS/Covariates/Global_2000_2020/JEY/VIIRS/jey_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61919,832,"JEY","Jersey","viirs_100m_2014","GIS/Covariates/Global_2000_2020/JEY/VIIRS/jey_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61920,832,"JEY","Jersey","viirs_100m_2015","GIS/Covariates/Global_2000_2020/JEY/VIIRS/jey_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61921,832,"JEY","Jersey","viirs_100m_2016","GIS/Covariates/Global_2000_2020/JEY/VIIRS/jey_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61922,833,"IMN","Isle of Man","viirs_100m_2012","GIS/Covariates/Global_2000_2020/IMN/VIIRS/imn_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61923,833,"IMN","Isle of Man","viirs_100m_2013","GIS/Covariates/Global_2000_2020/IMN/VIIRS/imn_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61924,833,"IMN","Isle of Man","viirs_100m_2014","GIS/Covariates/Global_2000_2020/IMN/VIIRS/imn_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61925,833,"IMN","Isle of Man","viirs_100m_2015","GIS/Covariates/Global_2000_2020/IMN/VIIRS/imn_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61926,833,"IMN","Isle of Man","viirs_100m_2016","GIS/Covariates/Global_2000_2020/IMN/VIIRS/imn_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61927,834,"TZA","Tanzania","viirs_100m_2012","GIS/Covariates/Global_2000_2020/TZA/VIIRS/tza_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61928,834,"TZA","Tanzania","viirs_100m_2013","GIS/Covariates/Global_2000_2020/TZA/VIIRS/tza_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61929,834,"TZA","Tanzania","viirs_100m_2014","GIS/Covariates/Global_2000_2020/TZA/VIIRS/tza_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61930,834,"TZA","Tanzania","viirs_100m_2015","GIS/Covariates/Global_2000_2020/TZA/VIIRS/tza_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61931,834,"TZA","Tanzania","viirs_100m_2016","GIS/Covariates/Global_2000_2020/TZA/VIIRS/tza_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61932,854,"BFA","Burkina Faso","viirs_100m_2012","GIS/Covariates/Global_2000_2020/BFA/VIIRS/bfa_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61933,854,"BFA","Burkina Faso","viirs_100m_2013","GIS/Covariates/Global_2000_2020/BFA/VIIRS/bfa_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61934,854,"BFA","Burkina Faso","viirs_100m_2014","GIS/Covariates/Global_2000_2020/BFA/VIIRS/bfa_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61935,854,"BFA","Burkina Faso","viirs_100m_2015","GIS/Covariates/Global_2000_2020/BFA/VIIRS/bfa_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61936,854,"BFA","Burkina Faso","viirs_100m_2016","GIS/Covariates/Global_2000_2020/BFA/VIIRS/bfa_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61937,858,"URY","Uruguay","viirs_100m_2012","GIS/Covariates/Global_2000_2020/URY/VIIRS/ury_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61938,858,"URY","Uruguay","viirs_100m_2013","GIS/Covariates/Global_2000_2020/URY/VIIRS/ury_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61939,858,"URY","Uruguay","viirs_100m_2014","GIS/Covariates/Global_2000_2020/URY/VIIRS/ury_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61940,858,"URY","Uruguay","viirs_100m_2015","GIS/Covariates/Global_2000_2020/URY/VIIRS/ury_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61941,858,"URY","Uruguay","viirs_100m_2016","GIS/Covariates/Global_2000_2020/URY/VIIRS/ury_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61942,860,"UZB","Uzbekistan","viirs_100m_2012","GIS/Covariates/Global_2000_2020/UZB/VIIRS/uzb_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61943,860,"UZB","Uzbekistan","viirs_100m_2013","GIS/Covariates/Global_2000_2020/UZB/VIIRS/uzb_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61944,860,"UZB","Uzbekistan","viirs_100m_2014","GIS/Covariates/Global_2000_2020/UZB/VIIRS/uzb_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61945,860,"UZB","Uzbekistan","viirs_100m_2015","GIS/Covariates/Global_2000_2020/UZB/VIIRS/uzb_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61946,860,"UZB","Uzbekistan","viirs_100m_2016","GIS/Covariates/Global_2000_2020/UZB/VIIRS/uzb_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61947,862,"VEN","Venezuela","viirs_100m_2012","GIS/Covariates/Global_2000_2020/VEN/VIIRS/ven_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61948,862,"VEN","Venezuela","viirs_100m_2013","GIS/Covariates/Global_2000_2020/VEN/VIIRS/ven_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61949,862,"VEN","Venezuela","viirs_100m_2014","GIS/Covariates/Global_2000_2020/VEN/VIIRS/ven_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61950,862,"VEN","Venezuela","viirs_100m_2015","GIS/Covariates/Global_2000_2020/VEN/VIIRS/ven_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61951,862,"VEN","Venezuela","viirs_100m_2016","GIS/Covariates/Global_2000_2020/VEN/VIIRS/ven_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61952,876,"WLF","Wallis and Futuna","viirs_100m_2012","GIS/Covariates/Global_2000_2020/WLF/VIIRS/wlf_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61953,876,"WLF","Wallis and Futuna","viirs_100m_2013","GIS/Covariates/Global_2000_2020/WLF/VIIRS/wlf_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61954,876,"WLF","Wallis and Futuna","viirs_100m_2014","GIS/Covariates/Global_2000_2020/WLF/VIIRS/wlf_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61955,876,"WLF","Wallis and Futuna","viirs_100m_2015","GIS/Covariates/Global_2000_2020/WLF/VIIRS/wlf_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61956,876,"WLF","Wallis and Futuna","viirs_100m_2016","GIS/Covariates/Global_2000_2020/WLF/VIIRS/wlf_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61957,882,"WSM","Samoa","viirs_100m_2012","GIS/Covariates/Global_2000_2020/WSM/VIIRS/wsm_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61958,882,"WSM","Samoa","viirs_100m_2013","GIS/Covariates/Global_2000_2020/WSM/VIIRS/wsm_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61959,882,"WSM","Samoa","viirs_100m_2014","GIS/Covariates/Global_2000_2020/WSM/VIIRS/wsm_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61960,882,"WSM","Samoa","viirs_100m_2015","GIS/Covariates/Global_2000_2020/WSM/VIIRS/wsm_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61961,882,"WSM","Samoa","viirs_100m_2016","GIS/Covariates/Global_2000_2020/WSM/VIIRS/wsm_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61962,887,"YEM","Yemen","viirs_100m_2012","GIS/Covariates/Global_2000_2020/YEM/VIIRS/yem_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61963,887,"YEM","Yemen","viirs_100m_2013","GIS/Covariates/Global_2000_2020/YEM/VIIRS/yem_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61964,887,"YEM","Yemen","viirs_100m_2014","GIS/Covariates/Global_2000_2020/YEM/VIIRS/yem_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61965,887,"YEM","Yemen","viirs_100m_2015","GIS/Covariates/Global_2000_2020/YEM/VIIRS/yem_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61966,887,"YEM","Yemen","viirs_100m_2016","GIS/Covariates/Global_2000_2020/YEM/VIIRS/yem_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61967,894,"ZMB","Zambia","viirs_100m_2012","GIS/Covariates/Global_2000_2020/ZMB/VIIRS/zmb_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61968,894,"ZMB","Zambia","viirs_100m_2013","GIS/Covariates/Global_2000_2020/ZMB/VIIRS/zmb_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61969,894,"ZMB","Zambia","viirs_100m_2014","GIS/Covariates/Global_2000_2020/ZMB/VIIRS/zmb_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61970,894,"ZMB","Zambia","viirs_100m_2015","GIS/Covariates/Global_2000_2020/ZMB/VIIRS/zmb_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61971,894,"ZMB","Zambia","viirs_100m_2016","GIS/Covariates/Global_2000_2020/ZMB/VIIRS/zmb_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61972,900,"KOS","Kosovo","viirs_100m_2012","GIS/Covariates/Global_2000_2020/KOS/VIIRS/kos_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61973,900,"KOS","Kosovo","viirs_100m_2013","GIS/Covariates/Global_2000_2020/KOS/VIIRS/kos_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61974,900,"KOS","Kosovo","viirs_100m_2014","GIS/Covariates/Global_2000_2020/KOS/VIIRS/kos_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61975,900,"KOS","Kosovo","viirs_100m_2015","GIS/Covariates/Global_2000_2020/KOS/VIIRS/kos_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61976,900,"KOS","Kosovo","viirs_100m_2016","GIS/Covariates/Global_2000_2020/KOS/VIIRS/kos_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61977,901,"SPR","Spratly Islands","viirs_100m_2012","GIS/Covariates/Global_2000_2020/SPR/VIIRS/spr_viirs_100m_2012.tif","VIIRS night-time lights 2012"
61978,901,"SPR","Spratly Islands","viirs_100m_2013","GIS/Covariates/Global_2000_2020/SPR/VIIRS/spr_viirs_100m_2013.tif","VIIRS night-time lights 2013"
61979,901,"SPR","Spratly Islands","viirs_100m_2014","GIS/Covariates/Global_2000_2020/SPR/VIIRS/spr_viirs_100m_2014.tif","VIIRS night-time lights 2014"
61980,901,"SPR","Spratly Islands","viirs_100m_2015","GIS/Covariates/Global_2000_2020/SPR/VIIRS/spr_viirs_100m_2015.tif","VIIRS night-time lights 2015"
61981,901,"SPR","Spratly Islands","viirs_100m_2016","GIS/Covariates/Global_2000_2020/SPR/VIIRS/spr_viirs_100m_2016.tif","VIIRS night-time lights 2016"
61982,643,"RUS","Russia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
61983,643,"RUS","Russia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
61984,643,"RUS","Russia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
61985,643,"RUS","Russia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
61986,643,"RUS","Russia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
61987,643,"RUS","Russia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
61988,643,"RUS","Russia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
61989,643,"RUS","Russia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
61990,643,"RUS","Russia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
61991,643,"RUS","Russia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
61992,643,"RUS","Russia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
61993,643,"RUS","Russia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
61994,643,"RUS","Russia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
61995,643,"RUS","Russia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
61996,643,"RUS","Russia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
61997,643,"RUS","Russia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
61998,643,"RUS","Russia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
61999,643,"RUS","Russia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62000,643,"RUS","Russia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62001,643,"RUS","Russia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62002,643,"RUS","Russia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62003,643,"RUS","Russia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62004,643,"RUS","Russia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62005,643,"RUS","Russia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62006,643,"RUS","Russia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62007,643,"RUS","Russia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62008,643,"RUS","Russia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62009,643,"RUS","Russia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62010,643,"RUS","Russia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62011,643,"RUS","Russia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62012,643,"RUS","Russia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62013,643,"RUS","Russia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62014,643,"RUS","Russia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62015,643,"RUS","Russia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62016,643,"RUS","Russia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62017,643,"RUS","Russia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RUS/rus_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62018,360,"IDN","Indonesia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62019,360,"IDN","Indonesia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62020,360,"IDN","Indonesia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62021,360,"IDN","Indonesia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62022,360,"IDN","Indonesia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62023,360,"IDN","Indonesia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62024,360,"IDN","Indonesia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62025,360,"IDN","Indonesia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62026,360,"IDN","Indonesia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62027,360,"IDN","Indonesia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62028,360,"IDN","Indonesia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62029,360,"IDN","Indonesia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62030,360,"IDN","Indonesia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62031,360,"IDN","Indonesia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62032,360,"IDN","Indonesia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62033,360,"IDN","Indonesia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62034,360,"IDN","Indonesia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62035,360,"IDN","Indonesia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62036,360,"IDN","Indonesia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62037,360,"IDN","Indonesia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62038,360,"IDN","Indonesia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62039,360,"IDN","Indonesia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62040,360,"IDN","Indonesia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62041,360,"IDN","Indonesia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62042,360,"IDN","Indonesia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62043,360,"IDN","Indonesia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62044,360,"IDN","Indonesia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62045,360,"IDN","Indonesia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62046,360,"IDN","Indonesia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62047,360,"IDN","Indonesia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62048,360,"IDN","Indonesia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62049,360,"IDN","Indonesia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62050,360,"IDN","Indonesia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62051,360,"IDN","Indonesia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62052,360,"IDN","Indonesia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62053,360,"IDN","Indonesia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IDN/idn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62054,840,"USA","United States","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62055,840,"USA","United States","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62056,840,"USA","United States","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62057,840,"USA","United States","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62058,840,"USA","United States","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62059,840,"USA","United States","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62060,840,"USA","United States","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62061,840,"USA","United States","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62062,840,"USA","United States","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62063,840,"USA","United States","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62064,840,"USA","United States","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62065,840,"USA","United States","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62066,840,"USA","United States","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62067,840,"USA","United States","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62068,840,"USA","United States","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62069,840,"USA","United States","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62070,840,"USA","United States","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62071,840,"USA","United States","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62072,840,"USA","United States","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62073,840,"USA","United States","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62074,840,"USA","United States","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62075,840,"USA","United States","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62076,840,"USA","United States","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62077,840,"USA","United States","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62078,840,"USA","United States","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62079,840,"USA","United States","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62080,840,"USA","United States","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62081,840,"USA","United States","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62082,840,"USA","United States","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62083,840,"USA","United States","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62084,840,"USA","United States","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62085,840,"USA","United States","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62086,840,"USA","United States","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62087,840,"USA","United States","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62088,840,"USA","United States","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62089,840,"USA","United States","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/USA/usa_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62090,850,"VIR","Virgin_Islands_U_S","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62091,850,"VIR","Virgin_Islands_U_S","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62092,850,"VIR","Virgin_Islands_U_S","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62093,850,"VIR","Virgin_Islands_U_S","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62094,850,"VIR","Virgin_Islands_U_S","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62095,850,"VIR","Virgin_Islands_U_S","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62096,850,"VIR","Virgin_Islands_U_S","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62097,850,"VIR","Virgin_Islands_U_S","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62098,850,"VIR","Virgin_Islands_U_S","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62099,850,"VIR","Virgin_Islands_U_S","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62100,850,"VIR","Virgin_Islands_U_S","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62101,850,"VIR","Virgin_Islands_U_S","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62102,850,"VIR","Virgin_Islands_U_S","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62103,850,"VIR","Virgin_Islands_U_S","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62104,850,"VIR","Virgin_Islands_U_S","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62105,850,"VIR","Virgin_Islands_U_S","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62106,850,"VIR","Virgin_Islands_U_S","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62107,850,"VIR","Virgin_Islands_U_S","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62108,850,"VIR","Virgin_Islands_U_S","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62109,850,"VIR","Virgin_Islands_U_S","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62110,850,"VIR","Virgin_Islands_U_S","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62111,850,"VIR","Virgin_Islands_U_S","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62112,850,"VIR","Virgin_Islands_U_S","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62113,850,"VIR","Virgin_Islands_U_S","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62114,850,"VIR","Virgin_Islands_U_S","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62115,850,"VIR","Virgin_Islands_U_S","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62116,850,"VIR","Virgin_Islands_U_S","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62117,850,"VIR","Virgin_Islands_U_S","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62118,850,"VIR","Virgin_Islands_U_S","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62119,850,"VIR","Virgin_Islands_U_S","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62120,850,"VIR","Virgin_Islands_U_S","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62121,850,"VIR","Virgin_Islands_U_S","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62122,850,"VIR","Virgin_Islands_U_S","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62123,850,"VIR","Virgin_Islands_U_S","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62124,850,"VIR","Virgin_Islands_U_S","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62125,850,"VIR","Virgin_Islands_U_S","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VIR/vir_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62126,304,"GRL","Greenland","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62127,304,"GRL","Greenland","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62128,304,"GRL","Greenland","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62129,304,"GRL","Greenland","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62130,304,"GRL","Greenland","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62131,304,"GRL","Greenland","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62132,304,"GRL","Greenland","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62133,304,"GRL","Greenland","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62134,304,"GRL","Greenland","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62135,304,"GRL","Greenland","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62136,304,"GRL","Greenland","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62137,304,"GRL","Greenland","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62138,304,"GRL","Greenland","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62139,304,"GRL","Greenland","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62140,304,"GRL","Greenland","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62141,304,"GRL","Greenland","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62142,304,"GRL","Greenland","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62143,304,"GRL","Greenland","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62144,304,"GRL","Greenland","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62145,304,"GRL","Greenland","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62146,304,"GRL","Greenland","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62147,304,"GRL","Greenland","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62148,304,"GRL","Greenland","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62149,304,"GRL","Greenland","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62150,304,"GRL","Greenland","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62151,304,"GRL","Greenland","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62152,304,"GRL","Greenland","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62153,304,"GRL","Greenland","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62154,304,"GRL","Greenland","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62155,304,"GRL","Greenland","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62156,304,"GRL","Greenland","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62157,304,"GRL","Greenland","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62158,304,"GRL","Greenland","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62159,304,"GRL","Greenland","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62160,304,"GRL","Greenland","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62161,304,"GRL","Greenland","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRL/grl_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62162,156,"CHN","China","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62163,156,"CHN","China","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62164,156,"CHN","China","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62165,156,"CHN","China","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62166,156,"CHN","China","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62167,156,"CHN","China","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62168,156,"CHN","China","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62169,156,"CHN","China","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62170,156,"CHN","China","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62171,156,"CHN","China","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62172,156,"CHN","China","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62173,156,"CHN","China","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62174,156,"CHN","China","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62175,156,"CHN","China","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62176,156,"CHN","China","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62177,156,"CHN","China","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62178,156,"CHN","China","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62179,156,"CHN","China","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62180,156,"CHN","China","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62181,156,"CHN","China","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62182,156,"CHN","China","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62183,156,"CHN","China","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62184,156,"CHN","China","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62185,156,"CHN","China","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62186,156,"CHN","China","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62187,156,"CHN","China","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62188,156,"CHN","China","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62189,156,"CHN","China","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62190,156,"CHN","China","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62191,156,"CHN","China","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62192,156,"CHN","China","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62193,156,"CHN","China","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62194,156,"CHN","China","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62195,156,"CHN","China","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62196,156,"CHN","China","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62197,156,"CHN","China","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHN/chn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62198,36,"AUS","Australia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62199,36,"AUS","Australia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62200,36,"AUS","Australia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62201,36,"AUS","Australia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62202,36,"AUS","Australia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62203,36,"AUS","Australia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62204,36,"AUS","Australia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62205,36,"AUS","Australia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62206,36,"AUS","Australia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62207,36,"AUS","Australia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62208,36,"AUS","Australia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62209,36,"AUS","Australia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62210,36,"AUS","Australia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62211,36,"AUS","Australia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62212,36,"AUS","Australia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62213,36,"AUS","Australia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62214,36,"AUS","Australia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62215,36,"AUS","Australia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62216,36,"AUS","Australia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62217,36,"AUS","Australia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62218,36,"AUS","Australia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62219,36,"AUS","Australia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62220,36,"AUS","Australia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62221,36,"AUS","Australia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62222,36,"AUS","Australia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62223,36,"AUS","Australia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62224,36,"AUS","Australia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62225,36,"AUS","Australia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62226,36,"AUS","Australia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62227,36,"AUS","Australia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62228,36,"AUS","Australia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62229,36,"AUS","Australia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62230,36,"AUS","Australia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62231,36,"AUS","Australia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62232,36,"AUS","Australia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62233,36,"AUS","Australia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUS/aus_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62234,76,"BRA","Brazil","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62235,76,"BRA","Brazil","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62236,76,"BRA","Brazil","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62237,76,"BRA","Brazil","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62238,76,"BRA","Brazil","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62239,76,"BRA","Brazil","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62240,76,"BRA","Brazil","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62241,76,"BRA","Brazil","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62242,76,"BRA","Brazil","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62243,76,"BRA","Brazil","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62244,76,"BRA","Brazil","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62245,76,"BRA","Brazil","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62246,76,"BRA","Brazil","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62247,76,"BRA","Brazil","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62248,76,"BRA","Brazil","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62249,76,"BRA","Brazil","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62250,76,"BRA","Brazil","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62251,76,"BRA","Brazil","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62252,76,"BRA","Brazil","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62253,76,"BRA","Brazil","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62254,76,"BRA","Brazil","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62255,76,"BRA","Brazil","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62256,76,"BRA","Brazil","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62257,76,"BRA","Brazil","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62258,76,"BRA","Brazil","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62259,76,"BRA","Brazil","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62260,76,"BRA","Brazil","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62261,76,"BRA","Brazil","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62262,76,"BRA","Brazil","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62263,76,"BRA","Brazil","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62264,76,"BRA","Brazil","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62265,76,"BRA","Brazil","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62266,76,"BRA","Brazil","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62267,76,"BRA","Brazil","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62268,76,"BRA","Brazil","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62269,76,"BRA","Brazil","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRA/bra_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62270,124,"CAN","Canada","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62271,124,"CAN","Canada","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62272,124,"CAN","Canada","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62273,124,"CAN","Canada","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62274,124,"CAN","Canada","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62275,124,"CAN","Canada","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62276,124,"CAN","Canada","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62277,124,"CAN","Canada","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62278,124,"CAN","Canada","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62279,124,"CAN","Canada","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62280,124,"CAN","Canada","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62281,124,"CAN","Canada","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62282,124,"CAN","Canada","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62283,124,"CAN","Canada","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62284,124,"CAN","Canada","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62285,124,"CAN","Canada","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62286,124,"CAN","Canada","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62287,124,"CAN","Canada","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62288,124,"CAN","Canada","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62289,124,"CAN","Canada","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62290,124,"CAN","Canada","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62291,124,"CAN","Canada","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62292,124,"CAN","Canada","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62293,124,"CAN","Canada","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62294,124,"CAN","Canada","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62295,124,"CAN","Canada","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62296,124,"CAN","Canada","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62297,124,"CAN","Canada","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62298,124,"CAN","Canada","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62299,124,"CAN","Canada","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62300,124,"CAN","Canada","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62301,124,"CAN","Canada","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62302,124,"CAN","Canada","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62303,124,"CAN","Canada","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62304,124,"CAN","Canada","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62305,124,"CAN","Canada","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAN/can_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62306,152,"CHL","Chile","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62307,152,"CHL","Chile","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62308,152,"CHL","Chile","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62309,152,"CHL","Chile","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62310,152,"CHL","Chile","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62311,152,"CHL","Chile","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62312,152,"CHL","Chile","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62313,152,"CHL","Chile","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62314,152,"CHL","Chile","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62315,152,"CHL","Chile","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62316,152,"CHL","Chile","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62317,152,"CHL","Chile","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62318,152,"CHL","Chile","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62319,152,"CHL","Chile","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62320,152,"CHL","Chile","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62321,152,"CHL","Chile","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62322,152,"CHL","Chile","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62323,152,"CHL","Chile","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62324,152,"CHL","Chile","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62325,152,"CHL","Chile","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62326,152,"CHL","Chile","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62327,152,"CHL","Chile","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62328,152,"CHL","Chile","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62329,152,"CHL","Chile","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62330,152,"CHL","Chile","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62331,152,"CHL","Chile","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62332,152,"CHL","Chile","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62333,152,"CHL","Chile","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62334,152,"CHL","Chile","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62335,152,"CHL","Chile","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62336,152,"CHL","Chile","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62337,152,"CHL","Chile","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62338,152,"CHL","Chile","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62339,152,"CHL","Chile","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62340,152,"CHL","Chile","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62341,152,"CHL","Chile","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHL/chl_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62342,4,"AFG","Afghanistan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62343,4,"AFG","Afghanistan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62344,4,"AFG","Afghanistan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62345,4,"AFG","Afghanistan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62346,4,"AFG","Afghanistan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62347,4,"AFG","Afghanistan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62348,4,"AFG","Afghanistan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62349,4,"AFG","Afghanistan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62350,4,"AFG","Afghanistan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62351,4,"AFG","Afghanistan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62352,4,"AFG","Afghanistan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62353,4,"AFG","Afghanistan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62354,4,"AFG","Afghanistan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62355,4,"AFG","Afghanistan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62356,4,"AFG","Afghanistan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62357,4,"AFG","Afghanistan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62358,4,"AFG","Afghanistan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62359,4,"AFG","Afghanistan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62360,4,"AFG","Afghanistan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62361,4,"AFG","Afghanistan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62362,4,"AFG","Afghanistan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62363,4,"AFG","Afghanistan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62364,4,"AFG","Afghanistan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62365,4,"AFG","Afghanistan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62366,4,"AFG","Afghanistan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62367,4,"AFG","Afghanistan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62368,4,"AFG","Afghanistan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62369,4,"AFG","Afghanistan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62370,4,"AFG","Afghanistan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62371,4,"AFG","Afghanistan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62372,4,"AFG","Afghanistan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62373,4,"AFG","Afghanistan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62374,4,"AFG","Afghanistan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62375,4,"AFG","Afghanistan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62376,4,"AFG","Afghanistan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62377,4,"AFG","Afghanistan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AFG/afg_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62378,8,"ALB","Albania","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62379,8,"ALB","Albania","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62380,8,"ALB","Albania","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62381,8,"ALB","Albania","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62382,8,"ALB","Albania","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62383,8,"ALB","Albania","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62384,8,"ALB","Albania","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62385,8,"ALB","Albania","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62386,8,"ALB","Albania","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62387,8,"ALB","Albania","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62388,8,"ALB","Albania","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62389,8,"ALB","Albania","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62390,8,"ALB","Albania","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62391,8,"ALB","Albania","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62392,8,"ALB","Albania","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62393,8,"ALB","Albania","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62394,8,"ALB","Albania","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62395,8,"ALB","Albania","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62396,8,"ALB","Albania","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62397,8,"ALB","Albania","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62398,8,"ALB","Albania","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62399,8,"ALB","Albania","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62400,8,"ALB","Albania","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62401,8,"ALB","Albania","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62402,8,"ALB","Albania","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62403,8,"ALB","Albania","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62404,8,"ALB","Albania","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62405,8,"ALB","Albania","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62406,8,"ALB","Albania","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62407,8,"ALB","Albania","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62408,8,"ALB","Albania","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62409,8,"ALB","Albania","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62410,8,"ALB","Albania","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62411,8,"ALB","Albania","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62412,8,"ALB","Albania","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62413,8,"ALB","Albania","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALB/alb_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62414,10,"ATA","Antarctica","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62415,10,"ATA","Antarctica","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62416,10,"ATA","Antarctica","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62417,10,"ATA","Antarctica","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62418,10,"ATA","Antarctica","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62419,10,"ATA","Antarctica","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62420,10,"ATA","Antarctica","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62421,10,"ATA","Antarctica","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62422,10,"ATA","Antarctica","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62423,10,"ATA","Antarctica","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62424,10,"ATA","Antarctica","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62425,10,"ATA","Antarctica","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62426,10,"ATA","Antarctica","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62427,10,"ATA","Antarctica","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62428,10,"ATA","Antarctica","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62429,10,"ATA","Antarctica","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62430,10,"ATA","Antarctica","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62431,10,"ATA","Antarctica","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62432,10,"ATA","Antarctica","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62433,10,"ATA","Antarctica","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62434,10,"ATA","Antarctica","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62435,10,"ATA","Antarctica","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62436,10,"ATA","Antarctica","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62437,10,"ATA","Antarctica","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62438,10,"ATA","Antarctica","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62439,10,"ATA","Antarctica","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62440,10,"ATA","Antarctica","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62441,10,"ATA","Antarctica","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62442,10,"ATA","Antarctica","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62443,10,"ATA","Antarctica","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62444,10,"ATA","Antarctica","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62445,10,"ATA","Antarctica","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62446,10,"ATA","Antarctica","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62447,10,"ATA","Antarctica","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62448,10,"ATA","Antarctica","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62449,10,"ATA","Antarctica","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATA/ata_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62450,12,"DZA","Algeria","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62451,12,"DZA","Algeria","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62452,12,"DZA","Algeria","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62453,12,"DZA","Algeria","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62454,12,"DZA","Algeria","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62455,12,"DZA","Algeria","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62456,12,"DZA","Algeria","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62457,12,"DZA","Algeria","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62458,12,"DZA","Algeria","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62459,12,"DZA","Algeria","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62460,12,"DZA","Algeria","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62461,12,"DZA","Algeria","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62462,12,"DZA","Algeria","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62463,12,"DZA","Algeria","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62464,12,"DZA","Algeria","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62465,12,"DZA","Algeria","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62466,12,"DZA","Algeria","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62467,12,"DZA","Algeria","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62468,12,"DZA","Algeria","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62469,12,"DZA","Algeria","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62470,12,"DZA","Algeria","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62471,12,"DZA","Algeria","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62472,12,"DZA","Algeria","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62473,12,"DZA","Algeria","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62474,12,"DZA","Algeria","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62475,12,"DZA","Algeria","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62476,12,"DZA","Algeria","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62477,12,"DZA","Algeria","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62478,12,"DZA","Algeria","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62479,12,"DZA","Algeria","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62480,12,"DZA","Algeria","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62481,12,"DZA","Algeria","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62482,12,"DZA","Algeria","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62483,12,"DZA","Algeria","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62484,12,"DZA","Algeria","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62485,12,"DZA","Algeria","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DZA/dza_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62486,16,"ASM","American Samoa","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62487,16,"ASM","American Samoa","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62488,16,"ASM","American Samoa","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62489,16,"ASM","American Samoa","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62490,16,"ASM","American Samoa","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62491,16,"ASM","American Samoa","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62492,16,"ASM","American Samoa","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62493,16,"ASM","American Samoa","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62494,16,"ASM","American Samoa","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62495,16,"ASM","American Samoa","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62496,16,"ASM","American Samoa","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62497,16,"ASM","American Samoa","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62498,16,"ASM","American Samoa","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62499,16,"ASM","American Samoa","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62500,16,"ASM","American Samoa","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62501,16,"ASM","American Samoa","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62502,16,"ASM","American Samoa","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62503,16,"ASM","American Samoa","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62504,16,"ASM","American Samoa","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62505,16,"ASM","American Samoa","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62506,16,"ASM","American Samoa","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62507,16,"ASM","American Samoa","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62508,16,"ASM","American Samoa","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62509,16,"ASM","American Samoa","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62510,16,"ASM","American Samoa","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62511,16,"ASM","American Samoa","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62512,16,"ASM","American Samoa","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62513,16,"ASM","American Samoa","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62514,16,"ASM","American Samoa","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62515,16,"ASM","American Samoa","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62516,16,"ASM","American Samoa","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62517,16,"ASM","American Samoa","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62518,16,"ASM","American Samoa","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62519,16,"ASM","American Samoa","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62520,16,"ASM","American Samoa","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62521,16,"ASM","American Samoa","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ASM/asm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62522,20,"AND","Andorra","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62523,20,"AND","Andorra","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62524,20,"AND","Andorra","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62525,20,"AND","Andorra","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62526,20,"AND","Andorra","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62527,20,"AND","Andorra","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62528,20,"AND","Andorra","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62529,20,"AND","Andorra","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62530,20,"AND","Andorra","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62531,20,"AND","Andorra","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62532,20,"AND","Andorra","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62533,20,"AND","Andorra","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62534,20,"AND","Andorra","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62535,20,"AND","Andorra","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62536,20,"AND","Andorra","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62537,20,"AND","Andorra","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62538,20,"AND","Andorra","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62539,20,"AND","Andorra","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62540,20,"AND","Andorra","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62541,20,"AND","Andorra","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62542,20,"AND","Andorra","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62543,20,"AND","Andorra","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62544,20,"AND","Andorra","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62545,20,"AND","Andorra","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62546,20,"AND","Andorra","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62547,20,"AND","Andorra","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62548,20,"AND","Andorra","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62549,20,"AND","Andorra","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62550,20,"AND","Andorra","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62551,20,"AND","Andorra","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62552,20,"AND","Andorra","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62553,20,"AND","Andorra","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62554,20,"AND","Andorra","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62555,20,"AND","Andorra","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62556,20,"AND","Andorra","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62557,20,"AND","Andorra","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AND/and_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62558,24,"AGO","Angola","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62559,24,"AGO","Angola","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62560,24,"AGO","Angola","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62561,24,"AGO","Angola","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62562,24,"AGO","Angola","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62563,24,"AGO","Angola","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62564,24,"AGO","Angola","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62565,24,"AGO","Angola","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62566,24,"AGO","Angola","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62567,24,"AGO","Angola","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62568,24,"AGO","Angola","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62569,24,"AGO","Angola","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62570,24,"AGO","Angola","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62571,24,"AGO","Angola","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62572,24,"AGO","Angola","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62573,24,"AGO","Angola","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62574,24,"AGO","Angola","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62575,24,"AGO","Angola","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62576,24,"AGO","Angola","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62577,24,"AGO","Angola","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62578,24,"AGO","Angola","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62579,24,"AGO","Angola","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62580,24,"AGO","Angola","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62581,24,"AGO","Angola","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62582,24,"AGO","Angola","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62583,24,"AGO","Angola","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62584,24,"AGO","Angola","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62585,24,"AGO","Angola","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62586,24,"AGO","Angola","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62587,24,"AGO","Angola","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62588,24,"AGO","Angola","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62589,24,"AGO","Angola","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62590,24,"AGO","Angola","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62591,24,"AGO","Angola","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62592,24,"AGO","Angola","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62593,24,"AGO","Angola","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AGO/ago_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62594,28,"ATG","Antigua and Barbuda","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62595,28,"ATG","Antigua and Barbuda","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62596,28,"ATG","Antigua and Barbuda","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62597,28,"ATG","Antigua and Barbuda","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62598,28,"ATG","Antigua and Barbuda","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62599,28,"ATG","Antigua and Barbuda","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62600,28,"ATG","Antigua and Barbuda","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62601,28,"ATG","Antigua and Barbuda","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62602,28,"ATG","Antigua and Barbuda","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62603,28,"ATG","Antigua and Barbuda","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62604,28,"ATG","Antigua and Barbuda","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62605,28,"ATG","Antigua and Barbuda","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62606,28,"ATG","Antigua and Barbuda","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62607,28,"ATG","Antigua and Barbuda","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62608,28,"ATG","Antigua and Barbuda","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62609,28,"ATG","Antigua and Barbuda","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62610,28,"ATG","Antigua and Barbuda","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62611,28,"ATG","Antigua and Barbuda","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62612,28,"ATG","Antigua and Barbuda","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62613,28,"ATG","Antigua and Barbuda","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62614,28,"ATG","Antigua and Barbuda","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62615,28,"ATG","Antigua and Barbuda","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62616,28,"ATG","Antigua and Barbuda","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62617,28,"ATG","Antigua and Barbuda","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62618,28,"ATG","Antigua and Barbuda","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62619,28,"ATG","Antigua and Barbuda","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62620,28,"ATG","Antigua and Barbuda","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62621,28,"ATG","Antigua and Barbuda","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62622,28,"ATG","Antigua and Barbuda","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62623,28,"ATG","Antigua and Barbuda","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62624,28,"ATG","Antigua and Barbuda","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62625,28,"ATG","Antigua and Barbuda","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62626,28,"ATG","Antigua and Barbuda","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62627,28,"ATG","Antigua and Barbuda","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62628,28,"ATG","Antigua and Barbuda","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62629,28,"ATG","Antigua and Barbuda","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATG/atg_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62630,31,"AZE","Azerbaijan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62631,31,"AZE","Azerbaijan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62632,31,"AZE","Azerbaijan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62633,31,"AZE","Azerbaijan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62634,31,"AZE","Azerbaijan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62635,31,"AZE","Azerbaijan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62636,31,"AZE","Azerbaijan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62637,31,"AZE","Azerbaijan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62638,31,"AZE","Azerbaijan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62639,31,"AZE","Azerbaijan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62640,31,"AZE","Azerbaijan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62641,31,"AZE","Azerbaijan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62642,31,"AZE","Azerbaijan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62643,31,"AZE","Azerbaijan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62644,31,"AZE","Azerbaijan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62645,31,"AZE","Azerbaijan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62646,31,"AZE","Azerbaijan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62647,31,"AZE","Azerbaijan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62648,31,"AZE","Azerbaijan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62649,31,"AZE","Azerbaijan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62650,31,"AZE","Azerbaijan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62651,31,"AZE","Azerbaijan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62652,31,"AZE","Azerbaijan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62653,31,"AZE","Azerbaijan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62654,31,"AZE","Azerbaijan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62655,31,"AZE","Azerbaijan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62656,31,"AZE","Azerbaijan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62657,31,"AZE","Azerbaijan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62658,31,"AZE","Azerbaijan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62659,31,"AZE","Azerbaijan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62660,31,"AZE","Azerbaijan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62661,31,"AZE","Azerbaijan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62662,31,"AZE","Azerbaijan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62663,31,"AZE","Azerbaijan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62664,31,"AZE","Azerbaijan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62665,31,"AZE","Azerbaijan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AZE/aze_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62666,32,"ARG","Argentina","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62667,32,"ARG","Argentina","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62668,32,"ARG","Argentina","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62669,32,"ARG","Argentina","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62670,32,"ARG","Argentina","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62671,32,"ARG","Argentina","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62672,32,"ARG","Argentina","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62673,32,"ARG","Argentina","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62674,32,"ARG","Argentina","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62675,32,"ARG","Argentina","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62676,32,"ARG","Argentina","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62677,32,"ARG","Argentina","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62678,32,"ARG","Argentina","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62679,32,"ARG","Argentina","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62680,32,"ARG","Argentina","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62681,32,"ARG","Argentina","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62682,32,"ARG","Argentina","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62683,32,"ARG","Argentina","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62684,32,"ARG","Argentina","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62685,32,"ARG","Argentina","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62686,32,"ARG","Argentina","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62687,32,"ARG","Argentina","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62688,32,"ARG","Argentina","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62689,32,"ARG","Argentina","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62690,32,"ARG","Argentina","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62691,32,"ARG","Argentina","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62692,32,"ARG","Argentina","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62693,32,"ARG","Argentina","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62694,32,"ARG","Argentina","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62695,32,"ARG","Argentina","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62696,32,"ARG","Argentina","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62697,32,"ARG","Argentina","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62698,32,"ARG","Argentina","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62699,32,"ARG","Argentina","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62700,32,"ARG","Argentina","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62701,32,"ARG","Argentina","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARG/arg_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62702,40,"AUT","Austria","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62703,40,"AUT","Austria","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62704,40,"AUT","Austria","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62705,40,"AUT","Austria","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62706,40,"AUT","Austria","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62707,40,"AUT","Austria","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62708,40,"AUT","Austria","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62709,40,"AUT","Austria","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62710,40,"AUT","Austria","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62711,40,"AUT","Austria","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62712,40,"AUT","Austria","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62713,40,"AUT","Austria","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62714,40,"AUT","Austria","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62715,40,"AUT","Austria","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62716,40,"AUT","Austria","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62717,40,"AUT","Austria","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62718,40,"AUT","Austria","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62719,40,"AUT","Austria","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62720,40,"AUT","Austria","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62721,40,"AUT","Austria","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62722,40,"AUT","Austria","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62723,40,"AUT","Austria","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62724,40,"AUT","Austria","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62725,40,"AUT","Austria","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62726,40,"AUT","Austria","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62727,40,"AUT","Austria","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62728,40,"AUT","Austria","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62729,40,"AUT","Austria","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62730,40,"AUT","Austria","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62731,40,"AUT","Austria","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62732,40,"AUT","Austria","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62733,40,"AUT","Austria","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62734,40,"AUT","Austria","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62735,40,"AUT","Austria","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62736,40,"AUT","Austria","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62737,40,"AUT","Austria","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AUT/aut_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62738,44,"BHS","Bahamas","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62739,44,"BHS","Bahamas","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62740,44,"BHS","Bahamas","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62741,44,"BHS","Bahamas","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62742,44,"BHS","Bahamas","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62743,44,"BHS","Bahamas","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62744,44,"BHS","Bahamas","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62745,44,"BHS","Bahamas","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62746,44,"BHS","Bahamas","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62747,44,"BHS","Bahamas","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62748,44,"BHS","Bahamas","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62749,44,"BHS","Bahamas","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62750,44,"BHS","Bahamas","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62751,44,"BHS","Bahamas","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62752,44,"BHS","Bahamas","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62753,44,"BHS","Bahamas","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62754,44,"BHS","Bahamas","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62755,44,"BHS","Bahamas","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62756,44,"BHS","Bahamas","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62757,44,"BHS","Bahamas","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62758,44,"BHS","Bahamas","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62759,44,"BHS","Bahamas","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62760,44,"BHS","Bahamas","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62761,44,"BHS","Bahamas","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62762,44,"BHS","Bahamas","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62763,44,"BHS","Bahamas","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62764,44,"BHS","Bahamas","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62765,44,"BHS","Bahamas","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62766,44,"BHS","Bahamas","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62767,44,"BHS","Bahamas","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62768,44,"BHS","Bahamas","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62769,44,"BHS","Bahamas","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62770,44,"BHS","Bahamas","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62771,44,"BHS","Bahamas","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62772,44,"BHS","Bahamas","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62773,44,"BHS","Bahamas","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHS/bhs_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62774,48,"BHR","Bahrain","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62775,48,"BHR","Bahrain","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62776,48,"BHR","Bahrain","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62777,48,"BHR","Bahrain","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62778,48,"BHR","Bahrain","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62779,48,"BHR","Bahrain","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62780,48,"BHR","Bahrain","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62781,48,"BHR","Bahrain","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62782,48,"BHR","Bahrain","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62783,48,"BHR","Bahrain","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62784,48,"BHR","Bahrain","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62785,48,"BHR","Bahrain","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62786,48,"BHR","Bahrain","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62787,48,"BHR","Bahrain","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62788,48,"BHR","Bahrain","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62789,48,"BHR","Bahrain","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62790,48,"BHR","Bahrain","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62791,48,"BHR","Bahrain","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62792,48,"BHR","Bahrain","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62793,48,"BHR","Bahrain","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62794,48,"BHR","Bahrain","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62795,48,"BHR","Bahrain","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62796,48,"BHR","Bahrain","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62797,48,"BHR","Bahrain","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62798,48,"BHR","Bahrain","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62799,48,"BHR","Bahrain","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62800,48,"BHR","Bahrain","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62801,48,"BHR","Bahrain","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62802,48,"BHR","Bahrain","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62803,48,"BHR","Bahrain","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62804,48,"BHR","Bahrain","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62805,48,"BHR","Bahrain","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62806,48,"BHR","Bahrain","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62807,48,"BHR","Bahrain","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62808,48,"BHR","Bahrain","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62809,48,"BHR","Bahrain","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BHR/bhr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62810,50,"BGD","Bangladesh","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62811,50,"BGD","Bangladesh","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62812,50,"BGD","Bangladesh","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62813,50,"BGD","Bangladesh","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62814,50,"BGD","Bangladesh","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62815,50,"BGD","Bangladesh","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62816,50,"BGD","Bangladesh","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62817,50,"BGD","Bangladesh","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62818,50,"BGD","Bangladesh","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62819,50,"BGD","Bangladesh","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62820,50,"BGD","Bangladesh","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62821,50,"BGD","Bangladesh","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62822,50,"BGD","Bangladesh","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62823,50,"BGD","Bangladesh","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62824,50,"BGD","Bangladesh","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62825,50,"BGD","Bangladesh","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62826,50,"BGD","Bangladesh","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62827,50,"BGD","Bangladesh","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62828,50,"BGD","Bangladesh","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62829,50,"BGD","Bangladesh","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62830,50,"BGD","Bangladesh","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62831,50,"BGD","Bangladesh","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62832,50,"BGD","Bangladesh","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62833,50,"BGD","Bangladesh","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62834,50,"BGD","Bangladesh","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62835,50,"BGD","Bangladesh","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62836,50,"BGD","Bangladesh","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62837,50,"BGD","Bangladesh","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62838,50,"BGD","Bangladesh","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62839,50,"BGD","Bangladesh","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62840,50,"BGD","Bangladesh","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62841,50,"BGD","Bangladesh","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62842,50,"BGD","Bangladesh","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62843,50,"BGD","Bangladesh","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62844,50,"BGD","Bangladesh","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62845,50,"BGD","Bangladesh","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGD/bgd_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62846,51,"ARM","Armenia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62847,51,"ARM","Armenia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62848,51,"ARM","Armenia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62849,51,"ARM","Armenia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62850,51,"ARM","Armenia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62851,51,"ARM","Armenia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62852,51,"ARM","Armenia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62853,51,"ARM","Armenia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62854,51,"ARM","Armenia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62855,51,"ARM","Armenia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62856,51,"ARM","Armenia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62857,51,"ARM","Armenia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62858,51,"ARM","Armenia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62859,51,"ARM","Armenia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62860,51,"ARM","Armenia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62861,51,"ARM","Armenia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62862,51,"ARM","Armenia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62863,51,"ARM","Armenia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62864,51,"ARM","Armenia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62865,51,"ARM","Armenia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62866,51,"ARM","Armenia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62867,51,"ARM","Armenia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62868,51,"ARM","Armenia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62869,51,"ARM","Armenia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62870,51,"ARM","Armenia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62871,51,"ARM","Armenia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62872,51,"ARM","Armenia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62873,51,"ARM","Armenia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62874,51,"ARM","Armenia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62875,51,"ARM","Armenia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62876,51,"ARM","Armenia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62877,51,"ARM","Armenia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62878,51,"ARM","Armenia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62879,51,"ARM","Armenia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62880,51,"ARM","Armenia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62881,51,"ARM","Armenia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARM/arm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62882,52,"BRB","Barbados","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62883,52,"BRB","Barbados","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62884,52,"BRB","Barbados","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62885,52,"BRB","Barbados","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62886,52,"BRB","Barbados","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62887,52,"BRB","Barbados","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62888,52,"BRB","Barbados","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62889,52,"BRB","Barbados","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62890,52,"BRB","Barbados","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62891,52,"BRB","Barbados","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62892,52,"BRB","Barbados","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62893,52,"BRB","Barbados","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62894,52,"BRB","Barbados","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62895,52,"BRB","Barbados","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62896,52,"BRB","Barbados","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62897,52,"BRB","Barbados","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62898,52,"BRB","Barbados","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62899,52,"BRB","Barbados","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62900,52,"BRB","Barbados","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62901,52,"BRB","Barbados","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62902,52,"BRB","Barbados","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62903,52,"BRB","Barbados","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62904,52,"BRB","Barbados","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62905,52,"BRB","Barbados","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62906,52,"BRB","Barbados","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62907,52,"BRB","Barbados","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62908,52,"BRB","Barbados","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62909,52,"BRB","Barbados","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62910,52,"BRB","Barbados","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62911,52,"BRB","Barbados","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62912,52,"BRB","Barbados","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62913,52,"BRB","Barbados","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62914,52,"BRB","Barbados","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62915,52,"BRB","Barbados","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62916,52,"BRB","Barbados","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62917,52,"BRB","Barbados","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRB/brb_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62918,56,"BEL","Belgium","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62919,56,"BEL","Belgium","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62920,56,"BEL","Belgium","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62921,56,"BEL","Belgium","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62922,56,"BEL","Belgium","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62923,56,"BEL","Belgium","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62924,56,"BEL","Belgium","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62925,56,"BEL","Belgium","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62926,56,"BEL","Belgium","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62927,56,"BEL","Belgium","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62928,56,"BEL","Belgium","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62929,56,"BEL","Belgium","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62930,56,"BEL","Belgium","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62931,56,"BEL","Belgium","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62932,56,"BEL","Belgium","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62933,56,"BEL","Belgium","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62934,56,"BEL","Belgium","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62935,56,"BEL","Belgium","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62936,56,"BEL","Belgium","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62937,56,"BEL","Belgium","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62938,56,"BEL","Belgium","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62939,56,"BEL","Belgium","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62940,56,"BEL","Belgium","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62941,56,"BEL","Belgium","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62942,56,"BEL","Belgium","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62943,56,"BEL","Belgium","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62944,56,"BEL","Belgium","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62945,56,"BEL","Belgium","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62946,56,"BEL","Belgium","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62947,56,"BEL","Belgium","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62948,56,"BEL","Belgium","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62949,56,"BEL","Belgium","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62950,56,"BEL","Belgium","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62951,56,"BEL","Belgium","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62952,56,"BEL","Belgium","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62953,56,"BEL","Belgium","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEL/bel_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62954,60,"BMU","Bermuda","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62955,60,"BMU","Bermuda","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62956,60,"BMU","Bermuda","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62957,60,"BMU","Bermuda","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62958,60,"BMU","Bermuda","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62959,60,"BMU","Bermuda","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62960,60,"BMU","Bermuda","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62961,60,"BMU","Bermuda","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62962,60,"BMU","Bermuda","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62963,60,"BMU","Bermuda","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
62964,60,"BMU","Bermuda","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
62965,60,"BMU","Bermuda","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
62966,60,"BMU","Bermuda","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
62967,60,"BMU","Bermuda","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
62968,60,"BMU","Bermuda","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
62969,60,"BMU","Bermuda","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
62970,60,"BMU","Bermuda","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
62971,60,"BMU","Bermuda","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
62972,60,"BMU","Bermuda","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
62973,60,"BMU","Bermuda","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
62974,60,"BMU","Bermuda","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
62975,60,"BMU","Bermuda","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
62976,60,"BMU","Bermuda","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
62977,60,"BMU","Bermuda","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
62978,60,"BMU","Bermuda","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
62979,60,"BMU","Bermuda","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
62980,60,"BMU","Bermuda","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
62981,60,"BMU","Bermuda","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
62982,60,"BMU","Bermuda","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
62983,60,"BMU","Bermuda","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
62984,60,"BMU","Bermuda","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
62985,60,"BMU","Bermuda","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
62986,60,"BMU","Bermuda","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
62987,60,"BMU","Bermuda","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
62988,60,"BMU","Bermuda","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
62989,60,"BMU","Bermuda","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BMU/bmu_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
62990,64,"BTN","Bhutan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
62991,64,"BTN","Bhutan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
62992,64,"BTN","Bhutan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
62993,64,"BTN","Bhutan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
62994,64,"BTN","Bhutan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
62995,64,"BTN","Bhutan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
62996,64,"BTN","Bhutan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
62997,64,"BTN","Bhutan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
62998,64,"BTN","Bhutan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
62999,64,"BTN","Bhutan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63000,64,"BTN","Bhutan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63001,64,"BTN","Bhutan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63002,64,"BTN","Bhutan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63003,64,"BTN","Bhutan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63004,64,"BTN","Bhutan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63005,64,"BTN","Bhutan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63006,64,"BTN","Bhutan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63007,64,"BTN","Bhutan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63008,64,"BTN","Bhutan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63009,64,"BTN","Bhutan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63010,64,"BTN","Bhutan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63011,64,"BTN","Bhutan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63012,64,"BTN","Bhutan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63013,64,"BTN","Bhutan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63014,64,"BTN","Bhutan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63015,64,"BTN","Bhutan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63016,64,"BTN","Bhutan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63017,64,"BTN","Bhutan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63018,64,"BTN","Bhutan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63019,64,"BTN","Bhutan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63020,64,"BTN","Bhutan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63021,64,"BTN","Bhutan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63022,64,"BTN","Bhutan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63023,64,"BTN","Bhutan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63024,64,"BTN","Bhutan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63025,64,"BTN","Bhutan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BTN/btn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63026,68,"BOL","Bolivia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63027,68,"BOL","Bolivia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63028,68,"BOL","Bolivia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63029,68,"BOL","Bolivia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63030,68,"BOL","Bolivia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63031,68,"BOL","Bolivia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63032,68,"BOL","Bolivia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63033,68,"BOL","Bolivia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63034,68,"BOL","Bolivia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63035,68,"BOL","Bolivia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63036,68,"BOL","Bolivia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63037,68,"BOL","Bolivia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63038,68,"BOL","Bolivia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63039,68,"BOL","Bolivia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63040,68,"BOL","Bolivia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63041,68,"BOL","Bolivia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63042,68,"BOL","Bolivia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63043,68,"BOL","Bolivia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63044,68,"BOL","Bolivia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63045,68,"BOL","Bolivia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63046,68,"BOL","Bolivia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63047,68,"BOL","Bolivia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63048,68,"BOL","Bolivia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63049,68,"BOL","Bolivia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63050,68,"BOL","Bolivia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63051,68,"BOL","Bolivia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63052,68,"BOL","Bolivia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63053,68,"BOL","Bolivia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63054,68,"BOL","Bolivia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63055,68,"BOL","Bolivia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63056,68,"BOL","Bolivia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63057,68,"BOL","Bolivia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63058,68,"BOL","Bolivia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63059,68,"BOL","Bolivia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63060,68,"BOL","Bolivia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63061,68,"BOL","Bolivia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BOL/bol_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63062,70,"BIH","Bosnia and Herzegovina","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63063,70,"BIH","Bosnia and Herzegovina","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63064,70,"BIH","Bosnia and Herzegovina","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63065,70,"BIH","Bosnia and Herzegovina","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63066,70,"BIH","Bosnia and Herzegovina","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63067,70,"BIH","Bosnia and Herzegovina","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63068,70,"BIH","Bosnia and Herzegovina","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63069,70,"BIH","Bosnia and Herzegovina","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63070,70,"BIH","Bosnia and Herzegovina","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63071,70,"BIH","Bosnia and Herzegovina","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63072,70,"BIH","Bosnia and Herzegovina","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63073,70,"BIH","Bosnia and Herzegovina","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63074,70,"BIH","Bosnia and Herzegovina","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63075,70,"BIH","Bosnia and Herzegovina","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63076,70,"BIH","Bosnia and Herzegovina","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63077,70,"BIH","Bosnia and Herzegovina","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63078,70,"BIH","Bosnia and Herzegovina","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63079,70,"BIH","Bosnia and Herzegovina","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63080,70,"BIH","Bosnia and Herzegovina","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63081,70,"BIH","Bosnia and Herzegovina","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63082,70,"BIH","Bosnia and Herzegovina","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63083,70,"BIH","Bosnia and Herzegovina","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63084,70,"BIH","Bosnia and Herzegovina","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63085,70,"BIH","Bosnia and Herzegovina","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63086,70,"BIH","Bosnia and Herzegovina","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63087,70,"BIH","Bosnia and Herzegovina","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63088,70,"BIH","Bosnia and Herzegovina","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63089,70,"BIH","Bosnia and Herzegovina","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63090,70,"BIH","Bosnia and Herzegovina","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63091,70,"BIH","Bosnia and Herzegovina","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63092,70,"BIH","Bosnia and Herzegovina","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63093,70,"BIH","Bosnia and Herzegovina","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63094,70,"BIH","Bosnia and Herzegovina","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63095,70,"BIH","Bosnia and Herzegovina","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63096,70,"BIH","Bosnia and Herzegovina","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63097,70,"BIH","Bosnia and Herzegovina","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BIH/bih_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63098,72,"BWA","Botswana","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63099,72,"BWA","Botswana","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63100,72,"BWA","Botswana","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63101,72,"BWA","Botswana","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63102,72,"BWA","Botswana","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63103,72,"BWA","Botswana","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63104,72,"BWA","Botswana","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63105,72,"BWA","Botswana","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63106,72,"BWA","Botswana","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63107,72,"BWA","Botswana","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63108,72,"BWA","Botswana","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63109,72,"BWA","Botswana","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63110,72,"BWA","Botswana","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63111,72,"BWA","Botswana","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63112,72,"BWA","Botswana","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63113,72,"BWA","Botswana","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63114,72,"BWA","Botswana","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63115,72,"BWA","Botswana","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63116,72,"BWA","Botswana","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63117,72,"BWA","Botswana","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63118,72,"BWA","Botswana","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63119,72,"BWA","Botswana","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63120,72,"BWA","Botswana","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63121,72,"BWA","Botswana","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63122,72,"BWA","Botswana","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63123,72,"BWA","Botswana","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63124,72,"BWA","Botswana","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63125,72,"BWA","Botswana","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63126,72,"BWA","Botswana","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63127,72,"BWA","Botswana","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63128,72,"BWA","Botswana","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63129,72,"BWA","Botswana","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63130,72,"BWA","Botswana","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63131,72,"BWA","Botswana","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63132,72,"BWA","Botswana","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63133,72,"BWA","Botswana","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BWA/bwa_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63134,74,"BVT","Bouvet Island","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63135,74,"BVT","Bouvet Island","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63136,74,"BVT","Bouvet Island","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63137,74,"BVT","Bouvet Island","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63138,74,"BVT","Bouvet Island","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63139,74,"BVT","Bouvet Island","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63140,74,"BVT","Bouvet Island","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63141,74,"BVT","Bouvet Island","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63142,74,"BVT","Bouvet Island","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63143,74,"BVT","Bouvet Island","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63144,74,"BVT","Bouvet Island","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63145,74,"BVT","Bouvet Island","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63146,74,"BVT","Bouvet Island","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63147,74,"BVT","Bouvet Island","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63148,74,"BVT","Bouvet Island","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63149,74,"BVT","Bouvet Island","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63150,74,"BVT","Bouvet Island","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63151,74,"BVT","Bouvet Island","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63152,74,"BVT","Bouvet Island","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63153,74,"BVT","Bouvet Island","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63154,74,"BVT","Bouvet Island","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63155,74,"BVT","Bouvet Island","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63156,74,"BVT","Bouvet Island","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63157,74,"BVT","Bouvet Island","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63158,74,"BVT","Bouvet Island","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63159,74,"BVT","Bouvet Island","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63160,74,"BVT","Bouvet Island","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63161,74,"BVT","Bouvet Island","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63162,74,"BVT","Bouvet Island","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63163,74,"BVT","Bouvet Island","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63164,74,"BVT","Bouvet Island","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63165,74,"BVT","Bouvet Island","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63166,74,"BVT","Bouvet Island","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63167,74,"BVT","Bouvet Island","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63168,74,"BVT","Bouvet Island","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63169,74,"BVT","Bouvet Island","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BVT/bvt_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63170,84,"BLZ","Belize","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63171,84,"BLZ","Belize","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63172,84,"BLZ","Belize","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63173,84,"BLZ","Belize","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63174,84,"BLZ","Belize","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63175,84,"BLZ","Belize","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63176,84,"BLZ","Belize","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63177,84,"BLZ","Belize","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63178,84,"BLZ","Belize","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63179,84,"BLZ","Belize","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63180,84,"BLZ","Belize","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63181,84,"BLZ","Belize","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63182,84,"BLZ","Belize","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63183,84,"BLZ","Belize","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63184,84,"BLZ","Belize","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63185,84,"BLZ","Belize","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63186,84,"BLZ","Belize","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63187,84,"BLZ","Belize","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63188,84,"BLZ","Belize","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63189,84,"BLZ","Belize","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63190,84,"BLZ","Belize","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63191,84,"BLZ","Belize","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63192,84,"BLZ","Belize","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63193,84,"BLZ","Belize","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63194,84,"BLZ","Belize","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63195,84,"BLZ","Belize","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63196,84,"BLZ","Belize","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63197,84,"BLZ","Belize","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63198,84,"BLZ","Belize","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63199,84,"BLZ","Belize","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63200,84,"BLZ","Belize","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63201,84,"BLZ","Belize","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63202,84,"BLZ","Belize","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63203,84,"BLZ","Belize","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63204,84,"BLZ","Belize","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63205,84,"BLZ","Belize","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLZ/blz_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63206,86,"IOT","British Indian Ocean Territory","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63207,86,"IOT","British Indian Ocean Territory","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63208,86,"IOT","British Indian Ocean Territory","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63209,86,"IOT","British Indian Ocean Territory","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63210,86,"IOT","British Indian Ocean Territory","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63211,86,"IOT","British Indian Ocean Territory","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63212,86,"IOT","British Indian Ocean Territory","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63213,86,"IOT","British Indian Ocean Territory","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63214,86,"IOT","British Indian Ocean Territory","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63215,86,"IOT","British Indian Ocean Territory","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63216,86,"IOT","British Indian Ocean Territory","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63217,86,"IOT","British Indian Ocean Territory","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63218,86,"IOT","British Indian Ocean Territory","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63219,86,"IOT","British Indian Ocean Territory","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63220,86,"IOT","British Indian Ocean Territory","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63221,86,"IOT","British Indian Ocean Territory","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63222,86,"IOT","British Indian Ocean Territory","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63223,86,"IOT","British Indian Ocean Territory","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63224,86,"IOT","British Indian Ocean Territory","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63225,86,"IOT","British Indian Ocean Territory","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63226,86,"IOT","British Indian Ocean Territory","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63227,86,"IOT","British Indian Ocean Territory","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63228,86,"IOT","British Indian Ocean Territory","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63229,86,"IOT","British Indian Ocean Territory","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63230,86,"IOT","British Indian Ocean Territory","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63231,86,"IOT","British Indian Ocean Territory","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63232,86,"IOT","British Indian Ocean Territory","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63233,86,"IOT","British Indian Ocean Territory","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63234,86,"IOT","British Indian Ocean Territory","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63235,86,"IOT","British Indian Ocean Territory","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63236,86,"IOT","British Indian Ocean Territory","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63237,86,"IOT","British Indian Ocean Territory","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63238,86,"IOT","British Indian Ocean Territory","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63239,86,"IOT","British Indian Ocean Territory","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63240,86,"IOT","British Indian Ocean Territory","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63241,86,"IOT","British Indian Ocean Territory","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IOT/iot_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63242,90,"SLB","Solomon Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63243,90,"SLB","Solomon Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63244,90,"SLB","Solomon Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63245,90,"SLB","Solomon Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63246,90,"SLB","Solomon Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63247,90,"SLB","Solomon Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63248,90,"SLB","Solomon Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63249,90,"SLB","Solomon Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63250,90,"SLB","Solomon Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63251,90,"SLB","Solomon Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63252,90,"SLB","Solomon Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63253,90,"SLB","Solomon Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63254,90,"SLB","Solomon Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63255,90,"SLB","Solomon Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63256,90,"SLB","Solomon Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63257,90,"SLB","Solomon Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63258,90,"SLB","Solomon Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63259,90,"SLB","Solomon Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63260,90,"SLB","Solomon Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63261,90,"SLB","Solomon Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63262,90,"SLB","Solomon Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63263,90,"SLB","Solomon Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63264,90,"SLB","Solomon Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63265,90,"SLB","Solomon Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63266,90,"SLB","Solomon Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63267,90,"SLB","Solomon Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63268,90,"SLB","Solomon Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63269,90,"SLB","Solomon Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63270,90,"SLB","Solomon Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63271,90,"SLB","Solomon Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63272,90,"SLB","Solomon Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63273,90,"SLB","Solomon Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63274,90,"SLB","Solomon Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63275,90,"SLB","Solomon Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63276,90,"SLB","Solomon Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63277,90,"SLB","Solomon Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLB/slb_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63278,92,"VGB","British Virgin Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63279,92,"VGB","British Virgin Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63280,92,"VGB","British Virgin Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63281,92,"VGB","British Virgin Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63282,92,"VGB","British Virgin Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63283,92,"VGB","British Virgin Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63284,92,"VGB","British Virgin Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63285,92,"VGB","British Virgin Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63286,92,"VGB","British Virgin Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63287,92,"VGB","British Virgin Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63288,92,"VGB","British Virgin Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63289,92,"VGB","British Virgin Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63290,92,"VGB","British Virgin Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63291,92,"VGB","British Virgin Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63292,92,"VGB","British Virgin Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63293,92,"VGB","British Virgin Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63294,92,"VGB","British Virgin Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63295,92,"VGB","British Virgin Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63296,92,"VGB","British Virgin Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63297,92,"VGB","British Virgin Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63298,92,"VGB","British Virgin Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63299,92,"VGB","British Virgin Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63300,92,"VGB","British Virgin Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63301,92,"VGB","British Virgin Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63302,92,"VGB","British Virgin Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63303,92,"VGB","British Virgin Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63304,92,"VGB","British Virgin Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63305,92,"VGB","British Virgin Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63306,92,"VGB","British Virgin Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63307,92,"VGB","British Virgin Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63308,92,"VGB","British Virgin Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63309,92,"VGB","British Virgin Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63310,92,"VGB","British Virgin Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63311,92,"VGB","British Virgin Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63312,92,"VGB","British Virgin Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63313,92,"VGB","British Virgin Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VGB/vgb_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63314,96,"BRN","Brunei","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63315,96,"BRN","Brunei","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63316,96,"BRN","Brunei","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63317,96,"BRN","Brunei","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63318,96,"BRN","Brunei","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63319,96,"BRN","Brunei","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63320,96,"BRN","Brunei","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63321,96,"BRN","Brunei","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63322,96,"BRN","Brunei","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63323,96,"BRN","Brunei","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63324,96,"BRN","Brunei","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63325,96,"BRN","Brunei","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63326,96,"BRN","Brunei","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63327,96,"BRN","Brunei","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63328,96,"BRN","Brunei","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63329,96,"BRN","Brunei","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63330,96,"BRN","Brunei","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63331,96,"BRN","Brunei","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63332,96,"BRN","Brunei","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63333,96,"BRN","Brunei","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63334,96,"BRN","Brunei","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63335,96,"BRN","Brunei","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63336,96,"BRN","Brunei","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63337,96,"BRN","Brunei","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63338,96,"BRN","Brunei","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63339,96,"BRN","Brunei","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63340,96,"BRN","Brunei","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63341,96,"BRN","Brunei","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63342,96,"BRN","Brunei","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63343,96,"BRN","Brunei","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63344,96,"BRN","Brunei","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63345,96,"BRN","Brunei","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63346,96,"BRN","Brunei","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63347,96,"BRN","Brunei","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63348,96,"BRN","Brunei","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63349,96,"BRN","Brunei","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BRN/brn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63350,100,"BGR","Bulgaria","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63351,100,"BGR","Bulgaria","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63352,100,"BGR","Bulgaria","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63353,100,"BGR","Bulgaria","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63354,100,"BGR","Bulgaria","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63355,100,"BGR","Bulgaria","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63356,100,"BGR","Bulgaria","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63357,100,"BGR","Bulgaria","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63358,100,"BGR","Bulgaria","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63359,100,"BGR","Bulgaria","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63360,100,"BGR","Bulgaria","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63361,100,"BGR","Bulgaria","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63362,100,"BGR","Bulgaria","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63363,100,"BGR","Bulgaria","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63364,100,"BGR","Bulgaria","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63365,100,"BGR","Bulgaria","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63366,100,"BGR","Bulgaria","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63367,100,"BGR","Bulgaria","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63368,100,"BGR","Bulgaria","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63369,100,"BGR","Bulgaria","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63370,100,"BGR","Bulgaria","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63371,100,"BGR","Bulgaria","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63372,100,"BGR","Bulgaria","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63373,100,"BGR","Bulgaria","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63374,100,"BGR","Bulgaria","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63375,100,"BGR","Bulgaria","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63376,100,"BGR","Bulgaria","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63377,100,"BGR","Bulgaria","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63378,100,"BGR","Bulgaria","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63379,100,"BGR","Bulgaria","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63380,100,"BGR","Bulgaria","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63381,100,"BGR","Bulgaria","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63382,100,"BGR","Bulgaria","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63383,100,"BGR","Bulgaria","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63384,100,"BGR","Bulgaria","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63385,100,"BGR","Bulgaria","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BGR/bgr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63386,104,"MMR","Myanmar","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63387,104,"MMR","Myanmar","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63388,104,"MMR","Myanmar","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63389,104,"MMR","Myanmar","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63390,104,"MMR","Myanmar","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63391,104,"MMR","Myanmar","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63392,104,"MMR","Myanmar","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63393,104,"MMR","Myanmar","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63394,104,"MMR","Myanmar","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63395,104,"MMR","Myanmar","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63396,104,"MMR","Myanmar","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63397,104,"MMR","Myanmar","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63398,104,"MMR","Myanmar","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63399,104,"MMR","Myanmar","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63400,104,"MMR","Myanmar","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63401,104,"MMR","Myanmar","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63402,104,"MMR","Myanmar","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63403,104,"MMR","Myanmar","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63404,104,"MMR","Myanmar","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63405,104,"MMR","Myanmar","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63406,104,"MMR","Myanmar","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63407,104,"MMR","Myanmar","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63408,104,"MMR","Myanmar","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63409,104,"MMR","Myanmar","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63410,104,"MMR","Myanmar","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63411,104,"MMR","Myanmar","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63412,104,"MMR","Myanmar","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63413,104,"MMR","Myanmar","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63414,104,"MMR","Myanmar","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63415,104,"MMR","Myanmar","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63416,104,"MMR","Myanmar","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63417,104,"MMR","Myanmar","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63418,104,"MMR","Myanmar","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63419,104,"MMR","Myanmar","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63420,104,"MMR","Myanmar","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63421,104,"MMR","Myanmar","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MMR/mmr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63422,108,"BDI","Burundi","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63423,108,"BDI","Burundi","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63424,108,"BDI","Burundi","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63425,108,"BDI","Burundi","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63426,108,"BDI","Burundi","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63427,108,"BDI","Burundi","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63428,108,"BDI","Burundi","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63429,108,"BDI","Burundi","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63430,108,"BDI","Burundi","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63431,108,"BDI","Burundi","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63432,108,"BDI","Burundi","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63433,108,"BDI","Burundi","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63434,108,"BDI","Burundi","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63435,108,"BDI","Burundi","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63436,108,"BDI","Burundi","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63437,108,"BDI","Burundi","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63438,108,"BDI","Burundi","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63439,108,"BDI","Burundi","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63440,108,"BDI","Burundi","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63441,108,"BDI","Burundi","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63442,108,"BDI","Burundi","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63443,108,"BDI","Burundi","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63444,108,"BDI","Burundi","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63445,108,"BDI","Burundi","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63446,108,"BDI","Burundi","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63447,108,"BDI","Burundi","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63448,108,"BDI","Burundi","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63449,108,"BDI","Burundi","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63450,108,"BDI","Burundi","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63451,108,"BDI","Burundi","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63452,108,"BDI","Burundi","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63453,108,"BDI","Burundi","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63454,108,"BDI","Burundi","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63455,108,"BDI","Burundi","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63456,108,"BDI","Burundi","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63457,108,"BDI","Burundi","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BDI/bdi_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63458,112,"BLR","Belarus","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63459,112,"BLR","Belarus","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63460,112,"BLR","Belarus","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63461,112,"BLR","Belarus","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63462,112,"BLR","Belarus","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63463,112,"BLR","Belarus","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63464,112,"BLR","Belarus","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63465,112,"BLR","Belarus","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63466,112,"BLR","Belarus","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63467,112,"BLR","Belarus","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63468,112,"BLR","Belarus","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63469,112,"BLR","Belarus","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63470,112,"BLR","Belarus","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63471,112,"BLR","Belarus","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63472,112,"BLR","Belarus","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63473,112,"BLR","Belarus","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63474,112,"BLR","Belarus","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63475,112,"BLR","Belarus","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63476,112,"BLR","Belarus","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63477,112,"BLR","Belarus","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63478,112,"BLR","Belarus","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63479,112,"BLR","Belarus","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63480,112,"BLR","Belarus","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63481,112,"BLR","Belarus","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63482,112,"BLR","Belarus","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63483,112,"BLR","Belarus","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63484,112,"BLR","Belarus","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63485,112,"BLR","Belarus","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63486,112,"BLR","Belarus","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63487,112,"BLR","Belarus","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63488,112,"BLR","Belarus","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63489,112,"BLR","Belarus","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63490,112,"BLR","Belarus","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63491,112,"BLR","Belarus","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63492,112,"BLR","Belarus","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63493,112,"BLR","Belarus","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLR/blr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63494,116,"KHM","Cambodia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63495,116,"KHM","Cambodia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63496,116,"KHM","Cambodia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63497,116,"KHM","Cambodia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63498,116,"KHM","Cambodia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63499,116,"KHM","Cambodia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63500,116,"KHM","Cambodia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63501,116,"KHM","Cambodia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63502,116,"KHM","Cambodia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63503,116,"KHM","Cambodia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63504,116,"KHM","Cambodia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63505,116,"KHM","Cambodia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63506,116,"KHM","Cambodia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63507,116,"KHM","Cambodia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63508,116,"KHM","Cambodia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63509,116,"KHM","Cambodia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63510,116,"KHM","Cambodia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63511,116,"KHM","Cambodia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63512,116,"KHM","Cambodia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63513,116,"KHM","Cambodia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63514,116,"KHM","Cambodia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63515,116,"KHM","Cambodia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63516,116,"KHM","Cambodia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63517,116,"KHM","Cambodia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63518,116,"KHM","Cambodia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63519,116,"KHM","Cambodia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63520,116,"KHM","Cambodia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63521,116,"KHM","Cambodia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63522,116,"KHM","Cambodia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63523,116,"KHM","Cambodia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63524,116,"KHM","Cambodia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63525,116,"KHM","Cambodia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63526,116,"KHM","Cambodia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63527,116,"KHM","Cambodia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63528,116,"KHM","Cambodia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63529,116,"KHM","Cambodia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KHM/khm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63530,120,"CMR","Cameroon","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63531,120,"CMR","Cameroon","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63532,120,"CMR","Cameroon","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63533,120,"CMR","Cameroon","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63534,120,"CMR","Cameroon","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63535,120,"CMR","Cameroon","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63536,120,"CMR","Cameroon","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63537,120,"CMR","Cameroon","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63538,120,"CMR","Cameroon","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63539,120,"CMR","Cameroon","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63540,120,"CMR","Cameroon","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63541,120,"CMR","Cameroon","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63542,120,"CMR","Cameroon","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63543,120,"CMR","Cameroon","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63544,120,"CMR","Cameroon","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63545,120,"CMR","Cameroon","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63546,120,"CMR","Cameroon","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63547,120,"CMR","Cameroon","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63548,120,"CMR","Cameroon","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63549,120,"CMR","Cameroon","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63550,120,"CMR","Cameroon","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63551,120,"CMR","Cameroon","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63552,120,"CMR","Cameroon","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63553,120,"CMR","Cameroon","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63554,120,"CMR","Cameroon","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63555,120,"CMR","Cameroon","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63556,120,"CMR","Cameroon","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63557,120,"CMR","Cameroon","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63558,120,"CMR","Cameroon","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63559,120,"CMR","Cameroon","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63560,120,"CMR","Cameroon","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63561,120,"CMR","Cameroon","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63562,120,"CMR","Cameroon","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63563,120,"CMR","Cameroon","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63564,120,"CMR","Cameroon","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63565,120,"CMR","Cameroon","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CMR/cmr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63566,132,"CPV","Cape Verde","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63567,132,"CPV","Cape Verde","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63568,132,"CPV","Cape Verde","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63569,132,"CPV","Cape Verde","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63570,132,"CPV","Cape Verde","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63571,132,"CPV","Cape Verde","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63572,132,"CPV","Cape Verde","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63573,132,"CPV","Cape Verde","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63574,132,"CPV","Cape Verde","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63575,132,"CPV","Cape Verde","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63576,132,"CPV","Cape Verde","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63577,132,"CPV","Cape Verde","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63578,132,"CPV","Cape Verde","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63579,132,"CPV","Cape Verde","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63580,132,"CPV","Cape Verde","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63581,132,"CPV","Cape Verde","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63582,132,"CPV","Cape Verde","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63583,132,"CPV","Cape Verde","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63584,132,"CPV","Cape Verde","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63585,132,"CPV","Cape Verde","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63586,132,"CPV","Cape Verde","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63587,132,"CPV","Cape Verde","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63588,132,"CPV","Cape Verde","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63589,132,"CPV","Cape Verde","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63590,132,"CPV","Cape Verde","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63591,132,"CPV","Cape Verde","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63592,132,"CPV","Cape Verde","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63593,132,"CPV","Cape Verde","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63594,132,"CPV","Cape Verde","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63595,132,"CPV","Cape Verde","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63596,132,"CPV","Cape Verde","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63597,132,"CPV","Cape Verde","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63598,132,"CPV","Cape Verde","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63599,132,"CPV","Cape Verde","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63600,132,"CPV","Cape Verde","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63601,132,"CPV","Cape Verde","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CPV/cpv_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63602,136,"CYM","Cayman Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63603,136,"CYM","Cayman Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63604,136,"CYM","Cayman Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63605,136,"CYM","Cayman Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63606,136,"CYM","Cayman Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63607,136,"CYM","Cayman Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63608,136,"CYM","Cayman Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63609,136,"CYM","Cayman Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63610,136,"CYM","Cayman Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63611,136,"CYM","Cayman Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63612,136,"CYM","Cayman Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63613,136,"CYM","Cayman Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63614,136,"CYM","Cayman Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63615,136,"CYM","Cayman Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63616,136,"CYM","Cayman Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63617,136,"CYM","Cayman Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63618,136,"CYM","Cayman Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63619,136,"CYM","Cayman Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63620,136,"CYM","Cayman Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63621,136,"CYM","Cayman Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63622,136,"CYM","Cayman Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63623,136,"CYM","Cayman Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63624,136,"CYM","Cayman Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63625,136,"CYM","Cayman Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63626,136,"CYM","Cayman Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63627,136,"CYM","Cayman Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63628,136,"CYM","Cayman Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63629,136,"CYM","Cayman Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63630,136,"CYM","Cayman Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63631,136,"CYM","Cayman Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63632,136,"CYM","Cayman Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63633,136,"CYM","Cayman Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63634,136,"CYM","Cayman Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63635,136,"CYM","Cayman Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63636,136,"CYM","Cayman Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63637,136,"CYM","Cayman Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYM/cym_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63638,140,"CAF","Central African Republic","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63639,140,"CAF","Central African Republic","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63640,140,"CAF","Central African Republic","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63641,140,"CAF","Central African Republic","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63642,140,"CAF","Central African Republic","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63643,140,"CAF","Central African Republic","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63644,140,"CAF","Central African Republic","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63645,140,"CAF","Central African Republic","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63646,140,"CAF","Central African Republic","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63647,140,"CAF","Central African Republic","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63648,140,"CAF","Central African Republic","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63649,140,"CAF","Central African Republic","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63650,140,"CAF","Central African Republic","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63651,140,"CAF","Central African Republic","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63652,140,"CAF","Central African Republic","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63653,140,"CAF","Central African Republic","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63654,140,"CAF","Central African Republic","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63655,140,"CAF","Central African Republic","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63656,140,"CAF","Central African Republic","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63657,140,"CAF","Central African Republic","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63658,140,"CAF","Central African Republic","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63659,140,"CAF","Central African Republic","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63660,140,"CAF","Central African Republic","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63661,140,"CAF","Central African Republic","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63662,140,"CAF","Central African Republic","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63663,140,"CAF","Central African Republic","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63664,140,"CAF","Central African Republic","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63665,140,"CAF","Central African Republic","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63666,140,"CAF","Central African Republic","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63667,140,"CAF","Central African Republic","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63668,140,"CAF","Central African Republic","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63669,140,"CAF","Central African Republic","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63670,140,"CAF","Central African Republic","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63671,140,"CAF","Central African Republic","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63672,140,"CAF","Central African Republic","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63673,140,"CAF","Central African Republic","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CAF/caf_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63674,144,"LKA","Sri Lanka","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63675,144,"LKA","Sri Lanka","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63676,144,"LKA","Sri Lanka","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63677,144,"LKA","Sri Lanka","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63678,144,"LKA","Sri Lanka","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63679,144,"LKA","Sri Lanka","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63680,144,"LKA","Sri Lanka","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63681,144,"LKA","Sri Lanka","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63682,144,"LKA","Sri Lanka","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63683,144,"LKA","Sri Lanka","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63684,144,"LKA","Sri Lanka","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63685,144,"LKA","Sri Lanka","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63686,144,"LKA","Sri Lanka","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63687,144,"LKA","Sri Lanka","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63688,144,"LKA","Sri Lanka","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63689,144,"LKA","Sri Lanka","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63690,144,"LKA","Sri Lanka","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63691,144,"LKA","Sri Lanka","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63692,144,"LKA","Sri Lanka","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63693,144,"LKA","Sri Lanka","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63694,144,"LKA","Sri Lanka","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63695,144,"LKA","Sri Lanka","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63696,144,"LKA","Sri Lanka","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63697,144,"LKA","Sri Lanka","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63698,144,"LKA","Sri Lanka","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63699,144,"LKA","Sri Lanka","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63700,144,"LKA","Sri Lanka","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63701,144,"LKA","Sri Lanka","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63702,144,"LKA","Sri Lanka","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63703,144,"LKA","Sri Lanka","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63704,144,"LKA","Sri Lanka","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63705,144,"LKA","Sri Lanka","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63706,144,"LKA","Sri Lanka","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63707,144,"LKA","Sri Lanka","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63708,144,"LKA","Sri Lanka","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63709,144,"LKA","Sri Lanka","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LKA/lka_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63710,148,"TCD","Chad","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63711,148,"TCD","Chad","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63712,148,"TCD","Chad","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63713,148,"TCD","Chad","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63714,148,"TCD","Chad","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63715,148,"TCD","Chad","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63716,148,"TCD","Chad","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63717,148,"TCD","Chad","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63718,148,"TCD","Chad","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63719,148,"TCD","Chad","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63720,148,"TCD","Chad","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63721,148,"TCD","Chad","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63722,148,"TCD","Chad","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63723,148,"TCD","Chad","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63724,148,"TCD","Chad","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63725,148,"TCD","Chad","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63726,148,"TCD","Chad","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63727,148,"TCD","Chad","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63728,148,"TCD","Chad","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63729,148,"TCD","Chad","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63730,148,"TCD","Chad","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63731,148,"TCD","Chad","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63732,148,"TCD","Chad","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63733,148,"TCD","Chad","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63734,148,"TCD","Chad","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63735,148,"TCD","Chad","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63736,148,"TCD","Chad","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63737,148,"TCD","Chad","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63738,148,"TCD","Chad","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63739,148,"TCD","Chad","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63740,148,"TCD","Chad","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63741,148,"TCD","Chad","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63742,148,"TCD","Chad","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63743,148,"TCD","Chad","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63744,148,"TCD","Chad","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63745,148,"TCD","Chad","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCD/tcd_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63746,158,"TWN","Taiwan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63747,158,"TWN","Taiwan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63748,158,"TWN","Taiwan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63749,158,"TWN","Taiwan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63750,158,"TWN","Taiwan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63751,158,"TWN","Taiwan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63752,158,"TWN","Taiwan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63753,158,"TWN","Taiwan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63754,158,"TWN","Taiwan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63755,158,"TWN","Taiwan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63756,158,"TWN","Taiwan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63757,158,"TWN","Taiwan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63758,158,"TWN","Taiwan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63759,158,"TWN","Taiwan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63760,158,"TWN","Taiwan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63761,158,"TWN","Taiwan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63762,158,"TWN","Taiwan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63763,158,"TWN","Taiwan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63764,158,"TWN","Taiwan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63765,158,"TWN","Taiwan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63766,158,"TWN","Taiwan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63767,158,"TWN","Taiwan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63768,158,"TWN","Taiwan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63769,158,"TWN","Taiwan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63770,158,"TWN","Taiwan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63771,158,"TWN","Taiwan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63772,158,"TWN","Taiwan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63773,158,"TWN","Taiwan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63774,158,"TWN","Taiwan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63775,158,"TWN","Taiwan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63776,158,"TWN","Taiwan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63777,158,"TWN","Taiwan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63778,158,"TWN","Taiwan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63779,158,"TWN","Taiwan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63780,158,"TWN","Taiwan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63781,158,"TWN","Taiwan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TWN/twn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63782,170,"COL","Colombia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63783,170,"COL","Colombia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63784,170,"COL","Colombia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63785,170,"COL","Colombia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63786,170,"COL","Colombia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63787,170,"COL","Colombia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63788,170,"COL","Colombia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63789,170,"COL","Colombia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63790,170,"COL","Colombia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63791,170,"COL","Colombia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63792,170,"COL","Colombia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63793,170,"COL","Colombia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63794,170,"COL","Colombia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63795,170,"COL","Colombia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63796,170,"COL","Colombia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63797,170,"COL","Colombia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63798,170,"COL","Colombia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63799,170,"COL","Colombia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63800,170,"COL","Colombia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63801,170,"COL","Colombia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63802,170,"COL","Colombia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63803,170,"COL","Colombia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63804,170,"COL","Colombia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63805,170,"COL","Colombia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63806,170,"COL","Colombia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63807,170,"COL","Colombia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63808,170,"COL","Colombia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63809,170,"COL","Colombia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63810,170,"COL","Colombia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63811,170,"COL","Colombia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63812,170,"COL","Colombia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63813,170,"COL","Colombia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63814,170,"COL","Colombia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63815,170,"COL","Colombia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63816,170,"COL","Colombia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63817,170,"COL","Colombia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COL/col_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63818,174,"COM","Comoros","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63819,174,"COM","Comoros","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63820,174,"COM","Comoros","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63821,174,"COM","Comoros","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63822,174,"COM","Comoros","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63823,174,"COM","Comoros","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63824,174,"COM","Comoros","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63825,174,"COM","Comoros","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63826,174,"COM","Comoros","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63827,174,"COM","Comoros","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63828,174,"COM","Comoros","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63829,174,"COM","Comoros","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63830,174,"COM","Comoros","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63831,174,"COM","Comoros","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63832,174,"COM","Comoros","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63833,174,"COM","Comoros","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63834,174,"COM","Comoros","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63835,174,"COM","Comoros","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63836,174,"COM","Comoros","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63837,174,"COM","Comoros","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63838,174,"COM","Comoros","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63839,174,"COM","Comoros","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63840,174,"COM","Comoros","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63841,174,"COM","Comoros","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63842,174,"COM","Comoros","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63843,174,"COM","Comoros","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63844,174,"COM","Comoros","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63845,174,"COM","Comoros","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63846,174,"COM","Comoros","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63847,174,"COM","Comoros","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63848,174,"COM","Comoros","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63849,174,"COM","Comoros","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63850,174,"COM","Comoros","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63851,174,"COM","Comoros","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63852,174,"COM","Comoros","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63853,174,"COM","Comoros","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COM/com_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63854,175,"MYT","Mayotte","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63855,175,"MYT","Mayotte","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63856,175,"MYT","Mayotte","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63857,175,"MYT","Mayotte","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63858,175,"MYT","Mayotte","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63859,175,"MYT","Mayotte","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63860,175,"MYT","Mayotte","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63861,175,"MYT","Mayotte","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63862,175,"MYT","Mayotte","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63863,175,"MYT","Mayotte","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63864,175,"MYT","Mayotte","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63865,175,"MYT","Mayotte","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63866,175,"MYT","Mayotte","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63867,175,"MYT","Mayotte","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63868,175,"MYT","Mayotte","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63869,175,"MYT","Mayotte","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63870,175,"MYT","Mayotte","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63871,175,"MYT","Mayotte","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63872,175,"MYT","Mayotte","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63873,175,"MYT","Mayotte","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63874,175,"MYT","Mayotte","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63875,175,"MYT","Mayotte","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63876,175,"MYT","Mayotte","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63877,175,"MYT","Mayotte","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63878,175,"MYT","Mayotte","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63879,175,"MYT","Mayotte","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63880,175,"MYT","Mayotte","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63881,175,"MYT","Mayotte","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63882,175,"MYT","Mayotte","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63883,175,"MYT","Mayotte","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63884,175,"MYT","Mayotte","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63885,175,"MYT","Mayotte","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63886,175,"MYT","Mayotte","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63887,175,"MYT","Mayotte","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63888,175,"MYT","Mayotte","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63889,175,"MYT","Mayotte","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYT/myt_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63890,178,"COG","Republic of Congo","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63891,178,"COG","Republic of Congo","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63892,178,"COG","Republic of Congo","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63893,178,"COG","Republic of Congo","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63894,178,"COG","Republic of Congo","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63895,178,"COG","Republic of Congo","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63896,178,"COG","Republic of Congo","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63897,178,"COG","Republic of Congo","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63898,178,"COG","Republic of Congo","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63899,178,"COG","Republic of Congo","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63900,178,"COG","Republic of Congo","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63901,178,"COG","Republic of Congo","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63902,178,"COG","Republic of Congo","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63903,178,"COG","Republic of Congo","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63904,178,"COG","Republic of Congo","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63905,178,"COG","Republic of Congo","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63906,178,"COG","Republic of Congo","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63907,178,"COG","Republic of Congo","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63908,178,"COG","Republic of Congo","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63909,178,"COG","Republic of Congo","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63910,178,"COG","Republic of Congo","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63911,178,"COG","Republic of Congo","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63912,178,"COG","Republic of Congo","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63913,178,"COG","Republic of Congo","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63914,178,"COG","Republic of Congo","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63915,178,"COG","Republic of Congo","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63916,178,"COG","Republic of Congo","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63917,178,"COG","Republic of Congo","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63918,178,"COG","Republic of Congo","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63919,178,"COG","Republic of Congo","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63920,178,"COG","Republic of Congo","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63921,178,"COG","Republic of Congo","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63922,178,"COG","Republic of Congo","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63923,178,"COG","Republic of Congo","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63924,178,"COG","Republic of Congo","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63925,178,"COG","Republic of Congo","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COG/cog_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63926,180,"COD","Democratic Republic of the Congo","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63927,180,"COD","Democratic Republic of the Congo","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63928,180,"COD","Democratic Republic of the Congo","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63929,180,"COD","Democratic Republic of the Congo","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63930,180,"COD","Democratic Republic of the Congo","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63931,180,"COD","Democratic Republic of the Congo","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63932,180,"COD","Democratic Republic of the Congo","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63933,180,"COD","Democratic Republic of the Congo","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63934,180,"COD","Democratic Republic of the Congo","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63935,180,"COD","Democratic Republic of the Congo","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63936,180,"COD","Democratic Republic of the Congo","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63937,180,"COD","Democratic Republic of the Congo","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63938,180,"COD","Democratic Republic of the Congo","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63939,180,"COD","Democratic Republic of the Congo","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63940,180,"COD","Democratic Republic of the Congo","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63941,180,"COD","Democratic Republic of the Congo","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63942,180,"COD","Democratic Republic of the Congo","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63943,180,"COD","Democratic Republic of the Congo","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63944,180,"COD","Democratic Republic of the Congo","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63945,180,"COD","Democratic Republic of the Congo","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63946,180,"COD","Democratic Republic of the Congo","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63947,180,"COD","Democratic Republic of the Congo","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63948,180,"COD","Democratic Republic of the Congo","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63949,180,"COD","Democratic Republic of the Congo","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63950,180,"COD","Democratic Republic of the Congo","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63951,180,"COD","Democratic Republic of the Congo","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63952,180,"COD","Democratic Republic of the Congo","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63953,180,"COD","Democratic Republic of the Congo","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63954,180,"COD","Democratic Republic of the Congo","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63955,180,"COD","Democratic Republic of the Congo","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63956,180,"COD","Democratic Republic of the Congo","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63957,180,"COD","Democratic Republic of the Congo","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63958,180,"COD","Democratic Republic of the Congo","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63959,180,"COD","Democratic Republic of the Congo","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63960,180,"COD","Democratic Republic of the Congo","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63961,180,"COD","Democratic Republic of the Congo","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COD/cod_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63962,184,"COK","Cook Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63963,184,"COK","Cook Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
63964,184,"COK","Cook Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
63965,184,"COK","Cook Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
63966,184,"COK","Cook Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
63967,184,"COK","Cook Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
63968,184,"COK","Cook Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
63969,184,"COK","Cook Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
63970,184,"COK","Cook Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
63971,184,"COK","Cook Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
63972,184,"COK","Cook Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
63973,184,"COK","Cook Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
63974,184,"COK","Cook Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
63975,184,"COK","Cook Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
63976,184,"COK","Cook Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
63977,184,"COK","Cook Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
63978,184,"COK","Cook Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
63979,184,"COK","Cook Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
63980,184,"COK","Cook Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
63981,184,"COK","Cook Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
63982,184,"COK","Cook Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
63983,184,"COK","Cook Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
63984,184,"COK","Cook Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
63985,184,"COK","Cook Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
63986,184,"COK","Cook Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
63987,184,"COK","Cook Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
63988,184,"COK","Cook Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
63989,184,"COK","Cook Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
63990,184,"COK","Cook Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
63991,184,"COK","Cook Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
63992,184,"COK","Cook Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
63993,184,"COK","Cook Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
63994,184,"COK","Cook Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
63995,184,"COK","Cook Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
63996,184,"COK","Cook Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
63997,184,"COK","Cook Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/COK/cok_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
63998,188,"CRI","Costa Rica","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
63999,188,"CRI","Costa Rica","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64000,188,"CRI","Costa Rica","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64001,188,"CRI","Costa Rica","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64002,188,"CRI","Costa Rica","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64003,188,"CRI","Costa Rica","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64004,188,"CRI","Costa Rica","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64005,188,"CRI","Costa Rica","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64006,188,"CRI","Costa Rica","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64007,188,"CRI","Costa Rica","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64008,188,"CRI","Costa Rica","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64009,188,"CRI","Costa Rica","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64010,188,"CRI","Costa Rica","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64011,188,"CRI","Costa Rica","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64012,188,"CRI","Costa Rica","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64013,188,"CRI","Costa Rica","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64014,188,"CRI","Costa Rica","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64015,188,"CRI","Costa Rica","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64016,188,"CRI","Costa Rica","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64017,188,"CRI","Costa Rica","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64018,188,"CRI","Costa Rica","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64019,188,"CRI","Costa Rica","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64020,188,"CRI","Costa Rica","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64021,188,"CRI","Costa Rica","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64022,188,"CRI","Costa Rica","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64023,188,"CRI","Costa Rica","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64024,188,"CRI","Costa Rica","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64025,188,"CRI","Costa Rica","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64026,188,"CRI","Costa Rica","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64027,188,"CRI","Costa Rica","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64028,188,"CRI","Costa Rica","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64029,188,"CRI","Costa Rica","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64030,188,"CRI","Costa Rica","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64031,188,"CRI","Costa Rica","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64032,188,"CRI","Costa Rica","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64033,188,"CRI","Costa Rica","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CRI/cri_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64034,191,"HRV","Croatia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64035,191,"HRV","Croatia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64036,191,"HRV","Croatia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64037,191,"HRV","Croatia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64038,191,"HRV","Croatia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64039,191,"HRV","Croatia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64040,191,"HRV","Croatia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64041,191,"HRV","Croatia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64042,191,"HRV","Croatia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64043,191,"HRV","Croatia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64044,191,"HRV","Croatia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64045,191,"HRV","Croatia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64046,191,"HRV","Croatia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64047,191,"HRV","Croatia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64048,191,"HRV","Croatia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64049,191,"HRV","Croatia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64050,191,"HRV","Croatia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64051,191,"HRV","Croatia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64052,191,"HRV","Croatia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64053,191,"HRV","Croatia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64054,191,"HRV","Croatia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64055,191,"HRV","Croatia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64056,191,"HRV","Croatia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64057,191,"HRV","Croatia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64058,191,"HRV","Croatia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64059,191,"HRV","Croatia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64060,191,"HRV","Croatia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64061,191,"HRV","Croatia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64062,191,"HRV","Croatia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64063,191,"HRV","Croatia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64064,191,"HRV","Croatia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64065,191,"HRV","Croatia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64066,191,"HRV","Croatia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64067,191,"HRV","Croatia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64068,191,"HRV","Croatia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64069,191,"HRV","Croatia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HRV/hrv_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64070,192,"CUB","Cuba","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64071,192,"CUB","Cuba","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64072,192,"CUB","Cuba","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64073,192,"CUB","Cuba","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64074,192,"CUB","Cuba","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64075,192,"CUB","Cuba","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64076,192,"CUB","Cuba","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64077,192,"CUB","Cuba","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64078,192,"CUB","Cuba","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64079,192,"CUB","Cuba","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64080,192,"CUB","Cuba","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64081,192,"CUB","Cuba","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64082,192,"CUB","Cuba","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64083,192,"CUB","Cuba","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64084,192,"CUB","Cuba","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64085,192,"CUB","Cuba","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64086,192,"CUB","Cuba","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64087,192,"CUB","Cuba","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64088,192,"CUB","Cuba","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64089,192,"CUB","Cuba","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64090,192,"CUB","Cuba","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64091,192,"CUB","Cuba","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64092,192,"CUB","Cuba","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64093,192,"CUB","Cuba","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64094,192,"CUB","Cuba","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64095,192,"CUB","Cuba","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64096,192,"CUB","Cuba","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64097,192,"CUB","Cuba","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64098,192,"CUB","Cuba","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64099,192,"CUB","Cuba","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64100,192,"CUB","Cuba","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64101,192,"CUB","Cuba","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64102,192,"CUB","Cuba","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64103,192,"CUB","Cuba","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64104,192,"CUB","Cuba","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64105,192,"CUB","Cuba","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUB/cub_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64106,196,"CYP","Cyprus","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64107,196,"CYP","Cyprus","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64108,196,"CYP","Cyprus","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64109,196,"CYP","Cyprus","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64110,196,"CYP","Cyprus","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64111,196,"CYP","Cyprus","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64112,196,"CYP","Cyprus","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64113,196,"CYP","Cyprus","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64114,196,"CYP","Cyprus","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64115,196,"CYP","Cyprus","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64116,196,"CYP","Cyprus","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64117,196,"CYP","Cyprus","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64118,196,"CYP","Cyprus","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64119,196,"CYP","Cyprus","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64120,196,"CYP","Cyprus","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64121,196,"CYP","Cyprus","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64122,196,"CYP","Cyprus","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64123,196,"CYP","Cyprus","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64124,196,"CYP","Cyprus","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64125,196,"CYP","Cyprus","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64126,196,"CYP","Cyprus","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64127,196,"CYP","Cyprus","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64128,196,"CYP","Cyprus","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64129,196,"CYP","Cyprus","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64130,196,"CYP","Cyprus","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64131,196,"CYP","Cyprus","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64132,196,"CYP","Cyprus","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64133,196,"CYP","Cyprus","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64134,196,"CYP","Cyprus","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64135,196,"CYP","Cyprus","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64136,196,"CYP","Cyprus","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64137,196,"CYP","Cyprus","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64138,196,"CYP","Cyprus","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64139,196,"CYP","Cyprus","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64140,196,"CYP","Cyprus","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64141,196,"CYP","Cyprus","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CYP/cyp_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64142,203,"CZE","Czech Republic","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64143,203,"CZE","Czech Republic","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64144,203,"CZE","Czech Republic","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64145,203,"CZE","Czech Republic","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64146,203,"CZE","Czech Republic","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64147,203,"CZE","Czech Republic","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64148,203,"CZE","Czech Republic","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64149,203,"CZE","Czech Republic","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64150,203,"CZE","Czech Republic","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64151,203,"CZE","Czech Republic","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64152,203,"CZE","Czech Republic","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64153,203,"CZE","Czech Republic","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64154,203,"CZE","Czech Republic","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64155,203,"CZE","Czech Republic","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64156,203,"CZE","Czech Republic","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64157,203,"CZE","Czech Republic","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64158,203,"CZE","Czech Republic","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64159,203,"CZE","Czech Republic","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64160,203,"CZE","Czech Republic","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64161,203,"CZE","Czech Republic","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64162,203,"CZE","Czech Republic","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64163,203,"CZE","Czech Republic","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64164,203,"CZE","Czech Republic","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64165,203,"CZE","Czech Republic","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64166,203,"CZE","Czech Republic","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64167,203,"CZE","Czech Republic","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64168,203,"CZE","Czech Republic","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64169,203,"CZE","Czech Republic","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64170,203,"CZE","Czech Republic","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64171,203,"CZE","Czech Republic","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64172,203,"CZE","Czech Republic","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64173,203,"CZE","Czech Republic","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64174,203,"CZE","Czech Republic","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64175,203,"CZE","Czech Republic","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64176,203,"CZE","Czech Republic","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64177,203,"CZE","Czech Republic","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CZE/cze_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64178,204,"BEN","Benin","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64179,204,"BEN","Benin","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64180,204,"BEN","Benin","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64181,204,"BEN","Benin","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64182,204,"BEN","Benin","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64183,204,"BEN","Benin","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64184,204,"BEN","Benin","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64185,204,"BEN","Benin","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64186,204,"BEN","Benin","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64187,204,"BEN","Benin","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64188,204,"BEN","Benin","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64189,204,"BEN","Benin","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64190,204,"BEN","Benin","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64191,204,"BEN","Benin","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64192,204,"BEN","Benin","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64193,204,"BEN","Benin","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64194,204,"BEN","Benin","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64195,204,"BEN","Benin","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64196,204,"BEN","Benin","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64197,204,"BEN","Benin","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64198,204,"BEN","Benin","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64199,204,"BEN","Benin","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64200,204,"BEN","Benin","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64201,204,"BEN","Benin","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64202,204,"BEN","Benin","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64203,204,"BEN","Benin","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64204,204,"BEN","Benin","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64205,204,"BEN","Benin","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64206,204,"BEN","Benin","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64207,204,"BEN","Benin","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64208,204,"BEN","Benin","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64209,204,"BEN","Benin","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64210,204,"BEN","Benin","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64211,204,"BEN","Benin","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64212,204,"BEN","Benin","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64213,204,"BEN","Benin","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BEN/ben_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64214,208,"DNK","Denmark","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64215,208,"DNK","Denmark","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64216,208,"DNK","Denmark","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64217,208,"DNK","Denmark","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64218,208,"DNK","Denmark","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64219,208,"DNK","Denmark","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64220,208,"DNK","Denmark","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64221,208,"DNK","Denmark","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64222,208,"DNK","Denmark","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64223,208,"DNK","Denmark","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64224,208,"DNK","Denmark","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64225,208,"DNK","Denmark","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64226,208,"DNK","Denmark","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64227,208,"DNK","Denmark","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64228,208,"DNK","Denmark","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64229,208,"DNK","Denmark","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64230,208,"DNK","Denmark","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64231,208,"DNK","Denmark","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64232,208,"DNK","Denmark","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64233,208,"DNK","Denmark","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64234,208,"DNK","Denmark","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64235,208,"DNK","Denmark","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64236,208,"DNK","Denmark","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64237,208,"DNK","Denmark","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64238,208,"DNK","Denmark","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64239,208,"DNK","Denmark","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64240,208,"DNK","Denmark","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64241,208,"DNK","Denmark","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64242,208,"DNK","Denmark","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64243,208,"DNK","Denmark","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64244,208,"DNK","Denmark","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64245,208,"DNK","Denmark","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64246,208,"DNK","Denmark","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64247,208,"DNK","Denmark","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64248,208,"DNK","Denmark","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64249,208,"DNK","Denmark","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DNK/dnk_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64250,212,"DMA","Dominica","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64251,212,"DMA","Dominica","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64252,212,"DMA","Dominica","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64253,212,"DMA","Dominica","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64254,212,"DMA","Dominica","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64255,212,"DMA","Dominica","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64256,212,"DMA","Dominica","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64257,212,"DMA","Dominica","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64258,212,"DMA","Dominica","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64259,212,"DMA","Dominica","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64260,212,"DMA","Dominica","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64261,212,"DMA","Dominica","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64262,212,"DMA","Dominica","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64263,212,"DMA","Dominica","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64264,212,"DMA","Dominica","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64265,212,"DMA","Dominica","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64266,212,"DMA","Dominica","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64267,212,"DMA","Dominica","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64268,212,"DMA","Dominica","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64269,212,"DMA","Dominica","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64270,212,"DMA","Dominica","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64271,212,"DMA","Dominica","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64272,212,"DMA","Dominica","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64273,212,"DMA","Dominica","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64274,212,"DMA","Dominica","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64275,212,"DMA","Dominica","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64276,212,"DMA","Dominica","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64277,212,"DMA","Dominica","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64278,212,"DMA","Dominica","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64279,212,"DMA","Dominica","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64280,212,"DMA","Dominica","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64281,212,"DMA","Dominica","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64282,212,"DMA","Dominica","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64283,212,"DMA","Dominica","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64284,212,"DMA","Dominica","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64285,212,"DMA","Dominica","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DMA/dma_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64286,214,"DOM","Dominican Republic","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64287,214,"DOM","Dominican Republic","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64288,214,"DOM","Dominican Republic","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64289,214,"DOM","Dominican Republic","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64290,214,"DOM","Dominican Republic","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64291,214,"DOM","Dominican Republic","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64292,214,"DOM","Dominican Republic","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64293,214,"DOM","Dominican Republic","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64294,214,"DOM","Dominican Republic","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64295,214,"DOM","Dominican Republic","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64296,214,"DOM","Dominican Republic","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64297,214,"DOM","Dominican Republic","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64298,214,"DOM","Dominican Republic","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64299,214,"DOM","Dominican Republic","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64300,214,"DOM","Dominican Republic","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64301,214,"DOM","Dominican Republic","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64302,214,"DOM","Dominican Republic","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64303,214,"DOM","Dominican Republic","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64304,214,"DOM","Dominican Republic","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64305,214,"DOM","Dominican Republic","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64306,214,"DOM","Dominican Republic","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64307,214,"DOM","Dominican Republic","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64308,214,"DOM","Dominican Republic","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64309,214,"DOM","Dominican Republic","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64310,214,"DOM","Dominican Republic","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64311,214,"DOM","Dominican Republic","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64312,214,"DOM","Dominican Republic","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64313,214,"DOM","Dominican Republic","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64314,214,"DOM","Dominican Republic","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64315,214,"DOM","Dominican Republic","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64316,214,"DOM","Dominican Republic","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64317,214,"DOM","Dominican Republic","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64318,214,"DOM","Dominican Republic","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64319,214,"DOM","Dominican Republic","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64320,214,"DOM","Dominican Republic","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64321,214,"DOM","Dominican Republic","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DOM/dom_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64322,218,"ECU","Ecuador","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64323,218,"ECU","Ecuador","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64324,218,"ECU","Ecuador","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64325,218,"ECU","Ecuador","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64326,218,"ECU","Ecuador","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64327,218,"ECU","Ecuador","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64328,218,"ECU","Ecuador","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64329,218,"ECU","Ecuador","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64330,218,"ECU","Ecuador","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64331,218,"ECU","Ecuador","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64332,218,"ECU","Ecuador","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64333,218,"ECU","Ecuador","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64334,218,"ECU","Ecuador","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64335,218,"ECU","Ecuador","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64336,218,"ECU","Ecuador","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64337,218,"ECU","Ecuador","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64338,218,"ECU","Ecuador","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64339,218,"ECU","Ecuador","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64340,218,"ECU","Ecuador","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64341,218,"ECU","Ecuador","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64342,218,"ECU","Ecuador","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64343,218,"ECU","Ecuador","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64344,218,"ECU","Ecuador","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64345,218,"ECU","Ecuador","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64346,218,"ECU","Ecuador","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64347,218,"ECU","Ecuador","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64348,218,"ECU","Ecuador","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64349,218,"ECU","Ecuador","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64350,218,"ECU","Ecuador","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64351,218,"ECU","Ecuador","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64352,218,"ECU","Ecuador","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64353,218,"ECU","Ecuador","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64354,218,"ECU","Ecuador","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64355,218,"ECU","Ecuador","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64356,218,"ECU","Ecuador","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64357,218,"ECU","Ecuador","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ECU/ecu_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64358,222,"SLV","El Salvador","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64359,222,"SLV","El Salvador","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64360,222,"SLV","El Salvador","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64361,222,"SLV","El Salvador","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64362,222,"SLV","El Salvador","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64363,222,"SLV","El Salvador","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64364,222,"SLV","El Salvador","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64365,222,"SLV","El Salvador","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64366,222,"SLV","El Salvador","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64367,222,"SLV","El Salvador","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64368,222,"SLV","El Salvador","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64369,222,"SLV","El Salvador","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64370,222,"SLV","El Salvador","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64371,222,"SLV","El Salvador","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64372,222,"SLV","El Salvador","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64373,222,"SLV","El Salvador","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64374,222,"SLV","El Salvador","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64375,222,"SLV","El Salvador","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64376,222,"SLV","El Salvador","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64377,222,"SLV","El Salvador","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64378,222,"SLV","El Salvador","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64379,222,"SLV","El Salvador","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64380,222,"SLV","El Salvador","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64381,222,"SLV","El Salvador","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64382,222,"SLV","El Salvador","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64383,222,"SLV","El Salvador","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64384,222,"SLV","El Salvador","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64385,222,"SLV","El Salvador","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64386,222,"SLV","El Salvador","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64387,222,"SLV","El Salvador","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64388,222,"SLV","El Salvador","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64389,222,"SLV","El Salvador","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64390,222,"SLV","El Salvador","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64391,222,"SLV","El Salvador","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64392,222,"SLV","El Salvador","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64393,222,"SLV","El Salvador","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLV/slv_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64394,226,"GNQ","Equatorial Guinea","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64395,226,"GNQ","Equatorial Guinea","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64396,226,"GNQ","Equatorial Guinea","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64397,226,"GNQ","Equatorial Guinea","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64398,226,"GNQ","Equatorial Guinea","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64399,226,"GNQ","Equatorial Guinea","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64400,226,"GNQ","Equatorial Guinea","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64401,226,"GNQ","Equatorial Guinea","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64402,226,"GNQ","Equatorial Guinea","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64403,226,"GNQ","Equatorial Guinea","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64404,226,"GNQ","Equatorial Guinea","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64405,226,"GNQ","Equatorial Guinea","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64406,226,"GNQ","Equatorial Guinea","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64407,226,"GNQ","Equatorial Guinea","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64408,226,"GNQ","Equatorial Guinea","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64409,226,"GNQ","Equatorial Guinea","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64410,226,"GNQ","Equatorial Guinea","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64411,226,"GNQ","Equatorial Guinea","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64412,226,"GNQ","Equatorial Guinea","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64413,226,"GNQ","Equatorial Guinea","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64414,226,"GNQ","Equatorial Guinea","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64415,226,"GNQ","Equatorial Guinea","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64416,226,"GNQ","Equatorial Guinea","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64417,226,"GNQ","Equatorial Guinea","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64418,226,"GNQ","Equatorial Guinea","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64419,226,"GNQ","Equatorial Guinea","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64420,226,"GNQ","Equatorial Guinea","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64421,226,"GNQ","Equatorial Guinea","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64422,226,"GNQ","Equatorial Guinea","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64423,226,"GNQ","Equatorial Guinea","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64424,226,"GNQ","Equatorial Guinea","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64425,226,"GNQ","Equatorial Guinea","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64426,226,"GNQ","Equatorial Guinea","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64427,226,"GNQ","Equatorial Guinea","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64428,226,"GNQ","Equatorial Guinea","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64429,226,"GNQ","Equatorial Guinea","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNQ/gnq_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64430,231,"ETH","Ethiopia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64431,231,"ETH","Ethiopia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64432,231,"ETH","Ethiopia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64433,231,"ETH","Ethiopia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64434,231,"ETH","Ethiopia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64435,231,"ETH","Ethiopia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64436,231,"ETH","Ethiopia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64437,231,"ETH","Ethiopia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64438,231,"ETH","Ethiopia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64439,231,"ETH","Ethiopia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64440,231,"ETH","Ethiopia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64441,231,"ETH","Ethiopia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64442,231,"ETH","Ethiopia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64443,231,"ETH","Ethiopia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64444,231,"ETH","Ethiopia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64445,231,"ETH","Ethiopia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64446,231,"ETH","Ethiopia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64447,231,"ETH","Ethiopia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64448,231,"ETH","Ethiopia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64449,231,"ETH","Ethiopia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64450,231,"ETH","Ethiopia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64451,231,"ETH","Ethiopia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64452,231,"ETH","Ethiopia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64453,231,"ETH","Ethiopia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64454,231,"ETH","Ethiopia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64455,231,"ETH","Ethiopia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64456,231,"ETH","Ethiopia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64457,231,"ETH","Ethiopia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64458,231,"ETH","Ethiopia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64459,231,"ETH","Ethiopia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64460,231,"ETH","Ethiopia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64461,231,"ETH","Ethiopia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64462,231,"ETH","Ethiopia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64463,231,"ETH","Ethiopia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64464,231,"ETH","Ethiopia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64465,231,"ETH","Ethiopia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ETH/eth_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64466,232,"ERI","Eritrea","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64467,232,"ERI","Eritrea","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64468,232,"ERI","Eritrea","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64469,232,"ERI","Eritrea","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64470,232,"ERI","Eritrea","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64471,232,"ERI","Eritrea","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64472,232,"ERI","Eritrea","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64473,232,"ERI","Eritrea","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64474,232,"ERI","Eritrea","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64475,232,"ERI","Eritrea","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64476,232,"ERI","Eritrea","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64477,232,"ERI","Eritrea","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64478,232,"ERI","Eritrea","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64479,232,"ERI","Eritrea","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64480,232,"ERI","Eritrea","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64481,232,"ERI","Eritrea","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64482,232,"ERI","Eritrea","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64483,232,"ERI","Eritrea","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64484,232,"ERI","Eritrea","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64485,232,"ERI","Eritrea","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64486,232,"ERI","Eritrea","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64487,232,"ERI","Eritrea","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64488,232,"ERI","Eritrea","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64489,232,"ERI","Eritrea","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64490,232,"ERI","Eritrea","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64491,232,"ERI","Eritrea","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64492,232,"ERI","Eritrea","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64493,232,"ERI","Eritrea","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64494,232,"ERI","Eritrea","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64495,232,"ERI","Eritrea","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64496,232,"ERI","Eritrea","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64497,232,"ERI","Eritrea","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64498,232,"ERI","Eritrea","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64499,232,"ERI","Eritrea","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64500,232,"ERI","Eritrea","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64501,232,"ERI","Eritrea","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ERI/eri_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64502,233,"EST","Estonia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64503,233,"EST","Estonia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64504,233,"EST","Estonia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64505,233,"EST","Estonia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64506,233,"EST","Estonia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64507,233,"EST","Estonia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64508,233,"EST","Estonia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64509,233,"EST","Estonia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64510,233,"EST","Estonia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64511,233,"EST","Estonia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64512,233,"EST","Estonia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64513,233,"EST","Estonia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64514,233,"EST","Estonia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64515,233,"EST","Estonia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64516,233,"EST","Estonia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64517,233,"EST","Estonia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64518,233,"EST","Estonia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64519,233,"EST","Estonia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64520,233,"EST","Estonia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64521,233,"EST","Estonia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64522,233,"EST","Estonia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64523,233,"EST","Estonia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64524,233,"EST","Estonia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64525,233,"EST","Estonia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64526,233,"EST","Estonia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64527,233,"EST","Estonia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64528,233,"EST","Estonia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64529,233,"EST","Estonia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64530,233,"EST","Estonia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64531,233,"EST","Estonia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64532,233,"EST","Estonia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64533,233,"EST","Estonia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64534,233,"EST","Estonia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64535,233,"EST","Estonia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64536,233,"EST","Estonia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64537,233,"EST","Estonia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EST/est_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64538,234,"FRO","Faroe Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64539,234,"FRO","Faroe Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64540,234,"FRO","Faroe Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64541,234,"FRO","Faroe Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64542,234,"FRO","Faroe Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64543,234,"FRO","Faroe Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64544,234,"FRO","Faroe Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64545,234,"FRO","Faroe Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64546,234,"FRO","Faroe Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64547,234,"FRO","Faroe Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64548,234,"FRO","Faroe Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64549,234,"FRO","Faroe Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64550,234,"FRO","Faroe Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64551,234,"FRO","Faroe Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64552,234,"FRO","Faroe Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64553,234,"FRO","Faroe Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64554,234,"FRO","Faroe Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64555,234,"FRO","Faroe Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64556,234,"FRO","Faroe Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64557,234,"FRO","Faroe Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64558,234,"FRO","Faroe Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64559,234,"FRO","Faroe Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64560,234,"FRO","Faroe Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64561,234,"FRO","Faroe Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64562,234,"FRO","Faroe Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64563,234,"FRO","Faroe Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64564,234,"FRO","Faroe Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64565,234,"FRO","Faroe Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64566,234,"FRO","Faroe Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64567,234,"FRO","Faroe Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64568,234,"FRO","Faroe Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64569,234,"FRO","Faroe Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64570,234,"FRO","Faroe Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64571,234,"FRO","Faroe Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64572,234,"FRO","Faroe Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64573,234,"FRO","Faroe Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRO/fro_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64574,238,"FLK","Falkland Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64575,238,"FLK","Falkland Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64576,238,"FLK","Falkland Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64577,238,"FLK","Falkland Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64578,238,"FLK","Falkland Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64579,238,"FLK","Falkland Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64580,238,"FLK","Falkland Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64581,238,"FLK","Falkland Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64582,238,"FLK","Falkland Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64583,238,"FLK","Falkland Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64584,238,"FLK","Falkland Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64585,238,"FLK","Falkland Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64586,238,"FLK","Falkland Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64587,238,"FLK","Falkland Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64588,238,"FLK","Falkland Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64589,238,"FLK","Falkland Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64590,238,"FLK","Falkland Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64591,238,"FLK","Falkland Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64592,238,"FLK","Falkland Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64593,238,"FLK","Falkland Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64594,238,"FLK","Falkland Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64595,238,"FLK","Falkland Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64596,238,"FLK","Falkland Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64597,238,"FLK","Falkland Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64598,238,"FLK","Falkland Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64599,238,"FLK","Falkland Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64600,238,"FLK","Falkland Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64601,238,"FLK","Falkland Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64602,238,"FLK","Falkland Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64603,238,"FLK","Falkland Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64604,238,"FLK","Falkland Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64605,238,"FLK","Falkland Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64606,238,"FLK","Falkland Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64607,238,"FLK","Falkland Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64608,238,"FLK","Falkland Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64609,238,"FLK","Falkland Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FLK/flk_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64610,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64611,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64612,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64613,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64614,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64615,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64616,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64617,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64618,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64619,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64620,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64621,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64622,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64623,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64624,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64625,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64626,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64627,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64628,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64629,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64630,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64631,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64632,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64633,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64634,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64635,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64636,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64637,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64638,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64639,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64640,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64641,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64642,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64643,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64644,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64645,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGS/sgs_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64646,242,"FJI","Fiji","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64647,242,"FJI","Fiji","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64648,242,"FJI","Fiji","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64649,242,"FJI","Fiji","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64650,242,"FJI","Fiji","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64651,242,"FJI","Fiji","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64652,242,"FJI","Fiji","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64653,242,"FJI","Fiji","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64654,242,"FJI","Fiji","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64655,242,"FJI","Fiji","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64656,242,"FJI","Fiji","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64657,242,"FJI","Fiji","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64658,242,"FJI","Fiji","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64659,242,"FJI","Fiji","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64660,242,"FJI","Fiji","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64661,242,"FJI","Fiji","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64662,242,"FJI","Fiji","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64663,242,"FJI","Fiji","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64664,242,"FJI","Fiji","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64665,242,"FJI","Fiji","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64666,242,"FJI","Fiji","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64667,242,"FJI","Fiji","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64668,242,"FJI","Fiji","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64669,242,"FJI","Fiji","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64670,242,"FJI","Fiji","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64671,242,"FJI","Fiji","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64672,242,"FJI","Fiji","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64673,242,"FJI","Fiji","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64674,242,"FJI","Fiji","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64675,242,"FJI","Fiji","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64676,242,"FJI","Fiji","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64677,242,"FJI","Fiji","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64678,242,"FJI","Fiji","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64679,242,"FJI","Fiji","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64680,242,"FJI","Fiji","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64681,242,"FJI","Fiji","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FJI/fji_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64682,246,"FIN","Finland","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64683,246,"FIN","Finland","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64684,246,"FIN","Finland","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64685,246,"FIN","Finland","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64686,246,"FIN","Finland","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64687,246,"FIN","Finland","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64688,246,"FIN","Finland","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64689,246,"FIN","Finland","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64690,246,"FIN","Finland","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64691,246,"FIN","Finland","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64692,246,"FIN","Finland","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64693,246,"FIN","Finland","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64694,246,"FIN","Finland","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64695,246,"FIN","Finland","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64696,246,"FIN","Finland","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64697,246,"FIN","Finland","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64698,246,"FIN","Finland","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64699,246,"FIN","Finland","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64700,246,"FIN","Finland","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64701,246,"FIN","Finland","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64702,246,"FIN","Finland","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64703,246,"FIN","Finland","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64704,246,"FIN","Finland","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64705,246,"FIN","Finland","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64706,246,"FIN","Finland","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64707,246,"FIN","Finland","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64708,246,"FIN","Finland","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64709,246,"FIN","Finland","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64710,246,"FIN","Finland","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64711,246,"FIN","Finland","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64712,246,"FIN","Finland","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64713,246,"FIN","Finland","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64714,246,"FIN","Finland","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64715,246,"FIN","Finland","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64716,246,"FIN","Finland","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64717,246,"FIN","Finland","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FIN/fin_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64718,248,"ALA","Aland Islands ","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64719,248,"ALA","Aland Islands ","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64720,248,"ALA","Aland Islands ","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64721,248,"ALA","Aland Islands ","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64722,248,"ALA","Aland Islands ","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64723,248,"ALA","Aland Islands ","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64724,248,"ALA","Aland Islands ","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64725,248,"ALA","Aland Islands ","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64726,248,"ALA","Aland Islands ","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64727,248,"ALA","Aland Islands ","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64728,248,"ALA","Aland Islands ","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64729,248,"ALA","Aland Islands ","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64730,248,"ALA","Aland Islands ","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64731,248,"ALA","Aland Islands ","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64732,248,"ALA","Aland Islands ","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64733,248,"ALA","Aland Islands ","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64734,248,"ALA","Aland Islands ","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64735,248,"ALA","Aland Islands ","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64736,248,"ALA","Aland Islands ","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64737,248,"ALA","Aland Islands ","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64738,248,"ALA","Aland Islands ","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64739,248,"ALA","Aland Islands ","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64740,248,"ALA","Aland Islands ","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64741,248,"ALA","Aland Islands ","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64742,248,"ALA","Aland Islands ","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64743,248,"ALA","Aland Islands ","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64744,248,"ALA","Aland Islands ","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64745,248,"ALA","Aland Islands ","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64746,248,"ALA","Aland Islands ","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64747,248,"ALA","Aland Islands ","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64748,248,"ALA","Aland Islands ","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64749,248,"ALA","Aland Islands ","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64750,248,"ALA","Aland Islands ","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64751,248,"ALA","Aland Islands ","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64752,248,"ALA","Aland Islands ","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64753,248,"ALA","Aland Islands ","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ALA/ala_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64754,250,"FRA","France","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64755,250,"FRA","France","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64756,250,"FRA","France","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64757,250,"FRA","France","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64758,250,"FRA","France","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64759,250,"FRA","France","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64760,250,"FRA","France","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64761,250,"FRA","France","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64762,250,"FRA","France","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64763,250,"FRA","France","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64764,250,"FRA","France","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64765,250,"FRA","France","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64766,250,"FRA","France","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64767,250,"FRA","France","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64768,250,"FRA","France","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64769,250,"FRA","France","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64770,250,"FRA","France","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64771,250,"FRA","France","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64772,250,"FRA","France","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64773,250,"FRA","France","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64774,250,"FRA","France","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64775,250,"FRA","France","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64776,250,"FRA","France","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64777,250,"FRA","France","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64778,250,"FRA","France","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64779,250,"FRA","France","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64780,250,"FRA","France","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64781,250,"FRA","France","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64782,250,"FRA","France","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64783,250,"FRA","France","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64784,250,"FRA","France","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64785,250,"FRA","France","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64786,250,"FRA","France","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64787,250,"FRA","France","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64788,250,"FRA","France","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64789,250,"FRA","France","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FRA/fra_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64790,254,"GUF","French Guiana","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64791,254,"GUF","French Guiana","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64792,254,"GUF","French Guiana","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64793,254,"GUF","French Guiana","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64794,254,"GUF","French Guiana","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64795,254,"GUF","French Guiana","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64796,254,"GUF","French Guiana","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64797,254,"GUF","French Guiana","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64798,254,"GUF","French Guiana","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64799,254,"GUF","French Guiana","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64800,254,"GUF","French Guiana","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64801,254,"GUF","French Guiana","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64802,254,"GUF","French Guiana","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64803,254,"GUF","French Guiana","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64804,254,"GUF","French Guiana","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64805,254,"GUF","French Guiana","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64806,254,"GUF","French Guiana","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64807,254,"GUF","French Guiana","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64808,254,"GUF","French Guiana","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64809,254,"GUF","French Guiana","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64810,254,"GUF","French Guiana","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64811,254,"GUF","French Guiana","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64812,254,"GUF","French Guiana","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64813,254,"GUF","French Guiana","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64814,254,"GUF","French Guiana","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64815,254,"GUF","French Guiana","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64816,254,"GUF","French Guiana","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64817,254,"GUF","French Guiana","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64818,254,"GUF","French Guiana","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64819,254,"GUF","French Guiana","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64820,254,"GUF","French Guiana","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64821,254,"GUF","French Guiana","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64822,254,"GUF","French Guiana","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64823,254,"GUF","French Guiana","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64824,254,"GUF","French Guiana","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64825,254,"GUF","French Guiana","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUF/guf_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64826,258,"PYF","French Polynesia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64827,258,"PYF","French Polynesia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64828,258,"PYF","French Polynesia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64829,258,"PYF","French Polynesia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64830,258,"PYF","French Polynesia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64831,258,"PYF","French Polynesia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64832,258,"PYF","French Polynesia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64833,258,"PYF","French Polynesia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64834,258,"PYF","French Polynesia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64835,258,"PYF","French Polynesia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64836,258,"PYF","French Polynesia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64837,258,"PYF","French Polynesia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64838,258,"PYF","French Polynesia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64839,258,"PYF","French Polynesia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64840,258,"PYF","French Polynesia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64841,258,"PYF","French Polynesia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64842,258,"PYF","French Polynesia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64843,258,"PYF","French Polynesia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64844,258,"PYF","French Polynesia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64845,258,"PYF","French Polynesia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64846,258,"PYF","French Polynesia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64847,258,"PYF","French Polynesia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64848,258,"PYF","French Polynesia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64849,258,"PYF","French Polynesia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64850,258,"PYF","French Polynesia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64851,258,"PYF","French Polynesia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64852,258,"PYF","French Polynesia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64853,258,"PYF","French Polynesia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64854,258,"PYF","French Polynesia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64855,258,"PYF","French Polynesia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64856,258,"PYF","French Polynesia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64857,258,"PYF","French Polynesia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64858,258,"PYF","French Polynesia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64859,258,"PYF","French Polynesia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64860,258,"PYF","French Polynesia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64861,258,"PYF","French Polynesia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PYF/pyf_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64862,260,"ATF","French Southern Territories","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64863,260,"ATF","French Southern Territories","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64864,260,"ATF","French Southern Territories","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64865,260,"ATF","French Southern Territories","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64866,260,"ATF","French Southern Territories","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64867,260,"ATF","French Southern Territories","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64868,260,"ATF","French Southern Territories","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64869,260,"ATF","French Southern Territories","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64870,260,"ATF","French Southern Territories","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64871,260,"ATF","French Southern Territories","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64872,260,"ATF","French Southern Territories","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64873,260,"ATF","French Southern Territories","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64874,260,"ATF","French Southern Territories","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64875,260,"ATF","French Southern Territories","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64876,260,"ATF","French Southern Territories","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64877,260,"ATF","French Southern Territories","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64878,260,"ATF","French Southern Territories","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64879,260,"ATF","French Southern Territories","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64880,260,"ATF","French Southern Territories","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64881,260,"ATF","French Southern Territories","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64882,260,"ATF","French Southern Territories","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64883,260,"ATF","French Southern Territories","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64884,260,"ATF","French Southern Territories","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64885,260,"ATF","French Southern Territories","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64886,260,"ATF","French Southern Territories","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64887,260,"ATF","French Southern Territories","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64888,260,"ATF","French Southern Territories","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64889,260,"ATF","French Southern Territories","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64890,260,"ATF","French Southern Territories","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64891,260,"ATF","French Southern Territories","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64892,260,"ATF","French Southern Territories","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64893,260,"ATF","French Southern Territories","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64894,260,"ATF","French Southern Territories","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64895,260,"ATF","French Southern Territories","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64896,260,"ATF","French Southern Territories","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64897,260,"ATF","French Southern Territories","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ATF/atf_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64898,262,"DJI","Djibouti","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64899,262,"DJI","Djibouti","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64900,262,"DJI","Djibouti","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64901,262,"DJI","Djibouti","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64902,262,"DJI","Djibouti","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64903,262,"DJI","Djibouti","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64904,262,"DJI","Djibouti","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64905,262,"DJI","Djibouti","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64906,262,"DJI","Djibouti","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64907,262,"DJI","Djibouti","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64908,262,"DJI","Djibouti","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64909,262,"DJI","Djibouti","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64910,262,"DJI","Djibouti","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64911,262,"DJI","Djibouti","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64912,262,"DJI","Djibouti","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64913,262,"DJI","Djibouti","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64914,262,"DJI","Djibouti","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64915,262,"DJI","Djibouti","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64916,262,"DJI","Djibouti","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64917,262,"DJI","Djibouti","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64918,262,"DJI","Djibouti","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64919,262,"DJI","Djibouti","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64920,262,"DJI","Djibouti","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64921,262,"DJI","Djibouti","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64922,262,"DJI","Djibouti","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64923,262,"DJI","Djibouti","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64924,262,"DJI","Djibouti","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64925,262,"DJI","Djibouti","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64926,262,"DJI","Djibouti","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64927,262,"DJI","Djibouti","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64928,262,"DJI","Djibouti","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64929,262,"DJI","Djibouti","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64930,262,"DJI","Djibouti","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64931,262,"DJI","Djibouti","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64932,262,"DJI","Djibouti","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64933,262,"DJI","Djibouti","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DJI/dji_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64934,266,"GAB","Gabon","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64935,266,"GAB","Gabon","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64936,266,"GAB","Gabon","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64937,266,"GAB","Gabon","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64938,266,"GAB","Gabon","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64939,266,"GAB","Gabon","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64940,266,"GAB","Gabon","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64941,266,"GAB","Gabon","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64942,266,"GAB","Gabon","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64943,266,"GAB","Gabon","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64944,266,"GAB","Gabon","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64945,266,"GAB","Gabon","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64946,266,"GAB","Gabon","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64947,266,"GAB","Gabon","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64948,266,"GAB","Gabon","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64949,266,"GAB","Gabon","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64950,266,"GAB","Gabon","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64951,266,"GAB","Gabon","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64952,266,"GAB","Gabon","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64953,266,"GAB","Gabon","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64954,266,"GAB","Gabon","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64955,266,"GAB","Gabon","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64956,266,"GAB","Gabon","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64957,266,"GAB","Gabon","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64958,266,"GAB","Gabon","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64959,266,"GAB","Gabon","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64960,266,"GAB","Gabon","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64961,266,"GAB","Gabon","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64962,266,"GAB","Gabon","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64963,266,"GAB","Gabon","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
64964,266,"GAB","Gabon","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
64965,266,"GAB","Gabon","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
64966,266,"GAB","Gabon","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
64967,266,"GAB","Gabon","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
64968,266,"GAB","Gabon","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
64969,266,"GAB","Gabon","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GAB/gab_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
64970,268,"GEO","Georgia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
64971,268,"GEO","Georgia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
64972,268,"GEO","Georgia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
64973,268,"GEO","Georgia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
64974,268,"GEO","Georgia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
64975,268,"GEO","Georgia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
64976,268,"GEO","Georgia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
64977,268,"GEO","Georgia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
64978,268,"GEO","Georgia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
64979,268,"GEO","Georgia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
64980,268,"GEO","Georgia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
64981,268,"GEO","Georgia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
64982,268,"GEO","Georgia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
64983,268,"GEO","Georgia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
64984,268,"GEO","Georgia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
64985,268,"GEO","Georgia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
64986,268,"GEO","Georgia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
64987,268,"GEO","Georgia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
64988,268,"GEO","Georgia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
64989,268,"GEO","Georgia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
64990,268,"GEO","Georgia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
64991,268,"GEO","Georgia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
64992,268,"GEO","Georgia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
64993,268,"GEO","Georgia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
64994,268,"GEO","Georgia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
64995,268,"GEO","Georgia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
64996,268,"GEO","Georgia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
64997,268,"GEO","Georgia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
64998,268,"GEO","Georgia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
64999,268,"GEO","Georgia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65000,268,"GEO","Georgia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65001,268,"GEO","Georgia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65002,268,"GEO","Georgia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65003,268,"GEO","Georgia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65004,268,"GEO","Georgia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65005,268,"GEO","Georgia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GEO/geo_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65006,270,"GMB","Gambia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65007,270,"GMB","Gambia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65008,270,"GMB","Gambia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65009,270,"GMB","Gambia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65010,270,"GMB","Gambia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65011,270,"GMB","Gambia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65012,270,"GMB","Gambia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65013,270,"GMB","Gambia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65014,270,"GMB","Gambia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65015,270,"GMB","Gambia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65016,270,"GMB","Gambia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65017,270,"GMB","Gambia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65018,270,"GMB","Gambia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65019,270,"GMB","Gambia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65020,270,"GMB","Gambia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65021,270,"GMB","Gambia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65022,270,"GMB","Gambia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65023,270,"GMB","Gambia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65024,270,"GMB","Gambia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65025,270,"GMB","Gambia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65026,270,"GMB","Gambia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65027,270,"GMB","Gambia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65028,270,"GMB","Gambia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65029,270,"GMB","Gambia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65030,270,"GMB","Gambia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65031,270,"GMB","Gambia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65032,270,"GMB","Gambia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65033,270,"GMB","Gambia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65034,270,"GMB","Gambia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65035,270,"GMB","Gambia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65036,270,"GMB","Gambia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65037,270,"GMB","Gambia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65038,270,"GMB","Gambia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65039,270,"GMB","Gambia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65040,270,"GMB","Gambia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65041,270,"GMB","Gambia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GMB/gmb_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65042,275,"PSE","Palestina","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65043,275,"PSE","Palestina","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65044,275,"PSE","Palestina","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65045,275,"PSE","Palestina","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65046,275,"PSE","Palestina","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65047,275,"PSE","Palestina","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65048,275,"PSE","Palestina","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65049,275,"PSE","Palestina","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65050,275,"PSE","Palestina","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65051,275,"PSE","Palestina","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65052,275,"PSE","Palestina","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65053,275,"PSE","Palestina","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65054,275,"PSE","Palestina","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65055,275,"PSE","Palestina","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65056,275,"PSE","Palestina","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65057,275,"PSE","Palestina","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65058,275,"PSE","Palestina","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65059,275,"PSE","Palestina","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65060,275,"PSE","Palestina","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65061,275,"PSE","Palestina","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65062,275,"PSE","Palestina","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65063,275,"PSE","Palestina","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65064,275,"PSE","Palestina","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65065,275,"PSE","Palestina","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65066,275,"PSE","Palestina","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65067,275,"PSE","Palestina","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65068,275,"PSE","Palestina","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65069,275,"PSE","Palestina","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65070,275,"PSE","Palestina","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65071,275,"PSE","Palestina","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65072,275,"PSE","Palestina","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65073,275,"PSE","Palestina","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65074,275,"PSE","Palestina","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65075,275,"PSE","Palestina","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65076,275,"PSE","Palestina","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65077,275,"PSE","Palestina","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PSE/pse_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65078,276,"DEU","Germany","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65079,276,"DEU","Germany","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65080,276,"DEU","Germany","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65081,276,"DEU","Germany","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65082,276,"DEU","Germany","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65083,276,"DEU","Germany","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65084,276,"DEU","Germany","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65085,276,"DEU","Germany","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65086,276,"DEU","Germany","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65087,276,"DEU","Germany","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65088,276,"DEU","Germany","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65089,276,"DEU","Germany","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65090,276,"DEU","Germany","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65091,276,"DEU","Germany","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65092,276,"DEU","Germany","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65093,276,"DEU","Germany","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65094,276,"DEU","Germany","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65095,276,"DEU","Germany","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65096,276,"DEU","Germany","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65097,276,"DEU","Germany","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65098,276,"DEU","Germany","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65099,276,"DEU","Germany","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65100,276,"DEU","Germany","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65101,276,"DEU","Germany","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65102,276,"DEU","Germany","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65103,276,"DEU","Germany","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65104,276,"DEU","Germany","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65105,276,"DEU","Germany","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65106,276,"DEU","Germany","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65107,276,"DEU","Germany","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65108,276,"DEU","Germany","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65109,276,"DEU","Germany","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65110,276,"DEU","Germany","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65111,276,"DEU","Germany","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65112,276,"DEU","Germany","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65113,276,"DEU","Germany","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/DEU/deu_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65114,288,"GHA","Ghana","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65115,288,"GHA","Ghana","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65116,288,"GHA","Ghana","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65117,288,"GHA","Ghana","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65118,288,"GHA","Ghana","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65119,288,"GHA","Ghana","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65120,288,"GHA","Ghana","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65121,288,"GHA","Ghana","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65122,288,"GHA","Ghana","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65123,288,"GHA","Ghana","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65124,288,"GHA","Ghana","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65125,288,"GHA","Ghana","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65126,288,"GHA","Ghana","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65127,288,"GHA","Ghana","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65128,288,"GHA","Ghana","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65129,288,"GHA","Ghana","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65130,288,"GHA","Ghana","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65131,288,"GHA","Ghana","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65132,288,"GHA","Ghana","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65133,288,"GHA","Ghana","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65134,288,"GHA","Ghana","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65135,288,"GHA","Ghana","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65136,288,"GHA","Ghana","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65137,288,"GHA","Ghana","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65138,288,"GHA","Ghana","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65139,288,"GHA","Ghana","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65140,288,"GHA","Ghana","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65141,288,"GHA","Ghana","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65142,288,"GHA","Ghana","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65143,288,"GHA","Ghana","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65144,288,"GHA","Ghana","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65145,288,"GHA","Ghana","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65146,288,"GHA","Ghana","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65147,288,"GHA","Ghana","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65148,288,"GHA","Ghana","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65149,288,"GHA","Ghana","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GHA/gha_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65150,292,"GIB","Gibraltar","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65151,292,"GIB","Gibraltar","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65152,292,"GIB","Gibraltar","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65153,292,"GIB","Gibraltar","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65154,292,"GIB","Gibraltar","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65155,292,"GIB","Gibraltar","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65156,292,"GIB","Gibraltar","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65157,292,"GIB","Gibraltar","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65158,292,"GIB","Gibraltar","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65159,292,"GIB","Gibraltar","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65160,292,"GIB","Gibraltar","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65161,292,"GIB","Gibraltar","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65162,292,"GIB","Gibraltar","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65163,292,"GIB","Gibraltar","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65164,292,"GIB","Gibraltar","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65165,292,"GIB","Gibraltar","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65166,292,"GIB","Gibraltar","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65167,292,"GIB","Gibraltar","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65168,292,"GIB","Gibraltar","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65169,292,"GIB","Gibraltar","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65170,292,"GIB","Gibraltar","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65171,292,"GIB","Gibraltar","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65172,292,"GIB","Gibraltar","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65173,292,"GIB","Gibraltar","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65174,292,"GIB","Gibraltar","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65175,292,"GIB","Gibraltar","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65176,292,"GIB","Gibraltar","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65177,292,"GIB","Gibraltar","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65178,292,"GIB","Gibraltar","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65179,292,"GIB","Gibraltar","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65180,292,"GIB","Gibraltar","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65181,292,"GIB","Gibraltar","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65182,292,"GIB","Gibraltar","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65183,292,"GIB","Gibraltar","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65184,292,"GIB","Gibraltar","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65185,292,"GIB","Gibraltar","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIB/gib_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65186,296,"KIR","Kiribati","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65187,296,"KIR","Kiribati","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65188,296,"KIR","Kiribati","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65189,296,"KIR","Kiribati","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65190,296,"KIR","Kiribati","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65191,296,"KIR","Kiribati","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65192,296,"KIR","Kiribati","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65193,296,"KIR","Kiribati","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65194,296,"KIR","Kiribati","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65195,296,"KIR","Kiribati","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65196,296,"KIR","Kiribati","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65197,296,"KIR","Kiribati","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65198,296,"KIR","Kiribati","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65199,296,"KIR","Kiribati","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65200,296,"KIR","Kiribati","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65201,296,"KIR","Kiribati","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65202,296,"KIR","Kiribati","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65203,296,"KIR","Kiribati","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65204,296,"KIR","Kiribati","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65205,296,"KIR","Kiribati","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65206,296,"KIR","Kiribati","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65207,296,"KIR","Kiribati","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65208,296,"KIR","Kiribati","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65209,296,"KIR","Kiribati","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65210,296,"KIR","Kiribati","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65211,296,"KIR","Kiribati","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65212,296,"KIR","Kiribati","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65213,296,"KIR","Kiribati","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65214,296,"KIR","Kiribati","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65215,296,"KIR","Kiribati","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65216,296,"KIR","Kiribati","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65217,296,"KIR","Kiribati","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65218,296,"KIR","Kiribati","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65219,296,"KIR","Kiribati","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65220,296,"KIR","Kiribati","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65221,296,"KIR","Kiribati","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KIR/kir_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65222,300,"GRC","Greece","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65223,300,"GRC","Greece","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65224,300,"GRC","Greece","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65225,300,"GRC","Greece","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65226,300,"GRC","Greece","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65227,300,"GRC","Greece","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65228,300,"GRC","Greece","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65229,300,"GRC","Greece","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65230,300,"GRC","Greece","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65231,300,"GRC","Greece","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65232,300,"GRC","Greece","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65233,300,"GRC","Greece","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65234,300,"GRC","Greece","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65235,300,"GRC","Greece","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65236,300,"GRC","Greece","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65237,300,"GRC","Greece","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65238,300,"GRC","Greece","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65239,300,"GRC","Greece","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65240,300,"GRC","Greece","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65241,300,"GRC","Greece","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65242,300,"GRC","Greece","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65243,300,"GRC","Greece","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65244,300,"GRC","Greece","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65245,300,"GRC","Greece","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65246,300,"GRC","Greece","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65247,300,"GRC","Greece","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65248,300,"GRC","Greece","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65249,300,"GRC","Greece","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65250,300,"GRC","Greece","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65251,300,"GRC","Greece","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65252,300,"GRC","Greece","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65253,300,"GRC","Greece","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65254,300,"GRC","Greece","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65255,300,"GRC","Greece","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65256,300,"GRC","Greece","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65257,300,"GRC","Greece","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRC/grc_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65258,308,"GRD","Grenada","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65259,308,"GRD","Grenada","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65260,308,"GRD","Grenada","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65261,308,"GRD","Grenada","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65262,308,"GRD","Grenada","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65263,308,"GRD","Grenada","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65264,308,"GRD","Grenada","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65265,308,"GRD","Grenada","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65266,308,"GRD","Grenada","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65267,308,"GRD","Grenada","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65268,308,"GRD","Grenada","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65269,308,"GRD","Grenada","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65270,308,"GRD","Grenada","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65271,308,"GRD","Grenada","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65272,308,"GRD","Grenada","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65273,308,"GRD","Grenada","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65274,308,"GRD","Grenada","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65275,308,"GRD","Grenada","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65276,308,"GRD","Grenada","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65277,308,"GRD","Grenada","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65278,308,"GRD","Grenada","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65279,308,"GRD","Grenada","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65280,308,"GRD","Grenada","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65281,308,"GRD","Grenada","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65282,308,"GRD","Grenada","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65283,308,"GRD","Grenada","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65284,308,"GRD","Grenada","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65285,308,"GRD","Grenada","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65286,308,"GRD","Grenada","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65287,308,"GRD","Grenada","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65288,308,"GRD","Grenada","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65289,308,"GRD","Grenada","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65290,308,"GRD","Grenada","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65291,308,"GRD","Grenada","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65292,308,"GRD","Grenada","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65293,308,"GRD","Grenada","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GRD/grd_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65294,312,"GLP","Guadeloupe","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65295,312,"GLP","Guadeloupe","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65296,312,"GLP","Guadeloupe","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65297,312,"GLP","Guadeloupe","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65298,312,"GLP","Guadeloupe","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65299,312,"GLP","Guadeloupe","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65300,312,"GLP","Guadeloupe","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65301,312,"GLP","Guadeloupe","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65302,312,"GLP","Guadeloupe","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65303,312,"GLP","Guadeloupe","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65304,312,"GLP","Guadeloupe","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65305,312,"GLP","Guadeloupe","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65306,312,"GLP","Guadeloupe","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65307,312,"GLP","Guadeloupe","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65308,312,"GLP","Guadeloupe","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65309,312,"GLP","Guadeloupe","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65310,312,"GLP","Guadeloupe","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65311,312,"GLP","Guadeloupe","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65312,312,"GLP","Guadeloupe","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65313,312,"GLP","Guadeloupe","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65314,312,"GLP","Guadeloupe","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65315,312,"GLP","Guadeloupe","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65316,312,"GLP","Guadeloupe","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65317,312,"GLP","Guadeloupe","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65318,312,"GLP","Guadeloupe","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65319,312,"GLP","Guadeloupe","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65320,312,"GLP","Guadeloupe","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65321,312,"GLP","Guadeloupe","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65322,312,"GLP","Guadeloupe","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65323,312,"GLP","Guadeloupe","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65324,312,"GLP","Guadeloupe","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65325,312,"GLP","Guadeloupe","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65326,312,"GLP","Guadeloupe","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65327,312,"GLP","Guadeloupe","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65328,312,"GLP","Guadeloupe","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65329,312,"GLP","Guadeloupe","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GLP/glp_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65330,316,"GUM","Guam","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65331,316,"GUM","Guam","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65332,316,"GUM","Guam","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65333,316,"GUM","Guam","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65334,316,"GUM","Guam","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65335,316,"GUM","Guam","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65336,316,"GUM","Guam","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65337,316,"GUM","Guam","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65338,316,"GUM","Guam","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65339,316,"GUM","Guam","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65340,316,"GUM","Guam","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65341,316,"GUM","Guam","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65342,316,"GUM","Guam","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65343,316,"GUM","Guam","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65344,316,"GUM","Guam","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65345,316,"GUM","Guam","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65346,316,"GUM","Guam","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65347,316,"GUM","Guam","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65348,316,"GUM","Guam","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65349,316,"GUM","Guam","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65350,316,"GUM","Guam","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65351,316,"GUM","Guam","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65352,316,"GUM","Guam","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65353,316,"GUM","Guam","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65354,316,"GUM","Guam","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65355,316,"GUM","Guam","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65356,316,"GUM","Guam","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65357,316,"GUM","Guam","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65358,316,"GUM","Guam","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65359,316,"GUM","Guam","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65360,316,"GUM","Guam","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65361,316,"GUM","Guam","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65362,316,"GUM","Guam","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65363,316,"GUM","Guam","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65364,316,"GUM","Guam","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65365,316,"GUM","Guam","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUM/gum_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65366,320,"GTM","Guatemala","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65367,320,"GTM","Guatemala","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65368,320,"GTM","Guatemala","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65369,320,"GTM","Guatemala","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65370,320,"GTM","Guatemala","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65371,320,"GTM","Guatemala","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65372,320,"GTM","Guatemala","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65373,320,"GTM","Guatemala","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65374,320,"GTM","Guatemala","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65375,320,"GTM","Guatemala","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65376,320,"GTM","Guatemala","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65377,320,"GTM","Guatemala","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65378,320,"GTM","Guatemala","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65379,320,"GTM","Guatemala","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65380,320,"GTM","Guatemala","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65381,320,"GTM","Guatemala","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65382,320,"GTM","Guatemala","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65383,320,"GTM","Guatemala","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65384,320,"GTM","Guatemala","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65385,320,"GTM","Guatemala","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65386,320,"GTM","Guatemala","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65387,320,"GTM","Guatemala","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65388,320,"GTM","Guatemala","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65389,320,"GTM","Guatemala","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65390,320,"GTM","Guatemala","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65391,320,"GTM","Guatemala","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65392,320,"GTM","Guatemala","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65393,320,"GTM","Guatemala","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65394,320,"GTM","Guatemala","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65395,320,"GTM","Guatemala","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65396,320,"GTM","Guatemala","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65397,320,"GTM","Guatemala","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65398,320,"GTM","Guatemala","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65399,320,"GTM","Guatemala","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65400,320,"GTM","Guatemala","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65401,320,"GTM","Guatemala","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GTM/gtm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65402,324,"GIN","Guinea","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65403,324,"GIN","Guinea","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65404,324,"GIN","Guinea","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65405,324,"GIN","Guinea","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65406,324,"GIN","Guinea","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65407,324,"GIN","Guinea","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65408,324,"GIN","Guinea","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65409,324,"GIN","Guinea","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65410,324,"GIN","Guinea","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65411,324,"GIN","Guinea","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65412,324,"GIN","Guinea","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65413,324,"GIN","Guinea","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65414,324,"GIN","Guinea","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65415,324,"GIN","Guinea","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65416,324,"GIN","Guinea","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65417,324,"GIN","Guinea","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65418,324,"GIN","Guinea","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65419,324,"GIN","Guinea","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65420,324,"GIN","Guinea","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65421,324,"GIN","Guinea","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65422,324,"GIN","Guinea","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65423,324,"GIN","Guinea","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65424,324,"GIN","Guinea","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65425,324,"GIN","Guinea","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65426,324,"GIN","Guinea","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65427,324,"GIN","Guinea","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65428,324,"GIN","Guinea","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65429,324,"GIN","Guinea","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65430,324,"GIN","Guinea","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65431,324,"GIN","Guinea","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65432,324,"GIN","Guinea","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65433,324,"GIN","Guinea","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65434,324,"GIN","Guinea","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65435,324,"GIN","Guinea","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65436,324,"GIN","Guinea","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65437,324,"GIN","Guinea","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GIN/gin_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65438,328,"GUY","Guyana","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65439,328,"GUY","Guyana","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65440,328,"GUY","Guyana","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65441,328,"GUY","Guyana","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65442,328,"GUY","Guyana","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65443,328,"GUY","Guyana","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65444,328,"GUY","Guyana","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65445,328,"GUY","Guyana","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65446,328,"GUY","Guyana","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65447,328,"GUY","Guyana","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65448,328,"GUY","Guyana","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65449,328,"GUY","Guyana","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65450,328,"GUY","Guyana","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65451,328,"GUY","Guyana","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65452,328,"GUY","Guyana","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65453,328,"GUY","Guyana","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65454,328,"GUY","Guyana","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65455,328,"GUY","Guyana","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65456,328,"GUY","Guyana","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65457,328,"GUY","Guyana","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65458,328,"GUY","Guyana","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65459,328,"GUY","Guyana","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65460,328,"GUY","Guyana","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65461,328,"GUY","Guyana","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65462,328,"GUY","Guyana","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65463,328,"GUY","Guyana","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65464,328,"GUY","Guyana","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65465,328,"GUY","Guyana","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65466,328,"GUY","Guyana","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65467,328,"GUY","Guyana","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65468,328,"GUY","Guyana","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65469,328,"GUY","Guyana","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65470,328,"GUY","Guyana","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65471,328,"GUY","Guyana","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65472,328,"GUY","Guyana","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65473,328,"GUY","Guyana","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GUY/guy_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65474,332,"HTI","Haiti","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65475,332,"HTI","Haiti","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65476,332,"HTI","Haiti","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65477,332,"HTI","Haiti","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65478,332,"HTI","Haiti","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65479,332,"HTI","Haiti","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65480,332,"HTI","Haiti","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65481,332,"HTI","Haiti","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65482,332,"HTI","Haiti","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65483,332,"HTI","Haiti","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65484,332,"HTI","Haiti","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65485,332,"HTI","Haiti","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65486,332,"HTI","Haiti","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65487,332,"HTI","Haiti","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65488,332,"HTI","Haiti","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65489,332,"HTI","Haiti","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65490,332,"HTI","Haiti","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65491,332,"HTI","Haiti","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65492,332,"HTI","Haiti","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65493,332,"HTI","Haiti","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65494,332,"HTI","Haiti","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65495,332,"HTI","Haiti","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65496,332,"HTI","Haiti","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65497,332,"HTI","Haiti","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65498,332,"HTI","Haiti","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65499,332,"HTI","Haiti","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65500,332,"HTI","Haiti","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65501,332,"HTI","Haiti","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65502,332,"HTI","Haiti","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65503,332,"HTI","Haiti","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65504,332,"HTI","Haiti","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65505,332,"HTI","Haiti","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65506,332,"HTI","Haiti","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65507,332,"HTI","Haiti","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65508,332,"HTI","Haiti","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65509,332,"HTI","Haiti","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HTI/hti_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65510,334,"HMD","Heard Island and McDonald Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65511,334,"HMD","Heard Island and McDonald Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65512,334,"HMD","Heard Island and McDonald Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65513,334,"HMD","Heard Island and McDonald Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65514,334,"HMD","Heard Island and McDonald Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65515,334,"HMD","Heard Island and McDonald Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65516,334,"HMD","Heard Island and McDonald Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65517,334,"HMD","Heard Island and McDonald Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65518,334,"HMD","Heard Island and McDonald Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65519,334,"HMD","Heard Island and McDonald Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65520,334,"HMD","Heard Island and McDonald Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65521,334,"HMD","Heard Island and McDonald Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65522,334,"HMD","Heard Island and McDonald Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65523,334,"HMD","Heard Island and McDonald Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65524,334,"HMD","Heard Island and McDonald Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65525,334,"HMD","Heard Island and McDonald Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65526,334,"HMD","Heard Island and McDonald Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65527,334,"HMD","Heard Island and McDonald Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65528,334,"HMD","Heard Island and McDonald Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65529,334,"HMD","Heard Island and McDonald Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65530,334,"HMD","Heard Island and McDonald Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65531,334,"HMD","Heard Island and McDonald Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65532,334,"HMD","Heard Island and McDonald Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65533,334,"HMD","Heard Island and McDonald Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65534,334,"HMD","Heard Island and McDonald Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65535,334,"HMD","Heard Island and McDonald Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65536,334,"HMD","Heard Island and McDonald Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65537,334,"HMD","Heard Island and McDonald Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65538,334,"HMD","Heard Island and McDonald Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65539,334,"HMD","Heard Island and McDonald Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65540,334,"HMD","Heard Island and McDonald Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65541,334,"HMD","Heard Island and McDonald Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65542,334,"HMD","Heard Island and McDonald Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65543,334,"HMD","Heard Island and McDonald Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65544,334,"HMD","Heard Island and McDonald Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65545,334,"HMD","Heard Island and McDonald Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HMD/hmd_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65546,336,"VAT","Vatican City","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65547,336,"VAT","Vatican City","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65548,336,"VAT","Vatican City","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65549,336,"VAT","Vatican City","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65550,336,"VAT","Vatican City","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65551,336,"VAT","Vatican City","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65552,336,"VAT","Vatican City","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65553,336,"VAT","Vatican City","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65554,336,"VAT","Vatican City","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65555,336,"VAT","Vatican City","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65556,336,"VAT","Vatican City","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65557,336,"VAT","Vatican City","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65558,336,"VAT","Vatican City","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65559,336,"VAT","Vatican City","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65560,336,"VAT","Vatican City","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65561,336,"VAT","Vatican City","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65562,336,"VAT","Vatican City","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65563,336,"VAT","Vatican City","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65564,336,"VAT","Vatican City","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65565,336,"VAT","Vatican City","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65566,336,"VAT","Vatican City","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65567,336,"VAT","Vatican City","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65568,336,"VAT","Vatican City","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65569,336,"VAT","Vatican City","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65570,336,"VAT","Vatican City","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65571,336,"VAT","Vatican City","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65572,336,"VAT","Vatican City","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65573,336,"VAT","Vatican City","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65574,336,"VAT","Vatican City","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65575,336,"VAT","Vatican City","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65576,336,"VAT","Vatican City","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65577,336,"VAT","Vatican City","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65578,336,"VAT","Vatican City","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65579,336,"VAT","Vatican City","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65580,336,"VAT","Vatican City","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65581,336,"VAT","Vatican City","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VAT/vat_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65582,340,"HND","Honduras","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65583,340,"HND","Honduras","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65584,340,"HND","Honduras","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65585,340,"HND","Honduras","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65586,340,"HND","Honduras","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65587,340,"HND","Honduras","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65588,340,"HND","Honduras","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65589,340,"HND","Honduras","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65590,340,"HND","Honduras","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65591,340,"HND","Honduras","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65592,340,"HND","Honduras","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65593,340,"HND","Honduras","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65594,340,"HND","Honduras","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65595,340,"HND","Honduras","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65596,340,"HND","Honduras","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65597,340,"HND","Honduras","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65598,340,"HND","Honduras","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65599,340,"HND","Honduras","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65600,340,"HND","Honduras","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65601,340,"HND","Honduras","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65602,340,"HND","Honduras","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65603,340,"HND","Honduras","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65604,340,"HND","Honduras","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65605,340,"HND","Honduras","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65606,340,"HND","Honduras","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65607,340,"HND","Honduras","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65608,340,"HND","Honduras","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65609,340,"HND","Honduras","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65610,340,"HND","Honduras","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65611,340,"HND","Honduras","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65612,340,"HND","Honduras","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65613,340,"HND","Honduras","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65614,340,"HND","Honduras","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65615,340,"HND","Honduras","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65616,340,"HND","Honduras","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65617,340,"HND","Honduras","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HND/hnd_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65618,344,"HKG","Hong Kong","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65619,344,"HKG","Hong Kong","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65620,344,"HKG","Hong Kong","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65621,344,"HKG","Hong Kong","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65622,344,"HKG","Hong Kong","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65623,344,"HKG","Hong Kong","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65624,344,"HKG","Hong Kong","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65625,344,"HKG","Hong Kong","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65626,344,"HKG","Hong Kong","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65627,344,"HKG","Hong Kong","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65628,344,"HKG","Hong Kong","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65629,344,"HKG","Hong Kong","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65630,344,"HKG","Hong Kong","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65631,344,"HKG","Hong Kong","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65632,344,"HKG","Hong Kong","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65633,344,"HKG","Hong Kong","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65634,344,"HKG","Hong Kong","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65635,344,"HKG","Hong Kong","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65636,344,"HKG","Hong Kong","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65637,344,"HKG","Hong Kong","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65638,344,"HKG","Hong Kong","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65639,344,"HKG","Hong Kong","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65640,344,"HKG","Hong Kong","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65641,344,"HKG","Hong Kong","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65642,344,"HKG","Hong Kong","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65643,344,"HKG","Hong Kong","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65644,344,"HKG","Hong Kong","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65645,344,"HKG","Hong Kong","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65646,344,"HKG","Hong Kong","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65647,344,"HKG","Hong Kong","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65648,344,"HKG","Hong Kong","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65649,344,"HKG","Hong Kong","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65650,344,"HKG","Hong Kong","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65651,344,"HKG","Hong Kong","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65652,344,"HKG","Hong Kong","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65653,344,"HKG","Hong Kong","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HKG/hkg_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65654,348,"HUN","Hungary","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65655,348,"HUN","Hungary","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65656,348,"HUN","Hungary","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65657,348,"HUN","Hungary","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65658,348,"HUN","Hungary","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65659,348,"HUN","Hungary","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65660,348,"HUN","Hungary","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65661,348,"HUN","Hungary","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65662,348,"HUN","Hungary","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65663,348,"HUN","Hungary","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65664,348,"HUN","Hungary","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65665,348,"HUN","Hungary","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65666,348,"HUN","Hungary","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65667,348,"HUN","Hungary","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65668,348,"HUN","Hungary","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65669,348,"HUN","Hungary","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65670,348,"HUN","Hungary","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65671,348,"HUN","Hungary","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65672,348,"HUN","Hungary","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65673,348,"HUN","Hungary","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65674,348,"HUN","Hungary","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65675,348,"HUN","Hungary","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65676,348,"HUN","Hungary","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65677,348,"HUN","Hungary","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65678,348,"HUN","Hungary","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65679,348,"HUN","Hungary","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65680,348,"HUN","Hungary","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65681,348,"HUN","Hungary","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65682,348,"HUN","Hungary","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65683,348,"HUN","Hungary","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65684,348,"HUN","Hungary","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65685,348,"HUN","Hungary","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65686,348,"HUN","Hungary","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65687,348,"HUN","Hungary","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65688,348,"HUN","Hungary","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65689,348,"HUN","Hungary","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/HUN/hun_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65690,352,"ISL","Iceland","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65691,352,"ISL","Iceland","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65692,352,"ISL","Iceland","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65693,352,"ISL","Iceland","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65694,352,"ISL","Iceland","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65695,352,"ISL","Iceland","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65696,352,"ISL","Iceland","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65697,352,"ISL","Iceland","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65698,352,"ISL","Iceland","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65699,352,"ISL","Iceland","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65700,352,"ISL","Iceland","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65701,352,"ISL","Iceland","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65702,352,"ISL","Iceland","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65703,352,"ISL","Iceland","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65704,352,"ISL","Iceland","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65705,352,"ISL","Iceland","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65706,352,"ISL","Iceland","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65707,352,"ISL","Iceland","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65708,352,"ISL","Iceland","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65709,352,"ISL","Iceland","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65710,352,"ISL","Iceland","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65711,352,"ISL","Iceland","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65712,352,"ISL","Iceland","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65713,352,"ISL","Iceland","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65714,352,"ISL","Iceland","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65715,352,"ISL","Iceland","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65716,352,"ISL","Iceland","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65717,352,"ISL","Iceland","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65718,352,"ISL","Iceland","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65719,352,"ISL","Iceland","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65720,352,"ISL","Iceland","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65721,352,"ISL","Iceland","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65722,352,"ISL","Iceland","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65723,352,"ISL","Iceland","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65724,352,"ISL","Iceland","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65725,352,"ISL","Iceland","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISL/isl_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65726,356,"IND","India","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65727,356,"IND","India","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65728,356,"IND","India","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65729,356,"IND","India","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65730,356,"IND","India","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65731,356,"IND","India","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65732,356,"IND","India","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65733,356,"IND","India","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65734,356,"IND","India","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65735,356,"IND","India","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65736,356,"IND","India","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65737,356,"IND","India","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65738,356,"IND","India","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65739,356,"IND","India","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65740,356,"IND","India","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65741,356,"IND","India","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65742,356,"IND","India","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65743,356,"IND","India","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65744,356,"IND","India","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65745,356,"IND","India","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65746,356,"IND","India","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65747,356,"IND","India","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65748,356,"IND","India","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65749,356,"IND","India","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65750,356,"IND","India","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65751,356,"IND","India","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65752,356,"IND","India","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65753,356,"IND","India","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65754,356,"IND","India","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65755,356,"IND","India","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65756,356,"IND","India","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65757,356,"IND","India","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65758,356,"IND","India","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65759,356,"IND","India","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65760,356,"IND","India","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65761,356,"IND","India","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IND/ind_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65762,364,"IRN","Iran","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65763,364,"IRN","Iran","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65764,364,"IRN","Iran","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65765,364,"IRN","Iran","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65766,364,"IRN","Iran","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65767,364,"IRN","Iran","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65768,364,"IRN","Iran","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65769,364,"IRN","Iran","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65770,364,"IRN","Iran","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65771,364,"IRN","Iran","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65772,364,"IRN","Iran","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65773,364,"IRN","Iran","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65774,364,"IRN","Iran","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65775,364,"IRN","Iran","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65776,364,"IRN","Iran","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65777,364,"IRN","Iran","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65778,364,"IRN","Iran","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65779,364,"IRN","Iran","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65780,364,"IRN","Iran","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65781,364,"IRN","Iran","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65782,364,"IRN","Iran","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65783,364,"IRN","Iran","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65784,364,"IRN","Iran","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65785,364,"IRN","Iran","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65786,364,"IRN","Iran","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65787,364,"IRN","Iran","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65788,364,"IRN","Iran","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65789,364,"IRN","Iran","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65790,364,"IRN","Iran","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65791,364,"IRN","Iran","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65792,364,"IRN","Iran","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65793,364,"IRN","Iran","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65794,364,"IRN","Iran","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65795,364,"IRN","Iran","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65796,364,"IRN","Iran","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65797,364,"IRN","Iran","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRN/irn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65798,368,"IRQ","Iraq","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65799,368,"IRQ","Iraq","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65800,368,"IRQ","Iraq","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65801,368,"IRQ","Iraq","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65802,368,"IRQ","Iraq","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65803,368,"IRQ","Iraq","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65804,368,"IRQ","Iraq","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65805,368,"IRQ","Iraq","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65806,368,"IRQ","Iraq","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65807,368,"IRQ","Iraq","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65808,368,"IRQ","Iraq","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65809,368,"IRQ","Iraq","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65810,368,"IRQ","Iraq","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65811,368,"IRQ","Iraq","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65812,368,"IRQ","Iraq","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65813,368,"IRQ","Iraq","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65814,368,"IRQ","Iraq","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65815,368,"IRQ","Iraq","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65816,368,"IRQ","Iraq","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65817,368,"IRQ","Iraq","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65818,368,"IRQ","Iraq","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65819,368,"IRQ","Iraq","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65820,368,"IRQ","Iraq","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65821,368,"IRQ","Iraq","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65822,368,"IRQ","Iraq","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65823,368,"IRQ","Iraq","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65824,368,"IRQ","Iraq","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65825,368,"IRQ","Iraq","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65826,368,"IRQ","Iraq","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65827,368,"IRQ","Iraq","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65828,368,"IRQ","Iraq","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65829,368,"IRQ","Iraq","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65830,368,"IRQ","Iraq","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65831,368,"IRQ","Iraq","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65832,368,"IRQ","Iraq","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65833,368,"IRQ","Iraq","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRQ/irq_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65834,372,"IRL","Ireland","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65835,372,"IRL","Ireland","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65836,372,"IRL","Ireland","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65837,372,"IRL","Ireland","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65838,372,"IRL","Ireland","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65839,372,"IRL","Ireland","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65840,372,"IRL","Ireland","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65841,372,"IRL","Ireland","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65842,372,"IRL","Ireland","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65843,372,"IRL","Ireland","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65844,372,"IRL","Ireland","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65845,372,"IRL","Ireland","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65846,372,"IRL","Ireland","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65847,372,"IRL","Ireland","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65848,372,"IRL","Ireland","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65849,372,"IRL","Ireland","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65850,372,"IRL","Ireland","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65851,372,"IRL","Ireland","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65852,372,"IRL","Ireland","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65853,372,"IRL","Ireland","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65854,372,"IRL","Ireland","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65855,372,"IRL","Ireland","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65856,372,"IRL","Ireland","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65857,372,"IRL","Ireland","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65858,372,"IRL","Ireland","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65859,372,"IRL","Ireland","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65860,372,"IRL","Ireland","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65861,372,"IRL","Ireland","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65862,372,"IRL","Ireland","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65863,372,"IRL","Ireland","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65864,372,"IRL","Ireland","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65865,372,"IRL","Ireland","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65866,372,"IRL","Ireland","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65867,372,"IRL","Ireland","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65868,372,"IRL","Ireland","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65869,372,"IRL","Ireland","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IRL/irl_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65870,376,"ISR","Israel","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65871,376,"ISR","Israel","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65872,376,"ISR","Israel","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65873,376,"ISR","Israel","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65874,376,"ISR","Israel","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65875,376,"ISR","Israel","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65876,376,"ISR","Israel","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65877,376,"ISR","Israel","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65878,376,"ISR","Israel","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65879,376,"ISR","Israel","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65880,376,"ISR","Israel","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65881,376,"ISR","Israel","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65882,376,"ISR","Israel","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65883,376,"ISR","Israel","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65884,376,"ISR","Israel","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65885,376,"ISR","Israel","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65886,376,"ISR","Israel","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65887,376,"ISR","Israel","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65888,376,"ISR","Israel","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65889,376,"ISR","Israel","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65890,376,"ISR","Israel","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65891,376,"ISR","Israel","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65892,376,"ISR","Israel","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65893,376,"ISR","Israel","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65894,376,"ISR","Israel","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65895,376,"ISR","Israel","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65896,376,"ISR","Israel","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65897,376,"ISR","Israel","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65898,376,"ISR","Israel","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65899,376,"ISR","Israel","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65900,376,"ISR","Israel","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65901,376,"ISR","Israel","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65902,376,"ISR","Israel","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65903,376,"ISR","Israel","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65904,376,"ISR","Israel","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65905,376,"ISR","Israel","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ISR/isr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65906,380,"ITA","Italy","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65907,380,"ITA","Italy","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65908,380,"ITA","Italy","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65909,380,"ITA","Italy","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65910,380,"ITA","Italy","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65911,380,"ITA","Italy","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65912,380,"ITA","Italy","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65913,380,"ITA","Italy","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65914,380,"ITA","Italy","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65915,380,"ITA","Italy","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65916,380,"ITA","Italy","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65917,380,"ITA","Italy","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65918,380,"ITA","Italy","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65919,380,"ITA","Italy","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65920,380,"ITA","Italy","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65921,380,"ITA","Italy","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65922,380,"ITA","Italy","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65923,380,"ITA","Italy","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65924,380,"ITA","Italy","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65925,380,"ITA","Italy","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65926,380,"ITA","Italy","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65927,380,"ITA","Italy","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65928,380,"ITA","Italy","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65929,380,"ITA","Italy","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65930,380,"ITA","Italy","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65931,380,"ITA","Italy","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65932,380,"ITA","Italy","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65933,380,"ITA","Italy","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65934,380,"ITA","Italy","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65935,380,"ITA","Italy","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65936,380,"ITA","Italy","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65937,380,"ITA","Italy","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65938,380,"ITA","Italy","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65939,380,"ITA","Italy","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65940,380,"ITA","Italy","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65941,380,"ITA","Italy","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ITA/ita_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65942,384,"CIV","CIte dIvoire","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65943,384,"CIV","CIte dIvoire","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65944,384,"CIV","CIte dIvoire","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65945,384,"CIV","CIte dIvoire","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65946,384,"CIV","CIte dIvoire","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65947,384,"CIV","CIte dIvoire","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65948,384,"CIV","CIte dIvoire","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65949,384,"CIV","CIte dIvoire","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65950,384,"CIV","CIte dIvoire","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65951,384,"CIV","CIte dIvoire","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65952,384,"CIV","CIte dIvoire","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65953,384,"CIV","CIte dIvoire","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65954,384,"CIV","CIte dIvoire","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65955,384,"CIV","CIte dIvoire","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65956,384,"CIV","CIte dIvoire","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65957,384,"CIV","CIte dIvoire","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65958,384,"CIV","CIte dIvoire","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65959,384,"CIV","CIte dIvoire","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65960,384,"CIV","CIte dIvoire","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65961,384,"CIV","CIte dIvoire","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65962,384,"CIV","CIte dIvoire","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65963,384,"CIV","CIte dIvoire","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
65964,384,"CIV","CIte dIvoire","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
65965,384,"CIV","CIte dIvoire","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
65966,384,"CIV","CIte dIvoire","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
65967,384,"CIV","CIte dIvoire","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
65968,384,"CIV","CIte dIvoire","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
65969,384,"CIV","CIte dIvoire","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
65970,384,"CIV","CIte dIvoire","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
65971,384,"CIV","CIte dIvoire","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
65972,384,"CIV","CIte dIvoire","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
65973,384,"CIV","CIte dIvoire","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
65974,384,"CIV","CIte dIvoire","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
65975,384,"CIV","CIte dIvoire","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
65976,384,"CIV","CIte dIvoire","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
65977,384,"CIV","CIte dIvoire","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CIV/civ_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
65978,388,"JAM","Jamaica","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
65979,388,"JAM","Jamaica","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
65980,388,"JAM","Jamaica","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
65981,388,"JAM","Jamaica","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
65982,388,"JAM","Jamaica","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
65983,388,"JAM","Jamaica","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
65984,388,"JAM","Jamaica","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
65985,388,"JAM","Jamaica","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
65986,388,"JAM","Jamaica","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
65987,388,"JAM","Jamaica","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
65988,388,"JAM","Jamaica","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
65989,388,"JAM","Jamaica","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
65990,388,"JAM","Jamaica","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
65991,388,"JAM","Jamaica","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
65992,388,"JAM","Jamaica","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
65993,388,"JAM","Jamaica","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
65994,388,"JAM","Jamaica","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
65995,388,"JAM","Jamaica","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
65996,388,"JAM","Jamaica","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
65997,388,"JAM","Jamaica","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
65998,388,"JAM","Jamaica","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
65999,388,"JAM","Jamaica","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66000,388,"JAM","Jamaica","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66001,388,"JAM","Jamaica","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66002,388,"JAM","Jamaica","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66003,388,"JAM","Jamaica","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66004,388,"JAM","Jamaica","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66005,388,"JAM","Jamaica","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66006,388,"JAM","Jamaica","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66007,388,"JAM","Jamaica","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66008,388,"JAM","Jamaica","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66009,388,"JAM","Jamaica","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66010,388,"JAM","Jamaica","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66011,388,"JAM","Jamaica","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66012,388,"JAM","Jamaica","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66013,388,"JAM","Jamaica","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JAM/jam_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66014,392,"JPN","Japan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66015,392,"JPN","Japan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66016,392,"JPN","Japan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66017,392,"JPN","Japan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66018,392,"JPN","Japan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66019,392,"JPN","Japan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66020,392,"JPN","Japan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66021,392,"JPN","Japan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66022,392,"JPN","Japan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66023,392,"JPN","Japan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66024,392,"JPN","Japan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66025,392,"JPN","Japan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66026,392,"JPN","Japan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66027,392,"JPN","Japan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66028,392,"JPN","Japan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66029,392,"JPN","Japan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66030,392,"JPN","Japan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66031,392,"JPN","Japan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66032,392,"JPN","Japan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66033,392,"JPN","Japan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66034,392,"JPN","Japan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66035,392,"JPN","Japan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66036,392,"JPN","Japan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66037,392,"JPN","Japan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66038,392,"JPN","Japan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66039,392,"JPN","Japan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66040,392,"JPN","Japan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66041,392,"JPN","Japan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66042,392,"JPN","Japan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66043,392,"JPN","Japan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66044,392,"JPN","Japan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66045,392,"JPN","Japan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66046,392,"JPN","Japan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66047,392,"JPN","Japan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66048,392,"JPN","Japan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66049,392,"JPN","Japan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JPN/jpn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66050,398,"KAZ","Kazakhstan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66051,398,"KAZ","Kazakhstan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66052,398,"KAZ","Kazakhstan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66053,398,"KAZ","Kazakhstan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66054,398,"KAZ","Kazakhstan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66055,398,"KAZ","Kazakhstan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66056,398,"KAZ","Kazakhstan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66057,398,"KAZ","Kazakhstan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66058,398,"KAZ","Kazakhstan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66059,398,"KAZ","Kazakhstan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66060,398,"KAZ","Kazakhstan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66061,398,"KAZ","Kazakhstan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66062,398,"KAZ","Kazakhstan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66063,398,"KAZ","Kazakhstan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66064,398,"KAZ","Kazakhstan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66065,398,"KAZ","Kazakhstan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66066,398,"KAZ","Kazakhstan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66067,398,"KAZ","Kazakhstan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66068,398,"KAZ","Kazakhstan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66069,398,"KAZ","Kazakhstan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66070,398,"KAZ","Kazakhstan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66071,398,"KAZ","Kazakhstan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66072,398,"KAZ","Kazakhstan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66073,398,"KAZ","Kazakhstan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66074,398,"KAZ","Kazakhstan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66075,398,"KAZ","Kazakhstan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66076,398,"KAZ","Kazakhstan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66077,398,"KAZ","Kazakhstan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66078,398,"KAZ","Kazakhstan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66079,398,"KAZ","Kazakhstan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66080,398,"KAZ","Kazakhstan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66081,398,"KAZ","Kazakhstan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66082,398,"KAZ","Kazakhstan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66083,398,"KAZ","Kazakhstan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66084,398,"KAZ","Kazakhstan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66085,398,"KAZ","Kazakhstan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KAZ/kaz_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66086,400,"JOR","Jordan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66087,400,"JOR","Jordan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66088,400,"JOR","Jordan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66089,400,"JOR","Jordan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66090,400,"JOR","Jordan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66091,400,"JOR","Jordan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66092,400,"JOR","Jordan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66093,400,"JOR","Jordan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66094,400,"JOR","Jordan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66095,400,"JOR","Jordan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66096,400,"JOR","Jordan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66097,400,"JOR","Jordan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66098,400,"JOR","Jordan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66099,400,"JOR","Jordan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66100,400,"JOR","Jordan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66101,400,"JOR","Jordan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66102,400,"JOR","Jordan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66103,400,"JOR","Jordan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66104,400,"JOR","Jordan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66105,400,"JOR","Jordan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66106,400,"JOR","Jordan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66107,400,"JOR","Jordan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66108,400,"JOR","Jordan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66109,400,"JOR","Jordan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66110,400,"JOR","Jordan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66111,400,"JOR","Jordan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66112,400,"JOR","Jordan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66113,400,"JOR","Jordan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66114,400,"JOR","Jordan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66115,400,"JOR","Jordan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66116,400,"JOR","Jordan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66117,400,"JOR","Jordan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66118,400,"JOR","Jordan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66119,400,"JOR","Jordan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66120,400,"JOR","Jordan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66121,400,"JOR","Jordan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JOR/jor_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66122,404,"KEN","Kenya","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66123,404,"KEN","Kenya","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66124,404,"KEN","Kenya","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66125,404,"KEN","Kenya","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66126,404,"KEN","Kenya","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66127,404,"KEN","Kenya","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66128,404,"KEN","Kenya","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66129,404,"KEN","Kenya","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66130,404,"KEN","Kenya","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66131,404,"KEN","Kenya","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66132,404,"KEN","Kenya","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66133,404,"KEN","Kenya","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66134,404,"KEN","Kenya","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66135,404,"KEN","Kenya","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66136,404,"KEN","Kenya","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66137,404,"KEN","Kenya","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66138,404,"KEN","Kenya","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66139,404,"KEN","Kenya","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66140,404,"KEN","Kenya","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66141,404,"KEN","Kenya","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66142,404,"KEN","Kenya","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66143,404,"KEN","Kenya","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66144,404,"KEN","Kenya","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66145,404,"KEN","Kenya","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66146,404,"KEN","Kenya","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66147,404,"KEN","Kenya","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66148,404,"KEN","Kenya","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66149,404,"KEN","Kenya","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66150,404,"KEN","Kenya","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66151,404,"KEN","Kenya","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66152,404,"KEN","Kenya","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66153,404,"KEN","Kenya","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66154,404,"KEN","Kenya","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66155,404,"KEN","Kenya","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66156,404,"KEN","Kenya","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66157,404,"KEN","Kenya","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KEN/ken_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66158,408,"PRK","North Korea","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66159,408,"PRK","North Korea","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66160,408,"PRK","North Korea","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66161,408,"PRK","North Korea","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66162,408,"PRK","North Korea","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66163,408,"PRK","North Korea","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66164,408,"PRK","North Korea","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66165,408,"PRK","North Korea","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66166,408,"PRK","North Korea","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66167,408,"PRK","North Korea","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66168,408,"PRK","North Korea","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66169,408,"PRK","North Korea","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66170,408,"PRK","North Korea","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66171,408,"PRK","North Korea","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66172,408,"PRK","North Korea","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66173,408,"PRK","North Korea","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66174,408,"PRK","North Korea","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66175,408,"PRK","North Korea","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66176,408,"PRK","North Korea","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66177,408,"PRK","North Korea","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66178,408,"PRK","North Korea","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66179,408,"PRK","North Korea","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66180,408,"PRK","North Korea","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66181,408,"PRK","North Korea","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66182,408,"PRK","North Korea","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66183,408,"PRK","North Korea","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66184,408,"PRK","North Korea","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66185,408,"PRK","North Korea","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66186,408,"PRK","North Korea","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66187,408,"PRK","North Korea","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66188,408,"PRK","North Korea","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66189,408,"PRK","North Korea","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66190,408,"PRK","North Korea","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66191,408,"PRK","North Korea","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66192,408,"PRK","North Korea","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66193,408,"PRK","North Korea","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRK/prk_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66194,410,"KOR","South Korea","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66195,410,"KOR","South Korea","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66196,410,"KOR","South Korea","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66197,410,"KOR","South Korea","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66198,410,"KOR","South Korea","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66199,410,"KOR","South Korea","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66200,410,"KOR","South Korea","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66201,410,"KOR","South Korea","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66202,410,"KOR","South Korea","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66203,410,"KOR","South Korea","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66204,410,"KOR","South Korea","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66205,410,"KOR","South Korea","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66206,410,"KOR","South Korea","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66207,410,"KOR","South Korea","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66208,410,"KOR","South Korea","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66209,410,"KOR","South Korea","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66210,410,"KOR","South Korea","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66211,410,"KOR","South Korea","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66212,410,"KOR","South Korea","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66213,410,"KOR","South Korea","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66214,410,"KOR","South Korea","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66215,410,"KOR","South Korea","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66216,410,"KOR","South Korea","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66217,410,"KOR","South Korea","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66218,410,"KOR","South Korea","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66219,410,"KOR","South Korea","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66220,410,"KOR","South Korea","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66221,410,"KOR","South Korea","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66222,410,"KOR","South Korea","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66223,410,"KOR","South Korea","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66224,410,"KOR","South Korea","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66225,410,"KOR","South Korea","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66226,410,"KOR","South Korea","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66227,410,"KOR","South Korea","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66228,410,"KOR","South Korea","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66229,410,"KOR","South Korea","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOR/kor_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66230,414,"KWT","Kuwait","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66231,414,"KWT","Kuwait","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66232,414,"KWT","Kuwait","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66233,414,"KWT","Kuwait","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66234,414,"KWT","Kuwait","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66235,414,"KWT","Kuwait","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66236,414,"KWT","Kuwait","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66237,414,"KWT","Kuwait","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66238,414,"KWT","Kuwait","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66239,414,"KWT","Kuwait","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66240,414,"KWT","Kuwait","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66241,414,"KWT","Kuwait","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66242,414,"KWT","Kuwait","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66243,414,"KWT","Kuwait","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66244,414,"KWT","Kuwait","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66245,414,"KWT","Kuwait","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66246,414,"KWT","Kuwait","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66247,414,"KWT","Kuwait","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66248,414,"KWT","Kuwait","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66249,414,"KWT","Kuwait","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66250,414,"KWT","Kuwait","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66251,414,"KWT","Kuwait","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66252,414,"KWT","Kuwait","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66253,414,"KWT","Kuwait","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66254,414,"KWT","Kuwait","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66255,414,"KWT","Kuwait","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66256,414,"KWT","Kuwait","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66257,414,"KWT","Kuwait","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66258,414,"KWT","Kuwait","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66259,414,"KWT","Kuwait","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66260,414,"KWT","Kuwait","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66261,414,"KWT","Kuwait","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66262,414,"KWT","Kuwait","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66263,414,"KWT","Kuwait","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66264,414,"KWT","Kuwait","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66265,414,"KWT","Kuwait","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KWT/kwt_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66266,417,"KGZ","Kyrgyzstan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66267,417,"KGZ","Kyrgyzstan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66268,417,"KGZ","Kyrgyzstan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66269,417,"KGZ","Kyrgyzstan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66270,417,"KGZ","Kyrgyzstan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66271,417,"KGZ","Kyrgyzstan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66272,417,"KGZ","Kyrgyzstan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66273,417,"KGZ","Kyrgyzstan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66274,417,"KGZ","Kyrgyzstan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66275,417,"KGZ","Kyrgyzstan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66276,417,"KGZ","Kyrgyzstan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66277,417,"KGZ","Kyrgyzstan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66278,417,"KGZ","Kyrgyzstan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66279,417,"KGZ","Kyrgyzstan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66280,417,"KGZ","Kyrgyzstan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66281,417,"KGZ","Kyrgyzstan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66282,417,"KGZ","Kyrgyzstan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66283,417,"KGZ","Kyrgyzstan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66284,417,"KGZ","Kyrgyzstan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66285,417,"KGZ","Kyrgyzstan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66286,417,"KGZ","Kyrgyzstan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66287,417,"KGZ","Kyrgyzstan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66288,417,"KGZ","Kyrgyzstan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66289,417,"KGZ","Kyrgyzstan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66290,417,"KGZ","Kyrgyzstan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66291,417,"KGZ","Kyrgyzstan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66292,417,"KGZ","Kyrgyzstan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66293,417,"KGZ","Kyrgyzstan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66294,417,"KGZ","Kyrgyzstan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66295,417,"KGZ","Kyrgyzstan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66296,417,"KGZ","Kyrgyzstan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66297,417,"KGZ","Kyrgyzstan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66298,417,"KGZ","Kyrgyzstan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66299,417,"KGZ","Kyrgyzstan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66300,417,"KGZ","Kyrgyzstan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66301,417,"KGZ","Kyrgyzstan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KGZ/kgz_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66302,418,"LAO","Laos","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66303,418,"LAO","Laos","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66304,418,"LAO","Laos","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66305,418,"LAO","Laos","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66306,418,"LAO","Laos","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66307,418,"LAO","Laos","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66308,418,"LAO","Laos","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66309,418,"LAO","Laos","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66310,418,"LAO","Laos","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66311,418,"LAO","Laos","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66312,418,"LAO","Laos","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66313,418,"LAO","Laos","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66314,418,"LAO","Laos","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66315,418,"LAO","Laos","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66316,418,"LAO","Laos","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66317,418,"LAO","Laos","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66318,418,"LAO","Laos","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66319,418,"LAO","Laos","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66320,418,"LAO","Laos","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66321,418,"LAO","Laos","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66322,418,"LAO","Laos","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66323,418,"LAO","Laos","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66324,418,"LAO","Laos","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66325,418,"LAO","Laos","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66326,418,"LAO","Laos","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66327,418,"LAO","Laos","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66328,418,"LAO","Laos","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66329,418,"LAO","Laos","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66330,418,"LAO","Laos","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66331,418,"LAO","Laos","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66332,418,"LAO","Laos","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66333,418,"LAO","Laos","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66334,418,"LAO","Laos","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66335,418,"LAO","Laos","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66336,418,"LAO","Laos","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66337,418,"LAO","Laos","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LAO/lao_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66338,422,"LBN","Lebanon","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66339,422,"LBN","Lebanon","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66340,422,"LBN","Lebanon","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66341,422,"LBN","Lebanon","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66342,422,"LBN","Lebanon","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66343,422,"LBN","Lebanon","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66344,422,"LBN","Lebanon","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66345,422,"LBN","Lebanon","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66346,422,"LBN","Lebanon","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66347,422,"LBN","Lebanon","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66348,422,"LBN","Lebanon","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66349,422,"LBN","Lebanon","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66350,422,"LBN","Lebanon","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66351,422,"LBN","Lebanon","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66352,422,"LBN","Lebanon","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66353,422,"LBN","Lebanon","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66354,422,"LBN","Lebanon","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66355,422,"LBN","Lebanon","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66356,422,"LBN","Lebanon","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66357,422,"LBN","Lebanon","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66358,422,"LBN","Lebanon","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66359,422,"LBN","Lebanon","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66360,422,"LBN","Lebanon","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66361,422,"LBN","Lebanon","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66362,422,"LBN","Lebanon","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66363,422,"LBN","Lebanon","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66364,422,"LBN","Lebanon","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66365,422,"LBN","Lebanon","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66366,422,"LBN","Lebanon","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66367,422,"LBN","Lebanon","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66368,422,"LBN","Lebanon","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66369,422,"LBN","Lebanon","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66370,422,"LBN","Lebanon","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66371,422,"LBN","Lebanon","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66372,422,"LBN","Lebanon","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66373,422,"LBN","Lebanon","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBN/lbn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66374,426,"LSO","Lesotho","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66375,426,"LSO","Lesotho","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66376,426,"LSO","Lesotho","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66377,426,"LSO","Lesotho","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66378,426,"LSO","Lesotho","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66379,426,"LSO","Lesotho","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66380,426,"LSO","Lesotho","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66381,426,"LSO","Lesotho","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66382,426,"LSO","Lesotho","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66383,426,"LSO","Lesotho","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66384,426,"LSO","Lesotho","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66385,426,"LSO","Lesotho","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66386,426,"LSO","Lesotho","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66387,426,"LSO","Lesotho","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66388,426,"LSO","Lesotho","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66389,426,"LSO","Lesotho","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66390,426,"LSO","Lesotho","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66391,426,"LSO","Lesotho","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66392,426,"LSO","Lesotho","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66393,426,"LSO","Lesotho","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66394,426,"LSO","Lesotho","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66395,426,"LSO","Lesotho","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66396,426,"LSO","Lesotho","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66397,426,"LSO","Lesotho","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66398,426,"LSO","Lesotho","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66399,426,"LSO","Lesotho","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66400,426,"LSO","Lesotho","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66401,426,"LSO","Lesotho","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66402,426,"LSO","Lesotho","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66403,426,"LSO","Lesotho","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66404,426,"LSO","Lesotho","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66405,426,"LSO","Lesotho","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66406,426,"LSO","Lesotho","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66407,426,"LSO","Lesotho","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66408,426,"LSO","Lesotho","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66409,426,"LSO","Lesotho","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LSO/lso_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66410,428,"LVA","Latvia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66411,428,"LVA","Latvia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66412,428,"LVA","Latvia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66413,428,"LVA","Latvia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66414,428,"LVA","Latvia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66415,428,"LVA","Latvia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66416,428,"LVA","Latvia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66417,428,"LVA","Latvia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66418,428,"LVA","Latvia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66419,428,"LVA","Latvia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66420,428,"LVA","Latvia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66421,428,"LVA","Latvia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66422,428,"LVA","Latvia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66423,428,"LVA","Latvia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66424,428,"LVA","Latvia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66425,428,"LVA","Latvia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66426,428,"LVA","Latvia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66427,428,"LVA","Latvia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66428,428,"LVA","Latvia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66429,428,"LVA","Latvia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66430,428,"LVA","Latvia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66431,428,"LVA","Latvia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66432,428,"LVA","Latvia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66433,428,"LVA","Latvia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66434,428,"LVA","Latvia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66435,428,"LVA","Latvia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66436,428,"LVA","Latvia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66437,428,"LVA","Latvia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66438,428,"LVA","Latvia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66439,428,"LVA","Latvia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66440,428,"LVA","Latvia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66441,428,"LVA","Latvia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66442,428,"LVA","Latvia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66443,428,"LVA","Latvia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66444,428,"LVA","Latvia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66445,428,"LVA","Latvia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LVA/lva_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66446,430,"LBR","Liberia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66447,430,"LBR","Liberia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66448,430,"LBR","Liberia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66449,430,"LBR","Liberia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66450,430,"LBR","Liberia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66451,430,"LBR","Liberia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66452,430,"LBR","Liberia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66453,430,"LBR","Liberia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66454,430,"LBR","Liberia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66455,430,"LBR","Liberia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66456,430,"LBR","Liberia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66457,430,"LBR","Liberia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66458,430,"LBR","Liberia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66459,430,"LBR","Liberia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66460,430,"LBR","Liberia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66461,430,"LBR","Liberia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66462,430,"LBR","Liberia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66463,430,"LBR","Liberia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66464,430,"LBR","Liberia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66465,430,"LBR","Liberia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66466,430,"LBR","Liberia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66467,430,"LBR","Liberia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66468,430,"LBR","Liberia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66469,430,"LBR","Liberia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66470,430,"LBR","Liberia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66471,430,"LBR","Liberia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66472,430,"LBR","Liberia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66473,430,"LBR","Liberia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66474,430,"LBR","Liberia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66475,430,"LBR","Liberia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66476,430,"LBR","Liberia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66477,430,"LBR","Liberia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66478,430,"LBR","Liberia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66479,430,"LBR","Liberia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66480,430,"LBR","Liberia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66481,430,"LBR","Liberia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBR/lbr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66482,434,"LBY","Libya","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66483,434,"LBY","Libya","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66484,434,"LBY","Libya","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66485,434,"LBY","Libya","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66486,434,"LBY","Libya","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66487,434,"LBY","Libya","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66488,434,"LBY","Libya","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66489,434,"LBY","Libya","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66490,434,"LBY","Libya","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66491,434,"LBY","Libya","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66492,434,"LBY","Libya","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66493,434,"LBY","Libya","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66494,434,"LBY","Libya","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66495,434,"LBY","Libya","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66496,434,"LBY","Libya","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66497,434,"LBY","Libya","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66498,434,"LBY","Libya","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66499,434,"LBY","Libya","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66500,434,"LBY","Libya","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66501,434,"LBY","Libya","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66502,434,"LBY","Libya","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66503,434,"LBY","Libya","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66504,434,"LBY","Libya","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66505,434,"LBY","Libya","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66506,434,"LBY","Libya","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66507,434,"LBY","Libya","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66508,434,"LBY","Libya","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66509,434,"LBY","Libya","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66510,434,"LBY","Libya","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66511,434,"LBY","Libya","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66512,434,"LBY","Libya","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66513,434,"LBY","Libya","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66514,434,"LBY","Libya","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66515,434,"LBY","Libya","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66516,434,"LBY","Libya","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66517,434,"LBY","Libya","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LBY/lby_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66518,438,"LIE","Liechtenstein","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66519,438,"LIE","Liechtenstein","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66520,438,"LIE","Liechtenstein","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66521,438,"LIE","Liechtenstein","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66522,438,"LIE","Liechtenstein","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66523,438,"LIE","Liechtenstein","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66524,438,"LIE","Liechtenstein","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66525,438,"LIE","Liechtenstein","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66526,438,"LIE","Liechtenstein","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66527,438,"LIE","Liechtenstein","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66528,438,"LIE","Liechtenstein","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66529,438,"LIE","Liechtenstein","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66530,438,"LIE","Liechtenstein","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66531,438,"LIE","Liechtenstein","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66532,438,"LIE","Liechtenstein","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66533,438,"LIE","Liechtenstein","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66534,438,"LIE","Liechtenstein","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66535,438,"LIE","Liechtenstein","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66536,438,"LIE","Liechtenstein","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66537,438,"LIE","Liechtenstein","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66538,438,"LIE","Liechtenstein","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66539,438,"LIE","Liechtenstein","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66540,438,"LIE","Liechtenstein","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66541,438,"LIE","Liechtenstein","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66542,438,"LIE","Liechtenstein","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66543,438,"LIE","Liechtenstein","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66544,438,"LIE","Liechtenstein","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66545,438,"LIE","Liechtenstein","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66546,438,"LIE","Liechtenstein","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66547,438,"LIE","Liechtenstein","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66548,438,"LIE","Liechtenstein","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66549,438,"LIE","Liechtenstein","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66550,438,"LIE","Liechtenstein","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66551,438,"LIE","Liechtenstein","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66552,438,"LIE","Liechtenstein","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66553,438,"LIE","Liechtenstein","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LIE/lie_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66554,440,"LTU","Lithuania","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66555,440,"LTU","Lithuania","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66556,440,"LTU","Lithuania","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66557,440,"LTU","Lithuania","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66558,440,"LTU","Lithuania","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66559,440,"LTU","Lithuania","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66560,440,"LTU","Lithuania","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66561,440,"LTU","Lithuania","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66562,440,"LTU","Lithuania","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66563,440,"LTU","Lithuania","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66564,440,"LTU","Lithuania","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66565,440,"LTU","Lithuania","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66566,440,"LTU","Lithuania","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66567,440,"LTU","Lithuania","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66568,440,"LTU","Lithuania","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66569,440,"LTU","Lithuania","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66570,440,"LTU","Lithuania","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66571,440,"LTU","Lithuania","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66572,440,"LTU","Lithuania","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66573,440,"LTU","Lithuania","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66574,440,"LTU","Lithuania","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66575,440,"LTU","Lithuania","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66576,440,"LTU","Lithuania","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66577,440,"LTU","Lithuania","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66578,440,"LTU","Lithuania","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66579,440,"LTU","Lithuania","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66580,440,"LTU","Lithuania","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66581,440,"LTU","Lithuania","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66582,440,"LTU","Lithuania","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66583,440,"LTU","Lithuania","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66584,440,"LTU","Lithuania","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66585,440,"LTU","Lithuania","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66586,440,"LTU","Lithuania","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66587,440,"LTU","Lithuania","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66588,440,"LTU","Lithuania","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66589,440,"LTU","Lithuania","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LTU/ltu_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66590,442,"LUX","Luxembourg","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66591,442,"LUX","Luxembourg","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66592,442,"LUX","Luxembourg","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66593,442,"LUX","Luxembourg","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66594,442,"LUX","Luxembourg","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66595,442,"LUX","Luxembourg","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66596,442,"LUX","Luxembourg","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66597,442,"LUX","Luxembourg","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66598,442,"LUX","Luxembourg","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66599,442,"LUX","Luxembourg","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66600,442,"LUX","Luxembourg","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66601,442,"LUX","Luxembourg","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66602,442,"LUX","Luxembourg","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66603,442,"LUX","Luxembourg","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66604,442,"LUX","Luxembourg","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66605,442,"LUX","Luxembourg","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66606,442,"LUX","Luxembourg","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66607,442,"LUX","Luxembourg","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66608,442,"LUX","Luxembourg","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66609,442,"LUX","Luxembourg","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66610,442,"LUX","Luxembourg","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66611,442,"LUX","Luxembourg","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66612,442,"LUX","Luxembourg","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66613,442,"LUX","Luxembourg","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66614,442,"LUX","Luxembourg","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66615,442,"LUX","Luxembourg","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66616,442,"LUX","Luxembourg","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66617,442,"LUX","Luxembourg","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66618,442,"LUX","Luxembourg","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66619,442,"LUX","Luxembourg","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66620,442,"LUX","Luxembourg","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66621,442,"LUX","Luxembourg","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66622,442,"LUX","Luxembourg","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66623,442,"LUX","Luxembourg","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66624,442,"LUX","Luxembourg","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66625,442,"LUX","Luxembourg","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LUX/lux_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66626,446,"MAC","Macao","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66627,446,"MAC","Macao","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66628,446,"MAC","Macao","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66629,446,"MAC","Macao","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66630,446,"MAC","Macao","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66631,446,"MAC","Macao","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66632,446,"MAC","Macao","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66633,446,"MAC","Macao","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66634,446,"MAC","Macao","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66635,446,"MAC","Macao","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66636,446,"MAC","Macao","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66637,446,"MAC","Macao","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66638,446,"MAC","Macao","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66639,446,"MAC","Macao","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66640,446,"MAC","Macao","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66641,446,"MAC","Macao","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66642,446,"MAC","Macao","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66643,446,"MAC","Macao","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66644,446,"MAC","Macao","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66645,446,"MAC","Macao","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66646,446,"MAC","Macao","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66647,446,"MAC","Macao","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66648,446,"MAC","Macao","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66649,446,"MAC","Macao","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66650,446,"MAC","Macao","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66651,446,"MAC","Macao","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66652,446,"MAC","Macao","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66653,446,"MAC","Macao","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66654,446,"MAC","Macao","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66655,446,"MAC","Macao","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66656,446,"MAC","Macao","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66657,446,"MAC","Macao","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66658,446,"MAC","Macao","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66659,446,"MAC","Macao","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66660,446,"MAC","Macao","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66661,446,"MAC","Macao","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAC/mac_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66662,450,"MDG","Madagascar","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66663,450,"MDG","Madagascar","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66664,450,"MDG","Madagascar","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66665,450,"MDG","Madagascar","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66666,450,"MDG","Madagascar","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66667,450,"MDG","Madagascar","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66668,450,"MDG","Madagascar","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66669,450,"MDG","Madagascar","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66670,450,"MDG","Madagascar","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66671,450,"MDG","Madagascar","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66672,450,"MDG","Madagascar","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66673,450,"MDG","Madagascar","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66674,450,"MDG","Madagascar","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66675,450,"MDG","Madagascar","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66676,450,"MDG","Madagascar","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66677,450,"MDG","Madagascar","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66678,450,"MDG","Madagascar","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66679,450,"MDG","Madagascar","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66680,450,"MDG","Madagascar","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66681,450,"MDG","Madagascar","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66682,450,"MDG","Madagascar","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66683,450,"MDG","Madagascar","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66684,450,"MDG","Madagascar","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66685,450,"MDG","Madagascar","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66686,450,"MDG","Madagascar","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66687,450,"MDG","Madagascar","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66688,450,"MDG","Madagascar","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66689,450,"MDG","Madagascar","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66690,450,"MDG","Madagascar","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66691,450,"MDG","Madagascar","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66692,450,"MDG","Madagascar","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66693,450,"MDG","Madagascar","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66694,450,"MDG","Madagascar","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66695,450,"MDG","Madagascar","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66696,450,"MDG","Madagascar","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66697,450,"MDG","Madagascar","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDG/mdg_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66698,454,"MWI","Malawi","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66699,454,"MWI","Malawi","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66700,454,"MWI","Malawi","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66701,454,"MWI","Malawi","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66702,454,"MWI","Malawi","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66703,454,"MWI","Malawi","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66704,454,"MWI","Malawi","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66705,454,"MWI","Malawi","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66706,454,"MWI","Malawi","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66707,454,"MWI","Malawi","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66708,454,"MWI","Malawi","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66709,454,"MWI","Malawi","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66710,454,"MWI","Malawi","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66711,454,"MWI","Malawi","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66712,454,"MWI","Malawi","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66713,454,"MWI","Malawi","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66714,454,"MWI","Malawi","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66715,454,"MWI","Malawi","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66716,454,"MWI","Malawi","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66717,454,"MWI","Malawi","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66718,454,"MWI","Malawi","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66719,454,"MWI","Malawi","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66720,454,"MWI","Malawi","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66721,454,"MWI","Malawi","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66722,454,"MWI","Malawi","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66723,454,"MWI","Malawi","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66724,454,"MWI","Malawi","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66725,454,"MWI","Malawi","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66726,454,"MWI","Malawi","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66727,454,"MWI","Malawi","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66728,454,"MWI","Malawi","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66729,454,"MWI","Malawi","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66730,454,"MWI","Malawi","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66731,454,"MWI","Malawi","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66732,454,"MWI","Malawi","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66733,454,"MWI","Malawi","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MWI/mwi_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66734,458,"MYS","Malaysia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66735,458,"MYS","Malaysia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66736,458,"MYS","Malaysia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66737,458,"MYS","Malaysia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66738,458,"MYS","Malaysia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66739,458,"MYS","Malaysia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66740,458,"MYS","Malaysia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66741,458,"MYS","Malaysia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66742,458,"MYS","Malaysia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66743,458,"MYS","Malaysia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66744,458,"MYS","Malaysia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66745,458,"MYS","Malaysia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66746,458,"MYS","Malaysia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66747,458,"MYS","Malaysia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66748,458,"MYS","Malaysia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66749,458,"MYS","Malaysia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66750,458,"MYS","Malaysia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66751,458,"MYS","Malaysia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66752,458,"MYS","Malaysia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66753,458,"MYS","Malaysia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66754,458,"MYS","Malaysia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66755,458,"MYS","Malaysia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66756,458,"MYS","Malaysia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66757,458,"MYS","Malaysia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66758,458,"MYS","Malaysia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66759,458,"MYS","Malaysia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66760,458,"MYS","Malaysia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66761,458,"MYS","Malaysia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66762,458,"MYS","Malaysia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66763,458,"MYS","Malaysia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66764,458,"MYS","Malaysia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66765,458,"MYS","Malaysia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66766,458,"MYS","Malaysia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66767,458,"MYS","Malaysia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66768,458,"MYS","Malaysia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66769,458,"MYS","Malaysia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MYS/mys_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66770,462,"MDV","Maldives","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66771,462,"MDV","Maldives","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66772,462,"MDV","Maldives","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66773,462,"MDV","Maldives","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66774,462,"MDV","Maldives","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66775,462,"MDV","Maldives","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66776,462,"MDV","Maldives","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66777,462,"MDV","Maldives","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66778,462,"MDV","Maldives","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66779,462,"MDV","Maldives","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66780,462,"MDV","Maldives","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66781,462,"MDV","Maldives","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66782,462,"MDV","Maldives","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66783,462,"MDV","Maldives","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66784,462,"MDV","Maldives","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66785,462,"MDV","Maldives","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66786,462,"MDV","Maldives","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66787,462,"MDV","Maldives","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66788,462,"MDV","Maldives","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66789,462,"MDV","Maldives","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66790,462,"MDV","Maldives","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66791,462,"MDV","Maldives","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66792,462,"MDV","Maldives","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66793,462,"MDV","Maldives","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66794,462,"MDV","Maldives","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66795,462,"MDV","Maldives","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66796,462,"MDV","Maldives","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66797,462,"MDV","Maldives","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66798,462,"MDV","Maldives","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66799,462,"MDV","Maldives","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66800,462,"MDV","Maldives","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66801,462,"MDV","Maldives","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66802,462,"MDV","Maldives","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66803,462,"MDV","Maldives","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66804,462,"MDV","Maldives","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66805,462,"MDV","Maldives","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDV/mdv_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66806,466,"MLI","Mali","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66807,466,"MLI","Mali","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66808,466,"MLI","Mali","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66809,466,"MLI","Mali","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66810,466,"MLI","Mali","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66811,466,"MLI","Mali","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66812,466,"MLI","Mali","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66813,466,"MLI","Mali","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66814,466,"MLI","Mali","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66815,466,"MLI","Mali","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66816,466,"MLI","Mali","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66817,466,"MLI","Mali","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66818,466,"MLI","Mali","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66819,466,"MLI","Mali","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66820,466,"MLI","Mali","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66821,466,"MLI","Mali","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66822,466,"MLI","Mali","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66823,466,"MLI","Mali","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66824,466,"MLI","Mali","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66825,466,"MLI","Mali","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66826,466,"MLI","Mali","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66827,466,"MLI","Mali","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66828,466,"MLI","Mali","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66829,466,"MLI","Mali","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66830,466,"MLI","Mali","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66831,466,"MLI","Mali","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66832,466,"MLI","Mali","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66833,466,"MLI","Mali","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66834,466,"MLI","Mali","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66835,466,"MLI","Mali","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66836,466,"MLI","Mali","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66837,466,"MLI","Mali","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66838,466,"MLI","Mali","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66839,466,"MLI","Mali","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66840,466,"MLI","Mali","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66841,466,"MLI","Mali","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLI/mli_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66842,470,"MLT","Malta","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66843,470,"MLT","Malta","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66844,470,"MLT","Malta","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66845,470,"MLT","Malta","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66846,470,"MLT","Malta","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66847,470,"MLT","Malta","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66848,470,"MLT","Malta","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66849,470,"MLT","Malta","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66850,470,"MLT","Malta","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66851,470,"MLT","Malta","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66852,470,"MLT","Malta","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66853,470,"MLT","Malta","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66854,470,"MLT","Malta","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66855,470,"MLT","Malta","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66856,470,"MLT","Malta","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66857,470,"MLT","Malta","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66858,470,"MLT","Malta","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66859,470,"MLT","Malta","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66860,470,"MLT","Malta","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66861,470,"MLT","Malta","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66862,470,"MLT","Malta","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66863,470,"MLT","Malta","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66864,470,"MLT","Malta","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66865,470,"MLT","Malta","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66866,470,"MLT","Malta","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66867,470,"MLT","Malta","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66868,470,"MLT","Malta","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66869,470,"MLT","Malta","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66870,470,"MLT","Malta","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66871,470,"MLT","Malta","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66872,470,"MLT","Malta","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66873,470,"MLT","Malta","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66874,470,"MLT","Malta","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66875,470,"MLT","Malta","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66876,470,"MLT","Malta","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66877,470,"MLT","Malta","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MLT/mlt_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66878,474,"MTQ","Martinique","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66879,474,"MTQ","Martinique","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66880,474,"MTQ","Martinique","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66881,474,"MTQ","Martinique","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66882,474,"MTQ","Martinique","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66883,474,"MTQ","Martinique","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66884,474,"MTQ","Martinique","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66885,474,"MTQ","Martinique","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66886,474,"MTQ","Martinique","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66887,474,"MTQ","Martinique","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66888,474,"MTQ","Martinique","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66889,474,"MTQ","Martinique","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66890,474,"MTQ","Martinique","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66891,474,"MTQ","Martinique","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66892,474,"MTQ","Martinique","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66893,474,"MTQ","Martinique","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66894,474,"MTQ","Martinique","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66895,474,"MTQ","Martinique","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66896,474,"MTQ","Martinique","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66897,474,"MTQ","Martinique","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66898,474,"MTQ","Martinique","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66899,474,"MTQ","Martinique","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66900,474,"MTQ","Martinique","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66901,474,"MTQ","Martinique","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66902,474,"MTQ","Martinique","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66903,474,"MTQ","Martinique","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66904,474,"MTQ","Martinique","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66905,474,"MTQ","Martinique","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66906,474,"MTQ","Martinique","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66907,474,"MTQ","Martinique","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66908,474,"MTQ","Martinique","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66909,474,"MTQ","Martinique","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66910,474,"MTQ","Martinique","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66911,474,"MTQ","Martinique","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66912,474,"MTQ","Martinique","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66913,474,"MTQ","Martinique","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MTQ/mtq_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66914,478,"MRT","Mauritania","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66915,478,"MRT","Mauritania","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66916,478,"MRT","Mauritania","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66917,478,"MRT","Mauritania","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66918,478,"MRT","Mauritania","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66919,478,"MRT","Mauritania","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66920,478,"MRT","Mauritania","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66921,478,"MRT","Mauritania","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66922,478,"MRT","Mauritania","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66923,478,"MRT","Mauritania","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66924,478,"MRT","Mauritania","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66925,478,"MRT","Mauritania","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66926,478,"MRT","Mauritania","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66927,478,"MRT","Mauritania","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66928,478,"MRT","Mauritania","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66929,478,"MRT","Mauritania","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66930,478,"MRT","Mauritania","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66931,478,"MRT","Mauritania","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66932,478,"MRT","Mauritania","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66933,478,"MRT","Mauritania","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66934,478,"MRT","Mauritania","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66935,478,"MRT","Mauritania","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66936,478,"MRT","Mauritania","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66937,478,"MRT","Mauritania","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66938,478,"MRT","Mauritania","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66939,478,"MRT","Mauritania","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66940,478,"MRT","Mauritania","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66941,478,"MRT","Mauritania","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66942,478,"MRT","Mauritania","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66943,478,"MRT","Mauritania","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66944,478,"MRT","Mauritania","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66945,478,"MRT","Mauritania","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66946,478,"MRT","Mauritania","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66947,478,"MRT","Mauritania","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66948,478,"MRT","Mauritania","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66949,478,"MRT","Mauritania","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MRT/mrt_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66950,480,"MUS","Mauritius","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66951,480,"MUS","Mauritius","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66952,480,"MUS","Mauritius","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66953,480,"MUS","Mauritius","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66954,480,"MUS","Mauritius","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66955,480,"MUS","Mauritius","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66956,480,"MUS","Mauritius","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66957,480,"MUS","Mauritius","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66958,480,"MUS","Mauritius","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66959,480,"MUS","Mauritius","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66960,480,"MUS","Mauritius","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66961,480,"MUS","Mauritius","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66962,480,"MUS","Mauritius","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66963,480,"MUS","Mauritius","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
66964,480,"MUS","Mauritius","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
66965,480,"MUS","Mauritius","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
66966,480,"MUS","Mauritius","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
66967,480,"MUS","Mauritius","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
66968,480,"MUS","Mauritius","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
66969,480,"MUS","Mauritius","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
66970,480,"MUS","Mauritius","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
66971,480,"MUS","Mauritius","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
66972,480,"MUS","Mauritius","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
66973,480,"MUS","Mauritius","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
66974,480,"MUS","Mauritius","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
66975,480,"MUS","Mauritius","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
66976,480,"MUS","Mauritius","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
66977,480,"MUS","Mauritius","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
66978,480,"MUS","Mauritius","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
66979,480,"MUS","Mauritius","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
66980,480,"MUS","Mauritius","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
66981,480,"MUS","Mauritius","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
66982,480,"MUS","Mauritius","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
66983,480,"MUS","Mauritius","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
66984,480,"MUS","Mauritius","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
66985,480,"MUS","Mauritius","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MUS/mus_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
66986,484,"MEX","Mexico","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
66987,484,"MEX","Mexico","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
66988,484,"MEX","Mexico","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
66989,484,"MEX","Mexico","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
66990,484,"MEX","Mexico","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
66991,484,"MEX","Mexico","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
66992,484,"MEX","Mexico","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
66993,484,"MEX","Mexico","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
66994,484,"MEX","Mexico","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
66995,484,"MEX","Mexico","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
66996,484,"MEX","Mexico","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
66997,484,"MEX","Mexico","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
66998,484,"MEX","Mexico","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
66999,484,"MEX","Mexico","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67000,484,"MEX","Mexico","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67001,484,"MEX","Mexico","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67002,484,"MEX","Mexico","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67003,484,"MEX","Mexico","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67004,484,"MEX","Mexico","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67005,484,"MEX","Mexico","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67006,484,"MEX","Mexico","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67007,484,"MEX","Mexico","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67008,484,"MEX","Mexico","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67009,484,"MEX","Mexico","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67010,484,"MEX","Mexico","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67011,484,"MEX","Mexico","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67012,484,"MEX","Mexico","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67013,484,"MEX","Mexico","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67014,484,"MEX","Mexico","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67015,484,"MEX","Mexico","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67016,484,"MEX","Mexico","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67017,484,"MEX","Mexico","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67018,484,"MEX","Mexico","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67019,484,"MEX","Mexico","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67020,484,"MEX","Mexico","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67021,484,"MEX","Mexico","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MEX/mex_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67022,492,"MCO","Monaco","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67023,492,"MCO","Monaco","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67024,492,"MCO","Monaco","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67025,492,"MCO","Monaco","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67026,492,"MCO","Monaco","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67027,492,"MCO","Monaco","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67028,492,"MCO","Monaco","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67029,492,"MCO","Monaco","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67030,492,"MCO","Monaco","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67031,492,"MCO","Monaco","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67032,492,"MCO","Monaco","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67033,492,"MCO","Monaco","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67034,492,"MCO","Monaco","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67035,492,"MCO","Monaco","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67036,492,"MCO","Monaco","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67037,492,"MCO","Monaco","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67038,492,"MCO","Monaco","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67039,492,"MCO","Monaco","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67040,492,"MCO","Monaco","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67041,492,"MCO","Monaco","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67042,492,"MCO","Monaco","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67043,492,"MCO","Monaco","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67044,492,"MCO","Monaco","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67045,492,"MCO","Monaco","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67046,492,"MCO","Monaco","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67047,492,"MCO","Monaco","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67048,492,"MCO","Monaco","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67049,492,"MCO","Monaco","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67050,492,"MCO","Monaco","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67051,492,"MCO","Monaco","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67052,492,"MCO","Monaco","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67053,492,"MCO","Monaco","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67054,492,"MCO","Monaco","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67055,492,"MCO","Monaco","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67056,492,"MCO","Monaco","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67057,492,"MCO","Monaco","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MCO/mco_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67058,496,"MNG","Mongolia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67059,496,"MNG","Mongolia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67060,496,"MNG","Mongolia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67061,496,"MNG","Mongolia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67062,496,"MNG","Mongolia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67063,496,"MNG","Mongolia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67064,496,"MNG","Mongolia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67065,496,"MNG","Mongolia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67066,496,"MNG","Mongolia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67067,496,"MNG","Mongolia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67068,496,"MNG","Mongolia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67069,496,"MNG","Mongolia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67070,496,"MNG","Mongolia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67071,496,"MNG","Mongolia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67072,496,"MNG","Mongolia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67073,496,"MNG","Mongolia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67074,496,"MNG","Mongolia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67075,496,"MNG","Mongolia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67076,496,"MNG","Mongolia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67077,496,"MNG","Mongolia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67078,496,"MNG","Mongolia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67079,496,"MNG","Mongolia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67080,496,"MNG","Mongolia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67081,496,"MNG","Mongolia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67082,496,"MNG","Mongolia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67083,496,"MNG","Mongolia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67084,496,"MNG","Mongolia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67085,496,"MNG","Mongolia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67086,496,"MNG","Mongolia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67087,496,"MNG","Mongolia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67088,496,"MNG","Mongolia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67089,496,"MNG","Mongolia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67090,496,"MNG","Mongolia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67091,496,"MNG","Mongolia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67092,496,"MNG","Mongolia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67093,496,"MNG","Mongolia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNG/mng_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67094,498,"MDA","Moldova","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67095,498,"MDA","Moldova","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67096,498,"MDA","Moldova","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67097,498,"MDA","Moldova","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67098,498,"MDA","Moldova","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67099,498,"MDA","Moldova","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67100,498,"MDA","Moldova","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67101,498,"MDA","Moldova","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67102,498,"MDA","Moldova","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67103,498,"MDA","Moldova","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67104,498,"MDA","Moldova","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67105,498,"MDA","Moldova","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67106,498,"MDA","Moldova","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67107,498,"MDA","Moldova","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67108,498,"MDA","Moldova","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67109,498,"MDA","Moldova","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67110,498,"MDA","Moldova","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67111,498,"MDA","Moldova","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67112,498,"MDA","Moldova","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67113,498,"MDA","Moldova","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67114,498,"MDA","Moldova","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67115,498,"MDA","Moldova","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67116,498,"MDA","Moldova","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67117,498,"MDA","Moldova","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67118,498,"MDA","Moldova","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67119,498,"MDA","Moldova","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67120,498,"MDA","Moldova","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67121,498,"MDA","Moldova","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67122,498,"MDA","Moldova","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67123,498,"MDA","Moldova","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67124,498,"MDA","Moldova","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67125,498,"MDA","Moldova","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67126,498,"MDA","Moldova","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67127,498,"MDA","Moldova","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67128,498,"MDA","Moldova","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67129,498,"MDA","Moldova","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MDA/mda_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67130,499,"MNE","Montenegro","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67131,499,"MNE","Montenegro","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67132,499,"MNE","Montenegro","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67133,499,"MNE","Montenegro","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67134,499,"MNE","Montenegro","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67135,499,"MNE","Montenegro","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67136,499,"MNE","Montenegro","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67137,499,"MNE","Montenegro","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67138,499,"MNE","Montenegro","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67139,499,"MNE","Montenegro","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67140,499,"MNE","Montenegro","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67141,499,"MNE","Montenegro","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67142,499,"MNE","Montenegro","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67143,499,"MNE","Montenegro","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67144,499,"MNE","Montenegro","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67145,499,"MNE","Montenegro","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67146,499,"MNE","Montenegro","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67147,499,"MNE","Montenegro","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67148,499,"MNE","Montenegro","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67149,499,"MNE","Montenegro","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67150,499,"MNE","Montenegro","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67151,499,"MNE","Montenegro","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67152,499,"MNE","Montenegro","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67153,499,"MNE","Montenegro","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67154,499,"MNE","Montenegro","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67155,499,"MNE","Montenegro","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67156,499,"MNE","Montenegro","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67157,499,"MNE","Montenegro","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67158,499,"MNE","Montenegro","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67159,499,"MNE","Montenegro","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67160,499,"MNE","Montenegro","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67161,499,"MNE","Montenegro","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67162,499,"MNE","Montenegro","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67163,499,"MNE","Montenegro","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67164,499,"MNE","Montenegro","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67165,499,"MNE","Montenegro","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNE/mne_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67166,500,"MSR","Montserrat","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67167,500,"MSR","Montserrat","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67168,500,"MSR","Montserrat","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67169,500,"MSR","Montserrat","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67170,500,"MSR","Montserrat","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67171,500,"MSR","Montserrat","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67172,500,"MSR","Montserrat","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67173,500,"MSR","Montserrat","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67174,500,"MSR","Montserrat","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67175,500,"MSR","Montserrat","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67176,500,"MSR","Montserrat","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67177,500,"MSR","Montserrat","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67178,500,"MSR","Montserrat","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67179,500,"MSR","Montserrat","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67180,500,"MSR","Montserrat","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67181,500,"MSR","Montserrat","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67182,500,"MSR","Montserrat","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67183,500,"MSR","Montserrat","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67184,500,"MSR","Montserrat","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67185,500,"MSR","Montserrat","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67186,500,"MSR","Montserrat","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67187,500,"MSR","Montserrat","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67188,500,"MSR","Montserrat","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67189,500,"MSR","Montserrat","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67190,500,"MSR","Montserrat","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67191,500,"MSR","Montserrat","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67192,500,"MSR","Montserrat","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67193,500,"MSR","Montserrat","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67194,500,"MSR","Montserrat","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67195,500,"MSR","Montserrat","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67196,500,"MSR","Montserrat","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67197,500,"MSR","Montserrat","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67198,500,"MSR","Montserrat","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67199,500,"MSR","Montserrat","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67200,500,"MSR","Montserrat","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67201,500,"MSR","Montserrat","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MSR/msr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67202,504,"MAR","Morocco","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67203,504,"MAR","Morocco","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67204,504,"MAR","Morocco","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67205,504,"MAR","Morocco","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67206,504,"MAR","Morocco","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67207,504,"MAR","Morocco","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67208,504,"MAR","Morocco","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67209,504,"MAR","Morocco","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67210,504,"MAR","Morocco","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67211,504,"MAR","Morocco","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67212,504,"MAR","Morocco","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67213,504,"MAR","Morocco","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67214,504,"MAR","Morocco","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67215,504,"MAR","Morocco","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67216,504,"MAR","Morocco","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67217,504,"MAR","Morocco","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67218,504,"MAR","Morocco","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67219,504,"MAR","Morocco","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67220,504,"MAR","Morocco","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67221,504,"MAR","Morocco","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67222,504,"MAR","Morocco","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67223,504,"MAR","Morocco","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67224,504,"MAR","Morocco","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67225,504,"MAR","Morocco","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67226,504,"MAR","Morocco","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67227,504,"MAR","Morocco","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67228,504,"MAR","Morocco","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67229,504,"MAR","Morocco","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67230,504,"MAR","Morocco","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67231,504,"MAR","Morocco","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67232,504,"MAR","Morocco","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67233,504,"MAR","Morocco","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67234,504,"MAR","Morocco","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67235,504,"MAR","Morocco","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67236,504,"MAR","Morocco","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67237,504,"MAR","Morocco","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAR/mar_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67238,508,"MOZ","Mozambique","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67239,508,"MOZ","Mozambique","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67240,508,"MOZ","Mozambique","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67241,508,"MOZ","Mozambique","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67242,508,"MOZ","Mozambique","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67243,508,"MOZ","Mozambique","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67244,508,"MOZ","Mozambique","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67245,508,"MOZ","Mozambique","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67246,508,"MOZ","Mozambique","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67247,508,"MOZ","Mozambique","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67248,508,"MOZ","Mozambique","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67249,508,"MOZ","Mozambique","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67250,508,"MOZ","Mozambique","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67251,508,"MOZ","Mozambique","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67252,508,"MOZ","Mozambique","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67253,508,"MOZ","Mozambique","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67254,508,"MOZ","Mozambique","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67255,508,"MOZ","Mozambique","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67256,508,"MOZ","Mozambique","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67257,508,"MOZ","Mozambique","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67258,508,"MOZ","Mozambique","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67259,508,"MOZ","Mozambique","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67260,508,"MOZ","Mozambique","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67261,508,"MOZ","Mozambique","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67262,508,"MOZ","Mozambique","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67263,508,"MOZ","Mozambique","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67264,508,"MOZ","Mozambique","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67265,508,"MOZ","Mozambique","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67266,508,"MOZ","Mozambique","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67267,508,"MOZ","Mozambique","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67268,508,"MOZ","Mozambique","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67269,508,"MOZ","Mozambique","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67270,508,"MOZ","Mozambique","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67271,508,"MOZ","Mozambique","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67272,508,"MOZ","Mozambique","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67273,508,"MOZ","Mozambique","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MOZ/moz_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67274,512,"OMN","Oman","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67275,512,"OMN","Oman","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67276,512,"OMN","Oman","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67277,512,"OMN","Oman","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67278,512,"OMN","Oman","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67279,512,"OMN","Oman","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67280,512,"OMN","Oman","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67281,512,"OMN","Oman","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67282,512,"OMN","Oman","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67283,512,"OMN","Oman","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67284,512,"OMN","Oman","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67285,512,"OMN","Oman","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67286,512,"OMN","Oman","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67287,512,"OMN","Oman","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67288,512,"OMN","Oman","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67289,512,"OMN","Oman","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67290,512,"OMN","Oman","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67291,512,"OMN","Oman","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67292,512,"OMN","Oman","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67293,512,"OMN","Oman","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67294,512,"OMN","Oman","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67295,512,"OMN","Oman","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67296,512,"OMN","Oman","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67297,512,"OMN","Oman","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67298,512,"OMN","Oman","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67299,512,"OMN","Oman","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67300,512,"OMN","Oman","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67301,512,"OMN","Oman","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67302,512,"OMN","Oman","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67303,512,"OMN","Oman","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67304,512,"OMN","Oman","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67305,512,"OMN","Oman","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67306,512,"OMN","Oman","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67307,512,"OMN","Oman","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67308,512,"OMN","Oman","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67309,512,"OMN","Oman","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/OMN/omn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67310,516,"NAM","Namibia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67311,516,"NAM","Namibia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67312,516,"NAM","Namibia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67313,516,"NAM","Namibia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67314,516,"NAM","Namibia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67315,516,"NAM","Namibia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67316,516,"NAM","Namibia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67317,516,"NAM","Namibia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67318,516,"NAM","Namibia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67319,516,"NAM","Namibia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67320,516,"NAM","Namibia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67321,516,"NAM","Namibia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67322,516,"NAM","Namibia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67323,516,"NAM","Namibia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67324,516,"NAM","Namibia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67325,516,"NAM","Namibia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67326,516,"NAM","Namibia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67327,516,"NAM","Namibia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67328,516,"NAM","Namibia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67329,516,"NAM","Namibia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67330,516,"NAM","Namibia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67331,516,"NAM","Namibia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67332,516,"NAM","Namibia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67333,516,"NAM","Namibia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67334,516,"NAM","Namibia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67335,516,"NAM","Namibia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67336,516,"NAM","Namibia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67337,516,"NAM","Namibia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67338,516,"NAM","Namibia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67339,516,"NAM","Namibia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67340,516,"NAM","Namibia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67341,516,"NAM","Namibia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67342,516,"NAM","Namibia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67343,516,"NAM","Namibia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67344,516,"NAM","Namibia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67345,516,"NAM","Namibia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NAM/nam_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67346,520,"NRU","Nauru","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67347,520,"NRU","Nauru","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67348,520,"NRU","Nauru","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67349,520,"NRU","Nauru","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67350,520,"NRU","Nauru","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67351,520,"NRU","Nauru","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67352,520,"NRU","Nauru","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67353,520,"NRU","Nauru","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67354,520,"NRU","Nauru","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67355,520,"NRU","Nauru","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67356,520,"NRU","Nauru","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67357,520,"NRU","Nauru","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67358,520,"NRU","Nauru","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67359,520,"NRU","Nauru","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67360,520,"NRU","Nauru","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67361,520,"NRU","Nauru","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67362,520,"NRU","Nauru","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67363,520,"NRU","Nauru","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67364,520,"NRU","Nauru","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67365,520,"NRU","Nauru","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67366,520,"NRU","Nauru","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67367,520,"NRU","Nauru","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67368,520,"NRU","Nauru","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67369,520,"NRU","Nauru","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67370,520,"NRU","Nauru","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67371,520,"NRU","Nauru","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67372,520,"NRU","Nauru","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67373,520,"NRU","Nauru","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67374,520,"NRU","Nauru","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67375,520,"NRU","Nauru","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67376,520,"NRU","Nauru","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67377,520,"NRU","Nauru","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67378,520,"NRU","Nauru","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67379,520,"NRU","Nauru","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67380,520,"NRU","Nauru","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67381,520,"NRU","Nauru","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NRU/nru_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67382,524,"NPL","Nepal","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67383,524,"NPL","Nepal","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67384,524,"NPL","Nepal","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67385,524,"NPL","Nepal","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67386,524,"NPL","Nepal","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67387,524,"NPL","Nepal","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67388,524,"NPL","Nepal","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67389,524,"NPL","Nepal","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67390,524,"NPL","Nepal","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67391,524,"NPL","Nepal","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67392,524,"NPL","Nepal","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67393,524,"NPL","Nepal","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67394,524,"NPL","Nepal","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67395,524,"NPL","Nepal","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67396,524,"NPL","Nepal","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67397,524,"NPL","Nepal","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67398,524,"NPL","Nepal","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67399,524,"NPL","Nepal","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67400,524,"NPL","Nepal","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67401,524,"NPL","Nepal","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67402,524,"NPL","Nepal","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67403,524,"NPL","Nepal","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67404,524,"NPL","Nepal","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67405,524,"NPL","Nepal","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67406,524,"NPL","Nepal","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67407,524,"NPL","Nepal","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67408,524,"NPL","Nepal","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67409,524,"NPL","Nepal","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67410,524,"NPL","Nepal","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67411,524,"NPL","Nepal","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67412,524,"NPL","Nepal","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67413,524,"NPL","Nepal","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67414,524,"NPL","Nepal","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67415,524,"NPL","Nepal","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67416,524,"NPL","Nepal","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67417,524,"NPL","Nepal","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NPL/npl_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67418,528,"NLD","Netherlands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67419,528,"NLD","Netherlands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67420,528,"NLD","Netherlands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67421,528,"NLD","Netherlands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67422,528,"NLD","Netherlands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67423,528,"NLD","Netherlands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67424,528,"NLD","Netherlands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67425,528,"NLD","Netherlands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67426,528,"NLD","Netherlands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67427,528,"NLD","Netherlands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67428,528,"NLD","Netherlands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67429,528,"NLD","Netherlands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67430,528,"NLD","Netherlands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67431,528,"NLD","Netherlands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67432,528,"NLD","Netherlands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67433,528,"NLD","Netherlands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67434,528,"NLD","Netherlands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67435,528,"NLD","Netherlands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67436,528,"NLD","Netherlands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67437,528,"NLD","Netherlands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67438,528,"NLD","Netherlands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67439,528,"NLD","Netherlands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67440,528,"NLD","Netherlands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67441,528,"NLD","Netherlands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67442,528,"NLD","Netherlands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67443,528,"NLD","Netherlands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67444,528,"NLD","Netherlands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67445,528,"NLD","Netherlands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67446,528,"NLD","Netherlands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67447,528,"NLD","Netherlands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67448,528,"NLD","Netherlands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67449,528,"NLD","Netherlands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67450,528,"NLD","Netherlands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67451,528,"NLD","Netherlands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67452,528,"NLD","Netherlands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67453,528,"NLD","Netherlands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NLD/nld_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67454,531,"CUW","Curacao","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67455,531,"CUW","Curacao","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67456,531,"CUW","Curacao","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67457,531,"CUW","Curacao","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67458,531,"CUW","Curacao","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67459,531,"CUW","Curacao","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67460,531,"CUW","Curacao","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67461,531,"CUW","Curacao","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67462,531,"CUW","Curacao","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67463,531,"CUW","Curacao","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67464,531,"CUW","Curacao","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67465,531,"CUW","Curacao","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67466,531,"CUW","Curacao","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67467,531,"CUW","Curacao","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67468,531,"CUW","Curacao","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67469,531,"CUW","Curacao","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67470,531,"CUW","Curacao","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67471,531,"CUW","Curacao","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67472,531,"CUW","Curacao","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67473,531,"CUW","Curacao","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67474,531,"CUW","Curacao","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67475,531,"CUW","Curacao","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67476,531,"CUW","Curacao","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67477,531,"CUW","Curacao","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67478,531,"CUW","Curacao","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67479,531,"CUW","Curacao","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67480,531,"CUW","Curacao","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67481,531,"CUW","Curacao","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67482,531,"CUW","Curacao","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67483,531,"CUW","Curacao","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67484,531,"CUW","Curacao","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67485,531,"CUW","Curacao","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67486,531,"CUW","Curacao","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67487,531,"CUW","Curacao","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67488,531,"CUW","Curacao","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67489,531,"CUW","Curacao","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CUW/cuw_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67490,533,"ABW","Aruba","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67491,533,"ABW","Aruba","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67492,533,"ABW","Aruba","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67493,533,"ABW","Aruba","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67494,533,"ABW","Aruba","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67495,533,"ABW","Aruba","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67496,533,"ABW","Aruba","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67497,533,"ABW","Aruba","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67498,533,"ABW","Aruba","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67499,533,"ABW","Aruba","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67500,533,"ABW","Aruba","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67501,533,"ABW","Aruba","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67502,533,"ABW","Aruba","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67503,533,"ABW","Aruba","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67504,533,"ABW","Aruba","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67505,533,"ABW","Aruba","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67506,533,"ABW","Aruba","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67507,533,"ABW","Aruba","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67508,533,"ABW","Aruba","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67509,533,"ABW","Aruba","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67510,533,"ABW","Aruba","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67511,533,"ABW","Aruba","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67512,533,"ABW","Aruba","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67513,533,"ABW","Aruba","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67514,533,"ABW","Aruba","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67515,533,"ABW","Aruba","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67516,533,"ABW","Aruba","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67517,533,"ABW","Aruba","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67518,533,"ABW","Aruba","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67519,533,"ABW","Aruba","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67520,533,"ABW","Aruba","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67521,533,"ABW","Aruba","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67522,533,"ABW","Aruba","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67523,533,"ABW","Aruba","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67524,533,"ABW","Aruba","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67525,533,"ABW","Aruba","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ABW/abw_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67526,534,"SXM","Sint Maarten (Dutch part)","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67527,534,"SXM","Sint Maarten (Dutch part)","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67528,534,"SXM","Sint Maarten (Dutch part)","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67529,534,"SXM","Sint Maarten (Dutch part)","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67530,534,"SXM","Sint Maarten (Dutch part)","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67531,534,"SXM","Sint Maarten (Dutch part)","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67532,534,"SXM","Sint Maarten (Dutch part)","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67533,534,"SXM","Sint Maarten (Dutch part)","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67534,534,"SXM","Sint Maarten (Dutch part)","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67535,534,"SXM","Sint Maarten (Dutch part)","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67536,534,"SXM","Sint Maarten (Dutch part)","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67537,534,"SXM","Sint Maarten (Dutch part)","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67538,534,"SXM","Sint Maarten (Dutch part)","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67539,534,"SXM","Sint Maarten (Dutch part)","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67540,534,"SXM","Sint Maarten (Dutch part)","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67541,534,"SXM","Sint Maarten (Dutch part)","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67542,534,"SXM","Sint Maarten (Dutch part)","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67543,534,"SXM","Sint Maarten (Dutch part)","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67544,534,"SXM","Sint Maarten (Dutch part)","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67545,534,"SXM","Sint Maarten (Dutch part)","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67546,534,"SXM","Sint Maarten (Dutch part)","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67547,534,"SXM","Sint Maarten (Dutch part)","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67548,534,"SXM","Sint Maarten (Dutch part)","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67549,534,"SXM","Sint Maarten (Dutch part)","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67550,534,"SXM","Sint Maarten (Dutch part)","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67551,534,"SXM","Sint Maarten (Dutch part)","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67552,534,"SXM","Sint Maarten (Dutch part)","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67553,534,"SXM","Sint Maarten (Dutch part)","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67554,534,"SXM","Sint Maarten (Dutch part)","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67555,534,"SXM","Sint Maarten (Dutch part)","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67556,534,"SXM","Sint Maarten (Dutch part)","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67557,534,"SXM","Sint Maarten (Dutch part)","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67558,534,"SXM","Sint Maarten (Dutch part)","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67559,534,"SXM","Sint Maarten (Dutch part)","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67560,534,"SXM","Sint Maarten (Dutch part)","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67561,534,"SXM","Sint Maarten (Dutch part)","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SXM/sxm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67562,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67563,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67564,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67565,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67566,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67567,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67568,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67569,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67570,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67571,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67572,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67573,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67574,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67575,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67576,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67577,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67578,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67579,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67580,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67581,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67582,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67583,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67584,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67585,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67586,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67587,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67588,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67589,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67590,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67591,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67592,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67593,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67594,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67595,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67596,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67597,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BES/bes_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67598,540,"NCL","New Caledonia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67599,540,"NCL","New Caledonia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67600,540,"NCL","New Caledonia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67601,540,"NCL","New Caledonia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67602,540,"NCL","New Caledonia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67603,540,"NCL","New Caledonia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67604,540,"NCL","New Caledonia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67605,540,"NCL","New Caledonia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67606,540,"NCL","New Caledonia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67607,540,"NCL","New Caledonia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67608,540,"NCL","New Caledonia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67609,540,"NCL","New Caledonia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67610,540,"NCL","New Caledonia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67611,540,"NCL","New Caledonia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67612,540,"NCL","New Caledonia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67613,540,"NCL","New Caledonia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67614,540,"NCL","New Caledonia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67615,540,"NCL","New Caledonia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67616,540,"NCL","New Caledonia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67617,540,"NCL","New Caledonia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67618,540,"NCL","New Caledonia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67619,540,"NCL","New Caledonia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67620,540,"NCL","New Caledonia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67621,540,"NCL","New Caledonia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67622,540,"NCL","New Caledonia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67623,540,"NCL","New Caledonia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67624,540,"NCL","New Caledonia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67625,540,"NCL","New Caledonia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67626,540,"NCL","New Caledonia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67627,540,"NCL","New Caledonia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67628,540,"NCL","New Caledonia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67629,540,"NCL","New Caledonia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67630,540,"NCL","New Caledonia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67631,540,"NCL","New Caledonia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67632,540,"NCL","New Caledonia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67633,540,"NCL","New Caledonia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NCL/ncl_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67634,548,"VUT","Vanuatu","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67635,548,"VUT","Vanuatu","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67636,548,"VUT","Vanuatu","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67637,548,"VUT","Vanuatu","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67638,548,"VUT","Vanuatu","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67639,548,"VUT","Vanuatu","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67640,548,"VUT","Vanuatu","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67641,548,"VUT","Vanuatu","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67642,548,"VUT","Vanuatu","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67643,548,"VUT","Vanuatu","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67644,548,"VUT","Vanuatu","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67645,548,"VUT","Vanuatu","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67646,548,"VUT","Vanuatu","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67647,548,"VUT","Vanuatu","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67648,548,"VUT","Vanuatu","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67649,548,"VUT","Vanuatu","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67650,548,"VUT","Vanuatu","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67651,548,"VUT","Vanuatu","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67652,548,"VUT","Vanuatu","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67653,548,"VUT","Vanuatu","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67654,548,"VUT","Vanuatu","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67655,548,"VUT","Vanuatu","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67656,548,"VUT","Vanuatu","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67657,548,"VUT","Vanuatu","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67658,548,"VUT","Vanuatu","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67659,548,"VUT","Vanuatu","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67660,548,"VUT","Vanuatu","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67661,548,"VUT","Vanuatu","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67662,548,"VUT","Vanuatu","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67663,548,"VUT","Vanuatu","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67664,548,"VUT","Vanuatu","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67665,548,"VUT","Vanuatu","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67666,548,"VUT","Vanuatu","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67667,548,"VUT","Vanuatu","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67668,548,"VUT","Vanuatu","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67669,548,"VUT","Vanuatu","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VUT/vut_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67670,554,"NZL","New Zealand","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67671,554,"NZL","New Zealand","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67672,554,"NZL","New Zealand","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67673,554,"NZL","New Zealand","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67674,554,"NZL","New Zealand","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67675,554,"NZL","New Zealand","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67676,554,"NZL","New Zealand","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67677,554,"NZL","New Zealand","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67678,554,"NZL","New Zealand","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67679,554,"NZL","New Zealand","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67680,554,"NZL","New Zealand","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67681,554,"NZL","New Zealand","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67682,554,"NZL","New Zealand","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67683,554,"NZL","New Zealand","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67684,554,"NZL","New Zealand","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67685,554,"NZL","New Zealand","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67686,554,"NZL","New Zealand","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67687,554,"NZL","New Zealand","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67688,554,"NZL","New Zealand","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67689,554,"NZL","New Zealand","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67690,554,"NZL","New Zealand","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67691,554,"NZL","New Zealand","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67692,554,"NZL","New Zealand","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67693,554,"NZL","New Zealand","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67694,554,"NZL","New Zealand","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67695,554,"NZL","New Zealand","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67696,554,"NZL","New Zealand","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67697,554,"NZL","New Zealand","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67698,554,"NZL","New Zealand","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67699,554,"NZL","New Zealand","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67700,554,"NZL","New Zealand","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67701,554,"NZL","New Zealand","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67702,554,"NZL","New Zealand","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67703,554,"NZL","New Zealand","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67704,554,"NZL","New Zealand","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67705,554,"NZL","New Zealand","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NZL/nzl_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67706,558,"NIC","Nicaragua","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67707,558,"NIC","Nicaragua","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67708,558,"NIC","Nicaragua","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67709,558,"NIC","Nicaragua","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67710,558,"NIC","Nicaragua","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67711,558,"NIC","Nicaragua","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67712,558,"NIC","Nicaragua","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67713,558,"NIC","Nicaragua","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67714,558,"NIC","Nicaragua","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67715,558,"NIC","Nicaragua","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67716,558,"NIC","Nicaragua","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67717,558,"NIC","Nicaragua","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67718,558,"NIC","Nicaragua","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67719,558,"NIC","Nicaragua","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67720,558,"NIC","Nicaragua","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67721,558,"NIC","Nicaragua","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67722,558,"NIC","Nicaragua","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67723,558,"NIC","Nicaragua","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67724,558,"NIC","Nicaragua","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67725,558,"NIC","Nicaragua","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67726,558,"NIC","Nicaragua","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67727,558,"NIC","Nicaragua","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67728,558,"NIC","Nicaragua","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67729,558,"NIC","Nicaragua","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67730,558,"NIC","Nicaragua","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67731,558,"NIC","Nicaragua","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67732,558,"NIC","Nicaragua","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67733,558,"NIC","Nicaragua","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67734,558,"NIC","Nicaragua","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67735,558,"NIC","Nicaragua","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67736,558,"NIC","Nicaragua","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67737,558,"NIC","Nicaragua","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67738,558,"NIC","Nicaragua","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67739,558,"NIC","Nicaragua","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67740,558,"NIC","Nicaragua","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67741,558,"NIC","Nicaragua","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIC/nic_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67742,562,"NER","Niger","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67743,562,"NER","Niger","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67744,562,"NER","Niger","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67745,562,"NER","Niger","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67746,562,"NER","Niger","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67747,562,"NER","Niger","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67748,562,"NER","Niger","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67749,562,"NER","Niger","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67750,562,"NER","Niger","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67751,562,"NER","Niger","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67752,562,"NER","Niger","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67753,562,"NER","Niger","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67754,562,"NER","Niger","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67755,562,"NER","Niger","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67756,562,"NER","Niger","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67757,562,"NER","Niger","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67758,562,"NER","Niger","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67759,562,"NER","Niger","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67760,562,"NER","Niger","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67761,562,"NER","Niger","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67762,562,"NER","Niger","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67763,562,"NER","Niger","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67764,562,"NER","Niger","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67765,562,"NER","Niger","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67766,562,"NER","Niger","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67767,562,"NER","Niger","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67768,562,"NER","Niger","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67769,562,"NER","Niger","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67770,562,"NER","Niger","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67771,562,"NER","Niger","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67772,562,"NER","Niger","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67773,562,"NER","Niger","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67774,562,"NER","Niger","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67775,562,"NER","Niger","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67776,562,"NER","Niger","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67777,562,"NER","Niger","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NER/ner_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67778,566,"NGA","Nigeria","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67779,566,"NGA","Nigeria","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67780,566,"NGA","Nigeria","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67781,566,"NGA","Nigeria","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67782,566,"NGA","Nigeria","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67783,566,"NGA","Nigeria","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67784,566,"NGA","Nigeria","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67785,566,"NGA","Nigeria","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67786,566,"NGA","Nigeria","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67787,566,"NGA","Nigeria","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67788,566,"NGA","Nigeria","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67789,566,"NGA","Nigeria","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67790,566,"NGA","Nigeria","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67791,566,"NGA","Nigeria","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67792,566,"NGA","Nigeria","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67793,566,"NGA","Nigeria","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67794,566,"NGA","Nigeria","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67795,566,"NGA","Nigeria","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67796,566,"NGA","Nigeria","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67797,566,"NGA","Nigeria","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67798,566,"NGA","Nigeria","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67799,566,"NGA","Nigeria","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67800,566,"NGA","Nigeria","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67801,566,"NGA","Nigeria","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67802,566,"NGA","Nigeria","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67803,566,"NGA","Nigeria","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67804,566,"NGA","Nigeria","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67805,566,"NGA","Nigeria","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67806,566,"NGA","Nigeria","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67807,566,"NGA","Nigeria","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67808,566,"NGA","Nigeria","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67809,566,"NGA","Nigeria","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67810,566,"NGA","Nigeria","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67811,566,"NGA","Nigeria","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67812,566,"NGA","Nigeria","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67813,566,"NGA","Nigeria","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NGA/nga_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67814,570,"NIU","Niue","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67815,570,"NIU","Niue","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67816,570,"NIU","Niue","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67817,570,"NIU","Niue","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67818,570,"NIU","Niue","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67819,570,"NIU","Niue","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67820,570,"NIU","Niue","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67821,570,"NIU","Niue","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67822,570,"NIU","Niue","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67823,570,"NIU","Niue","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67824,570,"NIU","Niue","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67825,570,"NIU","Niue","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67826,570,"NIU","Niue","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67827,570,"NIU","Niue","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67828,570,"NIU","Niue","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67829,570,"NIU","Niue","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67830,570,"NIU","Niue","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67831,570,"NIU","Niue","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67832,570,"NIU","Niue","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67833,570,"NIU","Niue","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67834,570,"NIU","Niue","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67835,570,"NIU","Niue","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67836,570,"NIU","Niue","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67837,570,"NIU","Niue","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67838,570,"NIU","Niue","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67839,570,"NIU","Niue","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67840,570,"NIU","Niue","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67841,570,"NIU","Niue","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67842,570,"NIU","Niue","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67843,570,"NIU","Niue","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67844,570,"NIU","Niue","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67845,570,"NIU","Niue","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67846,570,"NIU","Niue","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67847,570,"NIU","Niue","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67848,570,"NIU","Niue","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67849,570,"NIU","Niue","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NIU/niu_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67850,574,"NFK","Norfolk Island","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67851,574,"NFK","Norfolk Island","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67852,574,"NFK","Norfolk Island","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67853,574,"NFK","Norfolk Island","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67854,574,"NFK","Norfolk Island","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67855,574,"NFK","Norfolk Island","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67856,574,"NFK","Norfolk Island","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67857,574,"NFK","Norfolk Island","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67858,574,"NFK","Norfolk Island","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67859,574,"NFK","Norfolk Island","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67860,574,"NFK","Norfolk Island","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67861,574,"NFK","Norfolk Island","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67862,574,"NFK","Norfolk Island","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67863,574,"NFK","Norfolk Island","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67864,574,"NFK","Norfolk Island","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67865,574,"NFK","Norfolk Island","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67866,574,"NFK","Norfolk Island","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67867,574,"NFK","Norfolk Island","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67868,574,"NFK","Norfolk Island","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67869,574,"NFK","Norfolk Island","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67870,574,"NFK","Norfolk Island","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67871,574,"NFK","Norfolk Island","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67872,574,"NFK","Norfolk Island","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67873,574,"NFK","Norfolk Island","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67874,574,"NFK","Norfolk Island","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67875,574,"NFK","Norfolk Island","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67876,574,"NFK","Norfolk Island","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67877,574,"NFK","Norfolk Island","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67878,574,"NFK","Norfolk Island","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67879,574,"NFK","Norfolk Island","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67880,574,"NFK","Norfolk Island","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67881,574,"NFK","Norfolk Island","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67882,574,"NFK","Norfolk Island","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67883,574,"NFK","Norfolk Island","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67884,574,"NFK","Norfolk Island","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67885,574,"NFK","Norfolk Island","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NFK/nfk_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67886,578,"NOR","Norway","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67887,578,"NOR","Norway","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67888,578,"NOR","Norway","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67889,578,"NOR","Norway","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67890,578,"NOR","Norway","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67891,578,"NOR","Norway","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67892,578,"NOR","Norway","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67893,578,"NOR","Norway","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67894,578,"NOR","Norway","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67895,578,"NOR","Norway","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67896,578,"NOR","Norway","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67897,578,"NOR","Norway","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67898,578,"NOR","Norway","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67899,578,"NOR","Norway","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67900,578,"NOR","Norway","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67901,578,"NOR","Norway","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67902,578,"NOR","Norway","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67903,578,"NOR","Norway","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67904,578,"NOR","Norway","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67905,578,"NOR","Norway","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67906,578,"NOR","Norway","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67907,578,"NOR","Norway","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67908,578,"NOR","Norway","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67909,578,"NOR","Norway","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67910,578,"NOR","Norway","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67911,578,"NOR","Norway","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67912,578,"NOR","Norway","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67913,578,"NOR","Norway","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67914,578,"NOR","Norway","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67915,578,"NOR","Norway","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67916,578,"NOR","Norway","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67917,578,"NOR","Norway","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67918,578,"NOR","Norway","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67919,578,"NOR","Norway","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67920,578,"NOR","Norway","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67921,578,"NOR","Norway","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/NOR/nor_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67922,580,"MNP","Northern Mariana Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67923,580,"MNP","Northern Mariana Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67924,580,"MNP","Northern Mariana Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67925,580,"MNP","Northern Mariana Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67926,580,"MNP","Northern Mariana Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67927,580,"MNP","Northern Mariana Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67928,580,"MNP","Northern Mariana Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67929,580,"MNP","Northern Mariana Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67930,580,"MNP","Northern Mariana Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67931,580,"MNP","Northern Mariana Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67932,580,"MNP","Northern Mariana Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67933,580,"MNP","Northern Mariana Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67934,580,"MNP","Northern Mariana Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67935,580,"MNP","Northern Mariana Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67936,580,"MNP","Northern Mariana Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67937,580,"MNP","Northern Mariana Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67938,580,"MNP","Northern Mariana Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67939,580,"MNP","Northern Mariana Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67940,580,"MNP","Northern Mariana Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67941,580,"MNP","Northern Mariana Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67942,580,"MNP","Northern Mariana Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67943,580,"MNP","Northern Mariana Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67944,580,"MNP","Northern Mariana Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67945,580,"MNP","Northern Mariana Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67946,580,"MNP","Northern Mariana Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67947,580,"MNP","Northern Mariana Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67948,580,"MNP","Northern Mariana Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67949,580,"MNP","Northern Mariana Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67950,580,"MNP","Northern Mariana Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67951,580,"MNP","Northern Mariana Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67952,580,"MNP","Northern Mariana Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67953,580,"MNP","Northern Mariana Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67954,580,"MNP","Northern Mariana Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67955,580,"MNP","Northern Mariana Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67956,580,"MNP","Northern Mariana Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67957,580,"MNP","Northern Mariana Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MNP/mnp_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67958,581,"UMI","United States Minor Outlying Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67959,581,"UMI","United States Minor Outlying Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67960,581,"UMI","United States Minor Outlying Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67961,581,"UMI","United States Minor Outlying Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67962,581,"UMI","United States Minor Outlying Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67963,581,"UMI","United States Minor Outlying Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
67964,581,"UMI","United States Minor Outlying Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
67965,581,"UMI","United States Minor Outlying Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
67966,581,"UMI","United States Minor Outlying Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
67967,581,"UMI","United States Minor Outlying Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
67968,581,"UMI","United States Minor Outlying Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
67969,581,"UMI","United States Minor Outlying Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
67970,581,"UMI","United States Minor Outlying Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
67971,581,"UMI","United States Minor Outlying Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
67972,581,"UMI","United States Minor Outlying Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
67973,581,"UMI","United States Minor Outlying Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
67974,581,"UMI","United States Minor Outlying Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
67975,581,"UMI","United States Minor Outlying Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
67976,581,"UMI","United States Minor Outlying Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
67977,581,"UMI","United States Minor Outlying Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
67978,581,"UMI","United States Minor Outlying Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
67979,581,"UMI","United States Minor Outlying Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
67980,581,"UMI","United States Minor Outlying Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
67981,581,"UMI","United States Minor Outlying Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
67982,581,"UMI","United States Minor Outlying Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
67983,581,"UMI","United States Minor Outlying Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
67984,581,"UMI","United States Minor Outlying Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
67985,581,"UMI","United States Minor Outlying Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
67986,581,"UMI","United States Minor Outlying Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
67987,581,"UMI","United States Minor Outlying Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
67988,581,"UMI","United States Minor Outlying Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
67989,581,"UMI","United States Minor Outlying Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
67990,581,"UMI","United States Minor Outlying Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
67991,581,"UMI","United States Minor Outlying Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
67992,581,"UMI","United States Minor Outlying Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
67993,581,"UMI","United States Minor Outlying Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UMI/umi_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
67994,583,"FSM","Micronesia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
67995,583,"FSM","Micronesia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
67996,583,"FSM","Micronesia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
67997,583,"FSM","Micronesia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
67998,583,"FSM","Micronesia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
67999,583,"FSM","Micronesia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68000,583,"FSM","Micronesia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68001,583,"FSM","Micronesia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68002,583,"FSM","Micronesia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68003,583,"FSM","Micronesia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68004,583,"FSM","Micronesia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68005,583,"FSM","Micronesia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68006,583,"FSM","Micronesia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68007,583,"FSM","Micronesia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68008,583,"FSM","Micronesia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68009,583,"FSM","Micronesia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68010,583,"FSM","Micronesia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68011,583,"FSM","Micronesia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68012,583,"FSM","Micronesia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68013,583,"FSM","Micronesia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68014,583,"FSM","Micronesia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68015,583,"FSM","Micronesia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68016,583,"FSM","Micronesia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68017,583,"FSM","Micronesia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68018,583,"FSM","Micronesia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68019,583,"FSM","Micronesia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68020,583,"FSM","Micronesia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68021,583,"FSM","Micronesia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68022,583,"FSM","Micronesia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68023,583,"FSM","Micronesia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68024,583,"FSM","Micronesia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68025,583,"FSM","Micronesia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68026,583,"FSM","Micronesia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68027,583,"FSM","Micronesia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68028,583,"FSM","Micronesia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68029,583,"FSM","Micronesia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/FSM/fsm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68030,584,"MHL","Marshall Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68031,584,"MHL","Marshall Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68032,584,"MHL","Marshall Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68033,584,"MHL","Marshall Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68034,584,"MHL","Marshall Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68035,584,"MHL","Marshall Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68036,584,"MHL","Marshall Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68037,584,"MHL","Marshall Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68038,584,"MHL","Marshall Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68039,584,"MHL","Marshall Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68040,584,"MHL","Marshall Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68041,584,"MHL","Marshall Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68042,584,"MHL","Marshall Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68043,584,"MHL","Marshall Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68044,584,"MHL","Marshall Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68045,584,"MHL","Marshall Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68046,584,"MHL","Marshall Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68047,584,"MHL","Marshall Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68048,584,"MHL","Marshall Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68049,584,"MHL","Marshall Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68050,584,"MHL","Marshall Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68051,584,"MHL","Marshall Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68052,584,"MHL","Marshall Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68053,584,"MHL","Marshall Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68054,584,"MHL","Marshall Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68055,584,"MHL","Marshall Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68056,584,"MHL","Marshall Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68057,584,"MHL","Marshall Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68058,584,"MHL","Marshall Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68059,584,"MHL","Marshall Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68060,584,"MHL","Marshall Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68061,584,"MHL","Marshall Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68062,584,"MHL","Marshall Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68063,584,"MHL","Marshall Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68064,584,"MHL","Marshall Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68065,584,"MHL","Marshall Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MHL/mhl_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68066,585,"PLW","Palau","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68067,585,"PLW","Palau","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68068,585,"PLW","Palau","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68069,585,"PLW","Palau","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68070,585,"PLW","Palau","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68071,585,"PLW","Palau","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68072,585,"PLW","Palau","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68073,585,"PLW","Palau","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68074,585,"PLW","Palau","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68075,585,"PLW","Palau","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68076,585,"PLW","Palau","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68077,585,"PLW","Palau","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68078,585,"PLW","Palau","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68079,585,"PLW","Palau","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68080,585,"PLW","Palau","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68081,585,"PLW","Palau","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68082,585,"PLW","Palau","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68083,585,"PLW","Palau","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68084,585,"PLW","Palau","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68085,585,"PLW","Palau","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68086,585,"PLW","Palau","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68087,585,"PLW","Palau","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68088,585,"PLW","Palau","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68089,585,"PLW","Palau","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68090,585,"PLW","Palau","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68091,585,"PLW","Palau","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68092,585,"PLW","Palau","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68093,585,"PLW","Palau","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68094,585,"PLW","Palau","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68095,585,"PLW","Palau","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68096,585,"PLW","Palau","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68097,585,"PLW","Palau","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68098,585,"PLW","Palau","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68099,585,"PLW","Palau","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68100,585,"PLW","Palau","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68101,585,"PLW","Palau","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PLW/plw_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68102,586,"PAK","Pakistan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68103,586,"PAK","Pakistan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68104,586,"PAK","Pakistan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68105,586,"PAK","Pakistan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68106,586,"PAK","Pakistan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68107,586,"PAK","Pakistan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68108,586,"PAK","Pakistan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68109,586,"PAK","Pakistan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68110,586,"PAK","Pakistan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68111,586,"PAK","Pakistan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68112,586,"PAK","Pakistan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68113,586,"PAK","Pakistan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68114,586,"PAK","Pakistan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68115,586,"PAK","Pakistan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68116,586,"PAK","Pakistan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68117,586,"PAK","Pakistan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68118,586,"PAK","Pakistan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68119,586,"PAK","Pakistan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68120,586,"PAK","Pakistan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68121,586,"PAK","Pakistan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68122,586,"PAK","Pakistan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68123,586,"PAK","Pakistan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68124,586,"PAK","Pakistan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68125,586,"PAK","Pakistan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68126,586,"PAK","Pakistan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68127,586,"PAK","Pakistan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68128,586,"PAK","Pakistan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68129,586,"PAK","Pakistan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68130,586,"PAK","Pakistan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68131,586,"PAK","Pakistan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68132,586,"PAK","Pakistan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68133,586,"PAK","Pakistan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68134,586,"PAK","Pakistan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68135,586,"PAK","Pakistan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68136,586,"PAK","Pakistan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68137,586,"PAK","Pakistan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAK/pak_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68138,591,"PAN","Panama","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68139,591,"PAN","Panama","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68140,591,"PAN","Panama","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68141,591,"PAN","Panama","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68142,591,"PAN","Panama","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68143,591,"PAN","Panama","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68144,591,"PAN","Panama","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68145,591,"PAN","Panama","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68146,591,"PAN","Panama","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68147,591,"PAN","Panama","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68148,591,"PAN","Panama","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68149,591,"PAN","Panama","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68150,591,"PAN","Panama","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68151,591,"PAN","Panama","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68152,591,"PAN","Panama","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68153,591,"PAN","Panama","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68154,591,"PAN","Panama","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68155,591,"PAN","Panama","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68156,591,"PAN","Panama","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68157,591,"PAN","Panama","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68158,591,"PAN","Panama","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68159,591,"PAN","Panama","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68160,591,"PAN","Panama","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68161,591,"PAN","Panama","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68162,591,"PAN","Panama","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68163,591,"PAN","Panama","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68164,591,"PAN","Panama","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68165,591,"PAN","Panama","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68166,591,"PAN","Panama","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68167,591,"PAN","Panama","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68168,591,"PAN","Panama","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68169,591,"PAN","Panama","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68170,591,"PAN","Panama","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68171,591,"PAN","Panama","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68172,591,"PAN","Panama","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68173,591,"PAN","Panama","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PAN/pan_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68174,598,"PNG","Papua New Guinea","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68175,598,"PNG","Papua New Guinea","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68176,598,"PNG","Papua New Guinea","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68177,598,"PNG","Papua New Guinea","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68178,598,"PNG","Papua New Guinea","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68179,598,"PNG","Papua New Guinea","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68180,598,"PNG","Papua New Guinea","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68181,598,"PNG","Papua New Guinea","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68182,598,"PNG","Papua New Guinea","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68183,598,"PNG","Papua New Guinea","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68184,598,"PNG","Papua New Guinea","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68185,598,"PNG","Papua New Guinea","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68186,598,"PNG","Papua New Guinea","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68187,598,"PNG","Papua New Guinea","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68188,598,"PNG","Papua New Guinea","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68189,598,"PNG","Papua New Guinea","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68190,598,"PNG","Papua New Guinea","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68191,598,"PNG","Papua New Guinea","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68192,598,"PNG","Papua New Guinea","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68193,598,"PNG","Papua New Guinea","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68194,598,"PNG","Papua New Guinea","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68195,598,"PNG","Papua New Guinea","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68196,598,"PNG","Papua New Guinea","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68197,598,"PNG","Papua New Guinea","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68198,598,"PNG","Papua New Guinea","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68199,598,"PNG","Papua New Guinea","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68200,598,"PNG","Papua New Guinea","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68201,598,"PNG","Papua New Guinea","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68202,598,"PNG","Papua New Guinea","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68203,598,"PNG","Papua New Guinea","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68204,598,"PNG","Papua New Guinea","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68205,598,"PNG","Papua New Guinea","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68206,598,"PNG","Papua New Guinea","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68207,598,"PNG","Papua New Guinea","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68208,598,"PNG","Papua New Guinea","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68209,598,"PNG","Papua New Guinea","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PNG/png_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68210,600,"PRY","Paraguay","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68211,600,"PRY","Paraguay","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68212,600,"PRY","Paraguay","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68213,600,"PRY","Paraguay","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68214,600,"PRY","Paraguay","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68215,600,"PRY","Paraguay","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68216,600,"PRY","Paraguay","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68217,600,"PRY","Paraguay","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68218,600,"PRY","Paraguay","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68219,600,"PRY","Paraguay","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68220,600,"PRY","Paraguay","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68221,600,"PRY","Paraguay","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68222,600,"PRY","Paraguay","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68223,600,"PRY","Paraguay","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68224,600,"PRY","Paraguay","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68225,600,"PRY","Paraguay","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68226,600,"PRY","Paraguay","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68227,600,"PRY","Paraguay","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68228,600,"PRY","Paraguay","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68229,600,"PRY","Paraguay","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68230,600,"PRY","Paraguay","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68231,600,"PRY","Paraguay","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68232,600,"PRY","Paraguay","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68233,600,"PRY","Paraguay","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68234,600,"PRY","Paraguay","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68235,600,"PRY","Paraguay","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68236,600,"PRY","Paraguay","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68237,600,"PRY","Paraguay","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68238,600,"PRY","Paraguay","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68239,600,"PRY","Paraguay","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68240,600,"PRY","Paraguay","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68241,600,"PRY","Paraguay","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68242,600,"PRY","Paraguay","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68243,600,"PRY","Paraguay","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68244,600,"PRY","Paraguay","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68245,600,"PRY","Paraguay","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRY/pry_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68246,604,"PER","Peru","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68247,604,"PER","Peru","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68248,604,"PER","Peru","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68249,604,"PER","Peru","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68250,604,"PER","Peru","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68251,604,"PER","Peru","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68252,604,"PER","Peru","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68253,604,"PER","Peru","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68254,604,"PER","Peru","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68255,604,"PER","Peru","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68256,604,"PER","Peru","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68257,604,"PER","Peru","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68258,604,"PER","Peru","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68259,604,"PER","Peru","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68260,604,"PER","Peru","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68261,604,"PER","Peru","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68262,604,"PER","Peru","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68263,604,"PER","Peru","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68264,604,"PER","Peru","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68265,604,"PER","Peru","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68266,604,"PER","Peru","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68267,604,"PER","Peru","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68268,604,"PER","Peru","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68269,604,"PER","Peru","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68270,604,"PER","Peru","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68271,604,"PER","Peru","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68272,604,"PER","Peru","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68273,604,"PER","Peru","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68274,604,"PER","Peru","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68275,604,"PER","Peru","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68276,604,"PER","Peru","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68277,604,"PER","Peru","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68278,604,"PER","Peru","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68279,604,"PER","Peru","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68280,604,"PER","Peru","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68281,604,"PER","Peru","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PER/per_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68282,608,"PHL","Philippines","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68283,608,"PHL","Philippines","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68284,608,"PHL","Philippines","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68285,608,"PHL","Philippines","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68286,608,"PHL","Philippines","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68287,608,"PHL","Philippines","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68288,608,"PHL","Philippines","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68289,608,"PHL","Philippines","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68290,608,"PHL","Philippines","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68291,608,"PHL","Philippines","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68292,608,"PHL","Philippines","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68293,608,"PHL","Philippines","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68294,608,"PHL","Philippines","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68295,608,"PHL","Philippines","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68296,608,"PHL","Philippines","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68297,608,"PHL","Philippines","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68298,608,"PHL","Philippines","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68299,608,"PHL","Philippines","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68300,608,"PHL","Philippines","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68301,608,"PHL","Philippines","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68302,608,"PHL","Philippines","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68303,608,"PHL","Philippines","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68304,608,"PHL","Philippines","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68305,608,"PHL","Philippines","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68306,608,"PHL","Philippines","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68307,608,"PHL","Philippines","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68308,608,"PHL","Philippines","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68309,608,"PHL","Philippines","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68310,608,"PHL","Philippines","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68311,608,"PHL","Philippines","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68312,608,"PHL","Philippines","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68313,608,"PHL","Philippines","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68314,608,"PHL","Philippines","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68315,608,"PHL","Philippines","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68316,608,"PHL","Philippines","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68317,608,"PHL","Philippines","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PHL/phl_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68318,612,"PCN","Pitcairn Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68319,612,"PCN","Pitcairn Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68320,612,"PCN","Pitcairn Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68321,612,"PCN","Pitcairn Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68322,612,"PCN","Pitcairn Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68323,612,"PCN","Pitcairn Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68324,612,"PCN","Pitcairn Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68325,612,"PCN","Pitcairn Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68326,612,"PCN","Pitcairn Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68327,612,"PCN","Pitcairn Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68328,612,"PCN","Pitcairn Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68329,612,"PCN","Pitcairn Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68330,612,"PCN","Pitcairn Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68331,612,"PCN","Pitcairn Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68332,612,"PCN","Pitcairn Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68333,612,"PCN","Pitcairn Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68334,612,"PCN","Pitcairn Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68335,612,"PCN","Pitcairn Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68336,612,"PCN","Pitcairn Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68337,612,"PCN","Pitcairn Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68338,612,"PCN","Pitcairn Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68339,612,"PCN","Pitcairn Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68340,612,"PCN","Pitcairn Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68341,612,"PCN","Pitcairn Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68342,612,"PCN","Pitcairn Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68343,612,"PCN","Pitcairn Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68344,612,"PCN","Pitcairn Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68345,612,"PCN","Pitcairn Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68346,612,"PCN","Pitcairn Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68347,612,"PCN","Pitcairn Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68348,612,"PCN","Pitcairn Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68349,612,"PCN","Pitcairn Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68350,612,"PCN","Pitcairn Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68351,612,"PCN","Pitcairn Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68352,612,"PCN","Pitcairn Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68353,612,"PCN","Pitcairn Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PCN/pcn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68354,616,"POL","Poland","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68355,616,"POL","Poland","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68356,616,"POL","Poland","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68357,616,"POL","Poland","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68358,616,"POL","Poland","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68359,616,"POL","Poland","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68360,616,"POL","Poland","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68361,616,"POL","Poland","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68362,616,"POL","Poland","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68363,616,"POL","Poland","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68364,616,"POL","Poland","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68365,616,"POL","Poland","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68366,616,"POL","Poland","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68367,616,"POL","Poland","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68368,616,"POL","Poland","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68369,616,"POL","Poland","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68370,616,"POL","Poland","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68371,616,"POL","Poland","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68372,616,"POL","Poland","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68373,616,"POL","Poland","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68374,616,"POL","Poland","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68375,616,"POL","Poland","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68376,616,"POL","Poland","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68377,616,"POL","Poland","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68378,616,"POL","Poland","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68379,616,"POL","Poland","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68380,616,"POL","Poland","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68381,616,"POL","Poland","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68382,616,"POL","Poland","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68383,616,"POL","Poland","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68384,616,"POL","Poland","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68385,616,"POL","Poland","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68386,616,"POL","Poland","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68387,616,"POL","Poland","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68388,616,"POL","Poland","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68389,616,"POL","Poland","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/POL/pol_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68390,620,"PRT","Portugal","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68391,620,"PRT","Portugal","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68392,620,"PRT","Portugal","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68393,620,"PRT","Portugal","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68394,620,"PRT","Portugal","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68395,620,"PRT","Portugal","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68396,620,"PRT","Portugal","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68397,620,"PRT","Portugal","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68398,620,"PRT","Portugal","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68399,620,"PRT","Portugal","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68400,620,"PRT","Portugal","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68401,620,"PRT","Portugal","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68402,620,"PRT","Portugal","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68403,620,"PRT","Portugal","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68404,620,"PRT","Portugal","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68405,620,"PRT","Portugal","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68406,620,"PRT","Portugal","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68407,620,"PRT","Portugal","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68408,620,"PRT","Portugal","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68409,620,"PRT","Portugal","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68410,620,"PRT","Portugal","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68411,620,"PRT","Portugal","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68412,620,"PRT","Portugal","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68413,620,"PRT","Portugal","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68414,620,"PRT","Portugal","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68415,620,"PRT","Portugal","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68416,620,"PRT","Portugal","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68417,620,"PRT","Portugal","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68418,620,"PRT","Portugal","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68419,620,"PRT","Portugal","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68420,620,"PRT","Portugal","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68421,620,"PRT","Portugal","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68422,620,"PRT","Portugal","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68423,620,"PRT","Portugal","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68424,620,"PRT","Portugal","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68425,620,"PRT","Portugal","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRT/prt_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68426,624,"GNB","Guinea-Bissau","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68427,624,"GNB","Guinea-Bissau","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68428,624,"GNB","Guinea-Bissau","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68429,624,"GNB","Guinea-Bissau","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68430,624,"GNB","Guinea-Bissau","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68431,624,"GNB","Guinea-Bissau","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68432,624,"GNB","Guinea-Bissau","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68433,624,"GNB","Guinea-Bissau","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68434,624,"GNB","Guinea-Bissau","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68435,624,"GNB","Guinea-Bissau","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68436,624,"GNB","Guinea-Bissau","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68437,624,"GNB","Guinea-Bissau","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68438,624,"GNB","Guinea-Bissau","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68439,624,"GNB","Guinea-Bissau","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68440,624,"GNB","Guinea-Bissau","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68441,624,"GNB","Guinea-Bissau","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68442,624,"GNB","Guinea-Bissau","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68443,624,"GNB","Guinea-Bissau","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68444,624,"GNB","Guinea-Bissau","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68445,624,"GNB","Guinea-Bissau","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68446,624,"GNB","Guinea-Bissau","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68447,624,"GNB","Guinea-Bissau","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68448,624,"GNB","Guinea-Bissau","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68449,624,"GNB","Guinea-Bissau","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68450,624,"GNB","Guinea-Bissau","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68451,624,"GNB","Guinea-Bissau","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68452,624,"GNB","Guinea-Bissau","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68453,624,"GNB","Guinea-Bissau","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68454,624,"GNB","Guinea-Bissau","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68455,624,"GNB","Guinea-Bissau","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68456,624,"GNB","Guinea-Bissau","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68457,624,"GNB","Guinea-Bissau","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68458,624,"GNB","Guinea-Bissau","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68459,624,"GNB","Guinea-Bissau","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68460,624,"GNB","Guinea-Bissau","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68461,624,"GNB","Guinea-Bissau","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GNB/gnb_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68462,626,"TLS","East Timor","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68463,626,"TLS","East Timor","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68464,626,"TLS","East Timor","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68465,626,"TLS","East Timor","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68466,626,"TLS","East Timor","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68467,626,"TLS","East Timor","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68468,626,"TLS","East Timor","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68469,626,"TLS","East Timor","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68470,626,"TLS","East Timor","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68471,626,"TLS","East Timor","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68472,626,"TLS","East Timor","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68473,626,"TLS","East Timor","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68474,626,"TLS","East Timor","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68475,626,"TLS","East Timor","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68476,626,"TLS","East Timor","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68477,626,"TLS","East Timor","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68478,626,"TLS","East Timor","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68479,626,"TLS","East Timor","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68480,626,"TLS","East Timor","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68481,626,"TLS","East Timor","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68482,626,"TLS","East Timor","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68483,626,"TLS","East Timor","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68484,626,"TLS","East Timor","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68485,626,"TLS","East Timor","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68486,626,"TLS","East Timor","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68487,626,"TLS","East Timor","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68488,626,"TLS","East Timor","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68489,626,"TLS","East Timor","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68490,626,"TLS","East Timor","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68491,626,"TLS","East Timor","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68492,626,"TLS","East Timor","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68493,626,"TLS","East Timor","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68494,626,"TLS","East Timor","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68495,626,"TLS","East Timor","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68496,626,"TLS","East Timor","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68497,626,"TLS","East Timor","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TLS/tls_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68498,630,"PRI","Puerto Rico","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68499,630,"PRI","Puerto Rico","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68500,630,"PRI","Puerto Rico","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68501,630,"PRI","Puerto Rico","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68502,630,"PRI","Puerto Rico","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68503,630,"PRI","Puerto Rico","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68504,630,"PRI","Puerto Rico","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68505,630,"PRI","Puerto Rico","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68506,630,"PRI","Puerto Rico","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68507,630,"PRI","Puerto Rico","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68508,630,"PRI","Puerto Rico","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68509,630,"PRI","Puerto Rico","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68510,630,"PRI","Puerto Rico","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68511,630,"PRI","Puerto Rico","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68512,630,"PRI","Puerto Rico","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68513,630,"PRI","Puerto Rico","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68514,630,"PRI","Puerto Rico","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68515,630,"PRI","Puerto Rico","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68516,630,"PRI","Puerto Rico","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68517,630,"PRI","Puerto Rico","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68518,630,"PRI","Puerto Rico","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68519,630,"PRI","Puerto Rico","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68520,630,"PRI","Puerto Rico","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68521,630,"PRI","Puerto Rico","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68522,630,"PRI","Puerto Rico","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68523,630,"PRI","Puerto Rico","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68524,630,"PRI","Puerto Rico","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68525,630,"PRI","Puerto Rico","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68526,630,"PRI","Puerto Rico","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68527,630,"PRI","Puerto Rico","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68528,630,"PRI","Puerto Rico","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68529,630,"PRI","Puerto Rico","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68530,630,"PRI","Puerto Rico","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68531,630,"PRI","Puerto Rico","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68532,630,"PRI","Puerto Rico","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68533,630,"PRI","Puerto Rico","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/PRI/pri_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68534,634,"QAT","Qatar","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68535,634,"QAT","Qatar","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68536,634,"QAT","Qatar","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68537,634,"QAT","Qatar","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68538,634,"QAT","Qatar","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68539,634,"QAT","Qatar","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68540,634,"QAT","Qatar","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68541,634,"QAT","Qatar","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68542,634,"QAT","Qatar","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68543,634,"QAT","Qatar","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68544,634,"QAT","Qatar","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68545,634,"QAT","Qatar","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68546,634,"QAT","Qatar","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68547,634,"QAT","Qatar","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68548,634,"QAT","Qatar","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68549,634,"QAT","Qatar","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68550,634,"QAT","Qatar","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68551,634,"QAT","Qatar","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68552,634,"QAT","Qatar","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68553,634,"QAT","Qatar","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68554,634,"QAT","Qatar","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68555,634,"QAT","Qatar","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68556,634,"QAT","Qatar","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68557,634,"QAT","Qatar","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68558,634,"QAT","Qatar","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68559,634,"QAT","Qatar","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68560,634,"QAT","Qatar","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68561,634,"QAT","Qatar","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68562,634,"QAT","Qatar","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68563,634,"QAT","Qatar","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68564,634,"QAT","Qatar","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68565,634,"QAT","Qatar","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68566,634,"QAT","Qatar","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68567,634,"QAT","Qatar","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68568,634,"QAT","Qatar","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68569,634,"QAT","Qatar","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/QAT/qat_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68570,638,"REU","Reunion","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68571,638,"REU","Reunion","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68572,638,"REU","Reunion","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68573,638,"REU","Reunion","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68574,638,"REU","Reunion","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68575,638,"REU","Reunion","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68576,638,"REU","Reunion","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68577,638,"REU","Reunion","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68578,638,"REU","Reunion","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68579,638,"REU","Reunion","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68580,638,"REU","Reunion","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68581,638,"REU","Reunion","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68582,638,"REU","Reunion","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68583,638,"REU","Reunion","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68584,638,"REU","Reunion","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68585,638,"REU","Reunion","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68586,638,"REU","Reunion","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68587,638,"REU","Reunion","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68588,638,"REU","Reunion","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68589,638,"REU","Reunion","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68590,638,"REU","Reunion","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68591,638,"REU","Reunion","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68592,638,"REU","Reunion","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68593,638,"REU","Reunion","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68594,638,"REU","Reunion","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68595,638,"REU","Reunion","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68596,638,"REU","Reunion","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68597,638,"REU","Reunion","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68598,638,"REU","Reunion","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68599,638,"REU","Reunion","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68600,638,"REU","Reunion","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68601,638,"REU","Reunion","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68602,638,"REU","Reunion","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68603,638,"REU","Reunion","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68604,638,"REU","Reunion","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68605,638,"REU","Reunion","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/REU/reu_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68606,642,"ROU","Romania","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68607,642,"ROU","Romania","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68608,642,"ROU","Romania","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68609,642,"ROU","Romania","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68610,642,"ROU","Romania","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68611,642,"ROU","Romania","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68612,642,"ROU","Romania","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68613,642,"ROU","Romania","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68614,642,"ROU","Romania","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68615,642,"ROU","Romania","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68616,642,"ROU","Romania","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68617,642,"ROU","Romania","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68618,642,"ROU","Romania","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68619,642,"ROU","Romania","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68620,642,"ROU","Romania","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68621,642,"ROU","Romania","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68622,642,"ROU","Romania","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68623,642,"ROU","Romania","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68624,642,"ROU","Romania","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68625,642,"ROU","Romania","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68626,642,"ROU","Romania","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68627,642,"ROU","Romania","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68628,642,"ROU","Romania","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68629,642,"ROU","Romania","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68630,642,"ROU","Romania","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68631,642,"ROU","Romania","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68632,642,"ROU","Romania","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68633,642,"ROU","Romania","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68634,642,"ROU","Romania","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68635,642,"ROU","Romania","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68636,642,"ROU","Romania","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68637,642,"ROU","Romania","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68638,642,"ROU","Romania","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68639,642,"ROU","Romania","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68640,642,"ROU","Romania","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68641,642,"ROU","Romania","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ROU/rou_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68642,646,"RWA","Rwanda","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68643,646,"RWA","Rwanda","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68644,646,"RWA","Rwanda","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68645,646,"RWA","Rwanda","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68646,646,"RWA","Rwanda","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68647,646,"RWA","Rwanda","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68648,646,"RWA","Rwanda","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68649,646,"RWA","Rwanda","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68650,646,"RWA","Rwanda","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68651,646,"RWA","Rwanda","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68652,646,"RWA","Rwanda","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68653,646,"RWA","Rwanda","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68654,646,"RWA","Rwanda","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68655,646,"RWA","Rwanda","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68656,646,"RWA","Rwanda","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68657,646,"RWA","Rwanda","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68658,646,"RWA","Rwanda","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68659,646,"RWA","Rwanda","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68660,646,"RWA","Rwanda","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68661,646,"RWA","Rwanda","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68662,646,"RWA","Rwanda","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68663,646,"RWA","Rwanda","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68664,646,"RWA","Rwanda","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68665,646,"RWA","Rwanda","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68666,646,"RWA","Rwanda","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68667,646,"RWA","Rwanda","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68668,646,"RWA","Rwanda","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68669,646,"RWA","Rwanda","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68670,646,"RWA","Rwanda","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68671,646,"RWA","Rwanda","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68672,646,"RWA","Rwanda","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68673,646,"RWA","Rwanda","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68674,646,"RWA","Rwanda","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68675,646,"RWA","Rwanda","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68676,646,"RWA","Rwanda","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68677,646,"RWA","Rwanda","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/RWA/rwa_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68678,652,"BLM","Saint Barthelemy","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68679,652,"BLM","Saint Barthelemy","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68680,652,"BLM","Saint Barthelemy","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68681,652,"BLM","Saint Barthelemy","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68682,652,"BLM","Saint Barthelemy","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68683,652,"BLM","Saint Barthelemy","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68684,652,"BLM","Saint Barthelemy","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68685,652,"BLM","Saint Barthelemy","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68686,652,"BLM","Saint Barthelemy","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68687,652,"BLM","Saint Barthelemy","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68688,652,"BLM","Saint Barthelemy","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68689,652,"BLM","Saint Barthelemy","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68690,652,"BLM","Saint Barthelemy","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68691,652,"BLM","Saint Barthelemy","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68692,652,"BLM","Saint Barthelemy","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68693,652,"BLM","Saint Barthelemy","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68694,652,"BLM","Saint Barthelemy","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68695,652,"BLM","Saint Barthelemy","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68696,652,"BLM","Saint Barthelemy","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68697,652,"BLM","Saint Barthelemy","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68698,652,"BLM","Saint Barthelemy","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68699,652,"BLM","Saint Barthelemy","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68700,652,"BLM","Saint Barthelemy","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68701,652,"BLM","Saint Barthelemy","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68702,652,"BLM","Saint Barthelemy","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68703,652,"BLM","Saint Barthelemy","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68704,652,"BLM","Saint Barthelemy","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68705,652,"BLM","Saint Barthelemy","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68706,652,"BLM","Saint Barthelemy","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68707,652,"BLM","Saint Barthelemy","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68708,652,"BLM","Saint Barthelemy","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68709,652,"BLM","Saint Barthelemy","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68710,652,"BLM","Saint Barthelemy","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68711,652,"BLM","Saint Barthelemy","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68712,652,"BLM","Saint Barthelemy","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68713,652,"BLM","Saint Barthelemy","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BLM/blm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68714,654,"SHN","Saint Helena","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68715,654,"SHN","Saint Helena","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68716,654,"SHN","Saint Helena","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68717,654,"SHN","Saint Helena","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68718,654,"SHN","Saint Helena","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68719,654,"SHN","Saint Helena","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68720,654,"SHN","Saint Helena","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68721,654,"SHN","Saint Helena","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68722,654,"SHN","Saint Helena","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68723,654,"SHN","Saint Helena","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68724,654,"SHN","Saint Helena","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68725,654,"SHN","Saint Helena","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68726,654,"SHN","Saint Helena","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68727,654,"SHN","Saint Helena","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68728,654,"SHN","Saint Helena","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68729,654,"SHN","Saint Helena","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68730,654,"SHN","Saint Helena","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68731,654,"SHN","Saint Helena","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68732,654,"SHN","Saint Helena","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68733,654,"SHN","Saint Helena","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68734,654,"SHN","Saint Helena","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68735,654,"SHN","Saint Helena","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68736,654,"SHN","Saint Helena","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68737,654,"SHN","Saint Helena","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68738,654,"SHN","Saint Helena","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68739,654,"SHN","Saint Helena","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68740,654,"SHN","Saint Helena","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68741,654,"SHN","Saint Helena","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68742,654,"SHN","Saint Helena","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68743,654,"SHN","Saint Helena","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68744,654,"SHN","Saint Helena","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68745,654,"SHN","Saint Helena","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68746,654,"SHN","Saint Helena","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68747,654,"SHN","Saint Helena","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68748,654,"SHN","Saint Helena","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68749,654,"SHN","Saint Helena","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SHN/shn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68750,659,"KNA","Saint Kitts and Nevis","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68751,659,"KNA","Saint Kitts and Nevis","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68752,659,"KNA","Saint Kitts and Nevis","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68753,659,"KNA","Saint Kitts and Nevis","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68754,659,"KNA","Saint Kitts and Nevis","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68755,659,"KNA","Saint Kitts and Nevis","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68756,659,"KNA","Saint Kitts and Nevis","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68757,659,"KNA","Saint Kitts and Nevis","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68758,659,"KNA","Saint Kitts and Nevis","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68759,659,"KNA","Saint Kitts and Nevis","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68760,659,"KNA","Saint Kitts and Nevis","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68761,659,"KNA","Saint Kitts and Nevis","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68762,659,"KNA","Saint Kitts and Nevis","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68763,659,"KNA","Saint Kitts and Nevis","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68764,659,"KNA","Saint Kitts and Nevis","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68765,659,"KNA","Saint Kitts and Nevis","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68766,659,"KNA","Saint Kitts and Nevis","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68767,659,"KNA","Saint Kitts and Nevis","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68768,659,"KNA","Saint Kitts and Nevis","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68769,659,"KNA","Saint Kitts and Nevis","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68770,659,"KNA","Saint Kitts and Nevis","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68771,659,"KNA","Saint Kitts and Nevis","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68772,659,"KNA","Saint Kitts and Nevis","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68773,659,"KNA","Saint Kitts and Nevis","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68774,659,"KNA","Saint Kitts and Nevis","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68775,659,"KNA","Saint Kitts and Nevis","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68776,659,"KNA","Saint Kitts and Nevis","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68777,659,"KNA","Saint Kitts and Nevis","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68778,659,"KNA","Saint Kitts and Nevis","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68779,659,"KNA","Saint Kitts and Nevis","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68780,659,"KNA","Saint Kitts and Nevis","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68781,659,"KNA","Saint Kitts and Nevis","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68782,659,"KNA","Saint Kitts and Nevis","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68783,659,"KNA","Saint Kitts and Nevis","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68784,659,"KNA","Saint Kitts and Nevis","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68785,659,"KNA","Saint Kitts and Nevis","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KNA/kna_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68786,660,"AIA","Anguilla","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68787,660,"AIA","Anguilla","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68788,660,"AIA","Anguilla","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68789,660,"AIA","Anguilla","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68790,660,"AIA","Anguilla","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68791,660,"AIA","Anguilla","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68792,660,"AIA","Anguilla","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68793,660,"AIA","Anguilla","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68794,660,"AIA","Anguilla","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68795,660,"AIA","Anguilla","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68796,660,"AIA","Anguilla","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68797,660,"AIA","Anguilla","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68798,660,"AIA","Anguilla","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68799,660,"AIA","Anguilla","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68800,660,"AIA","Anguilla","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68801,660,"AIA","Anguilla","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68802,660,"AIA","Anguilla","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68803,660,"AIA","Anguilla","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68804,660,"AIA","Anguilla","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68805,660,"AIA","Anguilla","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68806,660,"AIA","Anguilla","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68807,660,"AIA","Anguilla","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68808,660,"AIA","Anguilla","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68809,660,"AIA","Anguilla","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68810,660,"AIA","Anguilla","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68811,660,"AIA","Anguilla","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68812,660,"AIA","Anguilla","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68813,660,"AIA","Anguilla","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68814,660,"AIA","Anguilla","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68815,660,"AIA","Anguilla","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68816,660,"AIA","Anguilla","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68817,660,"AIA","Anguilla","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68818,660,"AIA","Anguilla","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68819,660,"AIA","Anguilla","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68820,660,"AIA","Anguilla","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68821,660,"AIA","Anguilla","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/AIA/aia_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68822,662,"LCA","Saint Lucia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68823,662,"LCA","Saint Lucia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68824,662,"LCA","Saint Lucia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68825,662,"LCA","Saint Lucia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68826,662,"LCA","Saint Lucia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68827,662,"LCA","Saint Lucia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68828,662,"LCA","Saint Lucia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68829,662,"LCA","Saint Lucia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68830,662,"LCA","Saint Lucia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68831,662,"LCA","Saint Lucia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68832,662,"LCA","Saint Lucia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68833,662,"LCA","Saint Lucia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68834,662,"LCA","Saint Lucia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68835,662,"LCA","Saint Lucia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68836,662,"LCA","Saint Lucia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68837,662,"LCA","Saint Lucia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68838,662,"LCA","Saint Lucia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68839,662,"LCA","Saint Lucia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68840,662,"LCA","Saint Lucia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68841,662,"LCA","Saint Lucia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68842,662,"LCA","Saint Lucia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68843,662,"LCA","Saint Lucia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68844,662,"LCA","Saint Lucia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68845,662,"LCA","Saint Lucia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68846,662,"LCA","Saint Lucia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68847,662,"LCA","Saint Lucia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68848,662,"LCA","Saint Lucia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68849,662,"LCA","Saint Lucia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68850,662,"LCA","Saint Lucia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68851,662,"LCA","Saint Lucia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68852,662,"LCA","Saint Lucia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68853,662,"LCA","Saint Lucia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68854,662,"LCA","Saint Lucia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68855,662,"LCA","Saint Lucia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68856,662,"LCA","Saint Lucia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68857,662,"LCA","Saint Lucia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/LCA/lca_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68858,663,"MAF","Saint Martin (French part)","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68859,663,"MAF","Saint Martin (French part)","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68860,663,"MAF","Saint Martin (French part)","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68861,663,"MAF","Saint Martin (French part)","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68862,663,"MAF","Saint Martin (French part)","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68863,663,"MAF","Saint Martin (French part)","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68864,663,"MAF","Saint Martin (French part)","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68865,663,"MAF","Saint Martin (French part)","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68866,663,"MAF","Saint Martin (French part)","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68867,663,"MAF","Saint Martin (French part)","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68868,663,"MAF","Saint Martin (French part)","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68869,663,"MAF","Saint Martin (French part)","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68870,663,"MAF","Saint Martin (French part)","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68871,663,"MAF","Saint Martin (French part)","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68872,663,"MAF","Saint Martin (French part)","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68873,663,"MAF","Saint Martin (French part)","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68874,663,"MAF","Saint Martin (French part)","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68875,663,"MAF","Saint Martin (French part)","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68876,663,"MAF","Saint Martin (French part)","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68877,663,"MAF","Saint Martin (French part)","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68878,663,"MAF","Saint Martin (French part)","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68879,663,"MAF","Saint Martin (French part)","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68880,663,"MAF","Saint Martin (French part)","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68881,663,"MAF","Saint Martin (French part)","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68882,663,"MAF","Saint Martin (French part)","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68883,663,"MAF","Saint Martin (French part)","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68884,663,"MAF","Saint Martin (French part)","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68885,663,"MAF","Saint Martin (French part)","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68886,663,"MAF","Saint Martin (French part)","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68887,663,"MAF","Saint Martin (French part)","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68888,663,"MAF","Saint Martin (French part)","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68889,663,"MAF","Saint Martin (French part)","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68890,663,"MAF","Saint Martin (French part)","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68891,663,"MAF","Saint Martin (French part)","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68892,663,"MAF","Saint Martin (French part)","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68893,663,"MAF","Saint Martin (French part)","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MAF/maf_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68894,666,"SPM","Saint Pierre and Miquelon","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68895,666,"SPM","Saint Pierre and Miquelon","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68896,666,"SPM","Saint Pierre and Miquelon","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68897,666,"SPM","Saint Pierre and Miquelon","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68898,666,"SPM","Saint Pierre and Miquelon","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68899,666,"SPM","Saint Pierre and Miquelon","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68900,666,"SPM","Saint Pierre and Miquelon","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68901,666,"SPM","Saint Pierre and Miquelon","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68902,666,"SPM","Saint Pierre and Miquelon","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68903,666,"SPM","Saint Pierre and Miquelon","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68904,666,"SPM","Saint Pierre and Miquelon","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68905,666,"SPM","Saint Pierre and Miquelon","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68906,666,"SPM","Saint Pierre and Miquelon","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68907,666,"SPM","Saint Pierre and Miquelon","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68908,666,"SPM","Saint Pierre and Miquelon","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68909,666,"SPM","Saint Pierre and Miquelon","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68910,666,"SPM","Saint Pierre and Miquelon","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68911,666,"SPM","Saint Pierre and Miquelon","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68912,666,"SPM","Saint Pierre and Miquelon","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68913,666,"SPM","Saint Pierre and Miquelon","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68914,666,"SPM","Saint Pierre and Miquelon","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68915,666,"SPM","Saint Pierre and Miquelon","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68916,666,"SPM","Saint Pierre and Miquelon","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68917,666,"SPM","Saint Pierre and Miquelon","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68918,666,"SPM","Saint Pierre and Miquelon","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68919,666,"SPM","Saint Pierre and Miquelon","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68920,666,"SPM","Saint Pierre and Miquelon","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68921,666,"SPM","Saint Pierre and Miquelon","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68922,666,"SPM","Saint Pierre and Miquelon","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68923,666,"SPM","Saint Pierre and Miquelon","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68924,666,"SPM","Saint Pierre and Miquelon","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68925,666,"SPM","Saint Pierre and Miquelon","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68926,666,"SPM","Saint Pierre and Miquelon","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68927,666,"SPM","Saint Pierre and Miquelon","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68928,666,"SPM","Saint Pierre and Miquelon","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68929,666,"SPM","Saint Pierre and Miquelon","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPM/spm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68930,670,"VCT","Saint Vincent and the Grenadines","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68931,670,"VCT","Saint Vincent and the Grenadines","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68932,670,"VCT","Saint Vincent and the Grenadines","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68933,670,"VCT","Saint Vincent and the Grenadines","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68934,670,"VCT","Saint Vincent and the Grenadines","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68935,670,"VCT","Saint Vincent and the Grenadines","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68936,670,"VCT","Saint Vincent and the Grenadines","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68937,670,"VCT","Saint Vincent and the Grenadines","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68938,670,"VCT","Saint Vincent and the Grenadines","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68939,670,"VCT","Saint Vincent and the Grenadines","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68940,670,"VCT","Saint Vincent and the Grenadines","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68941,670,"VCT","Saint Vincent and the Grenadines","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68942,670,"VCT","Saint Vincent and the Grenadines","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68943,670,"VCT","Saint Vincent and the Grenadines","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68944,670,"VCT","Saint Vincent and the Grenadines","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68945,670,"VCT","Saint Vincent and the Grenadines","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68946,670,"VCT","Saint Vincent and the Grenadines","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68947,670,"VCT","Saint Vincent and the Grenadines","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68948,670,"VCT","Saint Vincent and the Grenadines","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68949,670,"VCT","Saint Vincent and the Grenadines","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68950,670,"VCT","Saint Vincent and the Grenadines","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68951,670,"VCT","Saint Vincent and the Grenadines","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68952,670,"VCT","Saint Vincent and the Grenadines","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68953,670,"VCT","Saint Vincent and the Grenadines","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68954,670,"VCT","Saint Vincent and the Grenadines","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68955,670,"VCT","Saint Vincent and the Grenadines","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68956,670,"VCT","Saint Vincent and the Grenadines","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68957,670,"VCT","Saint Vincent and the Grenadines","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68958,670,"VCT","Saint Vincent and the Grenadines","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68959,670,"VCT","Saint Vincent and the Grenadines","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68960,670,"VCT","Saint Vincent and the Grenadines","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68961,670,"VCT","Saint Vincent and the Grenadines","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68962,670,"VCT","Saint Vincent and the Grenadines","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68963,670,"VCT","Saint Vincent and the Grenadines","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
68964,670,"VCT","Saint Vincent and the Grenadines","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
68965,670,"VCT","Saint Vincent and the Grenadines","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VCT/vct_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
68966,674,"SMR","San Marino","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
68967,674,"SMR","San Marino","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
68968,674,"SMR","San Marino","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
68969,674,"SMR","San Marino","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
68970,674,"SMR","San Marino","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
68971,674,"SMR","San Marino","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
68972,674,"SMR","San Marino","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
68973,674,"SMR","San Marino","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
68974,674,"SMR","San Marino","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
68975,674,"SMR","San Marino","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
68976,674,"SMR","San Marino","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
68977,674,"SMR","San Marino","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
68978,674,"SMR","San Marino","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
68979,674,"SMR","San Marino","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
68980,674,"SMR","San Marino","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
68981,674,"SMR","San Marino","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
68982,674,"SMR","San Marino","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
68983,674,"SMR","San Marino","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
68984,674,"SMR","San Marino","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
68985,674,"SMR","San Marino","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
68986,674,"SMR","San Marino","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
68987,674,"SMR","San Marino","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
68988,674,"SMR","San Marino","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
68989,674,"SMR","San Marino","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
68990,674,"SMR","San Marino","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
68991,674,"SMR","San Marino","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
68992,674,"SMR","San Marino","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
68993,674,"SMR","San Marino","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
68994,674,"SMR","San Marino","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
68995,674,"SMR","San Marino","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
68996,674,"SMR","San Marino","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
68997,674,"SMR","San Marino","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
68998,674,"SMR","San Marino","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
68999,674,"SMR","San Marino","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69000,674,"SMR","San Marino","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69001,674,"SMR","San Marino","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SMR/smr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69002,678,"STP","Sao Tome and Principe","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69003,678,"STP","Sao Tome and Principe","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69004,678,"STP","Sao Tome and Principe","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69005,678,"STP","Sao Tome and Principe","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69006,678,"STP","Sao Tome and Principe","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69007,678,"STP","Sao Tome and Principe","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69008,678,"STP","Sao Tome and Principe","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69009,678,"STP","Sao Tome and Principe","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69010,678,"STP","Sao Tome and Principe","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69011,678,"STP","Sao Tome and Principe","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69012,678,"STP","Sao Tome and Principe","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69013,678,"STP","Sao Tome and Principe","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69014,678,"STP","Sao Tome and Principe","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69015,678,"STP","Sao Tome and Principe","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69016,678,"STP","Sao Tome and Principe","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69017,678,"STP","Sao Tome and Principe","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69018,678,"STP","Sao Tome and Principe","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69019,678,"STP","Sao Tome and Principe","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69020,678,"STP","Sao Tome and Principe","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69021,678,"STP","Sao Tome and Principe","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69022,678,"STP","Sao Tome and Principe","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69023,678,"STP","Sao Tome and Principe","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69024,678,"STP","Sao Tome and Principe","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69025,678,"STP","Sao Tome and Principe","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69026,678,"STP","Sao Tome and Principe","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69027,678,"STP","Sao Tome and Principe","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69028,678,"STP","Sao Tome and Principe","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69029,678,"STP","Sao Tome and Principe","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69030,678,"STP","Sao Tome and Principe","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69031,678,"STP","Sao Tome and Principe","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69032,678,"STP","Sao Tome and Principe","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69033,678,"STP","Sao Tome and Principe","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69034,678,"STP","Sao Tome and Principe","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69035,678,"STP","Sao Tome and Principe","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69036,678,"STP","Sao Tome and Principe","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69037,678,"STP","Sao Tome and Principe","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/STP/stp_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69038,682,"SAU","Saudi Arabia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69039,682,"SAU","Saudi Arabia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69040,682,"SAU","Saudi Arabia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69041,682,"SAU","Saudi Arabia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69042,682,"SAU","Saudi Arabia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69043,682,"SAU","Saudi Arabia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69044,682,"SAU","Saudi Arabia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69045,682,"SAU","Saudi Arabia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69046,682,"SAU","Saudi Arabia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69047,682,"SAU","Saudi Arabia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69048,682,"SAU","Saudi Arabia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69049,682,"SAU","Saudi Arabia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69050,682,"SAU","Saudi Arabia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69051,682,"SAU","Saudi Arabia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69052,682,"SAU","Saudi Arabia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69053,682,"SAU","Saudi Arabia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69054,682,"SAU","Saudi Arabia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69055,682,"SAU","Saudi Arabia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69056,682,"SAU","Saudi Arabia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69057,682,"SAU","Saudi Arabia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69058,682,"SAU","Saudi Arabia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69059,682,"SAU","Saudi Arabia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69060,682,"SAU","Saudi Arabia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69061,682,"SAU","Saudi Arabia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69062,682,"SAU","Saudi Arabia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69063,682,"SAU","Saudi Arabia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69064,682,"SAU","Saudi Arabia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69065,682,"SAU","Saudi Arabia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69066,682,"SAU","Saudi Arabia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69067,682,"SAU","Saudi Arabia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69068,682,"SAU","Saudi Arabia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69069,682,"SAU","Saudi Arabia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69070,682,"SAU","Saudi Arabia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69071,682,"SAU","Saudi Arabia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69072,682,"SAU","Saudi Arabia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69073,682,"SAU","Saudi Arabia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SAU/sau_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69074,686,"SEN","Senegal","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69075,686,"SEN","Senegal","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69076,686,"SEN","Senegal","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69077,686,"SEN","Senegal","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69078,686,"SEN","Senegal","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69079,686,"SEN","Senegal","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69080,686,"SEN","Senegal","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69081,686,"SEN","Senegal","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69082,686,"SEN","Senegal","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69083,686,"SEN","Senegal","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69084,686,"SEN","Senegal","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69085,686,"SEN","Senegal","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69086,686,"SEN","Senegal","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69087,686,"SEN","Senegal","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69088,686,"SEN","Senegal","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69089,686,"SEN","Senegal","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69090,686,"SEN","Senegal","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69091,686,"SEN","Senegal","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69092,686,"SEN","Senegal","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69093,686,"SEN","Senegal","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69094,686,"SEN","Senegal","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69095,686,"SEN","Senegal","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69096,686,"SEN","Senegal","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69097,686,"SEN","Senegal","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69098,686,"SEN","Senegal","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69099,686,"SEN","Senegal","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69100,686,"SEN","Senegal","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69101,686,"SEN","Senegal","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69102,686,"SEN","Senegal","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69103,686,"SEN","Senegal","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69104,686,"SEN","Senegal","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69105,686,"SEN","Senegal","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69106,686,"SEN","Senegal","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69107,686,"SEN","Senegal","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69108,686,"SEN","Senegal","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69109,686,"SEN","Senegal","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SEN/sen_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69110,688,"SRB","Serbia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69111,688,"SRB","Serbia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69112,688,"SRB","Serbia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69113,688,"SRB","Serbia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69114,688,"SRB","Serbia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69115,688,"SRB","Serbia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69116,688,"SRB","Serbia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69117,688,"SRB","Serbia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69118,688,"SRB","Serbia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69119,688,"SRB","Serbia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69120,688,"SRB","Serbia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69121,688,"SRB","Serbia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69122,688,"SRB","Serbia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69123,688,"SRB","Serbia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69124,688,"SRB","Serbia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69125,688,"SRB","Serbia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69126,688,"SRB","Serbia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69127,688,"SRB","Serbia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69128,688,"SRB","Serbia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69129,688,"SRB","Serbia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69130,688,"SRB","Serbia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69131,688,"SRB","Serbia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69132,688,"SRB","Serbia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69133,688,"SRB","Serbia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69134,688,"SRB","Serbia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69135,688,"SRB","Serbia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69136,688,"SRB","Serbia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69137,688,"SRB","Serbia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69138,688,"SRB","Serbia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69139,688,"SRB","Serbia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69140,688,"SRB","Serbia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69141,688,"SRB","Serbia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69142,688,"SRB","Serbia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69143,688,"SRB","Serbia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69144,688,"SRB","Serbia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69145,688,"SRB","Serbia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SRB/srb_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69146,690,"SYC","Seychelles","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69147,690,"SYC","Seychelles","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69148,690,"SYC","Seychelles","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69149,690,"SYC","Seychelles","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69150,690,"SYC","Seychelles","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69151,690,"SYC","Seychelles","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69152,690,"SYC","Seychelles","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69153,690,"SYC","Seychelles","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69154,690,"SYC","Seychelles","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69155,690,"SYC","Seychelles","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69156,690,"SYC","Seychelles","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69157,690,"SYC","Seychelles","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69158,690,"SYC","Seychelles","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69159,690,"SYC","Seychelles","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69160,690,"SYC","Seychelles","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69161,690,"SYC","Seychelles","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69162,690,"SYC","Seychelles","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69163,690,"SYC","Seychelles","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69164,690,"SYC","Seychelles","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69165,690,"SYC","Seychelles","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69166,690,"SYC","Seychelles","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69167,690,"SYC","Seychelles","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69168,690,"SYC","Seychelles","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69169,690,"SYC","Seychelles","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69170,690,"SYC","Seychelles","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69171,690,"SYC","Seychelles","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69172,690,"SYC","Seychelles","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69173,690,"SYC","Seychelles","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69174,690,"SYC","Seychelles","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69175,690,"SYC","Seychelles","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69176,690,"SYC","Seychelles","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69177,690,"SYC","Seychelles","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69178,690,"SYC","Seychelles","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69179,690,"SYC","Seychelles","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69180,690,"SYC","Seychelles","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69181,690,"SYC","Seychelles","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYC/syc_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69182,694,"SLE","Sierra Leone","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69183,694,"SLE","Sierra Leone","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69184,694,"SLE","Sierra Leone","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69185,694,"SLE","Sierra Leone","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69186,694,"SLE","Sierra Leone","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69187,694,"SLE","Sierra Leone","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69188,694,"SLE","Sierra Leone","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69189,694,"SLE","Sierra Leone","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69190,694,"SLE","Sierra Leone","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69191,694,"SLE","Sierra Leone","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69192,694,"SLE","Sierra Leone","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69193,694,"SLE","Sierra Leone","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69194,694,"SLE","Sierra Leone","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69195,694,"SLE","Sierra Leone","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69196,694,"SLE","Sierra Leone","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69197,694,"SLE","Sierra Leone","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69198,694,"SLE","Sierra Leone","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69199,694,"SLE","Sierra Leone","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69200,694,"SLE","Sierra Leone","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69201,694,"SLE","Sierra Leone","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69202,694,"SLE","Sierra Leone","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69203,694,"SLE","Sierra Leone","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69204,694,"SLE","Sierra Leone","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69205,694,"SLE","Sierra Leone","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69206,694,"SLE","Sierra Leone","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69207,694,"SLE","Sierra Leone","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69208,694,"SLE","Sierra Leone","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69209,694,"SLE","Sierra Leone","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69210,694,"SLE","Sierra Leone","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69211,694,"SLE","Sierra Leone","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69212,694,"SLE","Sierra Leone","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69213,694,"SLE","Sierra Leone","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69214,694,"SLE","Sierra Leone","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69215,694,"SLE","Sierra Leone","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69216,694,"SLE","Sierra Leone","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69217,694,"SLE","Sierra Leone","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SLE/sle_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69218,702,"SGP","Singapore","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69219,702,"SGP","Singapore","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69220,702,"SGP","Singapore","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69221,702,"SGP","Singapore","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69222,702,"SGP","Singapore","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69223,702,"SGP","Singapore","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69224,702,"SGP","Singapore","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69225,702,"SGP","Singapore","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69226,702,"SGP","Singapore","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69227,702,"SGP","Singapore","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69228,702,"SGP","Singapore","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69229,702,"SGP","Singapore","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69230,702,"SGP","Singapore","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69231,702,"SGP","Singapore","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69232,702,"SGP","Singapore","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69233,702,"SGP","Singapore","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69234,702,"SGP","Singapore","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69235,702,"SGP","Singapore","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69236,702,"SGP","Singapore","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69237,702,"SGP","Singapore","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69238,702,"SGP","Singapore","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69239,702,"SGP","Singapore","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69240,702,"SGP","Singapore","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69241,702,"SGP","Singapore","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69242,702,"SGP","Singapore","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69243,702,"SGP","Singapore","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69244,702,"SGP","Singapore","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69245,702,"SGP","Singapore","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69246,702,"SGP","Singapore","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69247,702,"SGP","Singapore","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69248,702,"SGP","Singapore","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69249,702,"SGP","Singapore","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69250,702,"SGP","Singapore","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69251,702,"SGP","Singapore","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69252,702,"SGP","Singapore","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69253,702,"SGP","Singapore","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SGP/sgp_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69254,703,"SVK","Slovakia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69255,703,"SVK","Slovakia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69256,703,"SVK","Slovakia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69257,703,"SVK","Slovakia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69258,703,"SVK","Slovakia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69259,703,"SVK","Slovakia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69260,703,"SVK","Slovakia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69261,703,"SVK","Slovakia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69262,703,"SVK","Slovakia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69263,703,"SVK","Slovakia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69264,703,"SVK","Slovakia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69265,703,"SVK","Slovakia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69266,703,"SVK","Slovakia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69267,703,"SVK","Slovakia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69268,703,"SVK","Slovakia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69269,703,"SVK","Slovakia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69270,703,"SVK","Slovakia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69271,703,"SVK","Slovakia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69272,703,"SVK","Slovakia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69273,703,"SVK","Slovakia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69274,703,"SVK","Slovakia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69275,703,"SVK","Slovakia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69276,703,"SVK","Slovakia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69277,703,"SVK","Slovakia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69278,703,"SVK","Slovakia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69279,703,"SVK","Slovakia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69280,703,"SVK","Slovakia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69281,703,"SVK","Slovakia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69282,703,"SVK","Slovakia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69283,703,"SVK","Slovakia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69284,703,"SVK","Slovakia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69285,703,"SVK","Slovakia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69286,703,"SVK","Slovakia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69287,703,"SVK","Slovakia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69288,703,"SVK","Slovakia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69289,703,"SVK","Slovakia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVK/svk_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69290,704,"VNM","Vietnam","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69291,704,"VNM","Vietnam","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69292,704,"VNM","Vietnam","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69293,704,"VNM","Vietnam","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69294,704,"VNM","Vietnam","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69295,704,"VNM","Vietnam","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69296,704,"VNM","Vietnam","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69297,704,"VNM","Vietnam","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69298,704,"VNM","Vietnam","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69299,704,"VNM","Vietnam","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69300,704,"VNM","Vietnam","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69301,704,"VNM","Vietnam","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69302,704,"VNM","Vietnam","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69303,704,"VNM","Vietnam","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69304,704,"VNM","Vietnam","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69305,704,"VNM","Vietnam","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69306,704,"VNM","Vietnam","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69307,704,"VNM","Vietnam","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69308,704,"VNM","Vietnam","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69309,704,"VNM","Vietnam","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69310,704,"VNM","Vietnam","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69311,704,"VNM","Vietnam","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69312,704,"VNM","Vietnam","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69313,704,"VNM","Vietnam","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69314,704,"VNM","Vietnam","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69315,704,"VNM","Vietnam","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69316,704,"VNM","Vietnam","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69317,704,"VNM","Vietnam","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69318,704,"VNM","Vietnam","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69319,704,"VNM","Vietnam","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69320,704,"VNM","Vietnam","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69321,704,"VNM","Vietnam","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69322,704,"VNM","Vietnam","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69323,704,"VNM","Vietnam","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69324,704,"VNM","Vietnam","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69325,704,"VNM","Vietnam","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VNM/vnm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69326,705,"SVN","Slovenia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69327,705,"SVN","Slovenia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69328,705,"SVN","Slovenia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69329,705,"SVN","Slovenia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69330,705,"SVN","Slovenia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69331,705,"SVN","Slovenia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69332,705,"SVN","Slovenia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69333,705,"SVN","Slovenia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69334,705,"SVN","Slovenia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69335,705,"SVN","Slovenia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69336,705,"SVN","Slovenia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69337,705,"SVN","Slovenia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69338,705,"SVN","Slovenia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69339,705,"SVN","Slovenia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69340,705,"SVN","Slovenia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69341,705,"SVN","Slovenia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69342,705,"SVN","Slovenia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69343,705,"SVN","Slovenia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69344,705,"SVN","Slovenia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69345,705,"SVN","Slovenia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69346,705,"SVN","Slovenia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69347,705,"SVN","Slovenia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69348,705,"SVN","Slovenia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69349,705,"SVN","Slovenia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69350,705,"SVN","Slovenia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69351,705,"SVN","Slovenia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69352,705,"SVN","Slovenia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69353,705,"SVN","Slovenia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69354,705,"SVN","Slovenia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69355,705,"SVN","Slovenia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69356,705,"SVN","Slovenia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69357,705,"SVN","Slovenia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69358,705,"SVN","Slovenia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69359,705,"SVN","Slovenia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69360,705,"SVN","Slovenia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69361,705,"SVN","Slovenia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SVN/svn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69362,706,"SOM","Somalia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69363,706,"SOM","Somalia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69364,706,"SOM","Somalia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69365,706,"SOM","Somalia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69366,706,"SOM","Somalia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69367,706,"SOM","Somalia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69368,706,"SOM","Somalia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69369,706,"SOM","Somalia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69370,706,"SOM","Somalia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69371,706,"SOM","Somalia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69372,706,"SOM","Somalia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69373,706,"SOM","Somalia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69374,706,"SOM","Somalia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69375,706,"SOM","Somalia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69376,706,"SOM","Somalia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69377,706,"SOM","Somalia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69378,706,"SOM","Somalia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69379,706,"SOM","Somalia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69380,706,"SOM","Somalia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69381,706,"SOM","Somalia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69382,706,"SOM","Somalia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69383,706,"SOM","Somalia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69384,706,"SOM","Somalia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69385,706,"SOM","Somalia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69386,706,"SOM","Somalia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69387,706,"SOM","Somalia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69388,706,"SOM","Somalia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69389,706,"SOM","Somalia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69390,706,"SOM","Somalia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69391,706,"SOM","Somalia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69392,706,"SOM","Somalia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69393,706,"SOM","Somalia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69394,706,"SOM","Somalia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69395,706,"SOM","Somalia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69396,706,"SOM","Somalia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69397,706,"SOM","Somalia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SOM/som_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69398,710,"ZAF","South Africa","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69399,710,"ZAF","South Africa","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69400,710,"ZAF","South Africa","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69401,710,"ZAF","South Africa","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69402,710,"ZAF","South Africa","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69403,710,"ZAF","South Africa","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69404,710,"ZAF","South Africa","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69405,710,"ZAF","South Africa","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69406,710,"ZAF","South Africa","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69407,710,"ZAF","South Africa","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69408,710,"ZAF","South Africa","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69409,710,"ZAF","South Africa","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69410,710,"ZAF","South Africa","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69411,710,"ZAF","South Africa","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69412,710,"ZAF","South Africa","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69413,710,"ZAF","South Africa","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69414,710,"ZAF","South Africa","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69415,710,"ZAF","South Africa","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69416,710,"ZAF","South Africa","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69417,710,"ZAF","South Africa","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69418,710,"ZAF","South Africa","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69419,710,"ZAF","South Africa","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69420,710,"ZAF","South Africa","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69421,710,"ZAF","South Africa","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69422,710,"ZAF","South Africa","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69423,710,"ZAF","South Africa","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69424,710,"ZAF","South Africa","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69425,710,"ZAF","South Africa","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69426,710,"ZAF","South Africa","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69427,710,"ZAF","South Africa","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69428,710,"ZAF","South Africa","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69429,710,"ZAF","South Africa","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69430,710,"ZAF","South Africa","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69431,710,"ZAF","South Africa","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69432,710,"ZAF","South Africa","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69433,710,"ZAF","South Africa","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZAF/zaf_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69434,716,"ZWE","Zimbabwe","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69435,716,"ZWE","Zimbabwe","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69436,716,"ZWE","Zimbabwe","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69437,716,"ZWE","Zimbabwe","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69438,716,"ZWE","Zimbabwe","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69439,716,"ZWE","Zimbabwe","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69440,716,"ZWE","Zimbabwe","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69441,716,"ZWE","Zimbabwe","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69442,716,"ZWE","Zimbabwe","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69443,716,"ZWE","Zimbabwe","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69444,716,"ZWE","Zimbabwe","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69445,716,"ZWE","Zimbabwe","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69446,716,"ZWE","Zimbabwe","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69447,716,"ZWE","Zimbabwe","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69448,716,"ZWE","Zimbabwe","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69449,716,"ZWE","Zimbabwe","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69450,716,"ZWE","Zimbabwe","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69451,716,"ZWE","Zimbabwe","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69452,716,"ZWE","Zimbabwe","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69453,716,"ZWE","Zimbabwe","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69454,716,"ZWE","Zimbabwe","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69455,716,"ZWE","Zimbabwe","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69456,716,"ZWE","Zimbabwe","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69457,716,"ZWE","Zimbabwe","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69458,716,"ZWE","Zimbabwe","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69459,716,"ZWE","Zimbabwe","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69460,716,"ZWE","Zimbabwe","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69461,716,"ZWE","Zimbabwe","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69462,716,"ZWE","Zimbabwe","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69463,716,"ZWE","Zimbabwe","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69464,716,"ZWE","Zimbabwe","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69465,716,"ZWE","Zimbabwe","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69466,716,"ZWE","Zimbabwe","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69467,716,"ZWE","Zimbabwe","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69468,716,"ZWE","Zimbabwe","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69469,716,"ZWE","Zimbabwe","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZWE/zwe_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69470,724,"ESP","Spain","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69471,724,"ESP","Spain","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69472,724,"ESP","Spain","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69473,724,"ESP","Spain","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69474,724,"ESP","Spain","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69475,724,"ESP","Spain","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69476,724,"ESP","Spain","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69477,724,"ESP","Spain","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69478,724,"ESP","Spain","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69479,724,"ESP","Spain","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69480,724,"ESP","Spain","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69481,724,"ESP","Spain","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69482,724,"ESP","Spain","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69483,724,"ESP","Spain","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69484,724,"ESP","Spain","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69485,724,"ESP","Spain","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69486,724,"ESP","Spain","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69487,724,"ESP","Spain","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69488,724,"ESP","Spain","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69489,724,"ESP","Spain","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69490,724,"ESP","Spain","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69491,724,"ESP","Spain","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69492,724,"ESP","Spain","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69493,724,"ESP","Spain","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69494,724,"ESP","Spain","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69495,724,"ESP","Spain","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69496,724,"ESP","Spain","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69497,724,"ESP","Spain","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69498,724,"ESP","Spain","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69499,724,"ESP","Spain","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69500,724,"ESP","Spain","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69501,724,"ESP","Spain","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69502,724,"ESP","Spain","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69503,724,"ESP","Spain","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69504,724,"ESP","Spain","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69505,724,"ESP","Spain","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESP/esp_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69506,728,"SSD","South Sudan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69507,728,"SSD","South Sudan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69508,728,"SSD","South Sudan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69509,728,"SSD","South Sudan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69510,728,"SSD","South Sudan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69511,728,"SSD","South Sudan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69512,728,"SSD","South Sudan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69513,728,"SSD","South Sudan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69514,728,"SSD","South Sudan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69515,728,"SSD","South Sudan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69516,728,"SSD","South Sudan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69517,728,"SSD","South Sudan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69518,728,"SSD","South Sudan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69519,728,"SSD","South Sudan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69520,728,"SSD","South Sudan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69521,728,"SSD","South Sudan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69522,728,"SSD","South Sudan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69523,728,"SSD","South Sudan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69524,728,"SSD","South Sudan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69525,728,"SSD","South Sudan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69526,728,"SSD","South Sudan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69527,728,"SSD","South Sudan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69528,728,"SSD","South Sudan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69529,728,"SSD","South Sudan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69530,728,"SSD","South Sudan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69531,728,"SSD","South Sudan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69532,728,"SSD","South Sudan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69533,728,"SSD","South Sudan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69534,728,"SSD","South Sudan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69535,728,"SSD","South Sudan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69536,728,"SSD","South Sudan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69537,728,"SSD","South Sudan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69538,728,"SSD","South Sudan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69539,728,"SSD","South Sudan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69540,728,"SSD","South Sudan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69541,728,"SSD","South Sudan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SSD/ssd_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69542,729,"SDN","Sudan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69543,729,"SDN","Sudan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69544,729,"SDN","Sudan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69545,729,"SDN","Sudan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69546,729,"SDN","Sudan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69547,729,"SDN","Sudan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69548,729,"SDN","Sudan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69549,729,"SDN","Sudan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69550,729,"SDN","Sudan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69551,729,"SDN","Sudan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69552,729,"SDN","Sudan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69553,729,"SDN","Sudan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69554,729,"SDN","Sudan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69555,729,"SDN","Sudan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69556,729,"SDN","Sudan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69557,729,"SDN","Sudan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69558,729,"SDN","Sudan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69559,729,"SDN","Sudan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69560,729,"SDN","Sudan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69561,729,"SDN","Sudan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69562,729,"SDN","Sudan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69563,729,"SDN","Sudan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69564,729,"SDN","Sudan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69565,729,"SDN","Sudan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69566,729,"SDN","Sudan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69567,729,"SDN","Sudan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69568,729,"SDN","Sudan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69569,729,"SDN","Sudan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69570,729,"SDN","Sudan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69571,729,"SDN","Sudan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69572,729,"SDN","Sudan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69573,729,"SDN","Sudan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69574,729,"SDN","Sudan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69575,729,"SDN","Sudan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69576,729,"SDN","Sudan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69577,729,"SDN","Sudan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SDN/sdn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69578,732,"ESH","Western Sahara","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69579,732,"ESH","Western Sahara","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69580,732,"ESH","Western Sahara","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69581,732,"ESH","Western Sahara","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69582,732,"ESH","Western Sahara","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69583,732,"ESH","Western Sahara","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69584,732,"ESH","Western Sahara","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69585,732,"ESH","Western Sahara","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69586,732,"ESH","Western Sahara","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69587,732,"ESH","Western Sahara","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69588,732,"ESH","Western Sahara","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69589,732,"ESH","Western Sahara","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69590,732,"ESH","Western Sahara","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69591,732,"ESH","Western Sahara","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69592,732,"ESH","Western Sahara","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69593,732,"ESH","Western Sahara","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69594,732,"ESH","Western Sahara","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69595,732,"ESH","Western Sahara","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69596,732,"ESH","Western Sahara","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69597,732,"ESH","Western Sahara","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69598,732,"ESH","Western Sahara","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69599,732,"ESH","Western Sahara","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69600,732,"ESH","Western Sahara","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69601,732,"ESH","Western Sahara","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69602,732,"ESH","Western Sahara","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69603,732,"ESH","Western Sahara","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69604,732,"ESH","Western Sahara","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69605,732,"ESH","Western Sahara","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69606,732,"ESH","Western Sahara","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69607,732,"ESH","Western Sahara","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69608,732,"ESH","Western Sahara","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69609,732,"ESH","Western Sahara","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69610,732,"ESH","Western Sahara","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69611,732,"ESH","Western Sahara","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69612,732,"ESH","Western Sahara","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69613,732,"ESH","Western Sahara","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ESH/esh_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69614,740,"SUR","Suriname","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69615,740,"SUR","Suriname","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69616,740,"SUR","Suriname","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69617,740,"SUR","Suriname","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69618,740,"SUR","Suriname","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69619,740,"SUR","Suriname","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69620,740,"SUR","Suriname","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69621,740,"SUR","Suriname","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69622,740,"SUR","Suriname","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69623,740,"SUR","Suriname","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69624,740,"SUR","Suriname","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69625,740,"SUR","Suriname","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69626,740,"SUR","Suriname","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69627,740,"SUR","Suriname","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69628,740,"SUR","Suriname","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69629,740,"SUR","Suriname","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69630,740,"SUR","Suriname","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69631,740,"SUR","Suriname","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69632,740,"SUR","Suriname","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69633,740,"SUR","Suriname","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69634,740,"SUR","Suriname","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69635,740,"SUR","Suriname","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69636,740,"SUR","Suriname","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69637,740,"SUR","Suriname","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69638,740,"SUR","Suriname","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69639,740,"SUR","Suriname","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69640,740,"SUR","Suriname","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69641,740,"SUR","Suriname","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69642,740,"SUR","Suriname","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69643,740,"SUR","Suriname","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69644,740,"SUR","Suriname","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69645,740,"SUR","Suriname","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69646,740,"SUR","Suriname","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69647,740,"SUR","Suriname","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69648,740,"SUR","Suriname","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69649,740,"SUR","Suriname","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SUR/sur_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69650,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69651,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69652,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69653,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69654,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69655,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69656,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69657,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69658,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69659,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69660,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69661,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69662,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69663,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69664,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69665,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69666,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69667,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69668,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69669,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69670,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69671,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69672,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69673,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69674,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69675,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69676,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69677,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69678,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69679,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69680,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69681,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69682,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69683,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69684,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69685,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SJM/sjm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69686,748,"SWZ","Swaziland","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69687,748,"SWZ","Swaziland","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69688,748,"SWZ","Swaziland","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69689,748,"SWZ","Swaziland","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69690,748,"SWZ","Swaziland","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69691,748,"SWZ","Swaziland","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69692,748,"SWZ","Swaziland","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69693,748,"SWZ","Swaziland","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69694,748,"SWZ","Swaziland","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69695,748,"SWZ","Swaziland","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69696,748,"SWZ","Swaziland","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69697,748,"SWZ","Swaziland","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69698,748,"SWZ","Swaziland","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69699,748,"SWZ","Swaziland","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69700,748,"SWZ","Swaziland","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69701,748,"SWZ","Swaziland","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69702,748,"SWZ","Swaziland","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69703,748,"SWZ","Swaziland","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69704,748,"SWZ","Swaziland","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69705,748,"SWZ","Swaziland","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69706,748,"SWZ","Swaziland","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69707,748,"SWZ","Swaziland","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69708,748,"SWZ","Swaziland","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69709,748,"SWZ","Swaziland","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69710,748,"SWZ","Swaziland","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69711,748,"SWZ","Swaziland","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69712,748,"SWZ","Swaziland","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69713,748,"SWZ","Swaziland","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69714,748,"SWZ","Swaziland","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69715,748,"SWZ","Swaziland","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69716,748,"SWZ","Swaziland","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69717,748,"SWZ","Swaziland","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69718,748,"SWZ","Swaziland","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69719,748,"SWZ","Swaziland","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69720,748,"SWZ","Swaziland","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69721,748,"SWZ","Swaziland","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWZ/swz_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69722,752,"SWE","Sweden","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69723,752,"SWE","Sweden","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69724,752,"SWE","Sweden","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69725,752,"SWE","Sweden","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69726,752,"SWE","Sweden","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69727,752,"SWE","Sweden","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69728,752,"SWE","Sweden","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69729,752,"SWE","Sweden","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69730,752,"SWE","Sweden","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69731,752,"SWE","Sweden","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69732,752,"SWE","Sweden","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69733,752,"SWE","Sweden","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69734,752,"SWE","Sweden","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69735,752,"SWE","Sweden","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69736,752,"SWE","Sweden","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69737,752,"SWE","Sweden","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69738,752,"SWE","Sweden","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69739,752,"SWE","Sweden","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69740,752,"SWE","Sweden","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69741,752,"SWE","Sweden","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69742,752,"SWE","Sweden","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69743,752,"SWE","Sweden","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69744,752,"SWE","Sweden","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69745,752,"SWE","Sweden","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69746,752,"SWE","Sweden","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69747,752,"SWE","Sweden","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69748,752,"SWE","Sweden","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69749,752,"SWE","Sweden","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69750,752,"SWE","Sweden","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69751,752,"SWE","Sweden","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69752,752,"SWE","Sweden","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69753,752,"SWE","Sweden","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69754,752,"SWE","Sweden","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69755,752,"SWE","Sweden","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69756,752,"SWE","Sweden","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69757,752,"SWE","Sweden","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SWE/swe_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69758,756,"CHE","Switzerland","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69759,756,"CHE","Switzerland","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69760,756,"CHE","Switzerland","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69761,756,"CHE","Switzerland","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69762,756,"CHE","Switzerland","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69763,756,"CHE","Switzerland","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69764,756,"CHE","Switzerland","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69765,756,"CHE","Switzerland","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69766,756,"CHE","Switzerland","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69767,756,"CHE","Switzerland","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69768,756,"CHE","Switzerland","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69769,756,"CHE","Switzerland","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69770,756,"CHE","Switzerland","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69771,756,"CHE","Switzerland","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69772,756,"CHE","Switzerland","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69773,756,"CHE","Switzerland","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69774,756,"CHE","Switzerland","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69775,756,"CHE","Switzerland","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69776,756,"CHE","Switzerland","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69777,756,"CHE","Switzerland","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69778,756,"CHE","Switzerland","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69779,756,"CHE","Switzerland","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69780,756,"CHE","Switzerland","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69781,756,"CHE","Switzerland","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69782,756,"CHE","Switzerland","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69783,756,"CHE","Switzerland","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69784,756,"CHE","Switzerland","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69785,756,"CHE","Switzerland","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69786,756,"CHE","Switzerland","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69787,756,"CHE","Switzerland","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69788,756,"CHE","Switzerland","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69789,756,"CHE","Switzerland","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69790,756,"CHE","Switzerland","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69791,756,"CHE","Switzerland","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69792,756,"CHE","Switzerland","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69793,756,"CHE","Switzerland","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/CHE/che_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69794,760,"SYR","Syria","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69795,760,"SYR","Syria","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69796,760,"SYR","Syria","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69797,760,"SYR","Syria","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69798,760,"SYR","Syria","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69799,760,"SYR","Syria","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69800,760,"SYR","Syria","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69801,760,"SYR","Syria","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69802,760,"SYR","Syria","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69803,760,"SYR","Syria","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69804,760,"SYR","Syria","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69805,760,"SYR","Syria","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69806,760,"SYR","Syria","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69807,760,"SYR","Syria","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69808,760,"SYR","Syria","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69809,760,"SYR","Syria","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69810,760,"SYR","Syria","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69811,760,"SYR","Syria","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69812,760,"SYR","Syria","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69813,760,"SYR","Syria","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69814,760,"SYR","Syria","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69815,760,"SYR","Syria","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69816,760,"SYR","Syria","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69817,760,"SYR","Syria","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69818,760,"SYR","Syria","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69819,760,"SYR","Syria","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69820,760,"SYR","Syria","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69821,760,"SYR","Syria","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69822,760,"SYR","Syria","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69823,760,"SYR","Syria","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69824,760,"SYR","Syria","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69825,760,"SYR","Syria","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69826,760,"SYR","Syria","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69827,760,"SYR","Syria","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69828,760,"SYR","Syria","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69829,760,"SYR","Syria","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SYR/syr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69830,762,"TJK","Tajikistan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69831,762,"TJK","Tajikistan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69832,762,"TJK","Tajikistan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69833,762,"TJK","Tajikistan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69834,762,"TJK","Tajikistan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69835,762,"TJK","Tajikistan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69836,762,"TJK","Tajikistan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69837,762,"TJK","Tajikistan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69838,762,"TJK","Tajikistan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69839,762,"TJK","Tajikistan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69840,762,"TJK","Tajikistan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69841,762,"TJK","Tajikistan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69842,762,"TJK","Tajikistan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69843,762,"TJK","Tajikistan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69844,762,"TJK","Tajikistan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69845,762,"TJK","Tajikistan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69846,762,"TJK","Tajikistan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69847,762,"TJK","Tajikistan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69848,762,"TJK","Tajikistan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69849,762,"TJK","Tajikistan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69850,762,"TJK","Tajikistan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69851,762,"TJK","Tajikistan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69852,762,"TJK","Tajikistan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69853,762,"TJK","Tajikistan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69854,762,"TJK","Tajikistan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69855,762,"TJK","Tajikistan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69856,762,"TJK","Tajikistan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69857,762,"TJK","Tajikistan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69858,762,"TJK","Tajikistan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69859,762,"TJK","Tajikistan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69860,762,"TJK","Tajikistan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69861,762,"TJK","Tajikistan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69862,762,"TJK","Tajikistan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69863,762,"TJK","Tajikistan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69864,762,"TJK","Tajikistan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69865,762,"TJK","Tajikistan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TJK/tjk_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69866,764,"THA","Thailand","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69867,764,"THA","Thailand","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69868,764,"THA","Thailand","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69869,764,"THA","Thailand","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69870,764,"THA","Thailand","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69871,764,"THA","Thailand","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69872,764,"THA","Thailand","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69873,764,"THA","Thailand","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69874,764,"THA","Thailand","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69875,764,"THA","Thailand","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69876,764,"THA","Thailand","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69877,764,"THA","Thailand","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69878,764,"THA","Thailand","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69879,764,"THA","Thailand","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69880,764,"THA","Thailand","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69881,764,"THA","Thailand","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69882,764,"THA","Thailand","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69883,764,"THA","Thailand","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69884,764,"THA","Thailand","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69885,764,"THA","Thailand","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69886,764,"THA","Thailand","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69887,764,"THA","Thailand","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69888,764,"THA","Thailand","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69889,764,"THA","Thailand","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69890,764,"THA","Thailand","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69891,764,"THA","Thailand","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69892,764,"THA","Thailand","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69893,764,"THA","Thailand","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69894,764,"THA","Thailand","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69895,764,"THA","Thailand","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69896,764,"THA","Thailand","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69897,764,"THA","Thailand","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69898,764,"THA","Thailand","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69899,764,"THA","Thailand","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69900,764,"THA","Thailand","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69901,764,"THA","Thailand","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/THA/tha_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69902,768,"TGO","Togo","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69903,768,"TGO","Togo","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69904,768,"TGO","Togo","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69905,768,"TGO","Togo","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69906,768,"TGO","Togo","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69907,768,"TGO","Togo","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69908,768,"TGO","Togo","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69909,768,"TGO","Togo","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69910,768,"TGO","Togo","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69911,768,"TGO","Togo","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69912,768,"TGO","Togo","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69913,768,"TGO","Togo","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69914,768,"TGO","Togo","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69915,768,"TGO","Togo","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69916,768,"TGO","Togo","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69917,768,"TGO","Togo","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69918,768,"TGO","Togo","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69919,768,"TGO","Togo","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69920,768,"TGO","Togo","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69921,768,"TGO","Togo","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69922,768,"TGO","Togo","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69923,768,"TGO","Togo","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69924,768,"TGO","Togo","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69925,768,"TGO","Togo","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69926,768,"TGO","Togo","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69927,768,"TGO","Togo","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69928,768,"TGO","Togo","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69929,768,"TGO","Togo","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69930,768,"TGO","Togo","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69931,768,"TGO","Togo","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69932,768,"TGO","Togo","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69933,768,"TGO","Togo","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69934,768,"TGO","Togo","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69935,768,"TGO","Togo","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69936,768,"TGO","Togo","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69937,768,"TGO","Togo","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TGO/tgo_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69938,772,"TKL","Tokelau","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69939,772,"TKL","Tokelau","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69940,772,"TKL","Tokelau","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69941,772,"TKL","Tokelau","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69942,772,"TKL","Tokelau","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69943,772,"TKL","Tokelau","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69944,772,"TKL","Tokelau","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69945,772,"TKL","Tokelau","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69946,772,"TKL","Tokelau","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69947,772,"TKL","Tokelau","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69948,772,"TKL","Tokelau","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69949,772,"TKL","Tokelau","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69950,772,"TKL","Tokelau","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69951,772,"TKL","Tokelau","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69952,772,"TKL","Tokelau","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69953,772,"TKL","Tokelau","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69954,772,"TKL","Tokelau","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69955,772,"TKL","Tokelau","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69956,772,"TKL","Tokelau","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69957,772,"TKL","Tokelau","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69958,772,"TKL","Tokelau","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69959,772,"TKL","Tokelau","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69960,772,"TKL","Tokelau","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69961,772,"TKL","Tokelau","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69962,772,"TKL","Tokelau","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69963,772,"TKL","Tokelau","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
69964,772,"TKL","Tokelau","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
69965,772,"TKL","Tokelau","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
69966,772,"TKL","Tokelau","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
69967,772,"TKL","Tokelau","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
69968,772,"TKL","Tokelau","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
69969,772,"TKL","Tokelau","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
69970,772,"TKL","Tokelau","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
69971,772,"TKL","Tokelau","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
69972,772,"TKL","Tokelau","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
69973,772,"TKL","Tokelau","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKL/tkl_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
69974,776,"TON","Tonga","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
69975,776,"TON","Tonga","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
69976,776,"TON","Tonga","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
69977,776,"TON","Tonga","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
69978,776,"TON","Tonga","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
69979,776,"TON","Tonga","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
69980,776,"TON","Tonga","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
69981,776,"TON","Tonga","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
69982,776,"TON","Tonga","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
69983,776,"TON","Tonga","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
69984,776,"TON","Tonga","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
69985,776,"TON","Tonga","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
69986,776,"TON","Tonga","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
69987,776,"TON","Tonga","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
69988,776,"TON","Tonga","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
69989,776,"TON","Tonga","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
69990,776,"TON","Tonga","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
69991,776,"TON","Tonga","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
69992,776,"TON","Tonga","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
69993,776,"TON","Tonga","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
69994,776,"TON","Tonga","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
69995,776,"TON","Tonga","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
69996,776,"TON","Tonga","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
69997,776,"TON","Tonga","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
69998,776,"TON","Tonga","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
69999,776,"TON","Tonga","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70000,776,"TON","Tonga","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70001,776,"TON","Tonga","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70002,776,"TON","Tonga","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70003,776,"TON","Tonga","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70004,776,"TON","Tonga","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70005,776,"TON","Tonga","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70006,776,"TON","Tonga","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70007,776,"TON","Tonga","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70008,776,"TON","Tonga","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70009,776,"TON","Tonga","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TON/ton_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70010,780,"TTO","Trinidad and Tobago","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70011,780,"TTO","Trinidad and Tobago","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70012,780,"TTO","Trinidad and Tobago","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70013,780,"TTO","Trinidad and Tobago","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70014,780,"TTO","Trinidad and Tobago","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70015,780,"TTO","Trinidad and Tobago","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70016,780,"TTO","Trinidad and Tobago","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70017,780,"TTO","Trinidad and Tobago","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70018,780,"TTO","Trinidad and Tobago","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70019,780,"TTO","Trinidad and Tobago","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70020,780,"TTO","Trinidad and Tobago","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70021,780,"TTO","Trinidad and Tobago","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70022,780,"TTO","Trinidad and Tobago","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70023,780,"TTO","Trinidad and Tobago","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70024,780,"TTO","Trinidad and Tobago","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70025,780,"TTO","Trinidad and Tobago","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70026,780,"TTO","Trinidad and Tobago","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70027,780,"TTO","Trinidad and Tobago","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70028,780,"TTO","Trinidad and Tobago","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70029,780,"TTO","Trinidad and Tobago","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70030,780,"TTO","Trinidad and Tobago","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70031,780,"TTO","Trinidad and Tobago","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70032,780,"TTO","Trinidad and Tobago","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70033,780,"TTO","Trinidad and Tobago","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70034,780,"TTO","Trinidad and Tobago","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70035,780,"TTO","Trinidad and Tobago","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70036,780,"TTO","Trinidad and Tobago","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70037,780,"TTO","Trinidad and Tobago","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70038,780,"TTO","Trinidad and Tobago","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70039,780,"TTO","Trinidad and Tobago","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70040,780,"TTO","Trinidad and Tobago","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70041,780,"TTO","Trinidad and Tobago","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70042,780,"TTO","Trinidad and Tobago","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70043,780,"TTO","Trinidad and Tobago","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70044,780,"TTO","Trinidad and Tobago","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70045,780,"TTO","Trinidad and Tobago","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TTO/tto_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70046,784,"ARE","United Arab Emirates","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70047,784,"ARE","United Arab Emirates","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70048,784,"ARE","United Arab Emirates","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70049,784,"ARE","United Arab Emirates","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70050,784,"ARE","United Arab Emirates","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70051,784,"ARE","United Arab Emirates","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70052,784,"ARE","United Arab Emirates","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70053,784,"ARE","United Arab Emirates","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70054,784,"ARE","United Arab Emirates","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70055,784,"ARE","United Arab Emirates","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70056,784,"ARE","United Arab Emirates","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70057,784,"ARE","United Arab Emirates","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70058,784,"ARE","United Arab Emirates","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70059,784,"ARE","United Arab Emirates","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70060,784,"ARE","United Arab Emirates","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70061,784,"ARE","United Arab Emirates","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70062,784,"ARE","United Arab Emirates","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70063,784,"ARE","United Arab Emirates","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70064,784,"ARE","United Arab Emirates","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70065,784,"ARE","United Arab Emirates","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70066,784,"ARE","United Arab Emirates","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70067,784,"ARE","United Arab Emirates","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70068,784,"ARE","United Arab Emirates","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70069,784,"ARE","United Arab Emirates","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70070,784,"ARE","United Arab Emirates","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70071,784,"ARE","United Arab Emirates","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70072,784,"ARE","United Arab Emirates","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70073,784,"ARE","United Arab Emirates","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70074,784,"ARE","United Arab Emirates","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70075,784,"ARE","United Arab Emirates","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70076,784,"ARE","United Arab Emirates","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70077,784,"ARE","United Arab Emirates","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70078,784,"ARE","United Arab Emirates","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70079,784,"ARE","United Arab Emirates","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70080,784,"ARE","United Arab Emirates","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70081,784,"ARE","United Arab Emirates","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ARE/are_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70082,788,"TUN","Tunisia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70083,788,"TUN","Tunisia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70084,788,"TUN","Tunisia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70085,788,"TUN","Tunisia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70086,788,"TUN","Tunisia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70087,788,"TUN","Tunisia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70088,788,"TUN","Tunisia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70089,788,"TUN","Tunisia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70090,788,"TUN","Tunisia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70091,788,"TUN","Tunisia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70092,788,"TUN","Tunisia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70093,788,"TUN","Tunisia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70094,788,"TUN","Tunisia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70095,788,"TUN","Tunisia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70096,788,"TUN","Tunisia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70097,788,"TUN","Tunisia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70098,788,"TUN","Tunisia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70099,788,"TUN","Tunisia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70100,788,"TUN","Tunisia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70101,788,"TUN","Tunisia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70102,788,"TUN","Tunisia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70103,788,"TUN","Tunisia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70104,788,"TUN","Tunisia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70105,788,"TUN","Tunisia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70106,788,"TUN","Tunisia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70107,788,"TUN","Tunisia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70108,788,"TUN","Tunisia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70109,788,"TUN","Tunisia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70110,788,"TUN","Tunisia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70111,788,"TUN","Tunisia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70112,788,"TUN","Tunisia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70113,788,"TUN","Tunisia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70114,788,"TUN","Tunisia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70115,788,"TUN","Tunisia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70116,788,"TUN","Tunisia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70117,788,"TUN","Tunisia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUN/tun_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70118,792,"TUR","Turkey","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70119,792,"TUR","Turkey","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70120,792,"TUR","Turkey","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70121,792,"TUR","Turkey","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70122,792,"TUR","Turkey","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70123,792,"TUR","Turkey","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70124,792,"TUR","Turkey","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70125,792,"TUR","Turkey","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70126,792,"TUR","Turkey","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70127,792,"TUR","Turkey","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70128,792,"TUR","Turkey","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70129,792,"TUR","Turkey","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70130,792,"TUR","Turkey","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70131,792,"TUR","Turkey","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70132,792,"TUR","Turkey","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70133,792,"TUR","Turkey","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70134,792,"TUR","Turkey","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70135,792,"TUR","Turkey","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70136,792,"TUR","Turkey","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70137,792,"TUR","Turkey","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70138,792,"TUR","Turkey","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70139,792,"TUR","Turkey","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70140,792,"TUR","Turkey","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70141,792,"TUR","Turkey","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70142,792,"TUR","Turkey","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70143,792,"TUR","Turkey","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70144,792,"TUR","Turkey","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70145,792,"TUR","Turkey","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70146,792,"TUR","Turkey","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70147,792,"TUR","Turkey","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70148,792,"TUR","Turkey","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70149,792,"TUR","Turkey","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70150,792,"TUR","Turkey","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70151,792,"TUR","Turkey","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70152,792,"TUR","Turkey","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70153,792,"TUR","Turkey","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUR/tur_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70154,795,"TKM","Turkmenistan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70155,795,"TKM","Turkmenistan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70156,795,"TKM","Turkmenistan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70157,795,"TKM","Turkmenistan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70158,795,"TKM","Turkmenistan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70159,795,"TKM","Turkmenistan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70160,795,"TKM","Turkmenistan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70161,795,"TKM","Turkmenistan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70162,795,"TKM","Turkmenistan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70163,795,"TKM","Turkmenistan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70164,795,"TKM","Turkmenistan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70165,795,"TKM","Turkmenistan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70166,795,"TKM","Turkmenistan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70167,795,"TKM","Turkmenistan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70168,795,"TKM","Turkmenistan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70169,795,"TKM","Turkmenistan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70170,795,"TKM","Turkmenistan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70171,795,"TKM","Turkmenistan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70172,795,"TKM","Turkmenistan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70173,795,"TKM","Turkmenistan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70174,795,"TKM","Turkmenistan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70175,795,"TKM","Turkmenistan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70176,795,"TKM","Turkmenistan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70177,795,"TKM","Turkmenistan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70178,795,"TKM","Turkmenistan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70179,795,"TKM","Turkmenistan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70180,795,"TKM","Turkmenistan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70181,795,"TKM","Turkmenistan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70182,795,"TKM","Turkmenistan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70183,795,"TKM","Turkmenistan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70184,795,"TKM","Turkmenistan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70185,795,"TKM","Turkmenistan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70186,795,"TKM","Turkmenistan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70187,795,"TKM","Turkmenistan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70188,795,"TKM","Turkmenistan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70189,795,"TKM","Turkmenistan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TKM/tkm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70190,796,"TCA","Turks and Caicos Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70191,796,"TCA","Turks and Caicos Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70192,796,"TCA","Turks and Caicos Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70193,796,"TCA","Turks and Caicos Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70194,796,"TCA","Turks and Caicos Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70195,796,"TCA","Turks and Caicos Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70196,796,"TCA","Turks and Caicos Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70197,796,"TCA","Turks and Caicos Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70198,796,"TCA","Turks and Caicos Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70199,796,"TCA","Turks and Caicos Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70200,796,"TCA","Turks and Caicos Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70201,796,"TCA","Turks and Caicos Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70202,796,"TCA","Turks and Caicos Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70203,796,"TCA","Turks and Caicos Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70204,796,"TCA","Turks and Caicos Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70205,796,"TCA","Turks and Caicos Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70206,796,"TCA","Turks and Caicos Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70207,796,"TCA","Turks and Caicos Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70208,796,"TCA","Turks and Caicos Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70209,796,"TCA","Turks and Caicos Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70210,796,"TCA","Turks and Caicos Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70211,796,"TCA","Turks and Caicos Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70212,796,"TCA","Turks and Caicos Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70213,796,"TCA","Turks and Caicos Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70214,796,"TCA","Turks and Caicos Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70215,796,"TCA","Turks and Caicos Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70216,796,"TCA","Turks and Caicos Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70217,796,"TCA","Turks and Caicos Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70218,796,"TCA","Turks and Caicos Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70219,796,"TCA","Turks and Caicos Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70220,796,"TCA","Turks and Caicos Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70221,796,"TCA","Turks and Caicos Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70222,796,"TCA","Turks and Caicos Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70223,796,"TCA","Turks and Caicos Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70224,796,"TCA","Turks and Caicos Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70225,796,"TCA","Turks and Caicos Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TCA/tca_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70226,798,"TUV","Tuvalu","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70227,798,"TUV","Tuvalu","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70228,798,"TUV","Tuvalu","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70229,798,"TUV","Tuvalu","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70230,798,"TUV","Tuvalu","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70231,798,"TUV","Tuvalu","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70232,798,"TUV","Tuvalu","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70233,798,"TUV","Tuvalu","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70234,798,"TUV","Tuvalu","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70235,798,"TUV","Tuvalu","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70236,798,"TUV","Tuvalu","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70237,798,"TUV","Tuvalu","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70238,798,"TUV","Tuvalu","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70239,798,"TUV","Tuvalu","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70240,798,"TUV","Tuvalu","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70241,798,"TUV","Tuvalu","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70242,798,"TUV","Tuvalu","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70243,798,"TUV","Tuvalu","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70244,798,"TUV","Tuvalu","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70245,798,"TUV","Tuvalu","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70246,798,"TUV","Tuvalu","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70247,798,"TUV","Tuvalu","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70248,798,"TUV","Tuvalu","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70249,798,"TUV","Tuvalu","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70250,798,"TUV","Tuvalu","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70251,798,"TUV","Tuvalu","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70252,798,"TUV","Tuvalu","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70253,798,"TUV","Tuvalu","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70254,798,"TUV","Tuvalu","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70255,798,"TUV","Tuvalu","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70256,798,"TUV","Tuvalu","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70257,798,"TUV","Tuvalu","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70258,798,"TUV","Tuvalu","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70259,798,"TUV","Tuvalu","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70260,798,"TUV","Tuvalu","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70261,798,"TUV","Tuvalu","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TUV/tuv_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70262,800,"UGA","Uganda","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70263,800,"UGA","Uganda","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70264,800,"UGA","Uganda","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70265,800,"UGA","Uganda","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70266,800,"UGA","Uganda","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70267,800,"UGA","Uganda","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70268,800,"UGA","Uganda","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70269,800,"UGA","Uganda","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70270,800,"UGA","Uganda","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70271,800,"UGA","Uganda","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70272,800,"UGA","Uganda","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70273,800,"UGA","Uganda","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70274,800,"UGA","Uganda","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70275,800,"UGA","Uganda","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70276,800,"UGA","Uganda","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70277,800,"UGA","Uganda","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70278,800,"UGA","Uganda","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70279,800,"UGA","Uganda","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70280,800,"UGA","Uganda","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70281,800,"UGA","Uganda","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70282,800,"UGA","Uganda","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70283,800,"UGA","Uganda","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70284,800,"UGA","Uganda","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70285,800,"UGA","Uganda","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70286,800,"UGA","Uganda","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70287,800,"UGA","Uganda","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70288,800,"UGA","Uganda","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70289,800,"UGA","Uganda","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70290,800,"UGA","Uganda","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70291,800,"UGA","Uganda","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70292,800,"UGA","Uganda","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70293,800,"UGA","Uganda","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70294,800,"UGA","Uganda","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70295,800,"UGA","Uganda","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70296,800,"UGA","Uganda","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70297,800,"UGA","Uganda","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UGA/uga_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70298,804,"UKR","Ukraine","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70299,804,"UKR","Ukraine","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70300,804,"UKR","Ukraine","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70301,804,"UKR","Ukraine","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70302,804,"UKR","Ukraine","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70303,804,"UKR","Ukraine","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70304,804,"UKR","Ukraine","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70305,804,"UKR","Ukraine","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70306,804,"UKR","Ukraine","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70307,804,"UKR","Ukraine","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70308,804,"UKR","Ukraine","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70309,804,"UKR","Ukraine","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70310,804,"UKR","Ukraine","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70311,804,"UKR","Ukraine","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70312,804,"UKR","Ukraine","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70313,804,"UKR","Ukraine","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70314,804,"UKR","Ukraine","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70315,804,"UKR","Ukraine","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70316,804,"UKR","Ukraine","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70317,804,"UKR","Ukraine","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70318,804,"UKR","Ukraine","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70319,804,"UKR","Ukraine","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70320,804,"UKR","Ukraine","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70321,804,"UKR","Ukraine","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70322,804,"UKR","Ukraine","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70323,804,"UKR","Ukraine","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70324,804,"UKR","Ukraine","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70325,804,"UKR","Ukraine","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70326,804,"UKR","Ukraine","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70327,804,"UKR","Ukraine","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70328,804,"UKR","Ukraine","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70329,804,"UKR","Ukraine","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70330,804,"UKR","Ukraine","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70331,804,"UKR","Ukraine","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70332,804,"UKR","Ukraine","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70333,804,"UKR","Ukraine","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UKR/ukr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70334,807,"MKD","Macedonia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70335,807,"MKD","Macedonia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70336,807,"MKD","Macedonia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70337,807,"MKD","Macedonia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70338,807,"MKD","Macedonia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70339,807,"MKD","Macedonia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70340,807,"MKD","Macedonia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70341,807,"MKD","Macedonia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70342,807,"MKD","Macedonia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70343,807,"MKD","Macedonia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70344,807,"MKD","Macedonia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70345,807,"MKD","Macedonia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70346,807,"MKD","Macedonia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70347,807,"MKD","Macedonia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70348,807,"MKD","Macedonia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70349,807,"MKD","Macedonia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70350,807,"MKD","Macedonia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70351,807,"MKD","Macedonia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70352,807,"MKD","Macedonia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70353,807,"MKD","Macedonia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70354,807,"MKD","Macedonia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70355,807,"MKD","Macedonia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70356,807,"MKD","Macedonia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70357,807,"MKD","Macedonia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70358,807,"MKD","Macedonia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70359,807,"MKD","Macedonia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70360,807,"MKD","Macedonia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70361,807,"MKD","Macedonia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70362,807,"MKD","Macedonia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70363,807,"MKD","Macedonia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70364,807,"MKD","Macedonia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70365,807,"MKD","Macedonia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70366,807,"MKD","Macedonia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70367,807,"MKD","Macedonia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70368,807,"MKD","Macedonia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70369,807,"MKD","Macedonia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/MKD/mkd_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70370,818,"EGY","Egypt","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70371,818,"EGY","Egypt","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70372,818,"EGY","Egypt","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70373,818,"EGY","Egypt","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70374,818,"EGY","Egypt","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70375,818,"EGY","Egypt","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70376,818,"EGY","Egypt","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70377,818,"EGY","Egypt","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70378,818,"EGY","Egypt","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70379,818,"EGY","Egypt","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70380,818,"EGY","Egypt","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70381,818,"EGY","Egypt","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70382,818,"EGY","Egypt","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70383,818,"EGY","Egypt","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70384,818,"EGY","Egypt","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70385,818,"EGY","Egypt","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70386,818,"EGY","Egypt","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70387,818,"EGY","Egypt","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70388,818,"EGY","Egypt","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70389,818,"EGY","Egypt","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70390,818,"EGY","Egypt","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70391,818,"EGY","Egypt","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70392,818,"EGY","Egypt","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70393,818,"EGY","Egypt","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70394,818,"EGY","Egypt","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70395,818,"EGY","Egypt","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70396,818,"EGY","Egypt","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70397,818,"EGY","Egypt","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70398,818,"EGY","Egypt","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70399,818,"EGY","Egypt","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70400,818,"EGY","Egypt","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70401,818,"EGY","Egypt","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70402,818,"EGY","Egypt","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70403,818,"EGY","Egypt","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70404,818,"EGY","Egypt","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70405,818,"EGY","Egypt","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/EGY/egy_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70406,826,"GBR","United Kingdom","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70407,826,"GBR","United Kingdom","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70408,826,"GBR","United Kingdom","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70409,826,"GBR","United Kingdom","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70410,826,"GBR","United Kingdom","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70411,826,"GBR","United Kingdom","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70412,826,"GBR","United Kingdom","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70413,826,"GBR","United Kingdom","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70414,826,"GBR","United Kingdom","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70415,826,"GBR","United Kingdom","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70416,826,"GBR","United Kingdom","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70417,826,"GBR","United Kingdom","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70418,826,"GBR","United Kingdom","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70419,826,"GBR","United Kingdom","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70420,826,"GBR","United Kingdom","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70421,826,"GBR","United Kingdom","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70422,826,"GBR","United Kingdom","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70423,826,"GBR","United Kingdom","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70424,826,"GBR","United Kingdom","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70425,826,"GBR","United Kingdom","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70426,826,"GBR","United Kingdom","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70427,826,"GBR","United Kingdom","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70428,826,"GBR","United Kingdom","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70429,826,"GBR","United Kingdom","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70430,826,"GBR","United Kingdom","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70431,826,"GBR","United Kingdom","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70432,826,"GBR","United Kingdom","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70433,826,"GBR","United Kingdom","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70434,826,"GBR","United Kingdom","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70435,826,"GBR","United Kingdom","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70436,826,"GBR","United Kingdom","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70437,826,"GBR","United Kingdom","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70438,826,"GBR","United Kingdom","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70439,826,"GBR","United Kingdom","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70440,826,"GBR","United Kingdom","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70441,826,"GBR","United Kingdom","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GBR/gbr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70442,831,"GGY","Guernsey","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70443,831,"GGY","Guernsey","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70444,831,"GGY","Guernsey","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70445,831,"GGY","Guernsey","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70446,831,"GGY","Guernsey","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70447,831,"GGY","Guernsey","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70448,831,"GGY","Guernsey","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70449,831,"GGY","Guernsey","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70450,831,"GGY","Guernsey","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70451,831,"GGY","Guernsey","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70452,831,"GGY","Guernsey","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70453,831,"GGY","Guernsey","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70454,831,"GGY","Guernsey","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70455,831,"GGY","Guernsey","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70456,831,"GGY","Guernsey","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70457,831,"GGY","Guernsey","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70458,831,"GGY","Guernsey","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70459,831,"GGY","Guernsey","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70460,831,"GGY","Guernsey","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70461,831,"GGY","Guernsey","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70462,831,"GGY","Guernsey","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70463,831,"GGY","Guernsey","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70464,831,"GGY","Guernsey","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70465,831,"GGY","Guernsey","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70466,831,"GGY","Guernsey","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70467,831,"GGY","Guernsey","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70468,831,"GGY","Guernsey","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70469,831,"GGY","Guernsey","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70470,831,"GGY","Guernsey","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70471,831,"GGY","Guernsey","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70472,831,"GGY","Guernsey","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70473,831,"GGY","Guernsey","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70474,831,"GGY","Guernsey","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70475,831,"GGY","Guernsey","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70476,831,"GGY","Guernsey","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70477,831,"GGY","Guernsey","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/GGY/ggy_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70478,832,"JEY","Jersey","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70479,832,"JEY","Jersey","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70480,832,"JEY","Jersey","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70481,832,"JEY","Jersey","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70482,832,"JEY","Jersey","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70483,832,"JEY","Jersey","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70484,832,"JEY","Jersey","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70485,832,"JEY","Jersey","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70486,832,"JEY","Jersey","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70487,832,"JEY","Jersey","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70488,832,"JEY","Jersey","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70489,832,"JEY","Jersey","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70490,832,"JEY","Jersey","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70491,832,"JEY","Jersey","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70492,832,"JEY","Jersey","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70493,832,"JEY","Jersey","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70494,832,"JEY","Jersey","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70495,832,"JEY","Jersey","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70496,832,"JEY","Jersey","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70497,832,"JEY","Jersey","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70498,832,"JEY","Jersey","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70499,832,"JEY","Jersey","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70500,832,"JEY","Jersey","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70501,832,"JEY","Jersey","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70502,832,"JEY","Jersey","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70503,832,"JEY","Jersey","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70504,832,"JEY","Jersey","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70505,832,"JEY","Jersey","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70506,832,"JEY","Jersey","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70507,832,"JEY","Jersey","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70508,832,"JEY","Jersey","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70509,832,"JEY","Jersey","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70510,832,"JEY","Jersey","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70511,832,"JEY","Jersey","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70512,832,"JEY","Jersey","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70513,832,"JEY","Jersey","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/JEY/jey_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70514,833,"IMN","Isle of Man","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70515,833,"IMN","Isle of Man","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70516,833,"IMN","Isle of Man","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70517,833,"IMN","Isle of Man","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70518,833,"IMN","Isle of Man","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70519,833,"IMN","Isle of Man","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70520,833,"IMN","Isle of Man","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70521,833,"IMN","Isle of Man","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70522,833,"IMN","Isle of Man","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70523,833,"IMN","Isle of Man","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70524,833,"IMN","Isle of Man","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70525,833,"IMN","Isle of Man","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70526,833,"IMN","Isle of Man","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70527,833,"IMN","Isle of Man","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70528,833,"IMN","Isle of Man","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70529,833,"IMN","Isle of Man","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70530,833,"IMN","Isle of Man","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70531,833,"IMN","Isle of Man","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70532,833,"IMN","Isle of Man","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70533,833,"IMN","Isle of Man","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70534,833,"IMN","Isle of Man","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70535,833,"IMN","Isle of Man","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70536,833,"IMN","Isle of Man","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70537,833,"IMN","Isle of Man","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70538,833,"IMN","Isle of Man","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70539,833,"IMN","Isle of Man","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70540,833,"IMN","Isle of Man","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70541,833,"IMN","Isle of Man","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70542,833,"IMN","Isle of Man","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70543,833,"IMN","Isle of Man","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70544,833,"IMN","Isle of Man","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70545,833,"IMN","Isle of Man","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70546,833,"IMN","Isle of Man","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70547,833,"IMN","Isle of Man","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70548,833,"IMN","Isle of Man","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70549,833,"IMN","Isle of Man","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/IMN/imn_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70550,834,"TZA","Tanzania","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70551,834,"TZA","Tanzania","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70552,834,"TZA","Tanzania","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70553,834,"TZA","Tanzania","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70554,834,"TZA","Tanzania","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70555,834,"TZA","Tanzania","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70556,834,"TZA","Tanzania","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70557,834,"TZA","Tanzania","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70558,834,"TZA","Tanzania","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70559,834,"TZA","Tanzania","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70560,834,"TZA","Tanzania","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70561,834,"TZA","Tanzania","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70562,834,"TZA","Tanzania","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70563,834,"TZA","Tanzania","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70564,834,"TZA","Tanzania","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70565,834,"TZA","Tanzania","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70566,834,"TZA","Tanzania","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70567,834,"TZA","Tanzania","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70568,834,"TZA","Tanzania","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70569,834,"TZA","Tanzania","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70570,834,"TZA","Tanzania","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70571,834,"TZA","Tanzania","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70572,834,"TZA","Tanzania","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70573,834,"TZA","Tanzania","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70574,834,"TZA","Tanzania","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70575,834,"TZA","Tanzania","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70576,834,"TZA","Tanzania","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70577,834,"TZA","Tanzania","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70578,834,"TZA","Tanzania","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70579,834,"TZA","Tanzania","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70580,834,"TZA","Tanzania","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70581,834,"TZA","Tanzania","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70582,834,"TZA","Tanzania","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70583,834,"TZA","Tanzania","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70584,834,"TZA","Tanzania","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70585,834,"TZA","Tanzania","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/TZA/tza_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70586,854,"BFA","Burkina Faso","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70587,854,"BFA","Burkina Faso","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70588,854,"BFA","Burkina Faso","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70589,854,"BFA","Burkina Faso","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70590,854,"BFA","Burkina Faso","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70591,854,"BFA","Burkina Faso","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70592,854,"BFA","Burkina Faso","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70593,854,"BFA","Burkina Faso","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70594,854,"BFA","Burkina Faso","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70595,854,"BFA","Burkina Faso","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70596,854,"BFA","Burkina Faso","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70597,854,"BFA","Burkina Faso","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70598,854,"BFA","Burkina Faso","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70599,854,"BFA","Burkina Faso","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70600,854,"BFA","Burkina Faso","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70601,854,"BFA","Burkina Faso","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70602,854,"BFA","Burkina Faso","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70603,854,"BFA","Burkina Faso","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70604,854,"BFA","Burkina Faso","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70605,854,"BFA","Burkina Faso","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70606,854,"BFA","Burkina Faso","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70607,854,"BFA","Burkina Faso","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70608,854,"BFA","Burkina Faso","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70609,854,"BFA","Burkina Faso","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70610,854,"BFA","Burkina Faso","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70611,854,"BFA","Burkina Faso","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70612,854,"BFA","Burkina Faso","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70613,854,"BFA","Burkina Faso","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70614,854,"BFA","Burkina Faso","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70615,854,"BFA","Burkina Faso","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70616,854,"BFA","Burkina Faso","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70617,854,"BFA","Burkina Faso","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70618,854,"BFA","Burkina Faso","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70619,854,"BFA","Burkina Faso","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70620,854,"BFA","Burkina Faso","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70621,854,"BFA","Burkina Faso","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/BFA/bfa_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70622,858,"URY","Uruguay","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70623,858,"URY","Uruguay","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70624,858,"URY","Uruguay","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70625,858,"URY","Uruguay","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70626,858,"URY","Uruguay","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70627,858,"URY","Uruguay","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70628,858,"URY","Uruguay","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70629,858,"URY","Uruguay","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70630,858,"URY","Uruguay","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70631,858,"URY","Uruguay","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70632,858,"URY","Uruguay","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70633,858,"URY","Uruguay","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70634,858,"URY","Uruguay","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70635,858,"URY","Uruguay","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70636,858,"URY","Uruguay","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70637,858,"URY","Uruguay","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70638,858,"URY","Uruguay","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70639,858,"URY","Uruguay","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70640,858,"URY","Uruguay","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70641,858,"URY","Uruguay","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70642,858,"URY","Uruguay","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70643,858,"URY","Uruguay","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70644,858,"URY","Uruguay","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70645,858,"URY","Uruguay","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70646,858,"URY","Uruguay","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70647,858,"URY","Uruguay","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70648,858,"URY","Uruguay","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70649,858,"URY","Uruguay","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70650,858,"URY","Uruguay","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70651,858,"URY","Uruguay","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70652,858,"URY","Uruguay","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70653,858,"URY","Uruguay","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70654,858,"URY","Uruguay","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70655,858,"URY","Uruguay","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70656,858,"URY","Uruguay","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70657,858,"URY","Uruguay","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/URY/ury_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70658,860,"UZB","Uzbekistan","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70659,860,"UZB","Uzbekistan","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70660,860,"UZB","Uzbekistan","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70661,860,"UZB","Uzbekistan","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70662,860,"UZB","Uzbekistan","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70663,860,"UZB","Uzbekistan","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70664,860,"UZB","Uzbekistan","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70665,860,"UZB","Uzbekistan","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70666,860,"UZB","Uzbekistan","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70667,860,"UZB","Uzbekistan","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70668,860,"UZB","Uzbekistan","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70669,860,"UZB","Uzbekistan","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70670,860,"UZB","Uzbekistan","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70671,860,"UZB","Uzbekistan","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70672,860,"UZB","Uzbekistan","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70673,860,"UZB","Uzbekistan","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70674,860,"UZB","Uzbekistan","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70675,860,"UZB","Uzbekistan","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70676,860,"UZB","Uzbekistan","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70677,860,"UZB","Uzbekistan","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70678,860,"UZB","Uzbekistan","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70679,860,"UZB","Uzbekistan","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70680,860,"UZB","Uzbekistan","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70681,860,"UZB","Uzbekistan","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70682,860,"UZB","Uzbekistan","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70683,860,"UZB","Uzbekistan","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70684,860,"UZB","Uzbekistan","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70685,860,"UZB","Uzbekistan","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70686,860,"UZB","Uzbekistan","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70687,860,"UZB","Uzbekistan","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70688,860,"UZB","Uzbekistan","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70689,860,"UZB","Uzbekistan","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70690,860,"UZB","Uzbekistan","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70691,860,"UZB","Uzbekistan","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70692,860,"UZB","Uzbekistan","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70693,860,"UZB","Uzbekistan","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/UZB/uzb_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70694,862,"VEN","Venezuela","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70695,862,"VEN","Venezuela","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70696,862,"VEN","Venezuela","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70697,862,"VEN","Venezuela","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70698,862,"VEN","Venezuela","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70699,862,"VEN","Venezuela","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70700,862,"VEN","Venezuela","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70701,862,"VEN","Venezuela","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70702,862,"VEN","Venezuela","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70703,862,"VEN","Venezuela","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70704,862,"VEN","Venezuela","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70705,862,"VEN","Venezuela","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70706,862,"VEN","Venezuela","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70707,862,"VEN","Venezuela","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70708,862,"VEN","Venezuela","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70709,862,"VEN","Venezuela","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70710,862,"VEN","Venezuela","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70711,862,"VEN","Venezuela","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70712,862,"VEN","Venezuela","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70713,862,"VEN","Venezuela","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70714,862,"VEN","Venezuela","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70715,862,"VEN","Venezuela","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70716,862,"VEN","Venezuela","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70717,862,"VEN","Venezuela","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70718,862,"VEN","Venezuela","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70719,862,"VEN","Venezuela","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70720,862,"VEN","Venezuela","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70721,862,"VEN","Venezuela","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70722,862,"VEN","Venezuela","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70723,862,"VEN","Venezuela","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70724,862,"VEN","Venezuela","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70725,862,"VEN","Venezuela","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70726,862,"VEN","Venezuela","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70727,862,"VEN","Venezuela","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70728,862,"VEN","Venezuela","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70729,862,"VEN","Venezuela","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/VEN/ven_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70730,876,"WLF","Wallis and Futuna","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70731,876,"WLF","Wallis and Futuna","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70732,876,"WLF","Wallis and Futuna","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70733,876,"WLF","Wallis and Futuna","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70734,876,"WLF","Wallis and Futuna","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70735,876,"WLF","Wallis and Futuna","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70736,876,"WLF","Wallis and Futuna","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70737,876,"WLF","Wallis and Futuna","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70738,876,"WLF","Wallis and Futuna","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70739,876,"WLF","Wallis and Futuna","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70740,876,"WLF","Wallis and Futuna","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70741,876,"WLF","Wallis and Futuna","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70742,876,"WLF","Wallis and Futuna","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70743,876,"WLF","Wallis and Futuna","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70744,876,"WLF","Wallis and Futuna","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70745,876,"WLF","Wallis and Futuna","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70746,876,"WLF","Wallis and Futuna","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70747,876,"WLF","Wallis and Futuna","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70748,876,"WLF","Wallis and Futuna","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70749,876,"WLF","Wallis and Futuna","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70750,876,"WLF","Wallis and Futuna","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70751,876,"WLF","Wallis and Futuna","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70752,876,"WLF","Wallis and Futuna","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70753,876,"WLF","Wallis and Futuna","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70754,876,"WLF","Wallis and Futuna","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70755,876,"WLF","Wallis and Futuna","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70756,876,"WLF","Wallis and Futuna","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70757,876,"WLF","Wallis and Futuna","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70758,876,"WLF","Wallis and Futuna","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70759,876,"WLF","Wallis and Futuna","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70760,876,"WLF","Wallis and Futuna","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70761,876,"WLF","Wallis and Futuna","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70762,876,"WLF","Wallis and Futuna","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70763,876,"WLF","Wallis and Futuna","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70764,876,"WLF","Wallis and Futuna","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70765,876,"WLF","Wallis and Futuna","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WLF/wlf_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70766,882,"WSM","Samoa","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70767,882,"WSM","Samoa","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70768,882,"WSM","Samoa","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70769,882,"WSM","Samoa","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70770,882,"WSM","Samoa","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70771,882,"WSM","Samoa","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70772,882,"WSM","Samoa","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70773,882,"WSM","Samoa","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70774,882,"WSM","Samoa","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70775,882,"WSM","Samoa","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70776,882,"WSM","Samoa","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70777,882,"WSM","Samoa","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70778,882,"WSM","Samoa","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70779,882,"WSM","Samoa","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70780,882,"WSM","Samoa","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70781,882,"WSM","Samoa","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70782,882,"WSM","Samoa","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70783,882,"WSM","Samoa","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70784,882,"WSM","Samoa","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70785,882,"WSM","Samoa","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70786,882,"WSM","Samoa","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70787,882,"WSM","Samoa","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70788,882,"WSM","Samoa","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70789,882,"WSM","Samoa","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70790,882,"WSM","Samoa","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70791,882,"WSM","Samoa","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70792,882,"WSM","Samoa","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70793,882,"WSM","Samoa","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70794,882,"WSM","Samoa","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70795,882,"WSM","Samoa","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70796,882,"WSM","Samoa","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70797,882,"WSM","Samoa","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70798,882,"WSM","Samoa","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70799,882,"WSM","Samoa","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70800,882,"WSM","Samoa","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70801,882,"WSM","Samoa","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/WSM/wsm_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70802,887,"YEM","Yemen","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70803,887,"YEM","Yemen","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70804,887,"YEM","Yemen","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70805,887,"YEM","Yemen","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70806,887,"YEM","Yemen","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70807,887,"YEM","Yemen","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70808,887,"YEM","Yemen","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70809,887,"YEM","Yemen","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70810,887,"YEM","Yemen","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70811,887,"YEM","Yemen","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70812,887,"YEM","Yemen","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70813,887,"YEM","Yemen","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70814,887,"YEM","Yemen","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70815,887,"YEM","Yemen","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70816,887,"YEM","Yemen","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70817,887,"YEM","Yemen","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70818,887,"YEM","Yemen","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70819,887,"YEM","Yemen","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70820,887,"YEM","Yemen","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70821,887,"YEM","Yemen","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70822,887,"YEM","Yemen","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70823,887,"YEM","Yemen","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70824,887,"YEM","Yemen","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70825,887,"YEM","Yemen","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70826,887,"YEM","Yemen","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70827,887,"YEM","Yemen","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70828,887,"YEM","Yemen","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70829,887,"YEM","Yemen","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70830,887,"YEM","Yemen","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70831,887,"YEM","Yemen","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70832,887,"YEM","Yemen","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70833,887,"YEM","Yemen","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70834,887,"YEM","Yemen","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70835,887,"YEM","Yemen","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70836,887,"YEM","Yemen","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70837,887,"YEM","Yemen","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/YEM/yem_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70838,894,"ZMB","Zambia","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70839,894,"ZMB","Zambia","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70840,894,"ZMB","Zambia","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70841,894,"ZMB","Zambia","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70842,894,"ZMB","Zambia","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70843,894,"ZMB","Zambia","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70844,894,"ZMB","Zambia","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70845,894,"ZMB","Zambia","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70846,894,"ZMB","Zambia","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70847,894,"ZMB","Zambia","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70848,894,"ZMB","Zambia","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70849,894,"ZMB","Zambia","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70850,894,"ZMB","Zambia","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70851,894,"ZMB","Zambia","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70852,894,"ZMB","Zambia","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70853,894,"ZMB","Zambia","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70854,894,"ZMB","Zambia","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70855,894,"ZMB","Zambia","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70856,894,"ZMB","Zambia","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70857,894,"ZMB","Zambia","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70858,894,"ZMB","Zambia","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70859,894,"ZMB","Zambia","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70860,894,"ZMB","Zambia","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70861,894,"ZMB","Zambia","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70862,894,"ZMB","Zambia","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70863,894,"ZMB","Zambia","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70864,894,"ZMB","Zambia","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70865,894,"ZMB","Zambia","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70866,894,"ZMB","Zambia","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70867,894,"ZMB","Zambia","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70868,894,"ZMB","Zambia","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70869,894,"ZMB","Zambia","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70870,894,"ZMB","Zambia","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70871,894,"ZMB","Zambia","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70872,894,"ZMB","Zambia","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70873,894,"ZMB","Zambia","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/ZMB/zmb_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70874,900,"KOS","Kosovo","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70875,900,"KOS","Kosovo","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70876,900,"KOS","Kosovo","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70877,900,"KOS","Kosovo","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70878,900,"KOS","Kosovo","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70879,900,"KOS","Kosovo","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70880,900,"KOS","Kosovo","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70881,900,"KOS","Kosovo","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70882,900,"KOS","Kosovo","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70883,900,"KOS","Kosovo","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70884,900,"KOS","Kosovo","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70885,900,"KOS","Kosovo","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70886,900,"KOS","Kosovo","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70887,900,"KOS","Kosovo","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70888,900,"KOS","Kosovo","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70889,900,"KOS","Kosovo","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70890,900,"KOS","Kosovo","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70891,900,"KOS","Kosovo","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70892,900,"KOS","Kosovo","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70893,900,"KOS","Kosovo","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70894,900,"KOS","Kosovo","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70895,900,"KOS","Kosovo","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70896,900,"KOS","Kosovo","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70897,900,"KOS","Kosovo","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70898,900,"KOS","Kosovo","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70899,900,"KOS","Kosovo","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70900,900,"KOS","Kosovo","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70901,900,"KOS","Kosovo","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70902,900,"KOS","Kosovo","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70903,900,"KOS","Kosovo","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70904,900,"KOS","Kosovo","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70905,900,"KOS","Kosovo","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70906,900,"KOS","Kosovo","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70907,900,"KOS","Kosovo","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70908,900,"KOS","Kosovo","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70909,900,"KOS","Kosovo","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/KOS/kos_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70910,901,"SPR","Spratly Islands","agesex_f_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_0_2019.tif","Estimated 0-12 month old female per grid-cell  in 2019"
70911,901,"SPR","Spratly Islands","agesex_f_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_1_2019.tif","Estimated 1-4 year old female per grid-cell  in 2019"
70912,901,"SPR","Spratly Islands","agesex_f_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_5_2019.tif","Estimated 5-8 year old female per grid-cell  in 2019"
70913,901,"SPR","Spratly Islands","agesex_f_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_10_2019.tif","Estimated 10-14 year old female per grid-cell  in 2019"
70914,901,"SPR","Spratly Islands","agesex_f_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_15_2019.tif","Estimated 15-19 year old female per grid-cell  in 2019"
70915,901,"SPR","Spratly Islands","agesex_f_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_20_2019.tif","Estimated 20-24 year old female per grid-cell  in 2019"
70916,901,"SPR","Spratly Islands","agesex_f_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_25_2019.tif","Estimated 25-29 year old female per grid-cell  in 2019"
70917,901,"SPR","Spratly Islands","agesex_f_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_30_2019.tif","Estimated 30-34 year old female per grid-cell  in 2019"
70918,901,"SPR","Spratly Islands","agesex_f_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_35_2019.tif","Estimated 35-39 year old female per grid-cell  in 2019"
70919,901,"SPR","Spratly Islands","agesex_f_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_40_2019.tif","Estimated 40-44 year old female per grid-cell  in 2019"
70920,901,"SPR","Spratly Islands","agesex_f_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_45_2019.tif","Estimated 45-49 year old female per grid-cell  in 2019"
70921,901,"SPR","Spratly Islands","agesex_f_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_50_2019.tif","Estimated 50-54 year old female per grid-cell  in 2019"
70922,901,"SPR","Spratly Islands","agesex_f_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_55_2019.tif","Estimated 55-59 year old female per grid-cell  in 2019"
70923,901,"SPR","Spratly Islands","agesex_f_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_60_2019.tif","Estimated 60-64 year old female per grid-cell  in 2019"
70924,901,"SPR","Spratly Islands","agesex_f_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_65_2019.tif","Estimated 65-69 year old female per grid-cell  in 2019"
70925,901,"SPR","Spratly Islands","agesex_f_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_70_2019.tif","Estimated 70-74 year old female per grid-cell  in 2019"
70926,901,"SPR","Spratly Islands","agesex_f_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_75_2019.tif","Estimated 75-79 year old female per grid-cell  in 2019"
70927,901,"SPR","Spratly Islands","agesex_f_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_f_80_2019.tif","Estimated 80 year old female per grid-cell  in 2019"
70928,901,"SPR","Spratly Islands","agesex_m_0_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_0_2019.tif","Estimated 0-12 month old male per grid-cell  in 2019"
70929,901,"SPR","Spratly Islands","agesex_m_1_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_1_2019.tif","Estimated 1-4 year old male per grid-cell  in 2019"
70930,901,"SPR","Spratly Islands","agesex_m_5_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_5_2019.tif","Estimated 5-8 year old male per grid-cell  in 2019"
70931,901,"SPR","Spratly Islands","agesex_m_10_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_10_2019.tif","Estimated 10-14 year old male per grid-cell  in 2019"
70932,901,"SPR","Spratly Islands","agesex_m_15_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_15_2019.tif","Estimated 15-19 year old male per grid-cell  in 2019"
70933,901,"SPR","Spratly Islands","agesex_m_20_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_20_2019.tif","Estimated 20-24 year old male per grid-cell  in 2019"
70934,901,"SPR","Spratly Islands","agesex_m_25_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_25_2019.tif","Estimated 25-29 year old male per grid-cell  in 2019"
70935,901,"SPR","Spratly Islands","agesex_m_30_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_30_2019.tif","Estimated 30-34 year old male per grid-cell  in 2019"
70936,901,"SPR","Spratly Islands","agesex_m_35_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_35_2019.tif","Estimated 35-39 year old male per grid-cell  in 2019"
70937,901,"SPR","Spratly Islands","agesex_m_40_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_40_2019.tif","Estimated 40-44 year old male per grid-cell  in 2019"
70938,901,"SPR","Spratly Islands","agesex_m_45_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_45_2019.tif","Estimated 45-49 year old male per grid-cell  in 2019"
70939,901,"SPR","Spratly Islands","agesex_m_50_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_50_2019.tif","Estimated 50-54 year old male per grid-cell  in 2019"
70940,901,"SPR","Spratly Islands","agesex_m_55_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_55_2019.tif","Estimated 55-59 year old male per grid-cell  in 2019"
70941,901,"SPR","Spratly Islands","agesex_m_60_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_60_2019.tif","Estimated 60-64 year old male per grid-cell  in 2019"
70942,901,"SPR","Spratly Islands","agesex_m_65_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_65_2019.tif","Estimated 65-69 year old male per grid-cell  in 2019"
70943,901,"SPR","Spratly Islands","agesex_m_70_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_70_2019.tif","Estimated 70-74 year old male per grid-cell  in 2019"
70944,901,"SPR","Spratly Islands","agesex_m_75_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_75_2019.tif","Estimated 75-79 year old male per grid-cell  in 2019"
70945,901,"SPR","Spratly Islands","agesex_m_80_2019","GIS/AgeSex_structures/Global_2000_2020/2019/SPR/spr_m_80_2019.tif","Estimated 80 year old male per grid-cell  in 2019"
70946,643,"RUS","Russia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
70947,643,"RUS","Russia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
70948,643,"RUS","Russia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
70949,643,"RUS","Russia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
70950,643,"RUS","Russia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
70951,643,"RUS","Russia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
70952,643,"RUS","Russia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
70953,643,"RUS","Russia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
70954,643,"RUS","Russia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
70955,643,"RUS","Russia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
70956,643,"RUS","Russia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
70957,643,"RUS","Russia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
70958,643,"RUS","Russia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
70959,643,"RUS","Russia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
70960,643,"RUS","Russia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
70961,643,"RUS","Russia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
70962,643,"RUS","Russia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
70963,643,"RUS","Russia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
70964,643,"RUS","Russia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
70965,643,"RUS","Russia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
70966,643,"RUS","Russia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
70967,643,"RUS","Russia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
70968,643,"RUS","Russia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
70969,643,"RUS","Russia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
70970,643,"RUS","Russia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
70971,643,"RUS","Russia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
70972,643,"RUS","Russia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
70973,643,"RUS","Russia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
70974,643,"RUS","Russia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
70975,643,"RUS","Russia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
70976,643,"RUS","Russia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
70977,643,"RUS","Russia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
70978,643,"RUS","Russia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
70979,643,"RUS","Russia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
70980,643,"RUS","Russia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
70981,643,"RUS","Russia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RUS/rus_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
70982,360,"IDN","Indonesia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
70983,360,"IDN","Indonesia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
70984,360,"IDN","Indonesia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
70985,360,"IDN","Indonesia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
70986,360,"IDN","Indonesia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
70987,360,"IDN","Indonesia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
70988,360,"IDN","Indonesia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
70989,360,"IDN","Indonesia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
70990,360,"IDN","Indonesia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
70991,360,"IDN","Indonesia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
70992,360,"IDN","Indonesia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
70993,360,"IDN","Indonesia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
70994,360,"IDN","Indonesia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
70995,360,"IDN","Indonesia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
70996,360,"IDN","Indonesia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
70997,360,"IDN","Indonesia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
70998,360,"IDN","Indonesia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
70999,360,"IDN","Indonesia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71000,360,"IDN","Indonesia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71001,360,"IDN","Indonesia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71002,360,"IDN","Indonesia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71003,360,"IDN","Indonesia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71004,360,"IDN","Indonesia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71005,360,"IDN","Indonesia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71006,360,"IDN","Indonesia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71007,360,"IDN","Indonesia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71008,360,"IDN","Indonesia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71009,360,"IDN","Indonesia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71010,360,"IDN","Indonesia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71011,360,"IDN","Indonesia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71012,360,"IDN","Indonesia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71013,360,"IDN","Indonesia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71014,360,"IDN","Indonesia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71015,360,"IDN","Indonesia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71016,360,"IDN","Indonesia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71017,360,"IDN","Indonesia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IDN/idn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71018,840,"USA","United States","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71019,840,"USA","United States","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71020,840,"USA","United States","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71021,840,"USA","United States","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71022,840,"USA","United States","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71023,840,"USA","United States","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71024,840,"USA","United States","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71025,840,"USA","United States","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71026,840,"USA","United States","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71027,840,"USA","United States","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71028,840,"USA","United States","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71029,840,"USA","United States","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71030,840,"USA","United States","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71031,840,"USA","United States","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71032,840,"USA","United States","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71033,840,"USA","United States","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71034,840,"USA","United States","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71035,840,"USA","United States","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71036,840,"USA","United States","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71037,840,"USA","United States","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71038,840,"USA","United States","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71039,840,"USA","United States","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71040,840,"USA","United States","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71041,840,"USA","United States","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71042,840,"USA","United States","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71043,840,"USA","United States","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71044,840,"USA","United States","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71045,840,"USA","United States","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71046,840,"USA","United States","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71047,840,"USA","United States","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71048,840,"USA","United States","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71049,840,"USA","United States","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71050,840,"USA","United States","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71051,840,"USA","United States","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71052,840,"USA","United States","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71053,840,"USA","United States","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/USA/usa_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71054,850,"VIR","Virgin_Islands_U_S","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71055,850,"VIR","Virgin_Islands_U_S","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71056,850,"VIR","Virgin_Islands_U_S","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71057,850,"VIR","Virgin_Islands_U_S","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71058,850,"VIR","Virgin_Islands_U_S","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71059,850,"VIR","Virgin_Islands_U_S","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71060,850,"VIR","Virgin_Islands_U_S","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71061,850,"VIR","Virgin_Islands_U_S","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71062,850,"VIR","Virgin_Islands_U_S","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71063,850,"VIR","Virgin_Islands_U_S","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71064,850,"VIR","Virgin_Islands_U_S","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71065,850,"VIR","Virgin_Islands_U_S","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71066,850,"VIR","Virgin_Islands_U_S","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71067,850,"VIR","Virgin_Islands_U_S","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71068,850,"VIR","Virgin_Islands_U_S","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71069,850,"VIR","Virgin_Islands_U_S","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71070,850,"VIR","Virgin_Islands_U_S","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71071,850,"VIR","Virgin_Islands_U_S","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71072,850,"VIR","Virgin_Islands_U_S","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71073,850,"VIR","Virgin_Islands_U_S","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71074,850,"VIR","Virgin_Islands_U_S","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71075,850,"VIR","Virgin_Islands_U_S","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71076,850,"VIR","Virgin_Islands_U_S","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71077,850,"VIR","Virgin_Islands_U_S","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71078,850,"VIR","Virgin_Islands_U_S","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71079,850,"VIR","Virgin_Islands_U_S","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71080,850,"VIR","Virgin_Islands_U_S","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71081,850,"VIR","Virgin_Islands_U_S","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71082,850,"VIR","Virgin_Islands_U_S","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71083,850,"VIR","Virgin_Islands_U_S","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71084,850,"VIR","Virgin_Islands_U_S","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71085,850,"VIR","Virgin_Islands_U_S","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71086,850,"VIR","Virgin_Islands_U_S","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71087,850,"VIR","Virgin_Islands_U_S","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71088,850,"VIR","Virgin_Islands_U_S","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71089,850,"VIR","Virgin_Islands_U_S","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VIR/vir_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71090,304,"GRL","Greenland","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71091,304,"GRL","Greenland","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71092,304,"GRL","Greenland","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71093,304,"GRL","Greenland","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71094,304,"GRL","Greenland","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71095,304,"GRL","Greenland","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71096,304,"GRL","Greenland","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71097,304,"GRL","Greenland","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71098,304,"GRL","Greenland","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71099,304,"GRL","Greenland","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71100,304,"GRL","Greenland","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71101,304,"GRL","Greenland","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71102,304,"GRL","Greenland","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71103,304,"GRL","Greenland","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71104,304,"GRL","Greenland","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71105,304,"GRL","Greenland","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71106,304,"GRL","Greenland","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71107,304,"GRL","Greenland","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71108,304,"GRL","Greenland","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71109,304,"GRL","Greenland","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71110,304,"GRL","Greenland","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71111,304,"GRL","Greenland","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71112,304,"GRL","Greenland","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71113,304,"GRL","Greenland","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71114,304,"GRL","Greenland","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71115,304,"GRL","Greenland","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71116,304,"GRL","Greenland","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71117,304,"GRL","Greenland","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71118,304,"GRL","Greenland","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71119,304,"GRL","Greenland","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71120,304,"GRL","Greenland","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71121,304,"GRL","Greenland","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71122,304,"GRL","Greenland","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71123,304,"GRL","Greenland","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71124,304,"GRL","Greenland","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71125,304,"GRL","Greenland","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRL/grl_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71126,156,"CHN","China","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71127,156,"CHN","China","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71128,156,"CHN","China","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71129,156,"CHN","China","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71130,156,"CHN","China","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71131,156,"CHN","China","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71132,156,"CHN","China","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71133,156,"CHN","China","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71134,156,"CHN","China","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71135,156,"CHN","China","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71136,156,"CHN","China","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71137,156,"CHN","China","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71138,156,"CHN","China","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71139,156,"CHN","China","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71140,156,"CHN","China","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71141,156,"CHN","China","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71142,156,"CHN","China","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71143,156,"CHN","China","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71144,156,"CHN","China","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71145,156,"CHN","China","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71146,156,"CHN","China","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71147,156,"CHN","China","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71148,156,"CHN","China","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71149,156,"CHN","China","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71150,156,"CHN","China","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71151,156,"CHN","China","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71152,156,"CHN","China","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71153,156,"CHN","China","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71154,156,"CHN","China","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71155,156,"CHN","China","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71156,156,"CHN","China","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71157,156,"CHN","China","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71158,156,"CHN","China","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71159,156,"CHN","China","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71160,156,"CHN","China","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71161,156,"CHN","China","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHN/chn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71162,36,"AUS","Australia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71163,36,"AUS","Australia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71164,36,"AUS","Australia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71165,36,"AUS","Australia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71166,36,"AUS","Australia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71167,36,"AUS","Australia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71168,36,"AUS","Australia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71169,36,"AUS","Australia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71170,36,"AUS","Australia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71171,36,"AUS","Australia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71172,36,"AUS","Australia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71173,36,"AUS","Australia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71174,36,"AUS","Australia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71175,36,"AUS","Australia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71176,36,"AUS","Australia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71177,36,"AUS","Australia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71178,36,"AUS","Australia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71179,36,"AUS","Australia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71180,36,"AUS","Australia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71181,36,"AUS","Australia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71182,36,"AUS","Australia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71183,36,"AUS","Australia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71184,36,"AUS","Australia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71185,36,"AUS","Australia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71186,36,"AUS","Australia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71187,36,"AUS","Australia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71188,36,"AUS","Australia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71189,36,"AUS","Australia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71190,36,"AUS","Australia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71191,36,"AUS","Australia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71192,36,"AUS","Australia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71193,36,"AUS","Australia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71194,36,"AUS","Australia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71195,36,"AUS","Australia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71196,36,"AUS","Australia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71197,36,"AUS","Australia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUS/aus_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71198,76,"BRA","Brazil","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71199,76,"BRA","Brazil","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71200,76,"BRA","Brazil","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71201,76,"BRA","Brazil","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71202,76,"BRA","Brazil","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71203,76,"BRA","Brazil","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71204,76,"BRA","Brazil","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71205,76,"BRA","Brazil","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71206,76,"BRA","Brazil","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71207,76,"BRA","Brazil","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71208,76,"BRA","Brazil","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71209,76,"BRA","Brazil","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71210,76,"BRA","Brazil","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71211,76,"BRA","Brazil","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71212,76,"BRA","Brazil","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71213,76,"BRA","Brazil","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71214,76,"BRA","Brazil","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71215,76,"BRA","Brazil","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71216,76,"BRA","Brazil","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71217,76,"BRA","Brazil","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71218,76,"BRA","Brazil","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71219,76,"BRA","Brazil","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71220,76,"BRA","Brazil","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71221,76,"BRA","Brazil","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71222,76,"BRA","Brazil","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71223,76,"BRA","Brazil","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71224,76,"BRA","Brazil","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71225,76,"BRA","Brazil","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71226,76,"BRA","Brazil","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71227,76,"BRA","Brazil","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71228,76,"BRA","Brazil","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71229,76,"BRA","Brazil","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71230,76,"BRA","Brazil","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71231,76,"BRA","Brazil","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71232,76,"BRA","Brazil","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71233,76,"BRA","Brazil","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRA/bra_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71234,124,"CAN","Canada","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71235,124,"CAN","Canada","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71236,124,"CAN","Canada","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71237,124,"CAN","Canada","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71238,124,"CAN","Canada","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71239,124,"CAN","Canada","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71240,124,"CAN","Canada","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71241,124,"CAN","Canada","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71242,124,"CAN","Canada","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71243,124,"CAN","Canada","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71244,124,"CAN","Canada","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71245,124,"CAN","Canada","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71246,124,"CAN","Canada","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71247,124,"CAN","Canada","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71248,124,"CAN","Canada","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71249,124,"CAN","Canada","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71250,124,"CAN","Canada","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71251,124,"CAN","Canada","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71252,124,"CAN","Canada","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71253,124,"CAN","Canada","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71254,124,"CAN","Canada","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71255,124,"CAN","Canada","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71256,124,"CAN","Canada","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71257,124,"CAN","Canada","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71258,124,"CAN","Canada","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71259,124,"CAN","Canada","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71260,124,"CAN","Canada","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71261,124,"CAN","Canada","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71262,124,"CAN","Canada","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71263,124,"CAN","Canada","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71264,124,"CAN","Canada","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71265,124,"CAN","Canada","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71266,124,"CAN","Canada","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71267,124,"CAN","Canada","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71268,124,"CAN","Canada","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71269,124,"CAN","Canada","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAN/can_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71270,152,"CHL","Chile","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71271,152,"CHL","Chile","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71272,152,"CHL","Chile","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71273,152,"CHL","Chile","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71274,152,"CHL","Chile","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71275,152,"CHL","Chile","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71276,152,"CHL","Chile","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71277,152,"CHL","Chile","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71278,152,"CHL","Chile","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71279,152,"CHL","Chile","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71280,152,"CHL","Chile","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71281,152,"CHL","Chile","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71282,152,"CHL","Chile","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71283,152,"CHL","Chile","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71284,152,"CHL","Chile","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71285,152,"CHL","Chile","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71286,152,"CHL","Chile","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71287,152,"CHL","Chile","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71288,152,"CHL","Chile","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71289,152,"CHL","Chile","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71290,152,"CHL","Chile","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71291,152,"CHL","Chile","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71292,152,"CHL","Chile","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71293,152,"CHL","Chile","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71294,152,"CHL","Chile","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71295,152,"CHL","Chile","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71296,152,"CHL","Chile","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71297,152,"CHL","Chile","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71298,152,"CHL","Chile","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71299,152,"CHL","Chile","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71300,152,"CHL","Chile","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71301,152,"CHL","Chile","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71302,152,"CHL","Chile","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71303,152,"CHL","Chile","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71304,152,"CHL","Chile","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71305,152,"CHL","Chile","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHL/chl_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71306,4,"AFG","Afghanistan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71307,4,"AFG","Afghanistan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71308,4,"AFG","Afghanistan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71309,4,"AFG","Afghanistan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71310,4,"AFG","Afghanistan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71311,4,"AFG","Afghanistan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71312,4,"AFG","Afghanistan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71313,4,"AFG","Afghanistan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71314,4,"AFG","Afghanistan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71315,4,"AFG","Afghanistan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71316,4,"AFG","Afghanistan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71317,4,"AFG","Afghanistan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71318,4,"AFG","Afghanistan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71319,4,"AFG","Afghanistan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71320,4,"AFG","Afghanistan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71321,4,"AFG","Afghanistan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71322,4,"AFG","Afghanistan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71323,4,"AFG","Afghanistan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71324,4,"AFG","Afghanistan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71325,4,"AFG","Afghanistan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71326,4,"AFG","Afghanistan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71327,4,"AFG","Afghanistan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71328,4,"AFG","Afghanistan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71329,4,"AFG","Afghanistan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71330,4,"AFG","Afghanistan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71331,4,"AFG","Afghanistan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71332,4,"AFG","Afghanistan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71333,4,"AFG","Afghanistan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71334,4,"AFG","Afghanistan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71335,4,"AFG","Afghanistan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71336,4,"AFG","Afghanistan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71337,4,"AFG","Afghanistan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71338,4,"AFG","Afghanistan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71339,4,"AFG","Afghanistan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71340,4,"AFG","Afghanistan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71341,4,"AFG","Afghanistan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AFG/afg_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71342,8,"ALB","Albania","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71343,8,"ALB","Albania","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71344,8,"ALB","Albania","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71345,8,"ALB","Albania","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71346,8,"ALB","Albania","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71347,8,"ALB","Albania","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71348,8,"ALB","Albania","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71349,8,"ALB","Albania","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71350,8,"ALB","Albania","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71351,8,"ALB","Albania","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71352,8,"ALB","Albania","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71353,8,"ALB","Albania","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71354,8,"ALB","Albania","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71355,8,"ALB","Albania","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71356,8,"ALB","Albania","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71357,8,"ALB","Albania","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71358,8,"ALB","Albania","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71359,8,"ALB","Albania","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71360,8,"ALB","Albania","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71361,8,"ALB","Albania","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71362,8,"ALB","Albania","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71363,8,"ALB","Albania","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71364,8,"ALB","Albania","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71365,8,"ALB","Albania","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71366,8,"ALB","Albania","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71367,8,"ALB","Albania","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71368,8,"ALB","Albania","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71369,8,"ALB","Albania","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71370,8,"ALB","Albania","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71371,8,"ALB","Albania","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71372,8,"ALB","Albania","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71373,8,"ALB","Albania","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71374,8,"ALB","Albania","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71375,8,"ALB","Albania","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71376,8,"ALB","Albania","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71377,8,"ALB","Albania","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALB/alb_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71378,10,"ATA","Antarctica","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71379,10,"ATA","Antarctica","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71380,10,"ATA","Antarctica","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71381,10,"ATA","Antarctica","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71382,10,"ATA","Antarctica","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71383,10,"ATA","Antarctica","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71384,10,"ATA","Antarctica","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71385,10,"ATA","Antarctica","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71386,10,"ATA","Antarctica","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71387,10,"ATA","Antarctica","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71388,10,"ATA","Antarctica","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71389,10,"ATA","Antarctica","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71390,10,"ATA","Antarctica","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71391,10,"ATA","Antarctica","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71392,10,"ATA","Antarctica","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71393,10,"ATA","Antarctica","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71394,10,"ATA","Antarctica","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71395,10,"ATA","Antarctica","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71396,10,"ATA","Antarctica","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71397,10,"ATA","Antarctica","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71398,10,"ATA","Antarctica","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71399,10,"ATA","Antarctica","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71400,10,"ATA","Antarctica","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71401,10,"ATA","Antarctica","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71402,10,"ATA","Antarctica","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71403,10,"ATA","Antarctica","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71404,10,"ATA","Antarctica","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71405,10,"ATA","Antarctica","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71406,10,"ATA","Antarctica","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71407,10,"ATA","Antarctica","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71408,10,"ATA","Antarctica","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71409,10,"ATA","Antarctica","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71410,10,"ATA","Antarctica","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71411,10,"ATA","Antarctica","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71412,10,"ATA","Antarctica","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71413,10,"ATA","Antarctica","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATA/ata_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71414,12,"DZA","Algeria","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71415,12,"DZA","Algeria","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71416,12,"DZA","Algeria","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71417,12,"DZA","Algeria","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71418,12,"DZA","Algeria","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71419,12,"DZA","Algeria","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71420,12,"DZA","Algeria","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71421,12,"DZA","Algeria","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71422,12,"DZA","Algeria","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71423,12,"DZA","Algeria","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71424,12,"DZA","Algeria","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71425,12,"DZA","Algeria","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71426,12,"DZA","Algeria","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71427,12,"DZA","Algeria","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71428,12,"DZA","Algeria","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71429,12,"DZA","Algeria","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71430,12,"DZA","Algeria","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71431,12,"DZA","Algeria","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71432,12,"DZA","Algeria","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71433,12,"DZA","Algeria","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71434,12,"DZA","Algeria","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71435,12,"DZA","Algeria","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71436,12,"DZA","Algeria","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71437,12,"DZA","Algeria","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71438,12,"DZA","Algeria","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71439,12,"DZA","Algeria","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71440,12,"DZA","Algeria","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71441,12,"DZA","Algeria","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71442,12,"DZA","Algeria","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71443,12,"DZA","Algeria","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71444,12,"DZA","Algeria","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71445,12,"DZA","Algeria","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71446,12,"DZA","Algeria","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71447,12,"DZA","Algeria","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71448,12,"DZA","Algeria","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71449,12,"DZA","Algeria","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DZA/dza_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71450,16,"ASM","American Samoa","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71451,16,"ASM","American Samoa","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71452,16,"ASM","American Samoa","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71453,16,"ASM","American Samoa","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71454,16,"ASM","American Samoa","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71455,16,"ASM","American Samoa","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71456,16,"ASM","American Samoa","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71457,16,"ASM","American Samoa","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71458,16,"ASM","American Samoa","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71459,16,"ASM","American Samoa","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71460,16,"ASM","American Samoa","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71461,16,"ASM","American Samoa","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71462,16,"ASM","American Samoa","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71463,16,"ASM","American Samoa","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71464,16,"ASM","American Samoa","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71465,16,"ASM","American Samoa","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71466,16,"ASM","American Samoa","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71467,16,"ASM","American Samoa","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71468,16,"ASM","American Samoa","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71469,16,"ASM","American Samoa","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71470,16,"ASM","American Samoa","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71471,16,"ASM","American Samoa","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71472,16,"ASM","American Samoa","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71473,16,"ASM","American Samoa","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71474,16,"ASM","American Samoa","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71475,16,"ASM","American Samoa","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71476,16,"ASM","American Samoa","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71477,16,"ASM","American Samoa","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71478,16,"ASM","American Samoa","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71479,16,"ASM","American Samoa","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71480,16,"ASM","American Samoa","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71481,16,"ASM","American Samoa","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71482,16,"ASM","American Samoa","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71483,16,"ASM","American Samoa","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71484,16,"ASM","American Samoa","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71485,16,"ASM","American Samoa","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ASM/asm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71486,20,"AND","Andorra","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71487,20,"AND","Andorra","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71488,20,"AND","Andorra","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71489,20,"AND","Andorra","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71490,20,"AND","Andorra","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71491,20,"AND","Andorra","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71492,20,"AND","Andorra","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71493,20,"AND","Andorra","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71494,20,"AND","Andorra","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71495,20,"AND","Andorra","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71496,20,"AND","Andorra","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71497,20,"AND","Andorra","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71498,20,"AND","Andorra","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71499,20,"AND","Andorra","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71500,20,"AND","Andorra","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71501,20,"AND","Andorra","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71502,20,"AND","Andorra","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71503,20,"AND","Andorra","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71504,20,"AND","Andorra","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71505,20,"AND","Andorra","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71506,20,"AND","Andorra","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71507,20,"AND","Andorra","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71508,20,"AND","Andorra","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71509,20,"AND","Andorra","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71510,20,"AND","Andorra","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71511,20,"AND","Andorra","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71512,20,"AND","Andorra","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71513,20,"AND","Andorra","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71514,20,"AND","Andorra","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71515,20,"AND","Andorra","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71516,20,"AND","Andorra","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71517,20,"AND","Andorra","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71518,20,"AND","Andorra","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71519,20,"AND","Andorra","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71520,20,"AND","Andorra","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71521,20,"AND","Andorra","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AND/and_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71522,24,"AGO","Angola","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71523,24,"AGO","Angola","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71524,24,"AGO","Angola","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71525,24,"AGO","Angola","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71526,24,"AGO","Angola","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71527,24,"AGO","Angola","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71528,24,"AGO","Angola","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71529,24,"AGO","Angola","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71530,24,"AGO","Angola","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71531,24,"AGO","Angola","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71532,24,"AGO","Angola","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71533,24,"AGO","Angola","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71534,24,"AGO","Angola","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71535,24,"AGO","Angola","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71536,24,"AGO","Angola","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71537,24,"AGO","Angola","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71538,24,"AGO","Angola","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71539,24,"AGO","Angola","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71540,24,"AGO","Angola","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71541,24,"AGO","Angola","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71542,24,"AGO","Angola","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71543,24,"AGO","Angola","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71544,24,"AGO","Angola","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71545,24,"AGO","Angola","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71546,24,"AGO","Angola","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71547,24,"AGO","Angola","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71548,24,"AGO","Angola","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71549,24,"AGO","Angola","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71550,24,"AGO","Angola","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71551,24,"AGO","Angola","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71552,24,"AGO","Angola","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71553,24,"AGO","Angola","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71554,24,"AGO","Angola","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71555,24,"AGO","Angola","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71556,24,"AGO","Angola","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71557,24,"AGO","Angola","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AGO/ago_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71558,28,"ATG","Antigua and Barbuda","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71559,28,"ATG","Antigua and Barbuda","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71560,28,"ATG","Antigua and Barbuda","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71561,28,"ATG","Antigua and Barbuda","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71562,28,"ATG","Antigua and Barbuda","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71563,28,"ATG","Antigua and Barbuda","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71564,28,"ATG","Antigua and Barbuda","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71565,28,"ATG","Antigua and Barbuda","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71566,28,"ATG","Antigua and Barbuda","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71567,28,"ATG","Antigua and Barbuda","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71568,28,"ATG","Antigua and Barbuda","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71569,28,"ATG","Antigua and Barbuda","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71570,28,"ATG","Antigua and Barbuda","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71571,28,"ATG","Antigua and Barbuda","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71572,28,"ATG","Antigua and Barbuda","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71573,28,"ATG","Antigua and Barbuda","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71574,28,"ATG","Antigua and Barbuda","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71575,28,"ATG","Antigua and Barbuda","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71576,28,"ATG","Antigua and Barbuda","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71577,28,"ATG","Antigua and Barbuda","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71578,28,"ATG","Antigua and Barbuda","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71579,28,"ATG","Antigua and Barbuda","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71580,28,"ATG","Antigua and Barbuda","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71581,28,"ATG","Antigua and Barbuda","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71582,28,"ATG","Antigua and Barbuda","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71583,28,"ATG","Antigua and Barbuda","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71584,28,"ATG","Antigua and Barbuda","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71585,28,"ATG","Antigua and Barbuda","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71586,28,"ATG","Antigua and Barbuda","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71587,28,"ATG","Antigua and Barbuda","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71588,28,"ATG","Antigua and Barbuda","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71589,28,"ATG","Antigua and Barbuda","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71590,28,"ATG","Antigua and Barbuda","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71591,28,"ATG","Antigua and Barbuda","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71592,28,"ATG","Antigua and Barbuda","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71593,28,"ATG","Antigua and Barbuda","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATG/atg_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71594,31,"AZE","Azerbaijan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71595,31,"AZE","Azerbaijan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71596,31,"AZE","Azerbaijan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71597,31,"AZE","Azerbaijan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71598,31,"AZE","Azerbaijan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71599,31,"AZE","Azerbaijan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71600,31,"AZE","Azerbaijan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71601,31,"AZE","Azerbaijan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71602,31,"AZE","Azerbaijan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71603,31,"AZE","Azerbaijan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71604,31,"AZE","Azerbaijan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71605,31,"AZE","Azerbaijan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71606,31,"AZE","Azerbaijan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71607,31,"AZE","Azerbaijan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71608,31,"AZE","Azerbaijan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71609,31,"AZE","Azerbaijan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71610,31,"AZE","Azerbaijan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71611,31,"AZE","Azerbaijan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71612,31,"AZE","Azerbaijan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71613,31,"AZE","Azerbaijan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71614,31,"AZE","Azerbaijan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71615,31,"AZE","Azerbaijan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71616,31,"AZE","Azerbaijan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71617,31,"AZE","Azerbaijan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71618,31,"AZE","Azerbaijan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71619,31,"AZE","Azerbaijan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71620,31,"AZE","Azerbaijan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71621,31,"AZE","Azerbaijan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71622,31,"AZE","Azerbaijan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71623,31,"AZE","Azerbaijan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71624,31,"AZE","Azerbaijan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71625,31,"AZE","Azerbaijan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71626,31,"AZE","Azerbaijan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71627,31,"AZE","Azerbaijan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71628,31,"AZE","Azerbaijan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71629,31,"AZE","Azerbaijan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AZE/aze_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71630,32,"ARG","Argentina","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71631,32,"ARG","Argentina","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71632,32,"ARG","Argentina","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71633,32,"ARG","Argentina","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71634,32,"ARG","Argentina","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71635,32,"ARG","Argentina","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71636,32,"ARG","Argentina","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71637,32,"ARG","Argentina","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71638,32,"ARG","Argentina","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71639,32,"ARG","Argentina","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71640,32,"ARG","Argentina","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71641,32,"ARG","Argentina","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71642,32,"ARG","Argentina","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71643,32,"ARG","Argentina","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71644,32,"ARG","Argentina","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71645,32,"ARG","Argentina","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71646,32,"ARG","Argentina","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71647,32,"ARG","Argentina","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71648,32,"ARG","Argentina","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71649,32,"ARG","Argentina","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71650,32,"ARG","Argentina","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71651,32,"ARG","Argentina","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71652,32,"ARG","Argentina","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71653,32,"ARG","Argentina","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71654,32,"ARG","Argentina","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71655,32,"ARG","Argentina","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71656,32,"ARG","Argentina","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71657,32,"ARG","Argentina","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71658,32,"ARG","Argentina","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71659,32,"ARG","Argentina","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71660,32,"ARG","Argentina","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71661,32,"ARG","Argentina","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71662,32,"ARG","Argentina","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71663,32,"ARG","Argentina","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71664,32,"ARG","Argentina","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71665,32,"ARG","Argentina","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARG/arg_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71666,40,"AUT","Austria","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71667,40,"AUT","Austria","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71668,40,"AUT","Austria","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71669,40,"AUT","Austria","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71670,40,"AUT","Austria","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71671,40,"AUT","Austria","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71672,40,"AUT","Austria","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71673,40,"AUT","Austria","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71674,40,"AUT","Austria","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71675,40,"AUT","Austria","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71676,40,"AUT","Austria","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71677,40,"AUT","Austria","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71678,40,"AUT","Austria","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71679,40,"AUT","Austria","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71680,40,"AUT","Austria","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71681,40,"AUT","Austria","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71682,40,"AUT","Austria","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71683,40,"AUT","Austria","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71684,40,"AUT","Austria","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71685,40,"AUT","Austria","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71686,40,"AUT","Austria","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71687,40,"AUT","Austria","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71688,40,"AUT","Austria","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71689,40,"AUT","Austria","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71690,40,"AUT","Austria","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71691,40,"AUT","Austria","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71692,40,"AUT","Austria","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71693,40,"AUT","Austria","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71694,40,"AUT","Austria","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71695,40,"AUT","Austria","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71696,40,"AUT","Austria","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71697,40,"AUT","Austria","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71698,40,"AUT","Austria","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71699,40,"AUT","Austria","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71700,40,"AUT","Austria","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71701,40,"AUT","Austria","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AUT/aut_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71702,44,"BHS","Bahamas","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71703,44,"BHS","Bahamas","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71704,44,"BHS","Bahamas","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71705,44,"BHS","Bahamas","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71706,44,"BHS","Bahamas","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71707,44,"BHS","Bahamas","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71708,44,"BHS","Bahamas","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71709,44,"BHS","Bahamas","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71710,44,"BHS","Bahamas","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71711,44,"BHS","Bahamas","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71712,44,"BHS","Bahamas","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71713,44,"BHS","Bahamas","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71714,44,"BHS","Bahamas","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71715,44,"BHS","Bahamas","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71716,44,"BHS","Bahamas","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71717,44,"BHS","Bahamas","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71718,44,"BHS","Bahamas","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71719,44,"BHS","Bahamas","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71720,44,"BHS","Bahamas","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71721,44,"BHS","Bahamas","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71722,44,"BHS","Bahamas","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71723,44,"BHS","Bahamas","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71724,44,"BHS","Bahamas","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71725,44,"BHS","Bahamas","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71726,44,"BHS","Bahamas","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71727,44,"BHS","Bahamas","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71728,44,"BHS","Bahamas","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71729,44,"BHS","Bahamas","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71730,44,"BHS","Bahamas","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71731,44,"BHS","Bahamas","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71732,44,"BHS","Bahamas","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71733,44,"BHS","Bahamas","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71734,44,"BHS","Bahamas","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71735,44,"BHS","Bahamas","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71736,44,"BHS","Bahamas","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71737,44,"BHS","Bahamas","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHS/bhs_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71738,48,"BHR","Bahrain","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71739,48,"BHR","Bahrain","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71740,48,"BHR","Bahrain","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71741,48,"BHR","Bahrain","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71742,48,"BHR","Bahrain","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71743,48,"BHR","Bahrain","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71744,48,"BHR","Bahrain","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71745,48,"BHR","Bahrain","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71746,48,"BHR","Bahrain","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71747,48,"BHR","Bahrain","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71748,48,"BHR","Bahrain","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71749,48,"BHR","Bahrain","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71750,48,"BHR","Bahrain","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71751,48,"BHR","Bahrain","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71752,48,"BHR","Bahrain","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71753,48,"BHR","Bahrain","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71754,48,"BHR","Bahrain","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71755,48,"BHR","Bahrain","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71756,48,"BHR","Bahrain","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71757,48,"BHR","Bahrain","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71758,48,"BHR","Bahrain","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71759,48,"BHR","Bahrain","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71760,48,"BHR","Bahrain","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71761,48,"BHR","Bahrain","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71762,48,"BHR","Bahrain","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71763,48,"BHR","Bahrain","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71764,48,"BHR","Bahrain","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71765,48,"BHR","Bahrain","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71766,48,"BHR","Bahrain","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71767,48,"BHR","Bahrain","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71768,48,"BHR","Bahrain","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71769,48,"BHR","Bahrain","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71770,48,"BHR","Bahrain","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71771,48,"BHR","Bahrain","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71772,48,"BHR","Bahrain","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71773,48,"BHR","Bahrain","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BHR/bhr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71774,50,"BGD","Bangladesh","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71775,50,"BGD","Bangladesh","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71776,50,"BGD","Bangladesh","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71777,50,"BGD","Bangladesh","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71778,50,"BGD","Bangladesh","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71779,50,"BGD","Bangladesh","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71780,50,"BGD","Bangladesh","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71781,50,"BGD","Bangladesh","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71782,50,"BGD","Bangladesh","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71783,50,"BGD","Bangladesh","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71784,50,"BGD","Bangladesh","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71785,50,"BGD","Bangladesh","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71786,50,"BGD","Bangladesh","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71787,50,"BGD","Bangladesh","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71788,50,"BGD","Bangladesh","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71789,50,"BGD","Bangladesh","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71790,50,"BGD","Bangladesh","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71791,50,"BGD","Bangladesh","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71792,50,"BGD","Bangladesh","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71793,50,"BGD","Bangladesh","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71794,50,"BGD","Bangladesh","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71795,50,"BGD","Bangladesh","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71796,50,"BGD","Bangladesh","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71797,50,"BGD","Bangladesh","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71798,50,"BGD","Bangladesh","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71799,50,"BGD","Bangladesh","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71800,50,"BGD","Bangladesh","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71801,50,"BGD","Bangladesh","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71802,50,"BGD","Bangladesh","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71803,50,"BGD","Bangladesh","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71804,50,"BGD","Bangladesh","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71805,50,"BGD","Bangladesh","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71806,50,"BGD","Bangladesh","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71807,50,"BGD","Bangladesh","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71808,50,"BGD","Bangladesh","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71809,50,"BGD","Bangladesh","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGD/bgd_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71810,51,"ARM","Armenia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71811,51,"ARM","Armenia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71812,51,"ARM","Armenia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71813,51,"ARM","Armenia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71814,51,"ARM","Armenia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71815,51,"ARM","Armenia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71816,51,"ARM","Armenia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71817,51,"ARM","Armenia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71818,51,"ARM","Armenia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71819,51,"ARM","Armenia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71820,51,"ARM","Armenia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71821,51,"ARM","Armenia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71822,51,"ARM","Armenia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71823,51,"ARM","Armenia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71824,51,"ARM","Armenia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71825,51,"ARM","Armenia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71826,51,"ARM","Armenia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71827,51,"ARM","Armenia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71828,51,"ARM","Armenia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71829,51,"ARM","Armenia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71830,51,"ARM","Armenia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71831,51,"ARM","Armenia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71832,51,"ARM","Armenia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71833,51,"ARM","Armenia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71834,51,"ARM","Armenia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71835,51,"ARM","Armenia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71836,51,"ARM","Armenia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71837,51,"ARM","Armenia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71838,51,"ARM","Armenia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71839,51,"ARM","Armenia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71840,51,"ARM","Armenia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71841,51,"ARM","Armenia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71842,51,"ARM","Armenia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71843,51,"ARM","Armenia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71844,51,"ARM","Armenia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71845,51,"ARM","Armenia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARM/arm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71846,52,"BRB","Barbados","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71847,52,"BRB","Barbados","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71848,52,"BRB","Barbados","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71849,52,"BRB","Barbados","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71850,52,"BRB","Barbados","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71851,52,"BRB","Barbados","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71852,52,"BRB","Barbados","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71853,52,"BRB","Barbados","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71854,52,"BRB","Barbados","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71855,52,"BRB","Barbados","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71856,52,"BRB","Barbados","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71857,52,"BRB","Barbados","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71858,52,"BRB","Barbados","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71859,52,"BRB","Barbados","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71860,52,"BRB","Barbados","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71861,52,"BRB","Barbados","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71862,52,"BRB","Barbados","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71863,52,"BRB","Barbados","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71864,52,"BRB","Barbados","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71865,52,"BRB","Barbados","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71866,52,"BRB","Barbados","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71867,52,"BRB","Barbados","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71868,52,"BRB","Barbados","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71869,52,"BRB","Barbados","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71870,52,"BRB","Barbados","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71871,52,"BRB","Barbados","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71872,52,"BRB","Barbados","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71873,52,"BRB","Barbados","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71874,52,"BRB","Barbados","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71875,52,"BRB","Barbados","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71876,52,"BRB","Barbados","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71877,52,"BRB","Barbados","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71878,52,"BRB","Barbados","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71879,52,"BRB","Barbados","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71880,52,"BRB","Barbados","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71881,52,"BRB","Barbados","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRB/brb_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71882,56,"BEL","Belgium","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71883,56,"BEL","Belgium","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71884,56,"BEL","Belgium","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71885,56,"BEL","Belgium","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71886,56,"BEL","Belgium","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71887,56,"BEL","Belgium","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71888,56,"BEL","Belgium","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71889,56,"BEL","Belgium","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71890,56,"BEL","Belgium","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71891,56,"BEL","Belgium","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71892,56,"BEL","Belgium","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71893,56,"BEL","Belgium","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71894,56,"BEL","Belgium","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71895,56,"BEL","Belgium","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71896,56,"BEL","Belgium","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71897,56,"BEL","Belgium","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71898,56,"BEL","Belgium","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71899,56,"BEL","Belgium","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71900,56,"BEL","Belgium","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71901,56,"BEL","Belgium","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71902,56,"BEL","Belgium","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71903,56,"BEL","Belgium","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71904,56,"BEL","Belgium","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71905,56,"BEL","Belgium","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71906,56,"BEL","Belgium","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71907,56,"BEL","Belgium","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71908,56,"BEL","Belgium","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71909,56,"BEL","Belgium","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71910,56,"BEL","Belgium","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71911,56,"BEL","Belgium","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71912,56,"BEL","Belgium","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71913,56,"BEL","Belgium","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71914,56,"BEL","Belgium","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71915,56,"BEL","Belgium","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71916,56,"BEL","Belgium","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71917,56,"BEL","Belgium","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEL/bel_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71918,60,"BMU","Bermuda","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71919,60,"BMU","Bermuda","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71920,60,"BMU","Bermuda","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71921,60,"BMU","Bermuda","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71922,60,"BMU","Bermuda","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71923,60,"BMU","Bermuda","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71924,60,"BMU","Bermuda","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71925,60,"BMU","Bermuda","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71926,60,"BMU","Bermuda","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71927,60,"BMU","Bermuda","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71928,60,"BMU","Bermuda","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71929,60,"BMU","Bermuda","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71930,60,"BMU","Bermuda","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71931,60,"BMU","Bermuda","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71932,60,"BMU","Bermuda","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71933,60,"BMU","Bermuda","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71934,60,"BMU","Bermuda","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71935,60,"BMU","Bermuda","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71936,60,"BMU","Bermuda","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71937,60,"BMU","Bermuda","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71938,60,"BMU","Bermuda","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71939,60,"BMU","Bermuda","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71940,60,"BMU","Bermuda","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71941,60,"BMU","Bermuda","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71942,60,"BMU","Bermuda","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71943,60,"BMU","Bermuda","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71944,60,"BMU","Bermuda","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71945,60,"BMU","Bermuda","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71946,60,"BMU","Bermuda","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71947,60,"BMU","Bermuda","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71948,60,"BMU","Bermuda","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71949,60,"BMU","Bermuda","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71950,60,"BMU","Bermuda","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71951,60,"BMU","Bermuda","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71952,60,"BMU","Bermuda","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71953,60,"BMU","Bermuda","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BMU/bmu_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71954,64,"BTN","Bhutan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71955,64,"BTN","Bhutan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71956,64,"BTN","Bhutan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71957,64,"BTN","Bhutan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71958,64,"BTN","Bhutan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71959,64,"BTN","Bhutan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71960,64,"BTN","Bhutan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71961,64,"BTN","Bhutan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71962,64,"BTN","Bhutan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71963,64,"BTN","Bhutan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
71964,64,"BTN","Bhutan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
71965,64,"BTN","Bhutan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
71966,64,"BTN","Bhutan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
71967,64,"BTN","Bhutan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
71968,64,"BTN","Bhutan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
71969,64,"BTN","Bhutan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
71970,64,"BTN","Bhutan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
71971,64,"BTN","Bhutan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
71972,64,"BTN","Bhutan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
71973,64,"BTN","Bhutan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
71974,64,"BTN","Bhutan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
71975,64,"BTN","Bhutan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
71976,64,"BTN","Bhutan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
71977,64,"BTN","Bhutan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
71978,64,"BTN","Bhutan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
71979,64,"BTN","Bhutan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
71980,64,"BTN","Bhutan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
71981,64,"BTN","Bhutan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
71982,64,"BTN","Bhutan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
71983,64,"BTN","Bhutan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
71984,64,"BTN","Bhutan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
71985,64,"BTN","Bhutan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
71986,64,"BTN","Bhutan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
71987,64,"BTN","Bhutan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
71988,64,"BTN","Bhutan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
71989,64,"BTN","Bhutan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BTN/btn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
71990,68,"BOL","Bolivia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
71991,68,"BOL","Bolivia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
71992,68,"BOL","Bolivia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
71993,68,"BOL","Bolivia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
71994,68,"BOL","Bolivia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
71995,68,"BOL","Bolivia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
71996,68,"BOL","Bolivia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
71997,68,"BOL","Bolivia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
71998,68,"BOL","Bolivia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
71999,68,"BOL","Bolivia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72000,68,"BOL","Bolivia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72001,68,"BOL","Bolivia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72002,68,"BOL","Bolivia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72003,68,"BOL","Bolivia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72004,68,"BOL","Bolivia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72005,68,"BOL","Bolivia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72006,68,"BOL","Bolivia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72007,68,"BOL","Bolivia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72008,68,"BOL","Bolivia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72009,68,"BOL","Bolivia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72010,68,"BOL","Bolivia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72011,68,"BOL","Bolivia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72012,68,"BOL","Bolivia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72013,68,"BOL","Bolivia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72014,68,"BOL","Bolivia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72015,68,"BOL","Bolivia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72016,68,"BOL","Bolivia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72017,68,"BOL","Bolivia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72018,68,"BOL","Bolivia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72019,68,"BOL","Bolivia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72020,68,"BOL","Bolivia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72021,68,"BOL","Bolivia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72022,68,"BOL","Bolivia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72023,68,"BOL","Bolivia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72024,68,"BOL","Bolivia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72025,68,"BOL","Bolivia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BOL/bol_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72026,70,"BIH","Bosnia and Herzegovina","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72027,70,"BIH","Bosnia and Herzegovina","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72028,70,"BIH","Bosnia and Herzegovina","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72029,70,"BIH","Bosnia and Herzegovina","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72030,70,"BIH","Bosnia and Herzegovina","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72031,70,"BIH","Bosnia and Herzegovina","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72032,70,"BIH","Bosnia and Herzegovina","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72033,70,"BIH","Bosnia and Herzegovina","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72034,70,"BIH","Bosnia and Herzegovina","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72035,70,"BIH","Bosnia and Herzegovina","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72036,70,"BIH","Bosnia and Herzegovina","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72037,70,"BIH","Bosnia and Herzegovina","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72038,70,"BIH","Bosnia and Herzegovina","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72039,70,"BIH","Bosnia and Herzegovina","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72040,70,"BIH","Bosnia and Herzegovina","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72041,70,"BIH","Bosnia and Herzegovina","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72042,70,"BIH","Bosnia and Herzegovina","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72043,70,"BIH","Bosnia and Herzegovina","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72044,70,"BIH","Bosnia and Herzegovina","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72045,70,"BIH","Bosnia and Herzegovina","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72046,70,"BIH","Bosnia and Herzegovina","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72047,70,"BIH","Bosnia and Herzegovina","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72048,70,"BIH","Bosnia and Herzegovina","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72049,70,"BIH","Bosnia and Herzegovina","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72050,70,"BIH","Bosnia and Herzegovina","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72051,70,"BIH","Bosnia and Herzegovina","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72052,70,"BIH","Bosnia and Herzegovina","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72053,70,"BIH","Bosnia and Herzegovina","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72054,70,"BIH","Bosnia and Herzegovina","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72055,70,"BIH","Bosnia and Herzegovina","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72056,70,"BIH","Bosnia and Herzegovina","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72057,70,"BIH","Bosnia and Herzegovina","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72058,70,"BIH","Bosnia and Herzegovina","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72059,70,"BIH","Bosnia and Herzegovina","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72060,70,"BIH","Bosnia and Herzegovina","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72061,70,"BIH","Bosnia and Herzegovina","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BIH/bih_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72062,72,"BWA","Botswana","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72063,72,"BWA","Botswana","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72064,72,"BWA","Botswana","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72065,72,"BWA","Botswana","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72066,72,"BWA","Botswana","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72067,72,"BWA","Botswana","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72068,72,"BWA","Botswana","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72069,72,"BWA","Botswana","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72070,72,"BWA","Botswana","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72071,72,"BWA","Botswana","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72072,72,"BWA","Botswana","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72073,72,"BWA","Botswana","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72074,72,"BWA","Botswana","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72075,72,"BWA","Botswana","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72076,72,"BWA","Botswana","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72077,72,"BWA","Botswana","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72078,72,"BWA","Botswana","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72079,72,"BWA","Botswana","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72080,72,"BWA","Botswana","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72081,72,"BWA","Botswana","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72082,72,"BWA","Botswana","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72083,72,"BWA","Botswana","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72084,72,"BWA","Botswana","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72085,72,"BWA","Botswana","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72086,72,"BWA","Botswana","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72087,72,"BWA","Botswana","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72088,72,"BWA","Botswana","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72089,72,"BWA","Botswana","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72090,72,"BWA","Botswana","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72091,72,"BWA","Botswana","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72092,72,"BWA","Botswana","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72093,72,"BWA","Botswana","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72094,72,"BWA","Botswana","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72095,72,"BWA","Botswana","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72096,72,"BWA","Botswana","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72097,72,"BWA","Botswana","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BWA/bwa_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72098,74,"BVT","Bouvet Island","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72099,74,"BVT","Bouvet Island","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72100,74,"BVT","Bouvet Island","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72101,74,"BVT","Bouvet Island","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72102,74,"BVT","Bouvet Island","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72103,74,"BVT","Bouvet Island","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72104,74,"BVT","Bouvet Island","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72105,74,"BVT","Bouvet Island","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72106,74,"BVT","Bouvet Island","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72107,74,"BVT","Bouvet Island","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72108,74,"BVT","Bouvet Island","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72109,74,"BVT","Bouvet Island","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72110,74,"BVT","Bouvet Island","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72111,74,"BVT","Bouvet Island","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72112,74,"BVT","Bouvet Island","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72113,74,"BVT","Bouvet Island","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72114,74,"BVT","Bouvet Island","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72115,74,"BVT","Bouvet Island","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72116,74,"BVT","Bouvet Island","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72117,74,"BVT","Bouvet Island","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72118,74,"BVT","Bouvet Island","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72119,74,"BVT","Bouvet Island","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72120,74,"BVT","Bouvet Island","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72121,74,"BVT","Bouvet Island","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72122,74,"BVT","Bouvet Island","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72123,74,"BVT","Bouvet Island","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72124,74,"BVT","Bouvet Island","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72125,74,"BVT","Bouvet Island","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72126,74,"BVT","Bouvet Island","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72127,74,"BVT","Bouvet Island","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72128,74,"BVT","Bouvet Island","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72129,74,"BVT","Bouvet Island","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72130,74,"BVT","Bouvet Island","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72131,74,"BVT","Bouvet Island","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72132,74,"BVT","Bouvet Island","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72133,74,"BVT","Bouvet Island","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BVT/bvt_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72134,84,"BLZ","Belize","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72135,84,"BLZ","Belize","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72136,84,"BLZ","Belize","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72137,84,"BLZ","Belize","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72138,84,"BLZ","Belize","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72139,84,"BLZ","Belize","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72140,84,"BLZ","Belize","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72141,84,"BLZ","Belize","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72142,84,"BLZ","Belize","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72143,84,"BLZ","Belize","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72144,84,"BLZ","Belize","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72145,84,"BLZ","Belize","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72146,84,"BLZ","Belize","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72147,84,"BLZ","Belize","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72148,84,"BLZ","Belize","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72149,84,"BLZ","Belize","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72150,84,"BLZ","Belize","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72151,84,"BLZ","Belize","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72152,84,"BLZ","Belize","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72153,84,"BLZ","Belize","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72154,84,"BLZ","Belize","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72155,84,"BLZ","Belize","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72156,84,"BLZ","Belize","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72157,84,"BLZ","Belize","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72158,84,"BLZ","Belize","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72159,84,"BLZ","Belize","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72160,84,"BLZ","Belize","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72161,84,"BLZ","Belize","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72162,84,"BLZ","Belize","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72163,84,"BLZ","Belize","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72164,84,"BLZ","Belize","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72165,84,"BLZ","Belize","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72166,84,"BLZ","Belize","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72167,84,"BLZ","Belize","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72168,84,"BLZ","Belize","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72169,84,"BLZ","Belize","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLZ/blz_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72170,86,"IOT","British Indian Ocean Territory","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72171,86,"IOT","British Indian Ocean Territory","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72172,86,"IOT","British Indian Ocean Territory","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72173,86,"IOT","British Indian Ocean Territory","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72174,86,"IOT","British Indian Ocean Territory","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72175,86,"IOT","British Indian Ocean Territory","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72176,86,"IOT","British Indian Ocean Territory","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72177,86,"IOT","British Indian Ocean Territory","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72178,86,"IOT","British Indian Ocean Territory","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72179,86,"IOT","British Indian Ocean Territory","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72180,86,"IOT","British Indian Ocean Territory","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72181,86,"IOT","British Indian Ocean Territory","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72182,86,"IOT","British Indian Ocean Territory","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72183,86,"IOT","British Indian Ocean Territory","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72184,86,"IOT","British Indian Ocean Territory","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72185,86,"IOT","British Indian Ocean Territory","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72186,86,"IOT","British Indian Ocean Territory","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72187,86,"IOT","British Indian Ocean Territory","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72188,86,"IOT","British Indian Ocean Territory","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72189,86,"IOT","British Indian Ocean Territory","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72190,86,"IOT","British Indian Ocean Territory","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72191,86,"IOT","British Indian Ocean Territory","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72192,86,"IOT","British Indian Ocean Territory","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72193,86,"IOT","British Indian Ocean Territory","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72194,86,"IOT","British Indian Ocean Territory","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72195,86,"IOT","British Indian Ocean Territory","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72196,86,"IOT","British Indian Ocean Territory","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72197,86,"IOT","British Indian Ocean Territory","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72198,86,"IOT","British Indian Ocean Territory","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72199,86,"IOT","British Indian Ocean Territory","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72200,86,"IOT","British Indian Ocean Territory","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72201,86,"IOT","British Indian Ocean Territory","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72202,86,"IOT","British Indian Ocean Territory","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72203,86,"IOT","British Indian Ocean Territory","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72204,86,"IOT","British Indian Ocean Territory","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72205,86,"IOT","British Indian Ocean Territory","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IOT/iot_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72206,90,"SLB","Solomon Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72207,90,"SLB","Solomon Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72208,90,"SLB","Solomon Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72209,90,"SLB","Solomon Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72210,90,"SLB","Solomon Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72211,90,"SLB","Solomon Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72212,90,"SLB","Solomon Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72213,90,"SLB","Solomon Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72214,90,"SLB","Solomon Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72215,90,"SLB","Solomon Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72216,90,"SLB","Solomon Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72217,90,"SLB","Solomon Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72218,90,"SLB","Solomon Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72219,90,"SLB","Solomon Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72220,90,"SLB","Solomon Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72221,90,"SLB","Solomon Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72222,90,"SLB","Solomon Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72223,90,"SLB","Solomon Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72224,90,"SLB","Solomon Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72225,90,"SLB","Solomon Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72226,90,"SLB","Solomon Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72227,90,"SLB","Solomon Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72228,90,"SLB","Solomon Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72229,90,"SLB","Solomon Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72230,90,"SLB","Solomon Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72231,90,"SLB","Solomon Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72232,90,"SLB","Solomon Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72233,90,"SLB","Solomon Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72234,90,"SLB","Solomon Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72235,90,"SLB","Solomon Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72236,90,"SLB","Solomon Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72237,90,"SLB","Solomon Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72238,90,"SLB","Solomon Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72239,90,"SLB","Solomon Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72240,90,"SLB","Solomon Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72241,90,"SLB","Solomon Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLB/slb_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72242,92,"VGB","British Virgin Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72243,92,"VGB","British Virgin Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72244,92,"VGB","British Virgin Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72245,92,"VGB","British Virgin Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72246,92,"VGB","British Virgin Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72247,92,"VGB","British Virgin Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72248,92,"VGB","British Virgin Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72249,92,"VGB","British Virgin Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72250,92,"VGB","British Virgin Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72251,92,"VGB","British Virgin Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72252,92,"VGB","British Virgin Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72253,92,"VGB","British Virgin Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72254,92,"VGB","British Virgin Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72255,92,"VGB","British Virgin Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72256,92,"VGB","British Virgin Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72257,92,"VGB","British Virgin Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72258,92,"VGB","British Virgin Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72259,92,"VGB","British Virgin Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72260,92,"VGB","British Virgin Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72261,92,"VGB","British Virgin Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72262,92,"VGB","British Virgin Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72263,92,"VGB","British Virgin Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72264,92,"VGB","British Virgin Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72265,92,"VGB","British Virgin Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72266,92,"VGB","British Virgin Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72267,92,"VGB","British Virgin Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72268,92,"VGB","British Virgin Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72269,92,"VGB","British Virgin Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72270,92,"VGB","British Virgin Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72271,92,"VGB","British Virgin Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72272,92,"VGB","British Virgin Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72273,92,"VGB","British Virgin Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72274,92,"VGB","British Virgin Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72275,92,"VGB","British Virgin Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72276,92,"VGB","British Virgin Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72277,92,"VGB","British Virgin Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VGB/vgb_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72278,96,"BRN","Brunei","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72279,96,"BRN","Brunei","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72280,96,"BRN","Brunei","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72281,96,"BRN","Brunei","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72282,96,"BRN","Brunei","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72283,96,"BRN","Brunei","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72284,96,"BRN","Brunei","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72285,96,"BRN","Brunei","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72286,96,"BRN","Brunei","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72287,96,"BRN","Brunei","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72288,96,"BRN","Brunei","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72289,96,"BRN","Brunei","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72290,96,"BRN","Brunei","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72291,96,"BRN","Brunei","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72292,96,"BRN","Brunei","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72293,96,"BRN","Brunei","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72294,96,"BRN","Brunei","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72295,96,"BRN","Brunei","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72296,96,"BRN","Brunei","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72297,96,"BRN","Brunei","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72298,96,"BRN","Brunei","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72299,96,"BRN","Brunei","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72300,96,"BRN","Brunei","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72301,96,"BRN","Brunei","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72302,96,"BRN","Brunei","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72303,96,"BRN","Brunei","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72304,96,"BRN","Brunei","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72305,96,"BRN","Brunei","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72306,96,"BRN","Brunei","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72307,96,"BRN","Brunei","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72308,96,"BRN","Brunei","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72309,96,"BRN","Brunei","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72310,96,"BRN","Brunei","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72311,96,"BRN","Brunei","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72312,96,"BRN","Brunei","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72313,96,"BRN","Brunei","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BRN/brn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72314,100,"BGR","Bulgaria","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72315,100,"BGR","Bulgaria","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72316,100,"BGR","Bulgaria","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72317,100,"BGR","Bulgaria","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72318,100,"BGR","Bulgaria","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72319,100,"BGR","Bulgaria","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72320,100,"BGR","Bulgaria","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72321,100,"BGR","Bulgaria","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72322,100,"BGR","Bulgaria","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72323,100,"BGR","Bulgaria","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72324,100,"BGR","Bulgaria","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72325,100,"BGR","Bulgaria","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72326,100,"BGR","Bulgaria","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72327,100,"BGR","Bulgaria","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72328,100,"BGR","Bulgaria","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72329,100,"BGR","Bulgaria","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72330,100,"BGR","Bulgaria","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72331,100,"BGR","Bulgaria","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72332,100,"BGR","Bulgaria","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72333,100,"BGR","Bulgaria","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72334,100,"BGR","Bulgaria","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72335,100,"BGR","Bulgaria","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72336,100,"BGR","Bulgaria","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72337,100,"BGR","Bulgaria","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72338,100,"BGR","Bulgaria","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72339,100,"BGR","Bulgaria","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72340,100,"BGR","Bulgaria","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72341,100,"BGR","Bulgaria","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72342,100,"BGR","Bulgaria","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72343,100,"BGR","Bulgaria","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72344,100,"BGR","Bulgaria","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72345,100,"BGR","Bulgaria","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72346,100,"BGR","Bulgaria","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72347,100,"BGR","Bulgaria","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72348,100,"BGR","Bulgaria","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72349,100,"BGR","Bulgaria","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BGR/bgr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72350,104,"MMR","Myanmar","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72351,104,"MMR","Myanmar","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72352,104,"MMR","Myanmar","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72353,104,"MMR","Myanmar","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72354,104,"MMR","Myanmar","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72355,104,"MMR","Myanmar","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72356,104,"MMR","Myanmar","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72357,104,"MMR","Myanmar","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72358,104,"MMR","Myanmar","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72359,104,"MMR","Myanmar","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72360,104,"MMR","Myanmar","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72361,104,"MMR","Myanmar","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72362,104,"MMR","Myanmar","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72363,104,"MMR","Myanmar","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72364,104,"MMR","Myanmar","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72365,104,"MMR","Myanmar","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72366,104,"MMR","Myanmar","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72367,104,"MMR","Myanmar","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72368,104,"MMR","Myanmar","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72369,104,"MMR","Myanmar","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72370,104,"MMR","Myanmar","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72371,104,"MMR","Myanmar","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72372,104,"MMR","Myanmar","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72373,104,"MMR","Myanmar","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72374,104,"MMR","Myanmar","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72375,104,"MMR","Myanmar","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72376,104,"MMR","Myanmar","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72377,104,"MMR","Myanmar","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72378,104,"MMR","Myanmar","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72379,104,"MMR","Myanmar","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72380,104,"MMR","Myanmar","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72381,104,"MMR","Myanmar","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72382,104,"MMR","Myanmar","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72383,104,"MMR","Myanmar","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72384,104,"MMR","Myanmar","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72385,104,"MMR","Myanmar","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MMR/mmr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72386,108,"BDI","Burundi","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72387,108,"BDI","Burundi","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72388,108,"BDI","Burundi","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72389,108,"BDI","Burundi","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72390,108,"BDI","Burundi","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72391,108,"BDI","Burundi","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72392,108,"BDI","Burundi","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72393,108,"BDI","Burundi","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72394,108,"BDI","Burundi","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72395,108,"BDI","Burundi","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72396,108,"BDI","Burundi","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72397,108,"BDI","Burundi","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72398,108,"BDI","Burundi","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72399,108,"BDI","Burundi","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72400,108,"BDI","Burundi","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72401,108,"BDI","Burundi","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72402,108,"BDI","Burundi","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72403,108,"BDI","Burundi","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72404,108,"BDI","Burundi","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72405,108,"BDI","Burundi","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72406,108,"BDI","Burundi","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72407,108,"BDI","Burundi","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72408,108,"BDI","Burundi","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72409,108,"BDI","Burundi","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72410,108,"BDI","Burundi","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72411,108,"BDI","Burundi","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72412,108,"BDI","Burundi","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72413,108,"BDI","Burundi","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72414,108,"BDI","Burundi","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72415,108,"BDI","Burundi","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72416,108,"BDI","Burundi","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72417,108,"BDI","Burundi","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72418,108,"BDI","Burundi","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72419,108,"BDI","Burundi","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72420,108,"BDI","Burundi","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72421,108,"BDI","Burundi","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BDI/bdi_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72422,112,"BLR","Belarus","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72423,112,"BLR","Belarus","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72424,112,"BLR","Belarus","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72425,112,"BLR","Belarus","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72426,112,"BLR","Belarus","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72427,112,"BLR","Belarus","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72428,112,"BLR","Belarus","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72429,112,"BLR","Belarus","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72430,112,"BLR","Belarus","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72431,112,"BLR","Belarus","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72432,112,"BLR","Belarus","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72433,112,"BLR","Belarus","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72434,112,"BLR","Belarus","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72435,112,"BLR","Belarus","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72436,112,"BLR","Belarus","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72437,112,"BLR","Belarus","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72438,112,"BLR","Belarus","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72439,112,"BLR","Belarus","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72440,112,"BLR","Belarus","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72441,112,"BLR","Belarus","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72442,112,"BLR","Belarus","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72443,112,"BLR","Belarus","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72444,112,"BLR","Belarus","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72445,112,"BLR","Belarus","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72446,112,"BLR","Belarus","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72447,112,"BLR","Belarus","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72448,112,"BLR","Belarus","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72449,112,"BLR","Belarus","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72450,112,"BLR","Belarus","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72451,112,"BLR","Belarus","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72452,112,"BLR","Belarus","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72453,112,"BLR","Belarus","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72454,112,"BLR","Belarus","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72455,112,"BLR","Belarus","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72456,112,"BLR","Belarus","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72457,112,"BLR","Belarus","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLR/blr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72458,116,"KHM","Cambodia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72459,116,"KHM","Cambodia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72460,116,"KHM","Cambodia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72461,116,"KHM","Cambodia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72462,116,"KHM","Cambodia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72463,116,"KHM","Cambodia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72464,116,"KHM","Cambodia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72465,116,"KHM","Cambodia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72466,116,"KHM","Cambodia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72467,116,"KHM","Cambodia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72468,116,"KHM","Cambodia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72469,116,"KHM","Cambodia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72470,116,"KHM","Cambodia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72471,116,"KHM","Cambodia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72472,116,"KHM","Cambodia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72473,116,"KHM","Cambodia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72474,116,"KHM","Cambodia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72475,116,"KHM","Cambodia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72476,116,"KHM","Cambodia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72477,116,"KHM","Cambodia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72478,116,"KHM","Cambodia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72479,116,"KHM","Cambodia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72480,116,"KHM","Cambodia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72481,116,"KHM","Cambodia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72482,116,"KHM","Cambodia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72483,116,"KHM","Cambodia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72484,116,"KHM","Cambodia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72485,116,"KHM","Cambodia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72486,116,"KHM","Cambodia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72487,116,"KHM","Cambodia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72488,116,"KHM","Cambodia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72489,116,"KHM","Cambodia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72490,116,"KHM","Cambodia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72491,116,"KHM","Cambodia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72492,116,"KHM","Cambodia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72493,116,"KHM","Cambodia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KHM/khm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72494,120,"CMR","Cameroon","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72495,120,"CMR","Cameroon","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72496,120,"CMR","Cameroon","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72497,120,"CMR","Cameroon","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72498,120,"CMR","Cameroon","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72499,120,"CMR","Cameroon","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72500,120,"CMR","Cameroon","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72501,120,"CMR","Cameroon","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72502,120,"CMR","Cameroon","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72503,120,"CMR","Cameroon","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72504,120,"CMR","Cameroon","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72505,120,"CMR","Cameroon","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72506,120,"CMR","Cameroon","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72507,120,"CMR","Cameroon","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72508,120,"CMR","Cameroon","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72509,120,"CMR","Cameroon","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72510,120,"CMR","Cameroon","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72511,120,"CMR","Cameroon","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72512,120,"CMR","Cameroon","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72513,120,"CMR","Cameroon","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72514,120,"CMR","Cameroon","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72515,120,"CMR","Cameroon","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72516,120,"CMR","Cameroon","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72517,120,"CMR","Cameroon","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72518,120,"CMR","Cameroon","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72519,120,"CMR","Cameroon","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72520,120,"CMR","Cameroon","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72521,120,"CMR","Cameroon","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72522,120,"CMR","Cameroon","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72523,120,"CMR","Cameroon","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72524,120,"CMR","Cameroon","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72525,120,"CMR","Cameroon","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72526,120,"CMR","Cameroon","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72527,120,"CMR","Cameroon","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72528,120,"CMR","Cameroon","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72529,120,"CMR","Cameroon","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CMR/cmr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72530,132,"CPV","Cape Verde","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72531,132,"CPV","Cape Verde","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72532,132,"CPV","Cape Verde","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72533,132,"CPV","Cape Verde","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72534,132,"CPV","Cape Verde","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72535,132,"CPV","Cape Verde","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72536,132,"CPV","Cape Verde","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72537,132,"CPV","Cape Verde","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72538,132,"CPV","Cape Verde","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72539,132,"CPV","Cape Verde","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72540,132,"CPV","Cape Verde","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72541,132,"CPV","Cape Verde","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72542,132,"CPV","Cape Verde","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72543,132,"CPV","Cape Verde","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72544,132,"CPV","Cape Verde","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72545,132,"CPV","Cape Verde","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72546,132,"CPV","Cape Verde","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72547,132,"CPV","Cape Verde","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72548,132,"CPV","Cape Verde","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72549,132,"CPV","Cape Verde","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72550,132,"CPV","Cape Verde","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72551,132,"CPV","Cape Verde","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72552,132,"CPV","Cape Verde","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72553,132,"CPV","Cape Verde","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72554,132,"CPV","Cape Verde","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72555,132,"CPV","Cape Verde","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72556,132,"CPV","Cape Verde","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72557,132,"CPV","Cape Verde","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72558,132,"CPV","Cape Verde","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72559,132,"CPV","Cape Verde","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72560,132,"CPV","Cape Verde","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72561,132,"CPV","Cape Verde","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72562,132,"CPV","Cape Verde","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72563,132,"CPV","Cape Verde","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72564,132,"CPV","Cape Verde","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72565,132,"CPV","Cape Verde","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CPV/cpv_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72566,136,"CYM","Cayman Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72567,136,"CYM","Cayman Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72568,136,"CYM","Cayman Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72569,136,"CYM","Cayman Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72570,136,"CYM","Cayman Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72571,136,"CYM","Cayman Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72572,136,"CYM","Cayman Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72573,136,"CYM","Cayman Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72574,136,"CYM","Cayman Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72575,136,"CYM","Cayman Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72576,136,"CYM","Cayman Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72577,136,"CYM","Cayman Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72578,136,"CYM","Cayman Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72579,136,"CYM","Cayman Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72580,136,"CYM","Cayman Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72581,136,"CYM","Cayman Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72582,136,"CYM","Cayman Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72583,136,"CYM","Cayman Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72584,136,"CYM","Cayman Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72585,136,"CYM","Cayman Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72586,136,"CYM","Cayman Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72587,136,"CYM","Cayman Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72588,136,"CYM","Cayman Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72589,136,"CYM","Cayman Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72590,136,"CYM","Cayman Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72591,136,"CYM","Cayman Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72592,136,"CYM","Cayman Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72593,136,"CYM","Cayman Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72594,136,"CYM","Cayman Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72595,136,"CYM","Cayman Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72596,136,"CYM","Cayman Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72597,136,"CYM","Cayman Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72598,136,"CYM","Cayman Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72599,136,"CYM","Cayman Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72600,136,"CYM","Cayman Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72601,136,"CYM","Cayman Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYM/cym_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72602,140,"CAF","Central African Republic","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72603,140,"CAF","Central African Republic","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72604,140,"CAF","Central African Republic","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72605,140,"CAF","Central African Republic","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72606,140,"CAF","Central African Republic","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72607,140,"CAF","Central African Republic","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72608,140,"CAF","Central African Republic","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72609,140,"CAF","Central African Republic","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72610,140,"CAF","Central African Republic","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72611,140,"CAF","Central African Republic","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72612,140,"CAF","Central African Republic","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72613,140,"CAF","Central African Republic","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72614,140,"CAF","Central African Republic","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72615,140,"CAF","Central African Republic","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72616,140,"CAF","Central African Republic","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72617,140,"CAF","Central African Republic","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72618,140,"CAF","Central African Republic","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72619,140,"CAF","Central African Republic","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72620,140,"CAF","Central African Republic","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72621,140,"CAF","Central African Republic","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72622,140,"CAF","Central African Republic","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72623,140,"CAF","Central African Republic","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72624,140,"CAF","Central African Republic","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72625,140,"CAF","Central African Republic","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72626,140,"CAF","Central African Republic","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72627,140,"CAF","Central African Republic","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72628,140,"CAF","Central African Republic","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72629,140,"CAF","Central African Republic","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72630,140,"CAF","Central African Republic","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72631,140,"CAF","Central African Republic","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72632,140,"CAF","Central African Republic","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72633,140,"CAF","Central African Republic","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72634,140,"CAF","Central African Republic","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72635,140,"CAF","Central African Republic","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72636,140,"CAF","Central African Republic","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72637,140,"CAF","Central African Republic","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CAF/caf_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72638,144,"LKA","Sri Lanka","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72639,144,"LKA","Sri Lanka","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72640,144,"LKA","Sri Lanka","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72641,144,"LKA","Sri Lanka","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72642,144,"LKA","Sri Lanka","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72643,144,"LKA","Sri Lanka","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72644,144,"LKA","Sri Lanka","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72645,144,"LKA","Sri Lanka","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72646,144,"LKA","Sri Lanka","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72647,144,"LKA","Sri Lanka","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72648,144,"LKA","Sri Lanka","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72649,144,"LKA","Sri Lanka","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72650,144,"LKA","Sri Lanka","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72651,144,"LKA","Sri Lanka","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72652,144,"LKA","Sri Lanka","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72653,144,"LKA","Sri Lanka","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72654,144,"LKA","Sri Lanka","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72655,144,"LKA","Sri Lanka","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72656,144,"LKA","Sri Lanka","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72657,144,"LKA","Sri Lanka","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72658,144,"LKA","Sri Lanka","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72659,144,"LKA","Sri Lanka","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72660,144,"LKA","Sri Lanka","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72661,144,"LKA","Sri Lanka","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72662,144,"LKA","Sri Lanka","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72663,144,"LKA","Sri Lanka","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72664,144,"LKA","Sri Lanka","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72665,144,"LKA","Sri Lanka","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72666,144,"LKA","Sri Lanka","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72667,144,"LKA","Sri Lanka","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72668,144,"LKA","Sri Lanka","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72669,144,"LKA","Sri Lanka","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72670,144,"LKA","Sri Lanka","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72671,144,"LKA","Sri Lanka","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72672,144,"LKA","Sri Lanka","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72673,144,"LKA","Sri Lanka","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LKA/lka_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72674,148,"TCD","Chad","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72675,148,"TCD","Chad","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72676,148,"TCD","Chad","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72677,148,"TCD","Chad","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72678,148,"TCD","Chad","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72679,148,"TCD","Chad","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72680,148,"TCD","Chad","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72681,148,"TCD","Chad","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72682,148,"TCD","Chad","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72683,148,"TCD","Chad","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72684,148,"TCD","Chad","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72685,148,"TCD","Chad","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72686,148,"TCD","Chad","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72687,148,"TCD","Chad","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72688,148,"TCD","Chad","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72689,148,"TCD","Chad","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72690,148,"TCD","Chad","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72691,148,"TCD","Chad","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72692,148,"TCD","Chad","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72693,148,"TCD","Chad","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72694,148,"TCD","Chad","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72695,148,"TCD","Chad","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72696,148,"TCD","Chad","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72697,148,"TCD","Chad","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72698,148,"TCD","Chad","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72699,148,"TCD","Chad","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72700,148,"TCD","Chad","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72701,148,"TCD","Chad","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72702,148,"TCD","Chad","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72703,148,"TCD","Chad","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72704,148,"TCD","Chad","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72705,148,"TCD","Chad","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72706,148,"TCD","Chad","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72707,148,"TCD","Chad","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72708,148,"TCD","Chad","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72709,148,"TCD","Chad","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCD/tcd_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72710,158,"TWN","Taiwan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72711,158,"TWN","Taiwan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72712,158,"TWN","Taiwan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72713,158,"TWN","Taiwan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72714,158,"TWN","Taiwan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72715,158,"TWN","Taiwan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72716,158,"TWN","Taiwan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72717,158,"TWN","Taiwan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72718,158,"TWN","Taiwan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72719,158,"TWN","Taiwan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72720,158,"TWN","Taiwan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72721,158,"TWN","Taiwan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72722,158,"TWN","Taiwan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72723,158,"TWN","Taiwan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72724,158,"TWN","Taiwan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72725,158,"TWN","Taiwan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72726,158,"TWN","Taiwan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72727,158,"TWN","Taiwan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72728,158,"TWN","Taiwan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72729,158,"TWN","Taiwan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72730,158,"TWN","Taiwan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72731,158,"TWN","Taiwan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72732,158,"TWN","Taiwan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72733,158,"TWN","Taiwan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72734,158,"TWN","Taiwan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72735,158,"TWN","Taiwan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72736,158,"TWN","Taiwan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72737,158,"TWN","Taiwan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72738,158,"TWN","Taiwan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72739,158,"TWN","Taiwan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72740,158,"TWN","Taiwan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72741,158,"TWN","Taiwan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72742,158,"TWN","Taiwan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72743,158,"TWN","Taiwan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72744,158,"TWN","Taiwan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72745,158,"TWN","Taiwan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TWN/twn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72746,170,"COL","Colombia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72747,170,"COL","Colombia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72748,170,"COL","Colombia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72749,170,"COL","Colombia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72750,170,"COL","Colombia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72751,170,"COL","Colombia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72752,170,"COL","Colombia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72753,170,"COL","Colombia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72754,170,"COL","Colombia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72755,170,"COL","Colombia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72756,170,"COL","Colombia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72757,170,"COL","Colombia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72758,170,"COL","Colombia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72759,170,"COL","Colombia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72760,170,"COL","Colombia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72761,170,"COL","Colombia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72762,170,"COL","Colombia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72763,170,"COL","Colombia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72764,170,"COL","Colombia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72765,170,"COL","Colombia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72766,170,"COL","Colombia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72767,170,"COL","Colombia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72768,170,"COL","Colombia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72769,170,"COL","Colombia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72770,170,"COL","Colombia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72771,170,"COL","Colombia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72772,170,"COL","Colombia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72773,170,"COL","Colombia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72774,170,"COL","Colombia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72775,170,"COL","Colombia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72776,170,"COL","Colombia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72777,170,"COL","Colombia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72778,170,"COL","Colombia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72779,170,"COL","Colombia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72780,170,"COL","Colombia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72781,170,"COL","Colombia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COL/col_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72782,174,"COM","Comoros","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72783,174,"COM","Comoros","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72784,174,"COM","Comoros","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72785,174,"COM","Comoros","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72786,174,"COM","Comoros","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72787,174,"COM","Comoros","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72788,174,"COM","Comoros","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72789,174,"COM","Comoros","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72790,174,"COM","Comoros","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72791,174,"COM","Comoros","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72792,174,"COM","Comoros","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72793,174,"COM","Comoros","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72794,174,"COM","Comoros","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72795,174,"COM","Comoros","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72796,174,"COM","Comoros","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72797,174,"COM","Comoros","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72798,174,"COM","Comoros","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72799,174,"COM","Comoros","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72800,174,"COM","Comoros","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72801,174,"COM","Comoros","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72802,174,"COM","Comoros","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72803,174,"COM","Comoros","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72804,174,"COM","Comoros","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72805,174,"COM","Comoros","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72806,174,"COM","Comoros","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72807,174,"COM","Comoros","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72808,174,"COM","Comoros","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72809,174,"COM","Comoros","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72810,174,"COM","Comoros","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72811,174,"COM","Comoros","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72812,174,"COM","Comoros","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72813,174,"COM","Comoros","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72814,174,"COM","Comoros","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72815,174,"COM","Comoros","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72816,174,"COM","Comoros","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72817,174,"COM","Comoros","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COM/com_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72818,175,"MYT","Mayotte","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72819,175,"MYT","Mayotte","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72820,175,"MYT","Mayotte","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72821,175,"MYT","Mayotte","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72822,175,"MYT","Mayotte","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72823,175,"MYT","Mayotte","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72824,175,"MYT","Mayotte","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72825,175,"MYT","Mayotte","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72826,175,"MYT","Mayotte","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72827,175,"MYT","Mayotte","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72828,175,"MYT","Mayotte","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72829,175,"MYT","Mayotte","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72830,175,"MYT","Mayotte","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72831,175,"MYT","Mayotte","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72832,175,"MYT","Mayotte","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72833,175,"MYT","Mayotte","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72834,175,"MYT","Mayotte","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72835,175,"MYT","Mayotte","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72836,175,"MYT","Mayotte","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72837,175,"MYT","Mayotte","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72838,175,"MYT","Mayotte","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72839,175,"MYT","Mayotte","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72840,175,"MYT","Mayotte","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72841,175,"MYT","Mayotte","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72842,175,"MYT","Mayotte","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72843,175,"MYT","Mayotte","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72844,175,"MYT","Mayotte","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72845,175,"MYT","Mayotte","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72846,175,"MYT","Mayotte","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72847,175,"MYT","Mayotte","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72848,175,"MYT","Mayotte","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72849,175,"MYT","Mayotte","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72850,175,"MYT","Mayotte","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72851,175,"MYT","Mayotte","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72852,175,"MYT","Mayotte","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72853,175,"MYT","Mayotte","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYT/myt_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72854,178,"COG","Republic of Congo","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72855,178,"COG","Republic of Congo","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72856,178,"COG","Republic of Congo","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72857,178,"COG","Republic of Congo","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72858,178,"COG","Republic of Congo","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72859,178,"COG","Republic of Congo","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72860,178,"COG","Republic of Congo","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72861,178,"COG","Republic of Congo","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72862,178,"COG","Republic of Congo","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72863,178,"COG","Republic of Congo","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72864,178,"COG","Republic of Congo","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72865,178,"COG","Republic of Congo","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72866,178,"COG","Republic of Congo","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72867,178,"COG","Republic of Congo","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72868,178,"COG","Republic of Congo","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72869,178,"COG","Republic of Congo","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72870,178,"COG","Republic of Congo","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72871,178,"COG","Republic of Congo","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72872,178,"COG","Republic of Congo","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72873,178,"COG","Republic of Congo","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72874,178,"COG","Republic of Congo","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72875,178,"COG","Republic of Congo","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72876,178,"COG","Republic of Congo","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72877,178,"COG","Republic of Congo","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72878,178,"COG","Republic of Congo","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72879,178,"COG","Republic of Congo","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72880,178,"COG","Republic of Congo","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72881,178,"COG","Republic of Congo","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72882,178,"COG","Republic of Congo","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72883,178,"COG","Republic of Congo","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72884,178,"COG","Republic of Congo","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72885,178,"COG","Republic of Congo","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72886,178,"COG","Republic of Congo","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72887,178,"COG","Republic of Congo","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72888,178,"COG","Republic of Congo","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72889,178,"COG","Republic of Congo","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COG/cog_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72890,180,"COD","Democratic Republic of the Congo","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72891,180,"COD","Democratic Republic of the Congo","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72892,180,"COD","Democratic Republic of the Congo","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72893,180,"COD","Democratic Republic of the Congo","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72894,180,"COD","Democratic Republic of the Congo","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72895,180,"COD","Democratic Republic of the Congo","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72896,180,"COD","Democratic Republic of the Congo","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72897,180,"COD","Democratic Republic of the Congo","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72898,180,"COD","Democratic Republic of the Congo","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72899,180,"COD","Democratic Republic of the Congo","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72900,180,"COD","Democratic Republic of the Congo","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72901,180,"COD","Democratic Republic of the Congo","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72902,180,"COD","Democratic Republic of the Congo","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72903,180,"COD","Democratic Republic of the Congo","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72904,180,"COD","Democratic Republic of the Congo","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72905,180,"COD","Democratic Republic of the Congo","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72906,180,"COD","Democratic Republic of the Congo","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72907,180,"COD","Democratic Republic of the Congo","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72908,180,"COD","Democratic Republic of the Congo","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72909,180,"COD","Democratic Republic of the Congo","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72910,180,"COD","Democratic Republic of the Congo","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72911,180,"COD","Democratic Republic of the Congo","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72912,180,"COD","Democratic Republic of the Congo","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72913,180,"COD","Democratic Republic of the Congo","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72914,180,"COD","Democratic Republic of the Congo","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72915,180,"COD","Democratic Republic of the Congo","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72916,180,"COD","Democratic Republic of the Congo","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72917,180,"COD","Democratic Republic of the Congo","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72918,180,"COD","Democratic Republic of the Congo","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72919,180,"COD","Democratic Republic of the Congo","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72920,180,"COD","Democratic Republic of the Congo","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72921,180,"COD","Democratic Republic of the Congo","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72922,180,"COD","Democratic Republic of the Congo","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72923,180,"COD","Democratic Republic of the Congo","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72924,180,"COD","Democratic Republic of the Congo","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72925,180,"COD","Democratic Republic of the Congo","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COD/cod_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72926,184,"COK","Cook Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72927,184,"COK","Cook Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72928,184,"COK","Cook Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72929,184,"COK","Cook Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72930,184,"COK","Cook Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72931,184,"COK","Cook Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72932,184,"COK","Cook Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72933,184,"COK","Cook Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72934,184,"COK","Cook Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72935,184,"COK","Cook Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72936,184,"COK","Cook Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72937,184,"COK","Cook Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72938,184,"COK","Cook Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72939,184,"COK","Cook Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72940,184,"COK","Cook Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72941,184,"COK","Cook Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72942,184,"COK","Cook Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72943,184,"COK","Cook Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72944,184,"COK","Cook Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72945,184,"COK","Cook Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72946,184,"COK","Cook Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72947,184,"COK","Cook Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72948,184,"COK","Cook Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72949,184,"COK","Cook Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72950,184,"COK","Cook Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72951,184,"COK","Cook Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72952,184,"COK","Cook Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72953,184,"COK","Cook Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72954,184,"COK","Cook Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72955,184,"COK","Cook Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72956,184,"COK","Cook Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72957,184,"COK","Cook Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72958,184,"COK","Cook Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72959,184,"COK","Cook Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72960,184,"COK","Cook Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72961,184,"COK","Cook Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/COK/cok_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72962,188,"CRI","Costa Rica","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72963,188,"CRI","Costa Rica","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
72964,188,"CRI","Costa Rica","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
72965,188,"CRI","Costa Rica","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
72966,188,"CRI","Costa Rica","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
72967,188,"CRI","Costa Rica","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
72968,188,"CRI","Costa Rica","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
72969,188,"CRI","Costa Rica","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
72970,188,"CRI","Costa Rica","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
72971,188,"CRI","Costa Rica","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
72972,188,"CRI","Costa Rica","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
72973,188,"CRI","Costa Rica","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
72974,188,"CRI","Costa Rica","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
72975,188,"CRI","Costa Rica","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
72976,188,"CRI","Costa Rica","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
72977,188,"CRI","Costa Rica","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
72978,188,"CRI","Costa Rica","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
72979,188,"CRI","Costa Rica","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
72980,188,"CRI","Costa Rica","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
72981,188,"CRI","Costa Rica","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
72982,188,"CRI","Costa Rica","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
72983,188,"CRI","Costa Rica","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
72984,188,"CRI","Costa Rica","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
72985,188,"CRI","Costa Rica","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
72986,188,"CRI","Costa Rica","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
72987,188,"CRI","Costa Rica","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
72988,188,"CRI","Costa Rica","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
72989,188,"CRI","Costa Rica","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
72990,188,"CRI","Costa Rica","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
72991,188,"CRI","Costa Rica","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
72992,188,"CRI","Costa Rica","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
72993,188,"CRI","Costa Rica","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
72994,188,"CRI","Costa Rica","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
72995,188,"CRI","Costa Rica","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
72996,188,"CRI","Costa Rica","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
72997,188,"CRI","Costa Rica","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CRI/cri_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
72998,191,"HRV","Croatia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
72999,191,"HRV","Croatia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73000,191,"HRV","Croatia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73001,191,"HRV","Croatia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73002,191,"HRV","Croatia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73003,191,"HRV","Croatia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73004,191,"HRV","Croatia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73005,191,"HRV","Croatia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73006,191,"HRV","Croatia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73007,191,"HRV","Croatia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73008,191,"HRV","Croatia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73009,191,"HRV","Croatia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73010,191,"HRV","Croatia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73011,191,"HRV","Croatia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73012,191,"HRV","Croatia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73013,191,"HRV","Croatia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73014,191,"HRV","Croatia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73015,191,"HRV","Croatia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73016,191,"HRV","Croatia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73017,191,"HRV","Croatia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73018,191,"HRV","Croatia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73019,191,"HRV","Croatia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73020,191,"HRV","Croatia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73021,191,"HRV","Croatia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73022,191,"HRV","Croatia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73023,191,"HRV","Croatia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73024,191,"HRV","Croatia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73025,191,"HRV","Croatia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73026,191,"HRV","Croatia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73027,191,"HRV","Croatia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73028,191,"HRV","Croatia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73029,191,"HRV","Croatia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73030,191,"HRV","Croatia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73031,191,"HRV","Croatia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73032,191,"HRV","Croatia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73033,191,"HRV","Croatia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HRV/hrv_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73034,192,"CUB","Cuba","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73035,192,"CUB","Cuba","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73036,192,"CUB","Cuba","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73037,192,"CUB","Cuba","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73038,192,"CUB","Cuba","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73039,192,"CUB","Cuba","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73040,192,"CUB","Cuba","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73041,192,"CUB","Cuba","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73042,192,"CUB","Cuba","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73043,192,"CUB","Cuba","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73044,192,"CUB","Cuba","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73045,192,"CUB","Cuba","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73046,192,"CUB","Cuba","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73047,192,"CUB","Cuba","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73048,192,"CUB","Cuba","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73049,192,"CUB","Cuba","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73050,192,"CUB","Cuba","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73051,192,"CUB","Cuba","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73052,192,"CUB","Cuba","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73053,192,"CUB","Cuba","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73054,192,"CUB","Cuba","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73055,192,"CUB","Cuba","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73056,192,"CUB","Cuba","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73057,192,"CUB","Cuba","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73058,192,"CUB","Cuba","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73059,192,"CUB","Cuba","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73060,192,"CUB","Cuba","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73061,192,"CUB","Cuba","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73062,192,"CUB","Cuba","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73063,192,"CUB","Cuba","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73064,192,"CUB","Cuba","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73065,192,"CUB","Cuba","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73066,192,"CUB","Cuba","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73067,192,"CUB","Cuba","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73068,192,"CUB","Cuba","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73069,192,"CUB","Cuba","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUB/cub_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73070,196,"CYP","Cyprus","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73071,196,"CYP","Cyprus","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73072,196,"CYP","Cyprus","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73073,196,"CYP","Cyprus","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73074,196,"CYP","Cyprus","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73075,196,"CYP","Cyprus","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73076,196,"CYP","Cyprus","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73077,196,"CYP","Cyprus","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73078,196,"CYP","Cyprus","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73079,196,"CYP","Cyprus","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73080,196,"CYP","Cyprus","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73081,196,"CYP","Cyprus","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73082,196,"CYP","Cyprus","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73083,196,"CYP","Cyprus","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73084,196,"CYP","Cyprus","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73085,196,"CYP","Cyprus","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73086,196,"CYP","Cyprus","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73087,196,"CYP","Cyprus","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73088,196,"CYP","Cyprus","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73089,196,"CYP","Cyprus","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73090,196,"CYP","Cyprus","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73091,196,"CYP","Cyprus","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73092,196,"CYP","Cyprus","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73093,196,"CYP","Cyprus","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73094,196,"CYP","Cyprus","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73095,196,"CYP","Cyprus","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73096,196,"CYP","Cyprus","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73097,196,"CYP","Cyprus","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73098,196,"CYP","Cyprus","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73099,196,"CYP","Cyprus","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73100,196,"CYP","Cyprus","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73101,196,"CYP","Cyprus","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73102,196,"CYP","Cyprus","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73103,196,"CYP","Cyprus","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73104,196,"CYP","Cyprus","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73105,196,"CYP","Cyprus","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CYP/cyp_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73106,203,"CZE","Czech Republic","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73107,203,"CZE","Czech Republic","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73108,203,"CZE","Czech Republic","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73109,203,"CZE","Czech Republic","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73110,203,"CZE","Czech Republic","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73111,203,"CZE","Czech Republic","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73112,203,"CZE","Czech Republic","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73113,203,"CZE","Czech Republic","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73114,203,"CZE","Czech Republic","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73115,203,"CZE","Czech Republic","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73116,203,"CZE","Czech Republic","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73117,203,"CZE","Czech Republic","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73118,203,"CZE","Czech Republic","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73119,203,"CZE","Czech Republic","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73120,203,"CZE","Czech Republic","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73121,203,"CZE","Czech Republic","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73122,203,"CZE","Czech Republic","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73123,203,"CZE","Czech Republic","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73124,203,"CZE","Czech Republic","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73125,203,"CZE","Czech Republic","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73126,203,"CZE","Czech Republic","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73127,203,"CZE","Czech Republic","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73128,203,"CZE","Czech Republic","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73129,203,"CZE","Czech Republic","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73130,203,"CZE","Czech Republic","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73131,203,"CZE","Czech Republic","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73132,203,"CZE","Czech Republic","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73133,203,"CZE","Czech Republic","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73134,203,"CZE","Czech Republic","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73135,203,"CZE","Czech Republic","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73136,203,"CZE","Czech Republic","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73137,203,"CZE","Czech Republic","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73138,203,"CZE","Czech Republic","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73139,203,"CZE","Czech Republic","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73140,203,"CZE","Czech Republic","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73141,203,"CZE","Czech Republic","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CZE/cze_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73142,204,"BEN","Benin","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73143,204,"BEN","Benin","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73144,204,"BEN","Benin","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73145,204,"BEN","Benin","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73146,204,"BEN","Benin","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73147,204,"BEN","Benin","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73148,204,"BEN","Benin","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73149,204,"BEN","Benin","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73150,204,"BEN","Benin","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73151,204,"BEN","Benin","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73152,204,"BEN","Benin","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73153,204,"BEN","Benin","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73154,204,"BEN","Benin","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73155,204,"BEN","Benin","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73156,204,"BEN","Benin","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73157,204,"BEN","Benin","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73158,204,"BEN","Benin","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73159,204,"BEN","Benin","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73160,204,"BEN","Benin","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73161,204,"BEN","Benin","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73162,204,"BEN","Benin","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73163,204,"BEN","Benin","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73164,204,"BEN","Benin","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73165,204,"BEN","Benin","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73166,204,"BEN","Benin","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73167,204,"BEN","Benin","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73168,204,"BEN","Benin","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73169,204,"BEN","Benin","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73170,204,"BEN","Benin","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73171,204,"BEN","Benin","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73172,204,"BEN","Benin","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73173,204,"BEN","Benin","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73174,204,"BEN","Benin","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73175,204,"BEN","Benin","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73176,204,"BEN","Benin","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73177,204,"BEN","Benin","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BEN/ben_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73178,208,"DNK","Denmark","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73179,208,"DNK","Denmark","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73180,208,"DNK","Denmark","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73181,208,"DNK","Denmark","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73182,208,"DNK","Denmark","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73183,208,"DNK","Denmark","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73184,208,"DNK","Denmark","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73185,208,"DNK","Denmark","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73186,208,"DNK","Denmark","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73187,208,"DNK","Denmark","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73188,208,"DNK","Denmark","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73189,208,"DNK","Denmark","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73190,208,"DNK","Denmark","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73191,208,"DNK","Denmark","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73192,208,"DNK","Denmark","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73193,208,"DNK","Denmark","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73194,208,"DNK","Denmark","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73195,208,"DNK","Denmark","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73196,208,"DNK","Denmark","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73197,208,"DNK","Denmark","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73198,208,"DNK","Denmark","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73199,208,"DNK","Denmark","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73200,208,"DNK","Denmark","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73201,208,"DNK","Denmark","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73202,208,"DNK","Denmark","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73203,208,"DNK","Denmark","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73204,208,"DNK","Denmark","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73205,208,"DNK","Denmark","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73206,208,"DNK","Denmark","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73207,208,"DNK","Denmark","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73208,208,"DNK","Denmark","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73209,208,"DNK","Denmark","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73210,208,"DNK","Denmark","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73211,208,"DNK","Denmark","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73212,208,"DNK","Denmark","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73213,208,"DNK","Denmark","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DNK/dnk_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73214,212,"DMA","Dominica","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73215,212,"DMA","Dominica","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73216,212,"DMA","Dominica","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73217,212,"DMA","Dominica","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73218,212,"DMA","Dominica","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73219,212,"DMA","Dominica","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73220,212,"DMA","Dominica","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73221,212,"DMA","Dominica","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73222,212,"DMA","Dominica","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73223,212,"DMA","Dominica","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73224,212,"DMA","Dominica","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73225,212,"DMA","Dominica","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73226,212,"DMA","Dominica","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73227,212,"DMA","Dominica","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73228,212,"DMA","Dominica","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73229,212,"DMA","Dominica","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73230,212,"DMA","Dominica","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73231,212,"DMA","Dominica","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73232,212,"DMA","Dominica","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73233,212,"DMA","Dominica","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73234,212,"DMA","Dominica","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73235,212,"DMA","Dominica","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73236,212,"DMA","Dominica","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73237,212,"DMA","Dominica","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73238,212,"DMA","Dominica","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73239,212,"DMA","Dominica","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73240,212,"DMA","Dominica","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73241,212,"DMA","Dominica","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73242,212,"DMA","Dominica","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73243,212,"DMA","Dominica","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73244,212,"DMA","Dominica","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73245,212,"DMA","Dominica","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73246,212,"DMA","Dominica","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73247,212,"DMA","Dominica","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73248,212,"DMA","Dominica","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73249,212,"DMA","Dominica","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DMA/dma_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73250,214,"DOM","Dominican Republic","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73251,214,"DOM","Dominican Republic","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73252,214,"DOM","Dominican Republic","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73253,214,"DOM","Dominican Republic","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73254,214,"DOM","Dominican Republic","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73255,214,"DOM","Dominican Republic","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73256,214,"DOM","Dominican Republic","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73257,214,"DOM","Dominican Republic","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73258,214,"DOM","Dominican Republic","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73259,214,"DOM","Dominican Republic","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73260,214,"DOM","Dominican Republic","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73261,214,"DOM","Dominican Republic","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73262,214,"DOM","Dominican Republic","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73263,214,"DOM","Dominican Republic","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73264,214,"DOM","Dominican Republic","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73265,214,"DOM","Dominican Republic","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73266,214,"DOM","Dominican Republic","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73267,214,"DOM","Dominican Republic","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73268,214,"DOM","Dominican Republic","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73269,214,"DOM","Dominican Republic","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73270,214,"DOM","Dominican Republic","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73271,214,"DOM","Dominican Republic","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73272,214,"DOM","Dominican Republic","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73273,214,"DOM","Dominican Republic","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73274,214,"DOM","Dominican Republic","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73275,214,"DOM","Dominican Republic","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73276,214,"DOM","Dominican Republic","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73277,214,"DOM","Dominican Republic","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73278,214,"DOM","Dominican Republic","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73279,214,"DOM","Dominican Republic","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73280,214,"DOM","Dominican Republic","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73281,214,"DOM","Dominican Republic","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73282,214,"DOM","Dominican Republic","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73283,214,"DOM","Dominican Republic","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73284,214,"DOM","Dominican Republic","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73285,214,"DOM","Dominican Republic","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DOM/dom_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73286,218,"ECU","Ecuador","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73287,218,"ECU","Ecuador","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73288,218,"ECU","Ecuador","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73289,218,"ECU","Ecuador","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73290,218,"ECU","Ecuador","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73291,218,"ECU","Ecuador","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73292,218,"ECU","Ecuador","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73293,218,"ECU","Ecuador","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73294,218,"ECU","Ecuador","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73295,218,"ECU","Ecuador","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73296,218,"ECU","Ecuador","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73297,218,"ECU","Ecuador","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73298,218,"ECU","Ecuador","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73299,218,"ECU","Ecuador","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73300,218,"ECU","Ecuador","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73301,218,"ECU","Ecuador","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73302,218,"ECU","Ecuador","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73303,218,"ECU","Ecuador","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73304,218,"ECU","Ecuador","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73305,218,"ECU","Ecuador","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73306,218,"ECU","Ecuador","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73307,218,"ECU","Ecuador","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73308,218,"ECU","Ecuador","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73309,218,"ECU","Ecuador","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73310,218,"ECU","Ecuador","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73311,218,"ECU","Ecuador","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73312,218,"ECU","Ecuador","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73313,218,"ECU","Ecuador","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73314,218,"ECU","Ecuador","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73315,218,"ECU","Ecuador","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73316,218,"ECU","Ecuador","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73317,218,"ECU","Ecuador","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73318,218,"ECU","Ecuador","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73319,218,"ECU","Ecuador","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73320,218,"ECU","Ecuador","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73321,218,"ECU","Ecuador","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ECU/ecu_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73322,222,"SLV","El Salvador","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73323,222,"SLV","El Salvador","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73324,222,"SLV","El Salvador","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73325,222,"SLV","El Salvador","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73326,222,"SLV","El Salvador","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73327,222,"SLV","El Salvador","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73328,222,"SLV","El Salvador","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73329,222,"SLV","El Salvador","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73330,222,"SLV","El Salvador","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73331,222,"SLV","El Salvador","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73332,222,"SLV","El Salvador","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73333,222,"SLV","El Salvador","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73334,222,"SLV","El Salvador","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73335,222,"SLV","El Salvador","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73336,222,"SLV","El Salvador","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73337,222,"SLV","El Salvador","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73338,222,"SLV","El Salvador","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73339,222,"SLV","El Salvador","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73340,222,"SLV","El Salvador","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73341,222,"SLV","El Salvador","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73342,222,"SLV","El Salvador","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73343,222,"SLV","El Salvador","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73344,222,"SLV","El Salvador","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73345,222,"SLV","El Salvador","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73346,222,"SLV","El Salvador","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73347,222,"SLV","El Salvador","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73348,222,"SLV","El Salvador","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73349,222,"SLV","El Salvador","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73350,222,"SLV","El Salvador","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73351,222,"SLV","El Salvador","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73352,222,"SLV","El Salvador","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73353,222,"SLV","El Salvador","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73354,222,"SLV","El Salvador","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73355,222,"SLV","El Salvador","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73356,222,"SLV","El Salvador","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73357,222,"SLV","El Salvador","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLV/slv_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73358,226,"GNQ","Equatorial Guinea","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73359,226,"GNQ","Equatorial Guinea","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73360,226,"GNQ","Equatorial Guinea","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73361,226,"GNQ","Equatorial Guinea","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73362,226,"GNQ","Equatorial Guinea","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73363,226,"GNQ","Equatorial Guinea","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73364,226,"GNQ","Equatorial Guinea","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73365,226,"GNQ","Equatorial Guinea","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73366,226,"GNQ","Equatorial Guinea","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73367,226,"GNQ","Equatorial Guinea","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73368,226,"GNQ","Equatorial Guinea","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73369,226,"GNQ","Equatorial Guinea","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73370,226,"GNQ","Equatorial Guinea","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73371,226,"GNQ","Equatorial Guinea","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73372,226,"GNQ","Equatorial Guinea","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73373,226,"GNQ","Equatorial Guinea","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73374,226,"GNQ","Equatorial Guinea","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73375,226,"GNQ","Equatorial Guinea","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73376,226,"GNQ","Equatorial Guinea","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73377,226,"GNQ","Equatorial Guinea","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73378,226,"GNQ","Equatorial Guinea","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73379,226,"GNQ","Equatorial Guinea","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73380,226,"GNQ","Equatorial Guinea","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73381,226,"GNQ","Equatorial Guinea","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73382,226,"GNQ","Equatorial Guinea","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73383,226,"GNQ","Equatorial Guinea","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73384,226,"GNQ","Equatorial Guinea","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73385,226,"GNQ","Equatorial Guinea","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73386,226,"GNQ","Equatorial Guinea","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73387,226,"GNQ","Equatorial Guinea","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73388,226,"GNQ","Equatorial Guinea","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73389,226,"GNQ","Equatorial Guinea","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73390,226,"GNQ","Equatorial Guinea","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73391,226,"GNQ","Equatorial Guinea","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73392,226,"GNQ","Equatorial Guinea","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73393,226,"GNQ","Equatorial Guinea","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNQ/gnq_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73394,231,"ETH","Ethiopia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73395,231,"ETH","Ethiopia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73396,231,"ETH","Ethiopia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73397,231,"ETH","Ethiopia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73398,231,"ETH","Ethiopia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73399,231,"ETH","Ethiopia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73400,231,"ETH","Ethiopia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73401,231,"ETH","Ethiopia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73402,231,"ETH","Ethiopia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73403,231,"ETH","Ethiopia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73404,231,"ETH","Ethiopia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73405,231,"ETH","Ethiopia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73406,231,"ETH","Ethiopia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73407,231,"ETH","Ethiopia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73408,231,"ETH","Ethiopia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73409,231,"ETH","Ethiopia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73410,231,"ETH","Ethiopia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73411,231,"ETH","Ethiopia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73412,231,"ETH","Ethiopia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73413,231,"ETH","Ethiopia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73414,231,"ETH","Ethiopia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73415,231,"ETH","Ethiopia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73416,231,"ETH","Ethiopia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73417,231,"ETH","Ethiopia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73418,231,"ETH","Ethiopia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73419,231,"ETH","Ethiopia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73420,231,"ETH","Ethiopia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73421,231,"ETH","Ethiopia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73422,231,"ETH","Ethiopia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73423,231,"ETH","Ethiopia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73424,231,"ETH","Ethiopia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73425,231,"ETH","Ethiopia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73426,231,"ETH","Ethiopia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73427,231,"ETH","Ethiopia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73428,231,"ETH","Ethiopia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73429,231,"ETH","Ethiopia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ETH/eth_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73430,232,"ERI","Eritrea","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73431,232,"ERI","Eritrea","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73432,232,"ERI","Eritrea","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73433,232,"ERI","Eritrea","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73434,232,"ERI","Eritrea","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73435,232,"ERI","Eritrea","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73436,232,"ERI","Eritrea","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73437,232,"ERI","Eritrea","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73438,232,"ERI","Eritrea","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73439,232,"ERI","Eritrea","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73440,232,"ERI","Eritrea","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73441,232,"ERI","Eritrea","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73442,232,"ERI","Eritrea","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73443,232,"ERI","Eritrea","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73444,232,"ERI","Eritrea","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73445,232,"ERI","Eritrea","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73446,232,"ERI","Eritrea","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73447,232,"ERI","Eritrea","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73448,232,"ERI","Eritrea","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73449,232,"ERI","Eritrea","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73450,232,"ERI","Eritrea","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73451,232,"ERI","Eritrea","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73452,232,"ERI","Eritrea","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73453,232,"ERI","Eritrea","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73454,232,"ERI","Eritrea","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73455,232,"ERI","Eritrea","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73456,232,"ERI","Eritrea","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73457,232,"ERI","Eritrea","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73458,232,"ERI","Eritrea","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73459,232,"ERI","Eritrea","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73460,232,"ERI","Eritrea","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73461,232,"ERI","Eritrea","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73462,232,"ERI","Eritrea","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73463,232,"ERI","Eritrea","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73464,232,"ERI","Eritrea","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73465,232,"ERI","Eritrea","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ERI/eri_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73466,233,"EST","Estonia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73467,233,"EST","Estonia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73468,233,"EST","Estonia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73469,233,"EST","Estonia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73470,233,"EST","Estonia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73471,233,"EST","Estonia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73472,233,"EST","Estonia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73473,233,"EST","Estonia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73474,233,"EST","Estonia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73475,233,"EST","Estonia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73476,233,"EST","Estonia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73477,233,"EST","Estonia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73478,233,"EST","Estonia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73479,233,"EST","Estonia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73480,233,"EST","Estonia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73481,233,"EST","Estonia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73482,233,"EST","Estonia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73483,233,"EST","Estonia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73484,233,"EST","Estonia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73485,233,"EST","Estonia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73486,233,"EST","Estonia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73487,233,"EST","Estonia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73488,233,"EST","Estonia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73489,233,"EST","Estonia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73490,233,"EST","Estonia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73491,233,"EST","Estonia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73492,233,"EST","Estonia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73493,233,"EST","Estonia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73494,233,"EST","Estonia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73495,233,"EST","Estonia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73496,233,"EST","Estonia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73497,233,"EST","Estonia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73498,233,"EST","Estonia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73499,233,"EST","Estonia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73500,233,"EST","Estonia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73501,233,"EST","Estonia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EST/est_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73502,234,"FRO","Faroe Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73503,234,"FRO","Faroe Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73504,234,"FRO","Faroe Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73505,234,"FRO","Faroe Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73506,234,"FRO","Faroe Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73507,234,"FRO","Faroe Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73508,234,"FRO","Faroe Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73509,234,"FRO","Faroe Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73510,234,"FRO","Faroe Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73511,234,"FRO","Faroe Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73512,234,"FRO","Faroe Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73513,234,"FRO","Faroe Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73514,234,"FRO","Faroe Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73515,234,"FRO","Faroe Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73516,234,"FRO","Faroe Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73517,234,"FRO","Faroe Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73518,234,"FRO","Faroe Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73519,234,"FRO","Faroe Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73520,234,"FRO","Faroe Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73521,234,"FRO","Faroe Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73522,234,"FRO","Faroe Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73523,234,"FRO","Faroe Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73524,234,"FRO","Faroe Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73525,234,"FRO","Faroe Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73526,234,"FRO","Faroe Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73527,234,"FRO","Faroe Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73528,234,"FRO","Faroe Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73529,234,"FRO","Faroe Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73530,234,"FRO","Faroe Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73531,234,"FRO","Faroe Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73532,234,"FRO","Faroe Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73533,234,"FRO","Faroe Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73534,234,"FRO","Faroe Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73535,234,"FRO","Faroe Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73536,234,"FRO","Faroe Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73537,234,"FRO","Faroe Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRO/fro_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73538,238,"FLK","Falkland Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73539,238,"FLK","Falkland Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73540,238,"FLK","Falkland Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73541,238,"FLK","Falkland Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73542,238,"FLK","Falkland Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73543,238,"FLK","Falkland Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73544,238,"FLK","Falkland Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73545,238,"FLK","Falkland Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73546,238,"FLK","Falkland Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73547,238,"FLK","Falkland Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73548,238,"FLK","Falkland Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73549,238,"FLK","Falkland Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73550,238,"FLK","Falkland Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73551,238,"FLK","Falkland Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73552,238,"FLK","Falkland Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73553,238,"FLK","Falkland Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73554,238,"FLK","Falkland Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73555,238,"FLK","Falkland Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73556,238,"FLK","Falkland Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73557,238,"FLK","Falkland Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73558,238,"FLK","Falkland Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73559,238,"FLK","Falkland Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73560,238,"FLK","Falkland Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73561,238,"FLK","Falkland Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73562,238,"FLK","Falkland Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73563,238,"FLK","Falkland Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73564,238,"FLK","Falkland Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73565,238,"FLK","Falkland Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73566,238,"FLK","Falkland Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73567,238,"FLK","Falkland Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73568,238,"FLK","Falkland Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73569,238,"FLK","Falkland Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73570,238,"FLK","Falkland Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73571,238,"FLK","Falkland Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73572,238,"FLK","Falkland Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73573,238,"FLK","Falkland Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FLK/flk_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73574,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73575,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73576,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73577,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73578,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73579,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73580,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73581,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73582,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73583,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73584,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73585,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73586,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73587,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73588,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73589,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73590,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73591,239,"SGS","South Georgia and the South Sandwich Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73592,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73593,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73594,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73595,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73596,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73597,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73598,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73599,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73600,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73601,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73602,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73603,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73604,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73605,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73606,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73607,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73608,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73609,239,"SGS","South Georgia and the South Sandwich Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGS/sgs_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73610,242,"FJI","Fiji","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73611,242,"FJI","Fiji","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73612,242,"FJI","Fiji","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73613,242,"FJI","Fiji","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73614,242,"FJI","Fiji","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73615,242,"FJI","Fiji","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73616,242,"FJI","Fiji","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73617,242,"FJI","Fiji","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73618,242,"FJI","Fiji","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73619,242,"FJI","Fiji","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73620,242,"FJI","Fiji","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73621,242,"FJI","Fiji","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73622,242,"FJI","Fiji","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73623,242,"FJI","Fiji","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73624,242,"FJI","Fiji","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73625,242,"FJI","Fiji","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73626,242,"FJI","Fiji","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73627,242,"FJI","Fiji","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73628,242,"FJI","Fiji","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73629,242,"FJI","Fiji","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73630,242,"FJI","Fiji","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73631,242,"FJI","Fiji","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73632,242,"FJI","Fiji","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73633,242,"FJI","Fiji","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73634,242,"FJI","Fiji","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73635,242,"FJI","Fiji","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73636,242,"FJI","Fiji","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73637,242,"FJI","Fiji","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73638,242,"FJI","Fiji","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73639,242,"FJI","Fiji","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73640,242,"FJI","Fiji","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73641,242,"FJI","Fiji","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73642,242,"FJI","Fiji","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73643,242,"FJI","Fiji","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73644,242,"FJI","Fiji","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73645,242,"FJI","Fiji","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FJI/fji_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73646,246,"FIN","Finland","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73647,246,"FIN","Finland","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73648,246,"FIN","Finland","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73649,246,"FIN","Finland","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73650,246,"FIN","Finland","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73651,246,"FIN","Finland","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73652,246,"FIN","Finland","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73653,246,"FIN","Finland","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73654,246,"FIN","Finland","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73655,246,"FIN","Finland","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73656,246,"FIN","Finland","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73657,246,"FIN","Finland","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73658,246,"FIN","Finland","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73659,246,"FIN","Finland","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73660,246,"FIN","Finland","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73661,246,"FIN","Finland","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73662,246,"FIN","Finland","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73663,246,"FIN","Finland","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73664,246,"FIN","Finland","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73665,246,"FIN","Finland","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73666,246,"FIN","Finland","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73667,246,"FIN","Finland","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73668,246,"FIN","Finland","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73669,246,"FIN","Finland","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73670,246,"FIN","Finland","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73671,246,"FIN","Finland","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73672,246,"FIN","Finland","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73673,246,"FIN","Finland","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73674,246,"FIN","Finland","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73675,246,"FIN","Finland","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73676,246,"FIN","Finland","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73677,246,"FIN","Finland","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73678,246,"FIN","Finland","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73679,246,"FIN","Finland","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73680,246,"FIN","Finland","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73681,246,"FIN","Finland","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FIN/fin_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73682,248,"ALA","Aland Islands ","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73683,248,"ALA","Aland Islands ","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73684,248,"ALA","Aland Islands ","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73685,248,"ALA","Aland Islands ","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73686,248,"ALA","Aland Islands ","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73687,248,"ALA","Aland Islands ","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73688,248,"ALA","Aland Islands ","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73689,248,"ALA","Aland Islands ","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73690,248,"ALA","Aland Islands ","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73691,248,"ALA","Aland Islands ","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73692,248,"ALA","Aland Islands ","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73693,248,"ALA","Aland Islands ","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73694,248,"ALA","Aland Islands ","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73695,248,"ALA","Aland Islands ","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73696,248,"ALA","Aland Islands ","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73697,248,"ALA","Aland Islands ","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73698,248,"ALA","Aland Islands ","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73699,248,"ALA","Aland Islands ","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73700,248,"ALA","Aland Islands ","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73701,248,"ALA","Aland Islands ","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73702,248,"ALA","Aland Islands ","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73703,248,"ALA","Aland Islands ","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73704,248,"ALA","Aland Islands ","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73705,248,"ALA","Aland Islands ","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73706,248,"ALA","Aland Islands ","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73707,248,"ALA","Aland Islands ","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73708,248,"ALA","Aland Islands ","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73709,248,"ALA","Aland Islands ","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73710,248,"ALA","Aland Islands ","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73711,248,"ALA","Aland Islands ","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73712,248,"ALA","Aland Islands ","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73713,248,"ALA","Aland Islands ","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73714,248,"ALA","Aland Islands ","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73715,248,"ALA","Aland Islands ","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73716,248,"ALA","Aland Islands ","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73717,248,"ALA","Aland Islands ","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ALA/ala_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73718,250,"FRA","France","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73719,250,"FRA","France","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73720,250,"FRA","France","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73721,250,"FRA","France","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73722,250,"FRA","France","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73723,250,"FRA","France","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73724,250,"FRA","France","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73725,250,"FRA","France","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73726,250,"FRA","France","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73727,250,"FRA","France","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73728,250,"FRA","France","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73729,250,"FRA","France","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73730,250,"FRA","France","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73731,250,"FRA","France","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73732,250,"FRA","France","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73733,250,"FRA","France","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73734,250,"FRA","France","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73735,250,"FRA","France","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73736,250,"FRA","France","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73737,250,"FRA","France","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73738,250,"FRA","France","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73739,250,"FRA","France","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73740,250,"FRA","France","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73741,250,"FRA","France","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73742,250,"FRA","France","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73743,250,"FRA","France","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73744,250,"FRA","France","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73745,250,"FRA","France","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73746,250,"FRA","France","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73747,250,"FRA","France","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73748,250,"FRA","France","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73749,250,"FRA","France","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73750,250,"FRA","France","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73751,250,"FRA","France","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73752,250,"FRA","France","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73753,250,"FRA","France","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FRA/fra_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73754,254,"GUF","French Guiana","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73755,254,"GUF","French Guiana","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73756,254,"GUF","French Guiana","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73757,254,"GUF","French Guiana","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73758,254,"GUF","French Guiana","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73759,254,"GUF","French Guiana","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73760,254,"GUF","French Guiana","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73761,254,"GUF","French Guiana","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73762,254,"GUF","French Guiana","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73763,254,"GUF","French Guiana","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73764,254,"GUF","French Guiana","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73765,254,"GUF","French Guiana","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73766,254,"GUF","French Guiana","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73767,254,"GUF","French Guiana","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73768,254,"GUF","French Guiana","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73769,254,"GUF","French Guiana","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73770,254,"GUF","French Guiana","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73771,254,"GUF","French Guiana","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73772,254,"GUF","French Guiana","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73773,254,"GUF","French Guiana","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73774,254,"GUF","French Guiana","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73775,254,"GUF","French Guiana","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73776,254,"GUF","French Guiana","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73777,254,"GUF","French Guiana","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73778,254,"GUF","French Guiana","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73779,254,"GUF","French Guiana","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73780,254,"GUF","French Guiana","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73781,254,"GUF","French Guiana","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73782,254,"GUF","French Guiana","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73783,254,"GUF","French Guiana","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73784,254,"GUF","French Guiana","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73785,254,"GUF","French Guiana","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73786,254,"GUF","French Guiana","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73787,254,"GUF","French Guiana","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73788,254,"GUF","French Guiana","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73789,254,"GUF","French Guiana","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUF/guf_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73790,258,"PYF","French Polynesia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73791,258,"PYF","French Polynesia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73792,258,"PYF","French Polynesia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73793,258,"PYF","French Polynesia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73794,258,"PYF","French Polynesia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73795,258,"PYF","French Polynesia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73796,258,"PYF","French Polynesia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73797,258,"PYF","French Polynesia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73798,258,"PYF","French Polynesia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73799,258,"PYF","French Polynesia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73800,258,"PYF","French Polynesia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73801,258,"PYF","French Polynesia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73802,258,"PYF","French Polynesia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73803,258,"PYF","French Polynesia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73804,258,"PYF","French Polynesia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73805,258,"PYF","French Polynesia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73806,258,"PYF","French Polynesia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73807,258,"PYF","French Polynesia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73808,258,"PYF","French Polynesia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73809,258,"PYF","French Polynesia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73810,258,"PYF","French Polynesia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73811,258,"PYF","French Polynesia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73812,258,"PYF","French Polynesia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73813,258,"PYF","French Polynesia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73814,258,"PYF","French Polynesia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73815,258,"PYF","French Polynesia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73816,258,"PYF","French Polynesia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73817,258,"PYF","French Polynesia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73818,258,"PYF","French Polynesia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73819,258,"PYF","French Polynesia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73820,258,"PYF","French Polynesia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73821,258,"PYF","French Polynesia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73822,258,"PYF","French Polynesia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73823,258,"PYF","French Polynesia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73824,258,"PYF","French Polynesia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73825,258,"PYF","French Polynesia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PYF/pyf_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73826,260,"ATF","French Southern Territories","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73827,260,"ATF","French Southern Territories","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73828,260,"ATF","French Southern Territories","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73829,260,"ATF","French Southern Territories","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73830,260,"ATF","French Southern Territories","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73831,260,"ATF","French Southern Territories","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73832,260,"ATF","French Southern Territories","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73833,260,"ATF","French Southern Territories","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73834,260,"ATF","French Southern Territories","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73835,260,"ATF","French Southern Territories","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73836,260,"ATF","French Southern Territories","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73837,260,"ATF","French Southern Territories","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73838,260,"ATF","French Southern Territories","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73839,260,"ATF","French Southern Territories","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73840,260,"ATF","French Southern Territories","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73841,260,"ATF","French Southern Territories","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73842,260,"ATF","French Southern Territories","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73843,260,"ATF","French Southern Territories","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73844,260,"ATF","French Southern Territories","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73845,260,"ATF","French Southern Territories","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73846,260,"ATF","French Southern Territories","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73847,260,"ATF","French Southern Territories","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73848,260,"ATF","French Southern Territories","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73849,260,"ATF","French Southern Territories","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73850,260,"ATF","French Southern Territories","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73851,260,"ATF","French Southern Territories","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73852,260,"ATF","French Southern Territories","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73853,260,"ATF","French Southern Territories","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73854,260,"ATF","French Southern Territories","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73855,260,"ATF","French Southern Territories","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73856,260,"ATF","French Southern Territories","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73857,260,"ATF","French Southern Territories","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73858,260,"ATF","French Southern Territories","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73859,260,"ATF","French Southern Territories","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73860,260,"ATF","French Southern Territories","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73861,260,"ATF","French Southern Territories","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ATF/atf_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73862,262,"DJI","Djibouti","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73863,262,"DJI","Djibouti","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73864,262,"DJI","Djibouti","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73865,262,"DJI","Djibouti","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73866,262,"DJI","Djibouti","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73867,262,"DJI","Djibouti","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73868,262,"DJI","Djibouti","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73869,262,"DJI","Djibouti","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73870,262,"DJI","Djibouti","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73871,262,"DJI","Djibouti","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73872,262,"DJI","Djibouti","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73873,262,"DJI","Djibouti","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73874,262,"DJI","Djibouti","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73875,262,"DJI","Djibouti","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73876,262,"DJI","Djibouti","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73877,262,"DJI","Djibouti","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73878,262,"DJI","Djibouti","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73879,262,"DJI","Djibouti","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73880,262,"DJI","Djibouti","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73881,262,"DJI","Djibouti","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73882,262,"DJI","Djibouti","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73883,262,"DJI","Djibouti","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73884,262,"DJI","Djibouti","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73885,262,"DJI","Djibouti","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73886,262,"DJI","Djibouti","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73887,262,"DJI","Djibouti","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73888,262,"DJI","Djibouti","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73889,262,"DJI","Djibouti","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73890,262,"DJI","Djibouti","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73891,262,"DJI","Djibouti","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73892,262,"DJI","Djibouti","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73893,262,"DJI","Djibouti","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73894,262,"DJI","Djibouti","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73895,262,"DJI","Djibouti","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73896,262,"DJI","Djibouti","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73897,262,"DJI","Djibouti","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DJI/dji_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73898,266,"GAB","Gabon","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73899,266,"GAB","Gabon","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73900,266,"GAB","Gabon","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73901,266,"GAB","Gabon","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73902,266,"GAB","Gabon","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73903,266,"GAB","Gabon","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73904,266,"GAB","Gabon","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73905,266,"GAB","Gabon","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73906,266,"GAB","Gabon","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73907,266,"GAB","Gabon","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73908,266,"GAB","Gabon","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73909,266,"GAB","Gabon","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73910,266,"GAB","Gabon","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73911,266,"GAB","Gabon","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73912,266,"GAB","Gabon","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73913,266,"GAB","Gabon","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73914,266,"GAB","Gabon","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73915,266,"GAB","Gabon","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73916,266,"GAB","Gabon","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73917,266,"GAB","Gabon","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73918,266,"GAB","Gabon","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73919,266,"GAB","Gabon","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73920,266,"GAB","Gabon","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73921,266,"GAB","Gabon","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73922,266,"GAB","Gabon","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73923,266,"GAB","Gabon","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73924,266,"GAB","Gabon","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73925,266,"GAB","Gabon","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73926,266,"GAB","Gabon","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73927,266,"GAB","Gabon","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73928,266,"GAB","Gabon","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73929,266,"GAB","Gabon","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73930,266,"GAB","Gabon","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73931,266,"GAB","Gabon","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73932,266,"GAB","Gabon","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73933,266,"GAB","Gabon","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GAB/gab_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73934,268,"GEO","Georgia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73935,268,"GEO","Georgia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73936,268,"GEO","Georgia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73937,268,"GEO","Georgia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73938,268,"GEO","Georgia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73939,268,"GEO","Georgia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73940,268,"GEO","Georgia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73941,268,"GEO","Georgia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73942,268,"GEO","Georgia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73943,268,"GEO","Georgia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73944,268,"GEO","Georgia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73945,268,"GEO","Georgia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73946,268,"GEO","Georgia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73947,268,"GEO","Georgia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73948,268,"GEO","Georgia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73949,268,"GEO","Georgia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73950,268,"GEO","Georgia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73951,268,"GEO","Georgia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73952,268,"GEO","Georgia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73953,268,"GEO","Georgia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73954,268,"GEO","Georgia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73955,268,"GEO","Georgia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73956,268,"GEO","Georgia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73957,268,"GEO","Georgia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73958,268,"GEO","Georgia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73959,268,"GEO","Georgia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73960,268,"GEO","Georgia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73961,268,"GEO","Georgia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73962,268,"GEO","Georgia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73963,268,"GEO","Georgia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
73964,268,"GEO","Georgia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
73965,268,"GEO","Georgia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
73966,268,"GEO","Georgia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
73967,268,"GEO","Georgia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
73968,268,"GEO","Georgia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
73969,268,"GEO","Georgia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GEO/geo_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
73970,270,"GMB","Gambia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
73971,270,"GMB","Gambia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
73972,270,"GMB","Gambia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
73973,270,"GMB","Gambia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
73974,270,"GMB","Gambia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
73975,270,"GMB","Gambia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
73976,270,"GMB","Gambia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
73977,270,"GMB","Gambia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
73978,270,"GMB","Gambia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
73979,270,"GMB","Gambia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
73980,270,"GMB","Gambia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
73981,270,"GMB","Gambia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
73982,270,"GMB","Gambia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
73983,270,"GMB","Gambia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
73984,270,"GMB","Gambia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
73985,270,"GMB","Gambia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
73986,270,"GMB","Gambia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
73987,270,"GMB","Gambia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
73988,270,"GMB","Gambia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
73989,270,"GMB","Gambia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
73990,270,"GMB","Gambia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
73991,270,"GMB","Gambia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
73992,270,"GMB","Gambia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
73993,270,"GMB","Gambia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
73994,270,"GMB","Gambia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
73995,270,"GMB","Gambia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
73996,270,"GMB","Gambia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
73997,270,"GMB","Gambia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
73998,270,"GMB","Gambia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
73999,270,"GMB","Gambia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74000,270,"GMB","Gambia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74001,270,"GMB","Gambia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74002,270,"GMB","Gambia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74003,270,"GMB","Gambia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74004,270,"GMB","Gambia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74005,270,"GMB","Gambia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GMB/gmb_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74006,275,"PSE","Palestina","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74007,275,"PSE","Palestina","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74008,275,"PSE","Palestina","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74009,275,"PSE","Palestina","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74010,275,"PSE","Palestina","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74011,275,"PSE","Palestina","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74012,275,"PSE","Palestina","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74013,275,"PSE","Palestina","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74014,275,"PSE","Palestina","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74015,275,"PSE","Palestina","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74016,275,"PSE","Palestina","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74017,275,"PSE","Palestina","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74018,275,"PSE","Palestina","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74019,275,"PSE","Palestina","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74020,275,"PSE","Palestina","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74021,275,"PSE","Palestina","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74022,275,"PSE","Palestina","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74023,275,"PSE","Palestina","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74024,275,"PSE","Palestina","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74025,275,"PSE","Palestina","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74026,275,"PSE","Palestina","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74027,275,"PSE","Palestina","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74028,275,"PSE","Palestina","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74029,275,"PSE","Palestina","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74030,275,"PSE","Palestina","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74031,275,"PSE","Palestina","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74032,275,"PSE","Palestina","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74033,275,"PSE","Palestina","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74034,275,"PSE","Palestina","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74035,275,"PSE","Palestina","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74036,275,"PSE","Palestina","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74037,275,"PSE","Palestina","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74038,275,"PSE","Palestina","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74039,275,"PSE","Palestina","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74040,275,"PSE","Palestina","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74041,275,"PSE","Palestina","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PSE/pse_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74042,276,"DEU","Germany","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74043,276,"DEU","Germany","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74044,276,"DEU","Germany","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74045,276,"DEU","Germany","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74046,276,"DEU","Germany","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74047,276,"DEU","Germany","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74048,276,"DEU","Germany","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74049,276,"DEU","Germany","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74050,276,"DEU","Germany","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74051,276,"DEU","Germany","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74052,276,"DEU","Germany","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74053,276,"DEU","Germany","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74054,276,"DEU","Germany","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74055,276,"DEU","Germany","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74056,276,"DEU","Germany","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74057,276,"DEU","Germany","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74058,276,"DEU","Germany","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74059,276,"DEU","Germany","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74060,276,"DEU","Germany","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74061,276,"DEU","Germany","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74062,276,"DEU","Germany","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74063,276,"DEU","Germany","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74064,276,"DEU","Germany","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74065,276,"DEU","Germany","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74066,276,"DEU","Germany","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74067,276,"DEU","Germany","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74068,276,"DEU","Germany","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74069,276,"DEU","Germany","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74070,276,"DEU","Germany","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74071,276,"DEU","Germany","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74072,276,"DEU","Germany","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74073,276,"DEU","Germany","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74074,276,"DEU","Germany","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74075,276,"DEU","Germany","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74076,276,"DEU","Germany","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74077,276,"DEU","Germany","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/DEU/deu_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74078,288,"GHA","Ghana","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74079,288,"GHA","Ghana","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74080,288,"GHA","Ghana","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74081,288,"GHA","Ghana","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74082,288,"GHA","Ghana","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74083,288,"GHA","Ghana","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74084,288,"GHA","Ghana","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74085,288,"GHA","Ghana","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74086,288,"GHA","Ghana","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74087,288,"GHA","Ghana","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74088,288,"GHA","Ghana","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74089,288,"GHA","Ghana","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74090,288,"GHA","Ghana","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74091,288,"GHA","Ghana","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74092,288,"GHA","Ghana","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74093,288,"GHA","Ghana","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74094,288,"GHA","Ghana","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74095,288,"GHA","Ghana","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74096,288,"GHA","Ghana","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74097,288,"GHA","Ghana","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74098,288,"GHA","Ghana","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74099,288,"GHA","Ghana","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74100,288,"GHA","Ghana","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74101,288,"GHA","Ghana","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74102,288,"GHA","Ghana","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74103,288,"GHA","Ghana","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74104,288,"GHA","Ghana","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74105,288,"GHA","Ghana","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74106,288,"GHA","Ghana","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74107,288,"GHA","Ghana","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74108,288,"GHA","Ghana","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74109,288,"GHA","Ghana","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74110,288,"GHA","Ghana","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74111,288,"GHA","Ghana","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74112,288,"GHA","Ghana","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74113,288,"GHA","Ghana","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GHA/gha_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74114,292,"GIB","Gibraltar","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74115,292,"GIB","Gibraltar","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74116,292,"GIB","Gibraltar","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74117,292,"GIB","Gibraltar","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74118,292,"GIB","Gibraltar","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74119,292,"GIB","Gibraltar","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74120,292,"GIB","Gibraltar","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74121,292,"GIB","Gibraltar","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74122,292,"GIB","Gibraltar","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74123,292,"GIB","Gibraltar","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74124,292,"GIB","Gibraltar","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74125,292,"GIB","Gibraltar","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74126,292,"GIB","Gibraltar","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74127,292,"GIB","Gibraltar","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74128,292,"GIB","Gibraltar","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74129,292,"GIB","Gibraltar","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74130,292,"GIB","Gibraltar","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74131,292,"GIB","Gibraltar","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74132,292,"GIB","Gibraltar","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74133,292,"GIB","Gibraltar","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74134,292,"GIB","Gibraltar","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74135,292,"GIB","Gibraltar","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74136,292,"GIB","Gibraltar","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74137,292,"GIB","Gibraltar","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74138,292,"GIB","Gibraltar","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74139,292,"GIB","Gibraltar","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74140,292,"GIB","Gibraltar","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74141,292,"GIB","Gibraltar","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74142,292,"GIB","Gibraltar","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74143,292,"GIB","Gibraltar","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74144,292,"GIB","Gibraltar","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74145,292,"GIB","Gibraltar","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74146,292,"GIB","Gibraltar","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74147,292,"GIB","Gibraltar","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74148,292,"GIB","Gibraltar","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74149,292,"GIB","Gibraltar","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIB/gib_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74150,296,"KIR","Kiribati","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74151,296,"KIR","Kiribati","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74152,296,"KIR","Kiribati","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74153,296,"KIR","Kiribati","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74154,296,"KIR","Kiribati","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74155,296,"KIR","Kiribati","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74156,296,"KIR","Kiribati","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74157,296,"KIR","Kiribati","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74158,296,"KIR","Kiribati","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74159,296,"KIR","Kiribati","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74160,296,"KIR","Kiribati","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74161,296,"KIR","Kiribati","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74162,296,"KIR","Kiribati","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74163,296,"KIR","Kiribati","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74164,296,"KIR","Kiribati","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74165,296,"KIR","Kiribati","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74166,296,"KIR","Kiribati","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74167,296,"KIR","Kiribati","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74168,296,"KIR","Kiribati","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74169,296,"KIR","Kiribati","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74170,296,"KIR","Kiribati","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74171,296,"KIR","Kiribati","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74172,296,"KIR","Kiribati","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74173,296,"KIR","Kiribati","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74174,296,"KIR","Kiribati","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74175,296,"KIR","Kiribati","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74176,296,"KIR","Kiribati","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74177,296,"KIR","Kiribati","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74178,296,"KIR","Kiribati","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74179,296,"KIR","Kiribati","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74180,296,"KIR","Kiribati","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74181,296,"KIR","Kiribati","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74182,296,"KIR","Kiribati","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74183,296,"KIR","Kiribati","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74184,296,"KIR","Kiribati","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74185,296,"KIR","Kiribati","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KIR/kir_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74186,300,"GRC","Greece","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74187,300,"GRC","Greece","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74188,300,"GRC","Greece","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74189,300,"GRC","Greece","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74190,300,"GRC","Greece","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74191,300,"GRC","Greece","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74192,300,"GRC","Greece","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74193,300,"GRC","Greece","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74194,300,"GRC","Greece","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74195,300,"GRC","Greece","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74196,300,"GRC","Greece","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74197,300,"GRC","Greece","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74198,300,"GRC","Greece","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74199,300,"GRC","Greece","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74200,300,"GRC","Greece","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74201,300,"GRC","Greece","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74202,300,"GRC","Greece","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74203,300,"GRC","Greece","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74204,300,"GRC","Greece","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74205,300,"GRC","Greece","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74206,300,"GRC","Greece","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74207,300,"GRC","Greece","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74208,300,"GRC","Greece","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74209,300,"GRC","Greece","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74210,300,"GRC","Greece","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74211,300,"GRC","Greece","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74212,300,"GRC","Greece","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74213,300,"GRC","Greece","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74214,300,"GRC","Greece","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74215,300,"GRC","Greece","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74216,300,"GRC","Greece","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74217,300,"GRC","Greece","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74218,300,"GRC","Greece","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74219,300,"GRC","Greece","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74220,300,"GRC","Greece","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74221,300,"GRC","Greece","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRC/grc_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74222,308,"GRD","Grenada","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74223,308,"GRD","Grenada","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74224,308,"GRD","Grenada","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74225,308,"GRD","Grenada","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74226,308,"GRD","Grenada","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74227,308,"GRD","Grenada","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74228,308,"GRD","Grenada","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74229,308,"GRD","Grenada","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74230,308,"GRD","Grenada","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74231,308,"GRD","Grenada","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74232,308,"GRD","Grenada","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74233,308,"GRD","Grenada","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74234,308,"GRD","Grenada","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74235,308,"GRD","Grenada","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74236,308,"GRD","Grenada","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74237,308,"GRD","Grenada","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74238,308,"GRD","Grenada","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74239,308,"GRD","Grenada","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74240,308,"GRD","Grenada","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74241,308,"GRD","Grenada","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74242,308,"GRD","Grenada","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74243,308,"GRD","Grenada","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74244,308,"GRD","Grenada","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74245,308,"GRD","Grenada","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74246,308,"GRD","Grenada","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74247,308,"GRD","Grenada","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74248,308,"GRD","Grenada","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74249,308,"GRD","Grenada","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74250,308,"GRD","Grenada","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74251,308,"GRD","Grenada","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74252,308,"GRD","Grenada","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74253,308,"GRD","Grenada","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74254,308,"GRD","Grenada","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74255,308,"GRD","Grenada","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74256,308,"GRD","Grenada","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74257,308,"GRD","Grenada","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GRD/grd_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74258,312,"GLP","Guadeloupe","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74259,312,"GLP","Guadeloupe","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74260,312,"GLP","Guadeloupe","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74261,312,"GLP","Guadeloupe","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74262,312,"GLP","Guadeloupe","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74263,312,"GLP","Guadeloupe","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74264,312,"GLP","Guadeloupe","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74265,312,"GLP","Guadeloupe","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74266,312,"GLP","Guadeloupe","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74267,312,"GLP","Guadeloupe","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74268,312,"GLP","Guadeloupe","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74269,312,"GLP","Guadeloupe","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74270,312,"GLP","Guadeloupe","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74271,312,"GLP","Guadeloupe","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74272,312,"GLP","Guadeloupe","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74273,312,"GLP","Guadeloupe","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74274,312,"GLP","Guadeloupe","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74275,312,"GLP","Guadeloupe","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74276,312,"GLP","Guadeloupe","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74277,312,"GLP","Guadeloupe","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74278,312,"GLP","Guadeloupe","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74279,312,"GLP","Guadeloupe","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74280,312,"GLP","Guadeloupe","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74281,312,"GLP","Guadeloupe","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74282,312,"GLP","Guadeloupe","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74283,312,"GLP","Guadeloupe","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74284,312,"GLP","Guadeloupe","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74285,312,"GLP","Guadeloupe","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74286,312,"GLP","Guadeloupe","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74287,312,"GLP","Guadeloupe","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74288,312,"GLP","Guadeloupe","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74289,312,"GLP","Guadeloupe","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74290,312,"GLP","Guadeloupe","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74291,312,"GLP","Guadeloupe","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74292,312,"GLP","Guadeloupe","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74293,312,"GLP","Guadeloupe","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GLP/glp_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74294,316,"GUM","Guam","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74295,316,"GUM","Guam","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74296,316,"GUM","Guam","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74297,316,"GUM","Guam","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74298,316,"GUM","Guam","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74299,316,"GUM","Guam","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74300,316,"GUM","Guam","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74301,316,"GUM","Guam","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74302,316,"GUM","Guam","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74303,316,"GUM","Guam","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74304,316,"GUM","Guam","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74305,316,"GUM","Guam","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74306,316,"GUM","Guam","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74307,316,"GUM","Guam","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74308,316,"GUM","Guam","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74309,316,"GUM","Guam","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74310,316,"GUM","Guam","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74311,316,"GUM","Guam","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74312,316,"GUM","Guam","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74313,316,"GUM","Guam","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74314,316,"GUM","Guam","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74315,316,"GUM","Guam","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74316,316,"GUM","Guam","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74317,316,"GUM","Guam","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74318,316,"GUM","Guam","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74319,316,"GUM","Guam","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74320,316,"GUM","Guam","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74321,316,"GUM","Guam","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74322,316,"GUM","Guam","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74323,316,"GUM","Guam","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74324,316,"GUM","Guam","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74325,316,"GUM","Guam","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74326,316,"GUM","Guam","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74327,316,"GUM","Guam","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74328,316,"GUM","Guam","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74329,316,"GUM","Guam","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUM/gum_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74330,320,"GTM","Guatemala","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74331,320,"GTM","Guatemala","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74332,320,"GTM","Guatemala","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74333,320,"GTM","Guatemala","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74334,320,"GTM","Guatemala","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74335,320,"GTM","Guatemala","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74336,320,"GTM","Guatemala","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74337,320,"GTM","Guatemala","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74338,320,"GTM","Guatemala","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74339,320,"GTM","Guatemala","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74340,320,"GTM","Guatemala","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74341,320,"GTM","Guatemala","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74342,320,"GTM","Guatemala","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74343,320,"GTM","Guatemala","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74344,320,"GTM","Guatemala","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74345,320,"GTM","Guatemala","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74346,320,"GTM","Guatemala","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74347,320,"GTM","Guatemala","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74348,320,"GTM","Guatemala","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74349,320,"GTM","Guatemala","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74350,320,"GTM","Guatemala","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74351,320,"GTM","Guatemala","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74352,320,"GTM","Guatemala","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74353,320,"GTM","Guatemala","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74354,320,"GTM","Guatemala","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74355,320,"GTM","Guatemala","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74356,320,"GTM","Guatemala","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74357,320,"GTM","Guatemala","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74358,320,"GTM","Guatemala","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74359,320,"GTM","Guatemala","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74360,320,"GTM","Guatemala","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74361,320,"GTM","Guatemala","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74362,320,"GTM","Guatemala","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74363,320,"GTM","Guatemala","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74364,320,"GTM","Guatemala","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74365,320,"GTM","Guatemala","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GTM/gtm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74366,324,"GIN","Guinea","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74367,324,"GIN","Guinea","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74368,324,"GIN","Guinea","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74369,324,"GIN","Guinea","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74370,324,"GIN","Guinea","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74371,324,"GIN","Guinea","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74372,324,"GIN","Guinea","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74373,324,"GIN","Guinea","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74374,324,"GIN","Guinea","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74375,324,"GIN","Guinea","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74376,324,"GIN","Guinea","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74377,324,"GIN","Guinea","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74378,324,"GIN","Guinea","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74379,324,"GIN","Guinea","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74380,324,"GIN","Guinea","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74381,324,"GIN","Guinea","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74382,324,"GIN","Guinea","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74383,324,"GIN","Guinea","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74384,324,"GIN","Guinea","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74385,324,"GIN","Guinea","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74386,324,"GIN","Guinea","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74387,324,"GIN","Guinea","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74388,324,"GIN","Guinea","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74389,324,"GIN","Guinea","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74390,324,"GIN","Guinea","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74391,324,"GIN","Guinea","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74392,324,"GIN","Guinea","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74393,324,"GIN","Guinea","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74394,324,"GIN","Guinea","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74395,324,"GIN","Guinea","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74396,324,"GIN","Guinea","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74397,324,"GIN","Guinea","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74398,324,"GIN","Guinea","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74399,324,"GIN","Guinea","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74400,324,"GIN","Guinea","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74401,324,"GIN","Guinea","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GIN/gin_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74402,328,"GUY","Guyana","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74403,328,"GUY","Guyana","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74404,328,"GUY","Guyana","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74405,328,"GUY","Guyana","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74406,328,"GUY","Guyana","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74407,328,"GUY","Guyana","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74408,328,"GUY","Guyana","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74409,328,"GUY","Guyana","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74410,328,"GUY","Guyana","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74411,328,"GUY","Guyana","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74412,328,"GUY","Guyana","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74413,328,"GUY","Guyana","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74414,328,"GUY","Guyana","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74415,328,"GUY","Guyana","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74416,328,"GUY","Guyana","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74417,328,"GUY","Guyana","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74418,328,"GUY","Guyana","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74419,328,"GUY","Guyana","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74420,328,"GUY","Guyana","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74421,328,"GUY","Guyana","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74422,328,"GUY","Guyana","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74423,328,"GUY","Guyana","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74424,328,"GUY","Guyana","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74425,328,"GUY","Guyana","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74426,328,"GUY","Guyana","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74427,328,"GUY","Guyana","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74428,328,"GUY","Guyana","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74429,328,"GUY","Guyana","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74430,328,"GUY","Guyana","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74431,328,"GUY","Guyana","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74432,328,"GUY","Guyana","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74433,328,"GUY","Guyana","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74434,328,"GUY","Guyana","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74435,328,"GUY","Guyana","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74436,328,"GUY","Guyana","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74437,328,"GUY","Guyana","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GUY/guy_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74438,332,"HTI","Haiti","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74439,332,"HTI","Haiti","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74440,332,"HTI","Haiti","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74441,332,"HTI","Haiti","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74442,332,"HTI","Haiti","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74443,332,"HTI","Haiti","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74444,332,"HTI","Haiti","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74445,332,"HTI","Haiti","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74446,332,"HTI","Haiti","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74447,332,"HTI","Haiti","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74448,332,"HTI","Haiti","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74449,332,"HTI","Haiti","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74450,332,"HTI","Haiti","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74451,332,"HTI","Haiti","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74452,332,"HTI","Haiti","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74453,332,"HTI","Haiti","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74454,332,"HTI","Haiti","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74455,332,"HTI","Haiti","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74456,332,"HTI","Haiti","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74457,332,"HTI","Haiti","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74458,332,"HTI","Haiti","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74459,332,"HTI","Haiti","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74460,332,"HTI","Haiti","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74461,332,"HTI","Haiti","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74462,332,"HTI","Haiti","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74463,332,"HTI","Haiti","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74464,332,"HTI","Haiti","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74465,332,"HTI","Haiti","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74466,332,"HTI","Haiti","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74467,332,"HTI","Haiti","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74468,332,"HTI","Haiti","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74469,332,"HTI","Haiti","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74470,332,"HTI","Haiti","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74471,332,"HTI","Haiti","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74472,332,"HTI","Haiti","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74473,332,"HTI","Haiti","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HTI/hti_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74474,334,"HMD","Heard Island and McDonald Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74475,334,"HMD","Heard Island and McDonald Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74476,334,"HMD","Heard Island and McDonald Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74477,334,"HMD","Heard Island and McDonald Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74478,334,"HMD","Heard Island and McDonald Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74479,334,"HMD","Heard Island and McDonald Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74480,334,"HMD","Heard Island and McDonald Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74481,334,"HMD","Heard Island and McDonald Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74482,334,"HMD","Heard Island and McDonald Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74483,334,"HMD","Heard Island and McDonald Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74484,334,"HMD","Heard Island and McDonald Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74485,334,"HMD","Heard Island and McDonald Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74486,334,"HMD","Heard Island and McDonald Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74487,334,"HMD","Heard Island and McDonald Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74488,334,"HMD","Heard Island and McDonald Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74489,334,"HMD","Heard Island and McDonald Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74490,334,"HMD","Heard Island and McDonald Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74491,334,"HMD","Heard Island and McDonald Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74492,334,"HMD","Heard Island and McDonald Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74493,334,"HMD","Heard Island and McDonald Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74494,334,"HMD","Heard Island and McDonald Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74495,334,"HMD","Heard Island and McDonald Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74496,334,"HMD","Heard Island and McDonald Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74497,334,"HMD","Heard Island and McDonald Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74498,334,"HMD","Heard Island and McDonald Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74499,334,"HMD","Heard Island and McDonald Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74500,334,"HMD","Heard Island and McDonald Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74501,334,"HMD","Heard Island and McDonald Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74502,334,"HMD","Heard Island and McDonald Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74503,334,"HMD","Heard Island and McDonald Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74504,334,"HMD","Heard Island and McDonald Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74505,334,"HMD","Heard Island and McDonald Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74506,334,"HMD","Heard Island and McDonald Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74507,334,"HMD","Heard Island and McDonald Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74508,334,"HMD","Heard Island and McDonald Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74509,334,"HMD","Heard Island and McDonald Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HMD/hmd_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74510,336,"VAT","Vatican City","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74511,336,"VAT","Vatican City","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74512,336,"VAT","Vatican City","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74513,336,"VAT","Vatican City","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74514,336,"VAT","Vatican City","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74515,336,"VAT","Vatican City","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74516,336,"VAT","Vatican City","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74517,336,"VAT","Vatican City","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74518,336,"VAT","Vatican City","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74519,336,"VAT","Vatican City","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74520,336,"VAT","Vatican City","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74521,336,"VAT","Vatican City","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74522,336,"VAT","Vatican City","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74523,336,"VAT","Vatican City","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74524,336,"VAT","Vatican City","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74525,336,"VAT","Vatican City","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74526,336,"VAT","Vatican City","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74527,336,"VAT","Vatican City","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74528,336,"VAT","Vatican City","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74529,336,"VAT","Vatican City","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74530,336,"VAT","Vatican City","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74531,336,"VAT","Vatican City","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74532,336,"VAT","Vatican City","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74533,336,"VAT","Vatican City","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74534,336,"VAT","Vatican City","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74535,336,"VAT","Vatican City","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74536,336,"VAT","Vatican City","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74537,336,"VAT","Vatican City","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74538,336,"VAT","Vatican City","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74539,336,"VAT","Vatican City","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74540,336,"VAT","Vatican City","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74541,336,"VAT","Vatican City","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74542,336,"VAT","Vatican City","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74543,336,"VAT","Vatican City","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74544,336,"VAT","Vatican City","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74545,336,"VAT","Vatican City","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VAT/vat_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74546,340,"HND","Honduras","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74547,340,"HND","Honduras","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74548,340,"HND","Honduras","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74549,340,"HND","Honduras","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74550,340,"HND","Honduras","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74551,340,"HND","Honduras","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74552,340,"HND","Honduras","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74553,340,"HND","Honduras","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74554,340,"HND","Honduras","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74555,340,"HND","Honduras","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74556,340,"HND","Honduras","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74557,340,"HND","Honduras","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74558,340,"HND","Honduras","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74559,340,"HND","Honduras","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74560,340,"HND","Honduras","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74561,340,"HND","Honduras","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74562,340,"HND","Honduras","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74563,340,"HND","Honduras","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74564,340,"HND","Honduras","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74565,340,"HND","Honduras","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74566,340,"HND","Honduras","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74567,340,"HND","Honduras","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74568,340,"HND","Honduras","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74569,340,"HND","Honduras","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74570,340,"HND","Honduras","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74571,340,"HND","Honduras","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74572,340,"HND","Honduras","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74573,340,"HND","Honduras","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74574,340,"HND","Honduras","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74575,340,"HND","Honduras","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74576,340,"HND","Honduras","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74577,340,"HND","Honduras","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74578,340,"HND","Honduras","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74579,340,"HND","Honduras","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74580,340,"HND","Honduras","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74581,340,"HND","Honduras","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HND/hnd_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74582,344,"HKG","Hong Kong","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74583,344,"HKG","Hong Kong","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74584,344,"HKG","Hong Kong","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74585,344,"HKG","Hong Kong","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74586,344,"HKG","Hong Kong","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74587,344,"HKG","Hong Kong","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74588,344,"HKG","Hong Kong","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74589,344,"HKG","Hong Kong","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74590,344,"HKG","Hong Kong","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74591,344,"HKG","Hong Kong","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74592,344,"HKG","Hong Kong","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74593,344,"HKG","Hong Kong","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74594,344,"HKG","Hong Kong","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74595,344,"HKG","Hong Kong","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74596,344,"HKG","Hong Kong","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74597,344,"HKG","Hong Kong","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74598,344,"HKG","Hong Kong","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74599,344,"HKG","Hong Kong","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74600,344,"HKG","Hong Kong","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74601,344,"HKG","Hong Kong","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74602,344,"HKG","Hong Kong","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74603,344,"HKG","Hong Kong","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74604,344,"HKG","Hong Kong","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74605,344,"HKG","Hong Kong","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74606,344,"HKG","Hong Kong","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74607,344,"HKG","Hong Kong","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74608,344,"HKG","Hong Kong","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74609,344,"HKG","Hong Kong","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74610,344,"HKG","Hong Kong","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74611,344,"HKG","Hong Kong","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74612,344,"HKG","Hong Kong","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74613,344,"HKG","Hong Kong","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74614,344,"HKG","Hong Kong","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74615,344,"HKG","Hong Kong","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74616,344,"HKG","Hong Kong","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74617,344,"HKG","Hong Kong","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HKG/hkg_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74618,348,"HUN","Hungary","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74619,348,"HUN","Hungary","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74620,348,"HUN","Hungary","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74621,348,"HUN","Hungary","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74622,348,"HUN","Hungary","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74623,348,"HUN","Hungary","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74624,348,"HUN","Hungary","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74625,348,"HUN","Hungary","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74626,348,"HUN","Hungary","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74627,348,"HUN","Hungary","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74628,348,"HUN","Hungary","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74629,348,"HUN","Hungary","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74630,348,"HUN","Hungary","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74631,348,"HUN","Hungary","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74632,348,"HUN","Hungary","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74633,348,"HUN","Hungary","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74634,348,"HUN","Hungary","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74635,348,"HUN","Hungary","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74636,348,"HUN","Hungary","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74637,348,"HUN","Hungary","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74638,348,"HUN","Hungary","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74639,348,"HUN","Hungary","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74640,348,"HUN","Hungary","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74641,348,"HUN","Hungary","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74642,348,"HUN","Hungary","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74643,348,"HUN","Hungary","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74644,348,"HUN","Hungary","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74645,348,"HUN","Hungary","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74646,348,"HUN","Hungary","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74647,348,"HUN","Hungary","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74648,348,"HUN","Hungary","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74649,348,"HUN","Hungary","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74650,348,"HUN","Hungary","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74651,348,"HUN","Hungary","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74652,348,"HUN","Hungary","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74653,348,"HUN","Hungary","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/HUN/hun_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74654,352,"ISL","Iceland","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74655,352,"ISL","Iceland","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74656,352,"ISL","Iceland","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74657,352,"ISL","Iceland","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74658,352,"ISL","Iceland","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74659,352,"ISL","Iceland","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74660,352,"ISL","Iceland","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74661,352,"ISL","Iceland","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74662,352,"ISL","Iceland","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74663,352,"ISL","Iceland","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74664,352,"ISL","Iceland","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74665,352,"ISL","Iceland","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74666,352,"ISL","Iceland","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74667,352,"ISL","Iceland","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74668,352,"ISL","Iceland","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74669,352,"ISL","Iceland","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74670,352,"ISL","Iceland","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74671,352,"ISL","Iceland","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74672,352,"ISL","Iceland","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74673,352,"ISL","Iceland","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74674,352,"ISL","Iceland","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74675,352,"ISL","Iceland","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74676,352,"ISL","Iceland","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74677,352,"ISL","Iceland","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74678,352,"ISL","Iceland","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74679,352,"ISL","Iceland","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74680,352,"ISL","Iceland","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74681,352,"ISL","Iceland","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74682,352,"ISL","Iceland","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74683,352,"ISL","Iceland","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74684,352,"ISL","Iceland","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74685,352,"ISL","Iceland","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74686,352,"ISL","Iceland","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74687,352,"ISL","Iceland","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74688,352,"ISL","Iceland","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74689,352,"ISL","Iceland","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISL/isl_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74690,356,"IND","India","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74691,356,"IND","India","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74692,356,"IND","India","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74693,356,"IND","India","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74694,356,"IND","India","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74695,356,"IND","India","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74696,356,"IND","India","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74697,356,"IND","India","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74698,356,"IND","India","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74699,356,"IND","India","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74700,356,"IND","India","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74701,356,"IND","India","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74702,356,"IND","India","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74703,356,"IND","India","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74704,356,"IND","India","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74705,356,"IND","India","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74706,356,"IND","India","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74707,356,"IND","India","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74708,356,"IND","India","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74709,356,"IND","India","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74710,356,"IND","India","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74711,356,"IND","India","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74712,356,"IND","India","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74713,356,"IND","India","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74714,356,"IND","India","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74715,356,"IND","India","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74716,356,"IND","India","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74717,356,"IND","India","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74718,356,"IND","India","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74719,356,"IND","India","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74720,356,"IND","India","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74721,356,"IND","India","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74722,356,"IND","India","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74723,356,"IND","India","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74724,356,"IND","India","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74725,356,"IND","India","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IND/ind_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74726,364,"IRN","Iran","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74727,364,"IRN","Iran","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74728,364,"IRN","Iran","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74729,364,"IRN","Iran","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74730,364,"IRN","Iran","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74731,364,"IRN","Iran","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74732,364,"IRN","Iran","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74733,364,"IRN","Iran","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74734,364,"IRN","Iran","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74735,364,"IRN","Iran","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74736,364,"IRN","Iran","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74737,364,"IRN","Iran","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74738,364,"IRN","Iran","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74739,364,"IRN","Iran","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74740,364,"IRN","Iran","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74741,364,"IRN","Iran","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74742,364,"IRN","Iran","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74743,364,"IRN","Iran","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74744,364,"IRN","Iran","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74745,364,"IRN","Iran","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74746,364,"IRN","Iran","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74747,364,"IRN","Iran","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74748,364,"IRN","Iran","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74749,364,"IRN","Iran","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74750,364,"IRN","Iran","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74751,364,"IRN","Iran","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74752,364,"IRN","Iran","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74753,364,"IRN","Iran","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74754,364,"IRN","Iran","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74755,364,"IRN","Iran","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74756,364,"IRN","Iran","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74757,364,"IRN","Iran","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74758,364,"IRN","Iran","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74759,364,"IRN","Iran","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74760,364,"IRN","Iran","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74761,364,"IRN","Iran","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRN/irn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74762,368,"IRQ","Iraq","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74763,368,"IRQ","Iraq","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74764,368,"IRQ","Iraq","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74765,368,"IRQ","Iraq","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74766,368,"IRQ","Iraq","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74767,368,"IRQ","Iraq","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74768,368,"IRQ","Iraq","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74769,368,"IRQ","Iraq","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74770,368,"IRQ","Iraq","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74771,368,"IRQ","Iraq","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74772,368,"IRQ","Iraq","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74773,368,"IRQ","Iraq","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74774,368,"IRQ","Iraq","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74775,368,"IRQ","Iraq","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74776,368,"IRQ","Iraq","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74777,368,"IRQ","Iraq","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74778,368,"IRQ","Iraq","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74779,368,"IRQ","Iraq","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74780,368,"IRQ","Iraq","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74781,368,"IRQ","Iraq","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74782,368,"IRQ","Iraq","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74783,368,"IRQ","Iraq","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74784,368,"IRQ","Iraq","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74785,368,"IRQ","Iraq","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74786,368,"IRQ","Iraq","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74787,368,"IRQ","Iraq","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74788,368,"IRQ","Iraq","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74789,368,"IRQ","Iraq","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74790,368,"IRQ","Iraq","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74791,368,"IRQ","Iraq","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74792,368,"IRQ","Iraq","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74793,368,"IRQ","Iraq","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74794,368,"IRQ","Iraq","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74795,368,"IRQ","Iraq","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74796,368,"IRQ","Iraq","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74797,368,"IRQ","Iraq","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRQ/irq_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74798,372,"IRL","Ireland","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74799,372,"IRL","Ireland","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74800,372,"IRL","Ireland","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74801,372,"IRL","Ireland","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74802,372,"IRL","Ireland","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74803,372,"IRL","Ireland","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74804,372,"IRL","Ireland","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74805,372,"IRL","Ireland","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74806,372,"IRL","Ireland","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74807,372,"IRL","Ireland","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74808,372,"IRL","Ireland","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74809,372,"IRL","Ireland","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74810,372,"IRL","Ireland","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74811,372,"IRL","Ireland","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74812,372,"IRL","Ireland","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74813,372,"IRL","Ireland","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74814,372,"IRL","Ireland","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74815,372,"IRL","Ireland","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74816,372,"IRL","Ireland","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74817,372,"IRL","Ireland","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74818,372,"IRL","Ireland","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74819,372,"IRL","Ireland","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74820,372,"IRL","Ireland","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74821,372,"IRL","Ireland","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74822,372,"IRL","Ireland","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74823,372,"IRL","Ireland","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74824,372,"IRL","Ireland","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74825,372,"IRL","Ireland","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74826,372,"IRL","Ireland","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74827,372,"IRL","Ireland","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74828,372,"IRL","Ireland","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74829,372,"IRL","Ireland","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74830,372,"IRL","Ireland","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74831,372,"IRL","Ireland","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74832,372,"IRL","Ireland","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74833,372,"IRL","Ireland","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IRL/irl_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74834,376,"ISR","Israel","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74835,376,"ISR","Israel","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74836,376,"ISR","Israel","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74837,376,"ISR","Israel","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74838,376,"ISR","Israel","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74839,376,"ISR","Israel","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74840,376,"ISR","Israel","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74841,376,"ISR","Israel","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74842,376,"ISR","Israel","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74843,376,"ISR","Israel","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74844,376,"ISR","Israel","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74845,376,"ISR","Israel","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74846,376,"ISR","Israel","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74847,376,"ISR","Israel","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74848,376,"ISR","Israel","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74849,376,"ISR","Israel","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74850,376,"ISR","Israel","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74851,376,"ISR","Israel","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74852,376,"ISR","Israel","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74853,376,"ISR","Israel","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74854,376,"ISR","Israel","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74855,376,"ISR","Israel","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74856,376,"ISR","Israel","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74857,376,"ISR","Israel","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74858,376,"ISR","Israel","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74859,376,"ISR","Israel","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74860,376,"ISR","Israel","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74861,376,"ISR","Israel","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74862,376,"ISR","Israel","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74863,376,"ISR","Israel","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74864,376,"ISR","Israel","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74865,376,"ISR","Israel","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74866,376,"ISR","Israel","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74867,376,"ISR","Israel","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74868,376,"ISR","Israel","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74869,376,"ISR","Israel","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ISR/isr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74870,380,"ITA","Italy","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74871,380,"ITA","Italy","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74872,380,"ITA","Italy","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74873,380,"ITA","Italy","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74874,380,"ITA","Italy","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74875,380,"ITA","Italy","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74876,380,"ITA","Italy","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74877,380,"ITA","Italy","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74878,380,"ITA","Italy","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74879,380,"ITA","Italy","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74880,380,"ITA","Italy","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74881,380,"ITA","Italy","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74882,380,"ITA","Italy","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74883,380,"ITA","Italy","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74884,380,"ITA","Italy","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74885,380,"ITA","Italy","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74886,380,"ITA","Italy","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74887,380,"ITA","Italy","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74888,380,"ITA","Italy","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74889,380,"ITA","Italy","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74890,380,"ITA","Italy","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74891,380,"ITA","Italy","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74892,380,"ITA","Italy","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74893,380,"ITA","Italy","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74894,380,"ITA","Italy","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74895,380,"ITA","Italy","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74896,380,"ITA","Italy","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74897,380,"ITA","Italy","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74898,380,"ITA","Italy","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74899,380,"ITA","Italy","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74900,380,"ITA","Italy","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74901,380,"ITA","Italy","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74902,380,"ITA","Italy","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74903,380,"ITA","Italy","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74904,380,"ITA","Italy","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74905,380,"ITA","Italy","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ITA/ita_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74906,384,"CIV","CIte dIvoire","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74907,384,"CIV","CIte dIvoire","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74908,384,"CIV","CIte dIvoire","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74909,384,"CIV","CIte dIvoire","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74910,384,"CIV","CIte dIvoire","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74911,384,"CIV","CIte dIvoire","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74912,384,"CIV","CIte dIvoire","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74913,384,"CIV","CIte dIvoire","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74914,384,"CIV","CIte dIvoire","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74915,384,"CIV","CIte dIvoire","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74916,384,"CIV","CIte dIvoire","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74917,384,"CIV","CIte dIvoire","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74918,384,"CIV","CIte dIvoire","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74919,384,"CIV","CIte dIvoire","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74920,384,"CIV","CIte dIvoire","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74921,384,"CIV","CIte dIvoire","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74922,384,"CIV","CIte dIvoire","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74923,384,"CIV","CIte dIvoire","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74924,384,"CIV","CIte dIvoire","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74925,384,"CIV","CIte dIvoire","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74926,384,"CIV","CIte dIvoire","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74927,384,"CIV","CIte dIvoire","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74928,384,"CIV","CIte dIvoire","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74929,384,"CIV","CIte dIvoire","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74930,384,"CIV","CIte dIvoire","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74931,384,"CIV","CIte dIvoire","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74932,384,"CIV","CIte dIvoire","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74933,384,"CIV","CIte dIvoire","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74934,384,"CIV","CIte dIvoire","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74935,384,"CIV","CIte dIvoire","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74936,384,"CIV","CIte dIvoire","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74937,384,"CIV","CIte dIvoire","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74938,384,"CIV","CIte dIvoire","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74939,384,"CIV","CIte dIvoire","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74940,384,"CIV","CIte dIvoire","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74941,384,"CIV","CIte dIvoire","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CIV/civ_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74942,388,"JAM","Jamaica","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74943,388,"JAM","Jamaica","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74944,388,"JAM","Jamaica","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74945,388,"JAM","Jamaica","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74946,388,"JAM","Jamaica","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74947,388,"JAM","Jamaica","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74948,388,"JAM","Jamaica","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74949,388,"JAM","Jamaica","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74950,388,"JAM","Jamaica","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74951,388,"JAM","Jamaica","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74952,388,"JAM","Jamaica","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74953,388,"JAM","Jamaica","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74954,388,"JAM","Jamaica","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74955,388,"JAM","Jamaica","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74956,388,"JAM","Jamaica","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74957,388,"JAM","Jamaica","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74958,388,"JAM","Jamaica","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74959,388,"JAM","Jamaica","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74960,388,"JAM","Jamaica","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74961,388,"JAM","Jamaica","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74962,388,"JAM","Jamaica","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74963,388,"JAM","Jamaica","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
74964,388,"JAM","Jamaica","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
74965,388,"JAM","Jamaica","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
74966,388,"JAM","Jamaica","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
74967,388,"JAM","Jamaica","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
74968,388,"JAM","Jamaica","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
74969,388,"JAM","Jamaica","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
74970,388,"JAM","Jamaica","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
74971,388,"JAM","Jamaica","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
74972,388,"JAM","Jamaica","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
74973,388,"JAM","Jamaica","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
74974,388,"JAM","Jamaica","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
74975,388,"JAM","Jamaica","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
74976,388,"JAM","Jamaica","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
74977,388,"JAM","Jamaica","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JAM/jam_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
74978,392,"JPN","Japan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
74979,392,"JPN","Japan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
74980,392,"JPN","Japan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
74981,392,"JPN","Japan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
74982,392,"JPN","Japan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
74983,392,"JPN","Japan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
74984,392,"JPN","Japan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
74985,392,"JPN","Japan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
74986,392,"JPN","Japan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
74987,392,"JPN","Japan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
74988,392,"JPN","Japan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
74989,392,"JPN","Japan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
74990,392,"JPN","Japan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
74991,392,"JPN","Japan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
74992,392,"JPN","Japan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
74993,392,"JPN","Japan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
74994,392,"JPN","Japan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
74995,392,"JPN","Japan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
74996,392,"JPN","Japan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
74997,392,"JPN","Japan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
74998,392,"JPN","Japan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
74999,392,"JPN","Japan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75000,392,"JPN","Japan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75001,392,"JPN","Japan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75002,392,"JPN","Japan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75003,392,"JPN","Japan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75004,392,"JPN","Japan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75005,392,"JPN","Japan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75006,392,"JPN","Japan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75007,392,"JPN","Japan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75008,392,"JPN","Japan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75009,392,"JPN","Japan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75010,392,"JPN","Japan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75011,392,"JPN","Japan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75012,392,"JPN","Japan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75013,392,"JPN","Japan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JPN/jpn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75014,398,"KAZ","Kazakhstan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75015,398,"KAZ","Kazakhstan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75016,398,"KAZ","Kazakhstan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75017,398,"KAZ","Kazakhstan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75018,398,"KAZ","Kazakhstan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75019,398,"KAZ","Kazakhstan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75020,398,"KAZ","Kazakhstan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75021,398,"KAZ","Kazakhstan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75022,398,"KAZ","Kazakhstan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75023,398,"KAZ","Kazakhstan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75024,398,"KAZ","Kazakhstan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75025,398,"KAZ","Kazakhstan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75026,398,"KAZ","Kazakhstan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75027,398,"KAZ","Kazakhstan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75028,398,"KAZ","Kazakhstan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75029,398,"KAZ","Kazakhstan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75030,398,"KAZ","Kazakhstan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75031,398,"KAZ","Kazakhstan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75032,398,"KAZ","Kazakhstan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75033,398,"KAZ","Kazakhstan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75034,398,"KAZ","Kazakhstan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75035,398,"KAZ","Kazakhstan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75036,398,"KAZ","Kazakhstan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75037,398,"KAZ","Kazakhstan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75038,398,"KAZ","Kazakhstan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75039,398,"KAZ","Kazakhstan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75040,398,"KAZ","Kazakhstan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75041,398,"KAZ","Kazakhstan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75042,398,"KAZ","Kazakhstan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75043,398,"KAZ","Kazakhstan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75044,398,"KAZ","Kazakhstan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75045,398,"KAZ","Kazakhstan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75046,398,"KAZ","Kazakhstan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75047,398,"KAZ","Kazakhstan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75048,398,"KAZ","Kazakhstan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75049,398,"KAZ","Kazakhstan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KAZ/kaz_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75050,400,"JOR","Jordan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75051,400,"JOR","Jordan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75052,400,"JOR","Jordan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75053,400,"JOR","Jordan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75054,400,"JOR","Jordan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75055,400,"JOR","Jordan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75056,400,"JOR","Jordan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75057,400,"JOR","Jordan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75058,400,"JOR","Jordan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75059,400,"JOR","Jordan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75060,400,"JOR","Jordan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75061,400,"JOR","Jordan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75062,400,"JOR","Jordan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75063,400,"JOR","Jordan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75064,400,"JOR","Jordan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75065,400,"JOR","Jordan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75066,400,"JOR","Jordan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75067,400,"JOR","Jordan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75068,400,"JOR","Jordan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75069,400,"JOR","Jordan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75070,400,"JOR","Jordan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75071,400,"JOR","Jordan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75072,400,"JOR","Jordan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75073,400,"JOR","Jordan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75074,400,"JOR","Jordan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75075,400,"JOR","Jordan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75076,400,"JOR","Jordan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75077,400,"JOR","Jordan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75078,400,"JOR","Jordan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75079,400,"JOR","Jordan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75080,400,"JOR","Jordan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75081,400,"JOR","Jordan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75082,400,"JOR","Jordan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75083,400,"JOR","Jordan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75084,400,"JOR","Jordan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75085,400,"JOR","Jordan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JOR/jor_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75086,404,"KEN","Kenya","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75087,404,"KEN","Kenya","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75088,404,"KEN","Kenya","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75089,404,"KEN","Kenya","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75090,404,"KEN","Kenya","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75091,404,"KEN","Kenya","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75092,404,"KEN","Kenya","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75093,404,"KEN","Kenya","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75094,404,"KEN","Kenya","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75095,404,"KEN","Kenya","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75096,404,"KEN","Kenya","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75097,404,"KEN","Kenya","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75098,404,"KEN","Kenya","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75099,404,"KEN","Kenya","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75100,404,"KEN","Kenya","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75101,404,"KEN","Kenya","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75102,404,"KEN","Kenya","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75103,404,"KEN","Kenya","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75104,404,"KEN","Kenya","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75105,404,"KEN","Kenya","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75106,404,"KEN","Kenya","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75107,404,"KEN","Kenya","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75108,404,"KEN","Kenya","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75109,404,"KEN","Kenya","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75110,404,"KEN","Kenya","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75111,404,"KEN","Kenya","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75112,404,"KEN","Kenya","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75113,404,"KEN","Kenya","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75114,404,"KEN","Kenya","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75115,404,"KEN","Kenya","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75116,404,"KEN","Kenya","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75117,404,"KEN","Kenya","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75118,404,"KEN","Kenya","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75119,404,"KEN","Kenya","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75120,404,"KEN","Kenya","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75121,404,"KEN","Kenya","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KEN/ken_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75122,408,"PRK","North Korea","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75123,408,"PRK","North Korea","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75124,408,"PRK","North Korea","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75125,408,"PRK","North Korea","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75126,408,"PRK","North Korea","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75127,408,"PRK","North Korea","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75128,408,"PRK","North Korea","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75129,408,"PRK","North Korea","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75130,408,"PRK","North Korea","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75131,408,"PRK","North Korea","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75132,408,"PRK","North Korea","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75133,408,"PRK","North Korea","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75134,408,"PRK","North Korea","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75135,408,"PRK","North Korea","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75136,408,"PRK","North Korea","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75137,408,"PRK","North Korea","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75138,408,"PRK","North Korea","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75139,408,"PRK","North Korea","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75140,408,"PRK","North Korea","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75141,408,"PRK","North Korea","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75142,408,"PRK","North Korea","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75143,408,"PRK","North Korea","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75144,408,"PRK","North Korea","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75145,408,"PRK","North Korea","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75146,408,"PRK","North Korea","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75147,408,"PRK","North Korea","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75148,408,"PRK","North Korea","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75149,408,"PRK","North Korea","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75150,408,"PRK","North Korea","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75151,408,"PRK","North Korea","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75152,408,"PRK","North Korea","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75153,408,"PRK","North Korea","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75154,408,"PRK","North Korea","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75155,408,"PRK","North Korea","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75156,408,"PRK","North Korea","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75157,408,"PRK","North Korea","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRK/prk_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75158,410,"KOR","South Korea","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75159,410,"KOR","South Korea","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75160,410,"KOR","South Korea","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75161,410,"KOR","South Korea","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75162,410,"KOR","South Korea","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75163,410,"KOR","South Korea","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75164,410,"KOR","South Korea","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75165,410,"KOR","South Korea","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75166,410,"KOR","South Korea","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75167,410,"KOR","South Korea","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75168,410,"KOR","South Korea","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75169,410,"KOR","South Korea","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75170,410,"KOR","South Korea","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75171,410,"KOR","South Korea","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75172,410,"KOR","South Korea","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75173,410,"KOR","South Korea","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75174,410,"KOR","South Korea","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75175,410,"KOR","South Korea","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75176,410,"KOR","South Korea","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75177,410,"KOR","South Korea","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75178,410,"KOR","South Korea","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75179,410,"KOR","South Korea","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75180,410,"KOR","South Korea","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75181,410,"KOR","South Korea","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75182,410,"KOR","South Korea","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75183,410,"KOR","South Korea","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75184,410,"KOR","South Korea","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75185,410,"KOR","South Korea","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75186,410,"KOR","South Korea","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75187,410,"KOR","South Korea","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75188,410,"KOR","South Korea","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75189,410,"KOR","South Korea","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75190,410,"KOR","South Korea","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75191,410,"KOR","South Korea","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75192,410,"KOR","South Korea","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75193,410,"KOR","South Korea","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOR/kor_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75194,414,"KWT","Kuwait","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75195,414,"KWT","Kuwait","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75196,414,"KWT","Kuwait","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75197,414,"KWT","Kuwait","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75198,414,"KWT","Kuwait","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75199,414,"KWT","Kuwait","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75200,414,"KWT","Kuwait","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75201,414,"KWT","Kuwait","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75202,414,"KWT","Kuwait","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75203,414,"KWT","Kuwait","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75204,414,"KWT","Kuwait","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75205,414,"KWT","Kuwait","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75206,414,"KWT","Kuwait","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75207,414,"KWT","Kuwait","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75208,414,"KWT","Kuwait","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75209,414,"KWT","Kuwait","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75210,414,"KWT","Kuwait","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75211,414,"KWT","Kuwait","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75212,414,"KWT","Kuwait","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75213,414,"KWT","Kuwait","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75214,414,"KWT","Kuwait","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75215,414,"KWT","Kuwait","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75216,414,"KWT","Kuwait","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75217,414,"KWT","Kuwait","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75218,414,"KWT","Kuwait","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75219,414,"KWT","Kuwait","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75220,414,"KWT","Kuwait","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75221,414,"KWT","Kuwait","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75222,414,"KWT","Kuwait","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75223,414,"KWT","Kuwait","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75224,414,"KWT","Kuwait","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75225,414,"KWT","Kuwait","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75226,414,"KWT","Kuwait","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75227,414,"KWT","Kuwait","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75228,414,"KWT","Kuwait","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75229,414,"KWT","Kuwait","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KWT/kwt_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75230,417,"KGZ","Kyrgyzstan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75231,417,"KGZ","Kyrgyzstan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75232,417,"KGZ","Kyrgyzstan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75233,417,"KGZ","Kyrgyzstan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75234,417,"KGZ","Kyrgyzstan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75235,417,"KGZ","Kyrgyzstan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75236,417,"KGZ","Kyrgyzstan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75237,417,"KGZ","Kyrgyzstan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75238,417,"KGZ","Kyrgyzstan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75239,417,"KGZ","Kyrgyzstan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75240,417,"KGZ","Kyrgyzstan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75241,417,"KGZ","Kyrgyzstan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75242,417,"KGZ","Kyrgyzstan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75243,417,"KGZ","Kyrgyzstan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75244,417,"KGZ","Kyrgyzstan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75245,417,"KGZ","Kyrgyzstan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75246,417,"KGZ","Kyrgyzstan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75247,417,"KGZ","Kyrgyzstan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75248,417,"KGZ","Kyrgyzstan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75249,417,"KGZ","Kyrgyzstan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75250,417,"KGZ","Kyrgyzstan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75251,417,"KGZ","Kyrgyzstan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75252,417,"KGZ","Kyrgyzstan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75253,417,"KGZ","Kyrgyzstan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75254,417,"KGZ","Kyrgyzstan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75255,417,"KGZ","Kyrgyzstan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75256,417,"KGZ","Kyrgyzstan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75257,417,"KGZ","Kyrgyzstan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75258,417,"KGZ","Kyrgyzstan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75259,417,"KGZ","Kyrgyzstan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75260,417,"KGZ","Kyrgyzstan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75261,417,"KGZ","Kyrgyzstan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75262,417,"KGZ","Kyrgyzstan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75263,417,"KGZ","Kyrgyzstan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75264,417,"KGZ","Kyrgyzstan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75265,417,"KGZ","Kyrgyzstan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KGZ/kgz_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75266,418,"LAO","Laos","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75267,418,"LAO","Laos","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75268,418,"LAO","Laos","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75269,418,"LAO","Laos","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75270,418,"LAO","Laos","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75271,418,"LAO","Laos","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75272,418,"LAO","Laos","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75273,418,"LAO","Laos","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75274,418,"LAO","Laos","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75275,418,"LAO","Laos","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75276,418,"LAO","Laos","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75277,418,"LAO","Laos","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75278,418,"LAO","Laos","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75279,418,"LAO","Laos","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75280,418,"LAO","Laos","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75281,418,"LAO","Laos","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75282,418,"LAO","Laos","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75283,418,"LAO","Laos","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75284,418,"LAO","Laos","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75285,418,"LAO","Laos","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75286,418,"LAO","Laos","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75287,418,"LAO","Laos","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75288,418,"LAO","Laos","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75289,418,"LAO","Laos","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75290,418,"LAO","Laos","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75291,418,"LAO","Laos","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75292,418,"LAO","Laos","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75293,418,"LAO","Laos","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75294,418,"LAO","Laos","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75295,418,"LAO","Laos","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75296,418,"LAO","Laos","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75297,418,"LAO","Laos","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75298,418,"LAO","Laos","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75299,418,"LAO","Laos","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75300,418,"LAO","Laos","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75301,418,"LAO","Laos","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LAO/lao_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75302,422,"LBN","Lebanon","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75303,422,"LBN","Lebanon","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75304,422,"LBN","Lebanon","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75305,422,"LBN","Lebanon","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75306,422,"LBN","Lebanon","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75307,422,"LBN","Lebanon","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75308,422,"LBN","Lebanon","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75309,422,"LBN","Lebanon","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75310,422,"LBN","Lebanon","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75311,422,"LBN","Lebanon","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75312,422,"LBN","Lebanon","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75313,422,"LBN","Lebanon","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75314,422,"LBN","Lebanon","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75315,422,"LBN","Lebanon","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75316,422,"LBN","Lebanon","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75317,422,"LBN","Lebanon","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75318,422,"LBN","Lebanon","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75319,422,"LBN","Lebanon","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75320,422,"LBN","Lebanon","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75321,422,"LBN","Lebanon","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75322,422,"LBN","Lebanon","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75323,422,"LBN","Lebanon","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75324,422,"LBN","Lebanon","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75325,422,"LBN","Lebanon","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75326,422,"LBN","Lebanon","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75327,422,"LBN","Lebanon","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75328,422,"LBN","Lebanon","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75329,422,"LBN","Lebanon","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75330,422,"LBN","Lebanon","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75331,422,"LBN","Lebanon","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75332,422,"LBN","Lebanon","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75333,422,"LBN","Lebanon","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75334,422,"LBN","Lebanon","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75335,422,"LBN","Lebanon","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75336,422,"LBN","Lebanon","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75337,422,"LBN","Lebanon","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBN/lbn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75338,426,"LSO","Lesotho","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75339,426,"LSO","Lesotho","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75340,426,"LSO","Lesotho","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75341,426,"LSO","Lesotho","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75342,426,"LSO","Lesotho","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75343,426,"LSO","Lesotho","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75344,426,"LSO","Lesotho","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75345,426,"LSO","Lesotho","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75346,426,"LSO","Lesotho","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75347,426,"LSO","Lesotho","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75348,426,"LSO","Lesotho","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75349,426,"LSO","Lesotho","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75350,426,"LSO","Lesotho","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75351,426,"LSO","Lesotho","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75352,426,"LSO","Lesotho","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75353,426,"LSO","Lesotho","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75354,426,"LSO","Lesotho","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75355,426,"LSO","Lesotho","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75356,426,"LSO","Lesotho","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75357,426,"LSO","Lesotho","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75358,426,"LSO","Lesotho","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75359,426,"LSO","Lesotho","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75360,426,"LSO","Lesotho","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75361,426,"LSO","Lesotho","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75362,426,"LSO","Lesotho","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75363,426,"LSO","Lesotho","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75364,426,"LSO","Lesotho","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75365,426,"LSO","Lesotho","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75366,426,"LSO","Lesotho","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75367,426,"LSO","Lesotho","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75368,426,"LSO","Lesotho","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75369,426,"LSO","Lesotho","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75370,426,"LSO","Lesotho","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75371,426,"LSO","Lesotho","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75372,426,"LSO","Lesotho","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75373,426,"LSO","Lesotho","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LSO/lso_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75374,428,"LVA","Latvia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75375,428,"LVA","Latvia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75376,428,"LVA","Latvia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75377,428,"LVA","Latvia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75378,428,"LVA","Latvia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75379,428,"LVA","Latvia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75380,428,"LVA","Latvia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75381,428,"LVA","Latvia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75382,428,"LVA","Latvia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75383,428,"LVA","Latvia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75384,428,"LVA","Latvia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75385,428,"LVA","Latvia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75386,428,"LVA","Latvia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75387,428,"LVA","Latvia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75388,428,"LVA","Latvia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75389,428,"LVA","Latvia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75390,428,"LVA","Latvia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75391,428,"LVA","Latvia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75392,428,"LVA","Latvia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75393,428,"LVA","Latvia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75394,428,"LVA","Latvia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75395,428,"LVA","Latvia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75396,428,"LVA","Latvia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75397,428,"LVA","Latvia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75398,428,"LVA","Latvia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75399,428,"LVA","Latvia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75400,428,"LVA","Latvia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75401,428,"LVA","Latvia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75402,428,"LVA","Latvia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75403,428,"LVA","Latvia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75404,428,"LVA","Latvia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75405,428,"LVA","Latvia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75406,428,"LVA","Latvia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75407,428,"LVA","Latvia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75408,428,"LVA","Latvia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75409,428,"LVA","Latvia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LVA/lva_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75410,430,"LBR","Liberia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75411,430,"LBR","Liberia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75412,430,"LBR","Liberia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75413,430,"LBR","Liberia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75414,430,"LBR","Liberia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75415,430,"LBR","Liberia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75416,430,"LBR","Liberia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75417,430,"LBR","Liberia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75418,430,"LBR","Liberia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75419,430,"LBR","Liberia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75420,430,"LBR","Liberia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75421,430,"LBR","Liberia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75422,430,"LBR","Liberia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75423,430,"LBR","Liberia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75424,430,"LBR","Liberia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75425,430,"LBR","Liberia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75426,430,"LBR","Liberia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75427,430,"LBR","Liberia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75428,430,"LBR","Liberia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75429,430,"LBR","Liberia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75430,430,"LBR","Liberia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75431,430,"LBR","Liberia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75432,430,"LBR","Liberia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75433,430,"LBR","Liberia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75434,430,"LBR","Liberia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75435,430,"LBR","Liberia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75436,430,"LBR","Liberia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75437,430,"LBR","Liberia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75438,430,"LBR","Liberia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75439,430,"LBR","Liberia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75440,430,"LBR","Liberia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75441,430,"LBR","Liberia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75442,430,"LBR","Liberia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75443,430,"LBR","Liberia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75444,430,"LBR","Liberia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75445,430,"LBR","Liberia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBR/lbr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75446,434,"LBY","Libya","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75447,434,"LBY","Libya","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75448,434,"LBY","Libya","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75449,434,"LBY","Libya","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75450,434,"LBY","Libya","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75451,434,"LBY","Libya","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75452,434,"LBY","Libya","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75453,434,"LBY","Libya","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75454,434,"LBY","Libya","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75455,434,"LBY","Libya","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75456,434,"LBY","Libya","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75457,434,"LBY","Libya","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75458,434,"LBY","Libya","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75459,434,"LBY","Libya","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75460,434,"LBY","Libya","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75461,434,"LBY","Libya","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75462,434,"LBY","Libya","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75463,434,"LBY","Libya","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75464,434,"LBY","Libya","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75465,434,"LBY","Libya","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75466,434,"LBY","Libya","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75467,434,"LBY","Libya","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75468,434,"LBY","Libya","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75469,434,"LBY","Libya","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75470,434,"LBY","Libya","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75471,434,"LBY","Libya","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75472,434,"LBY","Libya","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75473,434,"LBY","Libya","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75474,434,"LBY","Libya","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75475,434,"LBY","Libya","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75476,434,"LBY","Libya","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75477,434,"LBY","Libya","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75478,434,"LBY","Libya","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75479,434,"LBY","Libya","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75480,434,"LBY","Libya","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75481,434,"LBY","Libya","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LBY/lby_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75482,438,"LIE","Liechtenstein","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75483,438,"LIE","Liechtenstein","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75484,438,"LIE","Liechtenstein","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75485,438,"LIE","Liechtenstein","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75486,438,"LIE","Liechtenstein","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75487,438,"LIE","Liechtenstein","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75488,438,"LIE","Liechtenstein","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75489,438,"LIE","Liechtenstein","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75490,438,"LIE","Liechtenstein","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75491,438,"LIE","Liechtenstein","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75492,438,"LIE","Liechtenstein","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75493,438,"LIE","Liechtenstein","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75494,438,"LIE","Liechtenstein","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75495,438,"LIE","Liechtenstein","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75496,438,"LIE","Liechtenstein","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75497,438,"LIE","Liechtenstein","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75498,438,"LIE","Liechtenstein","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75499,438,"LIE","Liechtenstein","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75500,438,"LIE","Liechtenstein","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75501,438,"LIE","Liechtenstein","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75502,438,"LIE","Liechtenstein","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75503,438,"LIE","Liechtenstein","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75504,438,"LIE","Liechtenstein","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75505,438,"LIE","Liechtenstein","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75506,438,"LIE","Liechtenstein","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75507,438,"LIE","Liechtenstein","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75508,438,"LIE","Liechtenstein","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75509,438,"LIE","Liechtenstein","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75510,438,"LIE","Liechtenstein","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75511,438,"LIE","Liechtenstein","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75512,438,"LIE","Liechtenstein","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75513,438,"LIE","Liechtenstein","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75514,438,"LIE","Liechtenstein","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75515,438,"LIE","Liechtenstein","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75516,438,"LIE","Liechtenstein","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75517,438,"LIE","Liechtenstein","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LIE/lie_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75518,440,"LTU","Lithuania","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75519,440,"LTU","Lithuania","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75520,440,"LTU","Lithuania","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75521,440,"LTU","Lithuania","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75522,440,"LTU","Lithuania","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75523,440,"LTU","Lithuania","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75524,440,"LTU","Lithuania","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75525,440,"LTU","Lithuania","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75526,440,"LTU","Lithuania","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75527,440,"LTU","Lithuania","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75528,440,"LTU","Lithuania","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75529,440,"LTU","Lithuania","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75530,440,"LTU","Lithuania","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75531,440,"LTU","Lithuania","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75532,440,"LTU","Lithuania","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75533,440,"LTU","Lithuania","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75534,440,"LTU","Lithuania","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75535,440,"LTU","Lithuania","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75536,440,"LTU","Lithuania","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75537,440,"LTU","Lithuania","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75538,440,"LTU","Lithuania","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75539,440,"LTU","Lithuania","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75540,440,"LTU","Lithuania","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75541,440,"LTU","Lithuania","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75542,440,"LTU","Lithuania","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75543,440,"LTU","Lithuania","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75544,440,"LTU","Lithuania","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75545,440,"LTU","Lithuania","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75546,440,"LTU","Lithuania","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75547,440,"LTU","Lithuania","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75548,440,"LTU","Lithuania","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75549,440,"LTU","Lithuania","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75550,440,"LTU","Lithuania","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75551,440,"LTU","Lithuania","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75552,440,"LTU","Lithuania","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75553,440,"LTU","Lithuania","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LTU/ltu_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75554,442,"LUX","Luxembourg","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75555,442,"LUX","Luxembourg","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75556,442,"LUX","Luxembourg","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75557,442,"LUX","Luxembourg","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75558,442,"LUX","Luxembourg","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75559,442,"LUX","Luxembourg","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75560,442,"LUX","Luxembourg","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75561,442,"LUX","Luxembourg","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75562,442,"LUX","Luxembourg","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75563,442,"LUX","Luxembourg","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75564,442,"LUX","Luxembourg","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75565,442,"LUX","Luxembourg","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75566,442,"LUX","Luxembourg","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75567,442,"LUX","Luxembourg","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75568,442,"LUX","Luxembourg","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75569,442,"LUX","Luxembourg","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75570,442,"LUX","Luxembourg","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75571,442,"LUX","Luxembourg","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75572,442,"LUX","Luxembourg","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75573,442,"LUX","Luxembourg","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75574,442,"LUX","Luxembourg","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75575,442,"LUX","Luxembourg","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75576,442,"LUX","Luxembourg","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75577,442,"LUX","Luxembourg","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75578,442,"LUX","Luxembourg","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75579,442,"LUX","Luxembourg","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75580,442,"LUX","Luxembourg","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75581,442,"LUX","Luxembourg","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75582,442,"LUX","Luxembourg","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75583,442,"LUX","Luxembourg","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75584,442,"LUX","Luxembourg","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75585,442,"LUX","Luxembourg","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75586,442,"LUX","Luxembourg","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75587,442,"LUX","Luxembourg","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75588,442,"LUX","Luxembourg","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75589,442,"LUX","Luxembourg","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LUX/lux_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75590,446,"MAC","Macao","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75591,446,"MAC","Macao","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75592,446,"MAC","Macao","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75593,446,"MAC","Macao","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75594,446,"MAC","Macao","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75595,446,"MAC","Macao","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75596,446,"MAC","Macao","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75597,446,"MAC","Macao","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75598,446,"MAC","Macao","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75599,446,"MAC","Macao","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75600,446,"MAC","Macao","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75601,446,"MAC","Macao","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75602,446,"MAC","Macao","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75603,446,"MAC","Macao","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75604,446,"MAC","Macao","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75605,446,"MAC","Macao","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75606,446,"MAC","Macao","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75607,446,"MAC","Macao","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75608,446,"MAC","Macao","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75609,446,"MAC","Macao","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75610,446,"MAC","Macao","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75611,446,"MAC","Macao","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75612,446,"MAC","Macao","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75613,446,"MAC","Macao","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75614,446,"MAC","Macao","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75615,446,"MAC","Macao","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75616,446,"MAC","Macao","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75617,446,"MAC","Macao","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75618,446,"MAC","Macao","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75619,446,"MAC","Macao","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75620,446,"MAC","Macao","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75621,446,"MAC","Macao","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75622,446,"MAC","Macao","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75623,446,"MAC","Macao","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75624,446,"MAC","Macao","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75625,446,"MAC","Macao","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAC/mac_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75626,450,"MDG","Madagascar","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75627,450,"MDG","Madagascar","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75628,450,"MDG","Madagascar","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75629,450,"MDG","Madagascar","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75630,450,"MDG","Madagascar","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75631,450,"MDG","Madagascar","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75632,450,"MDG","Madagascar","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75633,450,"MDG","Madagascar","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75634,450,"MDG","Madagascar","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75635,450,"MDG","Madagascar","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75636,450,"MDG","Madagascar","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75637,450,"MDG","Madagascar","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75638,450,"MDG","Madagascar","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75639,450,"MDG","Madagascar","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75640,450,"MDG","Madagascar","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75641,450,"MDG","Madagascar","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75642,450,"MDG","Madagascar","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75643,450,"MDG","Madagascar","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75644,450,"MDG","Madagascar","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75645,450,"MDG","Madagascar","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75646,450,"MDG","Madagascar","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75647,450,"MDG","Madagascar","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75648,450,"MDG","Madagascar","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75649,450,"MDG","Madagascar","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75650,450,"MDG","Madagascar","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75651,450,"MDG","Madagascar","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75652,450,"MDG","Madagascar","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75653,450,"MDG","Madagascar","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75654,450,"MDG","Madagascar","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75655,450,"MDG","Madagascar","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75656,450,"MDG","Madagascar","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75657,450,"MDG","Madagascar","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75658,450,"MDG","Madagascar","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75659,450,"MDG","Madagascar","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75660,450,"MDG","Madagascar","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75661,450,"MDG","Madagascar","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDG/mdg_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75662,454,"MWI","Malawi","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75663,454,"MWI","Malawi","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75664,454,"MWI","Malawi","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75665,454,"MWI","Malawi","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75666,454,"MWI","Malawi","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75667,454,"MWI","Malawi","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75668,454,"MWI","Malawi","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75669,454,"MWI","Malawi","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75670,454,"MWI","Malawi","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75671,454,"MWI","Malawi","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75672,454,"MWI","Malawi","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75673,454,"MWI","Malawi","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75674,454,"MWI","Malawi","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75675,454,"MWI","Malawi","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75676,454,"MWI","Malawi","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75677,454,"MWI","Malawi","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75678,454,"MWI","Malawi","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75679,454,"MWI","Malawi","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75680,454,"MWI","Malawi","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75681,454,"MWI","Malawi","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75682,454,"MWI","Malawi","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75683,454,"MWI","Malawi","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75684,454,"MWI","Malawi","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75685,454,"MWI","Malawi","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75686,454,"MWI","Malawi","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75687,454,"MWI","Malawi","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75688,454,"MWI","Malawi","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75689,454,"MWI","Malawi","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75690,454,"MWI","Malawi","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75691,454,"MWI","Malawi","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75692,454,"MWI","Malawi","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75693,454,"MWI","Malawi","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75694,454,"MWI","Malawi","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75695,454,"MWI","Malawi","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75696,454,"MWI","Malawi","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75697,454,"MWI","Malawi","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MWI/mwi_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75698,458,"MYS","Malaysia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75699,458,"MYS","Malaysia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75700,458,"MYS","Malaysia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75701,458,"MYS","Malaysia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75702,458,"MYS","Malaysia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75703,458,"MYS","Malaysia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75704,458,"MYS","Malaysia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75705,458,"MYS","Malaysia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75706,458,"MYS","Malaysia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75707,458,"MYS","Malaysia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75708,458,"MYS","Malaysia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75709,458,"MYS","Malaysia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75710,458,"MYS","Malaysia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75711,458,"MYS","Malaysia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75712,458,"MYS","Malaysia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75713,458,"MYS","Malaysia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75714,458,"MYS","Malaysia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75715,458,"MYS","Malaysia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75716,458,"MYS","Malaysia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75717,458,"MYS","Malaysia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75718,458,"MYS","Malaysia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75719,458,"MYS","Malaysia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75720,458,"MYS","Malaysia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75721,458,"MYS","Malaysia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75722,458,"MYS","Malaysia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75723,458,"MYS","Malaysia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75724,458,"MYS","Malaysia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75725,458,"MYS","Malaysia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75726,458,"MYS","Malaysia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75727,458,"MYS","Malaysia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75728,458,"MYS","Malaysia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75729,458,"MYS","Malaysia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75730,458,"MYS","Malaysia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75731,458,"MYS","Malaysia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75732,458,"MYS","Malaysia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75733,458,"MYS","Malaysia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MYS/mys_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75734,462,"MDV","Maldives","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75735,462,"MDV","Maldives","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75736,462,"MDV","Maldives","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75737,462,"MDV","Maldives","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75738,462,"MDV","Maldives","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75739,462,"MDV","Maldives","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75740,462,"MDV","Maldives","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75741,462,"MDV","Maldives","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75742,462,"MDV","Maldives","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75743,462,"MDV","Maldives","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75744,462,"MDV","Maldives","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75745,462,"MDV","Maldives","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75746,462,"MDV","Maldives","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75747,462,"MDV","Maldives","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75748,462,"MDV","Maldives","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75749,462,"MDV","Maldives","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75750,462,"MDV","Maldives","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75751,462,"MDV","Maldives","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75752,462,"MDV","Maldives","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75753,462,"MDV","Maldives","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75754,462,"MDV","Maldives","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75755,462,"MDV","Maldives","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75756,462,"MDV","Maldives","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75757,462,"MDV","Maldives","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75758,462,"MDV","Maldives","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75759,462,"MDV","Maldives","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75760,462,"MDV","Maldives","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75761,462,"MDV","Maldives","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75762,462,"MDV","Maldives","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75763,462,"MDV","Maldives","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75764,462,"MDV","Maldives","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75765,462,"MDV","Maldives","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75766,462,"MDV","Maldives","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75767,462,"MDV","Maldives","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75768,462,"MDV","Maldives","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75769,462,"MDV","Maldives","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDV/mdv_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75770,466,"MLI","Mali","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75771,466,"MLI","Mali","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75772,466,"MLI","Mali","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75773,466,"MLI","Mali","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75774,466,"MLI","Mali","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75775,466,"MLI","Mali","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75776,466,"MLI","Mali","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75777,466,"MLI","Mali","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75778,466,"MLI","Mali","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75779,466,"MLI","Mali","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75780,466,"MLI","Mali","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75781,466,"MLI","Mali","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75782,466,"MLI","Mali","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75783,466,"MLI","Mali","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75784,466,"MLI","Mali","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75785,466,"MLI","Mali","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75786,466,"MLI","Mali","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75787,466,"MLI","Mali","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75788,466,"MLI","Mali","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75789,466,"MLI","Mali","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75790,466,"MLI","Mali","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75791,466,"MLI","Mali","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75792,466,"MLI","Mali","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75793,466,"MLI","Mali","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75794,466,"MLI","Mali","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75795,466,"MLI","Mali","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75796,466,"MLI","Mali","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75797,466,"MLI","Mali","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75798,466,"MLI","Mali","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75799,466,"MLI","Mali","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75800,466,"MLI","Mali","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75801,466,"MLI","Mali","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75802,466,"MLI","Mali","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75803,466,"MLI","Mali","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75804,466,"MLI","Mali","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75805,466,"MLI","Mali","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLI/mli_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75806,470,"MLT","Malta","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75807,470,"MLT","Malta","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75808,470,"MLT","Malta","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75809,470,"MLT","Malta","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75810,470,"MLT","Malta","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75811,470,"MLT","Malta","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75812,470,"MLT","Malta","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75813,470,"MLT","Malta","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75814,470,"MLT","Malta","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75815,470,"MLT","Malta","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75816,470,"MLT","Malta","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75817,470,"MLT","Malta","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75818,470,"MLT","Malta","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75819,470,"MLT","Malta","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75820,470,"MLT","Malta","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75821,470,"MLT","Malta","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75822,470,"MLT","Malta","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75823,470,"MLT","Malta","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75824,470,"MLT","Malta","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75825,470,"MLT","Malta","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75826,470,"MLT","Malta","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75827,470,"MLT","Malta","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75828,470,"MLT","Malta","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75829,470,"MLT","Malta","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75830,470,"MLT","Malta","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75831,470,"MLT","Malta","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75832,470,"MLT","Malta","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75833,470,"MLT","Malta","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75834,470,"MLT","Malta","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75835,470,"MLT","Malta","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75836,470,"MLT","Malta","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75837,470,"MLT","Malta","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75838,470,"MLT","Malta","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75839,470,"MLT","Malta","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75840,470,"MLT","Malta","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75841,470,"MLT","Malta","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MLT/mlt_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75842,474,"MTQ","Martinique","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75843,474,"MTQ","Martinique","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75844,474,"MTQ","Martinique","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75845,474,"MTQ","Martinique","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75846,474,"MTQ","Martinique","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75847,474,"MTQ","Martinique","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75848,474,"MTQ","Martinique","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75849,474,"MTQ","Martinique","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75850,474,"MTQ","Martinique","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75851,474,"MTQ","Martinique","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75852,474,"MTQ","Martinique","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75853,474,"MTQ","Martinique","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75854,474,"MTQ","Martinique","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75855,474,"MTQ","Martinique","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75856,474,"MTQ","Martinique","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75857,474,"MTQ","Martinique","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75858,474,"MTQ","Martinique","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75859,474,"MTQ","Martinique","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75860,474,"MTQ","Martinique","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75861,474,"MTQ","Martinique","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75862,474,"MTQ","Martinique","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75863,474,"MTQ","Martinique","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75864,474,"MTQ","Martinique","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75865,474,"MTQ","Martinique","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75866,474,"MTQ","Martinique","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75867,474,"MTQ","Martinique","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75868,474,"MTQ","Martinique","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75869,474,"MTQ","Martinique","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75870,474,"MTQ","Martinique","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75871,474,"MTQ","Martinique","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75872,474,"MTQ","Martinique","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75873,474,"MTQ","Martinique","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75874,474,"MTQ","Martinique","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75875,474,"MTQ","Martinique","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75876,474,"MTQ","Martinique","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75877,474,"MTQ","Martinique","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MTQ/mtq_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75878,478,"MRT","Mauritania","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75879,478,"MRT","Mauritania","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75880,478,"MRT","Mauritania","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75881,478,"MRT","Mauritania","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75882,478,"MRT","Mauritania","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75883,478,"MRT","Mauritania","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75884,478,"MRT","Mauritania","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75885,478,"MRT","Mauritania","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75886,478,"MRT","Mauritania","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75887,478,"MRT","Mauritania","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75888,478,"MRT","Mauritania","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75889,478,"MRT","Mauritania","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75890,478,"MRT","Mauritania","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75891,478,"MRT","Mauritania","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75892,478,"MRT","Mauritania","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75893,478,"MRT","Mauritania","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75894,478,"MRT","Mauritania","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75895,478,"MRT","Mauritania","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75896,478,"MRT","Mauritania","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75897,478,"MRT","Mauritania","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75898,478,"MRT","Mauritania","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75899,478,"MRT","Mauritania","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75900,478,"MRT","Mauritania","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75901,478,"MRT","Mauritania","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75902,478,"MRT","Mauritania","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75903,478,"MRT","Mauritania","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75904,478,"MRT","Mauritania","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75905,478,"MRT","Mauritania","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75906,478,"MRT","Mauritania","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75907,478,"MRT","Mauritania","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75908,478,"MRT","Mauritania","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75909,478,"MRT","Mauritania","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75910,478,"MRT","Mauritania","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75911,478,"MRT","Mauritania","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75912,478,"MRT","Mauritania","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75913,478,"MRT","Mauritania","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MRT/mrt_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75914,480,"MUS","Mauritius","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75915,480,"MUS","Mauritius","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75916,480,"MUS","Mauritius","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75917,480,"MUS","Mauritius","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75918,480,"MUS","Mauritius","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75919,480,"MUS","Mauritius","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75920,480,"MUS","Mauritius","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75921,480,"MUS","Mauritius","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75922,480,"MUS","Mauritius","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75923,480,"MUS","Mauritius","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75924,480,"MUS","Mauritius","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75925,480,"MUS","Mauritius","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75926,480,"MUS","Mauritius","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75927,480,"MUS","Mauritius","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75928,480,"MUS","Mauritius","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75929,480,"MUS","Mauritius","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75930,480,"MUS","Mauritius","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75931,480,"MUS","Mauritius","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75932,480,"MUS","Mauritius","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75933,480,"MUS","Mauritius","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75934,480,"MUS","Mauritius","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75935,480,"MUS","Mauritius","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75936,480,"MUS","Mauritius","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75937,480,"MUS","Mauritius","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75938,480,"MUS","Mauritius","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75939,480,"MUS","Mauritius","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75940,480,"MUS","Mauritius","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75941,480,"MUS","Mauritius","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75942,480,"MUS","Mauritius","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75943,480,"MUS","Mauritius","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75944,480,"MUS","Mauritius","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75945,480,"MUS","Mauritius","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75946,480,"MUS","Mauritius","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75947,480,"MUS","Mauritius","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75948,480,"MUS","Mauritius","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75949,480,"MUS","Mauritius","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MUS/mus_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75950,484,"MEX","Mexico","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75951,484,"MEX","Mexico","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75952,484,"MEX","Mexico","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75953,484,"MEX","Mexico","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75954,484,"MEX","Mexico","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75955,484,"MEX","Mexico","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75956,484,"MEX","Mexico","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75957,484,"MEX","Mexico","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75958,484,"MEX","Mexico","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75959,484,"MEX","Mexico","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75960,484,"MEX","Mexico","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75961,484,"MEX","Mexico","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75962,484,"MEX","Mexico","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75963,484,"MEX","Mexico","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
75964,484,"MEX","Mexico","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
75965,484,"MEX","Mexico","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
75966,484,"MEX","Mexico","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
75967,484,"MEX","Mexico","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
75968,484,"MEX","Mexico","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
75969,484,"MEX","Mexico","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
75970,484,"MEX","Mexico","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
75971,484,"MEX","Mexico","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
75972,484,"MEX","Mexico","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
75973,484,"MEX","Mexico","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
75974,484,"MEX","Mexico","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
75975,484,"MEX","Mexico","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
75976,484,"MEX","Mexico","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
75977,484,"MEX","Mexico","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
75978,484,"MEX","Mexico","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
75979,484,"MEX","Mexico","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
75980,484,"MEX","Mexico","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
75981,484,"MEX","Mexico","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
75982,484,"MEX","Mexico","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
75983,484,"MEX","Mexico","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
75984,484,"MEX","Mexico","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
75985,484,"MEX","Mexico","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MEX/mex_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
75986,492,"MCO","Monaco","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
75987,492,"MCO","Monaco","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
75988,492,"MCO","Monaco","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
75989,492,"MCO","Monaco","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
75990,492,"MCO","Monaco","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
75991,492,"MCO","Monaco","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
75992,492,"MCO","Monaco","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
75993,492,"MCO","Monaco","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
75994,492,"MCO","Monaco","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
75995,492,"MCO","Monaco","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
75996,492,"MCO","Monaco","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
75997,492,"MCO","Monaco","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
75998,492,"MCO","Monaco","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
75999,492,"MCO","Monaco","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76000,492,"MCO","Monaco","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76001,492,"MCO","Monaco","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76002,492,"MCO","Monaco","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76003,492,"MCO","Monaco","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76004,492,"MCO","Monaco","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76005,492,"MCO","Monaco","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76006,492,"MCO","Monaco","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76007,492,"MCO","Monaco","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76008,492,"MCO","Monaco","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76009,492,"MCO","Monaco","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76010,492,"MCO","Monaco","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76011,492,"MCO","Monaco","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76012,492,"MCO","Monaco","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76013,492,"MCO","Monaco","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76014,492,"MCO","Monaco","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76015,492,"MCO","Monaco","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76016,492,"MCO","Monaco","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76017,492,"MCO","Monaco","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76018,492,"MCO","Monaco","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76019,492,"MCO","Monaco","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76020,492,"MCO","Monaco","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76021,492,"MCO","Monaco","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MCO/mco_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76022,496,"MNG","Mongolia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76023,496,"MNG","Mongolia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76024,496,"MNG","Mongolia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76025,496,"MNG","Mongolia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76026,496,"MNG","Mongolia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76027,496,"MNG","Mongolia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76028,496,"MNG","Mongolia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76029,496,"MNG","Mongolia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76030,496,"MNG","Mongolia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76031,496,"MNG","Mongolia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76032,496,"MNG","Mongolia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76033,496,"MNG","Mongolia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76034,496,"MNG","Mongolia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76035,496,"MNG","Mongolia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76036,496,"MNG","Mongolia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76037,496,"MNG","Mongolia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76038,496,"MNG","Mongolia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76039,496,"MNG","Mongolia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76040,496,"MNG","Mongolia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76041,496,"MNG","Mongolia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76042,496,"MNG","Mongolia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76043,496,"MNG","Mongolia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76044,496,"MNG","Mongolia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76045,496,"MNG","Mongolia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76046,496,"MNG","Mongolia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76047,496,"MNG","Mongolia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76048,496,"MNG","Mongolia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76049,496,"MNG","Mongolia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76050,496,"MNG","Mongolia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76051,496,"MNG","Mongolia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76052,496,"MNG","Mongolia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76053,496,"MNG","Mongolia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76054,496,"MNG","Mongolia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76055,496,"MNG","Mongolia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76056,496,"MNG","Mongolia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76057,496,"MNG","Mongolia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNG/mng_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76058,498,"MDA","Moldova","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76059,498,"MDA","Moldova","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76060,498,"MDA","Moldova","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76061,498,"MDA","Moldova","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76062,498,"MDA","Moldova","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76063,498,"MDA","Moldova","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76064,498,"MDA","Moldova","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76065,498,"MDA","Moldova","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76066,498,"MDA","Moldova","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76067,498,"MDA","Moldova","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76068,498,"MDA","Moldova","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76069,498,"MDA","Moldova","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76070,498,"MDA","Moldova","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76071,498,"MDA","Moldova","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76072,498,"MDA","Moldova","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76073,498,"MDA","Moldova","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76074,498,"MDA","Moldova","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76075,498,"MDA","Moldova","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76076,498,"MDA","Moldova","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76077,498,"MDA","Moldova","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76078,498,"MDA","Moldova","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76079,498,"MDA","Moldova","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76080,498,"MDA","Moldova","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76081,498,"MDA","Moldova","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76082,498,"MDA","Moldova","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76083,498,"MDA","Moldova","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76084,498,"MDA","Moldova","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76085,498,"MDA","Moldova","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76086,498,"MDA","Moldova","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76087,498,"MDA","Moldova","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76088,498,"MDA","Moldova","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76089,498,"MDA","Moldova","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76090,498,"MDA","Moldova","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76091,498,"MDA","Moldova","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76092,498,"MDA","Moldova","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76093,498,"MDA","Moldova","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MDA/mda_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76094,499,"MNE","Montenegro","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76095,499,"MNE","Montenegro","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76096,499,"MNE","Montenegro","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76097,499,"MNE","Montenegro","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76098,499,"MNE","Montenegro","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76099,499,"MNE","Montenegro","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76100,499,"MNE","Montenegro","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76101,499,"MNE","Montenegro","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76102,499,"MNE","Montenegro","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76103,499,"MNE","Montenegro","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76104,499,"MNE","Montenegro","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76105,499,"MNE","Montenegro","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76106,499,"MNE","Montenegro","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76107,499,"MNE","Montenegro","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76108,499,"MNE","Montenegro","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76109,499,"MNE","Montenegro","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76110,499,"MNE","Montenegro","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76111,499,"MNE","Montenegro","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76112,499,"MNE","Montenegro","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76113,499,"MNE","Montenegro","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76114,499,"MNE","Montenegro","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76115,499,"MNE","Montenegro","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76116,499,"MNE","Montenegro","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76117,499,"MNE","Montenegro","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76118,499,"MNE","Montenegro","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76119,499,"MNE","Montenegro","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76120,499,"MNE","Montenegro","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76121,499,"MNE","Montenegro","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76122,499,"MNE","Montenegro","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76123,499,"MNE","Montenegro","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76124,499,"MNE","Montenegro","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76125,499,"MNE","Montenegro","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76126,499,"MNE","Montenegro","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76127,499,"MNE","Montenegro","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76128,499,"MNE","Montenegro","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76129,499,"MNE","Montenegro","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNE/mne_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76130,500,"MSR","Montserrat","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76131,500,"MSR","Montserrat","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76132,500,"MSR","Montserrat","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76133,500,"MSR","Montserrat","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76134,500,"MSR","Montserrat","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76135,500,"MSR","Montserrat","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76136,500,"MSR","Montserrat","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76137,500,"MSR","Montserrat","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76138,500,"MSR","Montserrat","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76139,500,"MSR","Montserrat","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76140,500,"MSR","Montserrat","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76141,500,"MSR","Montserrat","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76142,500,"MSR","Montserrat","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76143,500,"MSR","Montserrat","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76144,500,"MSR","Montserrat","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76145,500,"MSR","Montserrat","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76146,500,"MSR","Montserrat","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76147,500,"MSR","Montserrat","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76148,500,"MSR","Montserrat","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76149,500,"MSR","Montserrat","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76150,500,"MSR","Montserrat","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76151,500,"MSR","Montserrat","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76152,500,"MSR","Montserrat","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76153,500,"MSR","Montserrat","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76154,500,"MSR","Montserrat","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76155,500,"MSR","Montserrat","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76156,500,"MSR","Montserrat","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76157,500,"MSR","Montserrat","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76158,500,"MSR","Montserrat","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76159,500,"MSR","Montserrat","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76160,500,"MSR","Montserrat","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76161,500,"MSR","Montserrat","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76162,500,"MSR","Montserrat","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76163,500,"MSR","Montserrat","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76164,500,"MSR","Montserrat","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76165,500,"MSR","Montserrat","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MSR/msr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76166,504,"MAR","Morocco","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76167,504,"MAR","Morocco","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76168,504,"MAR","Morocco","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76169,504,"MAR","Morocco","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76170,504,"MAR","Morocco","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76171,504,"MAR","Morocco","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76172,504,"MAR","Morocco","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76173,504,"MAR","Morocco","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76174,504,"MAR","Morocco","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76175,504,"MAR","Morocco","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76176,504,"MAR","Morocco","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76177,504,"MAR","Morocco","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76178,504,"MAR","Morocco","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76179,504,"MAR","Morocco","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76180,504,"MAR","Morocco","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76181,504,"MAR","Morocco","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76182,504,"MAR","Morocco","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76183,504,"MAR","Morocco","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76184,504,"MAR","Morocco","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76185,504,"MAR","Morocco","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76186,504,"MAR","Morocco","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76187,504,"MAR","Morocco","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76188,504,"MAR","Morocco","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76189,504,"MAR","Morocco","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76190,504,"MAR","Morocco","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76191,504,"MAR","Morocco","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76192,504,"MAR","Morocco","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76193,504,"MAR","Morocco","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76194,504,"MAR","Morocco","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76195,504,"MAR","Morocco","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76196,504,"MAR","Morocco","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76197,504,"MAR","Morocco","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76198,504,"MAR","Morocco","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76199,504,"MAR","Morocco","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76200,504,"MAR","Morocco","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76201,504,"MAR","Morocco","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAR/mar_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76202,508,"MOZ","Mozambique","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76203,508,"MOZ","Mozambique","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76204,508,"MOZ","Mozambique","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76205,508,"MOZ","Mozambique","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76206,508,"MOZ","Mozambique","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76207,508,"MOZ","Mozambique","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76208,508,"MOZ","Mozambique","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76209,508,"MOZ","Mozambique","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76210,508,"MOZ","Mozambique","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76211,508,"MOZ","Mozambique","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76212,508,"MOZ","Mozambique","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76213,508,"MOZ","Mozambique","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76214,508,"MOZ","Mozambique","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76215,508,"MOZ","Mozambique","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76216,508,"MOZ","Mozambique","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76217,508,"MOZ","Mozambique","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76218,508,"MOZ","Mozambique","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76219,508,"MOZ","Mozambique","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76220,508,"MOZ","Mozambique","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76221,508,"MOZ","Mozambique","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76222,508,"MOZ","Mozambique","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76223,508,"MOZ","Mozambique","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76224,508,"MOZ","Mozambique","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76225,508,"MOZ","Mozambique","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76226,508,"MOZ","Mozambique","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76227,508,"MOZ","Mozambique","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76228,508,"MOZ","Mozambique","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76229,508,"MOZ","Mozambique","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76230,508,"MOZ","Mozambique","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76231,508,"MOZ","Mozambique","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76232,508,"MOZ","Mozambique","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76233,508,"MOZ","Mozambique","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76234,508,"MOZ","Mozambique","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76235,508,"MOZ","Mozambique","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76236,508,"MOZ","Mozambique","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76237,508,"MOZ","Mozambique","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MOZ/moz_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76238,512,"OMN","Oman","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76239,512,"OMN","Oman","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76240,512,"OMN","Oman","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76241,512,"OMN","Oman","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76242,512,"OMN","Oman","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76243,512,"OMN","Oman","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76244,512,"OMN","Oman","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76245,512,"OMN","Oman","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76246,512,"OMN","Oman","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76247,512,"OMN","Oman","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76248,512,"OMN","Oman","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76249,512,"OMN","Oman","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76250,512,"OMN","Oman","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76251,512,"OMN","Oman","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76252,512,"OMN","Oman","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76253,512,"OMN","Oman","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76254,512,"OMN","Oman","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76255,512,"OMN","Oman","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76256,512,"OMN","Oman","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76257,512,"OMN","Oman","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76258,512,"OMN","Oman","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76259,512,"OMN","Oman","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76260,512,"OMN","Oman","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76261,512,"OMN","Oman","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76262,512,"OMN","Oman","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76263,512,"OMN","Oman","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76264,512,"OMN","Oman","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76265,512,"OMN","Oman","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76266,512,"OMN","Oman","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76267,512,"OMN","Oman","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76268,512,"OMN","Oman","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76269,512,"OMN","Oman","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76270,512,"OMN","Oman","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76271,512,"OMN","Oman","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76272,512,"OMN","Oman","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76273,512,"OMN","Oman","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/OMN/omn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76274,516,"NAM","Namibia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76275,516,"NAM","Namibia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76276,516,"NAM","Namibia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76277,516,"NAM","Namibia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76278,516,"NAM","Namibia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76279,516,"NAM","Namibia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76280,516,"NAM","Namibia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76281,516,"NAM","Namibia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76282,516,"NAM","Namibia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76283,516,"NAM","Namibia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76284,516,"NAM","Namibia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76285,516,"NAM","Namibia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76286,516,"NAM","Namibia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76287,516,"NAM","Namibia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76288,516,"NAM","Namibia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76289,516,"NAM","Namibia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76290,516,"NAM","Namibia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76291,516,"NAM","Namibia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76292,516,"NAM","Namibia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76293,516,"NAM","Namibia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76294,516,"NAM","Namibia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76295,516,"NAM","Namibia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76296,516,"NAM","Namibia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76297,516,"NAM","Namibia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76298,516,"NAM","Namibia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76299,516,"NAM","Namibia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76300,516,"NAM","Namibia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76301,516,"NAM","Namibia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76302,516,"NAM","Namibia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76303,516,"NAM","Namibia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76304,516,"NAM","Namibia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76305,516,"NAM","Namibia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76306,516,"NAM","Namibia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76307,516,"NAM","Namibia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76308,516,"NAM","Namibia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76309,516,"NAM","Namibia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NAM/nam_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76310,520,"NRU","Nauru","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76311,520,"NRU","Nauru","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76312,520,"NRU","Nauru","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76313,520,"NRU","Nauru","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76314,520,"NRU","Nauru","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76315,520,"NRU","Nauru","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76316,520,"NRU","Nauru","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76317,520,"NRU","Nauru","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76318,520,"NRU","Nauru","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76319,520,"NRU","Nauru","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76320,520,"NRU","Nauru","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76321,520,"NRU","Nauru","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76322,520,"NRU","Nauru","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76323,520,"NRU","Nauru","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76324,520,"NRU","Nauru","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76325,520,"NRU","Nauru","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76326,520,"NRU","Nauru","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76327,520,"NRU","Nauru","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76328,520,"NRU","Nauru","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76329,520,"NRU","Nauru","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76330,520,"NRU","Nauru","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76331,520,"NRU","Nauru","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76332,520,"NRU","Nauru","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76333,520,"NRU","Nauru","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76334,520,"NRU","Nauru","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76335,520,"NRU","Nauru","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76336,520,"NRU","Nauru","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76337,520,"NRU","Nauru","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76338,520,"NRU","Nauru","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76339,520,"NRU","Nauru","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76340,520,"NRU","Nauru","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76341,520,"NRU","Nauru","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76342,520,"NRU","Nauru","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76343,520,"NRU","Nauru","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76344,520,"NRU","Nauru","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76345,520,"NRU","Nauru","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NRU/nru_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76346,524,"NPL","Nepal","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76347,524,"NPL","Nepal","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76348,524,"NPL","Nepal","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76349,524,"NPL","Nepal","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76350,524,"NPL","Nepal","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76351,524,"NPL","Nepal","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76352,524,"NPL","Nepal","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76353,524,"NPL","Nepal","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76354,524,"NPL","Nepal","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76355,524,"NPL","Nepal","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76356,524,"NPL","Nepal","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76357,524,"NPL","Nepal","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76358,524,"NPL","Nepal","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76359,524,"NPL","Nepal","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76360,524,"NPL","Nepal","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76361,524,"NPL","Nepal","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76362,524,"NPL","Nepal","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76363,524,"NPL","Nepal","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76364,524,"NPL","Nepal","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76365,524,"NPL","Nepal","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76366,524,"NPL","Nepal","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76367,524,"NPL","Nepal","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76368,524,"NPL","Nepal","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76369,524,"NPL","Nepal","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76370,524,"NPL","Nepal","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76371,524,"NPL","Nepal","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76372,524,"NPL","Nepal","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76373,524,"NPL","Nepal","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76374,524,"NPL","Nepal","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76375,524,"NPL","Nepal","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76376,524,"NPL","Nepal","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76377,524,"NPL","Nepal","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76378,524,"NPL","Nepal","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76379,524,"NPL","Nepal","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76380,524,"NPL","Nepal","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76381,524,"NPL","Nepal","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NPL/npl_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76382,528,"NLD","Netherlands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76383,528,"NLD","Netherlands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76384,528,"NLD","Netherlands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76385,528,"NLD","Netherlands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76386,528,"NLD","Netherlands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76387,528,"NLD","Netherlands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76388,528,"NLD","Netherlands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76389,528,"NLD","Netherlands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76390,528,"NLD","Netherlands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76391,528,"NLD","Netherlands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76392,528,"NLD","Netherlands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76393,528,"NLD","Netherlands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76394,528,"NLD","Netherlands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76395,528,"NLD","Netherlands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76396,528,"NLD","Netherlands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76397,528,"NLD","Netherlands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76398,528,"NLD","Netherlands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76399,528,"NLD","Netherlands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76400,528,"NLD","Netherlands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76401,528,"NLD","Netherlands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76402,528,"NLD","Netherlands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76403,528,"NLD","Netherlands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76404,528,"NLD","Netherlands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76405,528,"NLD","Netherlands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76406,528,"NLD","Netherlands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76407,528,"NLD","Netherlands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76408,528,"NLD","Netherlands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76409,528,"NLD","Netherlands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76410,528,"NLD","Netherlands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76411,528,"NLD","Netherlands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76412,528,"NLD","Netherlands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76413,528,"NLD","Netherlands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76414,528,"NLD","Netherlands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76415,528,"NLD","Netherlands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76416,528,"NLD","Netherlands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76417,528,"NLD","Netherlands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NLD/nld_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76418,531,"CUW","Curacao","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76419,531,"CUW","Curacao","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76420,531,"CUW","Curacao","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76421,531,"CUW","Curacao","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76422,531,"CUW","Curacao","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76423,531,"CUW","Curacao","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76424,531,"CUW","Curacao","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76425,531,"CUW","Curacao","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76426,531,"CUW","Curacao","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76427,531,"CUW","Curacao","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76428,531,"CUW","Curacao","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76429,531,"CUW","Curacao","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76430,531,"CUW","Curacao","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76431,531,"CUW","Curacao","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76432,531,"CUW","Curacao","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76433,531,"CUW","Curacao","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76434,531,"CUW","Curacao","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76435,531,"CUW","Curacao","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76436,531,"CUW","Curacao","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76437,531,"CUW","Curacao","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76438,531,"CUW","Curacao","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76439,531,"CUW","Curacao","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76440,531,"CUW","Curacao","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76441,531,"CUW","Curacao","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76442,531,"CUW","Curacao","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76443,531,"CUW","Curacao","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76444,531,"CUW","Curacao","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76445,531,"CUW","Curacao","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76446,531,"CUW","Curacao","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76447,531,"CUW","Curacao","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76448,531,"CUW","Curacao","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76449,531,"CUW","Curacao","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76450,531,"CUW","Curacao","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76451,531,"CUW","Curacao","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76452,531,"CUW","Curacao","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76453,531,"CUW","Curacao","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CUW/cuw_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76454,533,"ABW","Aruba","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76455,533,"ABW","Aruba","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76456,533,"ABW","Aruba","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76457,533,"ABW","Aruba","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76458,533,"ABW","Aruba","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76459,533,"ABW","Aruba","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76460,533,"ABW","Aruba","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76461,533,"ABW","Aruba","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76462,533,"ABW","Aruba","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76463,533,"ABW","Aruba","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76464,533,"ABW","Aruba","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76465,533,"ABW","Aruba","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76466,533,"ABW","Aruba","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76467,533,"ABW","Aruba","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76468,533,"ABW","Aruba","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76469,533,"ABW","Aruba","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76470,533,"ABW","Aruba","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76471,533,"ABW","Aruba","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76472,533,"ABW","Aruba","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76473,533,"ABW","Aruba","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76474,533,"ABW","Aruba","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76475,533,"ABW","Aruba","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76476,533,"ABW","Aruba","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76477,533,"ABW","Aruba","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76478,533,"ABW","Aruba","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76479,533,"ABW","Aruba","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76480,533,"ABW","Aruba","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76481,533,"ABW","Aruba","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76482,533,"ABW","Aruba","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76483,533,"ABW","Aruba","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76484,533,"ABW","Aruba","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76485,533,"ABW","Aruba","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76486,533,"ABW","Aruba","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76487,533,"ABW","Aruba","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76488,533,"ABW","Aruba","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76489,533,"ABW","Aruba","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ABW/abw_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76490,534,"SXM","Sint Maarten (Dutch part)","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76491,534,"SXM","Sint Maarten (Dutch part)","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76492,534,"SXM","Sint Maarten (Dutch part)","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76493,534,"SXM","Sint Maarten (Dutch part)","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76494,534,"SXM","Sint Maarten (Dutch part)","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76495,534,"SXM","Sint Maarten (Dutch part)","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76496,534,"SXM","Sint Maarten (Dutch part)","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76497,534,"SXM","Sint Maarten (Dutch part)","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76498,534,"SXM","Sint Maarten (Dutch part)","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76499,534,"SXM","Sint Maarten (Dutch part)","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76500,534,"SXM","Sint Maarten (Dutch part)","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76501,534,"SXM","Sint Maarten (Dutch part)","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76502,534,"SXM","Sint Maarten (Dutch part)","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76503,534,"SXM","Sint Maarten (Dutch part)","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76504,534,"SXM","Sint Maarten (Dutch part)","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76505,534,"SXM","Sint Maarten (Dutch part)","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76506,534,"SXM","Sint Maarten (Dutch part)","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76507,534,"SXM","Sint Maarten (Dutch part)","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76508,534,"SXM","Sint Maarten (Dutch part)","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76509,534,"SXM","Sint Maarten (Dutch part)","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76510,534,"SXM","Sint Maarten (Dutch part)","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76511,534,"SXM","Sint Maarten (Dutch part)","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76512,534,"SXM","Sint Maarten (Dutch part)","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76513,534,"SXM","Sint Maarten (Dutch part)","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76514,534,"SXM","Sint Maarten (Dutch part)","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76515,534,"SXM","Sint Maarten (Dutch part)","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76516,534,"SXM","Sint Maarten (Dutch part)","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76517,534,"SXM","Sint Maarten (Dutch part)","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76518,534,"SXM","Sint Maarten (Dutch part)","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76519,534,"SXM","Sint Maarten (Dutch part)","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76520,534,"SXM","Sint Maarten (Dutch part)","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76521,534,"SXM","Sint Maarten (Dutch part)","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76522,534,"SXM","Sint Maarten (Dutch part)","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76523,534,"SXM","Sint Maarten (Dutch part)","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76524,534,"SXM","Sint Maarten (Dutch part)","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76525,534,"SXM","Sint Maarten (Dutch part)","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SXM/sxm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76526,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76527,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76528,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76529,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76530,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76531,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76532,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76533,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76534,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76535,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76536,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76537,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76538,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76539,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76540,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76541,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76542,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76543,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76544,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76545,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76546,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76547,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76548,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76549,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76550,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76551,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76552,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76553,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76554,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76555,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76556,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76557,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76558,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76559,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76560,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76561,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BES/bes_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76562,540,"NCL","New Caledonia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76563,540,"NCL","New Caledonia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76564,540,"NCL","New Caledonia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76565,540,"NCL","New Caledonia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76566,540,"NCL","New Caledonia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76567,540,"NCL","New Caledonia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76568,540,"NCL","New Caledonia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76569,540,"NCL","New Caledonia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76570,540,"NCL","New Caledonia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76571,540,"NCL","New Caledonia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76572,540,"NCL","New Caledonia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76573,540,"NCL","New Caledonia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76574,540,"NCL","New Caledonia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76575,540,"NCL","New Caledonia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76576,540,"NCL","New Caledonia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76577,540,"NCL","New Caledonia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76578,540,"NCL","New Caledonia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76579,540,"NCL","New Caledonia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76580,540,"NCL","New Caledonia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76581,540,"NCL","New Caledonia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76582,540,"NCL","New Caledonia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76583,540,"NCL","New Caledonia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76584,540,"NCL","New Caledonia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76585,540,"NCL","New Caledonia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76586,540,"NCL","New Caledonia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76587,540,"NCL","New Caledonia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76588,540,"NCL","New Caledonia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76589,540,"NCL","New Caledonia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76590,540,"NCL","New Caledonia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76591,540,"NCL","New Caledonia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76592,540,"NCL","New Caledonia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76593,540,"NCL","New Caledonia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76594,540,"NCL","New Caledonia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76595,540,"NCL","New Caledonia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76596,540,"NCL","New Caledonia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76597,540,"NCL","New Caledonia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NCL/ncl_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76598,548,"VUT","Vanuatu","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76599,548,"VUT","Vanuatu","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76600,548,"VUT","Vanuatu","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76601,548,"VUT","Vanuatu","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76602,548,"VUT","Vanuatu","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76603,548,"VUT","Vanuatu","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76604,548,"VUT","Vanuatu","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76605,548,"VUT","Vanuatu","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76606,548,"VUT","Vanuatu","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76607,548,"VUT","Vanuatu","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76608,548,"VUT","Vanuatu","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76609,548,"VUT","Vanuatu","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76610,548,"VUT","Vanuatu","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76611,548,"VUT","Vanuatu","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76612,548,"VUT","Vanuatu","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76613,548,"VUT","Vanuatu","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76614,548,"VUT","Vanuatu","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76615,548,"VUT","Vanuatu","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76616,548,"VUT","Vanuatu","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76617,548,"VUT","Vanuatu","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76618,548,"VUT","Vanuatu","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76619,548,"VUT","Vanuatu","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76620,548,"VUT","Vanuatu","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76621,548,"VUT","Vanuatu","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76622,548,"VUT","Vanuatu","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76623,548,"VUT","Vanuatu","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76624,548,"VUT","Vanuatu","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76625,548,"VUT","Vanuatu","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76626,548,"VUT","Vanuatu","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76627,548,"VUT","Vanuatu","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76628,548,"VUT","Vanuatu","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76629,548,"VUT","Vanuatu","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76630,548,"VUT","Vanuatu","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76631,548,"VUT","Vanuatu","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76632,548,"VUT","Vanuatu","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76633,548,"VUT","Vanuatu","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VUT/vut_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76634,554,"NZL","New Zealand","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76635,554,"NZL","New Zealand","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76636,554,"NZL","New Zealand","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76637,554,"NZL","New Zealand","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76638,554,"NZL","New Zealand","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76639,554,"NZL","New Zealand","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76640,554,"NZL","New Zealand","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76641,554,"NZL","New Zealand","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76642,554,"NZL","New Zealand","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76643,554,"NZL","New Zealand","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76644,554,"NZL","New Zealand","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76645,554,"NZL","New Zealand","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76646,554,"NZL","New Zealand","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76647,554,"NZL","New Zealand","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76648,554,"NZL","New Zealand","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76649,554,"NZL","New Zealand","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76650,554,"NZL","New Zealand","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76651,554,"NZL","New Zealand","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76652,554,"NZL","New Zealand","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76653,554,"NZL","New Zealand","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76654,554,"NZL","New Zealand","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76655,554,"NZL","New Zealand","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76656,554,"NZL","New Zealand","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76657,554,"NZL","New Zealand","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76658,554,"NZL","New Zealand","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76659,554,"NZL","New Zealand","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76660,554,"NZL","New Zealand","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76661,554,"NZL","New Zealand","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76662,554,"NZL","New Zealand","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76663,554,"NZL","New Zealand","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76664,554,"NZL","New Zealand","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76665,554,"NZL","New Zealand","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76666,554,"NZL","New Zealand","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76667,554,"NZL","New Zealand","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76668,554,"NZL","New Zealand","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76669,554,"NZL","New Zealand","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NZL/nzl_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76670,558,"NIC","Nicaragua","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76671,558,"NIC","Nicaragua","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76672,558,"NIC","Nicaragua","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76673,558,"NIC","Nicaragua","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76674,558,"NIC","Nicaragua","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76675,558,"NIC","Nicaragua","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76676,558,"NIC","Nicaragua","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76677,558,"NIC","Nicaragua","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76678,558,"NIC","Nicaragua","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76679,558,"NIC","Nicaragua","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76680,558,"NIC","Nicaragua","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76681,558,"NIC","Nicaragua","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76682,558,"NIC","Nicaragua","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76683,558,"NIC","Nicaragua","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76684,558,"NIC","Nicaragua","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76685,558,"NIC","Nicaragua","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76686,558,"NIC","Nicaragua","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76687,558,"NIC","Nicaragua","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76688,558,"NIC","Nicaragua","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76689,558,"NIC","Nicaragua","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76690,558,"NIC","Nicaragua","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76691,558,"NIC","Nicaragua","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76692,558,"NIC","Nicaragua","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76693,558,"NIC","Nicaragua","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76694,558,"NIC","Nicaragua","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76695,558,"NIC","Nicaragua","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76696,558,"NIC","Nicaragua","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76697,558,"NIC","Nicaragua","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76698,558,"NIC","Nicaragua","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76699,558,"NIC","Nicaragua","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76700,558,"NIC","Nicaragua","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76701,558,"NIC","Nicaragua","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76702,558,"NIC","Nicaragua","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76703,558,"NIC","Nicaragua","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76704,558,"NIC","Nicaragua","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76705,558,"NIC","Nicaragua","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIC/nic_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76706,562,"NER","Niger","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76707,562,"NER","Niger","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76708,562,"NER","Niger","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76709,562,"NER","Niger","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76710,562,"NER","Niger","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76711,562,"NER","Niger","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76712,562,"NER","Niger","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76713,562,"NER","Niger","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76714,562,"NER","Niger","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76715,562,"NER","Niger","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76716,562,"NER","Niger","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76717,562,"NER","Niger","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76718,562,"NER","Niger","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76719,562,"NER","Niger","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76720,562,"NER","Niger","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76721,562,"NER","Niger","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76722,562,"NER","Niger","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76723,562,"NER","Niger","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76724,562,"NER","Niger","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76725,562,"NER","Niger","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76726,562,"NER","Niger","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76727,562,"NER","Niger","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76728,562,"NER","Niger","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76729,562,"NER","Niger","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76730,562,"NER","Niger","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76731,562,"NER","Niger","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76732,562,"NER","Niger","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76733,562,"NER","Niger","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76734,562,"NER","Niger","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76735,562,"NER","Niger","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76736,562,"NER","Niger","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76737,562,"NER","Niger","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76738,562,"NER","Niger","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76739,562,"NER","Niger","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76740,562,"NER","Niger","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76741,562,"NER","Niger","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NER/ner_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76742,566,"NGA","Nigeria","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76743,566,"NGA","Nigeria","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76744,566,"NGA","Nigeria","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76745,566,"NGA","Nigeria","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76746,566,"NGA","Nigeria","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76747,566,"NGA","Nigeria","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76748,566,"NGA","Nigeria","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76749,566,"NGA","Nigeria","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76750,566,"NGA","Nigeria","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76751,566,"NGA","Nigeria","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76752,566,"NGA","Nigeria","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76753,566,"NGA","Nigeria","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76754,566,"NGA","Nigeria","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76755,566,"NGA","Nigeria","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76756,566,"NGA","Nigeria","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76757,566,"NGA","Nigeria","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76758,566,"NGA","Nigeria","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76759,566,"NGA","Nigeria","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76760,566,"NGA","Nigeria","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76761,566,"NGA","Nigeria","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76762,566,"NGA","Nigeria","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76763,566,"NGA","Nigeria","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76764,566,"NGA","Nigeria","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76765,566,"NGA","Nigeria","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76766,566,"NGA","Nigeria","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76767,566,"NGA","Nigeria","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76768,566,"NGA","Nigeria","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76769,566,"NGA","Nigeria","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76770,566,"NGA","Nigeria","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76771,566,"NGA","Nigeria","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76772,566,"NGA","Nigeria","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76773,566,"NGA","Nigeria","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76774,566,"NGA","Nigeria","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76775,566,"NGA","Nigeria","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76776,566,"NGA","Nigeria","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76777,566,"NGA","Nigeria","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NGA/nga_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76778,570,"NIU","Niue","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76779,570,"NIU","Niue","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76780,570,"NIU","Niue","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76781,570,"NIU","Niue","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76782,570,"NIU","Niue","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76783,570,"NIU","Niue","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76784,570,"NIU","Niue","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76785,570,"NIU","Niue","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76786,570,"NIU","Niue","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76787,570,"NIU","Niue","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76788,570,"NIU","Niue","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76789,570,"NIU","Niue","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76790,570,"NIU","Niue","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76791,570,"NIU","Niue","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76792,570,"NIU","Niue","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76793,570,"NIU","Niue","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76794,570,"NIU","Niue","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76795,570,"NIU","Niue","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76796,570,"NIU","Niue","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76797,570,"NIU","Niue","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76798,570,"NIU","Niue","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76799,570,"NIU","Niue","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76800,570,"NIU","Niue","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76801,570,"NIU","Niue","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76802,570,"NIU","Niue","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76803,570,"NIU","Niue","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76804,570,"NIU","Niue","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76805,570,"NIU","Niue","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76806,570,"NIU","Niue","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76807,570,"NIU","Niue","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76808,570,"NIU","Niue","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76809,570,"NIU","Niue","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76810,570,"NIU","Niue","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76811,570,"NIU","Niue","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76812,570,"NIU","Niue","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76813,570,"NIU","Niue","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NIU/niu_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76814,574,"NFK","Norfolk Island","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76815,574,"NFK","Norfolk Island","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76816,574,"NFK","Norfolk Island","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76817,574,"NFK","Norfolk Island","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76818,574,"NFK","Norfolk Island","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76819,574,"NFK","Norfolk Island","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76820,574,"NFK","Norfolk Island","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76821,574,"NFK","Norfolk Island","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76822,574,"NFK","Norfolk Island","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76823,574,"NFK","Norfolk Island","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76824,574,"NFK","Norfolk Island","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76825,574,"NFK","Norfolk Island","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76826,574,"NFK","Norfolk Island","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76827,574,"NFK","Norfolk Island","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76828,574,"NFK","Norfolk Island","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76829,574,"NFK","Norfolk Island","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76830,574,"NFK","Norfolk Island","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76831,574,"NFK","Norfolk Island","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76832,574,"NFK","Norfolk Island","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76833,574,"NFK","Norfolk Island","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76834,574,"NFK","Norfolk Island","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76835,574,"NFK","Norfolk Island","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76836,574,"NFK","Norfolk Island","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76837,574,"NFK","Norfolk Island","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76838,574,"NFK","Norfolk Island","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76839,574,"NFK","Norfolk Island","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76840,574,"NFK","Norfolk Island","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76841,574,"NFK","Norfolk Island","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76842,574,"NFK","Norfolk Island","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76843,574,"NFK","Norfolk Island","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76844,574,"NFK","Norfolk Island","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76845,574,"NFK","Norfolk Island","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76846,574,"NFK","Norfolk Island","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76847,574,"NFK","Norfolk Island","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76848,574,"NFK","Norfolk Island","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76849,574,"NFK","Norfolk Island","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NFK/nfk_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76850,578,"NOR","Norway","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76851,578,"NOR","Norway","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76852,578,"NOR","Norway","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76853,578,"NOR","Norway","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76854,578,"NOR","Norway","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76855,578,"NOR","Norway","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76856,578,"NOR","Norway","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76857,578,"NOR","Norway","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76858,578,"NOR","Norway","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76859,578,"NOR","Norway","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76860,578,"NOR","Norway","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76861,578,"NOR","Norway","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76862,578,"NOR","Norway","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76863,578,"NOR","Norway","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76864,578,"NOR","Norway","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76865,578,"NOR","Norway","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76866,578,"NOR","Norway","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76867,578,"NOR","Norway","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76868,578,"NOR","Norway","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76869,578,"NOR","Norway","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76870,578,"NOR","Norway","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76871,578,"NOR","Norway","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76872,578,"NOR","Norway","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76873,578,"NOR","Norway","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76874,578,"NOR","Norway","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76875,578,"NOR","Norway","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76876,578,"NOR","Norway","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76877,578,"NOR","Norway","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76878,578,"NOR","Norway","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76879,578,"NOR","Norway","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76880,578,"NOR","Norway","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76881,578,"NOR","Norway","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76882,578,"NOR","Norway","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76883,578,"NOR","Norway","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76884,578,"NOR","Norway","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76885,578,"NOR","Norway","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/NOR/nor_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76886,580,"MNP","Northern Mariana Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76887,580,"MNP","Northern Mariana Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76888,580,"MNP","Northern Mariana Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76889,580,"MNP","Northern Mariana Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76890,580,"MNP","Northern Mariana Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76891,580,"MNP","Northern Mariana Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76892,580,"MNP","Northern Mariana Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76893,580,"MNP","Northern Mariana Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76894,580,"MNP","Northern Mariana Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76895,580,"MNP","Northern Mariana Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76896,580,"MNP","Northern Mariana Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76897,580,"MNP","Northern Mariana Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76898,580,"MNP","Northern Mariana Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76899,580,"MNP","Northern Mariana Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76900,580,"MNP","Northern Mariana Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76901,580,"MNP","Northern Mariana Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76902,580,"MNP","Northern Mariana Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76903,580,"MNP","Northern Mariana Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76904,580,"MNP","Northern Mariana Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76905,580,"MNP","Northern Mariana Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76906,580,"MNP","Northern Mariana Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76907,580,"MNP","Northern Mariana Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76908,580,"MNP","Northern Mariana Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76909,580,"MNP","Northern Mariana Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76910,580,"MNP","Northern Mariana Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76911,580,"MNP","Northern Mariana Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76912,580,"MNP","Northern Mariana Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76913,580,"MNP","Northern Mariana Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76914,580,"MNP","Northern Mariana Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76915,580,"MNP","Northern Mariana Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76916,580,"MNP","Northern Mariana Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76917,580,"MNP","Northern Mariana Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76918,580,"MNP","Northern Mariana Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76919,580,"MNP","Northern Mariana Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76920,580,"MNP","Northern Mariana Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76921,580,"MNP","Northern Mariana Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MNP/mnp_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76922,581,"UMI","United States Minor Outlying Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76923,581,"UMI","United States Minor Outlying Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76924,581,"UMI","United States Minor Outlying Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76925,581,"UMI","United States Minor Outlying Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76926,581,"UMI","United States Minor Outlying Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76927,581,"UMI","United States Minor Outlying Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76928,581,"UMI","United States Minor Outlying Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76929,581,"UMI","United States Minor Outlying Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76930,581,"UMI","United States Minor Outlying Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76931,581,"UMI","United States Minor Outlying Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76932,581,"UMI","United States Minor Outlying Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76933,581,"UMI","United States Minor Outlying Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76934,581,"UMI","United States Minor Outlying Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76935,581,"UMI","United States Minor Outlying Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76936,581,"UMI","United States Minor Outlying Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76937,581,"UMI","United States Minor Outlying Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76938,581,"UMI","United States Minor Outlying Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76939,581,"UMI","United States Minor Outlying Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76940,581,"UMI","United States Minor Outlying Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76941,581,"UMI","United States Minor Outlying Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76942,581,"UMI","United States Minor Outlying Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76943,581,"UMI","United States Minor Outlying Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76944,581,"UMI","United States Minor Outlying Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76945,581,"UMI","United States Minor Outlying Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76946,581,"UMI","United States Minor Outlying Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76947,581,"UMI","United States Minor Outlying Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76948,581,"UMI","United States Minor Outlying Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76949,581,"UMI","United States Minor Outlying Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76950,581,"UMI","United States Minor Outlying Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76951,581,"UMI","United States Minor Outlying Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76952,581,"UMI","United States Minor Outlying Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76953,581,"UMI","United States Minor Outlying Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76954,581,"UMI","United States Minor Outlying Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76955,581,"UMI","United States Minor Outlying Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76956,581,"UMI","United States Minor Outlying Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76957,581,"UMI","United States Minor Outlying Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UMI/umi_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76958,583,"FSM","Micronesia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76959,583,"FSM","Micronesia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76960,583,"FSM","Micronesia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76961,583,"FSM","Micronesia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76962,583,"FSM","Micronesia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76963,583,"FSM","Micronesia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
76964,583,"FSM","Micronesia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
76965,583,"FSM","Micronesia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
76966,583,"FSM","Micronesia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
76967,583,"FSM","Micronesia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
76968,583,"FSM","Micronesia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
76969,583,"FSM","Micronesia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
76970,583,"FSM","Micronesia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
76971,583,"FSM","Micronesia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
76972,583,"FSM","Micronesia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
76973,583,"FSM","Micronesia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
76974,583,"FSM","Micronesia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
76975,583,"FSM","Micronesia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
76976,583,"FSM","Micronesia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
76977,583,"FSM","Micronesia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
76978,583,"FSM","Micronesia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
76979,583,"FSM","Micronesia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
76980,583,"FSM","Micronesia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
76981,583,"FSM","Micronesia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
76982,583,"FSM","Micronesia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
76983,583,"FSM","Micronesia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
76984,583,"FSM","Micronesia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
76985,583,"FSM","Micronesia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
76986,583,"FSM","Micronesia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
76987,583,"FSM","Micronesia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
76988,583,"FSM","Micronesia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
76989,583,"FSM","Micronesia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
76990,583,"FSM","Micronesia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
76991,583,"FSM","Micronesia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
76992,583,"FSM","Micronesia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
76993,583,"FSM","Micronesia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/FSM/fsm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
76994,584,"MHL","Marshall Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
76995,584,"MHL","Marshall Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
76996,584,"MHL","Marshall Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
76997,584,"MHL","Marshall Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
76998,584,"MHL","Marshall Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
76999,584,"MHL","Marshall Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77000,584,"MHL","Marshall Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77001,584,"MHL","Marshall Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77002,584,"MHL","Marshall Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77003,584,"MHL","Marshall Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77004,584,"MHL","Marshall Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77005,584,"MHL","Marshall Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77006,584,"MHL","Marshall Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77007,584,"MHL","Marshall Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77008,584,"MHL","Marshall Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77009,584,"MHL","Marshall Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77010,584,"MHL","Marshall Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77011,584,"MHL","Marshall Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77012,584,"MHL","Marshall Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77013,584,"MHL","Marshall Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77014,584,"MHL","Marshall Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77015,584,"MHL","Marshall Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77016,584,"MHL","Marshall Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77017,584,"MHL","Marshall Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77018,584,"MHL","Marshall Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77019,584,"MHL","Marshall Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77020,584,"MHL","Marshall Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77021,584,"MHL","Marshall Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77022,584,"MHL","Marshall Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77023,584,"MHL","Marshall Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77024,584,"MHL","Marshall Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77025,584,"MHL","Marshall Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77026,584,"MHL","Marshall Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77027,584,"MHL","Marshall Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77028,584,"MHL","Marshall Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77029,584,"MHL","Marshall Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MHL/mhl_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77030,585,"PLW","Palau","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77031,585,"PLW","Palau","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77032,585,"PLW","Palau","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77033,585,"PLW","Palau","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77034,585,"PLW","Palau","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77035,585,"PLW","Palau","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77036,585,"PLW","Palau","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77037,585,"PLW","Palau","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77038,585,"PLW","Palau","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77039,585,"PLW","Palau","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77040,585,"PLW","Palau","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77041,585,"PLW","Palau","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77042,585,"PLW","Palau","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77043,585,"PLW","Palau","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77044,585,"PLW","Palau","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77045,585,"PLW","Palau","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77046,585,"PLW","Palau","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77047,585,"PLW","Palau","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77048,585,"PLW","Palau","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77049,585,"PLW","Palau","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77050,585,"PLW","Palau","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77051,585,"PLW","Palau","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77052,585,"PLW","Palau","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77053,585,"PLW","Palau","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77054,585,"PLW","Palau","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77055,585,"PLW","Palau","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77056,585,"PLW","Palau","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77057,585,"PLW","Palau","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77058,585,"PLW","Palau","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77059,585,"PLW","Palau","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77060,585,"PLW","Palau","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77061,585,"PLW","Palau","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77062,585,"PLW","Palau","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77063,585,"PLW","Palau","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77064,585,"PLW","Palau","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77065,585,"PLW","Palau","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PLW/plw_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77066,586,"PAK","Pakistan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77067,586,"PAK","Pakistan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77068,586,"PAK","Pakistan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77069,586,"PAK","Pakistan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77070,586,"PAK","Pakistan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77071,586,"PAK","Pakistan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77072,586,"PAK","Pakistan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77073,586,"PAK","Pakistan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77074,586,"PAK","Pakistan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77075,586,"PAK","Pakistan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77076,586,"PAK","Pakistan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77077,586,"PAK","Pakistan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77078,586,"PAK","Pakistan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77079,586,"PAK","Pakistan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77080,586,"PAK","Pakistan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77081,586,"PAK","Pakistan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77082,586,"PAK","Pakistan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77083,586,"PAK","Pakistan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77084,586,"PAK","Pakistan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77085,586,"PAK","Pakistan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77086,586,"PAK","Pakistan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77087,586,"PAK","Pakistan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77088,586,"PAK","Pakistan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77089,586,"PAK","Pakistan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77090,586,"PAK","Pakistan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77091,586,"PAK","Pakistan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77092,586,"PAK","Pakistan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77093,586,"PAK","Pakistan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77094,586,"PAK","Pakistan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77095,586,"PAK","Pakistan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77096,586,"PAK","Pakistan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77097,586,"PAK","Pakistan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77098,586,"PAK","Pakistan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77099,586,"PAK","Pakistan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77100,586,"PAK","Pakistan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77101,586,"PAK","Pakistan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAK/pak_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77102,591,"PAN","Panama","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77103,591,"PAN","Panama","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77104,591,"PAN","Panama","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77105,591,"PAN","Panama","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77106,591,"PAN","Panama","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77107,591,"PAN","Panama","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77108,591,"PAN","Panama","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77109,591,"PAN","Panama","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77110,591,"PAN","Panama","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77111,591,"PAN","Panama","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77112,591,"PAN","Panama","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77113,591,"PAN","Panama","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77114,591,"PAN","Panama","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77115,591,"PAN","Panama","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77116,591,"PAN","Panama","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77117,591,"PAN","Panama","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77118,591,"PAN","Panama","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77119,591,"PAN","Panama","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77120,591,"PAN","Panama","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77121,591,"PAN","Panama","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77122,591,"PAN","Panama","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77123,591,"PAN","Panama","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77124,591,"PAN","Panama","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77125,591,"PAN","Panama","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77126,591,"PAN","Panama","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77127,591,"PAN","Panama","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77128,591,"PAN","Panama","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77129,591,"PAN","Panama","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77130,591,"PAN","Panama","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77131,591,"PAN","Panama","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77132,591,"PAN","Panama","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77133,591,"PAN","Panama","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77134,591,"PAN","Panama","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77135,591,"PAN","Panama","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77136,591,"PAN","Panama","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77137,591,"PAN","Panama","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PAN/pan_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77138,598,"PNG","Papua New Guinea","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77139,598,"PNG","Papua New Guinea","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77140,598,"PNG","Papua New Guinea","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77141,598,"PNG","Papua New Guinea","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77142,598,"PNG","Papua New Guinea","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77143,598,"PNG","Papua New Guinea","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77144,598,"PNG","Papua New Guinea","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77145,598,"PNG","Papua New Guinea","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77146,598,"PNG","Papua New Guinea","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77147,598,"PNG","Papua New Guinea","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77148,598,"PNG","Papua New Guinea","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77149,598,"PNG","Papua New Guinea","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77150,598,"PNG","Papua New Guinea","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77151,598,"PNG","Papua New Guinea","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77152,598,"PNG","Papua New Guinea","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77153,598,"PNG","Papua New Guinea","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77154,598,"PNG","Papua New Guinea","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77155,598,"PNG","Papua New Guinea","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77156,598,"PNG","Papua New Guinea","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77157,598,"PNG","Papua New Guinea","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77158,598,"PNG","Papua New Guinea","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77159,598,"PNG","Papua New Guinea","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77160,598,"PNG","Papua New Guinea","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77161,598,"PNG","Papua New Guinea","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77162,598,"PNG","Papua New Guinea","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77163,598,"PNG","Papua New Guinea","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77164,598,"PNG","Papua New Guinea","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77165,598,"PNG","Papua New Guinea","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77166,598,"PNG","Papua New Guinea","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77167,598,"PNG","Papua New Guinea","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77168,598,"PNG","Papua New Guinea","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77169,598,"PNG","Papua New Guinea","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77170,598,"PNG","Papua New Guinea","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77171,598,"PNG","Papua New Guinea","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77172,598,"PNG","Papua New Guinea","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77173,598,"PNG","Papua New Guinea","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PNG/png_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77174,600,"PRY","Paraguay","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77175,600,"PRY","Paraguay","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77176,600,"PRY","Paraguay","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77177,600,"PRY","Paraguay","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77178,600,"PRY","Paraguay","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77179,600,"PRY","Paraguay","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77180,600,"PRY","Paraguay","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77181,600,"PRY","Paraguay","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77182,600,"PRY","Paraguay","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77183,600,"PRY","Paraguay","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77184,600,"PRY","Paraguay","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77185,600,"PRY","Paraguay","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77186,600,"PRY","Paraguay","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77187,600,"PRY","Paraguay","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77188,600,"PRY","Paraguay","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77189,600,"PRY","Paraguay","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77190,600,"PRY","Paraguay","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77191,600,"PRY","Paraguay","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77192,600,"PRY","Paraguay","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77193,600,"PRY","Paraguay","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77194,600,"PRY","Paraguay","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77195,600,"PRY","Paraguay","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77196,600,"PRY","Paraguay","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77197,600,"PRY","Paraguay","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77198,600,"PRY","Paraguay","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77199,600,"PRY","Paraguay","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77200,600,"PRY","Paraguay","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77201,600,"PRY","Paraguay","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77202,600,"PRY","Paraguay","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77203,600,"PRY","Paraguay","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77204,600,"PRY","Paraguay","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77205,600,"PRY","Paraguay","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77206,600,"PRY","Paraguay","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77207,600,"PRY","Paraguay","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77208,600,"PRY","Paraguay","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77209,600,"PRY","Paraguay","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRY/pry_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77210,604,"PER","Peru","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77211,604,"PER","Peru","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77212,604,"PER","Peru","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77213,604,"PER","Peru","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77214,604,"PER","Peru","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77215,604,"PER","Peru","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77216,604,"PER","Peru","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77217,604,"PER","Peru","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77218,604,"PER","Peru","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77219,604,"PER","Peru","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77220,604,"PER","Peru","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77221,604,"PER","Peru","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77222,604,"PER","Peru","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77223,604,"PER","Peru","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77224,604,"PER","Peru","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77225,604,"PER","Peru","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77226,604,"PER","Peru","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77227,604,"PER","Peru","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77228,604,"PER","Peru","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77229,604,"PER","Peru","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77230,604,"PER","Peru","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77231,604,"PER","Peru","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77232,604,"PER","Peru","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77233,604,"PER","Peru","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77234,604,"PER","Peru","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77235,604,"PER","Peru","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77236,604,"PER","Peru","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77237,604,"PER","Peru","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77238,604,"PER","Peru","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77239,604,"PER","Peru","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77240,604,"PER","Peru","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77241,604,"PER","Peru","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77242,604,"PER","Peru","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77243,604,"PER","Peru","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77244,604,"PER","Peru","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77245,604,"PER","Peru","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PER/per_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77246,608,"PHL","Philippines","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77247,608,"PHL","Philippines","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77248,608,"PHL","Philippines","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77249,608,"PHL","Philippines","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77250,608,"PHL","Philippines","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77251,608,"PHL","Philippines","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77252,608,"PHL","Philippines","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77253,608,"PHL","Philippines","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77254,608,"PHL","Philippines","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77255,608,"PHL","Philippines","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77256,608,"PHL","Philippines","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77257,608,"PHL","Philippines","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77258,608,"PHL","Philippines","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77259,608,"PHL","Philippines","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77260,608,"PHL","Philippines","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77261,608,"PHL","Philippines","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77262,608,"PHL","Philippines","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77263,608,"PHL","Philippines","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77264,608,"PHL","Philippines","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77265,608,"PHL","Philippines","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77266,608,"PHL","Philippines","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77267,608,"PHL","Philippines","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77268,608,"PHL","Philippines","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77269,608,"PHL","Philippines","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77270,608,"PHL","Philippines","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77271,608,"PHL","Philippines","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77272,608,"PHL","Philippines","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77273,608,"PHL","Philippines","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77274,608,"PHL","Philippines","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77275,608,"PHL","Philippines","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77276,608,"PHL","Philippines","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77277,608,"PHL","Philippines","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77278,608,"PHL","Philippines","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77279,608,"PHL","Philippines","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77280,608,"PHL","Philippines","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77281,608,"PHL","Philippines","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PHL/phl_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77282,612,"PCN","Pitcairn Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77283,612,"PCN","Pitcairn Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77284,612,"PCN","Pitcairn Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77285,612,"PCN","Pitcairn Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77286,612,"PCN","Pitcairn Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77287,612,"PCN","Pitcairn Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77288,612,"PCN","Pitcairn Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77289,612,"PCN","Pitcairn Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77290,612,"PCN","Pitcairn Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77291,612,"PCN","Pitcairn Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77292,612,"PCN","Pitcairn Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77293,612,"PCN","Pitcairn Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77294,612,"PCN","Pitcairn Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77295,612,"PCN","Pitcairn Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77296,612,"PCN","Pitcairn Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77297,612,"PCN","Pitcairn Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77298,612,"PCN","Pitcairn Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77299,612,"PCN","Pitcairn Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77300,612,"PCN","Pitcairn Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77301,612,"PCN","Pitcairn Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77302,612,"PCN","Pitcairn Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77303,612,"PCN","Pitcairn Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77304,612,"PCN","Pitcairn Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77305,612,"PCN","Pitcairn Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77306,612,"PCN","Pitcairn Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77307,612,"PCN","Pitcairn Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77308,612,"PCN","Pitcairn Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77309,612,"PCN","Pitcairn Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77310,612,"PCN","Pitcairn Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77311,612,"PCN","Pitcairn Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77312,612,"PCN","Pitcairn Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77313,612,"PCN","Pitcairn Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77314,612,"PCN","Pitcairn Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77315,612,"PCN","Pitcairn Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77316,612,"PCN","Pitcairn Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77317,612,"PCN","Pitcairn Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PCN/pcn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77318,616,"POL","Poland","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77319,616,"POL","Poland","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77320,616,"POL","Poland","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77321,616,"POL","Poland","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77322,616,"POL","Poland","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77323,616,"POL","Poland","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77324,616,"POL","Poland","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77325,616,"POL","Poland","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77326,616,"POL","Poland","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77327,616,"POL","Poland","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77328,616,"POL","Poland","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77329,616,"POL","Poland","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77330,616,"POL","Poland","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77331,616,"POL","Poland","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77332,616,"POL","Poland","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77333,616,"POL","Poland","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77334,616,"POL","Poland","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77335,616,"POL","Poland","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77336,616,"POL","Poland","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77337,616,"POL","Poland","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77338,616,"POL","Poland","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77339,616,"POL","Poland","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77340,616,"POL","Poland","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77341,616,"POL","Poland","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77342,616,"POL","Poland","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77343,616,"POL","Poland","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77344,616,"POL","Poland","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77345,616,"POL","Poland","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77346,616,"POL","Poland","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77347,616,"POL","Poland","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77348,616,"POL","Poland","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77349,616,"POL","Poland","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77350,616,"POL","Poland","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77351,616,"POL","Poland","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77352,616,"POL","Poland","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77353,616,"POL","Poland","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/POL/pol_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77354,620,"PRT","Portugal","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77355,620,"PRT","Portugal","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77356,620,"PRT","Portugal","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77357,620,"PRT","Portugal","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77358,620,"PRT","Portugal","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77359,620,"PRT","Portugal","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77360,620,"PRT","Portugal","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77361,620,"PRT","Portugal","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77362,620,"PRT","Portugal","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77363,620,"PRT","Portugal","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77364,620,"PRT","Portugal","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77365,620,"PRT","Portugal","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77366,620,"PRT","Portugal","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77367,620,"PRT","Portugal","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77368,620,"PRT","Portugal","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77369,620,"PRT","Portugal","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77370,620,"PRT","Portugal","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77371,620,"PRT","Portugal","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77372,620,"PRT","Portugal","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77373,620,"PRT","Portugal","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77374,620,"PRT","Portugal","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77375,620,"PRT","Portugal","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77376,620,"PRT","Portugal","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77377,620,"PRT","Portugal","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77378,620,"PRT","Portugal","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77379,620,"PRT","Portugal","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77380,620,"PRT","Portugal","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77381,620,"PRT","Portugal","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77382,620,"PRT","Portugal","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77383,620,"PRT","Portugal","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77384,620,"PRT","Portugal","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77385,620,"PRT","Portugal","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77386,620,"PRT","Portugal","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77387,620,"PRT","Portugal","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77388,620,"PRT","Portugal","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77389,620,"PRT","Portugal","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRT/prt_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77390,624,"GNB","Guinea-Bissau","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77391,624,"GNB","Guinea-Bissau","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77392,624,"GNB","Guinea-Bissau","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77393,624,"GNB","Guinea-Bissau","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77394,624,"GNB","Guinea-Bissau","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77395,624,"GNB","Guinea-Bissau","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77396,624,"GNB","Guinea-Bissau","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77397,624,"GNB","Guinea-Bissau","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77398,624,"GNB","Guinea-Bissau","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77399,624,"GNB","Guinea-Bissau","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77400,624,"GNB","Guinea-Bissau","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77401,624,"GNB","Guinea-Bissau","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77402,624,"GNB","Guinea-Bissau","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77403,624,"GNB","Guinea-Bissau","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77404,624,"GNB","Guinea-Bissau","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77405,624,"GNB","Guinea-Bissau","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77406,624,"GNB","Guinea-Bissau","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77407,624,"GNB","Guinea-Bissau","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77408,624,"GNB","Guinea-Bissau","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77409,624,"GNB","Guinea-Bissau","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77410,624,"GNB","Guinea-Bissau","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77411,624,"GNB","Guinea-Bissau","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77412,624,"GNB","Guinea-Bissau","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77413,624,"GNB","Guinea-Bissau","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77414,624,"GNB","Guinea-Bissau","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77415,624,"GNB","Guinea-Bissau","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77416,624,"GNB","Guinea-Bissau","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77417,624,"GNB","Guinea-Bissau","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77418,624,"GNB","Guinea-Bissau","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77419,624,"GNB","Guinea-Bissau","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77420,624,"GNB","Guinea-Bissau","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77421,624,"GNB","Guinea-Bissau","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77422,624,"GNB","Guinea-Bissau","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77423,624,"GNB","Guinea-Bissau","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77424,624,"GNB","Guinea-Bissau","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77425,624,"GNB","Guinea-Bissau","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GNB/gnb_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77426,626,"TLS","East Timor","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77427,626,"TLS","East Timor","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77428,626,"TLS","East Timor","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77429,626,"TLS","East Timor","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77430,626,"TLS","East Timor","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77431,626,"TLS","East Timor","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77432,626,"TLS","East Timor","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77433,626,"TLS","East Timor","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77434,626,"TLS","East Timor","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77435,626,"TLS","East Timor","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77436,626,"TLS","East Timor","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77437,626,"TLS","East Timor","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77438,626,"TLS","East Timor","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77439,626,"TLS","East Timor","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77440,626,"TLS","East Timor","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77441,626,"TLS","East Timor","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77442,626,"TLS","East Timor","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77443,626,"TLS","East Timor","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77444,626,"TLS","East Timor","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77445,626,"TLS","East Timor","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77446,626,"TLS","East Timor","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77447,626,"TLS","East Timor","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77448,626,"TLS","East Timor","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77449,626,"TLS","East Timor","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77450,626,"TLS","East Timor","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77451,626,"TLS","East Timor","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77452,626,"TLS","East Timor","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77453,626,"TLS","East Timor","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77454,626,"TLS","East Timor","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77455,626,"TLS","East Timor","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77456,626,"TLS","East Timor","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77457,626,"TLS","East Timor","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77458,626,"TLS","East Timor","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77459,626,"TLS","East Timor","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77460,626,"TLS","East Timor","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77461,626,"TLS","East Timor","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TLS/tls_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77462,630,"PRI","Puerto Rico","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77463,630,"PRI","Puerto Rico","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77464,630,"PRI","Puerto Rico","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77465,630,"PRI","Puerto Rico","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77466,630,"PRI","Puerto Rico","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77467,630,"PRI","Puerto Rico","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77468,630,"PRI","Puerto Rico","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77469,630,"PRI","Puerto Rico","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77470,630,"PRI","Puerto Rico","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77471,630,"PRI","Puerto Rico","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77472,630,"PRI","Puerto Rico","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77473,630,"PRI","Puerto Rico","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77474,630,"PRI","Puerto Rico","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77475,630,"PRI","Puerto Rico","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77476,630,"PRI","Puerto Rico","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77477,630,"PRI","Puerto Rico","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77478,630,"PRI","Puerto Rico","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77479,630,"PRI","Puerto Rico","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77480,630,"PRI","Puerto Rico","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77481,630,"PRI","Puerto Rico","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77482,630,"PRI","Puerto Rico","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77483,630,"PRI","Puerto Rico","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77484,630,"PRI","Puerto Rico","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77485,630,"PRI","Puerto Rico","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77486,630,"PRI","Puerto Rico","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77487,630,"PRI","Puerto Rico","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77488,630,"PRI","Puerto Rico","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77489,630,"PRI","Puerto Rico","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77490,630,"PRI","Puerto Rico","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77491,630,"PRI","Puerto Rico","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77492,630,"PRI","Puerto Rico","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77493,630,"PRI","Puerto Rico","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77494,630,"PRI","Puerto Rico","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77495,630,"PRI","Puerto Rico","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77496,630,"PRI","Puerto Rico","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77497,630,"PRI","Puerto Rico","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/PRI/pri_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77498,634,"QAT","Qatar","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77499,634,"QAT","Qatar","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77500,634,"QAT","Qatar","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77501,634,"QAT","Qatar","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77502,634,"QAT","Qatar","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77503,634,"QAT","Qatar","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77504,634,"QAT","Qatar","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77505,634,"QAT","Qatar","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77506,634,"QAT","Qatar","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77507,634,"QAT","Qatar","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77508,634,"QAT","Qatar","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77509,634,"QAT","Qatar","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77510,634,"QAT","Qatar","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77511,634,"QAT","Qatar","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77512,634,"QAT","Qatar","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77513,634,"QAT","Qatar","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77514,634,"QAT","Qatar","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77515,634,"QAT","Qatar","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77516,634,"QAT","Qatar","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77517,634,"QAT","Qatar","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77518,634,"QAT","Qatar","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77519,634,"QAT","Qatar","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77520,634,"QAT","Qatar","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77521,634,"QAT","Qatar","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77522,634,"QAT","Qatar","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77523,634,"QAT","Qatar","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77524,634,"QAT","Qatar","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77525,634,"QAT","Qatar","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77526,634,"QAT","Qatar","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77527,634,"QAT","Qatar","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77528,634,"QAT","Qatar","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77529,634,"QAT","Qatar","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77530,634,"QAT","Qatar","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77531,634,"QAT","Qatar","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77532,634,"QAT","Qatar","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77533,634,"QAT","Qatar","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/QAT/qat_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77534,638,"REU","Reunion","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77535,638,"REU","Reunion","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77536,638,"REU","Reunion","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77537,638,"REU","Reunion","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77538,638,"REU","Reunion","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77539,638,"REU","Reunion","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77540,638,"REU","Reunion","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77541,638,"REU","Reunion","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77542,638,"REU","Reunion","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77543,638,"REU","Reunion","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77544,638,"REU","Reunion","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77545,638,"REU","Reunion","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77546,638,"REU","Reunion","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77547,638,"REU","Reunion","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77548,638,"REU","Reunion","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77549,638,"REU","Reunion","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77550,638,"REU","Reunion","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77551,638,"REU","Reunion","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77552,638,"REU","Reunion","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77553,638,"REU","Reunion","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77554,638,"REU","Reunion","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77555,638,"REU","Reunion","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77556,638,"REU","Reunion","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77557,638,"REU","Reunion","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77558,638,"REU","Reunion","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77559,638,"REU","Reunion","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77560,638,"REU","Reunion","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77561,638,"REU","Reunion","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77562,638,"REU","Reunion","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77563,638,"REU","Reunion","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77564,638,"REU","Reunion","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77565,638,"REU","Reunion","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77566,638,"REU","Reunion","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77567,638,"REU","Reunion","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77568,638,"REU","Reunion","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77569,638,"REU","Reunion","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/REU/reu_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77570,642,"ROU","Romania","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77571,642,"ROU","Romania","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77572,642,"ROU","Romania","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77573,642,"ROU","Romania","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77574,642,"ROU","Romania","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77575,642,"ROU","Romania","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77576,642,"ROU","Romania","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77577,642,"ROU","Romania","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77578,642,"ROU","Romania","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77579,642,"ROU","Romania","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77580,642,"ROU","Romania","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77581,642,"ROU","Romania","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77582,642,"ROU","Romania","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77583,642,"ROU","Romania","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77584,642,"ROU","Romania","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77585,642,"ROU","Romania","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77586,642,"ROU","Romania","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77587,642,"ROU","Romania","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77588,642,"ROU","Romania","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77589,642,"ROU","Romania","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77590,642,"ROU","Romania","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77591,642,"ROU","Romania","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77592,642,"ROU","Romania","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77593,642,"ROU","Romania","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77594,642,"ROU","Romania","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77595,642,"ROU","Romania","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77596,642,"ROU","Romania","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77597,642,"ROU","Romania","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77598,642,"ROU","Romania","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77599,642,"ROU","Romania","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77600,642,"ROU","Romania","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77601,642,"ROU","Romania","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77602,642,"ROU","Romania","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77603,642,"ROU","Romania","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77604,642,"ROU","Romania","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77605,642,"ROU","Romania","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ROU/rou_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77606,646,"RWA","Rwanda","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77607,646,"RWA","Rwanda","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77608,646,"RWA","Rwanda","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77609,646,"RWA","Rwanda","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77610,646,"RWA","Rwanda","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77611,646,"RWA","Rwanda","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77612,646,"RWA","Rwanda","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77613,646,"RWA","Rwanda","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77614,646,"RWA","Rwanda","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77615,646,"RWA","Rwanda","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77616,646,"RWA","Rwanda","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77617,646,"RWA","Rwanda","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77618,646,"RWA","Rwanda","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77619,646,"RWA","Rwanda","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77620,646,"RWA","Rwanda","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77621,646,"RWA","Rwanda","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77622,646,"RWA","Rwanda","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77623,646,"RWA","Rwanda","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77624,646,"RWA","Rwanda","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77625,646,"RWA","Rwanda","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77626,646,"RWA","Rwanda","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77627,646,"RWA","Rwanda","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77628,646,"RWA","Rwanda","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77629,646,"RWA","Rwanda","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77630,646,"RWA","Rwanda","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77631,646,"RWA","Rwanda","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77632,646,"RWA","Rwanda","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77633,646,"RWA","Rwanda","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77634,646,"RWA","Rwanda","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77635,646,"RWA","Rwanda","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77636,646,"RWA","Rwanda","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77637,646,"RWA","Rwanda","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77638,646,"RWA","Rwanda","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77639,646,"RWA","Rwanda","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77640,646,"RWA","Rwanda","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77641,646,"RWA","Rwanda","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/RWA/rwa_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77642,652,"BLM","Saint Barthelemy","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77643,652,"BLM","Saint Barthelemy","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77644,652,"BLM","Saint Barthelemy","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77645,652,"BLM","Saint Barthelemy","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77646,652,"BLM","Saint Barthelemy","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77647,652,"BLM","Saint Barthelemy","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77648,652,"BLM","Saint Barthelemy","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77649,652,"BLM","Saint Barthelemy","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77650,652,"BLM","Saint Barthelemy","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77651,652,"BLM","Saint Barthelemy","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77652,652,"BLM","Saint Barthelemy","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77653,652,"BLM","Saint Barthelemy","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77654,652,"BLM","Saint Barthelemy","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77655,652,"BLM","Saint Barthelemy","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77656,652,"BLM","Saint Barthelemy","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77657,652,"BLM","Saint Barthelemy","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77658,652,"BLM","Saint Barthelemy","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77659,652,"BLM","Saint Barthelemy","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77660,652,"BLM","Saint Barthelemy","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77661,652,"BLM","Saint Barthelemy","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77662,652,"BLM","Saint Barthelemy","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77663,652,"BLM","Saint Barthelemy","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77664,652,"BLM","Saint Barthelemy","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77665,652,"BLM","Saint Barthelemy","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77666,652,"BLM","Saint Barthelemy","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77667,652,"BLM","Saint Barthelemy","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77668,652,"BLM","Saint Barthelemy","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77669,652,"BLM","Saint Barthelemy","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77670,652,"BLM","Saint Barthelemy","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77671,652,"BLM","Saint Barthelemy","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77672,652,"BLM","Saint Barthelemy","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77673,652,"BLM","Saint Barthelemy","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77674,652,"BLM","Saint Barthelemy","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77675,652,"BLM","Saint Barthelemy","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77676,652,"BLM","Saint Barthelemy","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77677,652,"BLM","Saint Barthelemy","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BLM/blm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77678,654,"SHN","Saint Helena","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77679,654,"SHN","Saint Helena","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77680,654,"SHN","Saint Helena","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77681,654,"SHN","Saint Helena","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77682,654,"SHN","Saint Helena","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77683,654,"SHN","Saint Helena","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77684,654,"SHN","Saint Helena","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77685,654,"SHN","Saint Helena","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77686,654,"SHN","Saint Helena","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77687,654,"SHN","Saint Helena","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77688,654,"SHN","Saint Helena","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77689,654,"SHN","Saint Helena","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77690,654,"SHN","Saint Helena","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77691,654,"SHN","Saint Helena","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77692,654,"SHN","Saint Helena","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77693,654,"SHN","Saint Helena","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77694,654,"SHN","Saint Helena","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77695,654,"SHN","Saint Helena","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77696,654,"SHN","Saint Helena","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77697,654,"SHN","Saint Helena","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77698,654,"SHN","Saint Helena","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77699,654,"SHN","Saint Helena","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77700,654,"SHN","Saint Helena","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77701,654,"SHN","Saint Helena","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77702,654,"SHN","Saint Helena","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77703,654,"SHN","Saint Helena","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77704,654,"SHN","Saint Helena","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77705,654,"SHN","Saint Helena","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77706,654,"SHN","Saint Helena","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77707,654,"SHN","Saint Helena","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77708,654,"SHN","Saint Helena","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77709,654,"SHN","Saint Helena","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77710,654,"SHN","Saint Helena","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77711,654,"SHN","Saint Helena","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77712,654,"SHN","Saint Helena","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77713,654,"SHN","Saint Helena","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SHN/shn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77714,659,"KNA","Saint Kitts and Nevis","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77715,659,"KNA","Saint Kitts and Nevis","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77716,659,"KNA","Saint Kitts and Nevis","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77717,659,"KNA","Saint Kitts and Nevis","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77718,659,"KNA","Saint Kitts and Nevis","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77719,659,"KNA","Saint Kitts and Nevis","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77720,659,"KNA","Saint Kitts and Nevis","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77721,659,"KNA","Saint Kitts and Nevis","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77722,659,"KNA","Saint Kitts and Nevis","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77723,659,"KNA","Saint Kitts and Nevis","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77724,659,"KNA","Saint Kitts and Nevis","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77725,659,"KNA","Saint Kitts and Nevis","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77726,659,"KNA","Saint Kitts and Nevis","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77727,659,"KNA","Saint Kitts and Nevis","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77728,659,"KNA","Saint Kitts and Nevis","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77729,659,"KNA","Saint Kitts and Nevis","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77730,659,"KNA","Saint Kitts and Nevis","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77731,659,"KNA","Saint Kitts and Nevis","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77732,659,"KNA","Saint Kitts and Nevis","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77733,659,"KNA","Saint Kitts and Nevis","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77734,659,"KNA","Saint Kitts and Nevis","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77735,659,"KNA","Saint Kitts and Nevis","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77736,659,"KNA","Saint Kitts and Nevis","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77737,659,"KNA","Saint Kitts and Nevis","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77738,659,"KNA","Saint Kitts and Nevis","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77739,659,"KNA","Saint Kitts and Nevis","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77740,659,"KNA","Saint Kitts and Nevis","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77741,659,"KNA","Saint Kitts and Nevis","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77742,659,"KNA","Saint Kitts and Nevis","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77743,659,"KNA","Saint Kitts and Nevis","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77744,659,"KNA","Saint Kitts and Nevis","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77745,659,"KNA","Saint Kitts and Nevis","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77746,659,"KNA","Saint Kitts and Nevis","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77747,659,"KNA","Saint Kitts and Nevis","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77748,659,"KNA","Saint Kitts and Nevis","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77749,659,"KNA","Saint Kitts and Nevis","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KNA/kna_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77750,660,"AIA","Anguilla","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77751,660,"AIA","Anguilla","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77752,660,"AIA","Anguilla","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77753,660,"AIA","Anguilla","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77754,660,"AIA","Anguilla","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77755,660,"AIA","Anguilla","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77756,660,"AIA","Anguilla","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77757,660,"AIA","Anguilla","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77758,660,"AIA","Anguilla","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77759,660,"AIA","Anguilla","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77760,660,"AIA","Anguilla","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77761,660,"AIA","Anguilla","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77762,660,"AIA","Anguilla","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77763,660,"AIA","Anguilla","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77764,660,"AIA","Anguilla","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77765,660,"AIA","Anguilla","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77766,660,"AIA","Anguilla","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77767,660,"AIA","Anguilla","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77768,660,"AIA","Anguilla","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77769,660,"AIA","Anguilla","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77770,660,"AIA","Anguilla","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77771,660,"AIA","Anguilla","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77772,660,"AIA","Anguilla","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77773,660,"AIA","Anguilla","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77774,660,"AIA","Anguilla","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77775,660,"AIA","Anguilla","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77776,660,"AIA","Anguilla","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77777,660,"AIA","Anguilla","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77778,660,"AIA","Anguilla","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77779,660,"AIA","Anguilla","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77780,660,"AIA","Anguilla","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77781,660,"AIA","Anguilla","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77782,660,"AIA","Anguilla","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77783,660,"AIA","Anguilla","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77784,660,"AIA","Anguilla","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77785,660,"AIA","Anguilla","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/AIA/aia_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77786,662,"LCA","Saint Lucia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77787,662,"LCA","Saint Lucia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77788,662,"LCA","Saint Lucia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77789,662,"LCA","Saint Lucia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77790,662,"LCA","Saint Lucia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77791,662,"LCA","Saint Lucia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77792,662,"LCA","Saint Lucia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77793,662,"LCA","Saint Lucia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77794,662,"LCA","Saint Lucia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77795,662,"LCA","Saint Lucia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77796,662,"LCA","Saint Lucia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77797,662,"LCA","Saint Lucia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77798,662,"LCA","Saint Lucia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77799,662,"LCA","Saint Lucia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77800,662,"LCA","Saint Lucia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77801,662,"LCA","Saint Lucia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77802,662,"LCA","Saint Lucia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77803,662,"LCA","Saint Lucia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77804,662,"LCA","Saint Lucia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77805,662,"LCA","Saint Lucia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77806,662,"LCA","Saint Lucia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77807,662,"LCA","Saint Lucia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77808,662,"LCA","Saint Lucia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77809,662,"LCA","Saint Lucia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77810,662,"LCA","Saint Lucia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77811,662,"LCA","Saint Lucia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77812,662,"LCA","Saint Lucia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77813,662,"LCA","Saint Lucia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77814,662,"LCA","Saint Lucia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77815,662,"LCA","Saint Lucia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77816,662,"LCA","Saint Lucia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77817,662,"LCA","Saint Lucia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77818,662,"LCA","Saint Lucia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77819,662,"LCA","Saint Lucia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77820,662,"LCA","Saint Lucia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77821,662,"LCA","Saint Lucia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/LCA/lca_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77822,663,"MAF","Saint Martin (French part)","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77823,663,"MAF","Saint Martin (French part)","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77824,663,"MAF","Saint Martin (French part)","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77825,663,"MAF","Saint Martin (French part)","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77826,663,"MAF","Saint Martin (French part)","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77827,663,"MAF","Saint Martin (French part)","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77828,663,"MAF","Saint Martin (French part)","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77829,663,"MAF","Saint Martin (French part)","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77830,663,"MAF","Saint Martin (French part)","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77831,663,"MAF","Saint Martin (French part)","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77832,663,"MAF","Saint Martin (French part)","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77833,663,"MAF","Saint Martin (French part)","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77834,663,"MAF","Saint Martin (French part)","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77835,663,"MAF","Saint Martin (French part)","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77836,663,"MAF","Saint Martin (French part)","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77837,663,"MAF","Saint Martin (French part)","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77838,663,"MAF","Saint Martin (French part)","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77839,663,"MAF","Saint Martin (French part)","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77840,663,"MAF","Saint Martin (French part)","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77841,663,"MAF","Saint Martin (French part)","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77842,663,"MAF","Saint Martin (French part)","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77843,663,"MAF","Saint Martin (French part)","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77844,663,"MAF","Saint Martin (French part)","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77845,663,"MAF","Saint Martin (French part)","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77846,663,"MAF","Saint Martin (French part)","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77847,663,"MAF","Saint Martin (French part)","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77848,663,"MAF","Saint Martin (French part)","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77849,663,"MAF","Saint Martin (French part)","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77850,663,"MAF","Saint Martin (French part)","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77851,663,"MAF","Saint Martin (French part)","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77852,663,"MAF","Saint Martin (French part)","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77853,663,"MAF","Saint Martin (French part)","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77854,663,"MAF","Saint Martin (French part)","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77855,663,"MAF","Saint Martin (French part)","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77856,663,"MAF","Saint Martin (French part)","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77857,663,"MAF","Saint Martin (French part)","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MAF/maf_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77858,666,"SPM","Saint Pierre and Miquelon","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77859,666,"SPM","Saint Pierre and Miquelon","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77860,666,"SPM","Saint Pierre and Miquelon","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77861,666,"SPM","Saint Pierre and Miquelon","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77862,666,"SPM","Saint Pierre and Miquelon","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77863,666,"SPM","Saint Pierre and Miquelon","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77864,666,"SPM","Saint Pierre and Miquelon","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77865,666,"SPM","Saint Pierre and Miquelon","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77866,666,"SPM","Saint Pierre and Miquelon","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77867,666,"SPM","Saint Pierre and Miquelon","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77868,666,"SPM","Saint Pierre and Miquelon","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77869,666,"SPM","Saint Pierre and Miquelon","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77870,666,"SPM","Saint Pierre and Miquelon","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77871,666,"SPM","Saint Pierre and Miquelon","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77872,666,"SPM","Saint Pierre and Miquelon","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77873,666,"SPM","Saint Pierre and Miquelon","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77874,666,"SPM","Saint Pierre and Miquelon","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77875,666,"SPM","Saint Pierre and Miquelon","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77876,666,"SPM","Saint Pierre and Miquelon","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77877,666,"SPM","Saint Pierre and Miquelon","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77878,666,"SPM","Saint Pierre and Miquelon","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77879,666,"SPM","Saint Pierre and Miquelon","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77880,666,"SPM","Saint Pierre and Miquelon","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77881,666,"SPM","Saint Pierre and Miquelon","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77882,666,"SPM","Saint Pierre and Miquelon","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77883,666,"SPM","Saint Pierre and Miquelon","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77884,666,"SPM","Saint Pierre and Miquelon","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77885,666,"SPM","Saint Pierre and Miquelon","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77886,666,"SPM","Saint Pierre and Miquelon","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77887,666,"SPM","Saint Pierre and Miquelon","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77888,666,"SPM","Saint Pierre and Miquelon","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77889,666,"SPM","Saint Pierre and Miquelon","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77890,666,"SPM","Saint Pierre and Miquelon","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77891,666,"SPM","Saint Pierre and Miquelon","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77892,666,"SPM","Saint Pierre and Miquelon","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77893,666,"SPM","Saint Pierre and Miquelon","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPM/spm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77894,670,"VCT","Saint Vincent and the Grenadines","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77895,670,"VCT","Saint Vincent and the Grenadines","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77896,670,"VCT","Saint Vincent and the Grenadines","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77897,670,"VCT","Saint Vincent and the Grenadines","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77898,670,"VCT","Saint Vincent and the Grenadines","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77899,670,"VCT","Saint Vincent and the Grenadines","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77900,670,"VCT","Saint Vincent and the Grenadines","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77901,670,"VCT","Saint Vincent and the Grenadines","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77902,670,"VCT","Saint Vincent and the Grenadines","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77903,670,"VCT","Saint Vincent and the Grenadines","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77904,670,"VCT","Saint Vincent and the Grenadines","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77905,670,"VCT","Saint Vincent and the Grenadines","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77906,670,"VCT","Saint Vincent and the Grenadines","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77907,670,"VCT","Saint Vincent and the Grenadines","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77908,670,"VCT","Saint Vincent and the Grenadines","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77909,670,"VCT","Saint Vincent and the Grenadines","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77910,670,"VCT","Saint Vincent and the Grenadines","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77911,670,"VCT","Saint Vincent and the Grenadines","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77912,670,"VCT","Saint Vincent and the Grenadines","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77913,670,"VCT","Saint Vincent and the Grenadines","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77914,670,"VCT","Saint Vincent and the Grenadines","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77915,670,"VCT","Saint Vincent and the Grenadines","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77916,670,"VCT","Saint Vincent and the Grenadines","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77917,670,"VCT","Saint Vincent and the Grenadines","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77918,670,"VCT","Saint Vincent and the Grenadines","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77919,670,"VCT","Saint Vincent and the Grenadines","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77920,670,"VCT","Saint Vincent and the Grenadines","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77921,670,"VCT","Saint Vincent and the Grenadines","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77922,670,"VCT","Saint Vincent and the Grenadines","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77923,670,"VCT","Saint Vincent and the Grenadines","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77924,670,"VCT","Saint Vincent and the Grenadines","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77925,670,"VCT","Saint Vincent and the Grenadines","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77926,670,"VCT","Saint Vincent and the Grenadines","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77927,670,"VCT","Saint Vincent and the Grenadines","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77928,670,"VCT","Saint Vincent and the Grenadines","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77929,670,"VCT","Saint Vincent and the Grenadines","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VCT/vct_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77930,674,"SMR","San Marino","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77931,674,"SMR","San Marino","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77932,674,"SMR","San Marino","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77933,674,"SMR","San Marino","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77934,674,"SMR","San Marino","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77935,674,"SMR","San Marino","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77936,674,"SMR","San Marino","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77937,674,"SMR","San Marino","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77938,674,"SMR","San Marino","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77939,674,"SMR","San Marino","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77940,674,"SMR","San Marino","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77941,674,"SMR","San Marino","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77942,674,"SMR","San Marino","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77943,674,"SMR","San Marino","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77944,674,"SMR","San Marino","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77945,674,"SMR","San Marino","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77946,674,"SMR","San Marino","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77947,674,"SMR","San Marino","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77948,674,"SMR","San Marino","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77949,674,"SMR","San Marino","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77950,674,"SMR","San Marino","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77951,674,"SMR","San Marino","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77952,674,"SMR","San Marino","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77953,674,"SMR","San Marino","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77954,674,"SMR","San Marino","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77955,674,"SMR","San Marino","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77956,674,"SMR","San Marino","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77957,674,"SMR","San Marino","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77958,674,"SMR","San Marino","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77959,674,"SMR","San Marino","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77960,674,"SMR","San Marino","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77961,674,"SMR","San Marino","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77962,674,"SMR","San Marino","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77963,674,"SMR","San Marino","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
77964,674,"SMR","San Marino","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
77965,674,"SMR","San Marino","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SMR/smr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
77966,678,"STP","Sao Tome and Principe","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
77967,678,"STP","Sao Tome and Principe","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
77968,678,"STP","Sao Tome and Principe","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
77969,678,"STP","Sao Tome and Principe","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
77970,678,"STP","Sao Tome and Principe","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
77971,678,"STP","Sao Tome and Principe","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
77972,678,"STP","Sao Tome and Principe","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
77973,678,"STP","Sao Tome and Principe","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
77974,678,"STP","Sao Tome and Principe","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
77975,678,"STP","Sao Tome and Principe","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
77976,678,"STP","Sao Tome and Principe","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
77977,678,"STP","Sao Tome and Principe","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
77978,678,"STP","Sao Tome and Principe","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
77979,678,"STP","Sao Tome and Principe","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
77980,678,"STP","Sao Tome and Principe","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
77981,678,"STP","Sao Tome and Principe","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
77982,678,"STP","Sao Tome and Principe","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
77983,678,"STP","Sao Tome and Principe","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
77984,678,"STP","Sao Tome and Principe","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
77985,678,"STP","Sao Tome and Principe","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
77986,678,"STP","Sao Tome and Principe","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
77987,678,"STP","Sao Tome and Principe","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
77988,678,"STP","Sao Tome and Principe","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
77989,678,"STP","Sao Tome and Principe","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
77990,678,"STP","Sao Tome and Principe","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
77991,678,"STP","Sao Tome and Principe","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
77992,678,"STP","Sao Tome and Principe","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
77993,678,"STP","Sao Tome and Principe","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
77994,678,"STP","Sao Tome and Principe","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
77995,678,"STP","Sao Tome and Principe","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
77996,678,"STP","Sao Tome and Principe","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
77997,678,"STP","Sao Tome and Principe","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
77998,678,"STP","Sao Tome and Principe","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
77999,678,"STP","Sao Tome and Principe","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78000,678,"STP","Sao Tome and Principe","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78001,678,"STP","Sao Tome and Principe","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/STP/stp_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78002,682,"SAU","Saudi Arabia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78003,682,"SAU","Saudi Arabia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78004,682,"SAU","Saudi Arabia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78005,682,"SAU","Saudi Arabia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78006,682,"SAU","Saudi Arabia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78007,682,"SAU","Saudi Arabia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78008,682,"SAU","Saudi Arabia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78009,682,"SAU","Saudi Arabia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78010,682,"SAU","Saudi Arabia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78011,682,"SAU","Saudi Arabia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78012,682,"SAU","Saudi Arabia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78013,682,"SAU","Saudi Arabia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78014,682,"SAU","Saudi Arabia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78015,682,"SAU","Saudi Arabia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78016,682,"SAU","Saudi Arabia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78017,682,"SAU","Saudi Arabia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78018,682,"SAU","Saudi Arabia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78019,682,"SAU","Saudi Arabia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78020,682,"SAU","Saudi Arabia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78021,682,"SAU","Saudi Arabia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78022,682,"SAU","Saudi Arabia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78023,682,"SAU","Saudi Arabia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78024,682,"SAU","Saudi Arabia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78025,682,"SAU","Saudi Arabia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78026,682,"SAU","Saudi Arabia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78027,682,"SAU","Saudi Arabia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78028,682,"SAU","Saudi Arabia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78029,682,"SAU","Saudi Arabia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78030,682,"SAU","Saudi Arabia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78031,682,"SAU","Saudi Arabia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78032,682,"SAU","Saudi Arabia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78033,682,"SAU","Saudi Arabia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78034,682,"SAU","Saudi Arabia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78035,682,"SAU","Saudi Arabia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78036,682,"SAU","Saudi Arabia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78037,682,"SAU","Saudi Arabia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SAU/sau_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78038,686,"SEN","Senegal","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78039,686,"SEN","Senegal","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78040,686,"SEN","Senegal","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78041,686,"SEN","Senegal","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78042,686,"SEN","Senegal","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78043,686,"SEN","Senegal","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78044,686,"SEN","Senegal","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78045,686,"SEN","Senegal","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78046,686,"SEN","Senegal","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78047,686,"SEN","Senegal","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78048,686,"SEN","Senegal","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78049,686,"SEN","Senegal","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78050,686,"SEN","Senegal","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78051,686,"SEN","Senegal","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78052,686,"SEN","Senegal","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78053,686,"SEN","Senegal","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78054,686,"SEN","Senegal","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78055,686,"SEN","Senegal","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78056,686,"SEN","Senegal","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78057,686,"SEN","Senegal","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78058,686,"SEN","Senegal","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78059,686,"SEN","Senegal","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78060,686,"SEN","Senegal","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78061,686,"SEN","Senegal","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78062,686,"SEN","Senegal","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78063,686,"SEN","Senegal","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78064,686,"SEN","Senegal","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78065,686,"SEN","Senegal","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78066,686,"SEN","Senegal","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78067,686,"SEN","Senegal","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78068,686,"SEN","Senegal","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78069,686,"SEN","Senegal","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78070,686,"SEN","Senegal","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78071,686,"SEN","Senegal","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78072,686,"SEN","Senegal","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78073,686,"SEN","Senegal","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SEN/sen_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78074,688,"SRB","Serbia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78075,688,"SRB","Serbia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78076,688,"SRB","Serbia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78077,688,"SRB","Serbia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78078,688,"SRB","Serbia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78079,688,"SRB","Serbia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78080,688,"SRB","Serbia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78081,688,"SRB","Serbia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78082,688,"SRB","Serbia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78083,688,"SRB","Serbia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78084,688,"SRB","Serbia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78085,688,"SRB","Serbia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78086,688,"SRB","Serbia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78087,688,"SRB","Serbia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78088,688,"SRB","Serbia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78089,688,"SRB","Serbia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78090,688,"SRB","Serbia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78091,688,"SRB","Serbia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78092,688,"SRB","Serbia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78093,688,"SRB","Serbia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78094,688,"SRB","Serbia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78095,688,"SRB","Serbia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78096,688,"SRB","Serbia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78097,688,"SRB","Serbia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78098,688,"SRB","Serbia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78099,688,"SRB","Serbia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78100,688,"SRB","Serbia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78101,688,"SRB","Serbia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78102,688,"SRB","Serbia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78103,688,"SRB","Serbia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78104,688,"SRB","Serbia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78105,688,"SRB","Serbia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78106,688,"SRB","Serbia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78107,688,"SRB","Serbia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78108,688,"SRB","Serbia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78109,688,"SRB","Serbia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SRB/srb_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78110,690,"SYC","Seychelles","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78111,690,"SYC","Seychelles","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78112,690,"SYC","Seychelles","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78113,690,"SYC","Seychelles","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78114,690,"SYC","Seychelles","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78115,690,"SYC","Seychelles","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78116,690,"SYC","Seychelles","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78117,690,"SYC","Seychelles","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78118,690,"SYC","Seychelles","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78119,690,"SYC","Seychelles","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78120,690,"SYC","Seychelles","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78121,690,"SYC","Seychelles","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78122,690,"SYC","Seychelles","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78123,690,"SYC","Seychelles","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78124,690,"SYC","Seychelles","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78125,690,"SYC","Seychelles","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78126,690,"SYC","Seychelles","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78127,690,"SYC","Seychelles","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78128,690,"SYC","Seychelles","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78129,690,"SYC","Seychelles","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78130,690,"SYC","Seychelles","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78131,690,"SYC","Seychelles","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78132,690,"SYC","Seychelles","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78133,690,"SYC","Seychelles","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78134,690,"SYC","Seychelles","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78135,690,"SYC","Seychelles","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78136,690,"SYC","Seychelles","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78137,690,"SYC","Seychelles","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78138,690,"SYC","Seychelles","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78139,690,"SYC","Seychelles","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78140,690,"SYC","Seychelles","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78141,690,"SYC","Seychelles","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78142,690,"SYC","Seychelles","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78143,690,"SYC","Seychelles","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78144,690,"SYC","Seychelles","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78145,690,"SYC","Seychelles","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYC/syc_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78146,694,"SLE","Sierra Leone","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78147,694,"SLE","Sierra Leone","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78148,694,"SLE","Sierra Leone","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78149,694,"SLE","Sierra Leone","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78150,694,"SLE","Sierra Leone","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78151,694,"SLE","Sierra Leone","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78152,694,"SLE","Sierra Leone","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78153,694,"SLE","Sierra Leone","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78154,694,"SLE","Sierra Leone","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78155,694,"SLE","Sierra Leone","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78156,694,"SLE","Sierra Leone","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78157,694,"SLE","Sierra Leone","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78158,694,"SLE","Sierra Leone","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78159,694,"SLE","Sierra Leone","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78160,694,"SLE","Sierra Leone","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78161,694,"SLE","Sierra Leone","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78162,694,"SLE","Sierra Leone","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78163,694,"SLE","Sierra Leone","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78164,694,"SLE","Sierra Leone","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78165,694,"SLE","Sierra Leone","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78166,694,"SLE","Sierra Leone","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78167,694,"SLE","Sierra Leone","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78168,694,"SLE","Sierra Leone","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78169,694,"SLE","Sierra Leone","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78170,694,"SLE","Sierra Leone","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78171,694,"SLE","Sierra Leone","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78172,694,"SLE","Sierra Leone","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78173,694,"SLE","Sierra Leone","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78174,694,"SLE","Sierra Leone","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78175,694,"SLE","Sierra Leone","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78176,694,"SLE","Sierra Leone","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78177,694,"SLE","Sierra Leone","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78178,694,"SLE","Sierra Leone","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78179,694,"SLE","Sierra Leone","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78180,694,"SLE","Sierra Leone","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78181,694,"SLE","Sierra Leone","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SLE/sle_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78182,702,"SGP","Singapore","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78183,702,"SGP","Singapore","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78184,702,"SGP","Singapore","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78185,702,"SGP","Singapore","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78186,702,"SGP","Singapore","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78187,702,"SGP","Singapore","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78188,702,"SGP","Singapore","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78189,702,"SGP","Singapore","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78190,702,"SGP","Singapore","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78191,702,"SGP","Singapore","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78192,702,"SGP","Singapore","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78193,702,"SGP","Singapore","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78194,702,"SGP","Singapore","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78195,702,"SGP","Singapore","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78196,702,"SGP","Singapore","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78197,702,"SGP","Singapore","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78198,702,"SGP","Singapore","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78199,702,"SGP","Singapore","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78200,702,"SGP","Singapore","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78201,702,"SGP","Singapore","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78202,702,"SGP","Singapore","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78203,702,"SGP","Singapore","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78204,702,"SGP","Singapore","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78205,702,"SGP","Singapore","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78206,702,"SGP","Singapore","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78207,702,"SGP","Singapore","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78208,702,"SGP","Singapore","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78209,702,"SGP","Singapore","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78210,702,"SGP","Singapore","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78211,702,"SGP","Singapore","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78212,702,"SGP","Singapore","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78213,702,"SGP","Singapore","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78214,702,"SGP","Singapore","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78215,702,"SGP","Singapore","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78216,702,"SGP","Singapore","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78217,702,"SGP","Singapore","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SGP/sgp_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78218,703,"SVK","Slovakia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78219,703,"SVK","Slovakia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78220,703,"SVK","Slovakia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78221,703,"SVK","Slovakia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78222,703,"SVK","Slovakia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78223,703,"SVK","Slovakia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78224,703,"SVK","Slovakia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78225,703,"SVK","Slovakia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78226,703,"SVK","Slovakia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78227,703,"SVK","Slovakia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78228,703,"SVK","Slovakia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78229,703,"SVK","Slovakia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78230,703,"SVK","Slovakia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78231,703,"SVK","Slovakia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78232,703,"SVK","Slovakia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78233,703,"SVK","Slovakia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78234,703,"SVK","Slovakia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78235,703,"SVK","Slovakia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78236,703,"SVK","Slovakia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78237,703,"SVK","Slovakia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78238,703,"SVK","Slovakia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78239,703,"SVK","Slovakia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78240,703,"SVK","Slovakia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78241,703,"SVK","Slovakia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78242,703,"SVK","Slovakia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78243,703,"SVK","Slovakia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78244,703,"SVK","Slovakia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78245,703,"SVK","Slovakia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78246,703,"SVK","Slovakia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78247,703,"SVK","Slovakia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78248,703,"SVK","Slovakia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78249,703,"SVK","Slovakia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78250,703,"SVK","Slovakia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78251,703,"SVK","Slovakia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78252,703,"SVK","Slovakia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78253,703,"SVK","Slovakia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVK/svk_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78254,704,"VNM","Vietnam","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78255,704,"VNM","Vietnam","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78256,704,"VNM","Vietnam","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78257,704,"VNM","Vietnam","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78258,704,"VNM","Vietnam","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78259,704,"VNM","Vietnam","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78260,704,"VNM","Vietnam","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78261,704,"VNM","Vietnam","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78262,704,"VNM","Vietnam","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78263,704,"VNM","Vietnam","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78264,704,"VNM","Vietnam","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78265,704,"VNM","Vietnam","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78266,704,"VNM","Vietnam","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78267,704,"VNM","Vietnam","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78268,704,"VNM","Vietnam","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78269,704,"VNM","Vietnam","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78270,704,"VNM","Vietnam","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78271,704,"VNM","Vietnam","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78272,704,"VNM","Vietnam","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78273,704,"VNM","Vietnam","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78274,704,"VNM","Vietnam","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78275,704,"VNM","Vietnam","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78276,704,"VNM","Vietnam","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78277,704,"VNM","Vietnam","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78278,704,"VNM","Vietnam","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78279,704,"VNM","Vietnam","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78280,704,"VNM","Vietnam","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78281,704,"VNM","Vietnam","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78282,704,"VNM","Vietnam","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78283,704,"VNM","Vietnam","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78284,704,"VNM","Vietnam","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78285,704,"VNM","Vietnam","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78286,704,"VNM","Vietnam","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78287,704,"VNM","Vietnam","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78288,704,"VNM","Vietnam","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78289,704,"VNM","Vietnam","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VNM/vnm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78290,705,"SVN","Slovenia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78291,705,"SVN","Slovenia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78292,705,"SVN","Slovenia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78293,705,"SVN","Slovenia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78294,705,"SVN","Slovenia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78295,705,"SVN","Slovenia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78296,705,"SVN","Slovenia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78297,705,"SVN","Slovenia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78298,705,"SVN","Slovenia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78299,705,"SVN","Slovenia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78300,705,"SVN","Slovenia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78301,705,"SVN","Slovenia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78302,705,"SVN","Slovenia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78303,705,"SVN","Slovenia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78304,705,"SVN","Slovenia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78305,705,"SVN","Slovenia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78306,705,"SVN","Slovenia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78307,705,"SVN","Slovenia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78308,705,"SVN","Slovenia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78309,705,"SVN","Slovenia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78310,705,"SVN","Slovenia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78311,705,"SVN","Slovenia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78312,705,"SVN","Slovenia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78313,705,"SVN","Slovenia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78314,705,"SVN","Slovenia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78315,705,"SVN","Slovenia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78316,705,"SVN","Slovenia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78317,705,"SVN","Slovenia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78318,705,"SVN","Slovenia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78319,705,"SVN","Slovenia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78320,705,"SVN","Slovenia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78321,705,"SVN","Slovenia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78322,705,"SVN","Slovenia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78323,705,"SVN","Slovenia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78324,705,"SVN","Slovenia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78325,705,"SVN","Slovenia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SVN/svn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78326,706,"SOM","Somalia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78327,706,"SOM","Somalia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78328,706,"SOM","Somalia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78329,706,"SOM","Somalia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78330,706,"SOM","Somalia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78331,706,"SOM","Somalia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78332,706,"SOM","Somalia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78333,706,"SOM","Somalia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78334,706,"SOM","Somalia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78335,706,"SOM","Somalia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78336,706,"SOM","Somalia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78337,706,"SOM","Somalia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78338,706,"SOM","Somalia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78339,706,"SOM","Somalia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78340,706,"SOM","Somalia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78341,706,"SOM","Somalia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78342,706,"SOM","Somalia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78343,706,"SOM","Somalia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78344,706,"SOM","Somalia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78345,706,"SOM","Somalia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78346,706,"SOM","Somalia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78347,706,"SOM","Somalia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78348,706,"SOM","Somalia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78349,706,"SOM","Somalia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78350,706,"SOM","Somalia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78351,706,"SOM","Somalia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78352,706,"SOM","Somalia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78353,706,"SOM","Somalia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78354,706,"SOM","Somalia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78355,706,"SOM","Somalia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78356,706,"SOM","Somalia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78357,706,"SOM","Somalia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78358,706,"SOM","Somalia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78359,706,"SOM","Somalia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78360,706,"SOM","Somalia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78361,706,"SOM","Somalia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SOM/som_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78362,710,"ZAF","South Africa","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78363,710,"ZAF","South Africa","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78364,710,"ZAF","South Africa","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78365,710,"ZAF","South Africa","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78366,710,"ZAF","South Africa","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78367,710,"ZAF","South Africa","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78368,710,"ZAF","South Africa","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78369,710,"ZAF","South Africa","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78370,710,"ZAF","South Africa","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78371,710,"ZAF","South Africa","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78372,710,"ZAF","South Africa","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78373,710,"ZAF","South Africa","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78374,710,"ZAF","South Africa","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78375,710,"ZAF","South Africa","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78376,710,"ZAF","South Africa","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78377,710,"ZAF","South Africa","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78378,710,"ZAF","South Africa","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78379,710,"ZAF","South Africa","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78380,710,"ZAF","South Africa","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78381,710,"ZAF","South Africa","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78382,710,"ZAF","South Africa","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78383,710,"ZAF","South Africa","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78384,710,"ZAF","South Africa","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78385,710,"ZAF","South Africa","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78386,710,"ZAF","South Africa","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78387,710,"ZAF","South Africa","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78388,710,"ZAF","South Africa","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78389,710,"ZAF","South Africa","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78390,710,"ZAF","South Africa","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78391,710,"ZAF","South Africa","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78392,710,"ZAF","South Africa","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78393,710,"ZAF","South Africa","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78394,710,"ZAF","South Africa","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78395,710,"ZAF","South Africa","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78396,710,"ZAF","South Africa","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78397,710,"ZAF","South Africa","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZAF/zaf_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78398,716,"ZWE","Zimbabwe","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78399,716,"ZWE","Zimbabwe","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78400,716,"ZWE","Zimbabwe","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78401,716,"ZWE","Zimbabwe","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78402,716,"ZWE","Zimbabwe","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78403,716,"ZWE","Zimbabwe","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78404,716,"ZWE","Zimbabwe","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78405,716,"ZWE","Zimbabwe","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78406,716,"ZWE","Zimbabwe","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78407,716,"ZWE","Zimbabwe","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78408,716,"ZWE","Zimbabwe","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78409,716,"ZWE","Zimbabwe","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78410,716,"ZWE","Zimbabwe","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78411,716,"ZWE","Zimbabwe","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78412,716,"ZWE","Zimbabwe","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78413,716,"ZWE","Zimbabwe","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78414,716,"ZWE","Zimbabwe","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78415,716,"ZWE","Zimbabwe","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78416,716,"ZWE","Zimbabwe","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78417,716,"ZWE","Zimbabwe","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78418,716,"ZWE","Zimbabwe","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78419,716,"ZWE","Zimbabwe","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78420,716,"ZWE","Zimbabwe","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78421,716,"ZWE","Zimbabwe","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78422,716,"ZWE","Zimbabwe","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78423,716,"ZWE","Zimbabwe","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78424,716,"ZWE","Zimbabwe","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78425,716,"ZWE","Zimbabwe","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78426,716,"ZWE","Zimbabwe","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78427,716,"ZWE","Zimbabwe","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78428,716,"ZWE","Zimbabwe","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78429,716,"ZWE","Zimbabwe","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78430,716,"ZWE","Zimbabwe","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78431,716,"ZWE","Zimbabwe","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78432,716,"ZWE","Zimbabwe","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78433,716,"ZWE","Zimbabwe","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZWE/zwe_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78434,724,"ESP","Spain","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78435,724,"ESP","Spain","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78436,724,"ESP","Spain","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78437,724,"ESP","Spain","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78438,724,"ESP","Spain","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78439,724,"ESP","Spain","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78440,724,"ESP","Spain","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78441,724,"ESP","Spain","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78442,724,"ESP","Spain","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78443,724,"ESP","Spain","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78444,724,"ESP","Spain","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78445,724,"ESP","Spain","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78446,724,"ESP","Spain","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78447,724,"ESP","Spain","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78448,724,"ESP","Spain","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78449,724,"ESP","Spain","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78450,724,"ESP","Spain","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78451,724,"ESP","Spain","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78452,724,"ESP","Spain","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78453,724,"ESP","Spain","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78454,724,"ESP","Spain","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78455,724,"ESP","Spain","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78456,724,"ESP","Spain","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78457,724,"ESP","Spain","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78458,724,"ESP","Spain","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78459,724,"ESP","Spain","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78460,724,"ESP","Spain","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78461,724,"ESP","Spain","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78462,724,"ESP","Spain","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78463,724,"ESP","Spain","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78464,724,"ESP","Spain","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78465,724,"ESP","Spain","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78466,724,"ESP","Spain","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78467,724,"ESP","Spain","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78468,724,"ESP","Spain","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78469,724,"ESP","Spain","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESP/esp_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78470,728,"SSD","South Sudan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78471,728,"SSD","South Sudan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78472,728,"SSD","South Sudan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78473,728,"SSD","South Sudan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78474,728,"SSD","South Sudan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78475,728,"SSD","South Sudan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78476,728,"SSD","South Sudan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78477,728,"SSD","South Sudan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78478,728,"SSD","South Sudan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78479,728,"SSD","South Sudan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78480,728,"SSD","South Sudan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78481,728,"SSD","South Sudan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78482,728,"SSD","South Sudan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78483,728,"SSD","South Sudan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78484,728,"SSD","South Sudan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78485,728,"SSD","South Sudan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78486,728,"SSD","South Sudan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78487,728,"SSD","South Sudan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78488,728,"SSD","South Sudan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78489,728,"SSD","South Sudan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78490,728,"SSD","South Sudan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78491,728,"SSD","South Sudan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78492,728,"SSD","South Sudan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78493,728,"SSD","South Sudan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78494,728,"SSD","South Sudan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78495,728,"SSD","South Sudan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78496,728,"SSD","South Sudan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78497,728,"SSD","South Sudan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78498,728,"SSD","South Sudan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78499,728,"SSD","South Sudan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78500,728,"SSD","South Sudan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78501,728,"SSD","South Sudan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78502,728,"SSD","South Sudan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78503,728,"SSD","South Sudan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78504,728,"SSD","South Sudan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78505,728,"SSD","South Sudan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SSD/ssd_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78506,729,"SDN","Sudan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78507,729,"SDN","Sudan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78508,729,"SDN","Sudan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78509,729,"SDN","Sudan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78510,729,"SDN","Sudan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78511,729,"SDN","Sudan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78512,729,"SDN","Sudan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78513,729,"SDN","Sudan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78514,729,"SDN","Sudan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78515,729,"SDN","Sudan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78516,729,"SDN","Sudan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78517,729,"SDN","Sudan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78518,729,"SDN","Sudan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78519,729,"SDN","Sudan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78520,729,"SDN","Sudan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78521,729,"SDN","Sudan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78522,729,"SDN","Sudan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78523,729,"SDN","Sudan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78524,729,"SDN","Sudan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78525,729,"SDN","Sudan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78526,729,"SDN","Sudan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78527,729,"SDN","Sudan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78528,729,"SDN","Sudan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78529,729,"SDN","Sudan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78530,729,"SDN","Sudan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78531,729,"SDN","Sudan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78532,729,"SDN","Sudan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78533,729,"SDN","Sudan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78534,729,"SDN","Sudan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78535,729,"SDN","Sudan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78536,729,"SDN","Sudan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78537,729,"SDN","Sudan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78538,729,"SDN","Sudan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78539,729,"SDN","Sudan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78540,729,"SDN","Sudan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78541,729,"SDN","Sudan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SDN/sdn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78542,732,"ESH","Western Sahara","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78543,732,"ESH","Western Sahara","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78544,732,"ESH","Western Sahara","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78545,732,"ESH","Western Sahara","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78546,732,"ESH","Western Sahara","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78547,732,"ESH","Western Sahara","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78548,732,"ESH","Western Sahara","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78549,732,"ESH","Western Sahara","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78550,732,"ESH","Western Sahara","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78551,732,"ESH","Western Sahara","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78552,732,"ESH","Western Sahara","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78553,732,"ESH","Western Sahara","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78554,732,"ESH","Western Sahara","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78555,732,"ESH","Western Sahara","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78556,732,"ESH","Western Sahara","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78557,732,"ESH","Western Sahara","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78558,732,"ESH","Western Sahara","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78559,732,"ESH","Western Sahara","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78560,732,"ESH","Western Sahara","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78561,732,"ESH","Western Sahara","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78562,732,"ESH","Western Sahara","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78563,732,"ESH","Western Sahara","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78564,732,"ESH","Western Sahara","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78565,732,"ESH","Western Sahara","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78566,732,"ESH","Western Sahara","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78567,732,"ESH","Western Sahara","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78568,732,"ESH","Western Sahara","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78569,732,"ESH","Western Sahara","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78570,732,"ESH","Western Sahara","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78571,732,"ESH","Western Sahara","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78572,732,"ESH","Western Sahara","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78573,732,"ESH","Western Sahara","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78574,732,"ESH","Western Sahara","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78575,732,"ESH","Western Sahara","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78576,732,"ESH","Western Sahara","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78577,732,"ESH","Western Sahara","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ESH/esh_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78578,740,"SUR","Suriname","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78579,740,"SUR","Suriname","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78580,740,"SUR","Suriname","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78581,740,"SUR","Suriname","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78582,740,"SUR","Suriname","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78583,740,"SUR","Suriname","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78584,740,"SUR","Suriname","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78585,740,"SUR","Suriname","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78586,740,"SUR","Suriname","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78587,740,"SUR","Suriname","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78588,740,"SUR","Suriname","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78589,740,"SUR","Suriname","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78590,740,"SUR","Suriname","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78591,740,"SUR","Suriname","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78592,740,"SUR","Suriname","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78593,740,"SUR","Suriname","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78594,740,"SUR","Suriname","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78595,740,"SUR","Suriname","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78596,740,"SUR","Suriname","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78597,740,"SUR","Suriname","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78598,740,"SUR","Suriname","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78599,740,"SUR","Suriname","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78600,740,"SUR","Suriname","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78601,740,"SUR","Suriname","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78602,740,"SUR","Suriname","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78603,740,"SUR","Suriname","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78604,740,"SUR","Suriname","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78605,740,"SUR","Suriname","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78606,740,"SUR","Suriname","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78607,740,"SUR","Suriname","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78608,740,"SUR","Suriname","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78609,740,"SUR","Suriname","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78610,740,"SUR","Suriname","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78611,740,"SUR","Suriname","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78612,740,"SUR","Suriname","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78613,740,"SUR","Suriname","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SUR/sur_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78614,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78615,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78616,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78617,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78618,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78619,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78620,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78621,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78622,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78623,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78624,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78625,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78626,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78627,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78628,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78629,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78630,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78631,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78632,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78633,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78634,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78635,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78636,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78637,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78638,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78639,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78640,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78641,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78642,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78643,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78644,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78645,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78646,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78647,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78648,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78649,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SJM/sjm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78650,748,"SWZ","Swaziland","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78651,748,"SWZ","Swaziland","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78652,748,"SWZ","Swaziland","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78653,748,"SWZ","Swaziland","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78654,748,"SWZ","Swaziland","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78655,748,"SWZ","Swaziland","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78656,748,"SWZ","Swaziland","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78657,748,"SWZ","Swaziland","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78658,748,"SWZ","Swaziland","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78659,748,"SWZ","Swaziland","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78660,748,"SWZ","Swaziland","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78661,748,"SWZ","Swaziland","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78662,748,"SWZ","Swaziland","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78663,748,"SWZ","Swaziland","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78664,748,"SWZ","Swaziland","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78665,748,"SWZ","Swaziland","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78666,748,"SWZ","Swaziland","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78667,748,"SWZ","Swaziland","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78668,748,"SWZ","Swaziland","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78669,748,"SWZ","Swaziland","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78670,748,"SWZ","Swaziland","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78671,748,"SWZ","Swaziland","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78672,748,"SWZ","Swaziland","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78673,748,"SWZ","Swaziland","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78674,748,"SWZ","Swaziland","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78675,748,"SWZ","Swaziland","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78676,748,"SWZ","Swaziland","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78677,748,"SWZ","Swaziland","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78678,748,"SWZ","Swaziland","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78679,748,"SWZ","Swaziland","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78680,748,"SWZ","Swaziland","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78681,748,"SWZ","Swaziland","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78682,748,"SWZ","Swaziland","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78683,748,"SWZ","Swaziland","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78684,748,"SWZ","Swaziland","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78685,748,"SWZ","Swaziland","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWZ/swz_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78686,752,"SWE","Sweden","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78687,752,"SWE","Sweden","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78688,752,"SWE","Sweden","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78689,752,"SWE","Sweden","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78690,752,"SWE","Sweden","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78691,752,"SWE","Sweden","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78692,752,"SWE","Sweden","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78693,752,"SWE","Sweden","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78694,752,"SWE","Sweden","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78695,752,"SWE","Sweden","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78696,752,"SWE","Sweden","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78697,752,"SWE","Sweden","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78698,752,"SWE","Sweden","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78699,752,"SWE","Sweden","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78700,752,"SWE","Sweden","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78701,752,"SWE","Sweden","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78702,752,"SWE","Sweden","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78703,752,"SWE","Sweden","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78704,752,"SWE","Sweden","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78705,752,"SWE","Sweden","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78706,752,"SWE","Sweden","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78707,752,"SWE","Sweden","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78708,752,"SWE","Sweden","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78709,752,"SWE","Sweden","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78710,752,"SWE","Sweden","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78711,752,"SWE","Sweden","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78712,752,"SWE","Sweden","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78713,752,"SWE","Sweden","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78714,752,"SWE","Sweden","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78715,752,"SWE","Sweden","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78716,752,"SWE","Sweden","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78717,752,"SWE","Sweden","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78718,752,"SWE","Sweden","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78719,752,"SWE","Sweden","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78720,752,"SWE","Sweden","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78721,752,"SWE","Sweden","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SWE/swe_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78722,756,"CHE","Switzerland","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78723,756,"CHE","Switzerland","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78724,756,"CHE","Switzerland","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78725,756,"CHE","Switzerland","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78726,756,"CHE","Switzerland","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78727,756,"CHE","Switzerland","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78728,756,"CHE","Switzerland","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78729,756,"CHE","Switzerland","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78730,756,"CHE","Switzerland","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78731,756,"CHE","Switzerland","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78732,756,"CHE","Switzerland","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78733,756,"CHE","Switzerland","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78734,756,"CHE","Switzerland","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78735,756,"CHE","Switzerland","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78736,756,"CHE","Switzerland","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78737,756,"CHE","Switzerland","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78738,756,"CHE","Switzerland","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78739,756,"CHE","Switzerland","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78740,756,"CHE","Switzerland","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78741,756,"CHE","Switzerland","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78742,756,"CHE","Switzerland","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78743,756,"CHE","Switzerland","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78744,756,"CHE","Switzerland","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78745,756,"CHE","Switzerland","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78746,756,"CHE","Switzerland","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78747,756,"CHE","Switzerland","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78748,756,"CHE","Switzerland","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78749,756,"CHE","Switzerland","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78750,756,"CHE","Switzerland","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78751,756,"CHE","Switzerland","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78752,756,"CHE","Switzerland","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78753,756,"CHE","Switzerland","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78754,756,"CHE","Switzerland","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78755,756,"CHE","Switzerland","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78756,756,"CHE","Switzerland","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78757,756,"CHE","Switzerland","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/CHE/che_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78758,760,"SYR","Syria","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78759,760,"SYR","Syria","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78760,760,"SYR","Syria","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78761,760,"SYR","Syria","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78762,760,"SYR","Syria","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78763,760,"SYR","Syria","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78764,760,"SYR","Syria","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78765,760,"SYR","Syria","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78766,760,"SYR","Syria","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78767,760,"SYR","Syria","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78768,760,"SYR","Syria","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78769,760,"SYR","Syria","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78770,760,"SYR","Syria","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78771,760,"SYR","Syria","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78772,760,"SYR","Syria","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78773,760,"SYR","Syria","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78774,760,"SYR","Syria","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78775,760,"SYR","Syria","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78776,760,"SYR","Syria","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78777,760,"SYR","Syria","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78778,760,"SYR","Syria","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78779,760,"SYR","Syria","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78780,760,"SYR","Syria","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78781,760,"SYR","Syria","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78782,760,"SYR","Syria","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78783,760,"SYR","Syria","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78784,760,"SYR","Syria","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78785,760,"SYR","Syria","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78786,760,"SYR","Syria","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78787,760,"SYR","Syria","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78788,760,"SYR","Syria","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78789,760,"SYR","Syria","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78790,760,"SYR","Syria","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78791,760,"SYR","Syria","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78792,760,"SYR","Syria","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78793,760,"SYR","Syria","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SYR/syr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78794,762,"TJK","Tajikistan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78795,762,"TJK","Tajikistan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78796,762,"TJK","Tajikistan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78797,762,"TJK","Tajikistan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78798,762,"TJK","Tajikistan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78799,762,"TJK","Tajikistan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78800,762,"TJK","Tajikistan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78801,762,"TJK","Tajikistan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78802,762,"TJK","Tajikistan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78803,762,"TJK","Tajikistan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78804,762,"TJK","Tajikistan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78805,762,"TJK","Tajikistan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78806,762,"TJK","Tajikistan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78807,762,"TJK","Tajikistan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78808,762,"TJK","Tajikistan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78809,762,"TJK","Tajikistan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78810,762,"TJK","Tajikistan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78811,762,"TJK","Tajikistan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78812,762,"TJK","Tajikistan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78813,762,"TJK","Tajikistan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78814,762,"TJK","Tajikistan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78815,762,"TJK","Tajikistan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78816,762,"TJK","Tajikistan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78817,762,"TJK","Tajikistan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78818,762,"TJK","Tajikistan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78819,762,"TJK","Tajikistan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78820,762,"TJK","Tajikistan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78821,762,"TJK","Tajikistan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78822,762,"TJK","Tajikistan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78823,762,"TJK","Tajikistan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78824,762,"TJK","Tajikistan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78825,762,"TJK","Tajikistan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78826,762,"TJK","Tajikistan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78827,762,"TJK","Tajikistan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78828,762,"TJK","Tajikistan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78829,762,"TJK","Tajikistan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TJK/tjk_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78830,764,"THA","Thailand","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78831,764,"THA","Thailand","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78832,764,"THA","Thailand","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78833,764,"THA","Thailand","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78834,764,"THA","Thailand","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78835,764,"THA","Thailand","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78836,764,"THA","Thailand","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78837,764,"THA","Thailand","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78838,764,"THA","Thailand","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78839,764,"THA","Thailand","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78840,764,"THA","Thailand","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78841,764,"THA","Thailand","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78842,764,"THA","Thailand","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78843,764,"THA","Thailand","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78844,764,"THA","Thailand","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78845,764,"THA","Thailand","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78846,764,"THA","Thailand","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78847,764,"THA","Thailand","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78848,764,"THA","Thailand","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78849,764,"THA","Thailand","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78850,764,"THA","Thailand","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78851,764,"THA","Thailand","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78852,764,"THA","Thailand","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78853,764,"THA","Thailand","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78854,764,"THA","Thailand","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78855,764,"THA","Thailand","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78856,764,"THA","Thailand","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78857,764,"THA","Thailand","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78858,764,"THA","Thailand","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78859,764,"THA","Thailand","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78860,764,"THA","Thailand","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78861,764,"THA","Thailand","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78862,764,"THA","Thailand","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78863,764,"THA","Thailand","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78864,764,"THA","Thailand","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78865,764,"THA","Thailand","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/THA/tha_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78866,768,"TGO","Togo","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78867,768,"TGO","Togo","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78868,768,"TGO","Togo","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78869,768,"TGO","Togo","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78870,768,"TGO","Togo","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78871,768,"TGO","Togo","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78872,768,"TGO","Togo","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78873,768,"TGO","Togo","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78874,768,"TGO","Togo","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78875,768,"TGO","Togo","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78876,768,"TGO","Togo","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78877,768,"TGO","Togo","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78878,768,"TGO","Togo","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78879,768,"TGO","Togo","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78880,768,"TGO","Togo","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78881,768,"TGO","Togo","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78882,768,"TGO","Togo","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78883,768,"TGO","Togo","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78884,768,"TGO","Togo","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78885,768,"TGO","Togo","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78886,768,"TGO","Togo","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78887,768,"TGO","Togo","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78888,768,"TGO","Togo","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78889,768,"TGO","Togo","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78890,768,"TGO","Togo","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78891,768,"TGO","Togo","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78892,768,"TGO","Togo","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78893,768,"TGO","Togo","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78894,768,"TGO","Togo","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78895,768,"TGO","Togo","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78896,768,"TGO","Togo","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78897,768,"TGO","Togo","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78898,768,"TGO","Togo","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78899,768,"TGO","Togo","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78900,768,"TGO","Togo","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78901,768,"TGO","Togo","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TGO/tgo_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78902,772,"TKL","Tokelau","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78903,772,"TKL","Tokelau","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78904,772,"TKL","Tokelau","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78905,772,"TKL","Tokelau","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78906,772,"TKL","Tokelau","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78907,772,"TKL","Tokelau","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78908,772,"TKL","Tokelau","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78909,772,"TKL","Tokelau","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78910,772,"TKL","Tokelau","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78911,772,"TKL","Tokelau","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78912,772,"TKL","Tokelau","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78913,772,"TKL","Tokelau","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78914,772,"TKL","Tokelau","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78915,772,"TKL","Tokelau","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78916,772,"TKL","Tokelau","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78917,772,"TKL","Tokelau","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78918,772,"TKL","Tokelau","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78919,772,"TKL","Tokelau","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78920,772,"TKL","Tokelau","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78921,772,"TKL","Tokelau","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78922,772,"TKL","Tokelau","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78923,772,"TKL","Tokelau","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78924,772,"TKL","Tokelau","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78925,772,"TKL","Tokelau","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78926,772,"TKL","Tokelau","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78927,772,"TKL","Tokelau","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78928,772,"TKL","Tokelau","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78929,772,"TKL","Tokelau","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78930,772,"TKL","Tokelau","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78931,772,"TKL","Tokelau","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78932,772,"TKL","Tokelau","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78933,772,"TKL","Tokelau","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78934,772,"TKL","Tokelau","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78935,772,"TKL","Tokelau","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78936,772,"TKL","Tokelau","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78937,772,"TKL","Tokelau","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKL/tkl_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78938,776,"TON","Tonga","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78939,776,"TON","Tonga","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78940,776,"TON","Tonga","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78941,776,"TON","Tonga","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78942,776,"TON","Tonga","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78943,776,"TON","Tonga","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78944,776,"TON","Tonga","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78945,776,"TON","Tonga","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78946,776,"TON","Tonga","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78947,776,"TON","Tonga","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78948,776,"TON","Tonga","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78949,776,"TON","Tonga","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78950,776,"TON","Tonga","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78951,776,"TON","Tonga","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78952,776,"TON","Tonga","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78953,776,"TON","Tonga","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78954,776,"TON","Tonga","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78955,776,"TON","Tonga","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78956,776,"TON","Tonga","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78957,776,"TON","Tonga","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78958,776,"TON","Tonga","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78959,776,"TON","Tonga","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78960,776,"TON","Tonga","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78961,776,"TON","Tonga","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78962,776,"TON","Tonga","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78963,776,"TON","Tonga","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
78964,776,"TON","Tonga","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
78965,776,"TON","Tonga","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
78966,776,"TON","Tonga","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
78967,776,"TON","Tonga","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
78968,776,"TON","Tonga","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
78969,776,"TON","Tonga","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
78970,776,"TON","Tonga","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
78971,776,"TON","Tonga","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
78972,776,"TON","Tonga","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
78973,776,"TON","Tonga","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TON/ton_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
78974,780,"TTO","Trinidad and Tobago","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
78975,780,"TTO","Trinidad and Tobago","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
78976,780,"TTO","Trinidad and Tobago","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
78977,780,"TTO","Trinidad and Tobago","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
78978,780,"TTO","Trinidad and Tobago","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
78979,780,"TTO","Trinidad and Tobago","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
78980,780,"TTO","Trinidad and Tobago","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
78981,780,"TTO","Trinidad and Tobago","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
78982,780,"TTO","Trinidad and Tobago","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
78983,780,"TTO","Trinidad and Tobago","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
78984,780,"TTO","Trinidad and Tobago","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
78985,780,"TTO","Trinidad and Tobago","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
78986,780,"TTO","Trinidad and Tobago","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
78987,780,"TTO","Trinidad and Tobago","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
78988,780,"TTO","Trinidad and Tobago","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
78989,780,"TTO","Trinidad and Tobago","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
78990,780,"TTO","Trinidad and Tobago","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
78991,780,"TTO","Trinidad and Tobago","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
78992,780,"TTO","Trinidad and Tobago","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
78993,780,"TTO","Trinidad and Tobago","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
78994,780,"TTO","Trinidad and Tobago","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
78995,780,"TTO","Trinidad and Tobago","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
78996,780,"TTO","Trinidad and Tobago","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
78997,780,"TTO","Trinidad and Tobago","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
78998,780,"TTO","Trinidad and Tobago","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
78999,780,"TTO","Trinidad and Tobago","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79000,780,"TTO","Trinidad and Tobago","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79001,780,"TTO","Trinidad and Tobago","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79002,780,"TTO","Trinidad and Tobago","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79003,780,"TTO","Trinidad and Tobago","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79004,780,"TTO","Trinidad and Tobago","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79005,780,"TTO","Trinidad and Tobago","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79006,780,"TTO","Trinidad and Tobago","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79007,780,"TTO","Trinidad and Tobago","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79008,780,"TTO","Trinidad and Tobago","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79009,780,"TTO","Trinidad and Tobago","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TTO/tto_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79010,784,"ARE","United Arab Emirates","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79011,784,"ARE","United Arab Emirates","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79012,784,"ARE","United Arab Emirates","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79013,784,"ARE","United Arab Emirates","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79014,784,"ARE","United Arab Emirates","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79015,784,"ARE","United Arab Emirates","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79016,784,"ARE","United Arab Emirates","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79017,784,"ARE","United Arab Emirates","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79018,784,"ARE","United Arab Emirates","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79019,784,"ARE","United Arab Emirates","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79020,784,"ARE","United Arab Emirates","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79021,784,"ARE","United Arab Emirates","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79022,784,"ARE","United Arab Emirates","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79023,784,"ARE","United Arab Emirates","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79024,784,"ARE","United Arab Emirates","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79025,784,"ARE","United Arab Emirates","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79026,784,"ARE","United Arab Emirates","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79027,784,"ARE","United Arab Emirates","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79028,784,"ARE","United Arab Emirates","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79029,784,"ARE","United Arab Emirates","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79030,784,"ARE","United Arab Emirates","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79031,784,"ARE","United Arab Emirates","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79032,784,"ARE","United Arab Emirates","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79033,784,"ARE","United Arab Emirates","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79034,784,"ARE","United Arab Emirates","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79035,784,"ARE","United Arab Emirates","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79036,784,"ARE","United Arab Emirates","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79037,784,"ARE","United Arab Emirates","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79038,784,"ARE","United Arab Emirates","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79039,784,"ARE","United Arab Emirates","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79040,784,"ARE","United Arab Emirates","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79041,784,"ARE","United Arab Emirates","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79042,784,"ARE","United Arab Emirates","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79043,784,"ARE","United Arab Emirates","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79044,784,"ARE","United Arab Emirates","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79045,784,"ARE","United Arab Emirates","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ARE/are_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79046,788,"TUN","Tunisia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79047,788,"TUN","Tunisia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79048,788,"TUN","Tunisia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79049,788,"TUN","Tunisia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79050,788,"TUN","Tunisia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79051,788,"TUN","Tunisia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79052,788,"TUN","Tunisia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79053,788,"TUN","Tunisia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79054,788,"TUN","Tunisia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79055,788,"TUN","Tunisia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79056,788,"TUN","Tunisia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79057,788,"TUN","Tunisia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79058,788,"TUN","Tunisia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79059,788,"TUN","Tunisia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79060,788,"TUN","Tunisia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79061,788,"TUN","Tunisia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79062,788,"TUN","Tunisia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79063,788,"TUN","Tunisia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79064,788,"TUN","Tunisia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79065,788,"TUN","Tunisia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79066,788,"TUN","Tunisia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79067,788,"TUN","Tunisia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79068,788,"TUN","Tunisia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79069,788,"TUN","Tunisia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79070,788,"TUN","Tunisia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79071,788,"TUN","Tunisia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79072,788,"TUN","Tunisia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79073,788,"TUN","Tunisia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79074,788,"TUN","Tunisia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79075,788,"TUN","Tunisia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79076,788,"TUN","Tunisia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79077,788,"TUN","Tunisia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79078,788,"TUN","Tunisia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79079,788,"TUN","Tunisia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79080,788,"TUN","Tunisia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79081,788,"TUN","Tunisia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUN/tun_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79082,792,"TUR","Turkey","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79083,792,"TUR","Turkey","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79084,792,"TUR","Turkey","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79085,792,"TUR","Turkey","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79086,792,"TUR","Turkey","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79087,792,"TUR","Turkey","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79088,792,"TUR","Turkey","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79089,792,"TUR","Turkey","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79090,792,"TUR","Turkey","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79091,792,"TUR","Turkey","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79092,792,"TUR","Turkey","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79093,792,"TUR","Turkey","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79094,792,"TUR","Turkey","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79095,792,"TUR","Turkey","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79096,792,"TUR","Turkey","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79097,792,"TUR","Turkey","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79098,792,"TUR","Turkey","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79099,792,"TUR","Turkey","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79100,792,"TUR","Turkey","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79101,792,"TUR","Turkey","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79102,792,"TUR","Turkey","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79103,792,"TUR","Turkey","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79104,792,"TUR","Turkey","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79105,792,"TUR","Turkey","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79106,792,"TUR","Turkey","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79107,792,"TUR","Turkey","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79108,792,"TUR","Turkey","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79109,792,"TUR","Turkey","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79110,792,"TUR","Turkey","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79111,792,"TUR","Turkey","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79112,792,"TUR","Turkey","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79113,792,"TUR","Turkey","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79114,792,"TUR","Turkey","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79115,792,"TUR","Turkey","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79116,792,"TUR","Turkey","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79117,792,"TUR","Turkey","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUR/tur_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79118,795,"TKM","Turkmenistan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79119,795,"TKM","Turkmenistan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79120,795,"TKM","Turkmenistan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79121,795,"TKM","Turkmenistan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79122,795,"TKM","Turkmenistan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79123,795,"TKM","Turkmenistan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79124,795,"TKM","Turkmenistan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79125,795,"TKM","Turkmenistan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79126,795,"TKM","Turkmenistan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79127,795,"TKM","Turkmenistan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79128,795,"TKM","Turkmenistan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79129,795,"TKM","Turkmenistan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79130,795,"TKM","Turkmenistan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79131,795,"TKM","Turkmenistan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79132,795,"TKM","Turkmenistan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79133,795,"TKM","Turkmenistan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79134,795,"TKM","Turkmenistan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79135,795,"TKM","Turkmenistan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79136,795,"TKM","Turkmenistan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79137,795,"TKM","Turkmenistan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79138,795,"TKM","Turkmenistan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79139,795,"TKM","Turkmenistan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79140,795,"TKM","Turkmenistan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79141,795,"TKM","Turkmenistan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79142,795,"TKM","Turkmenistan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79143,795,"TKM","Turkmenistan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79144,795,"TKM","Turkmenistan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79145,795,"TKM","Turkmenistan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79146,795,"TKM","Turkmenistan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79147,795,"TKM","Turkmenistan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79148,795,"TKM","Turkmenistan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79149,795,"TKM","Turkmenistan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79150,795,"TKM","Turkmenistan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79151,795,"TKM","Turkmenistan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79152,795,"TKM","Turkmenistan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79153,795,"TKM","Turkmenistan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TKM/tkm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79154,796,"TCA","Turks and Caicos Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79155,796,"TCA","Turks and Caicos Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79156,796,"TCA","Turks and Caicos Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79157,796,"TCA","Turks and Caicos Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79158,796,"TCA","Turks and Caicos Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79159,796,"TCA","Turks and Caicos Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79160,796,"TCA","Turks and Caicos Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79161,796,"TCA","Turks and Caicos Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79162,796,"TCA","Turks and Caicos Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79163,796,"TCA","Turks and Caicos Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79164,796,"TCA","Turks and Caicos Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79165,796,"TCA","Turks and Caicos Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79166,796,"TCA","Turks and Caicos Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79167,796,"TCA","Turks and Caicos Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79168,796,"TCA","Turks and Caicos Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79169,796,"TCA","Turks and Caicos Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79170,796,"TCA","Turks and Caicos Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79171,796,"TCA","Turks and Caicos Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79172,796,"TCA","Turks and Caicos Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79173,796,"TCA","Turks and Caicos Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79174,796,"TCA","Turks and Caicos Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79175,796,"TCA","Turks and Caicos Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79176,796,"TCA","Turks and Caicos Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79177,796,"TCA","Turks and Caicos Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79178,796,"TCA","Turks and Caicos Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79179,796,"TCA","Turks and Caicos Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79180,796,"TCA","Turks and Caicos Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79181,796,"TCA","Turks and Caicos Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79182,796,"TCA","Turks and Caicos Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79183,796,"TCA","Turks and Caicos Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79184,796,"TCA","Turks and Caicos Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79185,796,"TCA","Turks and Caicos Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79186,796,"TCA","Turks and Caicos Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79187,796,"TCA","Turks and Caicos Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79188,796,"TCA","Turks and Caicos Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79189,796,"TCA","Turks and Caicos Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TCA/tca_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79190,798,"TUV","Tuvalu","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79191,798,"TUV","Tuvalu","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79192,798,"TUV","Tuvalu","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79193,798,"TUV","Tuvalu","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79194,798,"TUV","Tuvalu","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79195,798,"TUV","Tuvalu","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79196,798,"TUV","Tuvalu","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79197,798,"TUV","Tuvalu","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79198,798,"TUV","Tuvalu","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79199,798,"TUV","Tuvalu","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79200,798,"TUV","Tuvalu","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79201,798,"TUV","Tuvalu","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79202,798,"TUV","Tuvalu","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79203,798,"TUV","Tuvalu","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79204,798,"TUV","Tuvalu","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79205,798,"TUV","Tuvalu","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79206,798,"TUV","Tuvalu","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79207,798,"TUV","Tuvalu","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79208,798,"TUV","Tuvalu","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79209,798,"TUV","Tuvalu","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79210,798,"TUV","Tuvalu","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79211,798,"TUV","Tuvalu","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79212,798,"TUV","Tuvalu","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79213,798,"TUV","Tuvalu","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79214,798,"TUV","Tuvalu","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79215,798,"TUV","Tuvalu","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79216,798,"TUV","Tuvalu","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79217,798,"TUV","Tuvalu","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79218,798,"TUV","Tuvalu","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79219,798,"TUV","Tuvalu","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79220,798,"TUV","Tuvalu","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79221,798,"TUV","Tuvalu","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79222,798,"TUV","Tuvalu","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79223,798,"TUV","Tuvalu","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79224,798,"TUV","Tuvalu","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79225,798,"TUV","Tuvalu","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TUV/tuv_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79226,800,"UGA","Uganda","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79227,800,"UGA","Uganda","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79228,800,"UGA","Uganda","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79229,800,"UGA","Uganda","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79230,800,"UGA","Uganda","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79231,800,"UGA","Uganda","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79232,800,"UGA","Uganda","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79233,800,"UGA","Uganda","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79234,800,"UGA","Uganda","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79235,800,"UGA","Uganda","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79236,800,"UGA","Uganda","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79237,800,"UGA","Uganda","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79238,800,"UGA","Uganda","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79239,800,"UGA","Uganda","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79240,800,"UGA","Uganda","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79241,800,"UGA","Uganda","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79242,800,"UGA","Uganda","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79243,800,"UGA","Uganda","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79244,800,"UGA","Uganda","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79245,800,"UGA","Uganda","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79246,800,"UGA","Uganda","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79247,800,"UGA","Uganda","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79248,800,"UGA","Uganda","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79249,800,"UGA","Uganda","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79250,800,"UGA","Uganda","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79251,800,"UGA","Uganda","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79252,800,"UGA","Uganda","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79253,800,"UGA","Uganda","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79254,800,"UGA","Uganda","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79255,800,"UGA","Uganda","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79256,800,"UGA","Uganda","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79257,800,"UGA","Uganda","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79258,800,"UGA","Uganda","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79259,800,"UGA","Uganda","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79260,800,"UGA","Uganda","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79261,800,"UGA","Uganda","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UGA/uga_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79262,804,"UKR","Ukraine","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79263,804,"UKR","Ukraine","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79264,804,"UKR","Ukraine","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79265,804,"UKR","Ukraine","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79266,804,"UKR","Ukraine","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79267,804,"UKR","Ukraine","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79268,804,"UKR","Ukraine","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79269,804,"UKR","Ukraine","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79270,804,"UKR","Ukraine","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79271,804,"UKR","Ukraine","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79272,804,"UKR","Ukraine","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79273,804,"UKR","Ukraine","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79274,804,"UKR","Ukraine","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79275,804,"UKR","Ukraine","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79276,804,"UKR","Ukraine","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79277,804,"UKR","Ukraine","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79278,804,"UKR","Ukraine","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79279,804,"UKR","Ukraine","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79280,804,"UKR","Ukraine","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79281,804,"UKR","Ukraine","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79282,804,"UKR","Ukraine","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79283,804,"UKR","Ukraine","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79284,804,"UKR","Ukraine","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79285,804,"UKR","Ukraine","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79286,804,"UKR","Ukraine","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79287,804,"UKR","Ukraine","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79288,804,"UKR","Ukraine","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79289,804,"UKR","Ukraine","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79290,804,"UKR","Ukraine","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79291,804,"UKR","Ukraine","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79292,804,"UKR","Ukraine","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79293,804,"UKR","Ukraine","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79294,804,"UKR","Ukraine","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79295,804,"UKR","Ukraine","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79296,804,"UKR","Ukraine","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79297,804,"UKR","Ukraine","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UKR/ukr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79298,807,"MKD","Macedonia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79299,807,"MKD","Macedonia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79300,807,"MKD","Macedonia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79301,807,"MKD","Macedonia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79302,807,"MKD","Macedonia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79303,807,"MKD","Macedonia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79304,807,"MKD","Macedonia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79305,807,"MKD","Macedonia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79306,807,"MKD","Macedonia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79307,807,"MKD","Macedonia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79308,807,"MKD","Macedonia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79309,807,"MKD","Macedonia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79310,807,"MKD","Macedonia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79311,807,"MKD","Macedonia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79312,807,"MKD","Macedonia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79313,807,"MKD","Macedonia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79314,807,"MKD","Macedonia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79315,807,"MKD","Macedonia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79316,807,"MKD","Macedonia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79317,807,"MKD","Macedonia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79318,807,"MKD","Macedonia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79319,807,"MKD","Macedonia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79320,807,"MKD","Macedonia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79321,807,"MKD","Macedonia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79322,807,"MKD","Macedonia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79323,807,"MKD","Macedonia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79324,807,"MKD","Macedonia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79325,807,"MKD","Macedonia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79326,807,"MKD","Macedonia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79327,807,"MKD","Macedonia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79328,807,"MKD","Macedonia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79329,807,"MKD","Macedonia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79330,807,"MKD","Macedonia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79331,807,"MKD","Macedonia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79332,807,"MKD","Macedonia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79333,807,"MKD","Macedonia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/MKD/mkd_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79334,818,"EGY","Egypt","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79335,818,"EGY","Egypt","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79336,818,"EGY","Egypt","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79337,818,"EGY","Egypt","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79338,818,"EGY","Egypt","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79339,818,"EGY","Egypt","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79340,818,"EGY","Egypt","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79341,818,"EGY","Egypt","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79342,818,"EGY","Egypt","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79343,818,"EGY","Egypt","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79344,818,"EGY","Egypt","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79345,818,"EGY","Egypt","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79346,818,"EGY","Egypt","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79347,818,"EGY","Egypt","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79348,818,"EGY","Egypt","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79349,818,"EGY","Egypt","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79350,818,"EGY","Egypt","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79351,818,"EGY","Egypt","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79352,818,"EGY","Egypt","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79353,818,"EGY","Egypt","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79354,818,"EGY","Egypt","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79355,818,"EGY","Egypt","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79356,818,"EGY","Egypt","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79357,818,"EGY","Egypt","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79358,818,"EGY","Egypt","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79359,818,"EGY","Egypt","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79360,818,"EGY","Egypt","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79361,818,"EGY","Egypt","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79362,818,"EGY","Egypt","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79363,818,"EGY","Egypt","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79364,818,"EGY","Egypt","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79365,818,"EGY","Egypt","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79366,818,"EGY","Egypt","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79367,818,"EGY","Egypt","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79368,818,"EGY","Egypt","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79369,818,"EGY","Egypt","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/EGY/egy_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79370,826,"GBR","United Kingdom","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79371,826,"GBR","United Kingdom","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79372,826,"GBR","United Kingdom","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79373,826,"GBR","United Kingdom","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79374,826,"GBR","United Kingdom","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79375,826,"GBR","United Kingdom","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79376,826,"GBR","United Kingdom","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79377,826,"GBR","United Kingdom","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79378,826,"GBR","United Kingdom","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79379,826,"GBR","United Kingdom","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79380,826,"GBR","United Kingdom","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79381,826,"GBR","United Kingdom","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79382,826,"GBR","United Kingdom","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79383,826,"GBR","United Kingdom","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79384,826,"GBR","United Kingdom","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79385,826,"GBR","United Kingdom","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79386,826,"GBR","United Kingdom","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79387,826,"GBR","United Kingdom","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79388,826,"GBR","United Kingdom","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79389,826,"GBR","United Kingdom","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79390,826,"GBR","United Kingdom","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79391,826,"GBR","United Kingdom","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79392,826,"GBR","United Kingdom","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79393,826,"GBR","United Kingdom","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79394,826,"GBR","United Kingdom","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79395,826,"GBR","United Kingdom","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79396,826,"GBR","United Kingdom","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79397,826,"GBR","United Kingdom","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79398,826,"GBR","United Kingdom","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79399,826,"GBR","United Kingdom","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79400,826,"GBR","United Kingdom","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79401,826,"GBR","United Kingdom","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79402,826,"GBR","United Kingdom","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79403,826,"GBR","United Kingdom","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79404,826,"GBR","United Kingdom","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79405,826,"GBR","United Kingdom","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GBR/gbr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79406,831,"GGY","Guernsey","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79407,831,"GGY","Guernsey","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79408,831,"GGY","Guernsey","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79409,831,"GGY","Guernsey","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79410,831,"GGY","Guernsey","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79411,831,"GGY","Guernsey","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79412,831,"GGY","Guernsey","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79413,831,"GGY","Guernsey","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79414,831,"GGY","Guernsey","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79415,831,"GGY","Guernsey","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79416,831,"GGY","Guernsey","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79417,831,"GGY","Guernsey","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79418,831,"GGY","Guernsey","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79419,831,"GGY","Guernsey","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79420,831,"GGY","Guernsey","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79421,831,"GGY","Guernsey","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79422,831,"GGY","Guernsey","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79423,831,"GGY","Guernsey","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79424,831,"GGY","Guernsey","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79425,831,"GGY","Guernsey","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79426,831,"GGY","Guernsey","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79427,831,"GGY","Guernsey","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79428,831,"GGY","Guernsey","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79429,831,"GGY","Guernsey","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79430,831,"GGY","Guernsey","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79431,831,"GGY","Guernsey","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79432,831,"GGY","Guernsey","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79433,831,"GGY","Guernsey","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79434,831,"GGY","Guernsey","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79435,831,"GGY","Guernsey","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79436,831,"GGY","Guernsey","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79437,831,"GGY","Guernsey","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79438,831,"GGY","Guernsey","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79439,831,"GGY","Guernsey","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79440,831,"GGY","Guernsey","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79441,831,"GGY","Guernsey","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/GGY/ggy_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79442,832,"JEY","Jersey","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79443,832,"JEY","Jersey","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79444,832,"JEY","Jersey","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79445,832,"JEY","Jersey","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79446,832,"JEY","Jersey","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79447,832,"JEY","Jersey","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79448,832,"JEY","Jersey","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79449,832,"JEY","Jersey","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79450,832,"JEY","Jersey","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79451,832,"JEY","Jersey","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79452,832,"JEY","Jersey","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79453,832,"JEY","Jersey","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79454,832,"JEY","Jersey","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79455,832,"JEY","Jersey","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79456,832,"JEY","Jersey","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79457,832,"JEY","Jersey","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79458,832,"JEY","Jersey","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79459,832,"JEY","Jersey","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79460,832,"JEY","Jersey","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79461,832,"JEY","Jersey","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79462,832,"JEY","Jersey","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79463,832,"JEY","Jersey","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79464,832,"JEY","Jersey","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79465,832,"JEY","Jersey","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79466,832,"JEY","Jersey","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79467,832,"JEY","Jersey","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79468,832,"JEY","Jersey","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79469,832,"JEY","Jersey","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79470,832,"JEY","Jersey","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79471,832,"JEY","Jersey","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79472,832,"JEY","Jersey","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79473,832,"JEY","Jersey","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79474,832,"JEY","Jersey","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79475,832,"JEY","Jersey","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79476,832,"JEY","Jersey","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79477,832,"JEY","Jersey","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/JEY/jey_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79478,833,"IMN","Isle of Man","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79479,833,"IMN","Isle of Man","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79480,833,"IMN","Isle of Man","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79481,833,"IMN","Isle of Man","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79482,833,"IMN","Isle of Man","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79483,833,"IMN","Isle of Man","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79484,833,"IMN","Isle of Man","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79485,833,"IMN","Isle of Man","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79486,833,"IMN","Isle of Man","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79487,833,"IMN","Isle of Man","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79488,833,"IMN","Isle of Man","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79489,833,"IMN","Isle of Man","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79490,833,"IMN","Isle of Man","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79491,833,"IMN","Isle of Man","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79492,833,"IMN","Isle of Man","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79493,833,"IMN","Isle of Man","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79494,833,"IMN","Isle of Man","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79495,833,"IMN","Isle of Man","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79496,833,"IMN","Isle of Man","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79497,833,"IMN","Isle of Man","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79498,833,"IMN","Isle of Man","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79499,833,"IMN","Isle of Man","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79500,833,"IMN","Isle of Man","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79501,833,"IMN","Isle of Man","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79502,833,"IMN","Isle of Man","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79503,833,"IMN","Isle of Man","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79504,833,"IMN","Isle of Man","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79505,833,"IMN","Isle of Man","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79506,833,"IMN","Isle of Man","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79507,833,"IMN","Isle of Man","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79508,833,"IMN","Isle of Man","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79509,833,"IMN","Isle of Man","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79510,833,"IMN","Isle of Man","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79511,833,"IMN","Isle of Man","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79512,833,"IMN","Isle of Man","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79513,833,"IMN","Isle of Man","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/IMN/imn_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79514,834,"TZA","Tanzania","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79515,834,"TZA","Tanzania","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79516,834,"TZA","Tanzania","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79517,834,"TZA","Tanzania","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79518,834,"TZA","Tanzania","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79519,834,"TZA","Tanzania","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79520,834,"TZA","Tanzania","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79521,834,"TZA","Tanzania","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79522,834,"TZA","Tanzania","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79523,834,"TZA","Tanzania","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79524,834,"TZA","Tanzania","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79525,834,"TZA","Tanzania","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79526,834,"TZA","Tanzania","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79527,834,"TZA","Tanzania","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79528,834,"TZA","Tanzania","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79529,834,"TZA","Tanzania","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79530,834,"TZA","Tanzania","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79531,834,"TZA","Tanzania","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79532,834,"TZA","Tanzania","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79533,834,"TZA","Tanzania","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79534,834,"TZA","Tanzania","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79535,834,"TZA","Tanzania","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79536,834,"TZA","Tanzania","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79537,834,"TZA","Tanzania","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79538,834,"TZA","Tanzania","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79539,834,"TZA","Tanzania","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79540,834,"TZA","Tanzania","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79541,834,"TZA","Tanzania","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79542,834,"TZA","Tanzania","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79543,834,"TZA","Tanzania","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79544,834,"TZA","Tanzania","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79545,834,"TZA","Tanzania","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79546,834,"TZA","Tanzania","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79547,834,"TZA","Tanzania","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79548,834,"TZA","Tanzania","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79549,834,"TZA","Tanzania","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/TZA/tza_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79550,854,"BFA","Burkina Faso","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79551,854,"BFA","Burkina Faso","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79552,854,"BFA","Burkina Faso","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79553,854,"BFA","Burkina Faso","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79554,854,"BFA","Burkina Faso","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79555,854,"BFA","Burkina Faso","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79556,854,"BFA","Burkina Faso","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79557,854,"BFA","Burkina Faso","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79558,854,"BFA","Burkina Faso","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79559,854,"BFA","Burkina Faso","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79560,854,"BFA","Burkina Faso","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79561,854,"BFA","Burkina Faso","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79562,854,"BFA","Burkina Faso","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79563,854,"BFA","Burkina Faso","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79564,854,"BFA","Burkina Faso","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79565,854,"BFA","Burkina Faso","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79566,854,"BFA","Burkina Faso","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79567,854,"BFA","Burkina Faso","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79568,854,"BFA","Burkina Faso","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79569,854,"BFA","Burkina Faso","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79570,854,"BFA","Burkina Faso","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79571,854,"BFA","Burkina Faso","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79572,854,"BFA","Burkina Faso","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79573,854,"BFA","Burkina Faso","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79574,854,"BFA","Burkina Faso","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79575,854,"BFA","Burkina Faso","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79576,854,"BFA","Burkina Faso","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79577,854,"BFA","Burkina Faso","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79578,854,"BFA","Burkina Faso","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79579,854,"BFA","Burkina Faso","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79580,854,"BFA","Burkina Faso","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79581,854,"BFA","Burkina Faso","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79582,854,"BFA","Burkina Faso","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79583,854,"BFA","Burkina Faso","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79584,854,"BFA","Burkina Faso","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79585,854,"BFA","Burkina Faso","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/BFA/bfa_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79586,858,"URY","Uruguay","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79587,858,"URY","Uruguay","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79588,858,"URY","Uruguay","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79589,858,"URY","Uruguay","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79590,858,"URY","Uruguay","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79591,858,"URY","Uruguay","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79592,858,"URY","Uruguay","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79593,858,"URY","Uruguay","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79594,858,"URY","Uruguay","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79595,858,"URY","Uruguay","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79596,858,"URY","Uruguay","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79597,858,"URY","Uruguay","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79598,858,"URY","Uruguay","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79599,858,"URY","Uruguay","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79600,858,"URY","Uruguay","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79601,858,"URY","Uruguay","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79602,858,"URY","Uruguay","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79603,858,"URY","Uruguay","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79604,858,"URY","Uruguay","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79605,858,"URY","Uruguay","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79606,858,"URY","Uruguay","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79607,858,"URY","Uruguay","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79608,858,"URY","Uruguay","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79609,858,"URY","Uruguay","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79610,858,"URY","Uruguay","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79611,858,"URY","Uruguay","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79612,858,"URY","Uruguay","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79613,858,"URY","Uruguay","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79614,858,"URY","Uruguay","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79615,858,"URY","Uruguay","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79616,858,"URY","Uruguay","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79617,858,"URY","Uruguay","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79618,858,"URY","Uruguay","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79619,858,"URY","Uruguay","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79620,858,"URY","Uruguay","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79621,858,"URY","Uruguay","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/URY/ury_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79622,860,"UZB","Uzbekistan","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79623,860,"UZB","Uzbekistan","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79624,860,"UZB","Uzbekistan","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79625,860,"UZB","Uzbekistan","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79626,860,"UZB","Uzbekistan","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79627,860,"UZB","Uzbekistan","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79628,860,"UZB","Uzbekistan","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79629,860,"UZB","Uzbekistan","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79630,860,"UZB","Uzbekistan","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79631,860,"UZB","Uzbekistan","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79632,860,"UZB","Uzbekistan","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79633,860,"UZB","Uzbekistan","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79634,860,"UZB","Uzbekistan","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79635,860,"UZB","Uzbekistan","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79636,860,"UZB","Uzbekistan","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79637,860,"UZB","Uzbekistan","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79638,860,"UZB","Uzbekistan","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79639,860,"UZB","Uzbekistan","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79640,860,"UZB","Uzbekistan","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79641,860,"UZB","Uzbekistan","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79642,860,"UZB","Uzbekistan","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79643,860,"UZB","Uzbekistan","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79644,860,"UZB","Uzbekistan","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79645,860,"UZB","Uzbekistan","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79646,860,"UZB","Uzbekistan","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79647,860,"UZB","Uzbekistan","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79648,860,"UZB","Uzbekistan","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79649,860,"UZB","Uzbekistan","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79650,860,"UZB","Uzbekistan","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79651,860,"UZB","Uzbekistan","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79652,860,"UZB","Uzbekistan","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79653,860,"UZB","Uzbekistan","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79654,860,"UZB","Uzbekistan","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79655,860,"UZB","Uzbekistan","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79656,860,"UZB","Uzbekistan","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79657,860,"UZB","Uzbekistan","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/UZB/uzb_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79658,862,"VEN","Venezuela","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79659,862,"VEN","Venezuela","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79660,862,"VEN","Venezuela","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79661,862,"VEN","Venezuela","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79662,862,"VEN","Venezuela","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79663,862,"VEN","Venezuela","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79664,862,"VEN","Venezuela","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79665,862,"VEN","Venezuela","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79666,862,"VEN","Venezuela","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79667,862,"VEN","Venezuela","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79668,862,"VEN","Venezuela","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79669,862,"VEN","Venezuela","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79670,862,"VEN","Venezuela","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79671,862,"VEN","Venezuela","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79672,862,"VEN","Venezuela","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79673,862,"VEN","Venezuela","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79674,862,"VEN","Venezuela","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79675,862,"VEN","Venezuela","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79676,862,"VEN","Venezuela","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79677,862,"VEN","Venezuela","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79678,862,"VEN","Venezuela","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79679,862,"VEN","Venezuela","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79680,862,"VEN","Venezuela","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79681,862,"VEN","Venezuela","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79682,862,"VEN","Venezuela","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79683,862,"VEN","Venezuela","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79684,862,"VEN","Venezuela","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79685,862,"VEN","Venezuela","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79686,862,"VEN","Venezuela","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79687,862,"VEN","Venezuela","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79688,862,"VEN","Venezuela","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79689,862,"VEN","Venezuela","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79690,862,"VEN","Venezuela","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79691,862,"VEN","Venezuela","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79692,862,"VEN","Venezuela","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79693,862,"VEN","Venezuela","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/VEN/ven_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79694,876,"WLF","Wallis and Futuna","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79695,876,"WLF","Wallis and Futuna","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79696,876,"WLF","Wallis and Futuna","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79697,876,"WLF","Wallis and Futuna","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79698,876,"WLF","Wallis and Futuna","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79699,876,"WLF","Wallis and Futuna","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79700,876,"WLF","Wallis and Futuna","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79701,876,"WLF","Wallis and Futuna","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79702,876,"WLF","Wallis and Futuna","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79703,876,"WLF","Wallis and Futuna","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79704,876,"WLF","Wallis and Futuna","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79705,876,"WLF","Wallis and Futuna","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79706,876,"WLF","Wallis and Futuna","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79707,876,"WLF","Wallis and Futuna","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79708,876,"WLF","Wallis and Futuna","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79709,876,"WLF","Wallis and Futuna","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79710,876,"WLF","Wallis and Futuna","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79711,876,"WLF","Wallis and Futuna","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79712,876,"WLF","Wallis and Futuna","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79713,876,"WLF","Wallis and Futuna","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79714,876,"WLF","Wallis and Futuna","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79715,876,"WLF","Wallis and Futuna","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79716,876,"WLF","Wallis and Futuna","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79717,876,"WLF","Wallis and Futuna","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79718,876,"WLF","Wallis and Futuna","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79719,876,"WLF","Wallis and Futuna","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79720,876,"WLF","Wallis and Futuna","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79721,876,"WLF","Wallis and Futuna","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79722,876,"WLF","Wallis and Futuna","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79723,876,"WLF","Wallis and Futuna","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79724,876,"WLF","Wallis and Futuna","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79725,876,"WLF","Wallis and Futuna","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79726,876,"WLF","Wallis and Futuna","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79727,876,"WLF","Wallis and Futuna","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79728,876,"WLF","Wallis and Futuna","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79729,876,"WLF","Wallis and Futuna","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WLF/wlf_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79730,882,"WSM","Samoa","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79731,882,"WSM","Samoa","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79732,882,"WSM","Samoa","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79733,882,"WSM","Samoa","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79734,882,"WSM","Samoa","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79735,882,"WSM","Samoa","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79736,882,"WSM","Samoa","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79737,882,"WSM","Samoa","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79738,882,"WSM","Samoa","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79739,882,"WSM","Samoa","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79740,882,"WSM","Samoa","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79741,882,"WSM","Samoa","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79742,882,"WSM","Samoa","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79743,882,"WSM","Samoa","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79744,882,"WSM","Samoa","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79745,882,"WSM","Samoa","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79746,882,"WSM","Samoa","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79747,882,"WSM","Samoa","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79748,882,"WSM","Samoa","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79749,882,"WSM","Samoa","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79750,882,"WSM","Samoa","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79751,882,"WSM","Samoa","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79752,882,"WSM","Samoa","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79753,882,"WSM","Samoa","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79754,882,"WSM","Samoa","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79755,882,"WSM","Samoa","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79756,882,"WSM","Samoa","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79757,882,"WSM","Samoa","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79758,882,"WSM","Samoa","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79759,882,"WSM","Samoa","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79760,882,"WSM","Samoa","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79761,882,"WSM","Samoa","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79762,882,"WSM","Samoa","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79763,882,"WSM","Samoa","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79764,882,"WSM","Samoa","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79765,882,"WSM","Samoa","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/WSM/wsm_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79766,887,"YEM","Yemen","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79767,887,"YEM","Yemen","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79768,887,"YEM","Yemen","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79769,887,"YEM","Yemen","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79770,887,"YEM","Yemen","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79771,887,"YEM","Yemen","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79772,887,"YEM","Yemen","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79773,887,"YEM","Yemen","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79774,887,"YEM","Yemen","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79775,887,"YEM","Yemen","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79776,887,"YEM","Yemen","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79777,887,"YEM","Yemen","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79778,887,"YEM","Yemen","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79779,887,"YEM","Yemen","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79780,887,"YEM","Yemen","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79781,887,"YEM","Yemen","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79782,887,"YEM","Yemen","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79783,887,"YEM","Yemen","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79784,887,"YEM","Yemen","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79785,887,"YEM","Yemen","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79786,887,"YEM","Yemen","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79787,887,"YEM","Yemen","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79788,887,"YEM","Yemen","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79789,887,"YEM","Yemen","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79790,887,"YEM","Yemen","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79791,887,"YEM","Yemen","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79792,887,"YEM","Yemen","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79793,887,"YEM","Yemen","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79794,887,"YEM","Yemen","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79795,887,"YEM","Yemen","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79796,887,"YEM","Yemen","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79797,887,"YEM","Yemen","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79798,887,"YEM","Yemen","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79799,887,"YEM","Yemen","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79800,887,"YEM","Yemen","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79801,887,"YEM","Yemen","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/YEM/yem_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79802,894,"ZMB","Zambia","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79803,894,"ZMB","Zambia","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79804,894,"ZMB","Zambia","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79805,894,"ZMB","Zambia","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79806,894,"ZMB","Zambia","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79807,894,"ZMB","Zambia","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79808,894,"ZMB","Zambia","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79809,894,"ZMB","Zambia","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79810,894,"ZMB","Zambia","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79811,894,"ZMB","Zambia","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79812,894,"ZMB","Zambia","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79813,894,"ZMB","Zambia","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79814,894,"ZMB","Zambia","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79815,894,"ZMB","Zambia","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79816,894,"ZMB","Zambia","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79817,894,"ZMB","Zambia","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79818,894,"ZMB","Zambia","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79819,894,"ZMB","Zambia","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79820,894,"ZMB","Zambia","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79821,894,"ZMB","Zambia","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79822,894,"ZMB","Zambia","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79823,894,"ZMB","Zambia","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79824,894,"ZMB","Zambia","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79825,894,"ZMB","Zambia","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79826,894,"ZMB","Zambia","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79827,894,"ZMB","Zambia","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79828,894,"ZMB","Zambia","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79829,894,"ZMB","Zambia","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79830,894,"ZMB","Zambia","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79831,894,"ZMB","Zambia","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79832,894,"ZMB","Zambia","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79833,894,"ZMB","Zambia","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79834,894,"ZMB","Zambia","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79835,894,"ZMB","Zambia","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79836,894,"ZMB","Zambia","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79837,894,"ZMB","Zambia","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/ZMB/zmb_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79838,900,"KOS","Kosovo","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79839,900,"KOS","Kosovo","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79840,900,"KOS","Kosovo","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79841,900,"KOS","Kosovo","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79842,900,"KOS","Kosovo","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79843,900,"KOS","Kosovo","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79844,900,"KOS","Kosovo","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79845,900,"KOS","Kosovo","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79846,900,"KOS","Kosovo","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79847,900,"KOS","Kosovo","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79848,900,"KOS","Kosovo","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79849,900,"KOS","Kosovo","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79850,900,"KOS","Kosovo","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79851,900,"KOS","Kosovo","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79852,900,"KOS","Kosovo","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79853,900,"KOS","Kosovo","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79854,900,"KOS","Kosovo","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79855,900,"KOS","Kosovo","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79856,900,"KOS","Kosovo","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79857,900,"KOS","Kosovo","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79858,900,"KOS","Kosovo","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79859,900,"KOS","Kosovo","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79860,900,"KOS","Kosovo","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79861,900,"KOS","Kosovo","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79862,900,"KOS","Kosovo","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79863,900,"KOS","Kosovo","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79864,900,"KOS","Kosovo","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79865,900,"KOS","Kosovo","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79866,900,"KOS","Kosovo","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79867,900,"KOS","Kosovo","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79868,900,"KOS","Kosovo","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79869,900,"KOS","Kosovo","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79870,900,"KOS","Kosovo","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79871,900,"KOS","Kosovo","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79872,900,"KOS","Kosovo","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79873,900,"KOS","Kosovo","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/KOS/kos_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79874,901,"SPR","Spratly Islands","agesex_f_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_0_2020.tif","Estimated 0-12 month old female per grid-cell  in 2020"
79875,901,"SPR","Spratly Islands","agesex_f_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_1_2020.tif","Estimated 1-4 year old female per grid-cell  in 2020"
79876,901,"SPR","Spratly Islands","agesex_f_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_5_2020.tif","Estimated 5-8 year old female per grid-cell  in 2020"
79877,901,"SPR","Spratly Islands","agesex_f_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_10_2020.tif","Estimated 10-14 year old female per grid-cell  in 2020"
79878,901,"SPR","Spratly Islands","agesex_f_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_15_2020.tif","Estimated 15-19 year old female per grid-cell  in 2020"
79879,901,"SPR","Spratly Islands","agesex_f_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_20_2020.tif","Estimated 20-24 year old female per grid-cell  in 2020"
79880,901,"SPR","Spratly Islands","agesex_f_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_25_2020.tif","Estimated 25-29 year old female per grid-cell  in 2020"
79881,901,"SPR","Spratly Islands","agesex_f_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_30_2020.tif","Estimated 30-34 year old female per grid-cell  in 2020"
79882,901,"SPR","Spratly Islands","agesex_f_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_35_2020.tif","Estimated 35-39 year old female per grid-cell  in 2020"
79883,901,"SPR","Spratly Islands","agesex_f_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_40_2020.tif","Estimated 40-44 year old female per grid-cell  in 2020"
79884,901,"SPR","Spratly Islands","agesex_f_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_45_2020.tif","Estimated 45-49 year old female per grid-cell  in 2020"
79885,901,"SPR","Spratly Islands","agesex_f_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_50_2020.tif","Estimated 50-54 year old female per grid-cell  in 2020"
79886,901,"SPR","Spratly Islands","agesex_f_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_55_2020.tif","Estimated 55-59 year old female per grid-cell  in 2020"
79887,901,"SPR","Spratly Islands","agesex_f_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_60_2020.tif","Estimated 60-64 year old female per grid-cell  in 2020"
79888,901,"SPR","Spratly Islands","agesex_f_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_65_2020.tif","Estimated 65-69 year old female per grid-cell  in 2020"
79889,901,"SPR","Spratly Islands","agesex_f_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_70_2020.tif","Estimated 70-74 year old female per grid-cell  in 2020"
79890,901,"SPR","Spratly Islands","agesex_f_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_75_2020.tif","Estimated 75-79 year old female per grid-cell  in 2020"
79891,901,"SPR","Spratly Islands","agesex_f_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_f_80_2020.tif","Estimated 80 year old female per grid-cell  in 2020"
79892,901,"SPR","Spratly Islands","agesex_m_0_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_0_2020.tif","Estimated 0-12 month old male per grid-cell  in 2020"
79893,901,"SPR","Spratly Islands","agesex_m_1_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_1_2020.tif","Estimated 1-4 year old male per grid-cell  in 2020"
79894,901,"SPR","Spratly Islands","agesex_m_5_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_5_2020.tif","Estimated 5-8 year old male per grid-cell  in 2020"
79895,901,"SPR","Spratly Islands","agesex_m_10_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_10_2020.tif","Estimated 10-14 year old male per grid-cell  in 2020"
79896,901,"SPR","Spratly Islands","agesex_m_15_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_15_2020.tif","Estimated 15-19 year old male per grid-cell  in 2020"
79897,901,"SPR","Spratly Islands","agesex_m_20_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_20_2020.tif","Estimated 20-24 year old male per grid-cell  in 2020"
79898,901,"SPR","Spratly Islands","agesex_m_25_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_25_2020.tif","Estimated 25-29 year old male per grid-cell  in 2020"
79899,901,"SPR","Spratly Islands","agesex_m_30_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_30_2020.tif","Estimated 30-34 year old male per grid-cell  in 2020"
79900,901,"SPR","Spratly Islands","agesex_m_35_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_35_2020.tif","Estimated 35-39 year old male per grid-cell  in 2020"
79901,901,"SPR","Spratly Islands","agesex_m_40_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_40_2020.tif","Estimated 40-44 year old male per grid-cell  in 2020"
79902,901,"SPR","Spratly Islands","agesex_m_45_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_45_2020.tif","Estimated 45-49 year old male per grid-cell  in 2020"
79903,901,"SPR","Spratly Islands","agesex_m_50_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_50_2020.tif","Estimated 50-54 year old male per grid-cell  in 2020"
79904,901,"SPR","Spratly Islands","agesex_m_55_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_55_2020.tif","Estimated 55-59 year old male per grid-cell  in 2020"
79905,901,"SPR","Spratly Islands","agesex_m_60_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_60_2020.tif","Estimated 60-64 year old male per grid-cell  in 2020"
79906,901,"SPR","Spratly Islands","agesex_m_65_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_65_2020.tif","Estimated 65-69 year old male per grid-cell  in 2020"
79907,901,"SPR","Spratly Islands","agesex_m_70_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_70_2020.tif","Estimated 70-74 year old male per grid-cell  in 2020"
79908,901,"SPR","Spratly Islands","agesex_m_75_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_75_2020.tif","Estimated 75-79 year old male per grid-cell  in 2020"
79909,901,"SPR","Spratly Islands","agesex_m_80_2020","GIS/AgeSex_structures/Global_2000_2020/2020/SPR/spr_m_80_2020.tif","Estimated 80 year old male per grid-cell  in 2020"
79910,643,"RUS","Russia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79911,643,"RUS","Russia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79912,643,"RUS","Russia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79913,643,"RUS","Russia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79914,643,"RUS","Russia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79915,643,"RUS","Russia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79916,643,"RUS","Russia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79917,643,"RUS","Russia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79918,643,"RUS","Russia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79919,643,"RUS","Russia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79920,643,"RUS","Russia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79921,643,"RUS","Russia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79922,643,"RUS","Russia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79923,643,"RUS","Russia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79924,643,"RUS","Russia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79925,643,"RUS","Russia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79926,643,"RUS","Russia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79927,643,"RUS","Russia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79928,643,"RUS","Russia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79929,643,"RUS","Russia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79930,643,"RUS","Russia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79931,643,"RUS","Russia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79932,643,"RUS","Russia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79933,643,"RUS","Russia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79934,643,"RUS","Russia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79935,643,"RUS","Russia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79936,643,"RUS","Russia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79937,643,"RUS","Russia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79938,643,"RUS","Russia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79939,643,"RUS","Russia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79940,643,"RUS","Russia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79941,643,"RUS","Russia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79942,643,"RUS","Russia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79943,643,"RUS","Russia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79944,643,"RUS","Russia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79945,643,"RUS","Russia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RUS/rus_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79946,360,"IDN","Indonesia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79947,360,"IDN","Indonesia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79948,360,"IDN","Indonesia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79949,360,"IDN","Indonesia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79950,360,"IDN","Indonesia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79951,360,"IDN","Indonesia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79952,360,"IDN","Indonesia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79953,360,"IDN","Indonesia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79954,360,"IDN","Indonesia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79955,360,"IDN","Indonesia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79956,360,"IDN","Indonesia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79957,360,"IDN","Indonesia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79958,360,"IDN","Indonesia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79959,360,"IDN","Indonesia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79960,360,"IDN","Indonesia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79961,360,"IDN","Indonesia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79962,360,"IDN","Indonesia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79963,360,"IDN","Indonesia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79964,360,"IDN","Indonesia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79965,360,"IDN","Indonesia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79966,360,"IDN","Indonesia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79967,360,"IDN","Indonesia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79968,360,"IDN","Indonesia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79969,360,"IDN","Indonesia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79970,360,"IDN","Indonesia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79971,360,"IDN","Indonesia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79972,360,"IDN","Indonesia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79973,360,"IDN","Indonesia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79974,360,"IDN","Indonesia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79975,360,"IDN","Indonesia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79976,360,"IDN","Indonesia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79977,360,"IDN","Indonesia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79978,360,"IDN","Indonesia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79979,360,"IDN","Indonesia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79980,360,"IDN","Indonesia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79981,360,"IDN","Indonesia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IDN/idn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79982,840,"USA","United States","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79983,840,"USA","United States","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79984,840,"USA","United States","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79985,840,"USA","United States","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79986,840,"USA","United States","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79987,840,"USA","United States","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79988,840,"USA","United States","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79989,840,"USA","United States","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79990,840,"USA","United States","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79991,840,"USA","United States","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79992,840,"USA","United States","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79993,840,"USA","United States","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79994,840,"USA","United States","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79995,840,"USA","United States","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79996,840,"USA","United States","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79997,840,"USA","United States","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79998,840,"USA","United States","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
79999,840,"USA","United States","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80000,840,"USA","United States","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80001,840,"USA","United States","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80002,840,"USA","United States","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80003,840,"USA","United States","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80004,840,"USA","United States","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80005,840,"USA","United States","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80006,840,"USA","United States","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80007,840,"USA","United States","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80008,840,"USA","United States","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80009,840,"USA","United States","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80010,840,"USA","United States","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80011,840,"USA","United States","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80012,840,"USA","United States","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80013,840,"USA","United States","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80014,840,"USA","United States","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80015,840,"USA","United States","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80016,840,"USA","United States","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80017,840,"USA","United States","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/USA/usa_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80018,850,"VIR","Virgin_Islands_U_S","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80019,850,"VIR","Virgin_Islands_U_S","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80020,850,"VIR","Virgin_Islands_U_S","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80021,850,"VIR","Virgin_Islands_U_S","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80022,850,"VIR","Virgin_Islands_U_S","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80023,850,"VIR","Virgin_Islands_U_S","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80024,850,"VIR","Virgin_Islands_U_S","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80025,850,"VIR","Virgin_Islands_U_S","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80026,850,"VIR","Virgin_Islands_U_S","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80027,850,"VIR","Virgin_Islands_U_S","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80028,850,"VIR","Virgin_Islands_U_S","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80029,850,"VIR","Virgin_Islands_U_S","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80030,850,"VIR","Virgin_Islands_U_S","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80031,850,"VIR","Virgin_Islands_U_S","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80032,850,"VIR","Virgin_Islands_U_S","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80033,850,"VIR","Virgin_Islands_U_S","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80034,850,"VIR","Virgin_Islands_U_S","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80035,850,"VIR","Virgin_Islands_U_S","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80036,850,"VIR","Virgin_Islands_U_S","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80037,850,"VIR","Virgin_Islands_U_S","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80038,850,"VIR","Virgin_Islands_U_S","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80039,850,"VIR","Virgin_Islands_U_S","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80040,850,"VIR","Virgin_Islands_U_S","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80041,850,"VIR","Virgin_Islands_U_S","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80042,850,"VIR","Virgin_Islands_U_S","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80043,850,"VIR","Virgin_Islands_U_S","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80044,850,"VIR","Virgin_Islands_U_S","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80045,850,"VIR","Virgin_Islands_U_S","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80046,850,"VIR","Virgin_Islands_U_S","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80047,850,"VIR","Virgin_Islands_U_S","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80048,850,"VIR","Virgin_Islands_U_S","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80049,850,"VIR","Virgin_Islands_U_S","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80050,850,"VIR","Virgin_Islands_U_S","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80051,850,"VIR","Virgin_Islands_U_S","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80052,850,"VIR","Virgin_Islands_U_S","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80053,850,"VIR","Virgin_Islands_U_S","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VIR/vir_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80054,304,"GRL","Greenland","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80055,304,"GRL","Greenland","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80056,304,"GRL","Greenland","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80057,304,"GRL","Greenland","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80058,304,"GRL","Greenland","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80059,304,"GRL","Greenland","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80060,304,"GRL","Greenland","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80061,304,"GRL","Greenland","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80062,304,"GRL","Greenland","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80063,304,"GRL","Greenland","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80064,304,"GRL","Greenland","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80065,304,"GRL","Greenland","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80066,304,"GRL","Greenland","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80067,304,"GRL","Greenland","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80068,304,"GRL","Greenland","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80069,304,"GRL","Greenland","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80070,304,"GRL","Greenland","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80071,304,"GRL","Greenland","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80072,304,"GRL","Greenland","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80073,304,"GRL","Greenland","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80074,304,"GRL","Greenland","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80075,304,"GRL","Greenland","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80076,304,"GRL","Greenland","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80077,304,"GRL","Greenland","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80078,304,"GRL","Greenland","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80079,304,"GRL","Greenland","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80080,304,"GRL","Greenland","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80081,304,"GRL","Greenland","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80082,304,"GRL","Greenland","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80083,304,"GRL","Greenland","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80084,304,"GRL","Greenland","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80085,304,"GRL","Greenland","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80086,304,"GRL","Greenland","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80087,304,"GRL","Greenland","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80088,304,"GRL","Greenland","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80089,304,"GRL","Greenland","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRL/grl_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80090,156,"CHN","China","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80091,156,"CHN","China","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80092,156,"CHN","China","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80093,156,"CHN","China","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80094,156,"CHN","China","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80095,156,"CHN","China","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80096,156,"CHN","China","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80097,156,"CHN","China","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80098,156,"CHN","China","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80099,156,"CHN","China","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80100,156,"CHN","China","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80101,156,"CHN","China","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80102,156,"CHN","China","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80103,156,"CHN","China","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80104,156,"CHN","China","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80105,156,"CHN","China","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80106,156,"CHN","China","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80107,156,"CHN","China","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80108,156,"CHN","China","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80109,156,"CHN","China","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80110,156,"CHN","China","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80111,156,"CHN","China","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80112,156,"CHN","China","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80113,156,"CHN","China","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80114,156,"CHN","China","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80115,156,"CHN","China","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80116,156,"CHN","China","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80117,156,"CHN","China","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80118,156,"CHN","China","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80119,156,"CHN","China","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80120,156,"CHN","China","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80121,156,"CHN","China","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80122,156,"CHN","China","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80123,156,"CHN","China","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80124,156,"CHN","China","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80125,156,"CHN","China","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHN/chn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80126,36,"AUS","Australia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80127,36,"AUS","Australia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80128,36,"AUS","Australia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80129,36,"AUS","Australia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80130,36,"AUS","Australia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80131,36,"AUS","Australia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80132,36,"AUS","Australia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80133,36,"AUS","Australia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80134,36,"AUS","Australia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80135,36,"AUS","Australia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80136,36,"AUS","Australia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80137,36,"AUS","Australia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80138,36,"AUS","Australia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80139,36,"AUS","Australia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80140,36,"AUS","Australia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80141,36,"AUS","Australia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80142,36,"AUS","Australia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80143,36,"AUS","Australia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80144,36,"AUS","Australia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80145,36,"AUS","Australia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80146,36,"AUS","Australia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80147,36,"AUS","Australia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80148,36,"AUS","Australia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80149,36,"AUS","Australia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80150,36,"AUS","Australia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80151,36,"AUS","Australia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80152,36,"AUS","Australia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80153,36,"AUS","Australia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80154,36,"AUS","Australia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80155,36,"AUS","Australia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80156,36,"AUS","Australia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80157,36,"AUS","Australia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80158,36,"AUS","Australia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80159,36,"AUS","Australia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80160,36,"AUS","Australia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80161,36,"AUS","Australia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUS/aus_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80162,76,"BRA","Brazil","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80163,76,"BRA","Brazil","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80164,76,"BRA","Brazil","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80165,76,"BRA","Brazil","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80166,76,"BRA","Brazil","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80167,76,"BRA","Brazil","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80168,76,"BRA","Brazil","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80169,76,"BRA","Brazil","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80170,76,"BRA","Brazil","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80171,76,"BRA","Brazil","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80172,76,"BRA","Brazil","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80173,76,"BRA","Brazil","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80174,76,"BRA","Brazil","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80175,76,"BRA","Brazil","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80176,76,"BRA","Brazil","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80177,76,"BRA","Brazil","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80178,76,"BRA","Brazil","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80179,76,"BRA","Brazil","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80180,76,"BRA","Brazil","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80181,76,"BRA","Brazil","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80182,76,"BRA","Brazil","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80183,76,"BRA","Brazil","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80184,76,"BRA","Brazil","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80185,76,"BRA","Brazil","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80186,76,"BRA","Brazil","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80187,76,"BRA","Brazil","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80188,76,"BRA","Brazil","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80189,76,"BRA","Brazil","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80190,76,"BRA","Brazil","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80191,76,"BRA","Brazil","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80192,76,"BRA","Brazil","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80193,76,"BRA","Brazil","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80194,76,"BRA","Brazil","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80195,76,"BRA","Brazil","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80196,76,"BRA","Brazil","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80197,76,"BRA","Brazil","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRA/bra_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80198,124,"CAN","Canada","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80199,124,"CAN","Canada","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80200,124,"CAN","Canada","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80201,124,"CAN","Canada","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80202,124,"CAN","Canada","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80203,124,"CAN","Canada","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80204,124,"CAN","Canada","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80205,124,"CAN","Canada","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80206,124,"CAN","Canada","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80207,124,"CAN","Canada","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80208,124,"CAN","Canada","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80209,124,"CAN","Canada","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80210,124,"CAN","Canada","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80211,124,"CAN","Canada","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80212,124,"CAN","Canada","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80213,124,"CAN","Canada","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80214,124,"CAN","Canada","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80215,124,"CAN","Canada","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80216,124,"CAN","Canada","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80217,124,"CAN","Canada","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80218,124,"CAN","Canada","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80219,124,"CAN","Canada","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80220,124,"CAN","Canada","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80221,124,"CAN","Canada","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80222,124,"CAN","Canada","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80223,124,"CAN","Canada","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80224,124,"CAN","Canada","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80225,124,"CAN","Canada","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80226,124,"CAN","Canada","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80227,124,"CAN","Canada","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80228,124,"CAN","Canada","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80229,124,"CAN","Canada","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80230,124,"CAN","Canada","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80231,124,"CAN","Canada","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80232,124,"CAN","Canada","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80233,124,"CAN","Canada","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAN/can_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80234,152,"CHL","Chile","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80235,152,"CHL","Chile","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80236,152,"CHL","Chile","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80237,152,"CHL","Chile","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80238,152,"CHL","Chile","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80239,152,"CHL","Chile","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80240,152,"CHL","Chile","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80241,152,"CHL","Chile","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80242,152,"CHL","Chile","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80243,152,"CHL","Chile","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80244,152,"CHL","Chile","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80245,152,"CHL","Chile","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80246,152,"CHL","Chile","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80247,152,"CHL","Chile","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80248,152,"CHL","Chile","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80249,152,"CHL","Chile","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80250,152,"CHL","Chile","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80251,152,"CHL","Chile","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80252,152,"CHL","Chile","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80253,152,"CHL","Chile","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80254,152,"CHL","Chile","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80255,152,"CHL","Chile","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80256,152,"CHL","Chile","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80257,152,"CHL","Chile","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80258,152,"CHL","Chile","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80259,152,"CHL","Chile","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80260,152,"CHL","Chile","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80261,152,"CHL","Chile","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80262,152,"CHL","Chile","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80263,152,"CHL","Chile","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80264,152,"CHL","Chile","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80265,152,"CHL","Chile","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80266,152,"CHL","Chile","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80267,152,"CHL","Chile","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80268,152,"CHL","Chile","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80269,152,"CHL","Chile","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHL/chl_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80270,4,"AFG","Afghanistan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80271,4,"AFG","Afghanistan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80272,4,"AFG","Afghanistan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80273,4,"AFG","Afghanistan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80274,4,"AFG","Afghanistan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80275,4,"AFG","Afghanistan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80276,4,"AFG","Afghanistan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80277,4,"AFG","Afghanistan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80278,4,"AFG","Afghanistan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80279,4,"AFG","Afghanistan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80280,4,"AFG","Afghanistan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80281,4,"AFG","Afghanistan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80282,4,"AFG","Afghanistan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80283,4,"AFG","Afghanistan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80284,4,"AFG","Afghanistan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80285,4,"AFG","Afghanistan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80286,4,"AFG","Afghanistan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80287,4,"AFG","Afghanistan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80288,4,"AFG","Afghanistan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80289,4,"AFG","Afghanistan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80290,4,"AFG","Afghanistan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80291,4,"AFG","Afghanistan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80292,4,"AFG","Afghanistan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80293,4,"AFG","Afghanistan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80294,4,"AFG","Afghanistan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80295,4,"AFG","Afghanistan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80296,4,"AFG","Afghanistan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80297,4,"AFG","Afghanistan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80298,4,"AFG","Afghanistan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80299,4,"AFG","Afghanistan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80300,4,"AFG","Afghanistan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80301,4,"AFG","Afghanistan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80302,4,"AFG","Afghanistan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80303,4,"AFG","Afghanistan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80304,4,"AFG","Afghanistan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80305,4,"AFG","Afghanistan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AFG/afg_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80306,8,"ALB","Albania","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80307,8,"ALB","Albania","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80308,8,"ALB","Albania","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80309,8,"ALB","Albania","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80310,8,"ALB","Albania","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80311,8,"ALB","Albania","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80312,8,"ALB","Albania","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80313,8,"ALB","Albania","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80314,8,"ALB","Albania","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80315,8,"ALB","Albania","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80316,8,"ALB","Albania","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80317,8,"ALB","Albania","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80318,8,"ALB","Albania","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80319,8,"ALB","Albania","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80320,8,"ALB","Albania","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80321,8,"ALB","Albania","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80322,8,"ALB","Albania","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80323,8,"ALB","Albania","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80324,8,"ALB","Albania","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80325,8,"ALB","Albania","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80326,8,"ALB","Albania","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80327,8,"ALB","Albania","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80328,8,"ALB","Albania","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80329,8,"ALB","Albania","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80330,8,"ALB","Albania","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80331,8,"ALB","Albania","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80332,8,"ALB","Albania","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80333,8,"ALB","Albania","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80334,8,"ALB","Albania","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80335,8,"ALB","Albania","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80336,8,"ALB","Albania","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80337,8,"ALB","Albania","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80338,8,"ALB","Albania","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80339,8,"ALB","Albania","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80340,8,"ALB","Albania","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80341,8,"ALB","Albania","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALB/alb_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80342,12,"DZA","Algeria","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80343,12,"DZA","Algeria","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80344,12,"DZA","Algeria","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80345,12,"DZA","Algeria","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80346,12,"DZA","Algeria","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80347,12,"DZA","Algeria","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80348,12,"DZA","Algeria","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80349,12,"DZA","Algeria","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80350,12,"DZA","Algeria","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80351,12,"DZA","Algeria","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80352,12,"DZA","Algeria","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80353,12,"DZA","Algeria","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80354,12,"DZA","Algeria","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80355,12,"DZA","Algeria","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80356,12,"DZA","Algeria","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80357,12,"DZA","Algeria","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80358,12,"DZA","Algeria","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80359,12,"DZA","Algeria","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80360,12,"DZA","Algeria","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80361,12,"DZA","Algeria","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80362,12,"DZA","Algeria","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80363,12,"DZA","Algeria","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80364,12,"DZA","Algeria","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80365,12,"DZA","Algeria","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80366,12,"DZA","Algeria","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80367,12,"DZA","Algeria","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80368,12,"DZA","Algeria","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80369,12,"DZA","Algeria","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80370,12,"DZA","Algeria","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80371,12,"DZA","Algeria","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80372,12,"DZA","Algeria","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80373,12,"DZA","Algeria","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80374,12,"DZA","Algeria","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80375,12,"DZA","Algeria","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80376,12,"DZA","Algeria","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80377,12,"DZA","Algeria","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DZA/dza_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80378,16,"ASM","American Samoa","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80379,16,"ASM","American Samoa","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80380,16,"ASM","American Samoa","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80381,16,"ASM","American Samoa","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80382,16,"ASM","American Samoa","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80383,16,"ASM","American Samoa","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80384,16,"ASM","American Samoa","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80385,16,"ASM","American Samoa","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80386,16,"ASM","American Samoa","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80387,16,"ASM","American Samoa","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80388,16,"ASM","American Samoa","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80389,16,"ASM","American Samoa","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80390,16,"ASM","American Samoa","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80391,16,"ASM","American Samoa","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80392,16,"ASM","American Samoa","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80393,16,"ASM","American Samoa","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80394,16,"ASM","American Samoa","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80395,16,"ASM","American Samoa","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80396,16,"ASM","American Samoa","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80397,16,"ASM","American Samoa","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80398,16,"ASM","American Samoa","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80399,16,"ASM","American Samoa","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80400,16,"ASM","American Samoa","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80401,16,"ASM","American Samoa","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80402,16,"ASM","American Samoa","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80403,16,"ASM","American Samoa","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80404,16,"ASM","American Samoa","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80405,16,"ASM","American Samoa","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80406,16,"ASM","American Samoa","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80407,16,"ASM","American Samoa","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80408,16,"ASM","American Samoa","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80409,16,"ASM","American Samoa","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80410,16,"ASM","American Samoa","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80411,16,"ASM","American Samoa","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80412,16,"ASM","American Samoa","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80413,16,"ASM","American Samoa","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ASM/asm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80414,20,"AND","Andorra","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80415,20,"AND","Andorra","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80416,20,"AND","Andorra","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80417,20,"AND","Andorra","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80418,20,"AND","Andorra","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80419,20,"AND","Andorra","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80420,20,"AND","Andorra","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80421,20,"AND","Andorra","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80422,20,"AND","Andorra","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80423,20,"AND","Andorra","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80424,20,"AND","Andorra","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80425,20,"AND","Andorra","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80426,20,"AND","Andorra","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80427,20,"AND","Andorra","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80428,20,"AND","Andorra","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80429,20,"AND","Andorra","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80430,20,"AND","Andorra","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80431,20,"AND","Andorra","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80432,20,"AND","Andorra","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80433,20,"AND","Andorra","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80434,20,"AND","Andorra","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80435,20,"AND","Andorra","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80436,20,"AND","Andorra","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80437,20,"AND","Andorra","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80438,20,"AND","Andorra","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80439,20,"AND","Andorra","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80440,20,"AND","Andorra","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80441,20,"AND","Andorra","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80442,20,"AND","Andorra","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80443,20,"AND","Andorra","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80444,20,"AND","Andorra","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80445,20,"AND","Andorra","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80446,20,"AND","Andorra","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80447,20,"AND","Andorra","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80448,20,"AND","Andorra","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80449,20,"AND","Andorra","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AND/and_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80450,24,"AGO","Angola","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80451,24,"AGO","Angola","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80452,24,"AGO","Angola","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80453,24,"AGO","Angola","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80454,24,"AGO","Angola","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80455,24,"AGO","Angola","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80456,24,"AGO","Angola","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80457,24,"AGO","Angola","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80458,24,"AGO","Angola","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80459,24,"AGO","Angola","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80460,24,"AGO","Angola","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80461,24,"AGO","Angola","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80462,24,"AGO","Angola","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80463,24,"AGO","Angola","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80464,24,"AGO","Angola","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80465,24,"AGO","Angola","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80466,24,"AGO","Angola","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80467,24,"AGO","Angola","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80468,24,"AGO","Angola","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80469,24,"AGO","Angola","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80470,24,"AGO","Angola","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80471,24,"AGO","Angola","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80472,24,"AGO","Angola","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80473,24,"AGO","Angola","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80474,24,"AGO","Angola","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80475,24,"AGO","Angola","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80476,24,"AGO","Angola","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80477,24,"AGO","Angola","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80478,24,"AGO","Angola","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80479,24,"AGO","Angola","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80480,24,"AGO","Angola","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80481,24,"AGO","Angola","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80482,24,"AGO","Angola","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80483,24,"AGO","Angola","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80484,24,"AGO","Angola","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80485,24,"AGO","Angola","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AGO/ago_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80486,28,"ATG","Antigua and Barbuda","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80487,28,"ATG","Antigua and Barbuda","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80488,28,"ATG","Antigua and Barbuda","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80489,28,"ATG","Antigua and Barbuda","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80490,28,"ATG","Antigua and Barbuda","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80491,28,"ATG","Antigua and Barbuda","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80492,28,"ATG","Antigua and Barbuda","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80493,28,"ATG","Antigua and Barbuda","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80494,28,"ATG","Antigua and Barbuda","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80495,28,"ATG","Antigua and Barbuda","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80496,28,"ATG","Antigua and Barbuda","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80497,28,"ATG","Antigua and Barbuda","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80498,28,"ATG","Antigua and Barbuda","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80499,28,"ATG","Antigua and Barbuda","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80500,28,"ATG","Antigua and Barbuda","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80501,28,"ATG","Antigua and Barbuda","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80502,28,"ATG","Antigua and Barbuda","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80503,28,"ATG","Antigua and Barbuda","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80504,28,"ATG","Antigua and Barbuda","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80505,28,"ATG","Antigua and Barbuda","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80506,28,"ATG","Antigua and Barbuda","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80507,28,"ATG","Antigua and Barbuda","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80508,28,"ATG","Antigua and Barbuda","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80509,28,"ATG","Antigua and Barbuda","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80510,28,"ATG","Antigua and Barbuda","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80511,28,"ATG","Antigua and Barbuda","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80512,28,"ATG","Antigua and Barbuda","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80513,28,"ATG","Antigua and Barbuda","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80514,28,"ATG","Antigua and Barbuda","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80515,28,"ATG","Antigua and Barbuda","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80516,28,"ATG","Antigua and Barbuda","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80517,28,"ATG","Antigua and Barbuda","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80518,28,"ATG","Antigua and Barbuda","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80519,28,"ATG","Antigua and Barbuda","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80520,28,"ATG","Antigua and Barbuda","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80521,28,"ATG","Antigua and Barbuda","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ATG/atg_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80522,31,"AZE","Azerbaijan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80523,31,"AZE","Azerbaijan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80524,31,"AZE","Azerbaijan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80525,31,"AZE","Azerbaijan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80526,31,"AZE","Azerbaijan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80527,31,"AZE","Azerbaijan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80528,31,"AZE","Azerbaijan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80529,31,"AZE","Azerbaijan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80530,31,"AZE","Azerbaijan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80531,31,"AZE","Azerbaijan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80532,31,"AZE","Azerbaijan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80533,31,"AZE","Azerbaijan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80534,31,"AZE","Azerbaijan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80535,31,"AZE","Azerbaijan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80536,31,"AZE","Azerbaijan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80537,31,"AZE","Azerbaijan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80538,31,"AZE","Azerbaijan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80539,31,"AZE","Azerbaijan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80540,31,"AZE","Azerbaijan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80541,31,"AZE","Azerbaijan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80542,31,"AZE","Azerbaijan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80543,31,"AZE","Azerbaijan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80544,31,"AZE","Azerbaijan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80545,31,"AZE","Azerbaijan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80546,31,"AZE","Azerbaijan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80547,31,"AZE","Azerbaijan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80548,31,"AZE","Azerbaijan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80549,31,"AZE","Azerbaijan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80550,31,"AZE","Azerbaijan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80551,31,"AZE","Azerbaijan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80552,31,"AZE","Azerbaijan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80553,31,"AZE","Azerbaijan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80554,31,"AZE","Azerbaijan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80555,31,"AZE","Azerbaijan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80556,31,"AZE","Azerbaijan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80557,31,"AZE","Azerbaijan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AZE/aze_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80558,32,"ARG","Argentina","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80559,32,"ARG","Argentina","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80560,32,"ARG","Argentina","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80561,32,"ARG","Argentina","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80562,32,"ARG","Argentina","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80563,32,"ARG","Argentina","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80564,32,"ARG","Argentina","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80565,32,"ARG","Argentina","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80566,32,"ARG","Argentina","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80567,32,"ARG","Argentina","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80568,32,"ARG","Argentina","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80569,32,"ARG","Argentina","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80570,32,"ARG","Argentina","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80571,32,"ARG","Argentina","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80572,32,"ARG","Argentina","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80573,32,"ARG","Argentina","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80574,32,"ARG","Argentina","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80575,32,"ARG","Argentina","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80576,32,"ARG","Argentina","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80577,32,"ARG","Argentina","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80578,32,"ARG","Argentina","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80579,32,"ARG","Argentina","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80580,32,"ARG","Argentina","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80581,32,"ARG","Argentina","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80582,32,"ARG","Argentina","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80583,32,"ARG","Argentina","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80584,32,"ARG","Argentina","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80585,32,"ARG","Argentina","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80586,32,"ARG","Argentina","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80587,32,"ARG","Argentina","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80588,32,"ARG","Argentina","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80589,32,"ARG","Argentina","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80590,32,"ARG","Argentina","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80591,32,"ARG","Argentina","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80592,32,"ARG","Argentina","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80593,32,"ARG","Argentina","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARG/arg_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80594,40,"AUT","Austria","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80595,40,"AUT","Austria","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80596,40,"AUT","Austria","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80597,40,"AUT","Austria","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80598,40,"AUT","Austria","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80599,40,"AUT","Austria","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80600,40,"AUT","Austria","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80601,40,"AUT","Austria","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80602,40,"AUT","Austria","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80603,40,"AUT","Austria","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80604,40,"AUT","Austria","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80605,40,"AUT","Austria","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80606,40,"AUT","Austria","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80607,40,"AUT","Austria","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80608,40,"AUT","Austria","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80609,40,"AUT","Austria","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80610,40,"AUT","Austria","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80611,40,"AUT","Austria","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80612,40,"AUT","Austria","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80613,40,"AUT","Austria","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80614,40,"AUT","Austria","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80615,40,"AUT","Austria","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80616,40,"AUT","Austria","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80617,40,"AUT","Austria","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80618,40,"AUT","Austria","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80619,40,"AUT","Austria","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80620,40,"AUT","Austria","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80621,40,"AUT","Austria","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80622,40,"AUT","Austria","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80623,40,"AUT","Austria","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80624,40,"AUT","Austria","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80625,40,"AUT","Austria","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80626,40,"AUT","Austria","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80627,40,"AUT","Austria","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80628,40,"AUT","Austria","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80629,40,"AUT","Austria","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AUT/aut_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80630,44,"BHS","Bahamas","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80631,44,"BHS","Bahamas","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80632,44,"BHS","Bahamas","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80633,44,"BHS","Bahamas","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80634,44,"BHS","Bahamas","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80635,44,"BHS","Bahamas","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80636,44,"BHS","Bahamas","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80637,44,"BHS","Bahamas","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80638,44,"BHS","Bahamas","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80639,44,"BHS","Bahamas","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80640,44,"BHS","Bahamas","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80641,44,"BHS","Bahamas","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80642,44,"BHS","Bahamas","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80643,44,"BHS","Bahamas","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80644,44,"BHS","Bahamas","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80645,44,"BHS","Bahamas","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80646,44,"BHS","Bahamas","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80647,44,"BHS","Bahamas","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80648,44,"BHS","Bahamas","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80649,44,"BHS","Bahamas","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80650,44,"BHS","Bahamas","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80651,44,"BHS","Bahamas","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80652,44,"BHS","Bahamas","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80653,44,"BHS","Bahamas","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80654,44,"BHS","Bahamas","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80655,44,"BHS","Bahamas","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80656,44,"BHS","Bahamas","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80657,44,"BHS","Bahamas","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80658,44,"BHS","Bahamas","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80659,44,"BHS","Bahamas","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80660,44,"BHS","Bahamas","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80661,44,"BHS","Bahamas","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80662,44,"BHS","Bahamas","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80663,44,"BHS","Bahamas","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80664,44,"BHS","Bahamas","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80665,44,"BHS","Bahamas","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHS/bhs_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80666,48,"BHR","Bahrain","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80667,48,"BHR","Bahrain","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80668,48,"BHR","Bahrain","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80669,48,"BHR","Bahrain","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80670,48,"BHR","Bahrain","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80671,48,"BHR","Bahrain","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80672,48,"BHR","Bahrain","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80673,48,"BHR","Bahrain","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80674,48,"BHR","Bahrain","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80675,48,"BHR","Bahrain","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80676,48,"BHR","Bahrain","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80677,48,"BHR","Bahrain","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80678,48,"BHR","Bahrain","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80679,48,"BHR","Bahrain","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80680,48,"BHR","Bahrain","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80681,48,"BHR","Bahrain","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80682,48,"BHR","Bahrain","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80683,48,"BHR","Bahrain","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80684,48,"BHR","Bahrain","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80685,48,"BHR","Bahrain","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80686,48,"BHR","Bahrain","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80687,48,"BHR","Bahrain","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80688,48,"BHR","Bahrain","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80689,48,"BHR","Bahrain","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80690,48,"BHR","Bahrain","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80691,48,"BHR","Bahrain","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80692,48,"BHR","Bahrain","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80693,48,"BHR","Bahrain","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80694,48,"BHR","Bahrain","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80695,48,"BHR","Bahrain","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80696,48,"BHR","Bahrain","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80697,48,"BHR","Bahrain","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80698,48,"BHR","Bahrain","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80699,48,"BHR","Bahrain","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80700,48,"BHR","Bahrain","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80701,48,"BHR","Bahrain","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BHR/bhr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80702,50,"BGD","Bangladesh","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80703,50,"BGD","Bangladesh","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80704,50,"BGD","Bangladesh","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80705,50,"BGD","Bangladesh","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80706,50,"BGD","Bangladesh","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80707,50,"BGD","Bangladesh","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80708,50,"BGD","Bangladesh","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80709,50,"BGD","Bangladesh","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80710,50,"BGD","Bangladesh","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80711,50,"BGD","Bangladesh","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80712,50,"BGD","Bangladesh","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80713,50,"BGD","Bangladesh","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80714,50,"BGD","Bangladesh","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80715,50,"BGD","Bangladesh","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80716,50,"BGD","Bangladesh","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80717,50,"BGD","Bangladesh","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80718,50,"BGD","Bangladesh","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80719,50,"BGD","Bangladesh","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80720,50,"BGD","Bangladesh","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80721,50,"BGD","Bangladesh","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80722,50,"BGD","Bangladesh","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80723,50,"BGD","Bangladesh","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80724,50,"BGD","Bangladesh","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80725,50,"BGD","Bangladesh","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80726,50,"BGD","Bangladesh","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80727,50,"BGD","Bangladesh","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80728,50,"BGD","Bangladesh","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80729,50,"BGD","Bangladesh","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80730,50,"BGD","Bangladesh","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80731,50,"BGD","Bangladesh","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80732,50,"BGD","Bangladesh","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80733,50,"BGD","Bangladesh","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80734,50,"BGD","Bangladesh","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80735,50,"BGD","Bangladesh","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80736,50,"BGD","Bangladesh","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80737,50,"BGD","Bangladesh","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGD/bgd_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80738,51,"ARM","Armenia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80739,51,"ARM","Armenia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80740,51,"ARM","Armenia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80741,51,"ARM","Armenia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80742,51,"ARM","Armenia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80743,51,"ARM","Armenia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80744,51,"ARM","Armenia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80745,51,"ARM","Armenia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80746,51,"ARM","Armenia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80747,51,"ARM","Armenia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80748,51,"ARM","Armenia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80749,51,"ARM","Armenia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80750,51,"ARM","Armenia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80751,51,"ARM","Armenia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80752,51,"ARM","Armenia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80753,51,"ARM","Armenia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80754,51,"ARM","Armenia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80755,51,"ARM","Armenia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80756,51,"ARM","Armenia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80757,51,"ARM","Armenia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80758,51,"ARM","Armenia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80759,51,"ARM","Armenia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80760,51,"ARM","Armenia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80761,51,"ARM","Armenia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80762,51,"ARM","Armenia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80763,51,"ARM","Armenia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80764,51,"ARM","Armenia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80765,51,"ARM","Armenia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80766,51,"ARM","Armenia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80767,51,"ARM","Armenia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80768,51,"ARM","Armenia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80769,51,"ARM","Armenia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80770,51,"ARM","Armenia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80771,51,"ARM","Armenia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80772,51,"ARM","Armenia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80773,51,"ARM","Armenia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARM/arm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80774,52,"BRB","Barbados","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80775,52,"BRB","Barbados","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80776,52,"BRB","Barbados","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80777,52,"BRB","Barbados","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80778,52,"BRB","Barbados","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80779,52,"BRB","Barbados","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80780,52,"BRB","Barbados","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80781,52,"BRB","Barbados","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80782,52,"BRB","Barbados","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80783,52,"BRB","Barbados","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80784,52,"BRB","Barbados","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80785,52,"BRB","Barbados","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80786,52,"BRB","Barbados","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80787,52,"BRB","Barbados","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80788,52,"BRB","Barbados","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80789,52,"BRB","Barbados","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80790,52,"BRB","Barbados","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80791,52,"BRB","Barbados","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80792,52,"BRB","Barbados","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80793,52,"BRB","Barbados","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80794,52,"BRB","Barbados","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80795,52,"BRB","Barbados","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80796,52,"BRB","Barbados","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80797,52,"BRB","Barbados","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80798,52,"BRB","Barbados","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80799,52,"BRB","Barbados","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80800,52,"BRB","Barbados","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80801,52,"BRB","Barbados","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80802,52,"BRB","Barbados","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80803,52,"BRB","Barbados","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80804,52,"BRB","Barbados","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80805,52,"BRB","Barbados","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80806,52,"BRB","Barbados","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80807,52,"BRB","Barbados","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80808,52,"BRB","Barbados","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80809,52,"BRB","Barbados","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRB/brb_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80810,56,"BEL","Belgium","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80811,56,"BEL","Belgium","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80812,56,"BEL","Belgium","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80813,56,"BEL","Belgium","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80814,56,"BEL","Belgium","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80815,56,"BEL","Belgium","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80816,56,"BEL","Belgium","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80817,56,"BEL","Belgium","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80818,56,"BEL","Belgium","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80819,56,"BEL","Belgium","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80820,56,"BEL","Belgium","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80821,56,"BEL","Belgium","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80822,56,"BEL","Belgium","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80823,56,"BEL","Belgium","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80824,56,"BEL","Belgium","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80825,56,"BEL","Belgium","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80826,56,"BEL","Belgium","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80827,56,"BEL","Belgium","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80828,56,"BEL","Belgium","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80829,56,"BEL","Belgium","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80830,56,"BEL","Belgium","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80831,56,"BEL","Belgium","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80832,56,"BEL","Belgium","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80833,56,"BEL","Belgium","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80834,56,"BEL","Belgium","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80835,56,"BEL","Belgium","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80836,56,"BEL","Belgium","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80837,56,"BEL","Belgium","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80838,56,"BEL","Belgium","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80839,56,"BEL","Belgium","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80840,56,"BEL","Belgium","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80841,56,"BEL","Belgium","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80842,56,"BEL","Belgium","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80843,56,"BEL","Belgium","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80844,56,"BEL","Belgium","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80845,56,"BEL","Belgium","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEL/bel_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80846,60,"BMU","Bermuda","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80847,60,"BMU","Bermuda","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80848,60,"BMU","Bermuda","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80849,60,"BMU","Bermuda","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80850,60,"BMU","Bermuda","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80851,60,"BMU","Bermuda","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80852,60,"BMU","Bermuda","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80853,60,"BMU","Bermuda","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80854,60,"BMU","Bermuda","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80855,60,"BMU","Bermuda","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80856,60,"BMU","Bermuda","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80857,60,"BMU","Bermuda","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80858,60,"BMU","Bermuda","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80859,60,"BMU","Bermuda","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80860,60,"BMU","Bermuda","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80861,60,"BMU","Bermuda","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80862,60,"BMU","Bermuda","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80863,60,"BMU","Bermuda","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80864,60,"BMU","Bermuda","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80865,60,"BMU","Bermuda","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80866,60,"BMU","Bermuda","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80867,60,"BMU","Bermuda","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80868,60,"BMU","Bermuda","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80869,60,"BMU","Bermuda","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80870,60,"BMU","Bermuda","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80871,60,"BMU","Bermuda","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80872,60,"BMU","Bermuda","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80873,60,"BMU","Bermuda","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80874,60,"BMU","Bermuda","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80875,60,"BMU","Bermuda","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80876,60,"BMU","Bermuda","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80877,60,"BMU","Bermuda","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80878,60,"BMU","Bermuda","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80879,60,"BMU","Bermuda","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80880,60,"BMU","Bermuda","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80881,60,"BMU","Bermuda","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BMU/bmu_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80882,64,"BTN","Bhutan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80883,64,"BTN","Bhutan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80884,64,"BTN","Bhutan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80885,64,"BTN","Bhutan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80886,64,"BTN","Bhutan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80887,64,"BTN","Bhutan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80888,64,"BTN","Bhutan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80889,64,"BTN","Bhutan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80890,64,"BTN","Bhutan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80891,64,"BTN","Bhutan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80892,64,"BTN","Bhutan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80893,64,"BTN","Bhutan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80894,64,"BTN","Bhutan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80895,64,"BTN","Bhutan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80896,64,"BTN","Bhutan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80897,64,"BTN","Bhutan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80898,64,"BTN","Bhutan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80899,64,"BTN","Bhutan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80900,64,"BTN","Bhutan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80901,64,"BTN","Bhutan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80902,64,"BTN","Bhutan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80903,64,"BTN","Bhutan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80904,64,"BTN","Bhutan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80905,64,"BTN","Bhutan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80906,64,"BTN","Bhutan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80907,64,"BTN","Bhutan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80908,64,"BTN","Bhutan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80909,64,"BTN","Bhutan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80910,64,"BTN","Bhutan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80911,64,"BTN","Bhutan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80912,64,"BTN","Bhutan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80913,64,"BTN","Bhutan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80914,64,"BTN","Bhutan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80915,64,"BTN","Bhutan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80916,64,"BTN","Bhutan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80917,64,"BTN","Bhutan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BTN/btn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80918,68,"BOL","Bolivia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80919,68,"BOL","Bolivia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80920,68,"BOL","Bolivia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80921,68,"BOL","Bolivia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80922,68,"BOL","Bolivia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80923,68,"BOL","Bolivia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80924,68,"BOL","Bolivia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80925,68,"BOL","Bolivia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80926,68,"BOL","Bolivia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80927,68,"BOL","Bolivia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80928,68,"BOL","Bolivia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80929,68,"BOL","Bolivia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80930,68,"BOL","Bolivia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80931,68,"BOL","Bolivia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80932,68,"BOL","Bolivia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80933,68,"BOL","Bolivia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80934,68,"BOL","Bolivia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80935,68,"BOL","Bolivia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80936,68,"BOL","Bolivia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80937,68,"BOL","Bolivia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80938,68,"BOL","Bolivia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80939,68,"BOL","Bolivia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80940,68,"BOL","Bolivia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80941,68,"BOL","Bolivia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80942,68,"BOL","Bolivia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80943,68,"BOL","Bolivia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80944,68,"BOL","Bolivia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80945,68,"BOL","Bolivia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80946,68,"BOL","Bolivia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80947,68,"BOL","Bolivia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80948,68,"BOL","Bolivia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80949,68,"BOL","Bolivia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80950,68,"BOL","Bolivia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80951,68,"BOL","Bolivia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80952,68,"BOL","Bolivia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80953,68,"BOL","Bolivia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BOL/bol_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80954,70,"BIH","Bosnia and Herzegovina","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80955,70,"BIH","Bosnia and Herzegovina","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80956,70,"BIH","Bosnia and Herzegovina","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80957,70,"BIH","Bosnia and Herzegovina","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80958,70,"BIH","Bosnia and Herzegovina","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80959,70,"BIH","Bosnia and Herzegovina","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80960,70,"BIH","Bosnia and Herzegovina","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80961,70,"BIH","Bosnia and Herzegovina","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80962,70,"BIH","Bosnia and Herzegovina","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80963,70,"BIH","Bosnia and Herzegovina","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80964,70,"BIH","Bosnia and Herzegovina","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80965,70,"BIH","Bosnia and Herzegovina","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80966,70,"BIH","Bosnia and Herzegovina","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80967,70,"BIH","Bosnia and Herzegovina","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80968,70,"BIH","Bosnia and Herzegovina","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80969,70,"BIH","Bosnia and Herzegovina","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80970,70,"BIH","Bosnia and Herzegovina","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80971,70,"BIH","Bosnia and Herzegovina","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80972,70,"BIH","Bosnia and Herzegovina","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80973,70,"BIH","Bosnia and Herzegovina","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80974,70,"BIH","Bosnia and Herzegovina","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80975,70,"BIH","Bosnia and Herzegovina","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80976,70,"BIH","Bosnia and Herzegovina","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80977,70,"BIH","Bosnia and Herzegovina","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80978,70,"BIH","Bosnia and Herzegovina","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80979,70,"BIH","Bosnia and Herzegovina","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80980,70,"BIH","Bosnia and Herzegovina","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80981,70,"BIH","Bosnia and Herzegovina","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80982,70,"BIH","Bosnia and Herzegovina","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80983,70,"BIH","Bosnia and Herzegovina","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80984,70,"BIH","Bosnia and Herzegovina","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80985,70,"BIH","Bosnia and Herzegovina","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80986,70,"BIH","Bosnia and Herzegovina","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80987,70,"BIH","Bosnia and Herzegovina","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80988,70,"BIH","Bosnia and Herzegovina","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80989,70,"BIH","Bosnia and Herzegovina","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BIH/bih_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
80990,72,"BWA","Botswana","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80991,72,"BWA","Botswana","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80992,72,"BWA","Botswana","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80993,72,"BWA","Botswana","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80994,72,"BWA","Botswana","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80995,72,"BWA","Botswana","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80996,72,"BWA","Botswana","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80997,72,"BWA","Botswana","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80998,72,"BWA","Botswana","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
80999,72,"BWA","Botswana","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81000,72,"BWA","Botswana","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81001,72,"BWA","Botswana","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81002,72,"BWA","Botswana","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81003,72,"BWA","Botswana","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81004,72,"BWA","Botswana","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81005,72,"BWA","Botswana","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81006,72,"BWA","Botswana","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81007,72,"BWA","Botswana","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81008,72,"BWA","Botswana","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81009,72,"BWA","Botswana","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81010,72,"BWA","Botswana","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81011,72,"BWA","Botswana","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81012,72,"BWA","Botswana","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81013,72,"BWA","Botswana","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81014,72,"BWA","Botswana","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81015,72,"BWA","Botswana","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81016,72,"BWA","Botswana","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81017,72,"BWA","Botswana","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81018,72,"BWA","Botswana","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81019,72,"BWA","Botswana","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81020,72,"BWA","Botswana","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81021,72,"BWA","Botswana","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81022,72,"BWA","Botswana","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81023,72,"BWA","Botswana","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81024,72,"BWA","Botswana","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81025,72,"BWA","Botswana","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BWA/bwa_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81026,84,"BLZ","Belize","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81027,84,"BLZ","Belize","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81028,84,"BLZ","Belize","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81029,84,"BLZ","Belize","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81030,84,"BLZ","Belize","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81031,84,"BLZ","Belize","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81032,84,"BLZ","Belize","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81033,84,"BLZ","Belize","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81034,84,"BLZ","Belize","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81035,84,"BLZ","Belize","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81036,84,"BLZ","Belize","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81037,84,"BLZ","Belize","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81038,84,"BLZ","Belize","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81039,84,"BLZ","Belize","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81040,84,"BLZ","Belize","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81041,84,"BLZ","Belize","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81042,84,"BLZ","Belize","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81043,84,"BLZ","Belize","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81044,84,"BLZ","Belize","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81045,84,"BLZ","Belize","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81046,84,"BLZ","Belize","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81047,84,"BLZ","Belize","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81048,84,"BLZ","Belize","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81049,84,"BLZ","Belize","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81050,84,"BLZ","Belize","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81051,84,"BLZ","Belize","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81052,84,"BLZ","Belize","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81053,84,"BLZ","Belize","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81054,84,"BLZ","Belize","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81055,84,"BLZ","Belize","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81056,84,"BLZ","Belize","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81057,84,"BLZ","Belize","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81058,84,"BLZ","Belize","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81059,84,"BLZ","Belize","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81060,84,"BLZ","Belize","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81061,84,"BLZ","Belize","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLZ/blz_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81062,90,"SLB","Solomon Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81063,90,"SLB","Solomon Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81064,90,"SLB","Solomon Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81065,90,"SLB","Solomon Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81066,90,"SLB","Solomon Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81067,90,"SLB","Solomon Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81068,90,"SLB","Solomon Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81069,90,"SLB","Solomon Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81070,90,"SLB","Solomon Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81071,90,"SLB","Solomon Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81072,90,"SLB","Solomon Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81073,90,"SLB","Solomon Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81074,90,"SLB","Solomon Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81075,90,"SLB","Solomon Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81076,90,"SLB","Solomon Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81077,90,"SLB","Solomon Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81078,90,"SLB","Solomon Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81079,90,"SLB","Solomon Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81080,90,"SLB","Solomon Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81081,90,"SLB","Solomon Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81082,90,"SLB","Solomon Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81083,90,"SLB","Solomon Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81084,90,"SLB","Solomon Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81085,90,"SLB","Solomon Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81086,90,"SLB","Solomon Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81087,90,"SLB","Solomon Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81088,90,"SLB","Solomon Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81089,90,"SLB","Solomon Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81090,90,"SLB","Solomon Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81091,90,"SLB","Solomon Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81092,90,"SLB","Solomon Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81093,90,"SLB","Solomon Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81094,90,"SLB","Solomon Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81095,90,"SLB","Solomon Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81096,90,"SLB","Solomon Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81097,90,"SLB","Solomon Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLB/slb_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81098,92,"VGB","British Virgin Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81099,92,"VGB","British Virgin Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81100,92,"VGB","British Virgin Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81101,92,"VGB","British Virgin Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81102,92,"VGB","British Virgin Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81103,92,"VGB","British Virgin Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81104,92,"VGB","British Virgin Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81105,92,"VGB","British Virgin Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81106,92,"VGB","British Virgin Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81107,92,"VGB","British Virgin Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81108,92,"VGB","British Virgin Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81109,92,"VGB","British Virgin Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81110,92,"VGB","British Virgin Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81111,92,"VGB","British Virgin Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81112,92,"VGB","British Virgin Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81113,92,"VGB","British Virgin Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81114,92,"VGB","British Virgin Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81115,92,"VGB","British Virgin Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81116,92,"VGB","British Virgin Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81117,92,"VGB","British Virgin Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81118,92,"VGB","British Virgin Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81119,92,"VGB","British Virgin Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81120,92,"VGB","British Virgin Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81121,92,"VGB","British Virgin Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81122,92,"VGB","British Virgin Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81123,92,"VGB","British Virgin Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81124,92,"VGB","British Virgin Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81125,92,"VGB","British Virgin Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81126,92,"VGB","British Virgin Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81127,92,"VGB","British Virgin Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81128,92,"VGB","British Virgin Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81129,92,"VGB","British Virgin Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81130,92,"VGB","British Virgin Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81131,92,"VGB","British Virgin Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81132,92,"VGB","British Virgin Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81133,92,"VGB","British Virgin Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VGB/vgb_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81134,96,"BRN","Brunei","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81135,96,"BRN","Brunei","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81136,96,"BRN","Brunei","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81137,96,"BRN","Brunei","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81138,96,"BRN","Brunei","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81139,96,"BRN","Brunei","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81140,96,"BRN","Brunei","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81141,96,"BRN","Brunei","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81142,96,"BRN","Brunei","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81143,96,"BRN","Brunei","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81144,96,"BRN","Brunei","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81145,96,"BRN","Brunei","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81146,96,"BRN","Brunei","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81147,96,"BRN","Brunei","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81148,96,"BRN","Brunei","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81149,96,"BRN","Brunei","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81150,96,"BRN","Brunei","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81151,96,"BRN","Brunei","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81152,96,"BRN","Brunei","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81153,96,"BRN","Brunei","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81154,96,"BRN","Brunei","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81155,96,"BRN","Brunei","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81156,96,"BRN","Brunei","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81157,96,"BRN","Brunei","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81158,96,"BRN","Brunei","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81159,96,"BRN","Brunei","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81160,96,"BRN","Brunei","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81161,96,"BRN","Brunei","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81162,96,"BRN","Brunei","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81163,96,"BRN","Brunei","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81164,96,"BRN","Brunei","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81165,96,"BRN","Brunei","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81166,96,"BRN","Brunei","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81167,96,"BRN","Brunei","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81168,96,"BRN","Brunei","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81169,96,"BRN","Brunei","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BRN/brn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81170,100,"BGR","Bulgaria","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81171,100,"BGR","Bulgaria","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81172,100,"BGR","Bulgaria","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81173,100,"BGR","Bulgaria","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81174,100,"BGR","Bulgaria","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81175,100,"BGR","Bulgaria","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81176,100,"BGR","Bulgaria","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81177,100,"BGR","Bulgaria","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81178,100,"BGR","Bulgaria","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81179,100,"BGR","Bulgaria","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81180,100,"BGR","Bulgaria","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81181,100,"BGR","Bulgaria","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81182,100,"BGR","Bulgaria","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81183,100,"BGR","Bulgaria","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81184,100,"BGR","Bulgaria","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81185,100,"BGR","Bulgaria","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81186,100,"BGR","Bulgaria","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81187,100,"BGR","Bulgaria","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81188,100,"BGR","Bulgaria","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81189,100,"BGR","Bulgaria","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81190,100,"BGR","Bulgaria","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81191,100,"BGR","Bulgaria","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81192,100,"BGR","Bulgaria","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81193,100,"BGR","Bulgaria","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81194,100,"BGR","Bulgaria","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81195,100,"BGR","Bulgaria","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81196,100,"BGR","Bulgaria","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81197,100,"BGR","Bulgaria","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81198,100,"BGR","Bulgaria","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81199,100,"BGR","Bulgaria","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81200,100,"BGR","Bulgaria","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81201,100,"BGR","Bulgaria","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81202,100,"BGR","Bulgaria","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81203,100,"BGR","Bulgaria","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81204,100,"BGR","Bulgaria","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81205,100,"BGR","Bulgaria","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BGR/bgr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81206,104,"MMR","Myanmar","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81207,104,"MMR","Myanmar","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81208,104,"MMR","Myanmar","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81209,104,"MMR","Myanmar","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81210,104,"MMR","Myanmar","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81211,104,"MMR","Myanmar","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81212,104,"MMR","Myanmar","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81213,104,"MMR","Myanmar","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81214,104,"MMR","Myanmar","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81215,104,"MMR","Myanmar","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81216,104,"MMR","Myanmar","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81217,104,"MMR","Myanmar","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81218,104,"MMR","Myanmar","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81219,104,"MMR","Myanmar","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81220,104,"MMR","Myanmar","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81221,104,"MMR","Myanmar","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81222,104,"MMR","Myanmar","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81223,104,"MMR","Myanmar","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81224,104,"MMR","Myanmar","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81225,104,"MMR","Myanmar","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81226,104,"MMR","Myanmar","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81227,104,"MMR","Myanmar","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81228,104,"MMR","Myanmar","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81229,104,"MMR","Myanmar","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81230,104,"MMR","Myanmar","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81231,104,"MMR","Myanmar","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81232,104,"MMR","Myanmar","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81233,104,"MMR","Myanmar","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81234,104,"MMR","Myanmar","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81235,104,"MMR","Myanmar","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81236,104,"MMR","Myanmar","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81237,104,"MMR","Myanmar","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81238,104,"MMR","Myanmar","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81239,104,"MMR","Myanmar","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81240,104,"MMR","Myanmar","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81241,104,"MMR","Myanmar","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MMR/mmr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81242,108,"BDI","Burundi","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81243,108,"BDI","Burundi","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81244,108,"BDI","Burundi","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81245,108,"BDI","Burundi","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81246,108,"BDI","Burundi","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81247,108,"BDI","Burundi","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81248,108,"BDI","Burundi","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81249,108,"BDI","Burundi","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81250,108,"BDI","Burundi","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81251,108,"BDI","Burundi","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81252,108,"BDI","Burundi","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81253,108,"BDI","Burundi","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81254,108,"BDI","Burundi","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81255,108,"BDI","Burundi","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81256,108,"BDI","Burundi","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81257,108,"BDI","Burundi","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81258,108,"BDI","Burundi","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81259,108,"BDI","Burundi","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81260,108,"BDI","Burundi","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81261,108,"BDI","Burundi","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81262,108,"BDI","Burundi","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81263,108,"BDI","Burundi","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81264,108,"BDI","Burundi","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81265,108,"BDI","Burundi","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81266,108,"BDI","Burundi","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81267,108,"BDI","Burundi","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81268,108,"BDI","Burundi","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81269,108,"BDI","Burundi","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81270,108,"BDI","Burundi","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81271,108,"BDI","Burundi","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81272,108,"BDI","Burundi","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81273,108,"BDI","Burundi","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81274,108,"BDI","Burundi","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81275,108,"BDI","Burundi","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81276,108,"BDI","Burundi","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81277,108,"BDI","Burundi","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BDI/bdi_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81278,112,"BLR","Belarus","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81279,112,"BLR","Belarus","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81280,112,"BLR","Belarus","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81281,112,"BLR","Belarus","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81282,112,"BLR","Belarus","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81283,112,"BLR","Belarus","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81284,112,"BLR","Belarus","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81285,112,"BLR","Belarus","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81286,112,"BLR","Belarus","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81287,112,"BLR","Belarus","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81288,112,"BLR","Belarus","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81289,112,"BLR","Belarus","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81290,112,"BLR","Belarus","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81291,112,"BLR","Belarus","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81292,112,"BLR","Belarus","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81293,112,"BLR","Belarus","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81294,112,"BLR","Belarus","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81295,112,"BLR","Belarus","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81296,112,"BLR","Belarus","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81297,112,"BLR","Belarus","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81298,112,"BLR","Belarus","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81299,112,"BLR","Belarus","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81300,112,"BLR","Belarus","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81301,112,"BLR","Belarus","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81302,112,"BLR","Belarus","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81303,112,"BLR","Belarus","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81304,112,"BLR","Belarus","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81305,112,"BLR","Belarus","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81306,112,"BLR","Belarus","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81307,112,"BLR","Belarus","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81308,112,"BLR","Belarus","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81309,112,"BLR","Belarus","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81310,112,"BLR","Belarus","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81311,112,"BLR","Belarus","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81312,112,"BLR","Belarus","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81313,112,"BLR","Belarus","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLR/blr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81314,116,"KHM","Cambodia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81315,116,"KHM","Cambodia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81316,116,"KHM","Cambodia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81317,116,"KHM","Cambodia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81318,116,"KHM","Cambodia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81319,116,"KHM","Cambodia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81320,116,"KHM","Cambodia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81321,116,"KHM","Cambodia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81322,116,"KHM","Cambodia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81323,116,"KHM","Cambodia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81324,116,"KHM","Cambodia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81325,116,"KHM","Cambodia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81326,116,"KHM","Cambodia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81327,116,"KHM","Cambodia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81328,116,"KHM","Cambodia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81329,116,"KHM","Cambodia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81330,116,"KHM","Cambodia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81331,116,"KHM","Cambodia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81332,116,"KHM","Cambodia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81333,116,"KHM","Cambodia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81334,116,"KHM","Cambodia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81335,116,"KHM","Cambodia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81336,116,"KHM","Cambodia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81337,116,"KHM","Cambodia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81338,116,"KHM","Cambodia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81339,116,"KHM","Cambodia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81340,116,"KHM","Cambodia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81341,116,"KHM","Cambodia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81342,116,"KHM","Cambodia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81343,116,"KHM","Cambodia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81344,116,"KHM","Cambodia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81345,116,"KHM","Cambodia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81346,116,"KHM","Cambodia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81347,116,"KHM","Cambodia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81348,116,"KHM","Cambodia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81349,116,"KHM","Cambodia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KHM/khm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81350,120,"CMR","Cameroon","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81351,120,"CMR","Cameroon","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81352,120,"CMR","Cameroon","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81353,120,"CMR","Cameroon","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81354,120,"CMR","Cameroon","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81355,120,"CMR","Cameroon","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81356,120,"CMR","Cameroon","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81357,120,"CMR","Cameroon","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81358,120,"CMR","Cameroon","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81359,120,"CMR","Cameroon","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81360,120,"CMR","Cameroon","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81361,120,"CMR","Cameroon","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81362,120,"CMR","Cameroon","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81363,120,"CMR","Cameroon","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81364,120,"CMR","Cameroon","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81365,120,"CMR","Cameroon","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81366,120,"CMR","Cameroon","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81367,120,"CMR","Cameroon","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81368,120,"CMR","Cameroon","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81369,120,"CMR","Cameroon","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81370,120,"CMR","Cameroon","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81371,120,"CMR","Cameroon","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81372,120,"CMR","Cameroon","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81373,120,"CMR","Cameroon","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81374,120,"CMR","Cameroon","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81375,120,"CMR","Cameroon","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81376,120,"CMR","Cameroon","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81377,120,"CMR","Cameroon","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81378,120,"CMR","Cameroon","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81379,120,"CMR","Cameroon","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81380,120,"CMR","Cameroon","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81381,120,"CMR","Cameroon","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81382,120,"CMR","Cameroon","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81383,120,"CMR","Cameroon","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81384,120,"CMR","Cameroon","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81385,120,"CMR","Cameroon","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CMR/cmr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81386,132,"CPV","Cape Verde","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81387,132,"CPV","Cape Verde","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81388,132,"CPV","Cape Verde","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81389,132,"CPV","Cape Verde","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81390,132,"CPV","Cape Verde","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81391,132,"CPV","Cape Verde","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81392,132,"CPV","Cape Verde","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81393,132,"CPV","Cape Verde","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81394,132,"CPV","Cape Verde","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81395,132,"CPV","Cape Verde","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81396,132,"CPV","Cape Verde","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81397,132,"CPV","Cape Verde","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81398,132,"CPV","Cape Verde","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81399,132,"CPV","Cape Verde","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81400,132,"CPV","Cape Verde","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81401,132,"CPV","Cape Verde","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81402,132,"CPV","Cape Verde","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81403,132,"CPV","Cape Verde","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81404,132,"CPV","Cape Verde","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81405,132,"CPV","Cape Verde","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81406,132,"CPV","Cape Verde","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81407,132,"CPV","Cape Verde","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81408,132,"CPV","Cape Verde","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81409,132,"CPV","Cape Verde","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81410,132,"CPV","Cape Verde","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81411,132,"CPV","Cape Verde","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81412,132,"CPV","Cape Verde","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81413,132,"CPV","Cape Verde","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81414,132,"CPV","Cape Verde","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81415,132,"CPV","Cape Verde","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81416,132,"CPV","Cape Verde","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81417,132,"CPV","Cape Verde","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81418,132,"CPV","Cape Verde","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81419,132,"CPV","Cape Verde","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81420,132,"CPV","Cape Verde","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81421,132,"CPV","Cape Verde","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CPV/cpv_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81422,136,"CYM","Cayman Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81423,136,"CYM","Cayman Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81424,136,"CYM","Cayman Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81425,136,"CYM","Cayman Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81426,136,"CYM","Cayman Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81427,136,"CYM","Cayman Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81428,136,"CYM","Cayman Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81429,136,"CYM","Cayman Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81430,136,"CYM","Cayman Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81431,136,"CYM","Cayman Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81432,136,"CYM","Cayman Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81433,136,"CYM","Cayman Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81434,136,"CYM","Cayman Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81435,136,"CYM","Cayman Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81436,136,"CYM","Cayman Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81437,136,"CYM","Cayman Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81438,136,"CYM","Cayman Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81439,136,"CYM","Cayman Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81440,136,"CYM","Cayman Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81441,136,"CYM","Cayman Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81442,136,"CYM","Cayman Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81443,136,"CYM","Cayman Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81444,136,"CYM","Cayman Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81445,136,"CYM","Cayman Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81446,136,"CYM","Cayman Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81447,136,"CYM","Cayman Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81448,136,"CYM","Cayman Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81449,136,"CYM","Cayman Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81450,136,"CYM","Cayman Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81451,136,"CYM","Cayman Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81452,136,"CYM","Cayman Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81453,136,"CYM","Cayman Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81454,136,"CYM","Cayman Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81455,136,"CYM","Cayman Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81456,136,"CYM","Cayman Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81457,136,"CYM","Cayman Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYM/cym_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81458,140,"CAF","Central African Republic","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81459,140,"CAF","Central African Republic","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81460,140,"CAF","Central African Republic","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81461,140,"CAF","Central African Republic","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81462,140,"CAF","Central African Republic","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81463,140,"CAF","Central African Republic","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81464,140,"CAF","Central African Republic","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81465,140,"CAF","Central African Republic","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81466,140,"CAF","Central African Republic","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81467,140,"CAF","Central African Republic","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81468,140,"CAF","Central African Republic","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81469,140,"CAF","Central African Republic","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81470,140,"CAF","Central African Republic","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81471,140,"CAF","Central African Republic","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81472,140,"CAF","Central African Republic","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81473,140,"CAF","Central African Republic","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81474,140,"CAF","Central African Republic","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81475,140,"CAF","Central African Republic","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81476,140,"CAF","Central African Republic","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81477,140,"CAF","Central African Republic","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81478,140,"CAF","Central African Republic","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81479,140,"CAF","Central African Republic","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81480,140,"CAF","Central African Republic","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81481,140,"CAF","Central African Republic","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81482,140,"CAF","Central African Republic","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81483,140,"CAF","Central African Republic","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81484,140,"CAF","Central African Republic","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81485,140,"CAF","Central African Republic","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81486,140,"CAF","Central African Republic","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81487,140,"CAF","Central African Republic","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81488,140,"CAF","Central African Republic","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81489,140,"CAF","Central African Republic","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81490,140,"CAF","Central African Republic","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81491,140,"CAF","Central African Republic","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81492,140,"CAF","Central African Republic","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81493,140,"CAF","Central African Republic","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CAF/caf_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81494,144,"LKA","Sri Lanka","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81495,144,"LKA","Sri Lanka","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81496,144,"LKA","Sri Lanka","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81497,144,"LKA","Sri Lanka","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81498,144,"LKA","Sri Lanka","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81499,144,"LKA","Sri Lanka","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81500,144,"LKA","Sri Lanka","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81501,144,"LKA","Sri Lanka","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81502,144,"LKA","Sri Lanka","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81503,144,"LKA","Sri Lanka","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81504,144,"LKA","Sri Lanka","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81505,144,"LKA","Sri Lanka","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81506,144,"LKA","Sri Lanka","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81507,144,"LKA","Sri Lanka","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81508,144,"LKA","Sri Lanka","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81509,144,"LKA","Sri Lanka","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81510,144,"LKA","Sri Lanka","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81511,144,"LKA","Sri Lanka","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81512,144,"LKA","Sri Lanka","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81513,144,"LKA","Sri Lanka","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81514,144,"LKA","Sri Lanka","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81515,144,"LKA","Sri Lanka","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81516,144,"LKA","Sri Lanka","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81517,144,"LKA","Sri Lanka","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81518,144,"LKA","Sri Lanka","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81519,144,"LKA","Sri Lanka","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81520,144,"LKA","Sri Lanka","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81521,144,"LKA","Sri Lanka","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81522,144,"LKA","Sri Lanka","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81523,144,"LKA","Sri Lanka","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81524,144,"LKA","Sri Lanka","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81525,144,"LKA","Sri Lanka","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81526,144,"LKA","Sri Lanka","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81527,144,"LKA","Sri Lanka","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81528,144,"LKA","Sri Lanka","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81529,144,"LKA","Sri Lanka","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LKA/lka_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81530,148,"TCD","Chad","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81531,148,"TCD","Chad","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81532,148,"TCD","Chad","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81533,148,"TCD","Chad","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81534,148,"TCD","Chad","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81535,148,"TCD","Chad","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81536,148,"TCD","Chad","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81537,148,"TCD","Chad","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81538,148,"TCD","Chad","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81539,148,"TCD","Chad","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81540,148,"TCD","Chad","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81541,148,"TCD","Chad","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81542,148,"TCD","Chad","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81543,148,"TCD","Chad","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81544,148,"TCD","Chad","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81545,148,"TCD","Chad","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81546,148,"TCD","Chad","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81547,148,"TCD","Chad","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81548,148,"TCD","Chad","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81549,148,"TCD","Chad","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81550,148,"TCD","Chad","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81551,148,"TCD","Chad","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81552,148,"TCD","Chad","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81553,148,"TCD","Chad","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81554,148,"TCD","Chad","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81555,148,"TCD","Chad","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81556,148,"TCD","Chad","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81557,148,"TCD","Chad","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81558,148,"TCD","Chad","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81559,148,"TCD","Chad","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81560,148,"TCD","Chad","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81561,148,"TCD","Chad","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81562,148,"TCD","Chad","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81563,148,"TCD","Chad","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81564,148,"TCD","Chad","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81565,148,"TCD","Chad","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCD/tcd_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81566,158,"TWN","Taiwan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81567,158,"TWN","Taiwan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81568,158,"TWN","Taiwan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81569,158,"TWN","Taiwan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81570,158,"TWN","Taiwan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81571,158,"TWN","Taiwan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81572,158,"TWN","Taiwan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81573,158,"TWN","Taiwan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81574,158,"TWN","Taiwan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81575,158,"TWN","Taiwan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81576,158,"TWN","Taiwan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81577,158,"TWN","Taiwan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81578,158,"TWN","Taiwan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81579,158,"TWN","Taiwan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81580,158,"TWN","Taiwan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81581,158,"TWN","Taiwan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81582,158,"TWN","Taiwan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81583,158,"TWN","Taiwan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81584,158,"TWN","Taiwan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81585,158,"TWN","Taiwan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81586,158,"TWN","Taiwan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81587,158,"TWN","Taiwan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81588,158,"TWN","Taiwan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81589,158,"TWN","Taiwan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81590,158,"TWN","Taiwan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81591,158,"TWN","Taiwan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81592,158,"TWN","Taiwan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81593,158,"TWN","Taiwan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81594,158,"TWN","Taiwan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81595,158,"TWN","Taiwan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81596,158,"TWN","Taiwan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81597,158,"TWN","Taiwan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81598,158,"TWN","Taiwan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81599,158,"TWN","Taiwan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81600,158,"TWN","Taiwan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81601,158,"TWN","Taiwan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TWN/twn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81602,170,"COL","Colombia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81603,170,"COL","Colombia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81604,170,"COL","Colombia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81605,170,"COL","Colombia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81606,170,"COL","Colombia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81607,170,"COL","Colombia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81608,170,"COL","Colombia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81609,170,"COL","Colombia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81610,170,"COL","Colombia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81611,170,"COL","Colombia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81612,170,"COL","Colombia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81613,170,"COL","Colombia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81614,170,"COL","Colombia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81615,170,"COL","Colombia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81616,170,"COL","Colombia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81617,170,"COL","Colombia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81618,170,"COL","Colombia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81619,170,"COL","Colombia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81620,170,"COL","Colombia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81621,170,"COL","Colombia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81622,170,"COL","Colombia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81623,170,"COL","Colombia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81624,170,"COL","Colombia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81625,170,"COL","Colombia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81626,170,"COL","Colombia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81627,170,"COL","Colombia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81628,170,"COL","Colombia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81629,170,"COL","Colombia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81630,170,"COL","Colombia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81631,170,"COL","Colombia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81632,170,"COL","Colombia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81633,170,"COL","Colombia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81634,170,"COL","Colombia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81635,170,"COL","Colombia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81636,170,"COL","Colombia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81637,170,"COL","Colombia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COL/col_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81638,174,"COM","Comoros","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81639,174,"COM","Comoros","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81640,174,"COM","Comoros","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81641,174,"COM","Comoros","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81642,174,"COM","Comoros","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81643,174,"COM","Comoros","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81644,174,"COM","Comoros","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81645,174,"COM","Comoros","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81646,174,"COM","Comoros","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81647,174,"COM","Comoros","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81648,174,"COM","Comoros","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81649,174,"COM","Comoros","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81650,174,"COM","Comoros","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81651,174,"COM","Comoros","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81652,174,"COM","Comoros","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81653,174,"COM","Comoros","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81654,174,"COM","Comoros","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81655,174,"COM","Comoros","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81656,174,"COM","Comoros","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81657,174,"COM","Comoros","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81658,174,"COM","Comoros","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81659,174,"COM","Comoros","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81660,174,"COM","Comoros","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81661,174,"COM","Comoros","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81662,174,"COM","Comoros","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81663,174,"COM","Comoros","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81664,174,"COM","Comoros","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81665,174,"COM","Comoros","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81666,174,"COM","Comoros","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81667,174,"COM","Comoros","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81668,174,"COM","Comoros","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81669,174,"COM","Comoros","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81670,174,"COM","Comoros","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81671,174,"COM","Comoros","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81672,174,"COM","Comoros","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81673,174,"COM","Comoros","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COM/com_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81674,175,"MYT","Mayotte","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81675,175,"MYT","Mayotte","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81676,175,"MYT","Mayotte","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81677,175,"MYT","Mayotte","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81678,175,"MYT","Mayotte","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81679,175,"MYT","Mayotte","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81680,175,"MYT","Mayotte","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81681,175,"MYT","Mayotte","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81682,175,"MYT","Mayotte","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81683,175,"MYT","Mayotte","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81684,175,"MYT","Mayotte","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81685,175,"MYT","Mayotte","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81686,175,"MYT","Mayotte","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81687,175,"MYT","Mayotte","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81688,175,"MYT","Mayotte","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81689,175,"MYT","Mayotte","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81690,175,"MYT","Mayotte","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81691,175,"MYT","Mayotte","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81692,175,"MYT","Mayotte","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81693,175,"MYT","Mayotte","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81694,175,"MYT","Mayotte","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81695,175,"MYT","Mayotte","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81696,175,"MYT","Mayotte","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81697,175,"MYT","Mayotte","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81698,175,"MYT","Mayotte","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81699,175,"MYT","Mayotte","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81700,175,"MYT","Mayotte","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81701,175,"MYT","Mayotte","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81702,175,"MYT","Mayotte","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81703,175,"MYT","Mayotte","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81704,175,"MYT","Mayotte","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81705,175,"MYT","Mayotte","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81706,175,"MYT","Mayotte","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81707,175,"MYT","Mayotte","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81708,175,"MYT","Mayotte","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81709,175,"MYT","Mayotte","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYT/myt_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81710,178,"COG","Republic of Congo","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81711,178,"COG","Republic of Congo","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81712,178,"COG","Republic of Congo","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81713,178,"COG","Republic of Congo","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81714,178,"COG","Republic of Congo","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81715,178,"COG","Republic of Congo","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81716,178,"COG","Republic of Congo","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81717,178,"COG","Republic of Congo","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81718,178,"COG","Republic of Congo","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81719,178,"COG","Republic of Congo","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81720,178,"COG","Republic of Congo","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81721,178,"COG","Republic of Congo","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81722,178,"COG","Republic of Congo","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81723,178,"COG","Republic of Congo","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81724,178,"COG","Republic of Congo","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81725,178,"COG","Republic of Congo","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81726,178,"COG","Republic of Congo","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81727,178,"COG","Republic of Congo","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81728,178,"COG","Republic of Congo","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81729,178,"COG","Republic of Congo","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81730,178,"COG","Republic of Congo","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81731,178,"COG","Republic of Congo","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81732,178,"COG","Republic of Congo","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81733,178,"COG","Republic of Congo","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81734,178,"COG","Republic of Congo","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81735,178,"COG","Republic of Congo","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81736,178,"COG","Republic of Congo","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81737,178,"COG","Republic of Congo","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81738,178,"COG","Republic of Congo","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81739,178,"COG","Republic of Congo","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81740,178,"COG","Republic of Congo","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81741,178,"COG","Republic of Congo","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81742,178,"COG","Republic of Congo","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81743,178,"COG","Republic of Congo","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81744,178,"COG","Republic of Congo","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81745,178,"COG","Republic of Congo","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COG/cog_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81746,180,"COD","Democratic Republic of the Congo","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81747,180,"COD","Democratic Republic of the Congo","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81748,180,"COD","Democratic Republic of the Congo","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81749,180,"COD","Democratic Republic of the Congo","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81750,180,"COD","Democratic Republic of the Congo","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81751,180,"COD","Democratic Republic of the Congo","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81752,180,"COD","Democratic Republic of the Congo","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81753,180,"COD","Democratic Republic of the Congo","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81754,180,"COD","Democratic Republic of the Congo","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81755,180,"COD","Democratic Republic of the Congo","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81756,180,"COD","Democratic Republic of the Congo","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81757,180,"COD","Democratic Republic of the Congo","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81758,180,"COD","Democratic Republic of the Congo","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81759,180,"COD","Democratic Republic of the Congo","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81760,180,"COD","Democratic Republic of the Congo","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81761,180,"COD","Democratic Republic of the Congo","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81762,180,"COD","Democratic Republic of the Congo","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81763,180,"COD","Democratic Republic of the Congo","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81764,180,"COD","Democratic Republic of the Congo","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81765,180,"COD","Democratic Republic of the Congo","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81766,180,"COD","Democratic Republic of the Congo","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81767,180,"COD","Democratic Republic of the Congo","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81768,180,"COD","Democratic Republic of the Congo","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81769,180,"COD","Democratic Republic of the Congo","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81770,180,"COD","Democratic Republic of the Congo","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81771,180,"COD","Democratic Republic of the Congo","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81772,180,"COD","Democratic Republic of the Congo","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81773,180,"COD","Democratic Republic of the Congo","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81774,180,"COD","Democratic Republic of the Congo","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81775,180,"COD","Democratic Republic of the Congo","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81776,180,"COD","Democratic Republic of the Congo","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81777,180,"COD","Democratic Republic of the Congo","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81778,180,"COD","Democratic Republic of the Congo","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81779,180,"COD","Democratic Republic of the Congo","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81780,180,"COD","Democratic Republic of the Congo","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81781,180,"COD","Democratic Republic of the Congo","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COD/cod_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81782,184,"COK","Cook Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81783,184,"COK","Cook Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81784,184,"COK","Cook Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81785,184,"COK","Cook Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81786,184,"COK","Cook Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81787,184,"COK","Cook Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81788,184,"COK","Cook Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81789,184,"COK","Cook Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81790,184,"COK","Cook Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81791,184,"COK","Cook Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81792,184,"COK","Cook Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81793,184,"COK","Cook Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81794,184,"COK","Cook Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81795,184,"COK","Cook Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81796,184,"COK","Cook Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81797,184,"COK","Cook Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81798,184,"COK","Cook Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81799,184,"COK","Cook Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81800,184,"COK","Cook Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81801,184,"COK","Cook Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81802,184,"COK","Cook Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81803,184,"COK","Cook Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81804,184,"COK","Cook Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81805,184,"COK","Cook Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81806,184,"COK","Cook Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81807,184,"COK","Cook Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81808,184,"COK","Cook Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81809,184,"COK","Cook Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81810,184,"COK","Cook Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81811,184,"COK","Cook Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81812,184,"COK","Cook Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81813,184,"COK","Cook Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81814,184,"COK","Cook Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81815,184,"COK","Cook Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81816,184,"COK","Cook Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81817,184,"COK","Cook Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/COK/cok_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81818,188,"CRI","Costa Rica","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81819,188,"CRI","Costa Rica","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81820,188,"CRI","Costa Rica","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81821,188,"CRI","Costa Rica","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81822,188,"CRI","Costa Rica","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81823,188,"CRI","Costa Rica","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81824,188,"CRI","Costa Rica","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81825,188,"CRI","Costa Rica","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81826,188,"CRI","Costa Rica","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81827,188,"CRI","Costa Rica","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81828,188,"CRI","Costa Rica","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81829,188,"CRI","Costa Rica","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81830,188,"CRI","Costa Rica","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81831,188,"CRI","Costa Rica","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81832,188,"CRI","Costa Rica","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81833,188,"CRI","Costa Rica","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81834,188,"CRI","Costa Rica","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81835,188,"CRI","Costa Rica","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81836,188,"CRI","Costa Rica","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81837,188,"CRI","Costa Rica","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81838,188,"CRI","Costa Rica","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81839,188,"CRI","Costa Rica","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81840,188,"CRI","Costa Rica","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81841,188,"CRI","Costa Rica","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81842,188,"CRI","Costa Rica","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81843,188,"CRI","Costa Rica","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81844,188,"CRI","Costa Rica","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81845,188,"CRI","Costa Rica","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81846,188,"CRI","Costa Rica","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81847,188,"CRI","Costa Rica","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81848,188,"CRI","Costa Rica","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81849,188,"CRI","Costa Rica","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81850,188,"CRI","Costa Rica","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81851,188,"CRI","Costa Rica","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81852,188,"CRI","Costa Rica","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81853,188,"CRI","Costa Rica","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CRI/cri_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81854,191,"HRV","Croatia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81855,191,"HRV","Croatia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81856,191,"HRV","Croatia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81857,191,"HRV","Croatia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81858,191,"HRV","Croatia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81859,191,"HRV","Croatia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81860,191,"HRV","Croatia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81861,191,"HRV","Croatia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81862,191,"HRV","Croatia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81863,191,"HRV","Croatia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81864,191,"HRV","Croatia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81865,191,"HRV","Croatia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81866,191,"HRV","Croatia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81867,191,"HRV","Croatia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81868,191,"HRV","Croatia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81869,191,"HRV","Croatia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81870,191,"HRV","Croatia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81871,191,"HRV","Croatia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81872,191,"HRV","Croatia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81873,191,"HRV","Croatia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81874,191,"HRV","Croatia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81875,191,"HRV","Croatia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81876,191,"HRV","Croatia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81877,191,"HRV","Croatia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81878,191,"HRV","Croatia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81879,191,"HRV","Croatia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81880,191,"HRV","Croatia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81881,191,"HRV","Croatia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81882,191,"HRV","Croatia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81883,191,"HRV","Croatia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81884,191,"HRV","Croatia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81885,191,"HRV","Croatia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81886,191,"HRV","Croatia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81887,191,"HRV","Croatia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81888,191,"HRV","Croatia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81889,191,"HRV","Croatia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HRV/hrv_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81890,192,"CUB","Cuba","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81891,192,"CUB","Cuba","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81892,192,"CUB","Cuba","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81893,192,"CUB","Cuba","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81894,192,"CUB","Cuba","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81895,192,"CUB","Cuba","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81896,192,"CUB","Cuba","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81897,192,"CUB","Cuba","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81898,192,"CUB","Cuba","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81899,192,"CUB","Cuba","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81900,192,"CUB","Cuba","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81901,192,"CUB","Cuba","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81902,192,"CUB","Cuba","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81903,192,"CUB","Cuba","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81904,192,"CUB","Cuba","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81905,192,"CUB","Cuba","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81906,192,"CUB","Cuba","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81907,192,"CUB","Cuba","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81908,192,"CUB","Cuba","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81909,192,"CUB","Cuba","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81910,192,"CUB","Cuba","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81911,192,"CUB","Cuba","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81912,192,"CUB","Cuba","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81913,192,"CUB","Cuba","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81914,192,"CUB","Cuba","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81915,192,"CUB","Cuba","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81916,192,"CUB","Cuba","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81917,192,"CUB","Cuba","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81918,192,"CUB","Cuba","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81919,192,"CUB","Cuba","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81920,192,"CUB","Cuba","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81921,192,"CUB","Cuba","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81922,192,"CUB","Cuba","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81923,192,"CUB","Cuba","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81924,192,"CUB","Cuba","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81925,192,"CUB","Cuba","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUB/cub_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81926,196,"CYP","Cyprus","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81927,196,"CYP","Cyprus","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81928,196,"CYP","Cyprus","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81929,196,"CYP","Cyprus","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81930,196,"CYP","Cyprus","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81931,196,"CYP","Cyprus","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81932,196,"CYP","Cyprus","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81933,196,"CYP","Cyprus","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81934,196,"CYP","Cyprus","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81935,196,"CYP","Cyprus","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81936,196,"CYP","Cyprus","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81937,196,"CYP","Cyprus","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81938,196,"CYP","Cyprus","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81939,196,"CYP","Cyprus","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81940,196,"CYP","Cyprus","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81941,196,"CYP","Cyprus","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81942,196,"CYP","Cyprus","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81943,196,"CYP","Cyprus","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81944,196,"CYP","Cyprus","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81945,196,"CYP","Cyprus","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81946,196,"CYP","Cyprus","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81947,196,"CYP","Cyprus","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81948,196,"CYP","Cyprus","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81949,196,"CYP","Cyprus","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81950,196,"CYP","Cyprus","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81951,196,"CYP","Cyprus","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81952,196,"CYP","Cyprus","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81953,196,"CYP","Cyprus","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81954,196,"CYP","Cyprus","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81955,196,"CYP","Cyprus","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81956,196,"CYP","Cyprus","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81957,196,"CYP","Cyprus","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81958,196,"CYP","Cyprus","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81959,196,"CYP","Cyprus","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81960,196,"CYP","Cyprus","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81961,196,"CYP","Cyprus","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CYP/cyp_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81962,203,"CZE","Czech Republic","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81963,203,"CZE","Czech Republic","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81964,203,"CZE","Czech Republic","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81965,203,"CZE","Czech Republic","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81966,203,"CZE","Czech Republic","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81967,203,"CZE","Czech Republic","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81968,203,"CZE","Czech Republic","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81969,203,"CZE","Czech Republic","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81970,203,"CZE","Czech Republic","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81971,203,"CZE","Czech Republic","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81972,203,"CZE","Czech Republic","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81973,203,"CZE","Czech Republic","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81974,203,"CZE","Czech Republic","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81975,203,"CZE","Czech Republic","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81976,203,"CZE","Czech Republic","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81977,203,"CZE","Czech Republic","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81978,203,"CZE","Czech Republic","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81979,203,"CZE","Czech Republic","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81980,203,"CZE","Czech Republic","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81981,203,"CZE","Czech Republic","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81982,203,"CZE","Czech Republic","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81983,203,"CZE","Czech Republic","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81984,203,"CZE","Czech Republic","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81985,203,"CZE","Czech Republic","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81986,203,"CZE","Czech Republic","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81987,203,"CZE","Czech Republic","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81988,203,"CZE","Czech Republic","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81989,203,"CZE","Czech Republic","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81990,203,"CZE","Czech Republic","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81991,203,"CZE","Czech Republic","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81992,203,"CZE","Czech Republic","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81993,203,"CZE","Czech Republic","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81994,203,"CZE","Czech Republic","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81995,203,"CZE","Czech Republic","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81996,203,"CZE","Czech Republic","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81997,203,"CZE","Czech Republic","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CZE/cze_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
81998,204,"BEN","Benin","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
81999,204,"BEN","Benin","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82000,204,"BEN","Benin","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82001,204,"BEN","Benin","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82002,204,"BEN","Benin","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82003,204,"BEN","Benin","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82004,204,"BEN","Benin","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82005,204,"BEN","Benin","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82006,204,"BEN","Benin","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82007,204,"BEN","Benin","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82008,204,"BEN","Benin","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82009,204,"BEN","Benin","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82010,204,"BEN","Benin","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82011,204,"BEN","Benin","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82012,204,"BEN","Benin","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82013,204,"BEN","Benin","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82014,204,"BEN","Benin","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82015,204,"BEN","Benin","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82016,204,"BEN","Benin","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82017,204,"BEN","Benin","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82018,204,"BEN","Benin","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82019,204,"BEN","Benin","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82020,204,"BEN","Benin","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82021,204,"BEN","Benin","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82022,204,"BEN","Benin","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82023,204,"BEN","Benin","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82024,204,"BEN","Benin","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82025,204,"BEN","Benin","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82026,204,"BEN","Benin","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82027,204,"BEN","Benin","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82028,204,"BEN","Benin","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82029,204,"BEN","Benin","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82030,204,"BEN","Benin","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82031,204,"BEN","Benin","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82032,204,"BEN","Benin","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82033,204,"BEN","Benin","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BEN/ben_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82034,208,"DNK","Denmark","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82035,208,"DNK","Denmark","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82036,208,"DNK","Denmark","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82037,208,"DNK","Denmark","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82038,208,"DNK","Denmark","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82039,208,"DNK","Denmark","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82040,208,"DNK","Denmark","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82041,208,"DNK","Denmark","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82042,208,"DNK","Denmark","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82043,208,"DNK","Denmark","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82044,208,"DNK","Denmark","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82045,208,"DNK","Denmark","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82046,208,"DNK","Denmark","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82047,208,"DNK","Denmark","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82048,208,"DNK","Denmark","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82049,208,"DNK","Denmark","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82050,208,"DNK","Denmark","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82051,208,"DNK","Denmark","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82052,208,"DNK","Denmark","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82053,208,"DNK","Denmark","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82054,208,"DNK","Denmark","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82055,208,"DNK","Denmark","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82056,208,"DNK","Denmark","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82057,208,"DNK","Denmark","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82058,208,"DNK","Denmark","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82059,208,"DNK","Denmark","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82060,208,"DNK","Denmark","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82061,208,"DNK","Denmark","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82062,208,"DNK","Denmark","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82063,208,"DNK","Denmark","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82064,208,"DNK","Denmark","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82065,208,"DNK","Denmark","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82066,208,"DNK","Denmark","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82067,208,"DNK","Denmark","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82068,208,"DNK","Denmark","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82069,208,"DNK","Denmark","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DNK/dnk_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82070,212,"DMA","Dominica","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82071,212,"DMA","Dominica","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82072,212,"DMA","Dominica","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82073,212,"DMA","Dominica","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82074,212,"DMA","Dominica","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82075,212,"DMA","Dominica","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82076,212,"DMA","Dominica","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82077,212,"DMA","Dominica","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82078,212,"DMA","Dominica","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82079,212,"DMA","Dominica","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82080,212,"DMA","Dominica","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82081,212,"DMA","Dominica","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82082,212,"DMA","Dominica","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82083,212,"DMA","Dominica","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82084,212,"DMA","Dominica","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82085,212,"DMA","Dominica","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82086,212,"DMA","Dominica","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82087,212,"DMA","Dominica","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82088,212,"DMA","Dominica","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82089,212,"DMA","Dominica","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82090,212,"DMA","Dominica","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82091,212,"DMA","Dominica","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82092,212,"DMA","Dominica","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82093,212,"DMA","Dominica","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82094,212,"DMA","Dominica","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82095,212,"DMA","Dominica","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82096,212,"DMA","Dominica","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82097,212,"DMA","Dominica","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82098,212,"DMA","Dominica","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82099,212,"DMA","Dominica","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82100,212,"DMA","Dominica","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82101,212,"DMA","Dominica","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82102,212,"DMA","Dominica","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82103,212,"DMA","Dominica","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82104,212,"DMA","Dominica","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82105,212,"DMA","Dominica","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DMA/dma_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82106,214,"DOM","Dominican Republic","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82107,214,"DOM","Dominican Republic","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82108,214,"DOM","Dominican Republic","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82109,214,"DOM","Dominican Republic","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82110,214,"DOM","Dominican Republic","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82111,214,"DOM","Dominican Republic","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82112,214,"DOM","Dominican Republic","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82113,214,"DOM","Dominican Republic","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82114,214,"DOM","Dominican Republic","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82115,214,"DOM","Dominican Republic","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82116,214,"DOM","Dominican Republic","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82117,214,"DOM","Dominican Republic","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82118,214,"DOM","Dominican Republic","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82119,214,"DOM","Dominican Republic","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82120,214,"DOM","Dominican Republic","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82121,214,"DOM","Dominican Republic","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82122,214,"DOM","Dominican Republic","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82123,214,"DOM","Dominican Republic","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82124,214,"DOM","Dominican Republic","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82125,214,"DOM","Dominican Republic","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82126,214,"DOM","Dominican Republic","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82127,214,"DOM","Dominican Republic","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82128,214,"DOM","Dominican Republic","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82129,214,"DOM","Dominican Republic","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82130,214,"DOM","Dominican Republic","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82131,214,"DOM","Dominican Republic","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82132,214,"DOM","Dominican Republic","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82133,214,"DOM","Dominican Republic","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82134,214,"DOM","Dominican Republic","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82135,214,"DOM","Dominican Republic","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82136,214,"DOM","Dominican Republic","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82137,214,"DOM","Dominican Republic","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82138,214,"DOM","Dominican Republic","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82139,214,"DOM","Dominican Republic","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82140,214,"DOM","Dominican Republic","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82141,214,"DOM","Dominican Republic","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DOM/dom_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82142,218,"ECU","Ecuador","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82143,218,"ECU","Ecuador","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82144,218,"ECU","Ecuador","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82145,218,"ECU","Ecuador","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82146,218,"ECU","Ecuador","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82147,218,"ECU","Ecuador","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82148,218,"ECU","Ecuador","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82149,218,"ECU","Ecuador","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82150,218,"ECU","Ecuador","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82151,218,"ECU","Ecuador","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82152,218,"ECU","Ecuador","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82153,218,"ECU","Ecuador","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82154,218,"ECU","Ecuador","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82155,218,"ECU","Ecuador","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82156,218,"ECU","Ecuador","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82157,218,"ECU","Ecuador","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82158,218,"ECU","Ecuador","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82159,218,"ECU","Ecuador","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82160,218,"ECU","Ecuador","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82161,218,"ECU","Ecuador","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82162,218,"ECU","Ecuador","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82163,218,"ECU","Ecuador","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82164,218,"ECU","Ecuador","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82165,218,"ECU","Ecuador","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82166,218,"ECU","Ecuador","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82167,218,"ECU","Ecuador","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82168,218,"ECU","Ecuador","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82169,218,"ECU","Ecuador","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82170,218,"ECU","Ecuador","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82171,218,"ECU","Ecuador","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82172,218,"ECU","Ecuador","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82173,218,"ECU","Ecuador","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82174,218,"ECU","Ecuador","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82175,218,"ECU","Ecuador","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82176,218,"ECU","Ecuador","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82177,218,"ECU","Ecuador","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ECU/ecu_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82178,222,"SLV","El Salvador","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82179,222,"SLV","El Salvador","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82180,222,"SLV","El Salvador","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82181,222,"SLV","El Salvador","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82182,222,"SLV","El Salvador","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82183,222,"SLV","El Salvador","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82184,222,"SLV","El Salvador","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82185,222,"SLV","El Salvador","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82186,222,"SLV","El Salvador","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82187,222,"SLV","El Salvador","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82188,222,"SLV","El Salvador","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82189,222,"SLV","El Salvador","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82190,222,"SLV","El Salvador","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82191,222,"SLV","El Salvador","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82192,222,"SLV","El Salvador","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82193,222,"SLV","El Salvador","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82194,222,"SLV","El Salvador","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82195,222,"SLV","El Salvador","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82196,222,"SLV","El Salvador","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82197,222,"SLV","El Salvador","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82198,222,"SLV","El Salvador","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82199,222,"SLV","El Salvador","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82200,222,"SLV","El Salvador","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82201,222,"SLV","El Salvador","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82202,222,"SLV","El Salvador","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82203,222,"SLV","El Salvador","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82204,222,"SLV","El Salvador","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82205,222,"SLV","El Salvador","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82206,222,"SLV","El Salvador","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82207,222,"SLV","El Salvador","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82208,222,"SLV","El Salvador","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82209,222,"SLV","El Salvador","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82210,222,"SLV","El Salvador","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82211,222,"SLV","El Salvador","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82212,222,"SLV","El Salvador","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82213,222,"SLV","El Salvador","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLV/slv_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82214,226,"GNQ","Equatorial Guinea","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82215,226,"GNQ","Equatorial Guinea","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82216,226,"GNQ","Equatorial Guinea","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82217,226,"GNQ","Equatorial Guinea","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82218,226,"GNQ","Equatorial Guinea","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82219,226,"GNQ","Equatorial Guinea","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82220,226,"GNQ","Equatorial Guinea","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82221,226,"GNQ","Equatorial Guinea","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82222,226,"GNQ","Equatorial Guinea","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82223,226,"GNQ","Equatorial Guinea","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82224,226,"GNQ","Equatorial Guinea","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82225,226,"GNQ","Equatorial Guinea","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82226,226,"GNQ","Equatorial Guinea","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82227,226,"GNQ","Equatorial Guinea","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82228,226,"GNQ","Equatorial Guinea","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82229,226,"GNQ","Equatorial Guinea","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82230,226,"GNQ","Equatorial Guinea","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82231,226,"GNQ","Equatorial Guinea","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82232,226,"GNQ","Equatorial Guinea","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82233,226,"GNQ","Equatorial Guinea","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82234,226,"GNQ","Equatorial Guinea","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82235,226,"GNQ","Equatorial Guinea","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82236,226,"GNQ","Equatorial Guinea","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82237,226,"GNQ","Equatorial Guinea","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82238,226,"GNQ","Equatorial Guinea","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82239,226,"GNQ","Equatorial Guinea","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82240,226,"GNQ","Equatorial Guinea","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82241,226,"GNQ","Equatorial Guinea","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82242,226,"GNQ","Equatorial Guinea","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82243,226,"GNQ","Equatorial Guinea","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82244,226,"GNQ","Equatorial Guinea","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82245,226,"GNQ","Equatorial Guinea","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82246,226,"GNQ","Equatorial Guinea","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82247,226,"GNQ","Equatorial Guinea","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82248,226,"GNQ","Equatorial Guinea","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82249,226,"GNQ","Equatorial Guinea","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNQ/gnq_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82250,231,"ETH","Ethiopia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82251,231,"ETH","Ethiopia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82252,231,"ETH","Ethiopia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82253,231,"ETH","Ethiopia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82254,231,"ETH","Ethiopia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82255,231,"ETH","Ethiopia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82256,231,"ETH","Ethiopia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82257,231,"ETH","Ethiopia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82258,231,"ETH","Ethiopia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82259,231,"ETH","Ethiopia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82260,231,"ETH","Ethiopia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82261,231,"ETH","Ethiopia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82262,231,"ETH","Ethiopia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82263,231,"ETH","Ethiopia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82264,231,"ETH","Ethiopia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82265,231,"ETH","Ethiopia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82266,231,"ETH","Ethiopia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82267,231,"ETH","Ethiopia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82268,231,"ETH","Ethiopia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82269,231,"ETH","Ethiopia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82270,231,"ETH","Ethiopia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82271,231,"ETH","Ethiopia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82272,231,"ETH","Ethiopia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82273,231,"ETH","Ethiopia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82274,231,"ETH","Ethiopia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82275,231,"ETH","Ethiopia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82276,231,"ETH","Ethiopia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82277,231,"ETH","Ethiopia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82278,231,"ETH","Ethiopia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82279,231,"ETH","Ethiopia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82280,231,"ETH","Ethiopia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82281,231,"ETH","Ethiopia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82282,231,"ETH","Ethiopia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82283,231,"ETH","Ethiopia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82284,231,"ETH","Ethiopia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82285,231,"ETH","Ethiopia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ETH/eth_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82286,232,"ERI","Eritrea","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82287,232,"ERI","Eritrea","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82288,232,"ERI","Eritrea","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82289,232,"ERI","Eritrea","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82290,232,"ERI","Eritrea","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82291,232,"ERI","Eritrea","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82292,232,"ERI","Eritrea","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82293,232,"ERI","Eritrea","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82294,232,"ERI","Eritrea","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82295,232,"ERI","Eritrea","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82296,232,"ERI","Eritrea","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82297,232,"ERI","Eritrea","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82298,232,"ERI","Eritrea","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82299,232,"ERI","Eritrea","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82300,232,"ERI","Eritrea","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82301,232,"ERI","Eritrea","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82302,232,"ERI","Eritrea","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82303,232,"ERI","Eritrea","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82304,232,"ERI","Eritrea","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82305,232,"ERI","Eritrea","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82306,232,"ERI","Eritrea","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82307,232,"ERI","Eritrea","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82308,232,"ERI","Eritrea","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82309,232,"ERI","Eritrea","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82310,232,"ERI","Eritrea","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82311,232,"ERI","Eritrea","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82312,232,"ERI","Eritrea","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82313,232,"ERI","Eritrea","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82314,232,"ERI","Eritrea","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82315,232,"ERI","Eritrea","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82316,232,"ERI","Eritrea","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82317,232,"ERI","Eritrea","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82318,232,"ERI","Eritrea","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82319,232,"ERI","Eritrea","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82320,232,"ERI","Eritrea","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82321,232,"ERI","Eritrea","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ERI/eri_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82322,233,"EST","Estonia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82323,233,"EST","Estonia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82324,233,"EST","Estonia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82325,233,"EST","Estonia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82326,233,"EST","Estonia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82327,233,"EST","Estonia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82328,233,"EST","Estonia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82329,233,"EST","Estonia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82330,233,"EST","Estonia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82331,233,"EST","Estonia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82332,233,"EST","Estonia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82333,233,"EST","Estonia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82334,233,"EST","Estonia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82335,233,"EST","Estonia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82336,233,"EST","Estonia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82337,233,"EST","Estonia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82338,233,"EST","Estonia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82339,233,"EST","Estonia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82340,233,"EST","Estonia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82341,233,"EST","Estonia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82342,233,"EST","Estonia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82343,233,"EST","Estonia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82344,233,"EST","Estonia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82345,233,"EST","Estonia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82346,233,"EST","Estonia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82347,233,"EST","Estonia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82348,233,"EST","Estonia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82349,233,"EST","Estonia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82350,233,"EST","Estonia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82351,233,"EST","Estonia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82352,233,"EST","Estonia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82353,233,"EST","Estonia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82354,233,"EST","Estonia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82355,233,"EST","Estonia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82356,233,"EST","Estonia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82357,233,"EST","Estonia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EST/est_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82358,234,"FRO","Faroe Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82359,234,"FRO","Faroe Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82360,234,"FRO","Faroe Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82361,234,"FRO","Faroe Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82362,234,"FRO","Faroe Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82363,234,"FRO","Faroe Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82364,234,"FRO","Faroe Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82365,234,"FRO","Faroe Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82366,234,"FRO","Faroe Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82367,234,"FRO","Faroe Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82368,234,"FRO","Faroe Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82369,234,"FRO","Faroe Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82370,234,"FRO","Faroe Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82371,234,"FRO","Faroe Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82372,234,"FRO","Faroe Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82373,234,"FRO","Faroe Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82374,234,"FRO","Faroe Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82375,234,"FRO","Faroe Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82376,234,"FRO","Faroe Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82377,234,"FRO","Faroe Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82378,234,"FRO","Faroe Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82379,234,"FRO","Faroe Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82380,234,"FRO","Faroe Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82381,234,"FRO","Faroe Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82382,234,"FRO","Faroe Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82383,234,"FRO","Faroe Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82384,234,"FRO","Faroe Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82385,234,"FRO","Faroe Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82386,234,"FRO","Faroe Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82387,234,"FRO","Faroe Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82388,234,"FRO","Faroe Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82389,234,"FRO","Faroe Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82390,234,"FRO","Faroe Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82391,234,"FRO","Faroe Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82392,234,"FRO","Faroe Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82393,234,"FRO","Faroe Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRO/fro_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82394,238,"FLK","Falkland Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82395,238,"FLK","Falkland Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82396,238,"FLK","Falkland Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82397,238,"FLK","Falkland Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82398,238,"FLK","Falkland Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82399,238,"FLK","Falkland Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82400,238,"FLK","Falkland Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82401,238,"FLK","Falkland Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82402,238,"FLK","Falkland Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82403,238,"FLK","Falkland Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82404,238,"FLK","Falkland Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82405,238,"FLK","Falkland Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82406,238,"FLK","Falkland Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82407,238,"FLK","Falkland Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82408,238,"FLK","Falkland Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82409,238,"FLK","Falkland Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82410,238,"FLK","Falkland Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82411,238,"FLK","Falkland Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82412,238,"FLK","Falkland Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82413,238,"FLK","Falkland Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82414,238,"FLK","Falkland Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82415,238,"FLK","Falkland Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82416,238,"FLK","Falkland Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82417,238,"FLK","Falkland Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82418,238,"FLK","Falkland Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82419,238,"FLK","Falkland Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82420,238,"FLK","Falkland Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82421,238,"FLK","Falkland Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82422,238,"FLK","Falkland Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82423,238,"FLK","Falkland Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82424,238,"FLK","Falkland Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82425,238,"FLK","Falkland Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82426,238,"FLK","Falkland Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82427,238,"FLK","Falkland Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82428,238,"FLK","Falkland Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82429,238,"FLK","Falkland Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FLK/flk_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82430,242,"FJI","Fiji","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82431,242,"FJI","Fiji","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82432,242,"FJI","Fiji","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82433,242,"FJI","Fiji","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82434,242,"FJI","Fiji","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82435,242,"FJI","Fiji","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82436,242,"FJI","Fiji","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82437,242,"FJI","Fiji","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82438,242,"FJI","Fiji","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82439,242,"FJI","Fiji","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82440,242,"FJI","Fiji","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82441,242,"FJI","Fiji","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82442,242,"FJI","Fiji","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82443,242,"FJI","Fiji","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82444,242,"FJI","Fiji","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82445,242,"FJI","Fiji","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82446,242,"FJI","Fiji","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82447,242,"FJI","Fiji","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82448,242,"FJI","Fiji","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82449,242,"FJI","Fiji","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82450,242,"FJI","Fiji","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82451,242,"FJI","Fiji","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82452,242,"FJI","Fiji","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82453,242,"FJI","Fiji","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82454,242,"FJI","Fiji","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82455,242,"FJI","Fiji","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82456,242,"FJI","Fiji","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82457,242,"FJI","Fiji","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82458,242,"FJI","Fiji","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82459,242,"FJI","Fiji","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82460,242,"FJI","Fiji","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82461,242,"FJI","Fiji","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82462,242,"FJI","Fiji","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82463,242,"FJI","Fiji","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82464,242,"FJI","Fiji","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82465,242,"FJI","Fiji","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FJI/fji_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82466,246,"FIN","Finland","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82467,246,"FIN","Finland","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82468,246,"FIN","Finland","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82469,246,"FIN","Finland","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82470,246,"FIN","Finland","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82471,246,"FIN","Finland","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82472,246,"FIN","Finland","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82473,246,"FIN","Finland","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82474,246,"FIN","Finland","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82475,246,"FIN","Finland","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82476,246,"FIN","Finland","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82477,246,"FIN","Finland","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82478,246,"FIN","Finland","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82479,246,"FIN","Finland","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82480,246,"FIN","Finland","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82481,246,"FIN","Finland","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82482,246,"FIN","Finland","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82483,246,"FIN","Finland","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82484,246,"FIN","Finland","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82485,246,"FIN","Finland","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82486,246,"FIN","Finland","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82487,246,"FIN","Finland","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82488,246,"FIN","Finland","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82489,246,"FIN","Finland","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82490,246,"FIN","Finland","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82491,246,"FIN","Finland","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82492,246,"FIN","Finland","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82493,246,"FIN","Finland","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82494,246,"FIN","Finland","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82495,246,"FIN","Finland","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82496,246,"FIN","Finland","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82497,246,"FIN","Finland","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82498,246,"FIN","Finland","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82499,246,"FIN","Finland","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82500,246,"FIN","Finland","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82501,246,"FIN","Finland","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FIN/fin_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82502,248,"ALA","Aland Islands ","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82503,248,"ALA","Aland Islands ","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82504,248,"ALA","Aland Islands ","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82505,248,"ALA","Aland Islands ","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82506,248,"ALA","Aland Islands ","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82507,248,"ALA","Aland Islands ","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82508,248,"ALA","Aland Islands ","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82509,248,"ALA","Aland Islands ","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82510,248,"ALA","Aland Islands ","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82511,248,"ALA","Aland Islands ","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82512,248,"ALA","Aland Islands ","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82513,248,"ALA","Aland Islands ","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82514,248,"ALA","Aland Islands ","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82515,248,"ALA","Aland Islands ","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82516,248,"ALA","Aland Islands ","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82517,248,"ALA","Aland Islands ","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82518,248,"ALA","Aland Islands ","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82519,248,"ALA","Aland Islands ","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82520,248,"ALA","Aland Islands ","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82521,248,"ALA","Aland Islands ","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82522,248,"ALA","Aland Islands ","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82523,248,"ALA","Aland Islands ","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82524,248,"ALA","Aland Islands ","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82525,248,"ALA","Aland Islands ","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82526,248,"ALA","Aland Islands ","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82527,248,"ALA","Aland Islands ","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82528,248,"ALA","Aland Islands ","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82529,248,"ALA","Aland Islands ","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82530,248,"ALA","Aland Islands ","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82531,248,"ALA","Aland Islands ","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82532,248,"ALA","Aland Islands ","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82533,248,"ALA","Aland Islands ","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82534,248,"ALA","Aland Islands ","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82535,248,"ALA","Aland Islands ","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82536,248,"ALA","Aland Islands ","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82537,248,"ALA","Aland Islands ","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ALA/ala_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82538,250,"FRA","France","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82539,250,"FRA","France","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82540,250,"FRA","France","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82541,250,"FRA","France","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82542,250,"FRA","France","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82543,250,"FRA","France","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82544,250,"FRA","France","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82545,250,"FRA","France","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82546,250,"FRA","France","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82547,250,"FRA","France","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82548,250,"FRA","France","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82549,250,"FRA","France","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82550,250,"FRA","France","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82551,250,"FRA","France","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82552,250,"FRA","France","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82553,250,"FRA","France","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82554,250,"FRA","France","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82555,250,"FRA","France","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82556,250,"FRA","France","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82557,250,"FRA","France","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82558,250,"FRA","France","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82559,250,"FRA","France","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82560,250,"FRA","France","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82561,250,"FRA","France","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82562,250,"FRA","France","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82563,250,"FRA","France","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82564,250,"FRA","France","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82565,250,"FRA","France","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82566,250,"FRA","France","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82567,250,"FRA","France","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82568,250,"FRA","France","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82569,250,"FRA","France","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82570,250,"FRA","France","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82571,250,"FRA","France","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82572,250,"FRA","France","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82573,250,"FRA","France","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FRA/fra_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82574,254,"GUF","French Guiana","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82575,254,"GUF","French Guiana","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82576,254,"GUF","French Guiana","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82577,254,"GUF","French Guiana","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82578,254,"GUF","French Guiana","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82579,254,"GUF","French Guiana","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82580,254,"GUF","French Guiana","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82581,254,"GUF","French Guiana","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82582,254,"GUF","French Guiana","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82583,254,"GUF","French Guiana","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82584,254,"GUF","French Guiana","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82585,254,"GUF","French Guiana","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82586,254,"GUF","French Guiana","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82587,254,"GUF","French Guiana","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82588,254,"GUF","French Guiana","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82589,254,"GUF","French Guiana","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82590,254,"GUF","French Guiana","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82591,254,"GUF","French Guiana","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82592,254,"GUF","French Guiana","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82593,254,"GUF","French Guiana","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82594,254,"GUF","French Guiana","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82595,254,"GUF","French Guiana","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82596,254,"GUF","French Guiana","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82597,254,"GUF","French Guiana","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82598,254,"GUF","French Guiana","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82599,254,"GUF","French Guiana","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82600,254,"GUF","French Guiana","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82601,254,"GUF","French Guiana","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82602,254,"GUF","French Guiana","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82603,254,"GUF","French Guiana","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82604,254,"GUF","French Guiana","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82605,254,"GUF","French Guiana","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82606,254,"GUF","French Guiana","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82607,254,"GUF","French Guiana","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82608,254,"GUF","French Guiana","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82609,254,"GUF","French Guiana","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUF/guf_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82610,258,"PYF","French Polynesia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82611,258,"PYF","French Polynesia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82612,258,"PYF","French Polynesia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82613,258,"PYF","French Polynesia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82614,258,"PYF","French Polynesia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82615,258,"PYF","French Polynesia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82616,258,"PYF","French Polynesia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82617,258,"PYF","French Polynesia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82618,258,"PYF","French Polynesia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82619,258,"PYF","French Polynesia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82620,258,"PYF","French Polynesia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82621,258,"PYF","French Polynesia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82622,258,"PYF","French Polynesia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82623,258,"PYF","French Polynesia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82624,258,"PYF","French Polynesia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82625,258,"PYF","French Polynesia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82626,258,"PYF","French Polynesia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82627,258,"PYF","French Polynesia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82628,258,"PYF","French Polynesia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82629,258,"PYF","French Polynesia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82630,258,"PYF","French Polynesia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82631,258,"PYF","French Polynesia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82632,258,"PYF","French Polynesia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82633,258,"PYF","French Polynesia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82634,258,"PYF","French Polynesia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82635,258,"PYF","French Polynesia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82636,258,"PYF","French Polynesia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82637,258,"PYF","French Polynesia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82638,258,"PYF","French Polynesia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82639,258,"PYF","French Polynesia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82640,258,"PYF","French Polynesia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82641,258,"PYF","French Polynesia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82642,258,"PYF","French Polynesia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82643,258,"PYF","French Polynesia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82644,258,"PYF","French Polynesia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82645,258,"PYF","French Polynesia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PYF/pyf_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82646,262,"DJI","Djibouti","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82647,262,"DJI","Djibouti","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82648,262,"DJI","Djibouti","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82649,262,"DJI","Djibouti","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82650,262,"DJI","Djibouti","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82651,262,"DJI","Djibouti","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82652,262,"DJI","Djibouti","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82653,262,"DJI","Djibouti","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82654,262,"DJI","Djibouti","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82655,262,"DJI","Djibouti","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82656,262,"DJI","Djibouti","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82657,262,"DJI","Djibouti","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82658,262,"DJI","Djibouti","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82659,262,"DJI","Djibouti","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82660,262,"DJI","Djibouti","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82661,262,"DJI","Djibouti","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82662,262,"DJI","Djibouti","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82663,262,"DJI","Djibouti","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82664,262,"DJI","Djibouti","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82665,262,"DJI","Djibouti","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82666,262,"DJI","Djibouti","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82667,262,"DJI","Djibouti","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82668,262,"DJI","Djibouti","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82669,262,"DJI","Djibouti","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82670,262,"DJI","Djibouti","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82671,262,"DJI","Djibouti","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82672,262,"DJI","Djibouti","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82673,262,"DJI","Djibouti","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82674,262,"DJI","Djibouti","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82675,262,"DJI","Djibouti","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82676,262,"DJI","Djibouti","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82677,262,"DJI","Djibouti","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82678,262,"DJI","Djibouti","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82679,262,"DJI","Djibouti","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82680,262,"DJI","Djibouti","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82681,262,"DJI","Djibouti","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DJI/dji_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82682,266,"GAB","Gabon","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82683,266,"GAB","Gabon","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82684,266,"GAB","Gabon","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82685,266,"GAB","Gabon","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82686,266,"GAB","Gabon","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82687,266,"GAB","Gabon","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82688,266,"GAB","Gabon","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82689,266,"GAB","Gabon","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82690,266,"GAB","Gabon","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82691,266,"GAB","Gabon","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82692,266,"GAB","Gabon","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82693,266,"GAB","Gabon","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82694,266,"GAB","Gabon","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82695,266,"GAB","Gabon","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82696,266,"GAB","Gabon","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82697,266,"GAB","Gabon","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82698,266,"GAB","Gabon","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82699,266,"GAB","Gabon","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82700,266,"GAB","Gabon","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82701,266,"GAB","Gabon","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82702,266,"GAB","Gabon","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82703,266,"GAB","Gabon","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82704,266,"GAB","Gabon","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82705,266,"GAB","Gabon","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82706,266,"GAB","Gabon","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82707,266,"GAB","Gabon","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82708,266,"GAB","Gabon","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82709,266,"GAB","Gabon","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82710,266,"GAB","Gabon","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82711,266,"GAB","Gabon","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82712,266,"GAB","Gabon","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82713,266,"GAB","Gabon","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82714,266,"GAB","Gabon","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82715,266,"GAB","Gabon","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82716,266,"GAB","Gabon","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82717,266,"GAB","Gabon","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GAB/gab_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82718,268,"GEO","Georgia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82719,268,"GEO","Georgia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82720,268,"GEO","Georgia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82721,268,"GEO","Georgia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82722,268,"GEO","Georgia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82723,268,"GEO","Georgia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82724,268,"GEO","Georgia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82725,268,"GEO","Georgia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82726,268,"GEO","Georgia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82727,268,"GEO","Georgia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82728,268,"GEO","Georgia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82729,268,"GEO","Georgia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82730,268,"GEO","Georgia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82731,268,"GEO","Georgia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82732,268,"GEO","Georgia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82733,268,"GEO","Georgia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82734,268,"GEO","Georgia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82735,268,"GEO","Georgia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82736,268,"GEO","Georgia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82737,268,"GEO","Georgia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82738,268,"GEO","Georgia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82739,268,"GEO","Georgia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82740,268,"GEO","Georgia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82741,268,"GEO","Georgia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82742,268,"GEO","Georgia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82743,268,"GEO","Georgia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82744,268,"GEO","Georgia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82745,268,"GEO","Georgia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82746,268,"GEO","Georgia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82747,268,"GEO","Georgia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82748,268,"GEO","Georgia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82749,268,"GEO","Georgia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82750,268,"GEO","Georgia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82751,268,"GEO","Georgia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82752,268,"GEO","Georgia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82753,268,"GEO","Georgia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GEO/geo_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82754,270,"GMB","Gambia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82755,270,"GMB","Gambia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82756,270,"GMB","Gambia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82757,270,"GMB","Gambia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82758,270,"GMB","Gambia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82759,270,"GMB","Gambia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82760,270,"GMB","Gambia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82761,270,"GMB","Gambia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82762,270,"GMB","Gambia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82763,270,"GMB","Gambia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82764,270,"GMB","Gambia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82765,270,"GMB","Gambia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82766,270,"GMB","Gambia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82767,270,"GMB","Gambia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82768,270,"GMB","Gambia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82769,270,"GMB","Gambia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82770,270,"GMB","Gambia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82771,270,"GMB","Gambia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82772,270,"GMB","Gambia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82773,270,"GMB","Gambia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82774,270,"GMB","Gambia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82775,270,"GMB","Gambia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82776,270,"GMB","Gambia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82777,270,"GMB","Gambia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82778,270,"GMB","Gambia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82779,270,"GMB","Gambia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82780,270,"GMB","Gambia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82781,270,"GMB","Gambia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82782,270,"GMB","Gambia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82783,270,"GMB","Gambia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82784,270,"GMB","Gambia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82785,270,"GMB","Gambia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82786,270,"GMB","Gambia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82787,270,"GMB","Gambia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82788,270,"GMB","Gambia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82789,270,"GMB","Gambia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GMB/gmb_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82790,275,"PSE","Palestina","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82791,275,"PSE","Palestina","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82792,275,"PSE","Palestina","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82793,275,"PSE","Palestina","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82794,275,"PSE","Palestina","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82795,275,"PSE","Palestina","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82796,275,"PSE","Palestina","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82797,275,"PSE","Palestina","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82798,275,"PSE","Palestina","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82799,275,"PSE","Palestina","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82800,275,"PSE","Palestina","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82801,275,"PSE","Palestina","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82802,275,"PSE","Palestina","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82803,275,"PSE","Palestina","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82804,275,"PSE","Palestina","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82805,275,"PSE","Palestina","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82806,275,"PSE","Palestina","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82807,275,"PSE","Palestina","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82808,275,"PSE","Palestina","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82809,275,"PSE","Palestina","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82810,275,"PSE","Palestina","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82811,275,"PSE","Palestina","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82812,275,"PSE","Palestina","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82813,275,"PSE","Palestina","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82814,275,"PSE","Palestina","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82815,275,"PSE","Palestina","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82816,275,"PSE","Palestina","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82817,275,"PSE","Palestina","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82818,275,"PSE","Palestina","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82819,275,"PSE","Palestina","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82820,275,"PSE","Palestina","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82821,275,"PSE","Palestina","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82822,275,"PSE","Palestina","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82823,275,"PSE","Palestina","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82824,275,"PSE","Palestina","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82825,275,"PSE","Palestina","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PSE/pse_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82826,276,"DEU","Germany","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82827,276,"DEU","Germany","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82828,276,"DEU","Germany","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82829,276,"DEU","Germany","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82830,276,"DEU","Germany","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82831,276,"DEU","Germany","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82832,276,"DEU","Germany","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82833,276,"DEU","Germany","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82834,276,"DEU","Germany","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82835,276,"DEU","Germany","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82836,276,"DEU","Germany","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82837,276,"DEU","Germany","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82838,276,"DEU","Germany","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82839,276,"DEU","Germany","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82840,276,"DEU","Germany","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82841,276,"DEU","Germany","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82842,276,"DEU","Germany","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82843,276,"DEU","Germany","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82844,276,"DEU","Germany","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82845,276,"DEU","Germany","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82846,276,"DEU","Germany","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82847,276,"DEU","Germany","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82848,276,"DEU","Germany","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82849,276,"DEU","Germany","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82850,276,"DEU","Germany","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82851,276,"DEU","Germany","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82852,276,"DEU","Germany","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82853,276,"DEU","Germany","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82854,276,"DEU","Germany","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82855,276,"DEU","Germany","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82856,276,"DEU","Germany","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82857,276,"DEU","Germany","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82858,276,"DEU","Germany","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82859,276,"DEU","Germany","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82860,276,"DEU","Germany","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82861,276,"DEU","Germany","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/DEU/deu_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82862,288,"GHA","Ghana","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82863,288,"GHA","Ghana","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82864,288,"GHA","Ghana","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82865,288,"GHA","Ghana","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82866,288,"GHA","Ghana","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82867,288,"GHA","Ghana","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82868,288,"GHA","Ghana","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82869,288,"GHA","Ghana","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82870,288,"GHA","Ghana","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82871,288,"GHA","Ghana","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82872,288,"GHA","Ghana","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82873,288,"GHA","Ghana","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82874,288,"GHA","Ghana","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82875,288,"GHA","Ghana","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82876,288,"GHA","Ghana","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82877,288,"GHA","Ghana","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82878,288,"GHA","Ghana","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82879,288,"GHA","Ghana","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82880,288,"GHA","Ghana","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82881,288,"GHA","Ghana","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82882,288,"GHA","Ghana","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82883,288,"GHA","Ghana","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82884,288,"GHA","Ghana","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82885,288,"GHA","Ghana","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82886,288,"GHA","Ghana","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82887,288,"GHA","Ghana","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82888,288,"GHA","Ghana","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82889,288,"GHA","Ghana","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82890,288,"GHA","Ghana","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82891,288,"GHA","Ghana","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82892,288,"GHA","Ghana","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82893,288,"GHA","Ghana","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82894,288,"GHA","Ghana","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82895,288,"GHA","Ghana","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82896,288,"GHA","Ghana","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82897,288,"GHA","Ghana","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GHA/gha_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
82898,292,"GIB","Gibraltar","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82899,292,"GIB","Gibraltar","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82900,292,"GIB","Gibraltar","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82901,292,"GIB","Gibraltar","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82902,292,"GIB","Gibraltar","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82903,292,"GIB","Gibraltar","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82904,292,"GIB","Gibraltar","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82905,292,"GIB","Gibraltar","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82906,292,"GIB","Gibraltar","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82907,292,"GIB","Gibraltar","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82908,292,"GIB","Gibraltar","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82909,292,"GIB","Gibraltar","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82910,292,"GIB","Gibraltar","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82911,292,"GIB","Gibraltar","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82912,292,"GIB","Gibraltar","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82913,292,"GIB","Gibraltar","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82914,292,"GIB","Gibraltar","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82915,292,"GIB","Gibraltar","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82916,292,"GIB","Gibraltar","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82917,292,"GIB","Gibraltar","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82918,292,"GIB","Gibraltar","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82919,292,"GIB","Gibraltar","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82920,292,"GIB","Gibraltar","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82921,292,"GIB","Gibraltar","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82922,292,"GIB","Gibraltar","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82923,292,"GIB","Gibraltar","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82924,292,"GIB","Gibraltar","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82925,292,"GIB","Gibraltar","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82926,292,"GIB","Gibraltar","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82927,292,"GIB","Gibraltar","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82928,292,"GIB","Gibraltar","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82929,292,"GIB","Gibraltar","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82930,292,"GIB","Gibraltar","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82931,292,"GIB","Gibraltar","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82932,292,"GIB","Gibraltar","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82933,292,"GIB","Gibraltar","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIB/gib_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82934,296,"KIR","Kiribati","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82935,296,"KIR","Kiribati","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82936,296,"KIR","Kiribati","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82937,296,"KIR","Kiribati","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82938,296,"KIR","Kiribati","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82939,296,"KIR","Kiribati","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82940,296,"KIR","Kiribati","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82941,296,"KIR","Kiribati","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82942,296,"KIR","Kiribati","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82943,296,"KIR","Kiribati","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82944,296,"KIR","Kiribati","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82945,296,"KIR","Kiribati","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82946,296,"KIR","Kiribati","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82947,296,"KIR","Kiribati","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82948,296,"KIR","Kiribati","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82949,296,"KIR","Kiribati","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82950,296,"KIR","Kiribati","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82951,296,"KIR","Kiribati","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82952,296,"KIR","Kiribati","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82953,296,"KIR","Kiribati","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82954,296,"KIR","Kiribati","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82955,296,"KIR","Kiribati","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82956,296,"KIR","Kiribati","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82957,296,"KIR","Kiribati","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82958,296,"KIR","Kiribati","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82959,296,"KIR","Kiribati","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82960,296,"KIR","Kiribati","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82961,296,"KIR","Kiribati","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82962,296,"KIR","Kiribati","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82963,296,"KIR","Kiribati","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82964,296,"KIR","Kiribati","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82965,296,"KIR","Kiribati","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82966,296,"KIR","Kiribati","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82967,296,"KIR","Kiribati","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82968,296,"KIR","Kiribati","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82969,296,"KIR","Kiribati","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KIR/kir_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82970,300,"GRC","Greece","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82971,300,"GRC","Greece","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82972,300,"GRC","Greece","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82973,300,"GRC","Greece","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82974,300,"GRC","Greece","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82975,300,"GRC","Greece","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82976,300,"GRC","Greece","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82977,300,"GRC","Greece","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82978,300,"GRC","Greece","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82979,300,"GRC","Greece","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82980,300,"GRC","Greece","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82981,300,"GRC","Greece","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82982,300,"GRC","Greece","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82983,300,"GRC","Greece","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82984,300,"GRC","Greece","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82985,300,"GRC","Greece","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82986,300,"GRC","Greece","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82987,300,"GRC","Greece","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82988,300,"GRC","Greece","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82989,300,"GRC","Greece","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82990,300,"GRC","Greece","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82991,300,"GRC","Greece","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82992,300,"GRC","Greece","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82993,300,"GRC","Greece","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82994,300,"GRC","Greece","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82995,300,"GRC","Greece","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82996,300,"GRC","Greece","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82997,300,"GRC","Greece","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82998,300,"GRC","Greece","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
82999,300,"GRC","Greece","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83000,300,"GRC","Greece","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83001,300,"GRC","Greece","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83002,300,"GRC","Greece","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83003,300,"GRC","Greece","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83004,300,"GRC","Greece","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83005,300,"GRC","Greece","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRC/grc_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83006,308,"GRD","Grenada","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83007,308,"GRD","Grenada","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83008,308,"GRD","Grenada","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83009,308,"GRD","Grenada","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83010,308,"GRD","Grenada","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83011,308,"GRD","Grenada","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83012,308,"GRD","Grenada","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83013,308,"GRD","Grenada","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83014,308,"GRD","Grenada","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83015,308,"GRD","Grenada","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83016,308,"GRD","Grenada","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83017,308,"GRD","Grenada","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83018,308,"GRD","Grenada","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83019,308,"GRD","Grenada","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83020,308,"GRD","Grenada","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83021,308,"GRD","Grenada","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83022,308,"GRD","Grenada","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83023,308,"GRD","Grenada","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83024,308,"GRD","Grenada","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83025,308,"GRD","Grenada","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83026,308,"GRD","Grenada","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83027,308,"GRD","Grenada","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83028,308,"GRD","Grenada","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83029,308,"GRD","Grenada","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83030,308,"GRD","Grenada","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83031,308,"GRD","Grenada","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83032,308,"GRD","Grenada","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83033,308,"GRD","Grenada","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83034,308,"GRD","Grenada","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83035,308,"GRD","Grenada","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83036,308,"GRD","Grenada","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83037,308,"GRD","Grenada","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83038,308,"GRD","Grenada","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83039,308,"GRD","Grenada","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83040,308,"GRD","Grenada","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83041,308,"GRD","Grenada","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GRD/grd_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83042,312,"GLP","Guadeloupe","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83043,312,"GLP","Guadeloupe","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83044,312,"GLP","Guadeloupe","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83045,312,"GLP","Guadeloupe","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83046,312,"GLP","Guadeloupe","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83047,312,"GLP","Guadeloupe","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83048,312,"GLP","Guadeloupe","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83049,312,"GLP","Guadeloupe","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83050,312,"GLP","Guadeloupe","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83051,312,"GLP","Guadeloupe","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83052,312,"GLP","Guadeloupe","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83053,312,"GLP","Guadeloupe","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83054,312,"GLP","Guadeloupe","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83055,312,"GLP","Guadeloupe","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83056,312,"GLP","Guadeloupe","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83057,312,"GLP","Guadeloupe","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83058,312,"GLP","Guadeloupe","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83059,312,"GLP","Guadeloupe","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83060,312,"GLP","Guadeloupe","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83061,312,"GLP","Guadeloupe","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83062,312,"GLP","Guadeloupe","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83063,312,"GLP","Guadeloupe","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83064,312,"GLP","Guadeloupe","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83065,312,"GLP","Guadeloupe","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83066,312,"GLP","Guadeloupe","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83067,312,"GLP","Guadeloupe","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83068,312,"GLP","Guadeloupe","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83069,312,"GLP","Guadeloupe","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83070,312,"GLP","Guadeloupe","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83071,312,"GLP","Guadeloupe","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83072,312,"GLP","Guadeloupe","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83073,312,"GLP","Guadeloupe","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83074,312,"GLP","Guadeloupe","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83075,312,"GLP","Guadeloupe","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83076,312,"GLP","Guadeloupe","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83077,312,"GLP","Guadeloupe","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GLP/glp_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83078,316,"GUM","Guam","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83079,316,"GUM","Guam","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83080,316,"GUM","Guam","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83081,316,"GUM","Guam","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83082,316,"GUM","Guam","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83083,316,"GUM","Guam","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83084,316,"GUM","Guam","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83085,316,"GUM","Guam","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83086,316,"GUM","Guam","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83087,316,"GUM","Guam","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83088,316,"GUM","Guam","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83089,316,"GUM","Guam","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83090,316,"GUM","Guam","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83091,316,"GUM","Guam","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83092,316,"GUM","Guam","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83093,316,"GUM","Guam","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83094,316,"GUM","Guam","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83095,316,"GUM","Guam","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83096,316,"GUM","Guam","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83097,316,"GUM","Guam","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83098,316,"GUM","Guam","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83099,316,"GUM","Guam","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83100,316,"GUM","Guam","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83101,316,"GUM","Guam","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83102,316,"GUM","Guam","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83103,316,"GUM","Guam","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83104,316,"GUM","Guam","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83105,316,"GUM","Guam","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83106,316,"GUM","Guam","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83107,316,"GUM","Guam","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83108,316,"GUM","Guam","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83109,316,"GUM","Guam","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83110,316,"GUM","Guam","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83111,316,"GUM","Guam","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83112,316,"GUM","Guam","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83113,316,"GUM","Guam","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUM/gum_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83114,320,"GTM","Guatemala","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83115,320,"GTM","Guatemala","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83116,320,"GTM","Guatemala","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83117,320,"GTM","Guatemala","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83118,320,"GTM","Guatemala","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83119,320,"GTM","Guatemala","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83120,320,"GTM","Guatemala","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83121,320,"GTM","Guatemala","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83122,320,"GTM","Guatemala","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83123,320,"GTM","Guatemala","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83124,320,"GTM","Guatemala","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83125,320,"GTM","Guatemala","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83126,320,"GTM","Guatemala","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83127,320,"GTM","Guatemala","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83128,320,"GTM","Guatemala","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83129,320,"GTM","Guatemala","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83130,320,"GTM","Guatemala","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83131,320,"GTM","Guatemala","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83132,320,"GTM","Guatemala","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83133,320,"GTM","Guatemala","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83134,320,"GTM","Guatemala","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83135,320,"GTM","Guatemala","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83136,320,"GTM","Guatemala","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83137,320,"GTM","Guatemala","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83138,320,"GTM","Guatemala","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83139,320,"GTM","Guatemala","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83140,320,"GTM","Guatemala","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83141,320,"GTM","Guatemala","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83142,320,"GTM","Guatemala","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83143,320,"GTM","Guatemala","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83144,320,"GTM","Guatemala","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83145,320,"GTM","Guatemala","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83146,320,"GTM","Guatemala","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83147,320,"GTM","Guatemala","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83148,320,"GTM","Guatemala","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83149,320,"GTM","Guatemala","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GTM/gtm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83150,324,"GIN","Guinea","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83151,324,"GIN","Guinea","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83152,324,"GIN","Guinea","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83153,324,"GIN","Guinea","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83154,324,"GIN","Guinea","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83155,324,"GIN","Guinea","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83156,324,"GIN","Guinea","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83157,324,"GIN","Guinea","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83158,324,"GIN","Guinea","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83159,324,"GIN","Guinea","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83160,324,"GIN","Guinea","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83161,324,"GIN","Guinea","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83162,324,"GIN","Guinea","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83163,324,"GIN","Guinea","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83164,324,"GIN","Guinea","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83165,324,"GIN","Guinea","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83166,324,"GIN","Guinea","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83167,324,"GIN","Guinea","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83168,324,"GIN","Guinea","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83169,324,"GIN","Guinea","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83170,324,"GIN","Guinea","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83171,324,"GIN","Guinea","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83172,324,"GIN","Guinea","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83173,324,"GIN","Guinea","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83174,324,"GIN","Guinea","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83175,324,"GIN","Guinea","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83176,324,"GIN","Guinea","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83177,324,"GIN","Guinea","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83178,324,"GIN","Guinea","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83179,324,"GIN","Guinea","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83180,324,"GIN","Guinea","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83181,324,"GIN","Guinea","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83182,324,"GIN","Guinea","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83183,324,"GIN","Guinea","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83184,324,"GIN","Guinea","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83185,324,"GIN","Guinea","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GIN/gin_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83186,328,"GUY","Guyana","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83187,328,"GUY","Guyana","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83188,328,"GUY","Guyana","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83189,328,"GUY","Guyana","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83190,328,"GUY","Guyana","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83191,328,"GUY","Guyana","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83192,328,"GUY","Guyana","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83193,328,"GUY","Guyana","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83194,328,"GUY","Guyana","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83195,328,"GUY","Guyana","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83196,328,"GUY","Guyana","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83197,328,"GUY","Guyana","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83198,328,"GUY","Guyana","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83199,328,"GUY","Guyana","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83200,328,"GUY","Guyana","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83201,328,"GUY","Guyana","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83202,328,"GUY","Guyana","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83203,328,"GUY","Guyana","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83204,328,"GUY","Guyana","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83205,328,"GUY","Guyana","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83206,328,"GUY","Guyana","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83207,328,"GUY","Guyana","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83208,328,"GUY","Guyana","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83209,328,"GUY","Guyana","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83210,328,"GUY","Guyana","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83211,328,"GUY","Guyana","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83212,328,"GUY","Guyana","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83213,328,"GUY","Guyana","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83214,328,"GUY","Guyana","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83215,328,"GUY","Guyana","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83216,328,"GUY","Guyana","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83217,328,"GUY","Guyana","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83218,328,"GUY","Guyana","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83219,328,"GUY","Guyana","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83220,328,"GUY","Guyana","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83221,328,"GUY","Guyana","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GUY/guy_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83222,332,"HTI","Haiti","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83223,332,"HTI","Haiti","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83224,332,"HTI","Haiti","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83225,332,"HTI","Haiti","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83226,332,"HTI","Haiti","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83227,332,"HTI","Haiti","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83228,332,"HTI","Haiti","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83229,332,"HTI","Haiti","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83230,332,"HTI","Haiti","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83231,332,"HTI","Haiti","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83232,332,"HTI","Haiti","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83233,332,"HTI","Haiti","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83234,332,"HTI","Haiti","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83235,332,"HTI","Haiti","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83236,332,"HTI","Haiti","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83237,332,"HTI","Haiti","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83238,332,"HTI","Haiti","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83239,332,"HTI","Haiti","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83240,332,"HTI","Haiti","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83241,332,"HTI","Haiti","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83242,332,"HTI","Haiti","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83243,332,"HTI","Haiti","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83244,332,"HTI","Haiti","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83245,332,"HTI","Haiti","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83246,332,"HTI","Haiti","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83247,332,"HTI","Haiti","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83248,332,"HTI","Haiti","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83249,332,"HTI","Haiti","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83250,332,"HTI","Haiti","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83251,332,"HTI","Haiti","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83252,332,"HTI","Haiti","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83253,332,"HTI","Haiti","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83254,332,"HTI","Haiti","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83255,332,"HTI","Haiti","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83256,332,"HTI","Haiti","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83257,332,"HTI","Haiti","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HTI/hti_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83258,336,"VAT","Vatican City","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83259,336,"VAT","Vatican City","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83260,336,"VAT","Vatican City","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83261,336,"VAT","Vatican City","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83262,336,"VAT","Vatican City","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83263,336,"VAT","Vatican City","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83264,336,"VAT","Vatican City","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83265,336,"VAT","Vatican City","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83266,336,"VAT","Vatican City","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83267,336,"VAT","Vatican City","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83268,336,"VAT","Vatican City","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83269,336,"VAT","Vatican City","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83270,336,"VAT","Vatican City","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83271,336,"VAT","Vatican City","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83272,336,"VAT","Vatican City","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83273,336,"VAT","Vatican City","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83274,336,"VAT","Vatican City","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83275,336,"VAT","Vatican City","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83276,336,"VAT","Vatican City","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83277,336,"VAT","Vatican City","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83278,336,"VAT","Vatican City","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83279,336,"VAT","Vatican City","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83280,336,"VAT","Vatican City","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83281,336,"VAT","Vatican City","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83282,336,"VAT","Vatican City","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83283,336,"VAT","Vatican City","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83284,336,"VAT","Vatican City","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83285,336,"VAT","Vatican City","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83286,336,"VAT","Vatican City","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83287,336,"VAT","Vatican City","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83288,336,"VAT","Vatican City","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83289,336,"VAT","Vatican City","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83290,336,"VAT","Vatican City","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83291,336,"VAT","Vatican City","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83292,336,"VAT","Vatican City","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83293,336,"VAT","Vatican City","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VAT/vat_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83294,340,"HND","Honduras","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83295,340,"HND","Honduras","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83296,340,"HND","Honduras","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83297,340,"HND","Honduras","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83298,340,"HND","Honduras","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83299,340,"HND","Honduras","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83300,340,"HND","Honduras","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83301,340,"HND","Honduras","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83302,340,"HND","Honduras","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83303,340,"HND","Honduras","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83304,340,"HND","Honduras","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83305,340,"HND","Honduras","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83306,340,"HND","Honduras","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83307,340,"HND","Honduras","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83308,340,"HND","Honduras","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83309,340,"HND","Honduras","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83310,340,"HND","Honduras","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83311,340,"HND","Honduras","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83312,340,"HND","Honduras","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83313,340,"HND","Honduras","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83314,340,"HND","Honduras","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83315,340,"HND","Honduras","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83316,340,"HND","Honduras","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83317,340,"HND","Honduras","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83318,340,"HND","Honduras","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83319,340,"HND","Honduras","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83320,340,"HND","Honduras","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83321,340,"HND","Honduras","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83322,340,"HND","Honduras","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83323,340,"HND","Honduras","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83324,340,"HND","Honduras","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83325,340,"HND","Honduras","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83326,340,"HND","Honduras","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83327,340,"HND","Honduras","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83328,340,"HND","Honduras","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83329,340,"HND","Honduras","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HND/hnd_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83330,344,"HKG","Hong Kong","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83331,344,"HKG","Hong Kong","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83332,344,"HKG","Hong Kong","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83333,344,"HKG","Hong Kong","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83334,344,"HKG","Hong Kong","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83335,344,"HKG","Hong Kong","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83336,344,"HKG","Hong Kong","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83337,344,"HKG","Hong Kong","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83338,344,"HKG","Hong Kong","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83339,344,"HKG","Hong Kong","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83340,344,"HKG","Hong Kong","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83341,344,"HKG","Hong Kong","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83342,344,"HKG","Hong Kong","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83343,344,"HKG","Hong Kong","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83344,344,"HKG","Hong Kong","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83345,344,"HKG","Hong Kong","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83346,344,"HKG","Hong Kong","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83347,344,"HKG","Hong Kong","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83348,344,"HKG","Hong Kong","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83349,344,"HKG","Hong Kong","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83350,344,"HKG","Hong Kong","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83351,344,"HKG","Hong Kong","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83352,344,"HKG","Hong Kong","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83353,344,"HKG","Hong Kong","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83354,344,"HKG","Hong Kong","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83355,344,"HKG","Hong Kong","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83356,344,"HKG","Hong Kong","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83357,344,"HKG","Hong Kong","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83358,344,"HKG","Hong Kong","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83359,344,"HKG","Hong Kong","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83360,344,"HKG","Hong Kong","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83361,344,"HKG","Hong Kong","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83362,344,"HKG","Hong Kong","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83363,344,"HKG","Hong Kong","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83364,344,"HKG","Hong Kong","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83365,344,"HKG","Hong Kong","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HKG/hkg_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83366,348,"HUN","Hungary","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83367,348,"HUN","Hungary","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83368,348,"HUN","Hungary","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83369,348,"HUN","Hungary","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83370,348,"HUN","Hungary","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83371,348,"HUN","Hungary","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83372,348,"HUN","Hungary","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83373,348,"HUN","Hungary","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83374,348,"HUN","Hungary","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83375,348,"HUN","Hungary","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83376,348,"HUN","Hungary","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83377,348,"HUN","Hungary","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83378,348,"HUN","Hungary","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83379,348,"HUN","Hungary","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83380,348,"HUN","Hungary","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83381,348,"HUN","Hungary","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83382,348,"HUN","Hungary","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83383,348,"HUN","Hungary","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83384,348,"HUN","Hungary","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83385,348,"HUN","Hungary","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83386,348,"HUN","Hungary","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83387,348,"HUN","Hungary","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83388,348,"HUN","Hungary","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83389,348,"HUN","Hungary","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83390,348,"HUN","Hungary","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83391,348,"HUN","Hungary","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83392,348,"HUN","Hungary","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83393,348,"HUN","Hungary","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83394,348,"HUN","Hungary","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83395,348,"HUN","Hungary","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83396,348,"HUN","Hungary","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83397,348,"HUN","Hungary","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83398,348,"HUN","Hungary","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83399,348,"HUN","Hungary","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83400,348,"HUN","Hungary","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83401,348,"HUN","Hungary","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/HUN/hun_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83402,352,"ISL","Iceland","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83403,352,"ISL","Iceland","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83404,352,"ISL","Iceland","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83405,352,"ISL","Iceland","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83406,352,"ISL","Iceland","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83407,352,"ISL","Iceland","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83408,352,"ISL","Iceland","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83409,352,"ISL","Iceland","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83410,352,"ISL","Iceland","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83411,352,"ISL","Iceland","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83412,352,"ISL","Iceland","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83413,352,"ISL","Iceland","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83414,352,"ISL","Iceland","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83415,352,"ISL","Iceland","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83416,352,"ISL","Iceland","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83417,352,"ISL","Iceland","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83418,352,"ISL","Iceland","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83419,352,"ISL","Iceland","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83420,352,"ISL","Iceland","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83421,352,"ISL","Iceland","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83422,352,"ISL","Iceland","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83423,352,"ISL","Iceland","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83424,352,"ISL","Iceland","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83425,352,"ISL","Iceland","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83426,352,"ISL","Iceland","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83427,352,"ISL","Iceland","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83428,352,"ISL","Iceland","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83429,352,"ISL","Iceland","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83430,352,"ISL","Iceland","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83431,352,"ISL","Iceland","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83432,352,"ISL","Iceland","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83433,352,"ISL","Iceland","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83434,352,"ISL","Iceland","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83435,352,"ISL","Iceland","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83436,352,"ISL","Iceland","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83437,352,"ISL","Iceland","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISL/isl_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83438,356,"IND","India","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83439,356,"IND","India","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83440,356,"IND","India","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83441,356,"IND","India","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83442,356,"IND","India","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83443,356,"IND","India","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83444,356,"IND","India","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83445,356,"IND","India","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83446,356,"IND","India","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83447,356,"IND","India","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83448,356,"IND","India","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83449,356,"IND","India","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83450,356,"IND","India","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83451,356,"IND","India","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83452,356,"IND","India","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83453,356,"IND","India","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83454,356,"IND","India","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83455,356,"IND","India","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83456,356,"IND","India","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83457,356,"IND","India","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83458,356,"IND","India","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83459,356,"IND","India","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83460,356,"IND","India","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83461,356,"IND","India","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83462,356,"IND","India","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83463,356,"IND","India","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83464,356,"IND","India","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83465,356,"IND","India","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83466,356,"IND","India","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83467,356,"IND","India","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83468,356,"IND","India","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83469,356,"IND","India","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83470,356,"IND","India","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83471,356,"IND","India","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83472,356,"IND","India","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83473,356,"IND","India","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IND/ind_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83474,364,"IRN","Iran","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83475,364,"IRN","Iran","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83476,364,"IRN","Iran","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83477,364,"IRN","Iran","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83478,364,"IRN","Iran","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83479,364,"IRN","Iran","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83480,364,"IRN","Iran","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83481,364,"IRN","Iran","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83482,364,"IRN","Iran","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83483,364,"IRN","Iran","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83484,364,"IRN","Iran","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83485,364,"IRN","Iran","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83486,364,"IRN","Iran","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83487,364,"IRN","Iran","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83488,364,"IRN","Iran","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83489,364,"IRN","Iran","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83490,364,"IRN","Iran","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83491,364,"IRN","Iran","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83492,364,"IRN","Iran","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83493,364,"IRN","Iran","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83494,364,"IRN","Iran","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83495,364,"IRN","Iran","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83496,364,"IRN","Iran","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83497,364,"IRN","Iran","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83498,364,"IRN","Iran","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83499,364,"IRN","Iran","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83500,364,"IRN","Iran","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83501,364,"IRN","Iran","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83502,364,"IRN","Iran","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83503,364,"IRN","Iran","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83504,364,"IRN","Iran","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83505,364,"IRN","Iran","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83506,364,"IRN","Iran","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83507,364,"IRN","Iran","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83508,364,"IRN","Iran","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83509,364,"IRN","Iran","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRN/irn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83510,368,"IRQ","Iraq","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83511,368,"IRQ","Iraq","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83512,368,"IRQ","Iraq","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83513,368,"IRQ","Iraq","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83514,368,"IRQ","Iraq","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83515,368,"IRQ","Iraq","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83516,368,"IRQ","Iraq","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83517,368,"IRQ","Iraq","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83518,368,"IRQ","Iraq","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83519,368,"IRQ","Iraq","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83520,368,"IRQ","Iraq","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83521,368,"IRQ","Iraq","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83522,368,"IRQ","Iraq","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83523,368,"IRQ","Iraq","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83524,368,"IRQ","Iraq","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83525,368,"IRQ","Iraq","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83526,368,"IRQ","Iraq","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83527,368,"IRQ","Iraq","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83528,368,"IRQ","Iraq","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83529,368,"IRQ","Iraq","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83530,368,"IRQ","Iraq","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83531,368,"IRQ","Iraq","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83532,368,"IRQ","Iraq","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83533,368,"IRQ","Iraq","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83534,368,"IRQ","Iraq","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83535,368,"IRQ","Iraq","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83536,368,"IRQ","Iraq","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83537,368,"IRQ","Iraq","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83538,368,"IRQ","Iraq","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83539,368,"IRQ","Iraq","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83540,368,"IRQ","Iraq","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83541,368,"IRQ","Iraq","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83542,368,"IRQ","Iraq","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83543,368,"IRQ","Iraq","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83544,368,"IRQ","Iraq","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83545,368,"IRQ","Iraq","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRQ/irq_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83546,372,"IRL","Ireland","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83547,372,"IRL","Ireland","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83548,372,"IRL","Ireland","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83549,372,"IRL","Ireland","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83550,372,"IRL","Ireland","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83551,372,"IRL","Ireland","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83552,372,"IRL","Ireland","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83553,372,"IRL","Ireland","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83554,372,"IRL","Ireland","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83555,372,"IRL","Ireland","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83556,372,"IRL","Ireland","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83557,372,"IRL","Ireland","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83558,372,"IRL","Ireland","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83559,372,"IRL","Ireland","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83560,372,"IRL","Ireland","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83561,372,"IRL","Ireland","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83562,372,"IRL","Ireland","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83563,372,"IRL","Ireland","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83564,372,"IRL","Ireland","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83565,372,"IRL","Ireland","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83566,372,"IRL","Ireland","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83567,372,"IRL","Ireland","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83568,372,"IRL","Ireland","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83569,372,"IRL","Ireland","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83570,372,"IRL","Ireland","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83571,372,"IRL","Ireland","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83572,372,"IRL","Ireland","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83573,372,"IRL","Ireland","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83574,372,"IRL","Ireland","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83575,372,"IRL","Ireland","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83576,372,"IRL","Ireland","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83577,372,"IRL","Ireland","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83578,372,"IRL","Ireland","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83579,372,"IRL","Ireland","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83580,372,"IRL","Ireland","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83581,372,"IRL","Ireland","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IRL/irl_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83582,376,"ISR","Israel","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83583,376,"ISR","Israel","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83584,376,"ISR","Israel","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83585,376,"ISR","Israel","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83586,376,"ISR","Israel","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83587,376,"ISR","Israel","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83588,376,"ISR","Israel","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83589,376,"ISR","Israel","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83590,376,"ISR","Israel","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83591,376,"ISR","Israel","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83592,376,"ISR","Israel","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83593,376,"ISR","Israel","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83594,376,"ISR","Israel","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83595,376,"ISR","Israel","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83596,376,"ISR","Israel","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83597,376,"ISR","Israel","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83598,376,"ISR","Israel","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83599,376,"ISR","Israel","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83600,376,"ISR","Israel","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83601,376,"ISR","Israel","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83602,376,"ISR","Israel","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83603,376,"ISR","Israel","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83604,376,"ISR","Israel","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83605,376,"ISR","Israel","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83606,376,"ISR","Israel","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83607,376,"ISR","Israel","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83608,376,"ISR","Israel","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83609,376,"ISR","Israel","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83610,376,"ISR","Israel","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83611,376,"ISR","Israel","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83612,376,"ISR","Israel","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83613,376,"ISR","Israel","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83614,376,"ISR","Israel","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83615,376,"ISR","Israel","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83616,376,"ISR","Israel","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83617,376,"ISR","Israel","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ISR/isr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83618,380,"ITA","Italy","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83619,380,"ITA","Italy","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83620,380,"ITA","Italy","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83621,380,"ITA","Italy","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83622,380,"ITA","Italy","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83623,380,"ITA","Italy","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83624,380,"ITA","Italy","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83625,380,"ITA","Italy","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83626,380,"ITA","Italy","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83627,380,"ITA","Italy","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83628,380,"ITA","Italy","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83629,380,"ITA","Italy","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83630,380,"ITA","Italy","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83631,380,"ITA","Italy","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83632,380,"ITA","Italy","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83633,380,"ITA","Italy","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83634,380,"ITA","Italy","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83635,380,"ITA","Italy","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83636,380,"ITA","Italy","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83637,380,"ITA","Italy","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83638,380,"ITA","Italy","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83639,380,"ITA","Italy","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83640,380,"ITA","Italy","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83641,380,"ITA","Italy","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83642,380,"ITA","Italy","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83643,380,"ITA","Italy","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83644,380,"ITA","Italy","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83645,380,"ITA","Italy","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83646,380,"ITA","Italy","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83647,380,"ITA","Italy","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83648,380,"ITA","Italy","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83649,380,"ITA","Italy","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83650,380,"ITA","Italy","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83651,380,"ITA","Italy","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83652,380,"ITA","Italy","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83653,380,"ITA","Italy","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ITA/ita_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83654,384,"CIV","CIte dIvoire","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83655,384,"CIV","CIte dIvoire","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83656,384,"CIV","CIte dIvoire","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83657,384,"CIV","CIte dIvoire","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83658,384,"CIV","CIte dIvoire","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83659,384,"CIV","CIte dIvoire","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83660,384,"CIV","CIte dIvoire","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83661,384,"CIV","CIte dIvoire","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83662,384,"CIV","CIte dIvoire","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83663,384,"CIV","CIte dIvoire","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83664,384,"CIV","CIte dIvoire","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83665,384,"CIV","CIte dIvoire","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83666,384,"CIV","CIte dIvoire","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83667,384,"CIV","CIte dIvoire","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83668,384,"CIV","CIte dIvoire","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83669,384,"CIV","CIte dIvoire","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83670,384,"CIV","CIte dIvoire","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83671,384,"CIV","CIte dIvoire","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83672,384,"CIV","CIte dIvoire","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83673,384,"CIV","CIte dIvoire","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83674,384,"CIV","CIte dIvoire","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83675,384,"CIV","CIte dIvoire","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83676,384,"CIV","CIte dIvoire","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83677,384,"CIV","CIte dIvoire","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83678,384,"CIV","CIte dIvoire","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83679,384,"CIV","CIte dIvoire","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83680,384,"CIV","CIte dIvoire","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83681,384,"CIV","CIte dIvoire","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83682,384,"CIV","CIte dIvoire","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83683,384,"CIV","CIte dIvoire","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83684,384,"CIV","CIte dIvoire","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83685,384,"CIV","CIte dIvoire","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83686,384,"CIV","CIte dIvoire","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83687,384,"CIV","CIte dIvoire","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83688,384,"CIV","CIte dIvoire","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83689,384,"CIV","CIte dIvoire","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CIV/civ_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83690,388,"JAM","Jamaica","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83691,388,"JAM","Jamaica","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83692,388,"JAM","Jamaica","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83693,388,"JAM","Jamaica","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83694,388,"JAM","Jamaica","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83695,388,"JAM","Jamaica","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83696,388,"JAM","Jamaica","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83697,388,"JAM","Jamaica","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83698,388,"JAM","Jamaica","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83699,388,"JAM","Jamaica","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83700,388,"JAM","Jamaica","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83701,388,"JAM","Jamaica","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83702,388,"JAM","Jamaica","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83703,388,"JAM","Jamaica","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83704,388,"JAM","Jamaica","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83705,388,"JAM","Jamaica","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83706,388,"JAM","Jamaica","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83707,388,"JAM","Jamaica","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83708,388,"JAM","Jamaica","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83709,388,"JAM","Jamaica","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83710,388,"JAM","Jamaica","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83711,388,"JAM","Jamaica","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83712,388,"JAM","Jamaica","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83713,388,"JAM","Jamaica","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83714,388,"JAM","Jamaica","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83715,388,"JAM","Jamaica","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83716,388,"JAM","Jamaica","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83717,388,"JAM","Jamaica","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83718,388,"JAM","Jamaica","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83719,388,"JAM","Jamaica","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83720,388,"JAM","Jamaica","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83721,388,"JAM","Jamaica","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83722,388,"JAM","Jamaica","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83723,388,"JAM","Jamaica","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83724,388,"JAM","Jamaica","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83725,388,"JAM","Jamaica","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JAM/jam_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83726,392,"JPN","Japan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83727,392,"JPN","Japan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83728,392,"JPN","Japan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83729,392,"JPN","Japan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83730,392,"JPN","Japan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83731,392,"JPN","Japan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83732,392,"JPN","Japan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83733,392,"JPN","Japan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83734,392,"JPN","Japan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83735,392,"JPN","Japan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83736,392,"JPN","Japan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83737,392,"JPN","Japan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83738,392,"JPN","Japan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83739,392,"JPN","Japan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83740,392,"JPN","Japan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83741,392,"JPN","Japan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83742,392,"JPN","Japan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83743,392,"JPN","Japan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83744,392,"JPN","Japan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83745,392,"JPN","Japan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83746,392,"JPN","Japan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83747,392,"JPN","Japan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83748,392,"JPN","Japan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83749,392,"JPN","Japan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83750,392,"JPN","Japan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83751,392,"JPN","Japan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83752,392,"JPN","Japan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83753,392,"JPN","Japan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83754,392,"JPN","Japan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83755,392,"JPN","Japan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83756,392,"JPN","Japan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83757,392,"JPN","Japan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83758,392,"JPN","Japan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83759,392,"JPN","Japan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83760,392,"JPN","Japan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83761,392,"JPN","Japan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JPN/jpn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83762,398,"KAZ","Kazakhstan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83763,398,"KAZ","Kazakhstan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83764,398,"KAZ","Kazakhstan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83765,398,"KAZ","Kazakhstan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83766,398,"KAZ","Kazakhstan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83767,398,"KAZ","Kazakhstan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83768,398,"KAZ","Kazakhstan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83769,398,"KAZ","Kazakhstan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83770,398,"KAZ","Kazakhstan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83771,398,"KAZ","Kazakhstan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83772,398,"KAZ","Kazakhstan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83773,398,"KAZ","Kazakhstan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83774,398,"KAZ","Kazakhstan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83775,398,"KAZ","Kazakhstan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83776,398,"KAZ","Kazakhstan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83777,398,"KAZ","Kazakhstan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83778,398,"KAZ","Kazakhstan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83779,398,"KAZ","Kazakhstan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83780,398,"KAZ","Kazakhstan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83781,398,"KAZ","Kazakhstan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83782,398,"KAZ","Kazakhstan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83783,398,"KAZ","Kazakhstan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83784,398,"KAZ","Kazakhstan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83785,398,"KAZ","Kazakhstan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83786,398,"KAZ","Kazakhstan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83787,398,"KAZ","Kazakhstan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83788,398,"KAZ","Kazakhstan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83789,398,"KAZ","Kazakhstan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83790,398,"KAZ","Kazakhstan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83791,398,"KAZ","Kazakhstan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83792,398,"KAZ","Kazakhstan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83793,398,"KAZ","Kazakhstan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83794,398,"KAZ","Kazakhstan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83795,398,"KAZ","Kazakhstan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83796,398,"KAZ","Kazakhstan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83797,398,"KAZ","Kazakhstan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KAZ/kaz_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83798,400,"JOR","Jordan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83799,400,"JOR","Jordan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83800,400,"JOR","Jordan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83801,400,"JOR","Jordan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83802,400,"JOR","Jordan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83803,400,"JOR","Jordan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83804,400,"JOR","Jordan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83805,400,"JOR","Jordan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83806,400,"JOR","Jordan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83807,400,"JOR","Jordan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83808,400,"JOR","Jordan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83809,400,"JOR","Jordan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83810,400,"JOR","Jordan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83811,400,"JOR","Jordan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83812,400,"JOR","Jordan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83813,400,"JOR","Jordan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83814,400,"JOR","Jordan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83815,400,"JOR","Jordan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83816,400,"JOR","Jordan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83817,400,"JOR","Jordan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83818,400,"JOR","Jordan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83819,400,"JOR","Jordan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83820,400,"JOR","Jordan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83821,400,"JOR","Jordan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83822,400,"JOR","Jordan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83823,400,"JOR","Jordan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83824,400,"JOR","Jordan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83825,400,"JOR","Jordan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83826,400,"JOR","Jordan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83827,400,"JOR","Jordan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83828,400,"JOR","Jordan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83829,400,"JOR","Jordan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83830,400,"JOR","Jordan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83831,400,"JOR","Jordan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83832,400,"JOR","Jordan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83833,400,"JOR","Jordan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JOR/jor_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83834,404,"KEN","Kenya","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83835,404,"KEN","Kenya","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83836,404,"KEN","Kenya","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83837,404,"KEN","Kenya","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83838,404,"KEN","Kenya","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83839,404,"KEN","Kenya","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83840,404,"KEN","Kenya","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83841,404,"KEN","Kenya","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83842,404,"KEN","Kenya","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83843,404,"KEN","Kenya","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83844,404,"KEN","Kenya","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83845,404,"KEN","Kenya","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83846,404,"KEN","Kenya","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83847,404,"KEN","Kenya","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83848,404,"KEN","Kenya","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83849,404,"KEN","Kenya","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83850,404,"KEN","Kenya","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83851,404,"KEN","Kenya","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83852,404,"KEN","Kenya","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83853,404,"KEN","Kenya","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83854,404,"KEN","Kenya","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83855,404,"KEN","Kenya","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83856,404,"KEN","Kenya","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83857,404,"KEN","Kenya","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83858,404,"KEN","Kenya","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83859,404,"KEN","Kenya","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83860,404,"KEN","Kenya","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83861,404,"KEN","Kenya","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83862,404,"KEN","Kenya","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83863,404,"KEN","Kenya","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83864,404,"KEN","Kenya","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83865,404,"KEN","Kenya","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83866,404,"KEN","Kenya","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83867,404,"KEN","Kenya","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83868,404,"KEN","Kenya","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83869,404,"KEN","Kenya","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KEN/ken_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
83870,408,"PRK","North Korea","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83871,408,"PRK","North Korea","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83872,408,"PRK","North Korea","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83873,408,"PRK","North Korea","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83874,408,"PRK","North Korea","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83875,408,"PRK","North Korea","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83876,408,"PRK","North Korea","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83877,408,"PRK","North Korea","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83878,408,"PRK","North Korea","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83879,408,"PRK","North Korea","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83880,408,"PRK","North Korea","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83881,408,"PRK","North Korea","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83882,408,"PRK","North Korea","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83883,408,"PRK","North Korea","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83884,408,"PRK","North Korea","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83885,408,"PRK","North Korea","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83886,408,"PRK","North Korea","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83887,408,"PRK","North Korea","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83888,408,"PRK","North Korea","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83889,408,"PRK","North Korea","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83890,408,"PRK","North Korea","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83891,408,"PRK","North Korea","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83892,408,"PRK","North Korea","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83893,408,"PRK","North Korea","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83894,408,"PRK","North Korea","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83895,408,"PRK","North Korea","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83896,408,"PRK","North Korea","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83897,408,"PRK","North Korea","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83898,408,"PRK","North Korea","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83899,408,"PRK","North Korea","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83900,408,"PRK","North Korea","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83901,408,"PRK","North Korea","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83902,408,"PRK","North Korea","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83903,408,"PRK","North Korea","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83904,408,"PRK","North Korea","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83905,408,"PRK","North Korea","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRK/prk_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83906,410,"KOR","South Korea","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83907,410,"KOR","South Korea","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83908,410,"KOR","South Korea","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83909,410,"KOR","South Korea","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83910,410,"KOR","South Korea","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83911,410,"KOR","South Korea","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83912,410,"KOR","South Korea","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83913,410,"KOR","South Korea","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83914,410,"KOR","South Korea","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83915,410,"KOR","South Korea","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83916,410,"KOR","South Korea","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83917,410,"KOR","South Korea","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83918,410,"KOR","South Korea","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83919,410,"KOR","South Korea","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83920,410,"KOR","South Korea","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83921,410,"KOR","South Korea","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83922,410,"KOR","South Korea","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83923,410,"KOR","South Korea","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83924,410,"KOR","South Korea","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83925,410,"KOR","South Korea","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83926,410,"KOR","South Korea","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83927,410,"KOR","South Korea","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83928,410,"KOR","South Korea","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83929,410,"KOR","South Korea","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83930,410,"KOR","South Korea","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83931,410,"KOR","South Korea","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83932,410,"KOR","South Korea","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83933,410,"KOR","South Korea","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83934,410,"KOR","South Korea","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83935,410,"KOR","South Korea","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83936,410,"KOR","South Korea","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83937,410,"KOR","South Korea","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83938,410,"KOR","South Korea","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83939,410,"KOR","South Korea","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83940,410,"KOR","South Korea","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83941,410,"KOR","South Korea","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOR/kor_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83942,414,"KWT","Kuwait","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83943,414,"KWT","Kuwait","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83944,414,"KWT","Kuwait","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83945,414,"KWT","Kuwait","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83946,414,"KWT","Kuwait","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83947,414,"KWT","Kuwait","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83948,414,"KWT","Kuwait","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83949,414,"KWT","Kuwait","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83950,414,"KWT","Kuwait","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83951,414,"KWT","Kuwait","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83952,414,"KWT","Kuwait","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83953,414,"KWT","Kuwait","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83954,414,"KWT","Kuwait","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83955,414,"KWT","Kuwait","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83956,414,"KWT","Kuwait","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83957,414,"KWT","Kuwait","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83958,414,"KWT","Kuwait","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83959,414,"KWT","Kuwait","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83960,414,"KWT","Kuwait","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83961,414,"KWT","Kuwait","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83962,414,"KWT","Kuwait","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83963,414,"KWT","Kuwait","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83964,414,"KWT","Kuwait","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83965,414,"KWT","Kuwait","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83966,414,"KWT","Kuwait","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83967,414,"KWT","Kuwait","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83968,414,"KWT","Kuwait","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83969,414,"KWT","Kuwait","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83970,414,"KWT","Kuwait","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83971,414,"KWT","Kuwait","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83972,414,"KWT","Kuwait","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83973,414,"KWT","Kuwait","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83974,414,"KWT","Kuwait","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83975,414,"KWT","Kuwait","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83976,414,"KWT","Kuwait","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83977,414,"KWT","Kuwait","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KWT/kwt_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83978,417,"KGZ","Kyrgyzstan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83979,417,"KGZ","Kyrgyzstan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83980,417,"KGZ","Kyrgyzstan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83981,417,"KGZ","Kyrgyzstan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83982,417,"KGZ","Kyrgyzstan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83983,417,"KGZ","Kyrgyzstan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83984,417,"KGZ","Kyrgyzstan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83985,417,"KGZ","Kyrgyzstan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83986,417,"KGZ","Kyrgyzstan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83987,417,"KGZ","Kyrgyzstan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83988,417,"KGZ","Kyrgyzstan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83989,417,"KGZ","Kyrgyzstan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83990,417,"KGZ","Kyrgyzstan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83991,417,"KGZ","Kyrgyzstan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83992,417,"KGZ","Kyrgyzstan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83993,417,"KGZ","Kyrgyzstan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83994,417,"KGZ","Kyrgyzstan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83995,417,"KGZ","Kyrgyzstan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83996,417,"KGZ","Kyrgyzstan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83997,417,"KGZ","Kyrgyzstan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83998,417,"KGZ","Kyrgyzstan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
83999,417,"KGZ","Kyrgyzstan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84000,417,"KGZ","Kyrgyzstan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84001,417,"KGZ","Kyrgyzstan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84002,417,"KGZ","Kyrgyzstan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84003,417,"KGZ","Kyrgyzstan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84004,417,"KGZ","Kyrgyzstan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84005,417,"KGZ","Kyrgyzstan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84006,417,"KGZ","Kyrgyzstan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84007,417,"KGZ","Kyrgyzstan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84008,417,"KGZ","Kyrgyzstan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84009,417,"KGZ","Kyrgyzstan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84010,417,"KGZ","Kyrgyzstan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84011,417,"KGZ","Kyrgyzstan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84012,417,"KGZ","Kyrgyzstan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84013,417,"KGZ","Kyrgyzstan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KGZ/kgz_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84014,418,"LAO","Laos","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84015,418,"LAO","Laos","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84016,418,"LAO","Laos","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84017,418,"LAO","Laos","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84018,418,"LAO","Laos","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84019,418,"LAO","Laos","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84020,418,"LAO","Laos","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84021,418,"LAO","Laos","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84022,418,"LAO","Laos","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84023,418,"LAO","Laos","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84024,418,"LAO","Laos","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84025,418,"LAO","Laos","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84026,418,"LAO","Laos","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84027,418,"LAO","Laos","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84028,418,"LAO","Laos","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84029,418,"LAO","Laos","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84030,418,"LAO","Laos","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84031,418,"LAO","Laos","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84032,418,"LAO","Laos","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84033,418,"LAO","Laos","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84034,418,"LAO","Laos","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84035,418,"LAO","Laos","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84036,418,"LAO","Laos","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84037,418,"LAO","Laos","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84038,418,"LAO","Laos","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84039,418,"LAO","Laos","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84040,418,"LAO","Laos","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84041,418,"LAO","Laos","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84042,418,"LAO","Laos","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84043,418,"LAO","Laos","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84044,418,"LAO","Laos","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84045,418,"LAO","Laos","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84046,418,"LAO","Laos","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84047,418,"LAO","Laos","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84048,418,"LAO","Laos","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84049,418,"LAO","Laos","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LAO/lao_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84050,422,"LBN","Lebanon","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84051,422,"LBN","Lebanon","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84052,422,"LBN","Lebanon","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84053,422,"LBN","Lebanon","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84054,422,"LBN","Lebanon","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84055,422,"LBN","Lebanon","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84056,422,"LBN","Lebanon","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84057,422,"LBN","Lebanon","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84058,422,"LBN","Lebanon","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84059,422,"LBN","Lebanon","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84060,422,"LBN","Lebanon","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84061,422,"LBN","Lebanon","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84062,422,"LBN","Lebanon","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84063,422,"LBN","Lebanon","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84064,422,"LBN","Lebanon","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84065,422,"LBN","Lebanon","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84066,422,"LBN","Lebanon","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84067,422,"LBN","Lebanon","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84068,422,"LBN","Lebanon","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84069,422,"LBN","Lebanon","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84070,422,"LBN","Lebanon","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84071,422,"LBN","Lebanon","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84072,422,"LBN","Lebanon","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84073,422,"LBN","Lebanon","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84074,422,"LBN","Lebanon","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84075,422,"LBN","Lebanon","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84076,422,"LBN","Lebanon","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84077,422,"LBN","Lebanon","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84078,422,"LBN","Lebanon","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84079,422,"LBN","Lebanon","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84080,422,"LBN","Lebanon","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84081,422,"LBN","Lebanon","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84082,422,"LBN","Lebanon","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84083,422,"LBN","Lebanon","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84084,422,"LBN","Lebanon","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84085,422,"LBN","Lebanon","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBN/lbn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84086,426,"LSO","Lesotho","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84087,426,"LSO","Lesotho","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84088,426,"LSO","Lesotho","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84089,426,"LSO","Lesotho","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84090,426,"LSO","Lesotho","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84091,426,"LSO","Lesotho","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84092,426,"LSO","Lesotho","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84093,426,"LSO","Lesotho","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84094,426,"LSO","Lesotho","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84095,426,"LSO","Lesotho","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84096,426,"LSO","Lesotho","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84097,426,"LSO","Lesotho","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84098,426,"LSO","Lesotho","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84099,426,"LSO","Lesotho","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84100,426,"LSO","Lesotho","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84101,426,"LSO","Lesotho","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84102,426,"LSO","Lesotho","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84103,426,"LSO","Lesotho","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84104,426,"LSO","Lesotho","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84105,426,"LSO","Lesotho","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84106,426,"LSO","Lesotho","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84107,426,"LSO","Lesotho","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84108,426,"LSO","Lesotho","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84109,426,"LSO","Lesotho","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84110,426,"LSO","Lesotho","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84111,426,"LSO","Lesotho","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84112,426,"LSO","Lesotho","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84113,426,"LSO","Lesotho","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84114,426,"LSO","Lesotho","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84115,426,"LSO","Lesotho","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84116,426,"LSO","Lesotho","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84117,426,"LSO","Lesotho","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84118,426,"LSO","Lesotho","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84119,426,"LSO","Lesotho","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84120,426,"LSO","Lesotho","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84121,426,"LSO","Lesotho","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LSO/lso_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84122,428,"LVA","Latvia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84123,428,"LVA","Latvia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84124,428,"LVA","Latvia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84125,428,"LVA","Latvia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84126,428,"LVA","Latvia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84127,428,"LVA","Latvia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84128,428,"LVA","Latvia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84129,428,"LVA","Latvia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84130,428,"LVA","Latvia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84131,428,"LVA","Latvia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84132,428,"LVA","Latvia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84133,428,"LVA","Latvia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84134,428,"LVA","Latvia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84135,428,"LVA","Latvia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84136,428,"LVA","Latvia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84137,428,"LVA","Latvia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84138,428,"LVA","Latvia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84139,428,"LVA","Latvia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84140,428,"LVA","Latvia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84141,428,"LVA","Latvia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84142,428,"LVA","Latvia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84143,428,"LVA","Latvia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84144,428,"LVA","Latvia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84145,428,"LVA","Latvia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84146,428,"LVA","Latvia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84147,428,"LVA","Latvia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84148,428,"LVA","Latvia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84149,428,"LVA","Latvia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84150,428,"LVA","Latvia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84151,428,"LVA","Latvia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84152,428,"LVA","Latvia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84153,428,"LVA","Latvia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84154,428,"LVA","Latvia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84155,428,"LVA","Latvia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84156,428,"LVA","Latvia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84157,428,"LVA","Latvia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LVA/lva_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84158,430,"LBR","Liberia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84159,430,"LBR","Liberia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84160,430,"LBR","Liberia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84161,430,"LBR","Liberia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84162,430,"LBR","Liberia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84163,430,"LBR","Liberia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84164,430,"LBR","Liberia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84165,430,"LBR","Liberia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84166,430,"LBR","Liberia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84167,430,"LBR","Liberia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84168,430,"LBR","Liberia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84169,430,"LBR","Liberia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84170,430,"LBR","Liberia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84171,430,"LBR","Liberia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84172,430,"LBR","Liberia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84173,430,"LBR","Liberia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84174,430,"LBR","Liberia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84175,430,"LBR","Liberia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84176,430,"LBR","Liberia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84177,430,"LBR","Liberia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84178,430,"LBR","Liberia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84179,430,"LBR","Liberia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84180,430,"LBR","Liberia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84181,430,"LBR","Liberia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84182,430,"LBR","Liberia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84183,430,"LBR","Liberia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84184,430,"LBR","Liberia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84185,430,"LBR","Liberia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84186,430,"LBR","Liberia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84187,430,"LBR","Liberia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84188,430,"LBR","Liberia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84189,430,"LBR","Liberia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84190,430,"LBR","Liberia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84191,430,"LBR","Liberia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84192,430,"LBR","Liberia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84193,430,"LBR","Liberia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBR/lbr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84194,434,"LBY","Libya","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84195,434,"LBY","Libya","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84196,434,"LBY","Libya","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84197,434,"LBY","Libya","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84198,434,"LBY","Libya","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84199,434,"LBY","Libya","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84200,434,"LBY","Libya","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84201,434,"LBY","Libya","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84202,434,"LBY","Libya","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84203,434,"LBY","Libya","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84204,434,"LBY","Libya","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84205,434,"LBY","Libya","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84206,434,"LBY","Libya","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84207,434,"LBY","Libya","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84208,434,"LBY","Libya","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84209,434,"LBY","Libya","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84210,434,"LBY","Libya","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84211,434,"LBY","Libya","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84212,434,"LBY","Libya","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84213,434,"LBY","Libya","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84214,434,"LBY","Libya","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84215,434,"LBY","Libya","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84216,434,"LBY","Libya","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84217,434,"LBY","Libya","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84218,434,"LBY","Libya","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84219,434,"LBY","Libya","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84220,434,"LBY","Libya","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84221,434,"LBY","Libya","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84222,434,"LBY","Libya","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84223,434,"LBY","Libya","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84224,434,"LBY","Libya","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84225,434,"LBY","Libya","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84226,434,"LBY","Libya","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84227,434,"LBY","Libya","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84228,434,"LBY","Libya","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84229,434,"LBY","Libya","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LBY/lby_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84230,438,"LIE","Liechtenstein","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84231,438,"LIE","Liechtenstein","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84232,438,"LIE","Liechtenstein","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84233,438,"LIE","Liechtenstein","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84234,438,"LIE","Liechtenstein","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84235,438,"LIE","Liechtenstein","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84236,438,"LIE","Liechtenstein","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84237,438,"LIE","Liechtenstein","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84238,438,"LIE","Liechtenstein","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84239,438,"LIE","Liechtenstein","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84240,438,"LIE","Liechtenstein","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84241,438,"LIE","Liechtenstein","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84242,438,"LIE","Liechtenstein","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84243,438,"LIE","Liechtenstein","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84244,438,"LIE","Liechtenstein","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84245,438,"LIE","Liechtenstein","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84246,438,"LIE","Liechtenstein","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84247,438,"LIE","Liechtenstein","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84248,438,"LIE","Liechtenstein","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84249,438,"LIE","Liechtenstein","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84250,438,"LIE","Liechtenstein","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84251,438,"LIE","Liechtenstein","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84252,438,"LIE","Liechtenstein","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84253,438,"LIE","Liechtenstein","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84254,438,"LIE","Liechtenstein","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84255,438,"LIE","Liechtenstein","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84256,438,"LIE","Liechtenstein","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84257,438,"LIE","Liechtenstein","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84258,438,"LIE","Liechtenstein","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84259,438,"LIE","Liechtenstein","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84260,438,"LIE","Liechtenstein","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84261,438,"LIE","Liechtenstein","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84262,438,"LIE","Liechtenstein","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84263,438,"LIE","Liechtenstein","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84264,438,"LIE","Liechtenstein","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84265,438,"LIE","Liechtenstein","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LIE/lie_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84266,440,"LTU","Lithuania","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84267,440,"LTU","Lithuania","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84268,440,"LTU","Lithuania","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84269,440,"LTU","Lithuania","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84270,440,"LTU","Lithuania","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84271,440,"LTU","Lithuania","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84272,440,"LTU","Lithuania","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84273,440,"LTU","Lithuania","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84274,440,"LTU","Lithuania","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84275,440,"LTU","Lithuania","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84276,440,"LTU","Lithuania","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84277,440,"LTU","Lithuania","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84278,440,"LTU","Lithuania","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84279,440,"LTU","Lithuania","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84280,440,"LTU","Lithuania","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84281,440,"LTU","Lithuania","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84282,440,"LTU","Lithuania","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84283,440,"LTU","Lithuania","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84284,440,"LTU","Lithuania","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84285,440,"LTU","Lithuania","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84286,440,"LTU","Lithuania","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84287,440,"LTU","Lithuania","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84288,440,"LTU","Lithuania","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84289,440,"LTU","Lithuania","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84290,440,"LTU","Lithuania","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84291,440,"LTU","Lithuania","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84292,440,"LTU","Lithuania","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84293,440,"LTU","Lithuania","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84294,440,"LTU","Lithuania","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84295,440,"LTU","Lithuania","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84296,440,"LTU","Lithuania","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84297,440,"LTU","Lithuania","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84298,440,"LTU","Lithuania","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84299,440,"LTU","Lithuania","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84300,440,"LTU","Lithuania","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84301,440,"LTU","Lithuania","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LTU/ltu_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84302,442,"LUX","Luxembourg","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84303,442,"LUX","Luxembourg","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84304,442,"LUX","Luxembourg","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84305,442,"LUX","Luxembourg","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84306,442,"LUX","Luxembourg","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84307,442,"LUX","Luxembourg","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84308,442,"LUX","Luxembourg","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84309,442,"LUX","Luxembourg","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84310,442,"LUX","Luxembourg","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84311,442,"LUX","Luxembourg","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84312,442,"LUX","Luxembourg","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84313,442,"LUX","Luxembourg","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84314,442,"LUX","Luxembourg","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84315,442,"LUX","Luxembourg","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84316,442,"LUX","Luxembourg","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84317,442,"LUX","Luxembourg","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84318,442,"LUX","Luxembourg","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84319,442,"LUX","Luxembourg","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84320,442,"LUX","Luxembourg","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84321,442,"LUX","Luxembourg","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84322,442,"LUX","Luxembourg","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84323,442,"LUX","Luxembourg","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84324,442,"LUX","Luxembourg","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84325,442,"LUX","Luxembourg","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84326,442,"LUX","Luxembourg","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84327,442,"LUX","Luxembourg","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84328,442,"LUX","Luxembourg","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84329,442,"LUX","Luxembourg","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84330,442,"LUX","Luxembourg","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84331,442,"LUX","Luxembourg","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84332,442,"LUX","Luxembourg","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84333,442,"LUX","Luxembourg","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84334,442,"LUX","Luxembourg","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84335,442,"LUX","Luxembourg","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84336,442,"LUX","Luxembourg","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84337,442,"LUX","Luxembourg","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LUX/lux_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84338,446,"MAC","Macao","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84339,446,"MAC","Macao","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84340,446,"MAC","Macao","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84341,446,"MAC","Macao","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84342,446,"MAC","Macao","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84343,446,"MAC","Macao","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84344,446,"MAC","Macao","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84345,446,"MAC","Macao","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84346,446,"MAC","Macao","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84347,446,"MAC","Macao","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84348,446,"MAC","Macao","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84349,446,"MAC","Macao","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84350,446,"MAC","Macao","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84351,446,"MAC","Macao","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84352,446,"MAC","Macao","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84353,446,"MAC","Macao","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84354,446,"MAC","Macao","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84355,446,"MAC","Macao","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84356,446,"MAC","Macao","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84357,446,"MAC","Macao","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84358,446,"MAC","Macao","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84359,446,"MAC","Macao","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84360,446,"MAC","Macao","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84361,446,"MAC","Macao","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84362,446,"MAC","Macao","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84363,446,"MAC","Macao","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84364,446,"MAC","Macao","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84365,446,"MAC","Macao","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84366,446,"MAC","Macao","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84367,446,"MAC","Macao","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84368,446,"MAC","Macao","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84369,446,"MAC","Macao","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84370,446,"MAC","Macao","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84371,446,"MAC","Macao","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84372,446,"MAC","Macao","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84373,446,"MAC","Macao","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAC/mac_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84374,450,"MDG","Madagascar","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84375,450,"MDG","Madagascar","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84376,450,"MDG","Madagascar","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84377,450,"MDG","Madagascar","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84378,450,"MDG","Madagascar","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84379,450,"MDG","Madagascar","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84380,450,"MDG","Madagascar","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84381,450,"MDG","Madagascar","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84382,450,"MDG","Madagascar","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84383,450,"MDG","Madagascar","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84384,450,"MDG","Madagascar","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84385,450,"MDG","Madagascar","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84386,450,"MDG","Madagascar","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84387,450,"MDG","Madagascar","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84388,450,"MDG","Madagascar","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84389,450,"MDG","Madagascar","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84390,450,"MDG","Madagascar","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84391,450,"MDG","Madagascar","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84392,450,"MDG","Madagascar","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84393,450,"MDG","Madagascar","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84394,450,"MDG","Madagascar","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84395,450,"MDG","Madagascar","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84396,450,"MDG","Madagascar","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84397,450,"MDG","Madagascar","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84398,450,"MDG","Madagascar","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84399,450,"MDG","Madagascar","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84400,450,"MDG","Madagascar","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84401,450,"MDG","Madagascar","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84402,450,"MDG","Madagascar","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84403,450,"MDG","Madagascar","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84404,450,"MDG","Madagascar","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84405,450,"MDG","Madagascar","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84406,450,"MDG","Madagascar","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84407,450,"MDG","Madagascar","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84408,450,"MDG","Madagascar","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84409,450,"MDG","Madagascar","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDG/mdg_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84410,454,"MWI","Malawi","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84411,454,"MWI","Malawi","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84412,454,"MWI","Malawi","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84413,454,"MWI","Malawi","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84414,454,"MWI","Malawi","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84415,454,"MWI","Malawi","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84416,454,"MWI","Malawi","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84417,454,"MWI","Malawi","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84418,454,"MWI","Malawi","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84419,454,"MWI","Malawi","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84420,454,"MWI","Malawi","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84421,454,"MWI","Malawi","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84422,454,"MWI","Malawi","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84423,454,"MWI","Malawi","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84424,454,"MWI","Malawi","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84425,454,"MWI","Malawi","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84426,454,"MWI","Malawi","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84427,454,"MWI","Malawi","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84428,454,"MWI","Malawi","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84429,454,"MWI","Malawi","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84430,454,"MWI","Malawi","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84431,454,"MWI","Malawi","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84432,454,"MWI","Malawi","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84433,454,"MWI","Malawi","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84434,454,"MWI","Malawi","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84435,454,"MWI","Malawi","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84436,454,"MWI","Malawi","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84437,454,"MWI","Malawi","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84438,454,"MWI","Malawi","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84439,454,"MWI","Malawi","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84440,454,"MWI","Malawi","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84441,454,"MWI","Malawi","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84442,454,"MWI","Malawi","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84443,454,"MWI","Malawi","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84444,454,"MWI","Malawi","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84445,454,"MWI","Malawi","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MWI/mwi_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84446,458,"MYS","Malaysia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84447,458,"MYS","Malaysia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84448,458,"MYS","Malaysia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84449,458,"MYS","Malaysia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84450,458,"MYS","Malaysia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84451,458,"MYS","Malaysia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84452,458,"MYS","Malaysia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84453,458,"MYS","Malaysia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84454,458,"MYS","Malaysia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84455,458,"MYS","Malaysia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84456,458,"MYS","Malaysia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84457,458,"MYS","Malaysia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84458,458,"MYS","Malaysia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84459,458,"MYS","Malaysia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84460,458,"MYS","Malaysia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84461,458,"MYS","Malaysia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84462,458,"MYS","Malaysia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84463,458,"MYS","Malaysia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84464,458,"MYS","Malaysia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84465,458,"MYS","Malaysia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84466,458,"MYS","Malaysia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84467,458,"MYS","Malaysia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84468,458,"MYS","Malaysia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84469,458,"MYS","Malaysia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84470,458,"MYS","Malaysia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84471,458,"MYS","Malaysia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84472,458,"MYS","Malaysia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84473,458,"MYS","Malaysia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84474,458,"MYS","Malaysia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84475,458,"MYS","Malaysia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84476,458,"MYS","Malaysia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84477,458,"MYS","Malaysia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84478,458,"MYS","Malaysia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84479,458,"MYS","Malaysia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84480,458,"MYS","Malaysia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84481,458,"MYS","Malaysia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MYS/mys_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84482,462,"MDV","Maldives","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84483,462,"MDV","Maldives","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84484,462,"MDV","Maldives","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84485,462,"MDV","Maldives","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84486,462,"MDV","Maldives","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84487,462,"MDV","Maldives","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84488,462,"MDV","Maldives","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84489,462,"MDV","Maldives","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84490,462,"MDV","Maldives","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84491,462,"MDV","Maldives","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84492,462,"MDV","Maldives","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84493,462,"MDV","Maldives","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84494,462,"MDV","Maldives","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84495,462,"MDV","Maldives","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84496,462,"MDV","Maldives","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84497,462,"MDV","Maldives","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84498,462,"MDV","Maldives","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84499,462,"MDV","Maldives","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84500,462,"MDV","Maldives","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84501,462,"MDV","Maldives","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84502,462,"MDV","Maldives","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84503,462,"MDV","Maldives","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84504,462,"MDV","Maldives","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84505,462,"MDV","Maldives","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84506,462,"MDV","Maldives","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84507,462,"MDV","Maldives","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84508,462,"MDV","Maldives","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84509,462,"MDV","Maldives","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84510,462,"MDV","Maldives","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84511,462,"MDV","Maldives","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84512,462,"MDV","Maldives","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84513,462,"MDV","Maldives","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84514,462,"MDV","Maldives","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84515,462,"MDV","Maldives","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84516,462,"MDV","Maldives","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84517,462,"MDV","Maldives","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDV/mdv_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84518,466,"MLI","Mali","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84519,466,"MLI","Mali","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84520,466,"MLI","Mali","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84521,466,"MLI","Mali","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84522,466,"MLI","Mali","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84523,466,"MLI","Mali","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84524,466,"MLI","Mali","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84525,466,"MLI","Mali","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84526,466,"MLI","Mali","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84527,466,"MLI","Mali","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84528,466,"MLI","Mali","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84529,466,"MLI","Mali","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84530,466,"MLI","Mali","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84531,466,"MLI","Mali","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84532,466,"MLI","Mali","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84533,466,"MLI","Mali","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84534,466,"MLI","Mali","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84535,466,"MLI","Mali","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84536,466,"MLI","Mali","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84537,466,"MLI","Mali","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84538,466,"MLI","Mali","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84539,466,"MLI","Mali","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84540,466,"MLI","Mali","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84541,466,"MLI","Mali","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84542,466,"MLI","Mali","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84543,466,"MLI","Mali","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84544,466,"MLI","Mali","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84545,466,"MLI","Mali","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84546,466,"MLI","Mali","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84547,466,"MLI","Mali","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84548,466,"MLI","Mali","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84549,466,"MLI","Mali","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84550,466,"MLI","Mali","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84551,466,"MLI","Mali","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84552,466,"MLI","Mali","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84553,466,"MLI","Mali","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLI/mli_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84554,470,"MLT","Malta","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84555,470,"MLT","Malta","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84556,470,"MLT","Malta","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84557,470,"MLT","Malta","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84558,470,"MLT","Malta","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84559,470,"MLT","Malta","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84560,470,"MLT","Malta","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84561,470,"MLT","Malta","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84562,470,"MLT","Malta","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84563,470,"MLT","Malta","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84564,470,"MLT","Malta","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84565,470,"MLT","Malta","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84566,470,"MLT","Malta","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84567,470,"MLT","Malta","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84568,470,"MLT","Malta","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84569,470,"MLT","Malta","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84570,470,"MLT","Malta","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84571,470,"MLT","Malta","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84572,470,"MLT","Malta","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84573,470,"MLT","Malta","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84574,470,"MLT","Malta","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84575,470,"MLT","Malta","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84576,470,"MLT","Malta","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84577,470,"MLT","Malta","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84578,470,"MLT","Malta","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84579,470,"MLT","Malta","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84580,470,"MLT","Malta","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84581,470,"MLT","Malta","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84582,470,"MLT","Malta","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84583,470,"MLT","Malta","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84584,470,"MLT","Malta","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84585,470,"MLT","Malta","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84586,470,"MLT","Malta","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84587,470,"MLT","Malta","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84588,470,"MLT","Malta","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84589,470,"MLT","Malta","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MLT/mlt_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84590,474,"MTQ","Martinique","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84591,474,"MTQ","Martinique","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84592,474,"MTQ","Martinique","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84593,474,"MTQ","Martinique","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84594,474,"MTQ","Martinique","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84595,474,"MTQ","Martinique","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84596,474,"MTQ","Martinique","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84597,474,"MTQ","Martinique","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84598,474,"MTQ","Martinique","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84599,474,"MTQ","Martinique","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84600,474,"MTQ","Martinique","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84601,474,"MTQ","Martinique","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84602,474,"MTQ","Martinique","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84603,474,"MTQ","Martinique","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84604,474,"MTQ","Martinique","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84605,474,"MTQ","Martinique","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84606,474,"MTQ","Martinique","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84607,474,"MTQ","Martinique","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84608,474,"MTQ","Martinique","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84609,474,"MTQ","Martinique","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84610,474,"MTQ","Martinique","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84611,474,"MTQ","Martinique","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84612,474,"MTQ","Martinique","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84613,474,"MTQ","Martinique","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84614,474,"MTQ","Martinique","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84615,474,"MTQ","Martinique","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84616,474,"MTQ","Martinique","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84617,474,"MTQ","Martinique","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84618,474,"MTQ","Martinique","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84619,474,"MTQ","Martinique","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84620,474,"MTQ","Martinique","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84621,474,"MTQ","Martinique","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84622,474,"MTQ","Martinique","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84623,474,"MTQ","Martinique","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84624,474,"MTQ","Martinique","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84625,474,"MTQ","Martinique","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MTQ/mtq_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84626,478,"MRT","Mauritania","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84627,478,"MRT","Mauritania","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84628,478,"MRT","Mauritania","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84629,478,"MRT","Mauritania","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84630,478,"MRT","Mauritania","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84631,478,"MRT","Mauritania","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84632,478,"MRT","Mauritania","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84633,478,"MRT","Mauritania","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84634,478,"MRT","Mauritania","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84635,478,"MRT","Mauritania","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84636,478,"MRT","Mauritania","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84637,478,"MRT","Mauritania","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84638,478,"MRT","Mauritania","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84639,478,"MRT","Mauritania","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84640,478,"MRT","Mauritania","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84641,478,"MRT","Mauritania","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84642,478,"MRT","Mauritania","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84643,478,"MRT","Mauritania","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84644,478,"MRT","Mauritania","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84645,478,"MRT","Mauritania","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84646,478,"MRT","Mauritania","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84647,478,"MRT","Mauritania","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84648,478,"MRT","Mauritania","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84649,478,"MRT","Mauritania","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84650,478,"MRT","Mauritania","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84651,478,"MRT","Mauritania","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84652,478,"MRT","Mauritania","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84653,478,"MRT","Mauritania","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84654,478,"MRT","Mauritania","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84655,478,"MRT","Mauritania","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84656,478,"MRT","Mauritania","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84657,478,"MRT","Mauritania","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84658,478,"MRT","Mauritania","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84659,478,"MRT","Mauritania","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84660,478,"MRT","Mauritania","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84661,478,"MRT","Mauritania","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MRT/mrt_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84662,480,"MUS","Mauritius","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84663,480,"MUS","Mauritius","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84664,480,"MUS","Mauritius","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84665,480,"MUS","Mauritius","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84666,480,"MUS","Mauritius","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84667,480,"MUS","Mauritius","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84668,480,"MUS","Mauritius","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84669,480,"MUS","Mauritius","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84670,480,"MUS","Mauritius","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84671,480,"MUS","Mauritius","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84672,480,"MUS","Mauritius","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84673,480,"MUS","Mauritius","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84674,480,"MUS","Mauritius","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84675,480,"MUS","Mauritius","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84676,480,"MUS","Mauritius","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84677,480,"MUS","Mauritius","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84678,480,"MUS","Mauritius","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84679,480,"MUS","Mauritius","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84680,480,"MUS","Mauritius","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84681,480,"MUS","Mauritius","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84682,480,"MUS","Mauritius","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84683,480,"MUS","Mauritius","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84684,480,"MUS","Mauritius","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84685,480,"MUS","Mauritius","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84686,480,"MUS","Mauritius","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84687,480,"MUS","Mauritius","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84688,480,"MUS","Mauritius","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84689,480,"MUS","Mauritius","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84690,480,"MUS","Mauritius","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84691,480,"MUS","Mauritius","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84692,480,"MUS","Mauritius","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84693,480,"MUS","Mauritius","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84694,480,"MUS","Mauritius","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84695,480,"MUS","Mauritius","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84696,480,"MUS","Mauritius","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84697,480,"MUS","Mauritius","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MUS/mus_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84698,484,"MEX","Mexico","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84699,484,"MEX","Mexico","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84700,484,"MEX","Mexico","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84701,484,"MEX","Mexico","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84702,484,"MEX","Mexico","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84703,484,"MEX","Mexico","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84704,484,"MEX","Mexico","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84705,484,"MEX","Mexico","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84706,484,"MEX","Mexico","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84707,484,"MEX","Mexico","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84708,484,"MEX","Mexico","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84709,484,"MEX","Mexico","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84710,484,"MEX","Mexico","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84711,484,"MEX","Mexico","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84712,484,"MEX","Mexico","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84713,484,"MEX","Mexico","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84714,484,"MEX","Mexico","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84715,484,"MEX","Mexico","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84716,484,"MEX","Mexico","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84717,484,"MEX","Mexico","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84718,484,"MEX","Mexico","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84719,484,"MEX","Mexico","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84720,484,"MEX","Mexico","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84721,484,"MEX","Mexico","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84722,484,"MEX","Mexico","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84723,484,"MEX","Mexico","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84724,484,"MEX","Mexico","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84725,484,"MEX","Mexico","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84726,484,"MEX","Mexico","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84727,484,"MEX","Mexico","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84728,484,"MEX","Mexico","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84729,484,"MEX","Mexico","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84730,484,"MEX","Mexico","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84731,484,"MEX","Mexico","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84732,484,"MEX","Mexico","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84733,484,"MEX","Mexico","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MEX/mex_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84734,492,"MCO","Monaco","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84735,492,"MCO","Monaco","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84736,492,"MCO","Monaco","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84737,492,"MCO","Monaco","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84738,492,"MCO","Monaco","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84739,492,"MCO","Monaco","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84740,492,"MCO","Monaco","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84741,492,"MCO","Monaco","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84742,492,"MCO","Monaco","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84743,492,"MCO","Monaco","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84744,492,"MCO","Monaco","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84745,492,"MCO","Monaco","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84746,492,"MCO","Monaco","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84747,492,"MCO","Monaco","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84748,492,"MCO","Monaco","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84749,492,"MCO","Monaco","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84750,492,"MCO","Monaco","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84751,492,"MCO","Monaco","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84752,492,"MCO","Monaco","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84753,492,"MCO","Monaco","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84754,492,"MCO","Monaco","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84755,492,"MCO","Monaco","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84756,492,"MCO","Monaco","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84757,492,"MCO","Monaco","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84758,492,"MCO","Monaco","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84759,492,"MCO","Monaco","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84760,492,"MCO","Monaco","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84761,492,"MCO","Monaco","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84762,492,"MCO","Monaco","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84763,492,"MCO","Monaco","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84764,492,"MCO","Monaco","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84765,492,"MCO","Monaco","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84766,492,"MCO","Monaco","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84767,492,"MCO","Monaco","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84768,492,"MCO","Monaco","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84769,492,"MCO","Monaco","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MCO/mco_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84770,496,"MNG","Mongolia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84771,496,"MNG","Mongolia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84772,496,"MNG","Mongolia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84773,496,"MNG","Mongolia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84774,496,"MNG","Mongolia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84775,496,"MNG","Mongolia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84776,496,"MNG","Mongolia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84777,496,"MNG","Mongolia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84778,496,"MNG","Mongolia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84779,496,"MNG","Mongolia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84780,496,"MNG","Mongolia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84781,496,"MNG","Mongolia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84782,496,"MNG","Mongolia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84783,496,"MNG","Mongolia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84784,496,"MNG","Mongolia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84785,496,"MNG","Mongolia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84786,496,"MNG","Mongolia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84787,496,"MNG","Mongolia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84788,496,"MNG","Mongolia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84789,496,"MNG","Mongolia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84790,496,"MNG","Mongolia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84791,496,"MNG","Mongolia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84792,496,"MNG","Mongolia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84793,496,"MNG","Mongolia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84794,496,"MNG","Mongolia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84795,496,"MNG","Mongolia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84796,496,"MNG","Mongolia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84797,496,"MNG","Mongolia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84798,496,"MNG","Mongolia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84799,496,"MNG","Mongolia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84800,496,"MNG","Mongolia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84801,496,"MNG","Mongolia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84802,496,"MNG","Mongolia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84803,496,"MNG","Mongolia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84804,496,"MNG","Mongolia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84805,496,"MNG","Mongolia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNG/mng_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84806,498,"MDA","Moldova","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84807,498,"MDA","Moldova","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84808,498,"MDA","Moldova","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84809,498,"MDA","Moldova","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84810,498,"MDA","Moldova","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84811,498,"MDA","Moldova","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84812,498,"MDA","Moldova","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84813,498,"MDA","Moldova","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84814,498,"MDA","Moldova","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84815,498,"MDA","Moldova","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84816,498,"MDA","Moldova","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84817,498,"MDA","Moldova","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84818,498,"MDA","Moldova","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84819,498,"MDA","Moldova","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84820,498,"MDA","Moldova","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84821,498,"MDA","Moldova","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84822,498,"MDA","Moldova","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84823,498,"MDA","Moldova","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84824,498,"MDA","Moldova","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84825,498,"MDA","Moldova","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84826,498,"MDA","Moldova","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84827,498,"MDA","Moldova","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84828,498,"MDA","Moldova","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84829,498,"MDA","Moldova","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84830,498,"MDA","Moldova","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84831,498,"MDA","Moldova","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84832,498,"MDA","Moldova","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84833,498,"MDA","Moldova","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84834,498,"MDA","Moldova","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84835,498,"MDA","Moldova","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84836,498,"MDA","Moldova","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84837,498,"MDA","Moldova","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84838,498,"MDA","Moldova","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84839,498,"MDA","Moldova","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84840,498,"MDA","Moldova","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84841,498,"MDA","Moldova","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MDA/mda_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84842,499,"MNE","Montenegro","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84843,499,"MNE","Montenegro","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84844,499,"MNE","Montenegro","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84845,499,"MNE","Montenegro","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84846,499,"MNE","Montenegro","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84847,499,"MNE","Montenegro","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84848,499,"MNE","Montenegro","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84849,499,"MNE","Montenegro","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84850,499,"MNE","Montenegro","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84851,499,"MNE","Montenegro","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84852,499,"MNE","Montenegro","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84853,499,"MNE","Montenegro","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84854,499,"MNE","Montenegro","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84855,499,"MNE","Montenegro","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84856,499,"MNE","Montenegro","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84857,499,"MNE","Montenegro","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84858,499,"MNE","Montenegro","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84859,499,"MNE","Montenegro","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84860,499,"MNE","Montenegro","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84861,499,"MNE","Montenegro","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84862,499,"MNE","Montenegro","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84863,499,"MNE","Montenegro","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84864,499,"MNE","Montenegro","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84865,499,"MNE","Montenegro","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84866,499,"MNE","Montenegro","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84867,499,"MNE","Montenegro","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84868,499,"MNE","Montenegro","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84869,499,"MNE","Montenegro","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84870,499,"MNE","Montenegro","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84871,499,"MNE","Montenegro","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84872,499,"MNE","Montenegro","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84873,499,"MNE","Montenegro","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84874,499,"MNE","Montenegro","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84875,499,"MNE","Montenegro","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84876,499,"MNE","Montenegro","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84877,499,"MNE","Montenegro","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNE/mne_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84878,500,"MSR","Montserrat","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84879,500,"MSR","Montserrat","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84880,500,"MSR","Montserrat","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84881,500,"MSR","Montserrat","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84882,500,"MSR","Montserrat","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84883,500,"MSR","Montserrat","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84884,500,"MSR","Montserrat","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84885,500,"MSR","Montserrat","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84886,500,"MSR","Montserrat","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84887,500,"MSR","Montserrat","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84888,500,"MSR","Montserrat","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84889,500,"MSR","Montserrat","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84890,500,"MSR","Montserrat","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84891,500,"MSR","Montserrat","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84892,500,"MSR","Montserrat","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84893,500,"MSR","Montserrat","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84894,500,"MSR","Montserrat","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84895,500,"MSR","Montserrat","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84896,500,"MSR","Montserrat","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84897,500,"MSR","Montserrat","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84898,500,"MSR","Montserrat","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84899,500,"MSR","Montserrat","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84900,500,"MSR","Montserrat","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84901,500,"MSR","Montserrat","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84902,500,"MSR","Montserrat","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84903,500,"MSR","Montserrat","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84904,500,"MSR","Montserrat","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84905,500,"MSR","Montserrat","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84906,500,"MSR","Montserrat","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84907,500,"MSR","Montserrat","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84908,500,"MSR","Montserrat","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84909,500,"MSR","Montserrat","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84910,500,"MSR","Montserrat","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84911,500,"MSR","Montserrat","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84912,500,"MSR","Montserrat","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84913,500,"MSR","Montserrat","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MSR/msr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84914,504,"MAR","Morocco","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84915,504,"MAR","Morocco","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84916,504,"MAR","Morocco","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84917,504,"MAR","Morocco","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84918,504,"MAR","Morocco","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84919,504,"MAR","Morocco","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84920,504,"MAR","Morocco","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84921,504,"MAR","Morocco","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84922,504,"MAR","Morocco","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84923,504,"MAR","Morocco","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84924,504,"MAR","Morocco","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84925,504,"MAR","Morocco","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84926,504,"MAR","Morocco","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84927,504,"MAR","Morocco","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84928,504,"MAR","Morocco","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84929,504,"MAR","Morocco","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84930,504,"MAR","Morocco","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84931,504,"MAR","Morocco","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84932,504,"MAR","Morocco","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84933,504,"MAR","Morocco","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84934,504,"MAR","Morocco","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84935,504,"MAR","Morocco","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84936,504,"MAR","Morocco","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84937,504,"MAR","Morocco","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84938,504,"MAR","Morocco","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84939,504,"MAR","Morocco","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84940,504,"MAR","Morocco","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84941,504,"MAR","Morocco","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84942,504,"MAR","Morocco","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84943,504,"MAR","Morocco","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84944,504,"MAR","Morocco","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84945,504,"MAR","Morocco","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84946,504,"MAR","Morocco","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84947,504,"MAR","Morocco","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84948,504,"MAR","Morocco","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84949,504,"MAR","Morocco","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAR/mar_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84950,508,"MOZ","Mozambique","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84951,508,"MOZ","Mozambique","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84952,508,"MOZ","Mozambique","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84953,508,"MOZ","Mozambique","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84954,508,"MOZ","Mozambique","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84955,508,"MOZ","Mozambique","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84956,508,"MOZ","Mozambique","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84957,508,"MOZ","Mozambique","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84958,508,"MOZ","Mozambique","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84959,508,"MOZ","Mozambique","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84960,508,"MOZ","Mozambique","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84961,508,"MOZ","Mozambique","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84962,508,"MOZ","Mozambique","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84963,508,"MOZ","Mozambique","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84964,508,"MOZ","Mozambique","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84965,508,"MOZ","Mozambique","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84966,508,"MOZ","Mozambique","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84967,508,"MOZ","Mozambique","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84968,508,"MOZ","Mozambique","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84969,508,"MOZ","Mozambique","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84970,508,"MOZ","Mozambique","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84971,508,"MOZ","Mozambique","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84972,508,"MOZ","Mozambique","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84973,508,"MOZ","Mozambique","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84974,508,"MOZ","Mozambique","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84975,508,"MOZ","Mozambique","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84976,508,"MOZ","Mozambique","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84977,508,"MOZ","Mozambique","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84978,508,"MOZ","Mozambique","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84979,508,"MOZ","Mozambique","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84980,508,"MOZ","Mozambique","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84981,508,"MOZ","Mozambique","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84982,508,"MOZ","Mozambique","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84983,508,"MOZ","Mozambique","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84984,508,"MOZ","Mozambique","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84985,508,"MOZ","Mozambique","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MOZ/moz_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
84986,512,"OMN","Oman","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84987,512,"OMN","Oman","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84988,512,"OMN","Oman","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84989,512,"OMN","Oman","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84990,512,"OMN","Oman","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84991,512,"OMN","Oman","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84992,512,"OMN","Oman","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84993,512,"OMN","Oman","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84994,512,"OMN","Oman","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84995,512,"OMN","Oman","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84996,512,"OMN","Oman","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84997,512,"OMN","Oman","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84998,512,"OMN","Oman","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
84999,512,"OMN","Oman","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85000,512,"OMN","Oman","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85001,512,"OMN","Oman","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85002,512,"OMN","Oman","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85003,512,"OMN","Oman","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85004,512,"OMN","Oman","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85005,512,"OMN","Oman","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85006,512,"OMN","Oman","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85007,512,"OMN","Oman","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85008,512,"OMN","Oman","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85009,512,"OMN","Oman","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85010,512,"OMN","Oman","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85011,512,"OMN","Oman","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85012,512,"OMN","Oman","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85013,512,"OMN","Oman","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85014,512,"OMN","Oman","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85015,512,"OMN","Oman","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85016,512,"OMN","Oman","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85017,512,"OMN","Oman","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85018,512,"OMN","Oman","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85019,512,"OMN","Oman","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85020,512,"OMN","Oman","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85021,512,"OMN","Oman","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/OMN/omn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85022,516,"NAM","Namibia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85023,516,"NAM","Namibia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85024,516,"NAM","Namibia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85025,516,"NAM","Namibia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85026,516,"NAM","Namibia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85027,516,"NAM","Namibia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85028,516,"NAM","Namibia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85029,516,"NAM","Namibia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85030,516,"NAM","Namibia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85031,516,"NAM","Namibia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85032,516,"NAM","Namibia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85033,516,"NAM","Namibia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85034,516,"NAM","Namibia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85035,516,"NAM","Namibia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85036,516,"NAM","Namibia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85037,516,"NAM","Namibia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85038,516,"NAM","Namibia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85039,516,"NAM","Namibia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85040,516,"NAM","Namibia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85041,516,"NAM","Namibia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85042,516,"NAM","Namibia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85043,516,"NAM","Namibia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85044,516,"NAM","Namibia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85045,516,"NAM","Namibia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85046,516,"NAM","Namibia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85047,516,"NAM","Namibia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85048,516,"NAM","Namibia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85049,516,"NAM","Namibia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85050,516,"NAM","Namibia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85051,516,"NAM","Namibia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85052,516,"NAM","Namibia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85053,516,"NAM","Namibia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85054,516,"NAM","Namibia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85055,516,"NAM","Namibia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85056,516,"NAM","Namibia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85057,516,"NAM","Namibia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NAM/nam_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85058,520,"NRU","Nauru","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85059,520,"NRU","Nauru","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85060,520,"NRU","Nauru","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85061,520,"NRU","Nauru","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85062,520,"NRU","Nauru","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85063,520,"NRU","Nauru","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85064,520,"NRU","Nauru","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85065,520,"NRU","Nauru","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85066,520,"NRU","Nauru","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85067,520,"NRU","Nauru","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85068,520,"NRU","Nauru","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85069,520,"NRU","Nauru","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85070,520,"NRU","Nauru","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85071,520,"NRU","Nauru","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85072,520,"NRU","Nauru","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85073,520,"NRU","Nauru","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85074,520,"NRU","Nauru","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85075,520,"NRU","Nauru","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85076,520,"NRU","Nauru","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85077,520,"NRU","Nauru","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85078,520,"NRU","Nauru","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85079,520,"NRU","Nauru","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85080,520,"NRU","Nauru","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85081,520,"NRU","Nauru","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85082,520,"NRU","Nauru","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85083,520,"NRU","Nauru","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85084,520,"NRU","Nauru","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85085,520,"NRU","Nauru","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85086,520,"NRU","Nauru","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85087,520,"NRU","Nauru","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85088,520,"NRU","Nauru","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85089,520,"NRU","Nauru","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85090,520,"NRU","Nauru","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85091,520,"NRU","Nauru","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85092,520,"NRU","Nauru","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85093,520,"NRU","Nauru","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NRU/nru_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85094,524,"NPL","Nepal","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85095,524,"NPL","Nepal","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85096,524,"NPL","Nepal","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85097,524,"NPL","Nepal","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85098,524,"NPL","Nepal","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85099,524,"NPL","Nepal","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85100,524,"NPL","Nepal","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85101,524,"NPL","Nepal","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85102,524,"NPL","Nepal","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85103,524,"NPL","Nepal","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85104,524,"NPL","Nepal","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85105,524,"NPL","Nepal","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85106,524,"NPL","Nepal","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85107,524,"NPL","Nepal","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85108,524,"NPL","Nepal","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85109,524,"NPL","Nepal","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85110,524,"NPL","Nepal","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85111,524,"NPL","Nepal","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85112,524,"NPL","Nepal","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85113,524,"NPL","Nepal","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85114,524,"NPL","Nepal","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85115,524,"NPL","Nepal","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85116,524,"NPL","Nepal","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85117,524,"NPL","Nepal","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85118,524,"NPL","Nepal","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85119,524,"NPL","Nepal","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85120,524,"NPL","Nepal","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85121,524,"NPL","Nepal","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85122,524,"NPL","Nepal","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85123,524,"NPL","Nepal","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85124,524,"NPL","Nepal","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85125,524,"NPL","Nepal","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85126,524,"NPL","Nepal","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85127,524,"NPL","Nepal","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85128,524,"NPL","Nepal","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85129,524,"NPL","Nepal","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NPL/npl_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85130,528,"NLD","Netherlands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85131,528,"NLD","Netherlands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85132,528,"NLD","Netherlands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85133,528,"NLD","Netherlands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85134,528,"NLD","Netherlands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85135,528,"NLD","Netherlands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85136,528,"NLD","Netherlands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85137,528,"NLD","Netherlands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85138,528,"NLD","Netherlands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85139,528,"NLD","Netherlands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85140,528,"NLD","Netherlands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85141,528,"NLD","Netherlands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85142,528,"NLD","Netherlands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85143,528,"NLD","Netherlands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85144,528,"NLD","Netherlands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85145,528,"NLD","Netherlands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85146,528,"NLD","Netherlands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85147,528,"NLD","Netherlands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85148,528,"NLD","Netherlands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85149,528,"NLD","Netherlands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85150,528,"NLD","Netherlands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85151,528,"NLD","Netherlands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85152,528,"NLD","Netherlands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85153,528,"NLD","Netherlands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85154,528,"NLD","Netherlands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85155,528,"NLD","Netherlands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85156,528,"NLD","Netherlands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85157,528,"NLD","Netherlands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85158,528,"NLD","Netherlands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85159,528,"NLD","Netherlands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85160,528,"NLD","Netherlands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85161,528,"NLD","Netherlands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85162,528,"NLD","Netherlands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85163,528,"NLD","Netherlands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85164,528,"NLD","Netherlands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85165,528,"NLD","Netherlands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NLD/nld_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85166,531,"CUW","Curacao","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85167,531,"CUW","Curacao","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85168,531,"CUW","Curacao","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85169,531,"CUW","Curacao","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85170,531,"CUW","Curacao","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85171,531,"CUW","Curacao","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85172,531,"CUW","Curacao","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85173,531,"CUW","Curacao","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85174,531,"CUW","Curacao","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85175,531,"CUW","Curacao","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85176,531,"CUW","Curacao","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85177,531,"CUW","Curacao","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85178,531,"CUW","Curacao","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85179,531,"CUW","Curacao","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85180,531,"CUW","Curacao","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85181,531,"CUW","Curacao","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85182,531,"CUW","Curacao","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85183,531,"CUW","Curacao","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85184,531,"CUW","Curacao","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85185,531,"CUW","Curacao","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85186,531,"CUW","Curacao","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85187,531,"CUW","Curacao","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85188,531,"CUW","Curacao","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85189,531,"CUW","Curacao","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85190,531,"CUW","Curacao","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85191,531,"CUW","Curacao","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85192,531,"CUW","Curacao","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85193,531,"CUW","Curacao","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85194,531,"CUW","Curacao","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85195,531,"CUW","Curacao","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85196,531,"CUW","Curacao","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85197,531,"CUW","Curacao","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85198,531,"CUW","Curacao","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85199,531,"CUW","Curacao","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85200,531,"CUW","Curacao","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85201,531,"CUW","Curacao","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CUW/cuw_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85202,533,"ABW","Aruba","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85203,533,"ABW","Aruba","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85204,533,"ABW","Aruba","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85205,533,"ABW","Aruba","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85206,533,"ABW","Aruba","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85207,533,"ABW","Aruba","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85208,533,"ABW","Aruba","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85209,533,"ABW","Aruba","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85210,533,"ABW","Aruba","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85211,533,"ABW","Aruba","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85212,533,"ABW","Aruba","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85213,533,"ABW","Aruba","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85214,533,"ABW","Aruba","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85215,533,"ABW","Aruba","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85216,533,"ABW","Aruba","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85217,533,"ABW","Aruba","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85218,533,"ABW","Aruba","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85219,533,"ABW","Aruba","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85220,533,"ABW","Aruba","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85221,533,"ABW","Aruba","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85222,533,"ABW","Aruba","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85223,533,"ABW","Aruba","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85224,533,"ABW","Aruba","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85225,533,"ABW","Aruba","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85226,533,"ABW","Aruba","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85227,533,"ABW","Aruba","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85228,533,"ABW","Aruba","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85229,533,"ABW","Aruba","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85230,533,"ABW","Aruba","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85231,533,"ABW","Aruba","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85232,533,"ABW","Aruba","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85233,533,"ABW","Aruba","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85234,533,"ABW","Aruba","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85235,533,"ABW","Aruba","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85236,533,"ABW","Aruba","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85237,533,"ABW","Aruba","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ABW/abw_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85238,534,"SXM","Sint Maarten (Dutch part)","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85239,534,"SXM","Sint Maarten (Dutch part)","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85240,534,"SXM","Sint Maarten (Dutch part)","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85241,534,"SXM","Sint Maarten (Dutch part)","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85242,534,"SXM","Sint Maarten (Dutch part)","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85243,534,"SXM","Sint Maarten (Dutch part)","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85244,534,"SXM","Sint Maarten (Dutch part)","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85245,534,"SXM","Sint Maarten (Dutch part)","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85246,534,"SXM","Sint Maarten (Dutch part)","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85247,534,"SXM","Sint Maarten (Dutch part)","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85248,534,"SXM","Sint Maarten (Dutch part)","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85249,534,"SXM","Sint Maarten (Dutch part)","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85250,534,"SXM","Sint Maarten (Dutch part)","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85251,534,"SXM","Sint Maarten (Dutch part)","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85252,534,"SXM","Sint Maarten (Dutch part)","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85253,534,"SXM","Sint Maarten (Dutch part)","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85254,534,"SXM","Sint Maarten (Dutch part)","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85255,534,"SXM","Sint Maarten (Dutch part)","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85256,534,"SXM","Sint Maarten (Dutch part)","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85257,534,"SXM","Sint Maarten (Dutch part)","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85258,534,"SXM","Sint Maarten (Dutch part)","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85259,534,"SXM","Sint Maarten (Dutch part)","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85260,534,"SXM","Sint Maarten (Dutch part)","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85261,534,"SXM","Sint Maarten (Dutch part)","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85262,534,"SXM","Sint Maarten (Dutch part)","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85263,534,"SXM","Sint Maarten (Dutch part)","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85264,534,"SXM","Sint Maarten (Dutch part)","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85265,534,"SXM","Sint Maarten (Dutch part)","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85266,534,"SXM","Sint Maarten (Dutch part)","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85267,534,"SXM","Sint Maarten (Dutch part)","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85268,534,"SXM","Sint Maarten (Dutch part)","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85269,534,"SXM","Sint Maarten (Dutch part)","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85270,534,"SXM","Sint Maarten (Dutch part)","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85271,534,"SXM","Sint Maarten (Dutch part)","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85272,534,"SXM","Sint Maarten (Dutch part)","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85273,534,"SXM","Sint Maarten (Dutch part)","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SXM/sxm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85274,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85275,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85276,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85277,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85278,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85279,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85280,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85281,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85282,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85283,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85284,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85285,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85286,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85287,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85288,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85289,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85290,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85291,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85292,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85293,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85294,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85295,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85296,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85297,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85298,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85299,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85300,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85301,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85302,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85303,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85304,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85305,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85306,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85307,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85308,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85309,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BES/bes_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85310,540,"NCL","New Caledonia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85311,540,"NCL","New Caledonia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85312,540,"NCL","New Caledonia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85313,540,"NCL","New Caledonia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85314,540,"NCL","New Caledonia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85315,540,"NCL","New Caledonia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85316,540,"NCL","New Caledonia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85317,540,"NCL","New Caledonia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85318,540,"NCL","New Caledonia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85319,540,"NCL","New Caledonia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85320,540,"NCL","New Caledonia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85321,540,"NCL","New Caledonia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85322,540,"NCL","New Caledonia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85323,540,"NCL","New Caledonia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85324,540,"NCL","New Caledonia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85325,540,"NCL","New Caledonia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85326,540,"NCL","New Caledonia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85327,540,"NCL","New Caledonia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85328,540,"NCL","New Caledonia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85329,540,"NCL","New Caledonia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85330,540,"NCL","New Caledonia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85331,540,"NCL","New Caledonia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85332,540,"NCL","New Caledonia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85333,540,"NCL","New Caledonia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85334,540,"NCL","New Caledonia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85335,540,"NCL","New Caledonia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85336,540,"NCL","New Caledonia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85337,540,"NCL","New Caledonia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85338,540,"NCL","New Caledonia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85339,540,"NCL","New Caledonia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85340,540,"NCL","New Caledonia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85341,540,"NCL","New Caledonia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85342,540,"NCL","New Caledonia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85343,540,"NCL","New Caledonia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85344,540,"NCL","New Caledonia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85345,540,"NCL","New Caledonia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NCL/ncl_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85346,548,"VUT","Vanuatu","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85347,548,"VUT","Vanuatu","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85348,548,"VUT","Vanuatu","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85349,548,"VUT","Vanuatu","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85350,548,"VUT","Vanuatu","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85351,548,"VUT","Vanuatu","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85352,548,"VUT","Vanuatu","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85353,548,"VUT","Vanuatu","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85354,548,"VUT","Vanuatu","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85355,548,"VUT","Vanuatu","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85356,548,"VUT","Vanuatu","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85357,548,"VUT","Vanuatu","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85358,548,"VUT","Vanuatu","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85359,548,"VUT","Vanuatu","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85360,548,"VUT","Vanuatu","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85361,548,"VUT","Vanuatu","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85362,548,"VUT","Vanuatu","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85363,548,"VUT","Vanuatu","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85364,548,"VUT","Vanuatu","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85365,548,"VUT","Vanuatu","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85366,548,"VUT","Vanuatu","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85367,548,"VUT","Vanuatu","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85368,548,"VUT","Vanuatu","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85369,548,"VUT","Vanuatu","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85370,548,"VUT","Vanuatu","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85371,548,"VUT","Vanuatu","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85372,548,"VUT","Vanuatu","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85373,548,"VUT","Vanuatu","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85374,548,"VUT","Vanuatu","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85375,548,"VUT","Vanuatu","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85376,548,"VUT","Vanuatu","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85377,548,"VUT","Vanuatu","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85378,548,"VUT","Vanuatu","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85379,548,"VUT","Vanuatu","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85380,548,"VUT","Vanuatu","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85381,548,"VUT","Vanuatu","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VUT/vut_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85382,554,"NZL","New Zealand","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85383,554,"NZL","New Zealand","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85384,554,"NZL","New Zealand","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85385,554,"NZL","New Zealand","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85386,554,"NZL","New Zealand","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85387,554,"NZL","New Zealand","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85388,554,"NZL","New Zealand","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85389,554,"NZL","New Zealand","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85390,554,"NZL","New Zealand","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85391,554,"NZL","New Zealand","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85392,554,"NZL","New Zealand","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85393,554,"NZL","New Zealand","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85394,554,"NZL","New Zealand","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85395,554,"NZL","New Zealand","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85396,554,"NZL","New Zealand","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85397,554,"NZL","New Zealand","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85398,554,"NZL","New Zealand","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85399,554,"NZL","New Zealand","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85400,554,"NZL","New Zealand","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85401,554,"NZL","New Zealand","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85402,554,"NZL","New Zealand","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85403,554,"NZL","New Zealand","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85404,554,"NZL","New Zealand","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85405,554,"NZL","New Zealand","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85406,554,"NZL","New Zealand","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85407,554,"NZL","New Zealand","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85408,554,"NZL","New Zealand","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85409,554,"NZL","New Zealand","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85410,554,"NZL","New Zealand","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85411,554,"NZL","New Zealand","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85412,554,"NZL","New Zealand","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85413,554,"NZL","New Zealand","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85414,554,"NZL","New Zealand","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85415,554,"NZL","New Zealand","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85416,554,"NZL","New Zealand","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85417,554,"NZL","New Zealand","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NZL/nzl_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85418,558,"NIC","Nicaragua","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85419,558,"NIC","Nicaragua","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85420,558,"NIC","Nicaragua","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85421,558,"NIC","Nicaragua","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85422,558,"NIC","Nicaragua","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85423,558,"NIC","Nicaragua","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85424,558,"NIC","Nicaragua","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85425,558,"NIC","Nicaragua","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85426,558,"NIC","Nicaragua","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85427,558,"NIC","Nicaragua","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85428,558,"NIC","Nicaragua","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85429,558,"NIC","Nicaragua","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85430,558,"NIC","Nicaragua","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85431,558,"NIC","Nicaragua","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85432,558,"NIC","Nicaragua","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85433,558,"NIC","Nicaragua","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85434,558,"NIC","Nicaragua","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85435,558,"NIC","Nicaragua","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85436,558,"NIC","Nicaragua","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85437,558,"NIC","Nicaragua","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85438,558,"NIC","Nicaragua","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85439,558,"NIC","Nicaragua","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85440,558,"NIC","Nicaragua","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85441,558,"NIC","Nicaragua","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85442,558,"NIC","Nicaragua","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85443,558,"NIC","Nicaragua","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85444,558,"NIC","Nicaragua","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85445,558,"NIC","Nicaragua","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85446,558,"NIC","Nicaragua","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85447,558,"NIC","Nicaragua","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85448,558,"NIC","Nicaragua","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85449,558,"NIC","Nicaragua","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85450,558,"NIC","Nicaragua","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85451,558,"NIC","Nicaragua","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85452,558,"NIC","Nicaragua","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85453,558,"NIC","Nicaragua","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIC/nic_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85454,562,"NER","Niger","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85455,562,"NER","Niger","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85456,562,"NER","Niger","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85457,562,"NER","Niger","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85458,562,"NER","Niger","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85459,562,"NER","Niger","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85460,562,"NER","Niger","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85461,562,"NER","Niger","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85462,562,"NER","Niger","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85463,562,"NER","Niger","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85464,562,"NER","Niger","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85465,562,"NER","Niger","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85466,562,"NER","Niger","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85467,562,"NER","Niger","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85468,562,"NER","Niger","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85469,562,"NER","Niger","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85470,562,"NER","Niger","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85471,562,"NER","Niger","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85472,562,"NER","Niger","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85473,562,"NER","Niger","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85474,562,"NER","Niger","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85475,562,"NER","Niger","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85476,562,"NER","Niger","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85477,562,"NER","Niger","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85478,562,"NER","Niger","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85479,562,"NER","Niger","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85480,562,"NER","Niger","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85481,562,"NER","Niger","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85482,562,"NER","Niger","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85483,562,"NER","Niger","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85484,562,"NER","Niger","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85485,562,"NER","Niger","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85486,562,"NER","Niger","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85487,562,"NER","Niger","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85488,562,"NER","Niger","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85489,562,"NER","Niger","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NER/ner_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85490,566,"NGA","Nigeria","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85491,566,"NGA","Nigeria","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85492,566,"NGA","Nigeria","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85493,566,"NGA","Nigeria","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85494,566,"NGA","Nigeria","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85495,566,"NGA","Nigeria","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85496,566,"NGA","Nigeria","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85497,566,"NGA","Nigeria","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85498,566,"NGA","Nigeria","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85499,566,"NGA","Nigeria","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85500,566,"NGA","Nigeria","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85501,566,"NGA","Nigeria","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85502,566,"NGA","Nigeria","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85503,566,"NGA","Nigeria","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85504,566,"NGA","Nigeria","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85505,566,"NGA","Nigeria","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85506,566,"NGA","Nigeria","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85507,566,"NGA","Nigeria","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85508,566,"NGA","Nigeria","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85509,566,"NGA","Nigeria","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85510,566,"NGA","Nigeria","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85511,566,"NGA","Nigeria","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85512,566,"NGA","Nigeria","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85513,566,"NGA","Nigeria","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85514,566,"NGA","Nigeria","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85515,566,"NGA","Nigeria","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85516,566,"NGA","Nigeria","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85517,566,"NGA","Nigeria","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85518,566,"NGA","Nigeria","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85519,566,"NGA","Nigeria","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85520,566,"NGA","Nigeria","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85521,566,"NGA","Nigeria","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85522,566,"NGA","Nigeria","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85523,566,"NGA","Nigeria","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85524,566,"NGA","Nigeria","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85525,566,"NGA","Nigeria","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NGA/nga_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
85526,570,"NIU","Niue","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85527,570,"NIU","Niue","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85528,570,"NIU","Niue","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85529,570,"NIU","Niue","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85530,570,"NIU","Niue","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85531,570,"NIU","Niue","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85532,570,"NIU","Niue","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85533,570,"NIU","Niue","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85534,570,"NIU","Niue","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85535,570,"NIU","Niue","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85536,570,"NIU","Niue","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85537,570,"NIU","Niue","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85538,570,"NIU","Niue","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85539,570,"NIU","Niue","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85540,570,"NIU","Niue","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85541,570,"NIU","Niue","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85542,570,"NIU","Niue","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85543,570,"NIU","Niue","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85544,570,"NIU","Niue","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85545,570,"NIU","Niue","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85546,570,"NIU","Niue","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85547,570,"NIU","Niue","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85548,570,"NIU","Niue","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85549,570,"NIU","Niue","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85550,570,"NIU","Niue","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85551,570,"NIU","Niue","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85552,570,"NIU","Niue","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85553,570,"NIU","Niue","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85554,570,"NIU","Niue","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85555,570,"NIU","Niue","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85556,570,"NIU","Niue","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85557,570,"NIU","Niue","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85558,570,"NIU","Niue","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85559,570,"NIU","Niue","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85560,570,"NIU","Niue","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85561,570,"NIU","Niue","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NIU/niu_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85562,574,"NFK","Norfolk Island","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85563,574,"NFK","Norfolk Island","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85564,574,"NFK","Norfolk Island","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85565,574,"NFK","Norfolk Island","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85566,574,"NFK","Norfolk Island","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85567,574,"NFK","Norfolk Island","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85568,574,"NFK","Norfolk Island","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85569,574,"NFK","Norfolk Island","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85570,574,"NFK","Norfolk Island","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85571,574,"NFK","Norfolk Island","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85572,574,"NFK","Norfolk Island","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85573,574,"NFK","Norfolk Island","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85574,574,"NFK","Norfolk Island","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85575,574,"NFK","Norfolk Island","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85576,574,"NFK","Norfolk Island","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85577,574,"NFK","Norfolk Island","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85578,574,"NFK","Norfolk Island","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85579,574,"NFK","Norfolk Island","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85580,574,"NFK","Norfolk Island","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85581,574,"NFK","Norfolk Island","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85582,574,"NFK","Norfolk Island","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85583,574,"NFK","Norfolk Island","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85584,574,"NFK","Norfolk Island","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85585,574,"NFK","Norfolk Island","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85586,574,"NFK","Norfolk Island","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85587,574,"NFK","Norfolk Island","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85588,574,"NFK","Norfolk Island","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85589,574,"NFK","Norfolk Island","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85590,574,"NFK","Norfolk Island","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85591,574,"NFK","Norfolk Island","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85592,574,"NFK","Norfolk Island","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85593,574,"NFK","Norfolk Island","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85594,574,"NFK","Norfolk Island","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85595,574,"NFK","Norfolk Island","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85596,574,"NFK","Norfolk Island","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85597,574,"NFK","Norfolk Island","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NFK/nfk_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85598,578,"NOR","Norway","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85599,578,"NOR","Norway","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85600,578,"NOR","Norway","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85601,578,"NOR","Norway","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85602,578,"NOR","Norway","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85603,578,"NOR","Norway","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85604,578,"NOR","Norway","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85605,578,"NOR","Norway","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85606,578,"NOR","Norway","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85607,578,"NOR","Norway","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85608,578,"NOR","Norway","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85609,578,"NOR","Norway","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85610,578,"NOR","Norway","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85611,578,"NOR","Norway","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85612,578,"NOR","Norway","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85613,578,"NOR","Norway","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85614,578,"NOR","Norway","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85615,578,"NOR","Norway","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85616,578,"NOR","Norway","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85617,578,"NOR","Norway","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85618,578,"NOR","Norway","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85619,578,"NOR","Norway","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85620,578,"NOR","Norway","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85621,578,"NOR","Norway","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85622,578,"NOR","Norway","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85623,578,"NOR","Norway","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85624,578,"NOR","Norway","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85625,578,"NOR","Norway","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85626,578,"NOR","Norway","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85627,578,"NOR","Norway","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85628,578,"NOR","Norway","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85629,578,"NOR","Norway","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85630,578,"NOR","Norway","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85631,578,"NOR","Norway","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85632,578,"NOR","Norway","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85633,578,"NOR","Norway","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/NOR/nor_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85634,580,"MNP","Northern Mariana Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85635,580,"MNP","Northern Mariana Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85636,580,"MNP","Northern Mariana Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85637,580,"MNP","Northern Mariana Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85638,580,"MNP","Northern Mariana Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85639,580,"MNP","Northern Mariana Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85640,580,"MNP","Northern Mariana Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85641,580,"MNP","Northern Mariana Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85642,580,"MNP","Northern Mariana Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85643,580,"MNP","Northern Mariana Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85644,580,"MNP","Northern Mariana Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85645,580,"MNP","Northern Mariana Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85646,580,"MNP","Northern Mariana Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85647,580,"MNP","Northern Mariana Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85648,580,"MNP","Northern Mariana Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85649,580,"MNP","Northern Mariana Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85650,580,"MNP","Northern Mariana Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85651,580,"MNP","Northern Mariana Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85652,580,"MNP","Northern Mariana Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85653,580,"MNP","Northern Mariana Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85654,580,"MNP","Northern Mariana Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85655,580,"MNP","Northern Mariana Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85656,580,"MNP","Northern Mariana Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85657,580,"MNP","Northern Mariana Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85658,580,"MNP","Northern Mariana Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85659,580,"MNP","Northern Mariana Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85660,580,"MNP","Northern Mariana Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85661,580,"MNP","Northern Mariana Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85662,580,"MNP","Northern Mariana Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85663,580,"MNP","Northern Mariana Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85664,580,"MNP","Northern Mariana Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85665,580,"MNP","Northern Mariana Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85666,580,"MNP","Northern Mariana Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85667,580,"MNP","Northern Mariana Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85668,580,"MNP","Northern Mariana Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85669,580,"MNP","Northern Mariana Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MNP/mnp_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85670,583,"FSM","Micronesia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85671,583,"FSM","Micronesia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85672,583,"FSM","Micronesia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85673,583,"FSM","Micronesia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85674,583,"FSM","Micronesia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85675,583,"FSM","Micronesia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85676,583,"FSM","Micronesia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85677,583,"FSM","Micronesia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85678,583,"FSM","Micronesia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85679,583,"FSM","Micronesia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85680,583,"FSM","Micronesia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85681,583,"FSM","Micronesia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85682,583,"FSM","Micronesia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85683,583,"FSM","Micronesia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85684,583,"FSM","Micronesia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85685,583,"FSM","Micronesia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85686,583,"FSM","Micronesia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85687,583,"FSM","Micronesia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85688,583,"FSM","Micronesia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85689,583,"FSM","Micronesia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85690,583,"FSM","Micronesia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85691,583,"FSM","Micronesia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85692,583,"FSM","Micronesia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85693,583,"FSM","Micronesia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85694,583,"FSM","Micronesia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85695,583,"FSM","Micronesia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85696,583,"FSM","Micronesia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85697,583,"FSM","Micronesia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85698,583,"FSM","Micronesia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85699,583,"FSM","Micronesia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85700,583,"FSM","Micronesia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85701,583,"FSM","Micronesia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85702,583,"FSM","Micronesia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85703,583,"FSM","Micronesia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85704,583,"FSM","Micronesia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85705,583,"FSM","Micronesia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/FSM/fsm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85706,584,"MHL","Marshall Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85707,584,"MHL","Marshall Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85708,584,"MHL","Marshall Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85709,584,"MHL","Marshall Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85710,584,"MHL","Marshall Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85711,584,"MHL","Marshall Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85712,584,"MHL","Marshall Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85713,584,"MHL","Marshall Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85714,584,"MHL","Marshall Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85715,584,"MHL","Marshall Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85716,584,"MHL","Marshall Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85717,584,"MHL","Marshall Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85718,584,"MHL","Marshall Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85719,584,"MHL","Marshall Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85720,584,"MHL","Marshall Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85721,584,"MHL","Marshall Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85722,584,"MHL","Marshall Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85723,584,"MHL","Marshall Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85724,584,"MHL","Marshall Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85725,584,"MHL","Marshall Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85726,584,"MHL","Marshall Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85727,584,"MHL","Marshall Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85728,584,"MHL","Marshall Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85729,584,"MHL","Marshall Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85730,584,"MHL","Marshall Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85731,584,"MHL","Marshall Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85732,584,"MHL","Marshall Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85733,584,"MHL","Marshall Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85734,584,"MHL","Marshall Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85735,584,"MHL","Marshall Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85736,584,"MHL","Marshall Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85737,584,"MHL","Marshall Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85738,584,"MHL","Marshall Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85739,584,"MHL","Marshall Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85740,584,"MHL","Marshall Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85741,584,"MHL","Marshall Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MHL/mhl_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85742,585,"PLW","Palau","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85743,585,"PLW","Palau","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85744,585,"PLW","Palau","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85745,585,"PLW","Palau","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85746,585,"PLW","Palau","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85747,585,"PLW","Palau","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85748,585,"PLW","Palau","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85749,585,"PLW","Palau","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85750,585,"PLW","Palau","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85751,585,"PLW","Palau","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85752,585,"PLW","Palau","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85753,585,"PLW","Palau","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85754,585,"PLW","Palau","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85755,585,"PLW","Palau","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85756,585,"PLW","Palau","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85757,585,"PLW","Palau","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85758,585,"PLW","Palau","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85759,585,"PLW","Palau","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85760,585,"PLW","Palau","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85761,585,"PLW","Palau","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85762,585,"PLW","Palau","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85763,585,"PLW","Palau","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85764,585,"PLW","Palau","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85765,585,"PLW","Palau","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85766,585,"PLW","Palau","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85767,585,"PLW","Palau","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85768,585,"PLW","Palau","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85769,585,"PLW","Palau","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85770,585,"PLW","Palau","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85771,585,"PLW","Palau","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85772,585,"PLW","Palau","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85773,585,"PLW","Palau","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85774,585,"PLW","Palau","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85775,585,"PLW","Palau","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85776,585,"PLW","Palau","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85777,585,"PLW","Palau","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PLW/plw_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85778,586,"PAK","Pakistan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85779,586,"PAK","Pakistan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85780,586,"PAK","Pakistan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85781,586,"PAK","Pakistan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85782,586,"PAK","Pakistan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85783,586,"PAK","Pakistan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85784,586,"PAK","Pakistan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85785,586,"PAK","Pakistan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85786,586,"PAK","Pakistan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85787,586,"PAK","Pakistan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85788,586,"PAK","Pakistan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85789,586,"PAK","Pakistan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85790,586,"PAK","Pakistan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85791,586,"PAK","Pakistan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85792,586,"PAK","Pakistan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85793,586,"PAK","Pakistan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85794,586,"PAK","Pakistan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85795,586,"PAK","Pakistan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85796,586,"PAK","Pakistan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85797,586,"PAK","Pakistan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85798,586,"PAK","Pakistan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85799,586,"PAK","Pakistan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85800,586,"PAK","Pakistan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85801,586,"PAK","Pakistan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85802,586,"PAK","Pakistan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85803,586,"PAK","Pakistan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85804,586,"PAK","Pakistan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85805,586,"PAK","Pakistan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85806,586,"PAK","Pakistan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85807,586,"PAK","Pakistan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85808,586,"PAK","Pakistan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85809,586,"PAK","Pakistan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85810,586,"PAK","Pakistan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85811,586,"PAK","Pakistan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85812,586,"PAK","Pakistan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85813,586,"PAK","Pakistan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAK/pak_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85814,591,"PAN","Panama","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85815,591,"PAN","Panama","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85816,591,"PAN","Panama","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85817,591,"PAN","Panama","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85818,591,"PAN","Panama","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85819,591,"PAN","Panama","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85820,591,"PAN","Panama","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85821,591,"PAN","Panama","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85822,591,"PAN","Panama","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85823,591,"PAN","Panama","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85824,591,"PAN","Panama","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85825,591,"PAN","Panama","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85826,591,"PAN","Panama","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85827,591,"PAN","Panama","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85828,591,"PAN","Panama","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85829,591,"PAN","Panama","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85830,591,"PAN","Panama","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85831,591,"PAN","Panama","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85832,591,"PAN","Panama","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85833,591,"PAN","Panama","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85834,591,"PAN","Panama","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85835,591,"PAN","Panama","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85836,591,"PAN","Panama","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85837,591,"PAN","Panama","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85838,591,"PAN","Panama","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85839,591,"PAN","Panama","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85840,591,"PAN","Panama","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85841,591,"PAN","Panama","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85842,591,"PAN","Panama","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85843,591,"PAN","Panama","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85844,591,"PAN","Panama","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85845,591,"PAN","Panama","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85846,591,"PAN","Panama","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85847,591,"PAN","Panama","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85848,591,"PAN","Panama","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85849,591,"PAN","Panama","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PAN/pan_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85850,598,"PNG","Papua New Guinea","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85851,598,"PNG","Papua New Guinea","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85852,598,"PNG","Papua New Guinea","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85853,598,"PNG","Papua New Guinea","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85854,598,"PNG","Papua New Guinea","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85855,598,"PNG","Papua New Guinea","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85856,598,"PNG","Papua New Guinea","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85857,598,"PNG","Papua New Guinea","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85858,598,"PNG","Papua New Guinea","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85859,598,"PNG","Papua New Guinea","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85860,598,"PNG","Papua New Guinea","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85861,598,"PNG","Papua New Guinea","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85862,598,"PNG","Papua New Guinea","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85863,598,"PNG","Papua New Guinea","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85864,598,"PNG","Papua New Guinea","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85865,598,"PNG","Papua New Guinea","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85866,598,"PNG","Papua New Guinea","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85867,598,"PNG","Papua New Guinea","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85868,598,"PNG","Papua New Guinea","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85869,598,"PNG","Papua New Guinea","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85870,598,"PNG","Papua New Guinea","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85871,598,"PNG","Papua New Guinea","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85872,598,"PNG","Papua New Guinea","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85873,598,"PNG","Papua New Guinea","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85874,598,"PNG","Papua New Guinea","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85875,598,"PNG","Papua New Guinea","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85876,598,"PNG","Papua New Guinea","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85877,598,"PNG","Papua New Guinea","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85878,598,"PNG","Papua New Guinea","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85879,598,"PNG","Papua New Guinea","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85880,598,"PNG","Papua New Guinea","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85881,598,"PNG","Papua New Guinea","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85882,598,"PNG","Papua New Guinea","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85883,598,"PNG","Papua New Guinea","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85884,598,"PNG","Papua New Guinea","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85885,598,"PNG","Papua New Guinea","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PNG/png_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85886,600,"PRY","Paraguay","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85887,600,"PRY","Paraguay","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85888,600,"PRY","Paraguay","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85889,600,"PRY","Paraguay","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85890,600,"PRY","Paraguay","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85891,600,"PRY","Paraguay","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85892,600,"PRY","Paraguay","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85893,600,"PRY","Paraguay","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85894,600,"PRY","Paraguay","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85895,600,"PRY","Paraguay","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85896,600,"PRY","Paraguay","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85897,600,"PRY","Paraguay","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85898,600,"PRY","Paraguay","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85899,600,"PRY","Paraguay","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85900,600,"PRY","Paraguay","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85901,600,"PRY","Paraguay","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85902,600,"PRY","Paraguay","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85903,600,"PRY","Paraguay","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85904,600,"PRY","Paraguay","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85905,600,"PRY","Paraguay","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85906,600,"PRY","Paraguay","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85907,600,"PRY","Paraguay","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85908,600,"PRY","Paraguay","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85909,600,"PRY","Paraguay","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85910,600,"PRY","Paraguay","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85911,600,"PRY","Paraguay","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85912,600,"PRY","Paraguay","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85913,600,"PRY","Paraguay","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85914,600,"PRY","Paraguay","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85915,600,"PRY","Paraguay","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85916,600,"PRY","Paraguay","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85917,600,"PRY","Paraguay","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85918,600,"PRY","Paraguay","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85919,600,"PRY","Paraguay","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85920,600,"PRY","Paraguay","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85921,600,"PRY","Paraguay","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRY/pry_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85922,604,"PER","Peru","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85923,604,"PER","Peru","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85924,604,"PER","Peru","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85925,604,"PER","Peru","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85926,604,"PER","Peru","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85927,604,"PER","Peru","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85928,604,"PER","Peru","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85929,604,"PER","Peru","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85930,604,"PER","Peru","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85931,604,"PER","Peru","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85932,604,"PER","Peru","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85933,604,"PER","Peru","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85934,604,"PER","Peru","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85935,604,"PER","Peru","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85936,604,"PER","Peru","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85937,604,"PER","Peru","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85938,604,"PER","Peru","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85939,604,"PER","Peru","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85940,604,"PER","Peru","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85941,604,"PER","Peru","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85942,604,"PER","Peru","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85943,604,"PER","Peru","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85944,604,"PER","Peru","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85945,604,"PER","Peru","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85946,604,"PER","Peru","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85947,604,"PER","Peru","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85948,604,"PER","Peru","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85949,604,"PER","Peru","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85950,604,"PER","Peru","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85951,604,"PER","Peru","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85952,604,"PER","Peru","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85953,604,"PER","Peru","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85954,604,"PER","Peru","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85955,604,"PER","Peru","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85956,604,"PER","Peru","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85957,604,"PER","Peru","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PER/per_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85958,608,"PHL","Philippines","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85959,608,"PHL","Philippines","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85960,608,"PHL","Philippines","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85961,608,"PHL","Philippines","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85962,608,"PHL","Philippines","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85963,608,"PHL","Philippines","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85964,608,"PHL","Philippines","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85965,608,"PHL","Philippines","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85966,608,"PHL","Philippines","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85967,608,"PHL","Philippines","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85968,608,"PHL","Philippines","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85969,608,"PHL","Philippines","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85970,608,"PHL","Philippines","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85971,608,"PHL","Philippines","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85972,608,"PHL","Philippines","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85973,608,"PHL","Philippines","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85974,608,"PHL","Philippines","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85975,608,"PHL","Philippines","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85976,608,"PHL","Philippines","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85977,608,"PHL","Philippines","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85978,608,"PHL","Philippines","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85979,608,"PHL","Philippines","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85980,608,"PHL","Philippines","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85981,608,"PHL","Philippines","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85982,608,"PHL","Philippines","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85983,608,"PHL","Philippines","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85984,608,"PHL","Philippines","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85985,608,"PHL","Philippines","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85986,608,"PHL","Philippines","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85987,608,"PHL","Philippines","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85988,608,"PHL","Philippines","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85989,608,"PHL","Philippines","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85990,608,"PHL","Philippines","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85991,608,"PHL","Philippines","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85992,608,"PHL","Philippines","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85993,608,"PHL","Philippines","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PHL/phl_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85994,612,"PCN","Pitcairn Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85995,612,"PCN","Pitcairn Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85996,612,"PCN","Pitcairn Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85997,612,"PCN","Pitcairn Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85998,612,"PCN","Pitcairn Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
85999,612,"PCN","Pitcairn Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86000,612,"PCN","Pitcairn Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86001,612,"PCN","Pitcairn Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86002,612,"PCN","Pitcairn Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86003,612,"PCN","Pitcairn Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86004,612,"PCN","Pitcairn Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86005,612,"PCN","Pitcairn Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86006,612,"PCN","Pitcairn Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86007,612,"PCN","Pitcairn Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86008,612,"PCN","Pitcairn Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86009,612,"PCN","Pitcairn Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86010,612,"PCN","Pitcairn Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86011,612,"PCN","Pitcairn Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86012,612,"PCN","Pitcairn Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86013,612,"PCN","Pitcairn Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86014,612,"PCN","Pitcairn Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86015,612,"PCN","Pitcairn Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86016,612,"PCN","Pitcairn Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86017,612,"PCN","Pitcairn Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86018,612,"PCN","Pitcairn Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86019,612,"PCN","Pitcairn Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86020,612,"PCN","Pitcairn Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86021,612,"PCN","Pitcairn Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86022,612,"PCN","Pitcairn Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86023,612,"PCN","Pitcairn Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86024,612,"PCN","Pitcairn Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86025,612,"PCN","Pitcairn Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86026,612,"PCN","Pitcairn Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86027,612,"PCN","Pitcairn Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86028,612,"PCN","Pitcairn Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86029,612,"PCN","Pitcairn Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PCN/pcn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86030,616,"POL","Poland","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86031,616,"POL","Poland","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86032,616,"POL","Poland","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86033,616,"POL","Poland","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86034,616,"POL","Poland","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86035,616,"POL","Poland","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86036,616,"POL","Poland","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86037,616,"POL","Poland","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86038,616,"POL","Poland","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86039,616,"POL","Poland","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86040,616,"POL","Poland","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86041,616,"POL","Poland","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86042,616,"POL","Poland","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86043,616,"POL","Poland","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86044,616,"POL","Poland","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86045,616,"POL","Poland","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86046,616,"POL","Poland","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86047,616,"POL","Poland","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86048,616,"POL","Poland","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86049,616,"POL","Poland","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86050,616,"POL","Poland","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86051,616,"POL","Poland","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86052,616,"POL","Poland","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86053,616,"POL","Poland","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86054,616,"POL","Poland","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86055,616,"POL","Poland","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86056,616,"POL","Poland","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86057,616,"POL","Poland","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86058,616,"POL","Poland","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86059,616,"POL","Poland","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86060,616,"POL","Poland","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86061,616,"POL","Poland","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86062,616,"POL","Poland","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86063,616,"POL","Poland","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86064,616,"POL","Poland","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86065,616,"POL","Poland","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/POL/pol_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86066,620,"PRT","Portugal","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86067,620,"PRT","Portugal","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86068,620,"PRT","Portugal","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86069,620,"PRT","Portugal","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86070,620,"PRT","Portugal","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86071,620,"PRT","Portugal","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86072,620,"PRT","Portugal","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86073,620,"PRT","Portugal","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86074,620,"PRT","Portugal","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86075,620,"PRT","Portugal","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86076,620,"PRT","Portugal","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86077,620,"PRT","Portugal","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86078,620,"PRT","Portugal","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86079,620,"PRT","Portugal","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86080,620,"PRT","Portugal","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86081,620,"PRT","Portugal","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86082,620,"PRT","Portugal","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86083,620,"PRT","Portugal","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86084,620,"PRT","Portugal","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86085,620,"PRT","Portugal","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86086,620,"PRT","Portugal","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86087,620,"PRT","Portugal","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86088,620,"PRT","Portugal","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86089,620,"PRT","Portugal","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86090,620,"PRT","Portugal","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86091,620,"PRT","Portugal","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86092,620,"PRT","Portugal","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86093,620,"PRT","Portugal","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86094,620,"PRT","Portugal","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86095,620,"PRT","Portugal","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86096,620,"PRT","Portugal","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86097,620,"PRT","Portugal","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86098,620,"PRT","Portugal","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86099,620,"PRT","Portugal","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86100,620,"PRT","Portugal","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86101,620,"PRT","Portugal","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRT/prt_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86102,624,"GNB","Guinea-Bissau","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86103,624,"GNB","Guinea-Bissau","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86104,624,"GNB","Guinea-Bissau","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86105,624,"GNB","Guinea-Bissau","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86106,624,"GNB","Guinea-Bissau","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86107,624,"GNB","Guinea-Bissau","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86108,624,"GNB","Guinea-Bissau","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86109,624,"GNB","Guinea-Bissau","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86110,624,"GNB","Guinea-Bissau","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86111,624,"GNB","Guinea-Bissau","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86112,624,"GNB","Guinea-Bissau","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86113,624,"GNB","Guinea-Bissau","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86114,624,"GNB","Guinea-Bissau","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86115,624,"GNB","Guinea-Bissau","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86116,624,"GNB","Guinea-Bissau","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86117,624,"GNB","Guinea-Bissau","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86118,624,"GNB","Guinea-Bissau","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86119,624,"GNB","Guinea-Bissau","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86120,624,"GNB","Guinea-Bissau","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86121,624,"GNB","Guinea-Bissau","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86122,624,"GNB","Guinea-Bissau","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86123,624,"GNB","Guinea-Bissau","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86124,624,"GNB","Guinea-Bissau","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86125,624,"GNB","Guinea-Bissau","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86126,624,"GNB","Guinea-Bissau","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86127,624,"GNB","Guinea-Bissau","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86128,624,"GNB","Guinea-Bissau","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86129,624,"GNB","Guinea-Bissau","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86130,624,"GNB","Guinea-Bissau","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86131,624,"GNB","Guinea-Bissau","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86132,624,"GNB","Guinea-Bissau","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86133,624,"GNB","Guinea-Bissau","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86134,624,"GNB","Guinea-Bissau","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86135,624,"GNB","Guinea-Bissau","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86136,624,"GNB","Guinea-Bissau","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86137,624,"GNB","Guinea-Bissau","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GNB/gnb_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86138,626,"TLS","East Timor","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86139,626,"TLS","East Timor","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86140,626,"TLS","East Timor","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86141,626,"TLS","East Timor","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86142,626,"TLS","East Timor","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86143,626,"TLS","East Timor","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86144,626,"TLS","East Timor","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86145,626,"TLS","East Timor","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86146,626,"TLS","East Timor","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86147,626,"TLS","East Timor","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86148,626,"TLS","East Timor","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86149,626,"TLS","East Timor","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86150,626,"TLS","East Timor","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86151,626,"TLS","East Timor","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86152,626,"TLS","East Timor","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86153,626,"TLS","East Timor","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86154,626,"TLS","East Timor","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86155,626,"TLS","East Timor","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86156,626,"TLS","East Timor","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86157,626,"TLS","East Timor","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86158,626,"TLS","East Timor","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86159,626,"TLS","East Timor","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86160,626,"TLS","East Timor","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86161,626,"TLS","East Timor","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86162,626,"TLS","East Timor","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86163,626,"TLS","East Timor","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86164,626,"TLS","East Timor","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86165,626,"TLS","East Timor","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86166,626,"TLS","East Timor","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86167,626,"TLS","East Timor","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86168,626,"TLS","East Timor","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86169,626,"TLS","East Timor","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86170,626,"TLS","East Timor","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86171,626,"TLS","East Timor","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86172,626,"TLS","East Timor","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86173,626,"TLS","East Timor","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TLS/tls_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86174,630,"PRI","Puerto Rico","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86175,630,"PRI","Puerto Rico","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86176,630,"PRI","Puerto Rico","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86177,630,"PRI","Puerto Rico","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86178,630,"PRI","Puerto Rico","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86179,630,"PRI","Puerto Rico","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86180,630,"PRI","Puerto Rico","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86181,630,"PRI","Puerto Rico","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86182,630,"PRI","Puerto Rico","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86183,630,"PRI","Puerto Rico","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86184,630,"PRI","Puerto Rico","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86185,630,"PRI","Puerto Rico","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86186,630,"PRI","Puerto Rico","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86187,630,"PRI","Puerto Rico","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86188,630,"PRI","Puerto Rico","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86189,630,"PRI","Puerto Rico","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86190,630,"PRI","Puerto Rico","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86191,630,"PRI","Puerto Rico","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86192,630,"PRI","Puerto Rico","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86193,630,"PRI","Puerto Rico","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86194,630,"PRI","Puerto Rico","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86195,630,"PRI","Puerto Rico","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86196,630,"PRI","Puerto Rico","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86197,630,"PRI","Puerto Rico","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86198,630,"PRI","Puerto Rico","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86199,630,"PRI","Puerto Rico","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86200,630,"PRI","Puerto Rico","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86201,630,"PRI","Puerto Rico","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86202,630,"PRI","Puerto Rico","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86203,630,"PRI","Puerto Rico","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86204,630,"PRI","Puerto Rico","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86205,630,"PRI","Puerto Rico","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86206,630,"PRI","Puerto Rico","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86207,630,"PRI","Puerto Rico","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86208,630,"PRI","Puerto Rico","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86209,630,"PRI","Puerto Rico","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/PRI/pri_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86210,634,"QAT","Qatar","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86211,634,"QAT","Qatar","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86212,634,"QAT","Qatar","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86213,634,"QAT","Qatar","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86214,634,"QAT","Qatar","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86215,634,"QAT","Qatar","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86216,634,"QAT","Qatar","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86217,634,"QAT","Qatar","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86218,634,"QAT","Qatar","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86219,634,"QAT","Qatar","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86220,634,"QAT","Qatar","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86221,634,"QAT","Qatar","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86222,634,"QAT","Qatar","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86223,634,"QAT","Qatar","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86224,634,"QAT","Qatar","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86225,634,"QAT","Qatar","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86226,634,"QAT","Qatar","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86227,634,"QAT","Qatar","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86228,634,"QAT","Qatar","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86229,634,"QAT","Qatar","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86230,634,"QAT","Qatar","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86231,634,"QAT","Qatar","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86232,634,"QAT","Qatar","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86233,634,"QAT","Qatar","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86234,634,"QAT","Qatar","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86235,634,"QAT","Qatar","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86236,634,"QAT","Qatar","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86237,634,"QAT","Qatar","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86238,634,"QAT","Qatar","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86239,634,"QAT","Qatar","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86240,634,"QAT","Qatar","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86241,634,"QAT","Qatar","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86242,634,"QAT","Qatar","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86243,634,"QAT","Qatar","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86244,634,"QAT","Qatar","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86245,634,"QAT","Qatar","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/QAT/qat_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86246,638,"REU","Reunion","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86247,638,"REU","Reunion","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86248,638,"REU","Reunion","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86249,638,"REU","Reunion","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86250,638,"REU","Reunion","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86251,638,"REU","Reunion","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86252,638,"REU","Reunion","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86253,638,"REU","Reunion","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86254,638,"REU","Reunion","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86255,638,"REU","Reunion","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86256,638,"REU","Reunion","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86257,638,"REU","Reunion","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86258,638,"REU","Reunion","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86259,638,"REU","Reunion","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86260,638,"REU","Reunion","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86261,638,"REU","Reunion","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86262,638,"REU","Reunion","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86263,638,"REU","Reunion","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86264,638,"REU","Reunion","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86265,638,"REU","Reunion","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86266,638,"REU","Reunion","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86267,638,"REU","Reunion","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86268,638,"REU","Reunion","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86269,638,"REU","Reunion","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86270,638,"REU","Reunion","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86271,638,"REU","Reunion","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86272,638,"REU","Reunion","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86273,638,"REU","Reunion","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86274,638,"REU","Reunion","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86275,638,"REU","Reunion","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86276,638,"REU","Reunion","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86277,638,"REU","Reunion","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86278,638,"REU","Reunion","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86279,638,"REU","Reunion","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86280,638,"REU","Reunion","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86281,638,"REU","Reunion","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/REU/reu_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86282,642,"ROU","Romania","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86283,642,"ROU","Romania","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86284,642,"ROU","Romania","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86285,642,"ROU","Romania","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86286,642,"ROU","Romania","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86287,642,"ROU","Romania","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86288,642,"ROU","Romania","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86289,642,"ROU","Romania","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86290,642,"ROU","Romania","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86291,642,"ROU","Romania","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86292,642,"ROU","Romania","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86293,642,"ROU","Romania","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86294,642,"ROU","Romania","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86295,642,"ROU","Romania","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86296,642,"ROU","Romania","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86297,642,"ROU","Romania","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86298,642,"ROU","Romania","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86299,642,"ROU","Romania","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86300,642,"ROU","Romania","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86301,642,"ROU","Romania","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86302,642,"ROU","Romania","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86303,642,"ROU","Romania","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86304,642,"ROU","Romania","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86305,642,"ROU","Romania","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86306,642,"ROU","Romania","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86307,642,"ROU","Romania","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86308,642,"ROU","Romania","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86309,642,"ROU","Romania","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86310,642,"ROU","Romania","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86311,642,"ROU","Romania","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86312,642,"ROU","Romania","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86313,642,"ROU","Romania","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86314,642,"ROU","Romania","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86315,642,"ROU","Romania","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86316,642,"ROU","Romania","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86317,642,"ROU","Romania","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ROU/rou_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86318,646,"RWA","Rwanda","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86319,646,"RWA","Rwanda","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86320,646,"RWA","Rwanda","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86321,646,"RWA","Rwanda","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86322,646,"RWA","Rwanda","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86323,646,"RWA","Rwanda","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86324,646,"RWA","Rwanda","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86325,646,"RWA","Rwanda","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86326,646,"RWA","Rwanda","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86327,646,"RWA","Rwanda","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86328,646,"RWA","Rwanda","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86329,646,"RWA","Rwanda","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86330,646,"RWA","Rwanda","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86331,646,"RWA","Rwanda","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86332,646,"RWA","Rwanda","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86333,646,"RWA","Rwanda","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86334,646,"RWA","Rwanda","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86335,646,"RWA","Rwanda","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86336,646,"RWA","Rwanda","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86337,646,"RWA","Rwanda","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86338,646,"RWA","Rwanda","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86339,646,"RWA","Rwanda","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86340,646,"RWA","Rwanda","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86341,646,"RWA","Rwanda","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86342,646,"RWA","Rwanda","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86343,646,"RWA","Rwanda","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86344,646,"RWA","Rwanda","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86345,646,"RWA","Rwanda","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86346,646,"RWA","Rwanda","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86347,646,"RWA","Rwanda","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86348,646,"RWA","Rwanda","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86349,646,"RWA","Rwanda","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86350,646,"RWA","Rwanda","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86351,646,"RWA","Rwanda","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86352,646,"RWA","Rwanda","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86353,646,"RWA","Rwanda","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/RWA/rwa_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86354,652,"BLM","Saint Barthelemy","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86355,652,"BLM","Saint Barthelemy","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86356,652,"BLM","Saint Barthelemy","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86357,652,"BLM","Saint Barthelemy","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86358,652,"BLM","Saint Barthelemy","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86359,652,"BLM","Saint Barthelemy","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86360,652,"BLM","Saint Barthelemy","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86361,652,"BLM","Saint Barthelemy","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86362,652,"BLM","Saint Barthelemy","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86363,652,"BLM","Saint Barthelemy","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86364,652,"BLM","Saint Barthelemy","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86365,652,"BLM","Saint Barthelemy","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86366,652,"BLM","Saint Barthelemy","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86367,652,"BLM","Saint Barthelemy","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86368,652,"BLM","Saint Barthelemy","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86369,652,"BLM","Saint Barthelemy","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86370,652,"BLM","Saint Barthelemy","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86371,652,"BLM","Saint Barthelemy","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86372,652,"BLM","Saint Barthelemy","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86373,652,"BLM","Saint Barthelemy","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86374,652,"BLM","Saint Barthelemy","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86375,652,"BLM","Saint Barthelemy","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86376,652,"BLM","Saint Barthelemy","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86377,652,"BLM","Saint Barthelemy","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86378,652,"BLM","Saint Barthelemy","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86379,652,"BLM","Saint Barthelemy","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86380,652,"BLM","Saint Barthelemy","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86381,652,"BLM","Saint Barthelemy","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86382,652,"BLM","Saint Barthelemy","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86383,652,"BLM","Saint Barthelemy","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86384,652,"BLM","Saint Barthelemy","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86385,652,"BLM","Saint Barthelemy","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86386,652,"BLM","Saint Barthelemy","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86387,652,"BLM","Saint Barthelemy","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86388,652,"BLM","Saint Barthelemy","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86389,652,"BLM","Saint Barthelemy","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BLM/blm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86390,654,"SHN","Saint Helena","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86391,654,"SHN","Saint Helena","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86392,654,"SHN","Saint Helena","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86393,654,"SHN","Saint Helena","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86394,654,"SHN","Saint Helena","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86395,654,"SHN","Saint Helena","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86396,654,"SHN","Saint Helena","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86397,654,"SHN","Saint Helena","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86398,654,"SHN","Saint Helena","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86399,654,"SHN","Saint Helena","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86400,654,"SHN","Saint Helena","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86401,654,"SHN","Saint Helena","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86402,654,"SHN","Saint Helena","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86403,654,"SHN","Saint Helena","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86404,654,"SHN","Saint Helena","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86405,654,"SHN","Saint Helena","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86406,654,"SHN","Saint Helena","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86407,654,"SHN","Saint Helena","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86408,654,"SHN","Saint Helena","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86409,654,"SHN","Saint Helena","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86410,654,"SHN","Saint Helena","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86411,654,"SHN","Saint Helena","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86412,654,"SHN","Saint Helena","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86413,654,"SHN","Saint Helena","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86414,654,"SHN","Saint Helena","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86415,654,"SHN","Saint Helena","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86416,654,"SHN","Saint Helena","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86417,654,"SHN","Saint Helena","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86418,654,"SHN","Saint Helena","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86419,654,"SHN","Saint Helena","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86420,654,"SHN","Saint Helena","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86421,654,"SHN","Saint Helena","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86422,654,"SHN","Saint Helena","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86423,654,"SHN","Saint Helena","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86424,654,"SHN","Saint Helena","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86425,654,"SHN","Saint Helena","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SHN/shn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86426,659,"KNA","Saint Kitts and Nevis","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86427,659,"KNA","Saint Kitts and Nevis","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86428,659,"KNA","Saint Kitts and Nevis","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86429,659,"KNA","Saint Kitts and Nevis","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86430,659,"KNA","Saint Kitts and Nevis","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86431,659,"KNA","Saint Kitts and Nevis","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86432,659,"KNA","Saint Kitts and Nevis","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86433,659,"KNA","Saint Kitts and Nevis","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86434,659,"KNA","Saint Kitts and Nevis","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86435,659,"KNA","Saint Kitts and Nevis","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86436,659,"KNA","Saint Kitts and Nevis","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86437,659,"KNA","Saint Kitts and Nevis","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86438,659,"KNA","Saint Kitts and Nevis","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86439,659,"KNA","Saint Kitts and Nevis","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86440,659,"KNA","Saint Kitts and Nevis","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86441,659,"KNA","Saint Kitts and Nevis","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86442,659,"KNA","Saint Kitts and Nevis","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86443,659,"KNA","Saint Kitts and Nevis","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86444,659,"KNA","Saint Kitts and Nevis","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86445,659,"KNA","Saint Kitts and Nevis","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86446,659,"KNA","Saint Kitts and Nevis","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86447,659,"KNA","Saint Kitts and Nevis","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86448,659,"KNA","Saint Kitts and Nevis","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86449,659,"KNA","Saint Kitts and Nevis","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86450,659,"KNA","Saint Kitts and Nevis","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86451,659,"KNA","Saint Kitts and Nevis","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86452,659,"KNA","Saint Kitts and Nevis","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86453,659,"KNA","Saint Kitts and Nevis","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86454,659,"KNA","Saint Kitts and Nevis","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86455,659,"KNA","Saint Kitts and Nevis","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86456,659,"KNA","Saint Kitts and Nevis","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86457,659,"KNA","Saint Kitts and Nevis","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86458,659,"KNA","Saint Kitts and Nevis","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86459,659,"KNA","Saint Kitts and Nevis","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86460,659,"KNA","Saint Kitts and Nevis","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86461,659,"KNA","Saint Kitts and Nevis","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KNA/kna_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86462,660,"AIA","Anguilla","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86463,660,"AIA","Anguilla","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86464,660,"AIA","Anguilla","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86465,660,"AIA","Anguilla","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86466,660,"AIA","Anguilla","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86467,660,"AIA","Anguilla","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86468,660,"AIA","Anguilla","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86469,660,"AIA","Anguilla","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86470,660,"AIA","Anguilla","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86471,660,"AIA","Anguilla","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86472,660,"AIA","Anguilla","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86473,660,"AIA","Anguilla","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86474,660,"AIA","Anguilla","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86475,660,"AIA","Anguilla","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86476,660,"AIA","Anguilla","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86477,660,"AIA","Anguilla","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86478,660,"AIA","Anguilla","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86479,660,"AIA","Anguilla","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86480,660,"AIA","Anguilla","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86481,660,"AIA","Anguilla","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86482,660,"AIA","Anguilla","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86483,660,"AIA","Anguilla","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86484,660,"AIA","Anguilla","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86485,660,"AIA","Anguilla","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86486,660,"AIA","Anguilla","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86487,660,"AIA","Anguilla","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86488,660,"AIA","Anguilla","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86489,660,"AIA","Anguilla","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86490,660,"AIA","Anguilla","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86491,660,"AIA","Anguilla","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86492,660,"AIA","Anguilla","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86493,660,"AIA","Anguilla","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86494,660,"AIA","Anguilla","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86495,660,"AIA","Anguilla","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86496,660,"AIA","Anguilla","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86497,660,"AIA","Anguilla","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/AIA/aia_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86498,662,"LCA","Saint Lucia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86499,662,"LCA","Saint Lucia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86500,662,"LCA","Saint Lucia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86501,662,"LCA","Saint Lucia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86502,662,"LCA","Saint Lucia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86503,662,"LCA","Saint Lucia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86504,662,"LCA","Saint Lucia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86505,662,"LCA","Saint Lucia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86506,662,"LCA","Saint Lucia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86507,662,"LCA","Saint Lucia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86508,662,"LCA","Saint Lucia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86509,662,"LCA","Saint Lucia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86510,662,"LCA","Saint Lucia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86511,662,"LCA","Saint Lucia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86512,662,"LCA","Saint Lucia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86513,662,"LCA","Saint Lucia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86514,662,"LCA","Saint Lucia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86515,662,"LCA","Saint Lucia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86516,662,"LCA","Saint Lucia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86517,662,"LCA","Saint Lucia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86518,662,"LCA","Saint Lucia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86519,662,"LCA","Saint Lucia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86520,662,"LCA","Saint Lucia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86521,662,"LCA","Saint Lucia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86522,662,"LCA","Saint Lucia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86523,662,"LCA","Saint Lucia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86524,662,"LCA","Saint Lucia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86525,662,"LCA","Saint Lucia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86526,662,"LCA","Saint Lucia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86527,662,"LCA","Saint Lucia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86528,662,"LCA","Saint Lucia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86529,662,"LCA","Saint Lucia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86530,662,"LCA","Saint Lucia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86531,662,"LCA","Saint Lucia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86532,662,"LCA","Saint Lucia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86533,662,"LCA","Saint Lucia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/LCA/lca_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86534,663,"MAF","Saint Martin (French part)","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86535,663,"MAF","Saint Martin (French part)","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86536,663,"MAF","Saint Martin (French part)","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86537,663,"MAF","Saint Martin (French part)","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86538,663,"MAF","Saint Martin (French part)","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86539,663,"MAF","Saint Martin (French part)","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86540,663,"MAF","Saint Martin (French part)","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86541,663,"MAF","Saint Martin (French part)","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86542,663,"MAF","Saint Martin (French part)","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86543,663,"MAF","Saint Martin (French part)","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86544,663,"MAF","Saint Martin (French part)","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86545,663,"MAF","Saint Martin (French part)","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86546,663,"MAF","Saint Martin (French part)","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86547,663,"MAF","Saint Martin (French part)","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86548,663,"MAF","Saint Martin (French part)","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86549,663,"MAF","Saint Martin (French part)","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86550,663,"MAF","Saint Martin (French part)","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86551,663,"MAF","Saint Martin (French part)","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86552,663,"MAF","Saint Martin (French part)","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86553,663,"MAF","Saint Martin (French part)","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86554,663,"MAF","Saint Martin (French part)","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86555,663,"MAF","Saint Martin (French part)","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86556,663,"MAF","Saint Martin (French part)","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86557,663,"MAF","Saint Martin (French part)","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86558,663,"MAF","Saint Martin (French part)","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86559,663,"MAF","Saint Martin (French part)","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86560,663,"MAF","Saint Martin (French part)","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86561,663,"MAF","Saint Martin (French part)","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86562,663,"MAF","Saint Martin (French part)","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86563,663,"MAF","Saint Martin (French part)","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86564,663,"MAF","Saint Martin (French part)","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86565,663,"MAF","Saint Martin (French part)","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86566,663,"MAF","Saint Martin (French part)","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86567,663,"MAF","Saint Martin (French part)","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86568,663,"MAF","Saint Martin (French part)","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86569,663,"MAF","Saint Martin (French part)","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MAF/maf_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86570,666,"SPM","Saint Pierre and Miquelon","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86571,666,"SPM","Saint Pierre and Miquelon","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86572,666,"SPM","Saint Pierre and Miquelon","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86573,666,"SPM","Saint Pierre and Miquelon","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86574,666,"SPM","Saint Pierre and Miquelon","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86575,666,"SPM","Saint Pierre and Miquelon","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86576,666,"SPM","Saint Pierre and Miquelon","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86577,666,"SPM","Saint Pierre and Miquelon","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86578,666,"SPM","Saint Pierre and Miquelon","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86579,666,"SPM","Saint Pierre and Miquelon","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86580,666,"SPM","Saint Pierre and Miquelon","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86581,666,"SPM","Saint Pierre and Miquelon","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86582,666,"SPM","Saint Pierre and Miquelon","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86583,666,"SPM","Saint Pierre and Miquelon","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86584,666,"SPM","Saint Pierre and Miquelon","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86585,666,"SPM","Saint Pierre and Miquelon","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86586,666,"SPM","Saint Pierre and Miquelon","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86587,666,"SPM","Saint Pierre and Miquelon","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86588,666,"SPM","Saint Pierre and Miquelon","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86589,666,"SPM","Saint Pierre and Miquelon","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86590,666,"SPM","Saint Pierre and Miquelon","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86591,666,"SPM","Saint Pierre and Miquelon","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86592,666,"SPM","Saint Pierre and Miquelon","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86593,666,"SPM","Saint Pierre and Miquelon","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86594,666,"SPM","Saint Pierre and Miquelon","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86595,666,"SPM","Saint Pierre and Miquelon","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86596,666,"SPM","Saint Pierre and Miquelon","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86597,666,"SPM","Saint Pierre and Miquelon","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86598,666,"SPM","Saint Pierre and Miquelon","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86599,666,"SPM","Saint Pierre and Miquelon","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86600,666,"SPM","Saint Pierre and Miquelon","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86601,666,"SPM","Saint Pierre and Miquelon","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86602,666,"SPM","Saint Pierre and Miquelon","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86603,666,"SPM","Saint Pierre and Miquelon","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86604,666,"SPM","Saint Pierre and Miquelon","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86605,666,"SPM","Saint Pierre and Miquelon","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SPM/spm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86606,670,"VCT","Saint Vincent and the Grenadines","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86607,670,"VCT","Saint Vincent and the Grenadines","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86608,670,"VCT","Saint Vincent and the Grenadines","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86609,670,"VCT","Saint Vincent and the Grenadines","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86610,670,"VCT","Saint Vincent and the Grenadines","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86611,670,"VCT","Saint Vincent and the Grenadines","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86612,670,"VCT","Saint Vincent and the Grenadines","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86613,670,"VCT","Saint Vincent and the Grenadines","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86614,670,"VCT","Saint Vincent and the Grenadines","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86615,670,"VCT","Saint Vincent and the Grenadines","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86616,670,"VCT","Saint Vincent and the Grenadines","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86617,670,"VCT","Saint Vincent and the Grenadines","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86618,670,"VCT","Saint Vincent and the Grenadines","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86619,670,"VCT","Saint Vincent and the Grenadines","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86620,670,"VCT","Saint Vincent and the Grenadines","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86621,670,"VCT","Saint Vincent and the Grenadines","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86622,670,"VCT","Saint Vincent and the Grenadines","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86623,670,"VCT","Saint Vincent and the Grenadines","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86624,670,"VCT","Saint Vincent and the Grenadines","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86625,670,"VCT","Saint Vincent and the Grenadines","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86626,670,"VCT","Saint Vincent and the Grenadines","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86627,670,"VCT","Saint Vincent and the Grenadines","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86628,670,"VCT","Saint Vincent and the Grenadines","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86629,670,"VCT","Saint Vincent and the Grenadines","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86630,670,"VCT","Saint Vincent and the Grenadines","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86631,670,"VCT","Saint Vincent and the Grenadines","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86632,670,"VCT","Saint Vincent and the Grenadines","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86633,670,"VCT","Saint Vincent and the Grenadines","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86634,670,"VCT","Saint Vincent and the Grenadines","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86635,670,"VCT","Saint Vincent and the Grenadines","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86636,670,"VCT","Saint Vincent and the Grenadines","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86637,670,"VCT","Saint Vincent and the Grenadines","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86638,670,"VCT","Saint Vincent and the Grenadines","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86639,670,"VCT","Saint Vincent and the Grenadines","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86640,670,"VCT","Saint Vincent and the Grenadines","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86641,670,"VCT","Saint Vincent and the Grenadines","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VCT/vct_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86642,674,"SMR","San Marino","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86643,674,"SMR","San Marino","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86644,674,"SMR","San Marino","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86645,674,"SMR","San Marino","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86646,674,"SMR","San Marino","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86647,674,"SMR","San Marino","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86648,674,"SMR","San Marino","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86649,674,"SMR","San Marino","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86650,674,"SMR","San Marino","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86651,674,"SMR","San Marino","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86652,674,"SMR","San Marino","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86653,674,"SMR","San Marino","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86654,674,"SMR","San Marino","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86655,674,"SMR","San Marino","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86656,674,"SMR","San Marino","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86657,674,"SMR","San Marino","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86658,674,"SMR","San Marino","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86659,674,"SMR","San Marino","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86660,674,"SMR","San Marino","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86661,674,"SMR","San Marino","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86662,674,"SMR","San Marino","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86663,674,"SMR","San Marino","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86664,674,"SMR","San Marino","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86665,674,"SMR","San Marino","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86666,674,"SMR","San Marino","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86667,674,"SMR","San Marino","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86668,674,"SMR","San Marino","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86669,674,"SMR","San Marino","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86670,674,"SMR","San Marino","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86671,674,"SMR","San Marino","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86672,674,"SMR","San Marino","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86673,674,"SMR","San Marino","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86674,674,"SMR","San Marino","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86675,674,"SMR","San Marino","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86676,674,"SMR","San Marino","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86677,674,"SMR","San Marino","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SMR/smr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86678,678,"STP","Sao Tome and Principe","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86679,678,"STP","Sao Tome and Principe","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86680,678,"STP","Sao Tome and Principe","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86681,678,"STP","Sao Tome and Principe","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86682,678,"STP","Sao Tome and Principe","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86683,678,"STP","Sao Tome and Principe","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86684,678,"STP","Sao Tome and Principe","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86685,678,"STP","Sao Tome and Principe","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86686,678,"STP","Sao Tome and Principe","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86687,678,"STP","Sao Tome and Principe","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86688,678,"STP","Sao Tome and Principe","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86689,678,"STP","Sao Tome and Principe","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86690,678,"STP","Sao Tome and Principe","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86691,678,"STP","Sao Tome and Principe","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86692,678,"STP","Sao Tome and Principe","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86693,678,"STP","Sao Tome and Principe","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86694,678,"STP","Sao Tome and Principe","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86695,678,"STP","Sao Tome and Principe","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86696,678,"STP","Sao Tome and Principe","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86697,678,"STP","Sao Tome and Principe","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86698,678,"STP","Sao Tome and Principe","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86699,678,"STP","Sao Tome and Principe","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86700,678,"STP","Sao Tome and Principe","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86701,678,"STP","Sao Tome and Principe","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86702,678,"STP","Sao Tome and Principe","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86703,678,"STP","Sao Tome and Principe","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86704,678,"STP","Sao Tome and Principe","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86705,678,"STP","Sao Tome and Principe","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86706,678,"STP","Sao Tome and Principe","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86707,678,"STP","Sao Tome and Principe","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86708,678,"STP","Sao Tome and Principe","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86709,678,"STP","Sao Tome and Principe","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86710,678,"STP","Sao Tome and Principe","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86711,678,"STP","Sao Tome and Principe","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86712,678,"STP","Sao Tome and Principe","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86713,678,"STP","Sao Tome and Principe","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/STP/stp_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86714,682,"SAU","Saudi Arabia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86715,682,"SAU","Saudi Arabia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86716,682,"SAU","Saudi Arabia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86717,682,"SAU","Saudi Arabia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86718,682,"SAU","Saudi Arabia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86719,682,"SAU","Saudi Arabia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86720,682,"SAU","Saudi Arabia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86721,682,"SAU","Saudi Arabia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86722,682,"SAU","Saudi Arabia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86723,682,"SAU","Saudi Arabia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86724,682,"SAU","Saudi Arabia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86725,682,"SAU","Saudi Arabia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86726,682,"SAU","Saudi Arabia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86727,682,"SAU","Saudi Arabia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86728,682,"SAU","Saudi Arabia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86729,682,"SAU","Saudi Arabia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86730,682,"SAU","Saudi Arabia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86731,682,"SAU","Saudi Arabia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86732,682,"SAU","Saudi Arabia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86733,682,"SAU","Saudi Arabia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86734,682,"SAU","Saudi Arabia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86735,682,"SAU","Saudi Arabia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86736,682,"SAU","Saudi Arabia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86737,682,"SAU","Saudi Arabia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86738,682,"SAU","Saudi Arabia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86739,682,"SAU","Saudi Arabia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86740,682,"SAU","Saudi Arabia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86741,682,"SAU","Saudi Arabia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86742,682,"SAU","Saudi Arabia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86743,682,"SAU","Saudi Arabia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86744,682,"SAU","Saudi Arabia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86745,682,"SAU","Saudi Arabia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86746,682,"SAU","Saudi Arabia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86747,682,"SAU","Saudi Arabia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86748,682,"SAU","Saudi Arabia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86749,682,"SAU","Saudi Arabia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SAU/sau_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86750,686,"SEN","Senegal","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86751,686,"SEN","Senegal","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86752,686,"SEN","Senegal","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86753,686,"SEN","Senegal","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86754,686,"SEN","Senegal","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86755,686,"SEN","Senegal","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86756,686,"SEN","Senegal","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86757,686,"SEN","Senegal","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86758,686,"SEN","Senegal","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86759,686,"SEN","Senegal","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86760,686,"SEN","Senegal","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86761,686,"SEN","Senegal","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86762,686,"SEN","Senegal","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86763,686,"SEN","Senegal","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86764,686,"SEN","Senegal","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86765,686,"SEN","Senegal","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86766,686,"SEN","Senegal","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86767,686,"SEN","Senegal","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86768,686,"SEN","Senegal","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86769,686,"SEN","Senegal","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86770,686,"SEN","Senegal","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86771,686,"SEN","Senegal","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86772,686,"SEN","Senegal","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86773,686,"SEN","Senegal","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86774,686,"SEN","Senegal","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86775,686,"SEN","Senegal","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86776,686,"SEN","Senegal","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86777,686,"SEN","Senegal","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86778,686,"SEN","Senegal","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86779,686,"SEN","Senegal","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86780,686,"SEN","Senegal","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86781,686,"SEN","Senegal","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86782,686,"SEN","Senegal","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86783,686,"SEN","Senegal","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86784,686,"SEN","Senegal","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86785,686,"SEN","Senegal","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SEN/sen_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86786,688,"SRB","Serbia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86787,688,"SRB","Serbia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86788,688,"SRB","Serbia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86789,688,"SRB","Serbia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86790,688,"SRB","Serbia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86791,688,"SRB","Serbia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86792,688,"SRB","Serbia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86793,688,"SRB","Serbia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86794,688,"SRB","Serbia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86795,688,"SRB","Serbia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86796,688,"SRB","Serbia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86797,688,"SRB","Serbia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86798,688,"SRB","Serbia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86799,688,"SRB","Serbia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86800,688,"SRB","Serbia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86801,688,"SRB","Serbia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86802,688,"SRB","Serbia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86803,688,"SRB","Serbia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86804,688,"SRB","Serbia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86805,688,"SRB","Serbia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86806,688,"SRB","Serbia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86807,688,"SRB","Serbia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86808,688,"SRB","Serbia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86809,688,"SRB","Serbia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86810,688,"SRB","Serbia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86811,688,"SRB","Serbia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86812,688,"SRB","Serbia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86813,688,"SRB","Serbia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86814,688,"SRB","Serbia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86815,688,"SRB","Serbia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86816,688,"SRB","Serbia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86817,688,"SRB","Serbia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86818,688,"SRB","Serbia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86819,688,"SRB","Serbia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86820,688,"SRB","Serbia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86821,688,"SRB","Serbia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SRB/srb_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86822,690,"SYC","Seychelles","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86823,690,"SYC","Seychelles","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86824,690,"SYC","Seychelles","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86825,690,"SYC","Seychelles","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86826,690,"SYC","Seychelles","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86827,690,"SYC","Seychelles","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86828,690,"SYC","Seychelles","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86829,690,"SYC","Seychelles","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86830,690,"SYC","Seychelles","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86831,690,"SYC","Seychelles","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86832,690,"SYC","Seychelles","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86833,690,"SYC","Seychelles","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86834,690,"SYC","Seychelles","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86835,690,"SYC","Seychelles","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86836,690,"SYC","Seychelles","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86837,690,"SYC","Seychelles","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86838,690,"SYC","Seychelles","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86839,690,"SYC","Seychelles","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86840,690,"SYC","Seychelles","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86841,690,"SYC","Seychelles","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86842,690,"SYC","Seychelles","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86843,690,"SYC","Seychelles","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86844,690,"SYC","Seychelles","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86845,690,"SYC","Seychelles","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86846,690,"SYC","Seychelles","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86847,690,"SYC","Seychelles","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86848,690,"SYC","Seychelles","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86849,690,"SYC","Seychelles","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86850,690,"SYC","Seychelles","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86851,690,"SYC","Seychelles","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86852,690,"SYC","Seychelles","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86853,690,"SYC","Seychelles","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86854,690,"SYC","Seychelles","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86855,690,"SYC","Seychelles","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86856,690,"SYC","Seychelles","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86857,690,"SYC","Seychelles","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYC/syc_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86858,694,"SLE","Sierra Leone","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86859,694,"SLE","Sierra Leone","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86860,694,"SLE","Sierra Leone","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86861,694,"SLE","Sierra Leone","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86862,694,"SLE","Sierra Leone","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86863,694,"SLE","Sierra Leone","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86864,694,"SLE","Sierra Leone","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86865,694,"SLE","Sierra Leone","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86866,694,"SLE","Sierra Leone","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86867,694,"SLE","Sierra Leone","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86868,694,"SLE","Sierra Leone","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86869,694,"SLE","Sierra Leone","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86870,694,"SLE","Sierra Leone","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86871,694,"SLE","Sierra Leone","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86872,694,"SLE","Sierra Leone","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86873,694,"SLE","Sierra Leone","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86874,694,"SLE","Sierra Leone","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86875,694,"SLE","Sierra Leone","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86876,694,"SLE","Sierra Leone","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86877,694,"SLE","Sierra Leone","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86878,694,"SLE","Sierra Leone","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86879,694,"SLE","Sierra Leone","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86880,694,"SLE","Sierra Leone","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86881,694,"SLE","Sierra Leone","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86882,694,"SLE","Sierra Leone","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86883,694,"SLE","Sierra Leone","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86884,694,"SLE","Sierra Leone","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86885,694,"SLE","Sierra Leone","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86886,694,"SLE","Sierra Leone","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86887,694,"SLE","Sierra Leone","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86888,694,"SLE","Sierra Leone","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86889,694,"SLE","Sierra Leone","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86890,694,"SLE","Sierra Leone","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86891,694,"SLE","Sierra Leone","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86892,694,"SLE","Sierra Leone","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86893,694,"SLE","Sierra Leone","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SLE/sle_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
86894,702,"SGP","Singapore","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86895,702,"SGP","Singapore","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86896,702,"SGP","Singapore","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86897,702,"SGP","Singapore","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86898,702,"SGP","Singapore","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86899,702,"SGP","Singapore","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86900,702,"SGP","Singapore","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86901,702,"SGP","Singapore","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86902,702,"SGP","Singapore","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86903,702,"SGP","Singapore","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86904,702,"SGP","Singapore","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86905,702,"SGP","Singapore","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86906,702,"SGP","Singapore","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86907,702,"SGP","Singapore","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86908,702,"SGP","Singapore","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86909,702,"SGP","Singapore","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86910,702,"SGP","Singapore","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86911,702,"SGP","Singapore","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86912,702,"SGP","Singapore","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86913,702,"SGP","Singapore","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86914,702,"SGP","Singapore","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86915,702,"SGP","Singapore","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86916,702,"SGP","Singapore","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86917,702,"SGP","Singapore","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86918,702,"SGP","Singapore","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86919,702,"SGP","Singapore","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86920,702,"SGP","Singapore","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86921,702,"SGP","Singapore","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86922,702,"SGP","Singapore","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86923,702,"SGP","Singapore","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86924,702,"SGP","Singapore","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86925,702,"SGP","Singapore","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86926,702,"SGP","Singapore","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86927,702,"SGP","Singapore","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86928,702,"SGP","Singapore","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86929,702,"SGP","Singapore","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SGP/sgp_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86930,703,"SVK","Slovakia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86931,703,"SVK","Slovakia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86932,703,"SVK","Slovakia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86933,703,"SVK","Slovakia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86934,703,"SVK","Slovakia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86935,703,"SVK","Slovakia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86936,703,"SVK","Slovakia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86937,703,"SVK","Slovakia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86938,703,"SVK","Slovakia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86939,703,"SVK","Slovakia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86940,703,"SVK","Slovakia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86941,703,"SVK","Slovakia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86942,703,"SVK","Slovakia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86943,703,"SVK","Slovakia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86944,703,"SVK","Slovakia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86945,703,"SVK","Slovakia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86946,703,"SVK","Slovakia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86947,703,"SVK","Slovakia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86948,703,"SVK","Slovakia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86949,703,"SVK","Slovakia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86950,703,"SVK","Slovakia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86951,703,"SVK","Slovakia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86952,703,"SVK","Slovakia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86953,703,"SVK","Slovakia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86954,703,"SVK","Slovakia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86955,703,"SVK","Slovakia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86956,703,"SVK","Slovakia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86957,703,"SVK","Slovakia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86958,703,"SVK","Slovakia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86959,703,"SVK","Slovakia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86960,703,"SVK","Slovakia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86961,703,"SVK","Slovakia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86962,703,"SVK","Slovakia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86963,703,"SVK","Slovakia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86964,703,"SVK","Slovakia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86965,703,"SVK","Slovakia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVK/svk_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86966,704,"VNM","Vietnam","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86967,704,"VNM","Vietnam","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86968,704,"VNM","Vietnam","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86969,704,"VNM","Vietnam","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86970,704,"VNM","Vietnam","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86971,704,"VNM","Vietnam","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86972,704,"VNM","Vietnam","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86973,704,"VNM","Vietnam","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86974,704,"VNM","Vietnam","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86975,704,"VNM","Vietnam","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86976,704,"VNM","Vietnam","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86977,704,"VNM","Vietnam","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86978,704,"VNM","Vietnam","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86979,704,"VNM","Vietnam","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86980,704,"VNM","Vietnam","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86981,704,"VNM","Vietnam","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86982,704,"VNM","Vietnam","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86983,704,"VNM","Vietnam","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86984,704,"VNM","Vietnam","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86985,704,"VNM","Vietnam","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86986,704,"VNM","Vietnam","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86987,704,"VNM","Vietnam","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86988,704,"VNM","Vietnam","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86989,704,"VNM","Vietnam","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86990,704,"VNM","Vietnam","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86991,704,"VNM","Vietnam","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86992,704,"VNM","Vietnam","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86993,704,"VNM","Vietnam","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86994,704,"VNM","Vietnam","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86995,704,"VNM","Vietnam","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86996,704,"VNM","Vietnam","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86997,704,"VNM","Vietnam","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86998,704,"VNM","Vietnam","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
86999,704,"VNM","Vietnam","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87000,704,"VNM","Vietnam","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87001,704,"VNM","Vietnam","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VNM/vnm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87002,705,"SVN","Slovenia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87003,705,"SVN","Slovenia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87004,705,"SVN","Slovenia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87005,705,"SVN","Slovenia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87006,705,"SVN","Slovenia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87007,705,"SVN","Slovenia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87008,705,"SVN","Slovenia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87009,705,"SVN","Slovenia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87010,705,"SVN","Slovenia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87011,705,"SVN","Slovenia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87012,705,"SVN","Slovenia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87013,705,"SVN","Slovenia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87014,705,"SVN","Slovenia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87015,705,"SVN","Slovenia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87016,705,"SVN","Slovenia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87017,705,"SVN","Slovenia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87018,705,"SVN","Slovenia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87019,705,"SVN","Slovenia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87020,705,"SVN","Slovenia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87021,705,"SVN","Slovenia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87022,705,"SVN","Slovenia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87023,705,"SVN","Slovenia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87024,705,"SVN","Slovenia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87025,705,"SVN","Slovenia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87026,705,"SVN","Slovenia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87027,705,"SVN","Slovenia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87028,705,"SVN","Slovenia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87029,705,"SVN","Slovenia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87030,705,"SVN","Slovenia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87031,705,"SVN","Slovenia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87032,705,"SVN","Slovenia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87033,705,"SVN","Slovenia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87034,705,"SVN","Slovenia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87035,705,"SVN","Slovenia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87036,705,"SVN","Slovenia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87037,705,"SVN","Slovenia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SVN/svn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87038,706,"SOM","Somalia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87039,706,"SOM","Somalia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87040,706,"SOM","Somalia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87041,706,"SOM","Somalia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87042,706,"SOM","Somalia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87043,706,"SOM","Somalia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87044,706,"SOM","Somalia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87045,706,"SOM","Somalia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87046,706,"SOM","Somalia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87047,706,"SOM","Somalia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87048,706,"SOM","Somalia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87049,706,"SOM","Somalia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87050,706,"SOM","Somalia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87051,706,"SOM","Somalia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87052,706,"SOM","Somalia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87053,706,"SOM","Somalia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87054,706,"SOM","Somalia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87055,706,"SOM","Somalia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87056,706,"SOM","Somalia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87057,706,"SOM","Somalia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87058,706,"SOM","Somalia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87059,706,"SOM","Somalia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87060,706,"SOM","Somalia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87061,706,"SOM","Somalia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87062,706,"SOM","Somalia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87063,706,"SOM","Somalia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87064,706,"SOM","Somalia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87065,706,"SOM","Somalia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87066,706,"SOM","Somalia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87067,706,"SOM","Somalia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87068,706,"SOM","Somalia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87069,706,"SOM","Somalia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87070,706,"SOM","Somalia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87071,706,"SOM","Somalia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87072,706,"SOM","Somalia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87073,706,"SOM","Somalia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SOM/som_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87074,710,"ZAF","South Africa","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87075,710,"ZAF","South Africa","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87076,710,"ZAF","South Africa","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87077,710,"ZAF","South Africa","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87078,710,"ZAF","South Africa","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87079,710,"ZAF","South Africa","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87080,710,"ZAF","South Africa","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87081,710,"ZAF","South Africa","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87082,710,"ZAF","South Africa","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87083,710,"ZAF","South Africa","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87084,710,"ZAF","South Africa","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87085,710,"ZAF","South Africa","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87086,710,"ZAF","South Africa","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87087,710,"ZAF","South Africa","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87088,710,"ZAF","South Africa","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87089,710,"ZAF","South Africa","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87090,710,"ZAF","South Africa","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87091,710,"ZAF","South Africa","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87092,710,"ZAF","South Africa","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87093,710,"ZAF","South Africa","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87094,710,"ZAF","South Africa","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87095,710,"ZAF","South Africa","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87096,710,"ZAF","South Africa","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87097,710,"ZAF","South Africa","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87098,710,"ZAF","South Africa","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87099,710,"ZAF","South Africa","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87100,710,"ZAF","South Africa","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87101,710,"ZAF","South Africa","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87102,710,"ZAF","South Africa","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87103,710,"ZAF","South Africa","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87104,710,"ZAF","South Africa","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87105,710,"ZAF","South Africa","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87106,710,"ZAF","South Africa","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87107,710,"ZAF","South Africa","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87108,710,"ZAF","South Africa","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87109,710,"ZAF","South Africa","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZAF/zaf_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87110,716,"ZWE","Zimbabwe","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87111,716,"ZWE","Zimbabwe","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87112,716,"ZWE","Zimbabwe","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87113,716,"ZWE","Zimbabwe","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87114,716,"ZWE","Zimbabwe","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87115,716,"ZWE","Zimbabwe","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87116,716,"ZWE","Zimbabwe","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87117,716,"ZWE","Zimbabwe","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87118,716,"ZWE","Zimbabwe","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87119,716,"ZWE","Zimbabwe","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87120,716,"ZWE","Zimbabwe","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87121,716,"ZWE","Zimbabwe","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87122,716,"ZWE","Zimbabwe","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87123,716,"ZWE","Zimbabwe","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87124,716,"ZWE","Zimbabwe","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87125,716,"ZWE","Zimbabwe","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87126,716,"ZWE","Zimbabwe","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87127,716,"ZWE","Zimbabwe","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87128,716,"ZWE","Zimbabwe","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87129,716,"ZWE","Zimbabwe","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87130,716,"ZWE","Zimbabwe","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87131,716,"ZWE","Zimbabwe","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87132,716,"ZWE","Zimbabwe","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87133,716,"ZWE","Zimbabwe","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87134,716,"ZWE","Zimbabwe","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87135,716,"ZWE","Zimbabwe","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87136,716,"ZWE","Zimbabwe","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87137,716,"ZWE","Zimbabwe","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87138,716,"ZWE","Zimbabwe","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87139,716,"ZWE","Zimbabwe","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87140,716,"ZWE","Zimbabwe","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87141,716,"ZWE","Zimbabwe","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87142,716,"ZWE","Zimbabwe","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87143,716,"ZWE","Zimbabwe","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87144,716,"ZWE","Zimbabwe","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87145,716,"ZWE","Zimbabwe","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZWE/zwe_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87146,724,"ESP","Spain","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87147,724,"ESP","Spain","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87148,724,"ESP","Spain","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87149,724,"ESP","Spain","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87150,724,"ESP","Spain","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87151,724,"ESP","Spain","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87152,724,"ESP","Spain","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87153,724,"ESP","Spain","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87154,724,"ESP","Spain","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87155,724,"ESP","Spain","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87156,724,"ESP","Spain","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87157,724,"ESP","Spain","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87158,724,"ESP","Spain","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87159,724,"ESP","Spain","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87160,724,"ESP","Spain","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87161,724,"ESP","Spain","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87162,724,"ESP","Spain","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87163,724,"ESP","Spain","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87164,724,"ESP","Spain","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87165,724,"ESP","Spain","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87166,724,"ESP","Spain","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87167,724,"ESP","Spain","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87168,724,"ESP","Spain","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87169,724,"ESP","Spain","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87170,724,"ESP","Spain","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87171,724,"ESP","Spain","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87172,724,"ESP","Spain","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87173,724,"ESP","Spain","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87174,724,"ESP","Spain","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87175,724,"ESP","Spain","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87176,724,"ESP","Spain","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87177,724,"ESP","Spain","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87178,724,"ESP","Spain","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87179,724,"ESP","Spain","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87180,724,"ESP","Spain","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87181,724,"ESP","Spain","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESP/esp_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87182,728,"SSD","South Sudan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87183,728,"SSD","South Sudan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87184,728,"SSD","South Sudan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87185,728,"SSD","South Sudan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87186,728,"SSD","South Sudan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87187,728,"SSD","South Sudan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87188,728,"SSD","South Sudan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87189,728,"SSD","South Sudan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87190,728,"SSD","South Sudan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87191,728,"SSD","South Sudan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87192,728,"SSD","South Sudan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87193,728,"SSD","South Sudan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87194,728,"SSD","South Sudan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87195,728,"SSD","South Sudan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87196,728,"SSD","South Sudan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87197,728,"SSD","South Sudan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87198,728,"SSD","South Sudan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87199,728,"SSD","South Sudan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87200,728,"SSD","South Sudan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87201,728,"SSD","South Sudan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87202,728,"SSD","South Sudan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87203,728,"SSD","South Sudan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87204,728,"SSD","South Sudan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87205,728,"SSD","South Sudan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87206,728,"SSD","South Sudan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87207,728,"SSD","South Sudan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87208,728,"SSD","South Sudan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87209,728,"SSD","South Sudan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87210,728,"SSD","South Sudan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87211,728,"SSD","South Sudan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87212,728,"SSD","South Sudan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87213,728,"SSD","South Sudan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87214,728,"SSD","South Sudan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87215,728,"SSD","South Sudan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87216,728,"SSD","South Sudan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87217,728,"SSD","South Sudan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SSD/ssd_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87218,729,"SDN","Sudan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87219,729,"SDN","Sudan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87220,729,"SDN","Sudan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87221,729,"SDN","Sudan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87222,729,"SDN","Sudan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87223,729,"SDN","Sudan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87224,729,"SDN","Sudan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87225,729,"SDN","Sudan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87226,729,"SDN","Sudan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87227,729,"SDN","Sudan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87228,729,"SDN","Sudan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87229,729,"SDN","Sudan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87230,729,"SDN","Sudan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87231,729,"SDN","Sudan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87232,729,"SDN","Sudan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87233,729,"SDN","Sudan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87234,729,"SDN","Sudan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87235,729,"SDN","Sudan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87236,729,"SDN","Sudan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87237,729,"SDN","Sudan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87238,729,"SDN","Sudan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87239,729,"SDN","Sudan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87240,729,"SDN","Sudan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87241,729,"SDN","Sudan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87242,729,"SDN","Sudan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87243,729,"SDN","Sudan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87244,729,"SDN","Sudan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87245,729,"SDN","Sudan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87246,729,"SDN","Sudan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87247,729,"SDN","Sudan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87248,729,"SDN","Sudan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87249,729,"SDN","Sudan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87250,729,"SDN","Sudan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87251,729,"SDN","Sudan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87252,729,"SDN","Sudan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87253,729,"SDN","Sudan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SDN/sdn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87254,732,"ESH","Western Sahara","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87255,732,"ESH","Western Sahara","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87256,732,"ESH","Western Sahara","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87257,732,"ESH","Western Sahara","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87258,732,"ESH","Western Sahara","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87259,732,"ESH","Western Sahara","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87260,732,"ESH","Western Sahara","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87261,732,"ESH","Western Sahara","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87262,732,"ESH","Western Sahara","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87263,732,"ESH","Western Sahara","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87264,732,"ESH","Western Sahara","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87265,732,"ESH","Western Sahara","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87266,732,"ESH","Western Sahara","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87267,732,"ESH","Western Sahara","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87268,732,"ESH","Western Sahara","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87269,732,"ESH","Western Sahara","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87270,732,"ESH","Western Sahara","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87271,732,"ESH","Western Sahara","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87272,732,"ESH","Western Sahara","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87273,732,"ESH","Western Sahara","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87274,732,"ESH","Western Sahara","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87275,732,"ESH","Western Sahara","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87276,732,"ESH","Western Sahara","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87277,732,"ESH","Western Sahara","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87278,732,"ESH","Western Sahara","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87279,732,"ESH","Western Sahara","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87280,732,"ESH","Western Sahara","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87281,732,"ESH","Western Sahara","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87282,732,"ESH","Western Sahara","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87283,732,"ESH","Western Sahara","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87284,732,"ESH","Western Sahara","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87285,732,"ESH","Western Sahara","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87286,732,"ESH","Western Sahara","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87287,732,"ESH","Western Sahara","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87288,732,"ESH","Western Sahara","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87289,732,"ESH","Western Sahara","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ESH/esh_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87290,740,"SUR","Suriname","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87291,740,"SUR","Suriname","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87292,740,"SUR","Suriname","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87293,740,"SUR","Suriname","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87294,740,"SUR","Suriname","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87295,740,"SUR","Suriname","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87296,740,"SUR","Suriname","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87297,740,"SUR","Suriname","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87298,740,"SUR","Suriname","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87299,740,"SUR","Suriname","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87300,740,"SUR","Suriname","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87301,740,"SUR","Suriname","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87302,740,"SUR","Suriname","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87303,740,"SUR","Suriname","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87304,740,"SUR","Suriname","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87305,740,"SUR","Suriname","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87306,740,"SUR","Suriname","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87307,740,"SUR","Suriname","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87308,740,"SUR","Suriname","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87309,740,"SUR","Suriname","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87310,740,"SUR","Suriname","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87311,740,"SUR","Suriname","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87312,740,"SUR","Suriname","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87313,740,"SUR","Suriname","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87314,740,"SUR","Suriname","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87315,740,"SUR","Suriname","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87316,740,"SUR","Suriname","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87317,740,"SUR","Suriname","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87318,740,"SUR","Suriname","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87319,740,"SUR","Suriname","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87320,740,"SUR","Suriname","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87321,740,"SUR","Suriname","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87322,740,"SUR","Suriname","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87323,740,"SUR","Suriname","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87324,740,"SUR","Suriname","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87325,740,"SUR","Suriname","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SUR/sur_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87326,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87327,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87328,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87329,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87330,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87331,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87332,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87333,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87334,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87335,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87336,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87337,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87338,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87339,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87340,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87341,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87342,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87343,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87344,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87345,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87346,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87347,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87348,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87349,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87350,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87351,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87352,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87353,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87354,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87355,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87356,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87357,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87358,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87359,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87360,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87361,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SJM/sjm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87362,748,"SWZ","Swaziland","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87363,748,"SWZ","Swaziland","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87364,748,"SWZ","Swaziland","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87365,748,"SWZ","Swaziland","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87366,748,"SWZ","Swaziland","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87367,748,"SWZ","Swaziland","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87368,748,"SWZ","Swaziland","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87369,748,"SWZ","Swaziland","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87370,748,"SWZ","Swaziland","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87371,748,"SWZ","Swaziland","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87372,748,"SWZ","Swaziland","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87373,748,"SWZ","Swaziland","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87374,748,"SWZ","Swaziland","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87375,748,"SWZ","Swaziland","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87376,748,"SWZ","Swaziland","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87377,748,"SWZ","Swaziland","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87378,748,"SWZ","Swaziland","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87379,748,"SWZ","Swaziland","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87380,748,"SWZ","Swaziland","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87381,748,"SWZ","Swaziland","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87382,748,"SWZ","Swaziland","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87383,748,"SWZ","Swaziland","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87384,748,"SWZ","Swaziland","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87385,748,"SWZ","Swaziland","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87386,748,"SWZ","Swaziland","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87387,748,"SWZ","Swaziland","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87388,748,"SWZ","Swaziland","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87389,748,"SWZ","Swaziland","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87390,748,"SWZ","Swaziland","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87391,748,"SWZ","Swaziland","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87392,748,"SWZ","Swaziland","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87393,748,"SWZ","Swaziland","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87394,748,"SWZ","Swaziland","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87395,748,"SWZ","Swaziland","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87396,748,"SWZ","Swaziland","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87397,748,"SWZ","Swaziland","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWZ/swz_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87398,752,"SWE","Sweden","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87399,752,"SWE","Sweden","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87400,752,"SWE","Sweden","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87401,752,"SWE","Sweden","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87402,752,"SWE","Sweden","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87403,752,"SWE","Sweden","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87404,752,"SWE","Sweden","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87405,752,"SWE","Sweden","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87406,752,"SWE","Sweden","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87407,752,"SWE","Sweden","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87408,752,"SWE","Sweden","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87409,752,"SWE","Sweden","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87410,752,"SWE","Sweden","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87411,752,"SWE","Sweden","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87412,752,"SWE","Sweden","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87413,752,"SWE","Sweden","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87414,752,"SWE","Sweden","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87415,752,"SWE","Sweden","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87416,752,"SWE","Sweden","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87417,752,"SWE","Sweden","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87418,752,"SWE","Sweden","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87419,752,"SWE","Sweden","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87420,752,"SWE","Sweden","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87421,752,"SWE","Sweden","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87422,752,"SWE","Sweden","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87423,752,"SWE","Sweden","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87424,752,"SWE","Sweden","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87425,752,"SWE","Sweden","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87426,752,"SWE","Sweden","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87427,752,"SWE","Sweden","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87428,752,"SWE","Sweden","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87429,752,"SWE","Sweden","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87430,752,"SWE","Sweden","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87431,752,"SWE","Sweden","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87432,752,"SWE","Sweden","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87433,752,"SWE","Sweden","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SWE/swe_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87434,756,"CHE","Switzerland","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87435,756,"CHE","Switzerland","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87436,756,"CHE","Switzerland","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87437,756,"CHE","Switzerland","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87438,756,"CHE","Switzerland","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87439,756,"CHE","Switzerland","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87440,756,"CHE","Switzerland","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87441,756,"CHE","Switzerland","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87442,756,"CHE","Switzerland","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87443,756,"CHE","Switzerland","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87444,756,"CHE","Switzerland","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87445,756,"CHE","Switzerland","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87446,756,"CHE","Switzerland","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87447,756,"CHE","Switzerland","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87448,756,"CHE","Switzerland","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87449,756,"CHE","Switzerland","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87450,756,"CHE","Switzerland","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87451,756,"CHE","Switzerland","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87452,756,"CHE","Switzerland","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87453,756,"CHE","Switzerland","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87454,756,"CHE","Switzerland","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87455,756,"CHE","Switzerland","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87456,756,"CHE","Switzerland","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87457,756,"CHE","Switzerland","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87458,756,"CHE","Switzerland","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87459,756,"CHE","Switzerland","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87460,756,"CHE","Switzerland","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87461,756,"CHE","Switzerland","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87462,756,"CHE","Switzerland","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87463,756,"CHE","Switzerland","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87464,756,"CHE","Switzerland","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87465,756,"CHE","Switzerland","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87466,756,"CHE","Switzerland","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87467,756,"CHE","Switzerland","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87468,756,"CHE","Switzerland","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87469,756,"CHE","Switzerland","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/CHE/che_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87470,760,"SYR","Syria","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87471,760,"SYR","Syria","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87472,760,"SYR","Syria","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87473,760,"SYR","Syria","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87474,760,"SYR","Syria","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87475,760,"SYR","Syria","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87476,760,"SYR","Syria","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87477,760,"SYR","Syria","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87478,760,"SYR","Syria","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87479,760,"SYR","Syria","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87480,760,"SYR","Syria","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87481,760,"SYR","Syria","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87482,760,"SYR","Syria","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87483,760,"SYR","Syria","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87484,760,"SYR","Syria","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87485,760,"SYR","Syria","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87486,760,"SYR","Syria","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87487,760,"SYR","Syria","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87488,760,"SYR","Syria","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87489,760,"SYR","Syria","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87490,760,"SYR","Syria","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87491,760,"SYR","Syria","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87492,760,"SYR","Syria","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87493,760,"SYR","Syria","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87494,760,"SYR","Syria","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87495,760,"SYR","Syria","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87496,760,"SYR","Syria","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87497,760,"SYR","Syria","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87498,760,"SYR","Syria","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87499,760,"SYR","Syria","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87500,760,"SYR","Syria","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87501,760,"SYR","Syria","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87502,760,"SYR","Syria","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87503,760,"SYR","Syria","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87504,760,"SYR","Syria","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87505,760,"SYR","Syria","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/SYR/syr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87506,762,"TJK","Tajikistan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87507,762,"TJK","Tajikistan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87508,762,"TJK","Tajikistan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87509,762,"TJK","Tajikistan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87510,762,"TJK","Tajikistan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87511,762,"TJK","Tajikistan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87512,762,"TJK","Tajikistan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87513,762,"TJK","Tajikistan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87514,762,"TJK","Tajikistan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87515,762,"TJK","Tajikistan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87516,762,"TJK","Tajikistan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87517,762,"TJK","Tajikistan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87518,762,"TJK","Tajikistan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87519,762,"TJK","Tajikistan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87520,762,"TJK","Tajikistan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87521,762,"TJK","Tajikistan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87522,762,"TJK","Tajikistan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87523,762,"TJK","Tajikistan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87524,762,"TJK","Tajikistan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87525,762,"TJK","Tajikistan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87526,762,"TJK","Tajikistan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87527,762,"TJK","Tajikistan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87528,762,"TJK","Tajikistan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87529,762,"TJK","Tajikistan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87530,762,"TJK","Tajikistan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87531,762,"TJK","Tajikistan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87532,762,"TJK","Tajikistan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87533,762,"TJK","Tajikistan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87534,762,"TJK","Tajikistan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87535,762,"TJK","Tajikistan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87536,762,"TJK","Tajikistan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87537,762,"TJK","Tajikistan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87538,762,"TJK","Tajikistan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87539,762,"TJK","Tajikistan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87540,762,"TJK","Tajikistan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87541,762,"TJK","Tajikistan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TJK/tjk_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87542,764,"THA","Thailand","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87543,764,"THA","Thailand","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87544,764,"THA","Thailand","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87545,764,"THA","Thailand","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87546,764,"THA","Thailand","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87547,764,"THA","Thailand","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87548,764,"THA","Thailand","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87549,764,"THA","Thailand","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87550,764,"THA","Thailand","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87551,764,"THA","Thailand","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87552,764,"THA","Thailand","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87553,764,"THA","Thailand","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87554,764,"THA","Thailand","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87555,764,"THA","Thailand","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87556,764,"THA","Thailand","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87557,764,"THA","Thailand","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87558,764,"THA","Thailand","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87559,764,"THA","Thailand","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87560,764,"THA","Thailand","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87561,764,"THA","Thailand","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87562,764,"THA","Thailand","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87563,764,"THA","Thailand","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87564,764,"THA","Thailand","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87565,764,"THA","Thailand","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87566,764,"THA","Thailand","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87567,764,"THA","Thailand","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87568,764,"THA","Thailand","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87569,764,"THA","Thailand","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87570,764,"THA","Thailand","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87571,764,"THA","Thailand","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87572,764,"THA","Thailand","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87573,764,"THA","Thailand","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87574,764,"THA","Thailand","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87575,764,"THA","Thailand","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87576,764,"THA","Thailand","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87577,764,"THA","Thailand","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/THA/tha_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87578,768,"TGO","Togo","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87579,768,"TGO","Togo","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87580,768,"TGO","Togo","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87581,768,"TGO","Togo","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87582,768,"TGO","Togo","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87583,768,"TGO","Togo","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87584,768,"TGO","Togo","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87585,768,"TGO","Togo","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87586,768,"TGO","Togo","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87587,768,"TGO","Togo","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87588,768,"TGO","Togo","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87589,768,"TGO","Togo","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87590,768,"TGO","Togo","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87591,768,"TGO","Togo","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87592,768,"TGO","Togo","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87593,768,"TGO","Togo","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87594,768,"TGO","Togo","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87595,768,"TGO","Togo","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87596,768,"TGO","Togo","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87597,768,"TGO","Togo","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87598,768,"TGO","Togo","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87599,768,"TGO","Togo","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87600,768,"TGO","Togo","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87601,768,"TGO","Togo","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87602,768,"TGO","Togo","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87603,768,"TGO","Togo","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87604,768,"TGO","Togo","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87605,768,"TGO","Togo","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87606,768,"TGO","Togo","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87607,768,"TGO","Togo","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87608,768,"TGO","Togo","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87609,768,"TGO","Togo","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87610,768,"TGO","Togo","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87611,768,"TGO","Togo","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87612,768,"TGO","Togo","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87613,768,"TGO","Togo","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TGO/tgo_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87614,772,"TKL","Tokelau","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87615,772,"TKL","Tokelau","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87616,772,"TKL","Tokelau","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87617,772,"TKL","Tokelau","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87618,772,"TKL","Tokelau","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87619,772,"TKL","Tokelau","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87620,772,"TKL","Tokelau","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87621,772,"TKL","Tokelau","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87622,772,"TKL","Tokelau","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87623,772,"TKL","Tokelau","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87624,772,"TKL","Tokelau","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87625,772,"TKL","Tokelau","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87626,772,"TKL","Tokelau","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87627,772,"TKL","Tokelau","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87628,772,"TKL","Tokelau","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87629,772,"TKL","Tokelau","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87630,772,"TKL","Tokelau","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87631,772,"TKL","Tokelau","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87632,772,"TKL","Tokelau","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87633,772,"TKL","Tokelau","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87634,772,"TKL","Tokelau","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87635,772,"TKL","Tokelau","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87636,772,"TKL","Tokelau","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87637,772,"TKL","Tokelau","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87638,772,"TKL","Tokelau","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87639,772,"TKL","Tokelau","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87640,772,"TKL","Tokelau","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87641,772,"TKL","Tokelau","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87642,772,"TKL","Tokelau","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87643,772,"TKL","Tokelau","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87644,772,"TKL","Tokelau","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87645,772,"TKL","Tokelau","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87646,772,"TKL","Tokelau","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87647,772,"TKL","Tokelau","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87648,772,"TKL","Tokelau","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87649,772,"TKL","Tokelau","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKL/tkl_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87650,776,"TON","Tonga","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87651,776,"TON","Tonga","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87652,776,"TON","Tonga","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87653,776,"TON","Tonga","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87654,776,"TON","Tonga","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87655,776,"TON","Tonga","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87656,776,"TON","Tonga","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87657,776,"TON","Tonga","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87658,776,"TON","Tonga","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87659,776,"TON","Tonga","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87660,776,"TON","Tonga","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87661,776,"TON","Tonga","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87662,776,"TON","Tonga","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87663,776,"TON","Tonga","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87664,776,"TON","Tonga","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87665,776,"TON","Tonga","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87666,776,"TON","Tonga","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87667,776,"TON","Tonga","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87668,776,"TON","Tonga","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87669,776,"TON","Tonga","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87670,776,"TON","Tonga","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87671,776,"TON","Tonga","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87672,776,"TON","Tonga","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87673,776,"TON","Tonga","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87674,776,"TON","Tonga","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87675,776,"TON","Tonga","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87676,776,"TON","Tonga","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87677,776,"TON","Tonga","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87678,776,"TON","Tonga","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87679,776,"TON","Tonga","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87680,776,"TON","Tonga","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87681,776,"TON","Tonga","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87682,776,"TON","Tonga","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87683,776,"TON","Tonga","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87684,776,"TON","Tonga","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87685,776,"TON","Tonga","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TON/ton_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87686,780,"TTO","Trinidad and Tobago","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87687,780,"TTO","Trinidad and Tobago","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87688,780,"TTO","Trinidad and Tobago","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87689,780,"TTO","Trinidad and Tobago","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87690,780,"TTO","Trinidad and Tobago","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87691,780,"TTO","Trinidad and Tobago","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87692,780,"TTO","Trinidad and Tobago","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87693,780,"TTO","Trinidad and Tobago","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87694,780,"TTO","Trinidad and Tobago","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87695,780,"TTO","Trinidad and Tobago","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87696,780,"TTO","Trinidad and Tobago","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87697,780,"TTO","Trinidad and Tobago","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87698,780,"TTO","Trinidad and Tobago","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87699,780,"TTO","Trinidad and Tobago","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87700,780,"TTO","Trinidad and Tobago","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87701,780,"TTO","Trinidad and Tobago","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87702,780,"TTO","Trinidad and Tobago","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87703,780,"TTO","Trinidad and Tobago","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87704,780,"TTO","Trinidad and Tobago","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87705,780,"TTO","Trinidad and Tobago","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87706,780,"TTO","Trinidad and Tobago","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87707,780,"TTO","Trinidad and Tobago","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87708,780,"TTO","Trinidad and Tobago","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87709,780,"TTO","Trinidad and Tobago","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87710,780,"TTO","Trinidad and Tobago","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87711,780,"TTO","Trinidad and Tobago","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87712,780,"TTO","Trinidad and Tobago","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87713,780,"TTO","Trinidad and Tobago","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87714,780,"TTO","Trinidad and Tobago","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87715,780,"TTO","Trinidad and Tobago","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87716,780,"TTO","Trinidad and Tobago","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87717,780,"TTO","Trinidad and Tobago","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87718,780,"TTO","Trinidad and Tobago","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87719,780,"TTO","Trinidad and Tobago","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87720,780,"TTO","Trinidad and Tobago","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87721,780,"TTO","Trinidad and Tobago","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TTO/tto_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87722,784,"ARE","United Arab Emirates","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87723,784,"ARE","United Arab Emirates","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87724,784,"ARE","United Arab Emirates","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87725,784,"ARE","United Arab Emirates","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87726,784,"ARE","United Arab Emirates","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87727,784,"ARE","United Arab Emirates","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87728,784,"ARE","United Arab Emirates","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87729,784,"ARE","United Arab Emirates","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87730,784,"ARE","United Arab Emirates","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87731,784,"ARE","United Arab Emirates","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87732,784,"ARE","United Arab Emirates","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87733,784,"ARE","United Arab Emirates","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87734,784,"ARE","United Arab Emirates","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87735,784,"ARE","United Arab Emirates","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87736,784,"ARE","United Arab Emirates","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87737,784,"ARE","United Arab Emirates","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87738,784,"ARE","United Arab Emirates","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87739,784,"ARE","United Arab Emirates","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87740,784,"ARE","United Arab Emirates","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87741,784,"ARE","United Arab Emirates","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87742,784,"ARE","United Arab Emirates","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87743,784,"ARE","United Arab Emirates","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87744,784,"ARE","United Arab Emirates","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87745,784,"ARE","United Arab Emirates","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87746,784,"ARE","United Arab Emirates","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87747,784,"ARE","United Arab Emirates","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87748,784,"ARE","United Arab Emirates","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87749,784,"ARE","United Arab Emirates","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87750,784,"ARE","United Arab Emirates","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87751,784,"ARE","United Arab Emirates","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87752,784,"ARE","United Arab Emirates","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87753,784,"ARE","United Arab Emirates","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87754,784,"ARE","United Arab Emirates","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87755,784,"ARE","United Arab Emirates","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87756,784,"ARE","United Arab Emirates","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87757,784,"ARE","United Arab Emirates","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ARE/are_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87758,788,"TUN","Tunisia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87759,788,"TUN","Tunisia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87760,788,"TUN","Tunisia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87761,788,"TUN","Tunisia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87762,788,"TUN","Tunisia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87763,788,"TUN","Tunisia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87764,788,"TUN","Tunisia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87765,788,"TUN","Tunisia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87766,788,"TUN","Tunisia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87767,788,"TUN","Tunisia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87768,788,"TUN","Tunisia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87769,788,"TUN","Tunisia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87770,788,"TUN","Tunisia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87771,788,"TUN","Tunisia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87772,788,"TUN","Tunisia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87773,788,"TUN","Tunisia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87774,788,"TUN","Tunisia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87775,788,"TUN","Tunisia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87776,788,"TUN","Tunisia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87777,788,"TUN","Tunisia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87778,788,"TUN","Tunisia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87779,788,"TUN","Tunisia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87780,788,"TUN","Tunisia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87781,788,"TUN","Tunisia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87782,788,"TUN","Tunisia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87783,788,"TUN","Tunisia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87784,788,"TUN","Tunisia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87785,788,"TUN","Tunisia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87786,788,"TUN","Tunisia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87787,788,"TUN","Tunisia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87788,788,"TUN","Tunisia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87789,788,"TUN","Tunisia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87790,788,"TUN","Tunisia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87791,788,"TUN","Tunisia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87792,788,"TUN","Tunisia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87793,788,"TUN","Tunisia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUN/tun_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87794,792,"TUR","Turkey","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87795,792,"TUR","Turkey","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87796,792,"TUR","Turkey","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87797,792,"TUR","Turkey","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87798,792,"TUR","Turkey","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87799,792,"TUR","Turkey","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87800,792,"TUR","Turkey","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87801,792,"TUR","Turkey","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87802,792,"TUR","Turkey","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87803,792,"TUR","Turkey","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87804,792,"TUR","Turkey","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87805,792,"TUR","Turkey","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87806,792,"TUR","Turkey","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87807,792,"TUR","Turkey","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87808,792,"TUR","Turkey","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87809,792,"TUR","Turkey","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87810,792,"TUR","Turkey","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87811,792,"TUR","Turkey","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87812,792,"TUR","Turkey","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87813,792,"TUR","Turkey","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87814,792,"TUR","Turkey","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87815,792,"TUR","Turkey","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87816,792,"TUR","Turkey","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87817,792,"TUR","Turkey","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87818,792,"TUR","Turkey","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87819,792,"TUR","Turkey","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87820,792,"TUR","Turkey","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87821,792,"TUR","Turkey","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87822,792,"TUR","Turkey","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87823,792,"TUR","Turkey","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87824,792,"TUR","Turkey","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87825,792,"TUR","Turkey","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87826,792,"TUR","Turkey","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87827,792,"TUR","Turkey","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87828,792,"TUR","Turkey","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87829,792,"TUR","Turkey","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUR/tur_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87830,795,"TKM","Turkmenistan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87831,795,"TKM","Turkmenistan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87832,795,"TKM","Turkmenistan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87833,795,"TKM","Turkmenistan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87834,795,"TKM","Turkmenistan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87835,795,"TKM","Turkmenistan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87836,795,"TKM","Turkmenistan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87837,795,"TKM","Turkmenistan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87838,795,"TKM","Turkmenistan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87839,795,"TKM","Turkmenistan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87840,795,"TKM","Turkmenistan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87841,795,"TKM","Turkmenistan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87842,795,"TKM","Turkmenistan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87843,795,"TKM","Turkmenistan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87844,795,"TKM","Turkmenistan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87845,795,"TKM","Turkmenistan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87846,795,"TKM","Turkmenistan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87847,795,"TKM","Turkmenistan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87848,795,"TKM","Turkmenistan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87849,795,"TKM","Turkmenistan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87850,795,"TKM","Turkmenistan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87851,795,"TKM","Turkmenistan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87852,795,"TKM","Turkmenistan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87853,795,"TKM","Turkmenistan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87854,795,"TKM","Turkmenistan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87855,795,"TKM","Turkmenistan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87856,795,"TKM","Turkmenistan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87857,795,"TKM","Turkmenistan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87858,795,"TKM","Turkmenistan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87859,795,"TKM","Turkmenistan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87860,795,"TKM","Turkmenistan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87861,795,"TKM","Turkmenistan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87862,795,"TKM","Turkmenistan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87863,795,"TKM","Turkmenistan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87864,795,"TKM","Turkmenistan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87865,795,"TKM","Turkmenistan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TKM/tkm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87866,796,"TCA","Turks and Caicos Islands","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87867,796,"TCA","Turks and Caicos Islands","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87868,796,"TCA","Turks and Caicos Islands","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87869,796,"TCA","Turks and Caicos Islands","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87870,796,"TCA","Turks and Caicos Islands","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87871,796,"TCA","Turks and Caicos Islands","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87872,796,"TCA","Turks and Caicos Islands","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87873,796,"TCA","Turks and Caicos Islands","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87874,796,"TCA","Turks and Caicos Islands","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87875,796,"TCA","Turks and Caicos Islands","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87876,796,"TCA","Turks and Caicos Islands","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87877,796,"TCA","Turks and Caicos Islands","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87878,796,"TCA","Turks and Caicos Islands","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87879,796,"TCA","Turks and Caicos Islands","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87880,796,"TCA","Turks and Caicos Islands","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87881,796,"TCA","Turks and Caicos Islands","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87882,796,"TCA","Turks and Caicos Islands","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87883,796,"TCA","Turks and Caicos Islands","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87884,796,"TCA","Turks and Caicos Islands","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87885,796,"TCA","Turks and Caicos Islands","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87886,796,"TCA","Turks and Caicos Islands","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87887,796,"TCA","Turks and Caicos Islands","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87888,796,"TCA","Turks and Caicos Islands","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87889,796,"TCA","Turks and Caicos Islands","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87890,796,"TCA","Turks and Caicos Islands","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87891,796,"TCA","Turks and Caicos Islands","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87892,796,"TCA","Turks and Caicos Islands","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87893,796,"TCA","Turks and Caicos Islands","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87894,796,"TCA","Turks and Caicos Islands","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87895,796,"TCA","Turks and Caicos Islands","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87896,796,"TCA","Turks and Caicos Islands","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87897,796,"TCA","Turks and Caicos Islands","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87898,796,"TCA","Turks and Caicos Islands","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87899,796,"TCA","Turks and Caicos Islands","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87900,796,"TCA","Turks and Caicos Islands","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87901,796,"TCA","Turks and Caicos Islands","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TCA/tca_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87902,798,"TUV","Tuvalu","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87903,798,"TUV","Tuvalu","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87904,798,"TUV","Tuvalu","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87905,798,"TUV","Tuvalu","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87906,798,"TUV","Tuvalu","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87907,798,"TUV","Tuvalu","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87908,798,"TUV","Tuvalu","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87909,798,"TUV","Tuvalu","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87910,798,"TUV","Tuvalu","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87911,798,"TUV","Tuvalu","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87912,798,"TUV","Tuvalu","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87913,798,"TUV","Tuvalu","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87914,798,"TUV","Tuvalu","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87915,798,"TUV","Tuvalu","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87916,798,"TUV","Tuvalu","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87917,798,"TUV","Tuvalu","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87918,798,"TUV","Tuvalu","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87919,798,"TUV","Tuvalu","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87920,798,"TUV","Tuvalu","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87921,798,"TUV","Tuvalu","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87922,798,"TUV","Tuvalu","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87923,798,"TUV","Tuvalu","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87924,798,"TUV","Tuvalu","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87925,798,"TUV","Tuvalu","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87926,798,"TUV","Tuvalu","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87927,798,"TUV","Tuvalu","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87928,798,"TUV","Tuvalu","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87929,798,"TUV","Tuvalu","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87930,798,"TUV","Tuvalu","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87931,798,"TUV","Tuvalu","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87932,798,"TUV","Tuvalu","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87933,798,"TUV","Tuvalu","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87934,798,"TUV","Tuvalu","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87935,798,"TUV","Tuvalu","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87936,798,"TUV","Tuvalu","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87937,798,"TUV","Tuvalu","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TUV/tuv_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87938,800,"UGA","Uganda","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87939,800,"UGA","Uganda","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87940,800,"UGA","Uganda","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87941,800,"UGA","Uganda","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87942,800,"UGA","Uganda","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87943,800,"UGA","Uganda","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87944,800,"UGA","Uganda","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87945,800,"UGA","Uganda","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87946,800,"UGA","Uganda","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87947,800,"UGA","Uganda","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87948,800,"UGA","Uganda","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87949,800,"UGA","Uganda","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87950,800,"UGA","Uganda","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87951,800,"UGA","Uganda","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87952,800,"UGA","Uganda","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87953,800,"UGA","Uganda","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87954,800,"UGA","Uganda","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87955,800,"UGA","Uganda","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87956,800,"UGA","Uganda","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87957,800,"UGA","Uganda","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87958,800,"UGA","Uganda","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87959,800,"UGA","Uganda","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87960,800,"UGA","Uganda","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87961,800,"UGA","Uganda","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87962,800,"UGA","Uganda","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87963,800,"UGA","Uganda","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87964,800,"UGA","Uganda","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87965,800,"UGA","Uganda","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87966,800,"UGA","Uganda","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87967,800,"UGA","Uganda","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87968,800,"UGA","Uganda","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87969,800,"UGA","Uganda","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87970,800,"UGA","Uganda","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87971,800,"UGA","Uganda","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87972,800,"UGA","Uganda","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87973,800,"UGA","Uganda","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UGA/uga_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
87974,804,"UKR","Ukraine","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87975,804,"UKR","Ukraine","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87976,804,"UKR","Ukraine","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87977,804,"UKR","Ukraine","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87978,804,"UKR","Ukraine","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87979,804,"UKR","Ukraine","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87980,804,"UKR","Ukraine","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87981,804,"UKR","Ukraine","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87982,804,"UKR","Ukraine","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87983,804,"UKR","Ukraine","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87984,804,"UKR","Ukraine","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87985,804,"UKR","Ukraine","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87986,804,"UKR","Ukraine","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87987,804,"UKR","Ukraine","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87988,804,"UKR","Ukraine","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87989,804,"UKR","Ukraine","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87990,804,"UKR","Ukraine","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87991,804,"UKR","Ukraine","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87992,804,"UKR","Ukraine","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87993,804,"UKR","Ukraine","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87994,804,"UKR","Ukraine","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87995,804,"UKR","Ukraine","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87996,804,"UKR","Ukraine","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87997,804,"UKR","Ukraine","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87998,804,"UKR","Ukraine","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
87999,804,"UKR","Ukraine","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88000,804,"UKR","Ukraine","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88001,804,"UKR","Ukraine","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88002,804,"UKR","Ukraine","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88003,804,"UKR","Ukraine","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88004,804,"UKR","Ukraine","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88005,804,"UKR","Ukraine","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88006,804,"UKR","Ukraine","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88007,804,"UKR","Ukraine","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88008,804,"UKR","Ukraine","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88009,804,"UKR","Ukraine","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UKR/ukr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88010,807,"MKD","Macedonia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88011,807,"MKD","Macedonia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88012,807,"MKD","Macedonia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88013,807,"MKD","Macedonia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88014,807,"MKD","Macedonia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88015,807,"MKD","Macedonia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88016,807,"MKD","Macedonia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88017,807,"MKD","Macedonia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88018,807,"MKD","Macedonia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88019,807,"MKD","Macedonia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88020,807,"MKD","Macedonia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88021,807,"MKD","Macedonia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88022,807,"MKD","Macedonia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88023,807,"MKD","Macedonia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88024,807,"MKD","Macedonia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88025,807,"MKD","Macedonia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88026,807,"MKD","Macedonia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88027,807,"MKD","Macedonia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88028,807,"MKD","Macedonia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88029,807,"MKD","Macedonia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88030,807,"MKD","Macedonia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88031,807,"MKD","Macedonia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88032,807,"MKD","Macedonia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88033,807,"MKD","Macedonia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88034,807,"MKD","Macedonia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88035,807,"MKD","Macedonia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88036,807,"MKD","Macedonia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88037,807,"MKD","Macedonia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88038,807,"MKD","Macedonia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88039,807,"MKD","Macedonia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88040,807,"MKD","Macedonia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88041,807,"MKD","Macedonia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88042,807,"MKD","Macedonia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88043,807,"MKD","Macedonia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88044,807,"MKD","Macedonia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88045,807,"MKD","Macedonia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/MKD/mkd_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88046,818,"EGY","Egypt","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88047,818,"EGY","Egypt","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88048,818,"EGY","Egypt","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88049,818,"EGY","Egypt","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88050,818,"EGY","Egypt","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88051,818,"EGY","Egypt","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88052,818,"EGY","Egypt","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88053,818,"EGY","Egypt","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88054,818,"EGY","Egypt","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88055,818,"EGY","Egypt","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88056,818,"EGY","Egypt","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88057,818,"EGY","Egypt","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88058,818,"EGY","Egypt","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88059,818,"EGY","Egypt","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88060,818,"EGY","Egypt","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88061,818,"EGY","Egypt","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88062,818,"EGY","Egypt","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88063,818,"EGY","Egypt","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88064,818,"EGY","Egypt","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88065,818,"EGY","Egypt","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88066,818,"EGY","Egypt","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88067,818,"EGY","Egypt","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88068,818,"EGY","Egypt","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88069,818,"EGY","Egypt","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88070,818,"EGY","Egypt","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88071,818,"EGY","Egypt","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88072,818,"EGY","Egypt","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88073,818,"EGY","Egypt","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88074,818,"EGY","Egypt","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88075,818,"EGY","Egypt","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88076,818,"EGY","Egypt","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88077,818,"EGY","Egypt","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88078,818,"EGY","Egypt","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88079,818,"EGY","Egypt","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88080,818,"EGY","Egypt","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88081,818,"EGY","Egypt","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/EGY/egy_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88082,826,"GBR","United Kingdom","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88083,826,"GBR","United Kingdom","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88084,826,"GBR","United Kingdom","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88085,826,"GBR","United Kingdom","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88086,826,"GBR","United Kingdom","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88087,826,"GBR","United Kingdom","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88088,826,"GBR","United Kingdom","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88089,826,"GBR","United Kingdom","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88090,826,"GBR","United Kingdom","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88091,826,"GBR","United Kingdom","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88092,826,"GBR","United Kingdom","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88093,826,"GBR","United Kingdom","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88094,826,"GBR","United Kingdom","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88095,826,"GBR","United Kingdom","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88096,826,"GBR","United Kingdom","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88097,826,"GBR","United Kingdom","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88098,826,"GBR","United Kingdom","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88099,826,"GBR","United Kingdom","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88100,826,"GBR","United Kingdom","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88101,826,"GBR","United Kingdom","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88102,826,"GBR","United Kingdom","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88103,826,"GBR","United Kingdom","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88104,826,"GBR","United Kingdom","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88105,826,"GBR","United Kingdom","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88106,826,"GBR","United Kingdom","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88107,826,"GBR","United Kingdom","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88108,826,"GBR","United Kingdom","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88109,826,"GBR","United Kingdom","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88110,826,"GBR","United Kingdom","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88111,826,"GBR","United Kingdom","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88112,826,"GBR","United Kingdom","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88113,826,"GBR","United Kingdom","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88114,826,"GBR","United Kingdom","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88115,826,"GBR","United Kingdom","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88116,826,"GBR","United Kingdom","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88117,826,"GBR","United Kingdom","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GBR/gbr_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88118,831,"GGY","Guernsey","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88119,831,"GGY","Guernsey","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88120,831,"GGY","Guernsey","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88121,831,"GGY","Guernsey","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88122,831,"GGY","Guernsey","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88123,831,"GGY","Guernsey","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88124,831,"GGY","Guernsey","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88125,831,"GGY","Guernsey","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88126,831,"GGY","Guernsey","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88127,831,"GGY","Guernsey","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88128,831,"GGY","Guernsey","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88129,831,"GGY","Guernsey","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88130,831,"GGY","Guernsey","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88131,831,"GGY","Guernsey","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88132,831,"GGY","Guernsey","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88133,831,"GGY","Guernsey","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88134,831,"GGY","Guernsey","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88135,831,"GGY","Guernsey","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88136,831,"GGY","Guernsey","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88137,831,"GGY","Guernsey","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88138,831,"GGY","Guernsey","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88139,831,"GGY","Guernsey","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88140,831,"GGY","Guernsey","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88141,831,"GGY","Guernsey","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88142,831,"GGY","Guernsey","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88143,831,"GGY","Guernsey","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88144,831,"GGY","Guernsey","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88145,831,"GGY","Guernsey","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88146,831,"GGY","Guernsey","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88147,831,"GGY","Guernsey","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88148,831,"GGY","Guernsey","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88149,831,"GGY","Guernsey","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88150,831,"GGY","Guernsey","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88151,831,"GGY","Guernsey","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88152,831,"GGY","Guernsey","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88153,831,"GGY","Guernsey","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/GGY/ggy_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88154,832,"JEY","Jersey","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88155,832,"JEY","Jersey","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88156,832,"JEY","Jersey","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88157,832,"JEY","Jersey","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88158,832,"JEY","Jersey","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88159,832,"JEY","Jersey","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88160,832,"JEY","Jersey","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88161,832,"JEY","Jersey","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88162,832,"JEY","Jersey","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88163,832,"JEY","Jersey","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88164,832,"JEY","Jersey","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88165,832,"JEY","Jersey","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88166,832,"JEY","Jersey","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88167,832,"JEY","Jersey","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88168,832,"JEY","Jersey","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88169,832,"JEY","Jersey","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88170,832,"JEY","Jersey","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88171,832,"JEY","Jersey","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88172,832,"JEY","Jersey","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88173,832,"JEY","Jersey","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88174,832,"JEY","Jersey","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88175,832,"JEY","Jersey","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88176,832,"JEY","Jersey","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88177,832,"JEY","Jersey","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88178,832,"JEY","Jersey","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88179,832,"JEY","Jersey","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88180,832,"JEY","Jersey","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88181,832,"JEY","Jersey","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88182,832,"JEY","Jersey","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88183,832,"JEY","Jersey","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88184,832,"JEY","Jersey","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88185,832,"JEY","Jersey","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88186,832,"JEY","Jersey","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88187,832,"JEY","Jersey","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88188,832,"JEY","Jersey","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88189,832,"JEY","Jersey","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/JEY/jey_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88190,833,"IMN","Isle of Man","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88191,833,"IMN","Isle of Man","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88192,833,"IMN","Isle of Man","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88193,833,"IMN","Isle of Man","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88194,833,"IMN","Isle of Man","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88195,833,"IMN","Isle of Man","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88196,833,"IMN","Isle of Man","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88197,833,"IMN","Isle of Man","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88198,833,"IMN","Isle of Man","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88199,833,"IMN","Isle of Man","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88200,833,"IMN","Isle of Man","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88201,833,"IMN","Isle of Man","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88202,833,"IMN","Isle of Man","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88203,833,"IMN","Isle of Man","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88204,833,"IMN","Isle of Man","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88205,833,"IMN","Isle of Man","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88206,833,"IMN","Isle of Man","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88207,833,"IMN","Isle of Man","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88208,833,"IMN","Isle of Man","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88209,833,"IMN","Isle of Man","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88210,833,"IMN","Isle of Man","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88211,833,"IMN","Isle of Man","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88212,833,"IMN","Isle of Man","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88213,833,"IMN","Isle of Man","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88214,833,"IMN","Isle of Man","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88215,833,"IMN","Isle of Man","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88216,833,"IMN","Isle of Man","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88217,833,"IMN","Isle of Man","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88218,833,"IMN","Isle of Man","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88219,833,"IMN","Isle of Man","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88220,833,"IMN","Isle of Man","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88221,833,"IMN","Isle of Man","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88222,833,"IMN","Isle of Man","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88223,833,"IMN","Isle of Man","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88224,833,"IMN","Isle of Man","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88225,833,"IMN","Isle of Man","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/IMN/imn_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88226,834,"TZA","Tanzania","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88227,834,"TZA","Tanzania","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88228,834,"TZA","Tanzania","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88229,834,"TZA","Tanzania","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88230,834,"TZA","Tanzania","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88231,834,"TZA","Tanzania","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88232,834,"TZA","Tanzania","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88233,834,"TZA","Tanzania","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88234,834,"TZA","Tanzania","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88235,834,"TZA","Tanzania","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88236,834,"TZA","Tanzania","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88237,834,"TZA","Tanzania","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88238,834,"TZA","Tanzania","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88239,834,"TZA","Tanzania","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88240,834,"TZA","Tanzania","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88241,834,"TZA","Tanzania","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88242,834,"TZA","Tanzania","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88243,834,"TZA","Tanzania","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88244,834,"TZA","Tanzania","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88245,834,"TZA","Tanzania","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88246,834,"TZA","Tanzania","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88247,834,"TZA","Tanzania","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88248,834,"TZA","Tanzania","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88249,834,"TZA","Tanzania","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88250,834,"TZA","Tanzania","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88251,834,"TZA","Tanzania","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88252,834,"TZA","Tanzania","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88253,834,"TZA","Tanzania","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88254,834,"TZA","Tanzania","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88255,834,"TZA","Tanzania","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88256,834,"TZA","Tanzania","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88257,834,"TZA","Tanzania","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88258,834,"TZA","Tanzania","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88259,834,"TZA","Tanzania","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88260,834,"TZA","Tanzania","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88261,834,"TZA","Tanzania","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/TZA/tza_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88262,854,"BFA","Burkina Faso","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88263,854,"BFA","Burkina Faso","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88264,854,"BFA","Burkina Faso","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88265,854,"BFA","Burkina Faso","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88266,854,"BFA","Burkina Faso","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88267,854,"BFA","Burkina Faso","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88268,854,"BFA","Burkina Faso","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88269,854,"BFA","Burkina Faso","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88270,854,"BFA","Burkina Faso","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88271,854,"BFA","Burkina Faso","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88272,854,"BFA","Burkina Faso","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88273,854,"BFA","Burkina Faso","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88274,854,"BFA","Burkina Faso","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88275,854,"BFA","Burkina Faso","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88276,854,"BFA","Burkina Faso","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88277,854,"BFA","Burkina Faso","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88278,854,"BFA","Burkina Faso","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88279,854,"BFA","Burkina Faso","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88280,854,"BFA","Burkina Faso","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88281,854,"BFA","Burkina Faso","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88282,854,"BFA","Burkina Faso","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88283,854,"BFA","Burkina Faso","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88284,854,"BFA","Burkina Faso","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88285,854,"BFA","Burkina Faso","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88286,854,"BFA","Burkina Faso","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88287,854,"BFA","Burkina Faso","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88288,854,"BFA","Burkina Faso","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88289,854,"BFA","Burkina Faso","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88290,854,"BFA","Burkina Faso","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88291,854,"BFA","Burkina Faso","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88292,854,"BFA","Burkina Faso","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88293,854,"BFA","Burkina Faso","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88294,854,"BFA","Burkina Faso","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88295,854,"BFA","Burkina Faso","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88296,854,"BFA","Burkina Faso","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88297,854,"BFA","Burkina Faso","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/BFA/bfa_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88298,858,"URY","Uruguay","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88299,858,"URY","Uruguay","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88300,858,"URY","Uruguay","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88301,858,"URY","Uruguay","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88302,858,"URY","Uruguay","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88303,858,"URY","Uruguay","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88304,858,"URY","Uruguay","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88305,858,"URY","Uruguay","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88306,858,"URY","Uruguay","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88307,858,"URY","Uruguay","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88308,858,"URY","Uruguay","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88309,858,"URY","Uruguay","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88310,858,"URY","Uruguay","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88311,858,"URY","Uruguay","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88312,858,"URY","Uruguay","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88313,858,"URY","Uruguay","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88314,858,"URY","Uruguay","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88315,858,"URY","Uruguay","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88316,858,"URY","Uruguay","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88317,858,"URY","Uruguay","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88318,858,"URY","Uruguay","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88319,858,"URY","Uruguay","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88320,858,"URY","Uruguay","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88321,858,"URY","Uruguay","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88322,858,"URY","Uruguay","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88323,858,"URY","Uruguay","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88324,858,"URY","Uruguay","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88325,858,"URY","Uruguay","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88326,858,"URY","Uruguay","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88327,858,"URY","Uruguay","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88328,858,"URY","Uruguay","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88329,858,"URY","Uruguay","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88330,858,"URY","Uruguay","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88331,858,"URY","Uruguay","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88332,858,"URY","Uruguay","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88333,858,"URY","Uruguay","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/URY/ury_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88334,860,"UZB","Uzbekistan","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88335,860,"UZB","Uzbekistan","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88336,860,"UZB","Uzbekistan","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88337,860,"UZB","Uzbekistan","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88338,860,"UZB","Uzbekistan","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88339,860,"UZB","Uzbekistan","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88340,860,"UZB","Uzbekistan","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88341,860,"UZB","Uzbekistan","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88342,860,"UZB","Uzbekistan","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88343,860,"UZB","Uzbekistan","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88344,860,"UZB","Uzbekistan","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88345,860,"UZB","Uzbekistan","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88346,860,"UZB","Uzbekistan","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88347,860,"UZB","Uzbekistan","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88348,860,"UZB","Uzbekistan","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88349,860,"UZB","Uzbekistan","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88350,860,"UZB","Uzbekistan","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88351,860,"UZB","Uzbekistan","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88352,860,"UZB","Uzbekistan","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88353,860,"UZB","Uzbekistan","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88354,860,"UZB","Uzbekistan","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88355,860,"UZB","Uzbekistan","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88356,860,"UZB","Uzbekistan","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88357,860,"UZB","Uzbekistan","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88358,860,"UZB","Uzbekistan","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88359,860,"UZB","Uzbekistan","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88360,860,"UZB","Uzbekistan","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88361,860,"UZB","Uzbekistan","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88362,860,"UZB","Uzbekistan","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88363,860,"UZB","Uzbekistan","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88364,860,"UZB","Uzbekistan","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88365,860,"UZB","Uzbekistan","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88366,860,"UZB","Uzbekistan","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88367,860,"UZB","Uzbekistan","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88368,860,"UZB","Uzbekistan","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88369,860,"UZB","Uzbekistan","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/UZB/uzb_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88370,862,"VEN","Venezuela","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88371,862,"VEN","Venezuela","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88372,862,"VEN","Venezuela","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88373,862,"VEN","Venezuela","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88374,862,"VEN","Venezuela","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88375,862,"VEN","Venezuela","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88376,862,"VEN","Venezuela","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88377,862,"VEN","Venezuela","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88378,862,"VEN","Venezuela","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88379,862,"VEN","Venezuela","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88380,862,"VEN","Venezuela","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88381,862,"VEN","Venezuela","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88382,862,"VEN","Venezuela","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88383,862,"VEN","Venezuela","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88384,862,"VEN","Venezuela","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88385,862,"VEN","Venezuela","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88386,862,"VEN","Venezuela","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88387,862,"VEN","Venezuela","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88388,862,"VEN","Venezuela","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88389,862,"VEN","Venezuela","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88390,862,"VEN","Venezuela","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88391,862,"VEN","Venezuela","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88392,862,"VEN","Venezuela","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88393,862,"VEN","Venezuela","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88394,862,"VEN","Venezuela","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88395,862,"VEN","Venezuela","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88396,862,"VEN","Venezuela","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88397,862,"VEN","Venezuela","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88398,862,"VEN","Venezuela","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88399,862,"VEN","Venezuela","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88400,862,"VEN","Venezuela","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88401,862,"VEN","Venezuela","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88402,862,"VEN","Venezuela","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88403,862,"VEN","Venezuela","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88404,862,"VEN","Venezuela","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88405,862,"VEN","Venezuela","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/VEN/ven_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88406,876,"WLF","Wallis and Futuna","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88407,876,"WLF","Wallis and Futuna","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88408,876,"WLF","Wallis and Futuna","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88409,876,"WLF","Wallis and Futuna","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88410,876,"WLF","Wallis and Futuna","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88411,876,"WLF","Wallis and Futuna","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88412,876,"WLF","Wallis and Futuna","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88413,876,"WLF","Wallis and Futuna","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88414,876,"WLF","Wallis and Futuna","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88415,876,"WLF","Wallis and Futuna","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88416,876,"WLF","Wallis and Futuna","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88417,876,"WLF","Wallis and Futuna","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88418,876,"WLF","Wallis and Futuna","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88419,876,"WLF","Wallis and Futuna","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88420,876,"WLF","Wallis and Futuna","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88421,876,"WLF","Wallis and Futuna","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88422,876,"WLF","Wallis and Futuna","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88423,876,"WLF","Wallis and Futuna","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88424,876,"WLF","Wallis and Futuna","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88425,876,"WLF","Wallis and Futuna","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88426,876,"WLF","Wallis and Futuna","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88427,876,"WLF","Wallis and Futuna","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88428,876,"WLF","Wallis and Futuna","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88429,876,"WLF","Wallis and Futuna","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88430,876,"WLF","Wallis and Futuna","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88431,876,"WLF","Wallis and Futuna","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88432,876,"WLF","Wallis and Futuna","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88433,876,"WLF","Wallis and Futuna","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88434,876,"WLF","Wallis and Futuna","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88435,876,"WLF","Wallis and Futuna","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88436,876,"WLF","Wallis and Futuna","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88437,876,"WLF","Wallis and Futuna","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88438,876,"WLF","Wallis and Futuna","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88439,876,"WLF","Wallis and Futuna","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88440,876,"WLF","Wallis and Futuna","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88441,876,"WLF","Wallis and Futuna","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WLF/wlf_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88442,882,"WSM","Samoa","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88443,882,"WSM","Samoa","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88444,882,"WSM","Samoa","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88445,882,"WSM","Samoa","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88446,882,"WSM","Samoa","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88447,882,"WSM","Samoa","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88448,882,"WSM","Samoa","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88449,882,"WSM","Samoa","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88450,882,"WSM","Samoa","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88451,882,"WSM","Samoa","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88452,882,"WSM","Samoa","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88453,882,"WSM","Samoa","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88454,882,"WSM","Samoa","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88455,882,"WSM","Samoa","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88456,882,"WSM","Samoa","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88457,882,"WSM","Samoa","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88458,882,"WSM","Samoa","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88459,882,"WSM","Samoa","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88460,882,"WSM","Samoa","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88461,882,"WSM","Samoa","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88462,882,"WSM","Samoa","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88463,882,"WSM","Samoa","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88464,882,"WSM","Samoa","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88465,882,"WSM","Samoa","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88466,882,"WSM","Samoa","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88467,882,"WSM","Samoa","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88468,882,"WSM","Samoa","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88469,882,"WSM","Samoa","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88470,882,"WSM","Samoa","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88471,882,"WSM","Samoa","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88472,882,"WSM","Samoa","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88473,882,"WSM","Samoa","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88474,882,"WSM","Samoa","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88475,882,"WSM","Samoa","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88476,882,"WSM","Samoa","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88477,882,"WSM","Samoa","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/WSM/wsm_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88478,887,"YEM","Yemen","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88479,887,"YEM","Yemen","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88480,887,"YEM","Yemen","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88481,887,"YEM","Yemen","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88482,887,"YEM","Yemen","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88483,887,"YEM","Yemen","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88484,887,"YEM","Yemen","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88485,887,"YEM","Yemen","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88486,887,"YEM","Yemen","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88487,887,"YEM","Yemen","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88488,887,"YEM","Yemen","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88489,887,"YEM","Yemen","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88490,887,"YEM","Yemen","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88491,887,"YEM","Yemen","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88492,887,"YEM","Yemen","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88493,887,"YEM","Yemen","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88494,887,"YEM","Yemen","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88495,887,"YEM","Yemen","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88496,887,"YEM","Yemen","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88497,887,"YEM","Yemen","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88498,887,"YEM","Yemen","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88499,887,"YEM","Yemen","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88500,887,"YEM","Yemen","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88501,887,"YEM","Yemen","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88502,887,"YEM","Yemen","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88503,887,"YEM","Yemen","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88504,887,"YEM","Yemen","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88505,887,"YEM","Yemen","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88506,887,"YEM","Yemen","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88507,887,"YEM","Yemen","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88508,887,"YEM","Yemen","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88509,887,"YEM","Yemen","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88510,887,"YEM","Yemen","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88511,887,"YEM","Yemen","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88512,887,"YEM","Yemen","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88513,887,"YEM","Yemen","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/YEM/yem_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88514,894,"ZMB","Zambia","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88515,894,"ZMB","Zambia","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88516,894,"ZMB","Zambia","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88517,894,"ZMB","Zambia","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88518,894,"ZMB","Zambia","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88519,894,"ZMB","Zambia","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88520,894,"ZMB","Zambia","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88521,894,"ZMB","Zambia","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88522,894,"ZMB","Zambia","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88523,894,"ZMB","Zambia","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88524,894,"ZMB","Zambia","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88525,894,"ZMB","Zambia","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88526,894,"ZMB","Zambia","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88527,894,"ZMB","Zambia","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88528,894,"ZMB","Zambia","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88529,894,"ZMB","Zambia","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88530,894,"ZMB","Zambia","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88531,894,"ZMB","Zambia","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88532,894,"ZMB","Zambia","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88533,894,"ZMB","Zambia","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88534,894,"ZMB","Zambia","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88535,894,"ZMB","Zambia","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88536,894,"ZMB","Zambia","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88537,894,"ZMB","Zambia","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88538,894,"ZMB","Zambia","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88539,894,"ZMB","Zambia","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88540,894,"ZMB","Zambia","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88541,894,"ZMB","Zambia","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88542,894,"ZMB","Zambia","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88543,894,"ZMB","Zambia","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88544,894,"ZMB","Zambia","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88545,894,"ZMB","Zambia","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88546,894,"ZMB","Zambia","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88547,894,"ZMB","Zambia","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88548,894,"ZMB","Zambia","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88549,894,"ZMB","Zambia","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/ZMB/zmb_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
88550,900,"KOS","Kosovo","agesex_f_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_0_2020_constrained.tif","Estimated 0-12 month old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88551,900,"KOS","Kosovo","agesex_f_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_1_2020_constrained.tif","Estimated 1-4 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88552,900,"KOS","Kosovo","agesex_f_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_5_2020_constrained.tif","Estimated 5-8 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88553,900,"KOS","Kosovo","agesex_f_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_10_2020_constrained.tif","Estimated 10-14 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88554,900,"KOS","Kosovo","agesex_f_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_15_2020_constrained.tif","Estimated 15-19 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88555,900,"KOS","Kosovo","agesex_f_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_20_2020_constrained.tif","Estimated 20-24 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88556,900,"KOS","Kosovo","agesex_f_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_25_2020_constrained.tif","Estimated 25-29 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88557,900,"KOS","Kosovo","agesex_f_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_30_2020_constrained.tif","Estimated 30-34 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88558,900,"KOS","Kosovo","agesex_f_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_35_2020_constrained.tif","Estimated 35-39 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88559,900,"KOS","Kosovo","agesex_f_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_40_2020_constrained.tif","Estimated 40-44 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88560,900,"KOS","Kosovo","agesex_f_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_45_2020_constrained.tif","Estimated 45-49 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88561,900,"KOS","Kosovo","agesex_f_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_50_2020_constrained.tif","Estimated 50-54 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88562,900,"KOS","Kosovo","agesex_f_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_55_2020_constrained.tif","Estimated 55-59 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88563,900,"KOS","Kosovo","agesex_f_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_60_2020_constrained.tif","Estimated 60-64 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88564,900,"KOS","Kosovo","agesex_f_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_65_2020_constrained.tif","Estimated 65-69 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88565,900,"KOS","Kosovo","agesex_f_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_70_2020_constrained.tif","Estimated 70-74 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88566,900,"KOS","Kosovo","agesex_f_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_75_2020_constrained.tif","Estimated 75-79 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88567,900,"KOS","Kosovo","agesex_f_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_f_80_2020_constrained.tif","Estimated 80 year old female per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88568,900,"KOS","Kosovo","agesex_m_0_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_0_2020_constrained.tif","Estimated 0-12 month old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88569,900,"KOS","Kosovo","agesex_m_1_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_1_2020_constrained.tif","Estimated 1-4 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88570,900,"KOS","Kosovo","agesex_m_5_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_5_2020_constrained.tif","Estimated 5-8 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88571,900,"KOS","Kosovo","agesex_m_10_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_10_2020_constrained.tif","Estimated 10-14 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88572,900,"KOS","Kosovo","agesex_m_15_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_15_2020_constrained.tif","Estimated 15-19 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88573,900,"KOS","Kosovo","agesex_m_20_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_20_2020_constrained.tif","Estimated 20-24 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88574,900,"KOS","Kosovo","agesex_m_25_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_25_2020_constrained.tif","Estimated 25-29 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88575,900,"KOS","Kosovo","agesex_m_30_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_30_2020_constrained.tif","Estimated 30-34 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88576,900,"KOS","Kosovo","agesex_m_35_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_35_2020_constrained.tif","Estimated 35-39 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88577,900,"KOS","Kosovo","agesex_m_40_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_40_2020_constrained.tif","Estimated 40-44 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88578,900,"KOS","Kosovo","agesex_m_45_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_45_2020_constrained.tif","Estimated 45-49 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88579,900,"KOS","Kosovo","agesex_m_50_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_50_2020_constrained.tif","Estimated 50-54 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88580,900,"KOS","Kosovo","agesex_m_55_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_55_2020_constrained.tif","Estimated 55-59 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88581,900,"KOS","Kosovo","agesex_m_60_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_60_2020_constrained.tif","Estimated 60-64 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88582,900,"KOS","Kosovo","agesex_m_65_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_65_2020_constrained.tif","Estimated 65-69 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88583,900,"KOS","Kosovo","agesex_m_70_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_70_2020_constrained.tif","Estimated 70-74 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88584,900,"KOS","Kosovo","agesex_m_75_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_75_2020_constrained.tif","Estimated 75-79 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88585,900,"KOS","Kosovo","agesex_m_80_2020_constrained","GIS/AgeSex_structures/Global_2000_2020_Constrained/2020/KOS/kos_m_80_2020_constrained.tif","Estimated 80 year old male per grid-cell  in 2020. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88586,643,"RUS","Russia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88587,643,"RUS","Russia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88588,643,"RUS","Russia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88589,643,"RUS","Russia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88590,643,"RUS","Russia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88591,643,"RUS","Russia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88592,643,"RUS","Russia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88593,643,"RUS","Russia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88594,643,"RUS","Russia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88595,643,"RUS","Russia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88596,643,"RUS","Russia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88597,643,"RUS","Russia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88598,643,"RUS","Russia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88599,643,"RUS","Russia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88600,643,"RUS","Russia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88601,643,"RUS","Russia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88602,643,"RUS","Russia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88603,643,"RUS","Russia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88604,643,"RUS","Russia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88605,643,"RUS","Russia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88606,643,"RUS","Russia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88607,643,"RUS","Russia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88608,643,"RUS","Russia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88609,643,"RUS","Russia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88610,643,"RUS","Russia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88611,643,"RUS","Russia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88612,643,"RUS","Russia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88613,643,"RUS","Russia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88614,643,"RUS","Russia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88615,643,"RUS","Russia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88616,643,"RUS","Russia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88617,643,"RUS","Russia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88618,643,"RUS","Russia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88619,643,"RUS","Russia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88620,643,"RUS","Russia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88621,643,"RUS","Russia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RUS/rus_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88622,360,"IDN","Indonesia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88623,360,"IDN","Indonesia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88624,360,"IDN","Indonesia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88625,360,"IDN","Indonesia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88626,360,"IDN","Indonesia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88627,360,"IDN","Indonesia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88628,360,"IDN","Indonesia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88629,360,"IDN","Indonesia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88630,360,"IDN","Indonesia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88631,360,"IDN","Indonesia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88632,360,"IDN","Indonesia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88633,360,"IDN","Indonesia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88634,360,"IDN","Indonesia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88635,360,"IDN","Indonesia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88636,360,"IDN","Indonesia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88637,360,"IDN","Indonesia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88638,360,"IDN","Indonesia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88639,360,"IDN","Indonesia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88640,360,"IDN","Indonesia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88641,360,"IDN","Indonesia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88642,360,"IDN","Indonesia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88643,360,"IDN","Indonesia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88644,360,"IDN","Indonesia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88645,360,"IDN","Indonesia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88646,360,"IDN","Indonesia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88647,360,"IDN","Indonesia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88648,360,"IDN","Indonesia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88649,360,"IDN","Indonesia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88650,360,"IDN","Indonesia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88651,360,"IDN","Indonesia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88652,360,"IDN","Indonesia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88653,360,"IDN","Indonesia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88654,360,"IDN","Indonesia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88655,360,"IDN","Indonesia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88656,360,"IDN","Indonesia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88657,360,"IDN","Indonesia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IDN/idn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88658,840,"USA","United States","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88659,840,"USA","United States","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88660,840,"USA","United States","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88661,840,"USA","United States","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88662,840,"USA","United States","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88663,840,"USA","United States","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88664,840,"USA","United States","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88665,840,"USA","United States","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88666,840,"USA","United States","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88667,840,"USA","United States","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88668,840,"USA","United States","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88669,840,"USA","United States","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88670,840,"USA","United States","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88671,840,"USA","United States","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88672,840,"USA","United States","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88673,840,"USA","United States","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88674,840,"USA","United States","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88675,840,"USA","United States","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88676,840,"USA","United States","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88677,840,"USA","United States","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88678,840,"USA","United States","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88679,840,"USA","United States","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88680,840,"USA","United States","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88681,840,"USA","United States","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88682,840,"USA","United States","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88683,840,"USA","United States","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88684,840,"USA","United States","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88685,840,"USA","United States","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88686,840,"USA","United States","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88687,840,"USA","United States","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88688,840,"USA","United States","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88689,840,"USA","United States","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88690,840,"USA","United States","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88691,840,"USA","United States","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88692,840,"USA","United States","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88693,840,"USA","United States","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/USA/usa_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88694,850,"VIR","Virgin_Islands_U_S","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88695,850,"VIR","Virgin_Islands_U_S","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88696,850,"VIR","Virgin_Islands_U_S","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88697,850,"VIR","Virgin_Islands_U_S","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88698,850,"VIR","Virgin_Islands_U_S","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88699,850,"VIR","Virgin_Islands_U_S","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88700,850,"VIR","Virgin_Islands_U_S","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88701,850,"VIR","Virgin_Islands_U_S","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88702,850,"VIR","Virgin_Islands_U_S","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88703,850,"VIR","Virgin_Islands_U_S","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88704,850,"VIR","Virgin_Islands_U_S","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88705,850,"VIR","Virgin_Islands_U_S","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88706,850,"VIR","Virgin_Islands_U_S","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88707,850,"VIR","Virgin_Islands_U_S","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88708,850,"VIR","Virgin_Islands_U_S","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88709,850,"VIR","Virgin_Islands_U_S","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88710,850,"VIR","Virgin_Islands_U_S","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88711,850,"VIR","Virgin_Islands_U_S","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88712,850,"VIR","Virgin_Islands_U_S","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88713,850,"VIR","Virgin_Islands_U_S","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88714,850,"VIR","Virgin_Islands_U_S","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88715,850,"VIR","Virgin_Islands_U_S","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88716,850,"VIR","Virgin_Islands_U_S","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88717,850,"VIR","Virgin_Islands_U_S","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88718,850,"VIR","Virgin_Islands_U_S","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88719,850,"VIR","Virgin_Islands_U_S","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88720,850,"VIR","Virgin_Islands_U_S","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88721,850,"VIR","Virgin_Islands_U_S","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88722,850,"VIR","Virgin_Islands_U_S","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88723,850,"VIR","Virgin_Islands_U_S","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88724,850,"VIR","Virgin_Islands_U_S","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88725,850,"VIR","Virgin_Islands_U_S","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88726,850,"VIR","Virgin_Islands_U_S","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88727,850,"VIR","Virgin_Islands_U_S","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88728,850,"VIR","Virgin_Islands_U_S","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88729,850,"VIR","Virgin_Islands_U_S","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VIR/vir_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88730,304,"GRL","Greenland","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88731,304,"GRL","Greenland","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88732,304,"GRL","Greenland","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88733,304,"GRL","Greenland","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88734,304,"GRL","Greenland","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88735,304,"GRL","Greenland","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88736,304,"GRL","Greenland","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88737,304,"GRL","Greenland","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88738,304,"GRL","Greenland","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88739,304,"GRL","Greenland","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88740,304,"GRL","Greenland","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88741,304,"GRL","Greenland","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88742,304,"GRL","Greenland","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88743,304,"GRL","Greenland","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88744,304,"GRL","Greenland","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88745,304,"GRL","Greenland","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88746,304,"GRL","Greenland","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88747,304,"GRL","Greenland","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88748,304,"GRL","Greenland","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88749,304,"GRL","Greenland","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88750,304,"GRL","Greenland","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88751,304,"GRL","Greenland","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88752,304,"GRL","Greenland","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88753,304,"GRL","Greenland","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88754,304,"GRL","Greenland","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88755,304,"GRL","Greenland","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88756,304,"GRL","Greenland","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88757,304,"GRL","Greenland","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88758,304,"GRL","Greenland","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88759,304,"GRL","Greenland","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88760,304,"GRL","Greenland","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88761,304,"GRL","Greenland","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88762,304,"GRL","Greenland","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88763,304,"GRL","Greenland","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88764,304,"GRL","Greenland","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88765,304,"GRL","Greenland","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRL/grl_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88766,156,"CHN","China","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88767,156,"CHN","China","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88768,156,"CHN","China","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88769,156,"CHN","China","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88770,156,"CHN","China","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88771,156,"CHN","China","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88772,156,"CHN","China","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88773,156,"CHN","China","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88774,156,"CHN","China","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88775,156,"CHN","China","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88776,156,"CHN","China","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88777,156,"CHN","China","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88778,156,"CHN","China","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88779,156,"CHN","China","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88780,156,"CHN","China","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88781,156,"CHN","China","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88782,156,"CHN","China","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88783,156,"CHN","China","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88784,156,"CHN","China","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88785,156,"CHN","China","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88786,156,"CHN","China","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88787,156,"CHN","China","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88788,156,"CHN","China","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88789,156,"CHN","China","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88790,156,"CHN","China","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88791,156,"CHN","China","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88792,156,"CHN","China","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88793,156,"CHN","China","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88794,156,"CHN","China","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88795,156,"CHN","China","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88796,156,"CHN","China","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88797,156,"CHN","China","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88798,156,"CHN","China","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88799,156,"CHN","China","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88800,156,"CHN","China","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88801,156,"CHN","China","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHN/chn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88802,36,"AUS","Australia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88803,36,"AUS","Australia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88804,36,"AUS","Australia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88805,36,"AUS","Australia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88806,36,"AUS","Australia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88807,36,"AUS","Australia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88808,36,"AUS","Australia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88809,36,"AUS","Australia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88810,36,"AUS","Australia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88811,36,"AUS","Australia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88812,36,"AUS","Australia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88813,36,"AUS","Australia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88814,36,"AUS","Australia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88815,36,"AUS","Australia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88816,36,"AUS","Australia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88817,36,"AUS","Australia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88818,36,"AUS","Australia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88819,36,"AUS","Australia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88820,36,"AUS","Australia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88821,36,"AUS","Australia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88822,36,"AUS","Australia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88823,36,"AUS","Australia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88824,36,"AUS","Australia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88825,36,"AUS","Australia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88826,36,"AUS","Australia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88827,36,"AUS","Australia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88828,36,"AUS","Australia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88829,36,"AUS","Australia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88830,36,"AUS","Australia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88831,36,"AUS","Australia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88832,36,"AUS","Australia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88833,36,"AUS","Australia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88834,36,"AUS","Australia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88835,36,"AUS","Australia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88836,36,"AUS","Australia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88837,36,"AUS","Australia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUS/aus_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88838,76,"BRA","Brazil","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88839,76,"BRA","Brazil","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88840,76,"BRA","Brazil","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88841,76,"BRA","Brazil","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88842,76,"BRA","Brazil","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88843,76,"BRA","Brazil","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88844,76,"BRA","Brazil","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88845,76,"BRA","Brazil","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88846,76,"BRA","Brazil","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88847,76,"BRA","Brazil","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88848,76,"BRA","Brazil","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88849,76,"BRA","Brazil","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88850,76,"BRA","Brazil","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88851,76,"BRA","Brazil","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88852,76,"BRA","Brazil","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88853,76,"BRA","Brazil","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88854,76,"BRA","Brazil","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88855,76,"BRA","Brazil","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88856,76,"BRA","Brazil","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88857,76,"BRA","Brazil","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88858,76,"BRA","Brazil","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88859,76,"BRA","Brazil","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88860,76,"BRA","Brazil","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88861,76,"BRA","Brazil","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88862,76,"BRA","Brazil","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88863,76,"BRA","Brazil","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88864,76,"BRA","Brazil","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88865,76,"BRA","Brazil","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88866,76,"BRA","Brazil","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88867,76,"BRA","Brazil","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88868,76,"BRA","Brazil","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88869,76,"BRA","Brazil","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88870,76,"BRA","Brazil","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88871,76,"BRA","Brazil","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88872,76,"BRA","Brazil","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88873,76,"BRA","Brazil","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRA/bra_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88874,124,"CAN","Canada","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88875,124,"CAN","Canada","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88876,124,"CAN","Canada","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88877,124,"CAN","Canada","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88878,124,"CAN","Canada","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88879,124,"CAN","Canada","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88880,124,"CAN","Canada","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88881,124,"CAN","Canada","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88882,124,"CAN","Canada","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88883,124,"CAN","Canada","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88884,124,"CAN","Canada","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88885,124,"CAN","Canada","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88886,124,"CAN","Canada","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88887,124,"CAN","Canada","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88888,124,"CAN","Canada","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88889,124,"CAN","Canada","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88890,124,"CAN","Canada","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88891,124,"CAN","Canada","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88892,124,"CAN","Canada","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88893,124,"CAN","Canada","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88894,124,"CAN","Canada","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88895,124,"CAN","Canada","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88896,124,"CAN","Canada","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88897,124,"CAN","Canada","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88898,124,"CAN","Canada","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88899,124,"CAN","Canada","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88900,124,"CAN","Canada","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88901,124,"CAN","Canada","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88902,124,"CAN","Canada","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88903,124,"CAN","Canada","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88904,124,"CAN","Canada","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88905,124,"CAN","Canada","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88906,124,"CAN","Canada","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88907,124,"CAN","Canada","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88908,124,"CAN","Canada","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88909,124,"CAN","Canada","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAN/can_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88910,152,"CHL","Chile","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88911,152,"CHL","Chile","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88912,152,"CHL","Chile","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88913,152,"CHL","Chile","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88914,152,"CHL","Chile","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88915,152,"CHL","Chile","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88916,152,"CHL","Chile","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88917,152,"CHL","Chile","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88918,152,"CHL","Chile","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88919,152,"CHL","Chile","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88920,152,"CHL","Chile","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88921,152,"CHL","Chile","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88922,152,"CHL","Chile","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88923,152,"CHL","Chile","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88924,152,"CHL","Chile","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88925,152,"CHL","Chile","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88926,152,"CHL","Chile","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88927,152,"CHL","Chile","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88928,152,"CHL","Chile","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88929,152,"CHL","Chile","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88930,152,"CHL","Chile","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88931,152,"CHL","Chile","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88932,152,"CHL","Chile","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88933,152,"CHL","Chile","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88934,152,"CHL","Chile","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88935,152,"CHL","Chile","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88936,152,"CHL","Chile","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88937,152,"CHL","Chile","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88938,152,"CHL","Chile","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88939,152,"CHL","Chile","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88940,152,"CHL","Chile","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88941,152,"CHL","Chile","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88942,152,"CHL","Chile","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88943,152,"CHL","Chile","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88944,152,"CHL","Chile","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88945,152,"CHL","Chile","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHL/chl_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88946,4,"AFG","Afghanistan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88947,4,"AFG","Afghanistan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88948,4,"AFG","Afghanistan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88949,4,"AFG","Afghanistan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88950,4,"AFG","Afghanistan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88951,4,"AFG","Afghanistan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88952,4,"AFG","Afghanistan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88953,4,"AFG","Afghanistan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88954,4,"AFG","Afghanistan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88955,4,"AFG","Afghanistan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88956,4,"AFG","Afghanistan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88957,4,"AFG","Afghanistan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88958,4,"AFG","Afghanistan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88959,4,"AFG","Afghanistan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88960,4,"AFG","Afghanistan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88961,4,"AFG","Afghanistan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88962,4,"AFG","Afghanistan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88963,4,"AFG","Afghanistan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88964,4,"AFG","Afghanistan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88965,4,"AFG","Afghanistan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88966,4,"AFG","Afghanistan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88967,4,"AFG","Afghanistan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88968,4,"AFG","Afghanistan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88969,4,"AFG","Afghanistan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88970,4,"AFG","Afghanistan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88971,4,"AFG","Afghanistan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88972,4,"AFG","Afghanistan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88973,4,"AFG","Afghanistan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88974,4,"AFG","Afghanistan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88975,4,"AFG","Afghanistan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88976,4,"AFG","Afghanistan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88977,4,"AFG","Afghanistan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88978,4,"AFG","Afghanistan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88979,4,"AFG","Afghanistan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88980,4,"AFG","Afghanistan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88981,4,"AFG","Afghanistan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AFG/afg_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88982,8,"ALB","Albania","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88983,8,"ALB","Albania","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88984,8,"ALB","Albania","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88985,8,"ALB","Albania","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88986,8,"ALB","Albania","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88987,8,"ALB","Albania","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88988,8,"ALB","Albania","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88989,8,"ALB","Albania","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88990,8,"ALB","Albania","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88991,8,"ALB","Albania","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88992,8,"ALB","Albania","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88993,8,"ALB","Albania","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88994,8,"ALB","Albania","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88995,8,"ALB","Albania","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88996,8,"ALB","Albania","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88997,8,"ALB","Albania","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88998,8,"ALB","Albania","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
88999,8,"ALB","Albania","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89000,8,"ALB","Albania","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89001,8,"ALB","Albania","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89002,8,"ALB","Albania","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89003,8,"ALB","Albania","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89004,8,"ALB","Albania","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89005,8,"ALB","Albania","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89006,8,"ALB","Albania","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89007,8,"ALB","Albania","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89008,8,"ALB","Albania","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89009,8,"ALB","Albania","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89010,8,"ALB","Albania","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89011,8,"ALB","Albania","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89012,8,"ALB","Albania","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89013,8,"ALB","Albania","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89014,8,"ALB","Albania","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89015,8,"ALB","Albania","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89016,8,"ALB","Albania","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89017,8,"ALB","Albania","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALB/alb_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89018,12,"DZA","Algeria","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89019,12,"DZA","Algeria","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89020,12,"DZA","Algeria","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89021,12,"DZA","Algeria","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89022,12,"DZA","Algeria","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89023,12,"DZA","Algeria","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89024,12,"DZA","Algeria","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89025,12,"DZA","Algeria","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89026,12,"DZA","Algeria","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89027,12,"DZA","Algeria","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89028,12,"DZA","Algeria","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89029,12,"DZA","Algeria","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89030,12,"DZA","Algeria","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89031,12,"DZA","Algeria","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89032,12,"DZA","Algeria","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89033,12,"DZA","Algeria","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89034,12,"DZA","Algeria","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89035,12,"DZA","Algeria","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89036,12,"DZA","Algeria","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89037,12,"DZA","Algeria","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89038,12,"DZA","Algeria","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89039,12,"DZA","Algeria","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89040,12,"DZA","Algeria","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89041,12,"DZA","Algeria","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89042,12,"DZA","Algeria","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89043,12,"DZA","Algeria","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89044,12,"DZA","Algeria","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89045,12,"DZA","Algeria","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89046,12,"DZA","Algeria","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89047,12,"DZA","Algeria","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89048,12,"DZA","Algeria","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89049,12,"DZA","Algeria","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89050,12,"DZA","Algeria","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89051,12,"DZA","Algeria","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89052,12,"DZA","Algeria","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89053,12,"DZA","Algeria","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DZA/dza_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89054,16,"ASM","American Samoa","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89055,16,"ASM","American Samoa","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89056,16,"ASM","American Samoa","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89057,16,"ASM","American Samoa","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89058,16,"ASM","American Samoa","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89059,16,"ASM","American Samoa","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89060,16,"ASM","American Samoa","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89061,16,"ASM","American Samoa","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89062,16,"ASM","American Samoa","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89063,16,"ASM","American Samoa","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89064,16,"ASM","American Samoa","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89065,16,"ASM","American Samoa","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89066,16,"ASM","American Samoa","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89067,16,"ASM","American Samoa","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89068,16,"ASM","American Samoa","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89069,16,"ASM","American Samoa","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89070,16,"ASM","American Samoa","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89071,16,"ASM","American Samoa","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89072,16,"ASM","American Samoa","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89073,16,"ASM","American Samoa","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89074,16,"ASM","American Samoa","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89075,16,"ASM","American Samoa","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89076,16,"ASM","American Samoa","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89077,16,"ASM","American Samoa","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89078,16,"ASM","American Samoa","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89079,16,"ASM","American Samoa","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89080,16,"ASM","American Samoa","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89081,16,"ASM","American Samoa","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89082,16,"ASM","American Samoa","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89083,16,"ASM","American Samoa","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89084,16,"ASM","American Samoa","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89085,16,"ASM","American Samoa","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89086,16,"ASM","American Samoa","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89087,16,"ASM","American Samoa","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89088,16,"ASM","American Samoa","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89089,16,"ASM","American Samoa","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ASM/asm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89090,20,"AND","Andorra","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89091,20,"AND","Andorra","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89092,20,"AND","Andorra","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89093,20,"AND","Andorra","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89094,20,"AND","Andorra","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89095,20,"AND","Andorra","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89096,20,"AND","Andorra","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89097,20,"AND","Andorra","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89098,20,"AND","Andorra","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89099,20,"AND","Andorra","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89100,20,"AND","Andorra","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89101,20,"AND","Andorra","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89102,20,"AND","Andorra","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89103,20,"AND","Andorra","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89104,20,"AND","Andorra","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89105,20,"AND","Andorra","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89106,20,"AND","Andorra","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89107,20,"AND","Andorra","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89108,20,"AND","Andorra","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89109,20,"AND","Andorra","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89110,20,"AND","Andorra","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89111,20,"AND","Andorra","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89112,20,"AND","Andorra","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89113,20,"AND","Andorra","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89114,20,"AND","Andorra","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89115,20,"AND","Andorra","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89116,20,"AND","Andorra","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89117,20,"AND","Andorra","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89118,20,"AND","Andorra","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89119,20,"AND","Andorra","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89120,20,"AND","Andorra","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89121,20,"AND","Andorra","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89122,20,"AND","Andorra","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89123,20,"AND","Andorra","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89124,20,"AND","Andorra","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89125,20,"AND","Andorra","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AND/and_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89126,24,"AGO","Angola","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89127,24,"AGO","Angola","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89128,24,"AGO","Angola","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89129,24,"AGO","Angola","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89130,24,"AGO","Angola","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89131,24,"AGO","Angola","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89132,24,"AGO","Angola","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89133,24,"AGO","Angola","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89134,24,"AGO","Angola","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89135,24,"AGO","Angola","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89136,24,"AGO","Angola","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89137,24,"AGO","Angola","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89138,24,"AGO","Angola","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89139,24,"AGO","Angola","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89140,24,"AGO","Angola","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89141,24,"AGO","Angola","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89142,24,"AGO","Angola","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89143,24,"AGO","Angola","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89144,24,"AGO","Angola","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89145,24,"AGO","Angola","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89146,24,"AGO","Angola","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89147,24,"AGO","Angola","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89148,24,"AGO","Angola","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89149,24,"AGO","Angola","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89150,24,"AGO","Angola","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89151,24,"AGO","Angola","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89152,24,"AGO","Angola","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89153,24,"AGO","Angola","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89154,24,"AGO","Angola","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89155,24,"AGO","Angola","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89156,24,"AGO","Angola","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89157,24,"AGO","Angola","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89158,24,"AGO","Angola","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89159,24,"AGO","Angola","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89160,24,"AGO","Angola","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89161,24,"AGO","Angola","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AGO/ago_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89162,28,"ATG","Antigua and Barbuda","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89163,28,"ATG","Antigua and Barbuda","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89164,28,"ATG","Antigua and Barbuda","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89165,28,"ATG","Antigua and Barbuda","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89166,28,"ATG","Antigua and Barbuda","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89167,28,"ATG","Antigua and Barbuda","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89168,28,"ATG","Antigua and Barbuda","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89169,28,"ATG","Antigua and Barbuda","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89170,28,"ATG","Antigua and Barbuda","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89171,28,"ATG","Antigua and Barbuda","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89172,28,"ATG","Antigua and Barbuda","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89173,28,"ATG","Antigua and Barbuda","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89174,28,"ATG","Antigua and Barbuda","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89175,28,"ATG","Antigua and Barbuda","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89176,28,"ATG","Antigua and Barbuda","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89177,28,"ATG","Antigua and Barbuda","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89178,28,"ATG","Antigua and Barbuda","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89179,28,"ATG","Antigua and Barbuda","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89180,28,"ATG","Antigua and Barbuda","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89181,28,"ATG","Antigua and Barbuda","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89182,28,"ATG","Antigua and Barbuda","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89183,28,"ATG","Antigua and Barbuda","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89184,28,"ATG","Antigua and Barbuda","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89185,28,"ATG","Antigua and Barbuda","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89186,28,"ATG","Antigua and Barbuda","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89187,28,"ATG","Antigua and Barbuda","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89188,28,"ATG","Antigua and Barbuda","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89189,28,"ATG","Antigua and Barbuda","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89190,28,"ATG","Antigua and Barbuda","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89191,28,"ATG","Antigua and Barbuda","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89192,28,"ATG","Antigua and Barbuda","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89193,28,"ATG","Antigua and Barbuda","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89194,28,"ATG","Antigua and Barbuda","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89195,28,"ATG","Antigua and Barbuda","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89196,28,"ATG","Antigua and Barbuda","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89197,28,"ATG","Antigua and Barbuda","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ATG/atg_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89198,31,"AZE","Azerbaijan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89199,31,"AZE","Azerbaijan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89200,31,"AZE","Azerbaijan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89201,31,"AZE","Azerbaijan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89202,31,"AZE","Azerbaijan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89203,31,"AZE","Azerbaijan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89204,31,"AZE","Azerbaijan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89205,31,"AZE","Azerbaijan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89206,31,"AZE","Azerbaijan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89207,31,"AZE","Azerbaijan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89208,31,"AZE","Azerbaijan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89209,31,"AZE","Azerbaijan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89210,31,"AZE","Azerbaijan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89211,31,"AZE","Azerbaijan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89212,31,"AZE","Azerbaijan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89213,31,"AZE","Azerbaijan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89214,31,"AZE","Azerbaijan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89215,31,"AZE","Azerbaijan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89216,31,"AZE","Azerbaijan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89217,31,"AZE","Azerbaijan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89218,31,"AZE","Azerbaijan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89219,31,"AZE","Azerbaijan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89220,31,"AZE","Azerbaijan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89221,31,"AZE","Azerbaijan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89222,31,"AZE","Azerbaijan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89223,31,"AZE","Azerbaijan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89224,31,"AZE","Azerbaijan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89225,31,"AZE","Azerbaijan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89226,31,"AZE","Azerbaijan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89227,31,"AZE","Azerbaijan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89228,31,"AZE","Azerbaijan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89229,31,"AZE","Azerbaijan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89230,31,"AZE","Azerbaijan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89231,31,"AZE","Azerbaijan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89232,31,"AZE","Azerbaijan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89233,31,"AZE","Azerbaijan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AZE/aze_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89234,32,"ARG","Argentina","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89235,32,"ARG","Argentina","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89236,32,"ARG","Argentina","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89237,32,"ARG","Argentina","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89238,32,"ARG","Argentina","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89239,32,"ARG","Argentina","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89240,32,"ARG","Argentina","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89241,32,"ARG","Argentina","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89242,32,"ARG","Argentina","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89243,32,"ARG","Argentina","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89244,32,"ARG","Argentina","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89245,32,"ARG","Argentina","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89246,32,"ARG","Argentina","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89247,32,"ARG","Argentina","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89248,32,"ARG","Argentina","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89249,32,"ARG","Argentina","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89250,32,"ARG","Argentina","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89251,32,"ARG","Argentina","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89252,32,"ARG","Argentina","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89253,32,"ARG","Argentina","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89254,32,"ARG","Argentina","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89255,32,"ARG","Argentina","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89256,32,"ARG","Argentina","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89257,32,"ARG","Argentina","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89258,32,"ARG","Argentina","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89259,32,"ARG","Argentina","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89260,32,"ARG","Argentina","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89261,32,"ARG","Argentina","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89262,32,"ARG","Argentina","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89263,32,"ARG","Argentina","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89264,32,"ARG","Argentina","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89265,32,"ARG","Argentina","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89266,32,"ARG","Argentina","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89267,32,"ARG","Argentina","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89268,32,"ARG","Argentina","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89269,32,"ARG","Argentina","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARG/arg_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89270,40,"AUT","Austria","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89271,40,"AUT","Austria","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89272,40,"AUT","Austria","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89273,40,"AUT","Austria","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89274,40,"AUT","Austria","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89275,40,"AUT","Austria","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89276,40,"AUT","Austria","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89277,40,"AUT","Austria","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89278,40,"AUT","Austria","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89279,40,"AUT","Austria","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89280,40,"AUT","Austria","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89281,40,"AUT","Austria","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89282,40,"AUT","Austria","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89283,40,"AUT","Austria","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89284,40,"AUT","Austria","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89285,40,"AUT","Austria","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89286,40,"AUT","Austria","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89287,40,"AUT","Austria","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89288,40,"AUT","Austria","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89289,40,"AUT","Austria","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89290,40,"AUT","Austria","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89291,40,"AUT","Austria","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89292,40,"AUT","Austria","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89293,40,"AUT","Austria","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89294,40,"AUT","Austria","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89295,40,"AUT","Austria","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89296,40,"AUT","Austria","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89297,40,"AUT","Austria","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89298,40,"AUT","Austria","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89299,40,"AUT","Austria","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89300,40,"AUT","Austria","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89301,40,"AUT","Austria","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89302,40,"AUT","Austria","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89303,40,"AUT","Austria","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89304,40,"AUT","Austria","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89305,40,"AUT","Austria","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AUT/aut_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89306,44,"BHS","Bahamas","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89307,44,"BHS","Bahamas","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89308,44,"BHS","Bahamas","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89309,44,"BHS","Bahamas","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89310,44,"BHS","Bahamas","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89311,44,"BHS","Bahamas","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89312,44,"BHS","Bahamas","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89313,44,"BHS","Bahamas","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89314,44,"BHS","Bahamas","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89315,44,"BHS","Bahamas","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89316,44,"BHS","Bahamas","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89317,44,"BHS","Bahamas","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89318,44,"BHS","Bahamas","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89319,44,"BHS","Bahamas","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89320,44,"BHS","Bahamas","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89321,44,"BHS","Bahamas","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89322,44,"BHS","Bahamas","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89323,44,"BHS","Bahamas","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89324,44,"BHS","Bahamas","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89325,44,"BHS","Bahamas","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89326,44,"BHS","Bahamas","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89327,44,"BHS","Bahamas","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89328,44,"BHS","Bahamas","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89329,44,"BHS","Bahamas","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89330,44,"BHS","Bahamas","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89331,44,"BHS","Bahamas","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89332,44,"BHS","Bahamas","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89333,44,"BHS","Bahamas","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89334,44,"BHS","Bahamas","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89335,44,"BHS","Bahamas","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89336,44,"BHS","Bahamas","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89337,44,"BHS","Bahamas","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89338,44,"BHS","Bahamas","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89339,44,"BHS","Bahamas","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89340,44,"BHS","Bahamas","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89341,44,"BHS","Bahamas","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHS/bhs_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89342,48,"BHR","Bahrain","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89343,48,"BHR","Bahrain","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89344,48,"BHR","Bahrain","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89345,48,"BHR","Bahrain","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89346,48,"BHR","Bahrain","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89347,48,"BHR","Bahrain","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89348,48,"BHR","Bahrain","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89349,48,"BHR","Bahrain","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89350,48,"BHR","Bahrain","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89351,48,"BHR","Bahrain","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89352,48,"BHR","Bahrain","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89353,48,"BHR","Bahrain","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89354,48,"BHR","Bahrain","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89355,48,"BHR","Bahrain","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89356,48,"BHR","Bahrain","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89357,48,"BHR","Bahrain","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89358,48,"BHR","Bahrain","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89359,48,"BHR","Bahrain","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89360,48,"BHR","Bahrain","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89361,48,"BHR","Bahrain","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89362,48,"BHR","Bahrain","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89363,48,"BHR","Bahrain","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89364,48,"BHR","Bahrain","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89365,48,"BHR","Bahrain","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89366,48,"BHR","Bahrain","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89367,48,"BHR","Bahrain","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89368,48,"BHR","Bahrain","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89369,48,"BHR","Bahrain","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89370,48,"BHR","Bahrain","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89371,48,"BHR","Bahrain","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89372,48,"BHR","Bahrain","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89373,48,"BHR","Bahrain","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89374,48,"BHR","Bahrain","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89375,48,"BHR","Bahrain","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89376,48,"BHR","Bahrain","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89377,48,"BHR","Bahrain","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BHR/bhr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89378,50,"BGD","Bangladesh","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89379,50,"BGD","Bangladesh","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89380,50,"BGD","Bangladesh","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89381,50,"BGD","Bangladesh","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89382,50,"BGD","Bangladesh","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89383,50,"BGD","Bangladesh","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89384,50,"BGD","Bangladesh","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89385,50,"BGD","Bangladesh","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89386,50,"BGD","Bangladesh","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89387,50,"BGD","Bangladesh","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89388,50,"BGD","Bangladesh","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89389,50,"BGD","Bangladesh","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89390,50,"BGD","Bangladesh","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89391,50,"BGD","Bangladesh","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89392,50,"BGD","Bangladesh","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89393,50,"BGD","Bangladesh","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89394,50,"BGD","Bangladesh","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89395,50,"BGD","Bangladesh","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89396,50,"BGD","Bangladesh","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89397,50,"BGD","Bangladesh","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89398,50,"BGD","Bangladesh","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89399,50,"BGD","Bangladesh","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89400,50,"BGD","Bangladesh","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89401,50,"BGD","Bangladesh","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89402,50,"BGD","Bangladesh","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89403,50,"BGD","Bangladesh","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89404,50,"BGD","Bangladesh","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89405,50,"BGD","Bangladesh","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89406,50,"BGD","Bangladesh","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89407,50,"BGD","Bangladesh","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89408,50,"BGD","Bangladesh","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89409,50,"BGD","Bangladesh","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89410,50,"BGD","Bangladesh","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89411,50,"BGD","Bangladesh","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89412,50,"BGD","Bangladesh","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89413,50,"BGD","Bangladesh","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGD/bgd_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89414,51,"ARM","Armenia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89415,51,"ARM","Armenia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89416,51,"ARM","Armenia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89417,51,"ARM","Armenia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89418,51,"ARM","Armenia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89419,51,"ARM","Armenia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89420,51,"ARM","Armenia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89421,51,"ARM","Armenia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89422,51,"ARM","Armenia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89423,51,"ARM","Armenia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89424,51,"ARM","Armenia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89425,51,"ARM","Armenia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89426,51,"ARM","Armenia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89427,51,"ARM","Armenia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89428,51,"ARM","Armenia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89429,51,"ARM","Armenia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89430,51,"ARM","Armenia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89431,51,"ARM","Armenia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89432,51,"ARM","Armenia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89433,51,"ARM","Armenia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89434,51,"ARM","Armenia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89435,51,"ARM","Armenia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89436,51,"ARM","Armenia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89437,51,"ARM","Armenia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89438,51,"ARM","Armenia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89439,51,"ARM","Armenia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89440,51,"ARM","Armenia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89441,51,"ARM","Armenia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89442,51,"ARM","Armenia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89443,51,"ARM","Armenia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89444,51,"ARM","Armenia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89445,51,"ARM","Armenia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89446,51,"ARM","Armenia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89447,51,"ARM","Armenia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89448,51,"ARM","Armenia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89449,51,"ARM","Armenia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARM/arm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89450,52,"BRB","Barbados","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89451,52,"BRB","Barbados","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89452,52,"BRB","Barbados","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89453,52,"BRB","Barbados","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89454,52,"BRB","Barbados","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89455,52,"BRB","Barbados","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89456,52,"BRB","Barbados","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89457,52,"BRB","Barbados","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89458,52,"BRB","Barbados","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89459,52,"BRB","Barbados","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89460,52,"BRB","Barbados","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89461,52,"BRB","Barbados","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89462,52,"BRB","Barbados","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89463,52,"BRB","Barbados","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89464,52,"BRB","Barbados","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89465,52,"BRB","Barbados","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89466,52,"BRB","Barbados","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89467,52,"BRB","Barbados","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89468,52,"BRB","Barbados","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89469,52,"BRB","Barbados","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89470,52,"BRB","Barbados","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89471,52,"BRB","Barbados","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89472,52,"BRB","Barbados","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89473,52,"BRB","Barbados","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89474,52,"BRB","Barbados","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89475,52,"BRB","Barbados","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89476,52,"BRB","Barbados","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89477,52,"BRB","Barbados","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89478,52,"BRB","Barbados","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89479,52,"BRB","Barbados","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89480,52,"BRB","Barbados","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89481,52,"BRB","Barbados","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89482,52,"BRB","Barbados","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89483,52,"BRB","Barbados","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89484,52,"BRB","Barbados","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89485,52,"BRB","Barbados","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRB/brb_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89486,56,"BEL","Belgium","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89487,56,"BEL","Belgium","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89488,56,"BEL","Belgium","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89489,56,"BEL","Belgium","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89490,56,"BEL","Belgium","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89491,56,"BEL","Belgium","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89492,56,"BEL","Belgium","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89493,56,"BEL","Belgium","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89494,56,"BEL","Belgium","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89495,56,"BEL","Belgium","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89496,56,"BEL","Belgium","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89497,56,"BEL","Belgium","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89498,56,"BEL","Belgium","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89499,56,"BEL","Belgium","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89500,56,"BEL","Belgium","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89501,56,"BEL","Belgium","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89502,56,"BEL","Belgium","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89503,56,"BEL","Belgium","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89504,56,"BEL","Belgium","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89505,56,"BEL","Belgium","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89506,56,"BEL","Belgium","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89507,56,"BEL","Belgium","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89508,56,"BEL","Belgium","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89509,56,"BEL","Belgium","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89510,56,"BEL","Belgium","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89511,56,"BEL","Belgium","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89512,56,"BEL","Belgium","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89513,56,"BEL","Belgium","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89514,56,"BEL","Belgium","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89515,56,"BEL","Belgium","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89516,56,"BEL","Belgium","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89517,56,"BEL","Belgium","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89518,56,"BEL","Belgium","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89519,56,"BEL","Belgium","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89520,56,"BEL","Belgium","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89521,56,"BEL","Belgium","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEL/bel_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89522,60,"BMU","Bermuda","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89523,60,"BMU","Bermuda","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89524,60,"BMU","Bermuda","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89525,60,"BMU","Bermuda","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89526,60,"BMU","Bermuda","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89527,60,"BMU","Bermuda","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89528,60,"BMU","Bermuda","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89529,60,"BMU","Bermuda","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89530,60,"BMU","Bermuda","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89531,60,"BMU","Bermuda","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89532,60,"BMU","Bermuda","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89533,60,"BMU","Bermuda","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89534,60,"BMU","Bermuda","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89535,60,"BMU","Bermuda","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89536,60,"BMU","Bermuda","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89537,60,"BMU","Bermuda","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89538,60,"BMU","Bermuda","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89539,60,"BMU","Bermuda","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89540,60,"BMU","Bermuda","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89541,60,"BMU","Bermuda","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89542,60,"BMU","Bermuda","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89543,60,"BMU","Bermuda","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89544,60,"BMU","Bermuda","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89545,60,"BMU","Bermuda","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89546,60,"BMU","Bermuda","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89547,60,"BMU","Bermuda","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89548,60,"BMU","Bermuda","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89549,60,"BMU","Bermuda","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89550,60,"BMU","Bermuda","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89551,60,"BMU","Bermuda","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89552,60,"BMU","Bermuda","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89553,60,"BMU","Bermuda","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89554,60,"BMU","Bermuda","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89555,60,"BMU","Bermuda","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89556,60,"BMU","Bermuda","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89557,60,"BMU","Bermuda","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BMU/bmu_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89558,64,"BTN","Bhutan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89559,64,"BTN","Bhutan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89560,64,"BTN","Bhutan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89561,64,"BTN","Bhutan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89562,64,"BTN","Bhutan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89563,64,"BTN","Bhutan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89564,64,"BTN","Bhutan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89565,64,"BTN","Bhutan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89566,64,"BTN","Bhutan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89567,64,"BTN","Bhutan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89568,64,"BTN","Bhutan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89569,64,"BTN","Bhutan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89570,64,"BTN","Bhutan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89571,64,"BTN","Bhutan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89572,64,"BTN","Bhutan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89573,64,"BTN","Bhutan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89574,64,"BTN","Bhutan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89575,64,"BTN","Bhutan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89576,64,"BTN","Bhutan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89577,64,"BTN","Bhutan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89578,64,"BTN","Bhutan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89579,64,"BTN","Bhutan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89580,64,"BTN","Bhutan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89581,64,"BTN","Bhutan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89582,64,"BTN","Bhutan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89583,64,"BTN","Bhutan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89584,64,"BTN","Bhutan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89585,64,"BTN","Bhutan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89586,64,"BTN","Bhutan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89587,64,"BTN","Bhutan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89588,64,"BTN","Bhutan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89589,64,"BTN","Bhutan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89590,64,"BTN","Bhutan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89591,64,"BTN","Bhutan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89592,64,"BTN","Bhutan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89593,64,"BTN","Bhutan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BTN/btn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89594,68,"BOL","Bolivia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89595,68,"BOL","Bolivia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89596,68,"BOL","Bolivia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89597,68,"BOL","Bolivia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89598,68,"BOL","Bolivia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89599,68,"BOL","Bolivia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89600,68,"BOL","Bolivia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89601,68,"BOL","Bolivia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89602,68,"BOL","Bolivia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89603,68,"BOL","Bolivia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89604,68,"BOL","Bolivia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89605,68,"BOL","Bolivia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89606,68,"BOL","Bolivia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89607,68,"BOL","Bolivia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89608,68,"BOL","Bolivia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89609,68,"BOL","Bolivia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89610,68,"BOL","Bolivia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89611,68,"BOL","Bolivia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89612,68,"BOL","Bolivia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89613,68,"BOL","Bolivia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89614,68,"BOL","Bolivia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89615,68,"BOL","Bolivia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89616,68,"BOL","Bolivia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89617,68,"BOL","Bolivia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89618,68,"BOL","Bolivia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89619,68,"BOL","Bolivia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89620,68,"BOL","Bolivia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89621,68,"BOL","Bolivia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89622,68,"BOL","Bolivia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89623,68,"BOL","Bolivia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89624,68,"BOL","Bolivia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89625,68,"BOL","Bolivia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89626,68,"BOL","Bolivia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89627,68,"BOL","Bolivia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89628,68,"BOL","Bolivia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89629,68,"BOL","Bolivia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BOL/bol_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89630,70,"BIH","Bosnia and Herzegovina","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89631,70,"BIH","Bosnia and Herzegovina","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89632,70,"BIH","Bosnia and Herzegovina","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89633,70,"BIH","Bosnia and Herzegovina","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89634,70,"BIH","Bosnia and Herzegovina","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89635,70,"BIH","Bosnia and Herzegovina","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89636,70,"BIH","Bosnia and Herzegovina","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89637,70,"BIH","Bosnia and Herzegovina","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89638,70,"BIH","Bosnia and Herzegovina","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89639,70,"BIH","Bosnia and Herzegovina","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89640,70,"BIH","Bosnia and Herzegovina","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89641,70,"BIH","Bosnia and Herzegovina","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89642,70,"BIH","Bosnia and Herzegovina","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89643,70,"BIH","Bosnia and Herzegovina","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89644,70,"BIH","Bosnia and Herzegovina","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89645,70,"BIH","Bosnia and Herzegovina","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89646,70,"BIH","Bosnia and Herzegovina","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89647,70,"BIH","Bosnia and Herzegovina","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89648,70,"BIH","Bosnia and Herzegovina","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89649,70,"BIH","Bosnia and Herzegovina","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89650,70,"BIH","Bosnia and Herzegovina","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89651,70,"BIH","Bosnia and Herzegovina","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89652,70,"BIH","Bosnia and Herzegovina","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89653,70,"BIH","Bosnia and Herzegovina","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89654,70,"BIH","Bosnia and Herzegovina","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89655,70,"BIH","Bosnia and Herzegovina","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89656,70,"BIH","Bosnia and Herzegovina","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89657,70,"BIH","Bosnia and Herzegovina","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89658,70,"BIH","Bosnia and Herzegovina","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89659,70,"BIH","Bosnia and Herzegovina","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89660,70,"BIH","Bosnia and Herzegovina","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89661,70,"BIH","Bosnia and Herzegovina","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89662,70,"BIH","Bosnia and Herzegovina","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89663,70,"BIH","Bosnia and Herzegovina","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89664,70,"BIH","Bosnia and Herzegovina","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89665,70,"BIH","Bosnia and Herzegovina","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BIH/bih_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89666,72,"BWA","Botswana","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89667,72,"BWA","Botswana","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89668,72,"BWA","Botswana","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89669,72,"BWA","Botswana","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89670,72,"BWA","Botswana","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89671,72,"BWA","Botswana","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89672,72,"BWA","Botswana","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89673,72,"BWA","Botswana","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89674,72,"BWA","Botswana","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89675,72,"BWA","Botswana","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89676,72,"BWA","Botswana","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89677,72,"BWA","Botswana","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89678,72,"BWA","Botswana","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89679,72,"BWA","Botswana","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89680,72,"BWA","Botswana","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89681,72,"BWA","Botswana","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89682,72,"BWA","Botswana","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89683,72,"BWA","Botswana","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89684,72,"BWA","Botswana","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89685,72,"BWA","Botswana","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89686,72,"BWA","Botswana","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89687,72,"BWA","Botswana","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89688,72,"BWA","Botswana","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89689,72,"BWA","Botswana","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89690,72,"BWA","Botswana","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89691,72,"BWA","Botswana","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89692,72,"BWA","Botswana","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89693,72,"BWA","Botswana","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89694,72,"BWA","Botswana","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89695,72,"BWA","Botswana","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89696,72,"BWA","Botswana","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89697,72,"BWA","Botswana","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89698,72,"BWA","Botswana","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89699,72,"BWA","Botswana","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89700,72,"BWA","Botswana","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89701,72,"BWA","Botswana","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BWA/bwa_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89702,84,"BLZ","Belize","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89703,84,"BLZ","Belize","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89704,84,"BLZ","Belize","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89705,84,"BLZ","Belize","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89706,84,"BLZ","Belize","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89707,84,"BLZ","Belize","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89708,84,"BLZ","Belize","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89709,84,"BLZ","Belize","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89710,84,"BLZ","Belize","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89711,84,"BLZ","Belize","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89712,84,"BLZ","Belize","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89713,84,"BLZ","Belize","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89714,84,"BLZ","Belize","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89715,84,"BLZ","Belize","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89716,84,"BLZ","Belize","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89717,84,"BLZ","Belize","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89718,84,"BLZ","Belize","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89719,84,"BLZ","Belize","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89720,84,"BLZ","Belize","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89721,84,"BLZ","Belize","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89722,84,"BLZ","Belize","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89723,84,"BLZ","Belize","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89724,84,"BLZ","Belize","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89725,84,"BLZ","Belize","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89726,84,"BLZ","Belize","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89727,84,"BLZ","Belize","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89728,84,"BLZ","Belize","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89729,84,"BLZ","Belize","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89730,84,"BLZ","Belize","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89731,84,"BLZ","Belize","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89732,84,"BLZ","Belize","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89733,84,"BLZ","Belize","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89734,84,"BLZ","Belize","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89735,84,"BLZ","Belize","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89736,84,"BLZ","Belize","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89737,84,"BLZ","Belize","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLZ/blz_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89738,90,"SLB","Solomon Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89739,90,"SLB","Solomon Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89740,90,"SLB","Solomon Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89741,90,"SLB","Solomon Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89742,90,"SLB","Solomon Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89743,90,"SLB","Solomon Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89744,90,"SLB","Solomon Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89745,90,"SLB","Solomon Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89746,90,"SLB","Solomon Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89747,90,"SLB","Solomon Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89748,90,"SLB","Solomon Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89749,90,"SLB","Solomon Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89750,90,"SLB","Solomon Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89751,90,"SLB","Solomon Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89752,90,"SLB","Solomon Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89753,90,"SLB","Solomon Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89754,90,"SLB","Solomon Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89755,90,"SLB","Solomon Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89756,90,"SLB","Solomon Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89757,90,"SLB","Solomon Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89758,90,"SLB","Solomon Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89759,90,"SLB","Solomon Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89760,90,"SLB","Solomon Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89761,90,"SLB","Solomon Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89762,90,"SLB","Solomon Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89763,90,"SLB","Solomon Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89764,90,"SLB","Solomon Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89765,90,"SLB","Solomon Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89766,90,"SLB","Solomon Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89767,90,"SLB","Solomon Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89768,90,"SLB","Solomon Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89769,90,"SLB","Solomon Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89770,90,"SLB","Solomon Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89771,90,"SLB","Solomon Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89772,90,"SLB","Solomon Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89773,90,"SLB","Solomon Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLB/slb_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89774,92,"VGB","British Virgin Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89775,92,"VGB","British Virgin Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89776,92,"VGB","British Virgin Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89777,92,"VGB","British Virgin Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89778,92,"VGB","British Virgin Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89779,92,"VGB","British Virgin Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89780,92,"VGB","British Virgin Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89781,92,"VGB","British Virgin Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89782,92,"VGB","British Virgin Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89783,92,"VGB","British Virgin Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89784,92,"VGB","British Virgin Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89785,92,"VGB","British Virgin Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89786,92,"VGB","British Virgin Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89787,92,"VGB","British Virgin Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89788,92,"VGB","British Virgin Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89789,92,"VGB","British Virgin Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89790,92,"VGB","British Virgin Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89791,92,"VGB","British Virgin Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89792,92,"VGB","British Virgin Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89793,92,"VGB","British Virgin Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89794,92,"VGB","British Virgin Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89795,92,"VGB","British Virgin Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89796,92,"VGB","British Virgin Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89797,92,"VGB","British Virgin Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89798,92,"VGB","British Virgin Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89799,92,"VGB","British Virgin Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89800,92,"VGB","British Virgin Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89801,92,"VGB","British Virgin Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89802,92,"VGB","British Virgin Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89803,92,"VGB","British Virgin Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89804,92,"VGB","British Virgin Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89805,92,"VGB","British Virgin Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89806,92,"VGB","British Virgin Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89807,92,"VGB","British Virgin Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89808,92,"VGB","British Virgin Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89809,92,"VGB","British Virgin Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VGB/vgb_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89810,96,"BRN","Brunei","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89811,96,"BRN","Brunei","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89812,96,"BRN","Brunei","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89813,96,"BRN","Brunei","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89814,96,"BRN","Brunei","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89815,96,"BRN","Brunei","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89816,96,"BRN","Brunei","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89817,96,"BRN","Brunei","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89818,96,"BRN","Brunei","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89819,96,"BRN","Brunei","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89820,96,"BRN","Brunei","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89821,96,"BRN","Brunei","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89822,96,"BRN","Brunei","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89823,96,"BRN","Brunei","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89824,96,"BRN","Brunei","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89825,96,"BRN","Brunei","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89826,96,"BRN","Brunei","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89827,96,"BRN","Brunei","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89828,96,"BRN","Brunei","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89829,96,"BRN","Brunei","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89830,96,"BRN","Brunei","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89831,96,"BRN","Brunei","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89832,96,"BRN","Brunei","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89833,96,"BRN","Brunei","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89834,96,"BRN","Brunei","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89835,96,"BRN","Brunei","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89836,96,"BRN","Brunei","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89837,96,"BRN","Brunei","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89838,96,"BRN","Brunei","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89839,96,"BRN","Brunei","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89840,96,"BRN","Brunei","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89841,96,"BRN","Brunei","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89842,96,"BRN","Brunei","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89843,96,"BRN","Brunei","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89844,96,"BRN","Brunei","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89845,96,"BRN","Brunei","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BRN/brn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89846,100,"BGR","Bulgaria","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89847,100,"BGR","Bulgaria","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89848,100,"BGR","Bulgaria","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89849,100,"BGR","Bulgaria","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89850,100,"BGR","Bulgaria","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89851,100,"BGR","Bulgaria","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89852,100,"BGR","Bulgaria","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89853,100,"BGR","Bulgaria","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89854,100,"BGR","Bulgaria","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89855,100,"BGR","Bulgaria","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89856,100,"BGR","Bulgaria","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89857,100,"BGR","Bulgaria","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89858,100,"BGR","Bulgaria","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89859,100,"BGR","Bulgaria","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89860,100,"BGR","Bulgaria","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89861,100,"BGR","Bulgaria","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89862,100,"BGR","Bulgaria","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89863,100,"BGR","Bulgaria","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89864,100,"BGR","Bulgaria","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89865,100,"BGR","Bulgaria","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89866,100,"BGR","Bulgaria","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89867,100,"BGR","Bulgaria","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89868,100,"BGR","Bulgaria","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89869,100,"BGR","Bulgaria","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89870,100,"BGR","Bulgaria","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89871,100,"BGR","Bulgaria","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89872,100,"BGR","Bulgaria","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89873,100,"BGR","Bulgaria","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89874,100,"BGR","Bulgaria","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89875,100,"BGR","Bulgaria","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89876,100,"BGR","Bulgaria","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89877,100,"BGR","Bulgaria","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89878,100,"BGR","Bulgaria","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89879,100,"BGR","Bulgaria","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89880,100,"BGR","Bulgaria","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89881,100,"BGR","Bulgaria","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BGR/bgr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89882,104,"MMR","Myanmar","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89883,104,"MMR","Myanmar","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89884,104,"MMR","Myanmar","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89885,104,"MMR","Myanmar","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89886,104,"MMR","Myanmar","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89887,104,"MMR","Myanmar","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89888,104,"MMR","Myanmar","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89889,104,"MMR","Myanmar","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89890,104,"MMR","Myanmar","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89891,104,"MMR","Myanmar","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89892,104,"MMR","Myanmar","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89893,104,"MMR","Myanmar","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89894,104,"MMR","Myanmar","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89895,104,"MMR","Myanmar","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89896,104,"MMR","Myanmar","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89897,104,"MMR","Myanmar","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89898,104,"MMR","Myanmar","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89899,104,"MMR","Myanmar","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89900,104,"MMR","Myanmar","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89901,104,"MMR","Myanmar","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89902,104,"MMR","Myanmar","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89903,104,"MMR","Myanmar","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89904,104,"MMR","Myanmar","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89905,104,"MMR","Myanmar","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89906,104,"MMR","Myanmar","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89907,104,"MMR","Myanmar","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89908,104,"MMR","Myanmar","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89909,104,"MMR","Myanmar","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89910,104,"MMR","Myanmar","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89911,104,"MMR","Myanmar","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89912,104,"MMR","Myanmar","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89913,104,"MMR","Myanmar","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89914,104,"MMR","Myanmar","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89915,104,"MMR","Myanmar","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89916,104,"MMR","Myanmar","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89917,104,"MMR","Myanmar","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MMR/mmr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89918,108,"BDI","Burundi","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89919,108,"BDI","Burundi","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89920,108,"BDI","Burundi","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89921,108,"BDI","Burundi","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89922,108,"BDI","Burundi","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89923,108,"BDI","Burundi","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89924,108,"BDI","Burundi","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89925,108,"BDI","Burundi","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89926,108,"BDI","Burundi","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89927,108,"BDI","Burundi","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89928,108,"BDI","Burundi","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89929,108,"BDI","Burundi","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89930,108,"BDI","Burundi","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89931,108,"BDI","Burundi","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89932,108,"BDI","Burundi","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89933,108,"BDI","Burundi","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89934,108,"BDI","Burundi","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89935,108,"BDI","Burundi","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89936,108,"BDI","Burundi","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89937,108,"BDI","Burundi","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89938,108,"BDI","Burundi","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89939,108,"BDI","Burundi","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89940,108,"BDI","Burundi","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89941,108,"BDI","Burundi","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89942,108,"BDI","Burundi","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89943,108,"BDI","Burundi","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89944,108,"BDI","Burundi","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89945,108,"BDI","Burundi","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89946,108,"BDI","Burundi","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89947,108,"BDI","Burundi","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89948,108,"BDI","Burundi","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89949,108,"BDI","Burundi","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89950,108,"BDI","Burundi","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89951,108,"BDI","Burundi","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89952,108,"BDI","Burundi","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89953,108,"BDI","Burundi","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BDI/bdi_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
89954,112,"BLR","Belarus","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89955,112,"BLR","Belarus","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89956,112,"BLR","Belarus","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89957,112,"BLR","Belarus","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89958,112,"BLR","Belarus","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89959,112,"BLR","Belarus","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89960,112,"BLR","Belarus","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89961,112,"BLR","Belarus","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89962,112,"BLR","Belarus","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89963,112,"BLR","Belarus","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89964,112,"BLR","Belarus","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89965,112,"BLR","Belarus","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89966,112,"BLR","Belarus","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89967,112,"BLR","Belarus","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89968,112,"BLR","Belarus","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89969,112,"BLR","Belarus","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89970,112,"BLR","Belarus","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89971,112,"BLR","Belarus","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89972,112,"BLR","Belarus","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89973,112,"BLR","Belarus","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89974,112,"BLR","Belarus","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89975,112,"BLR","Belarus","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89976,112,"BLR","Belarus","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89977,112,"BLR","Belarus","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89978,112,"BLR","Belarus","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89979,112,"BLR","Belarus","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89980,112,"BLR","Belarus","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89981,112,"BLR","Belarus","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89982,112,"BLR","Belarus","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89983,112,"BLR","Belarus","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89984,112,"BLR","Belarus","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89985,112,"BLR","Belarus","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89986,112,"BLR","Belarus","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89987,112,"BLR","Belarus","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89988,112,"BLR","Belarus","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89989,112,"BLR","Belarus","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLR/blr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89990,116,"KHM","Cambodia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89991,116,"KHM","Cambodia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89992,116,"KHM","Cambodia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89993,116,"KHM","Cambodia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89994,116,"KHM","Cambodia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89995,116,"KHM","Cambodia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89996,116,"KHM","Cambodia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89997,116,"KHM","Cambodia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89998,116,"KHM","Cambodia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
89999,116,"KHM","Cambodia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90000,116,"KHM","Cambodia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90001,116,"KHM","Cambodia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90002,116,"KHM","Cambodia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90003,116,"KHM","Cambodia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90004,116,"KHM","Cambodia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90005,116,"KHM","Cambodia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90006,116,"KHM","Cambodia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90007,116,"KHM","Cambodia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90008,116,"KHM","Cambodia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90009,116,"KHM","Cambodia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90010,116,"KHM","Cambodia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90011,116,"KHM","Cambodia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90012,116,"KHM","Cambodia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90013,116,"KHM","Cambodia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90014,116,"KHM","Cambodia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90015,116,"KHM","Cambodia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90016,116,"KHM","Cambodia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90017,116,"KHM","Cambodia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90018,116,"KHM","Cambodia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90019,116,"KHM","Cambodia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90020,116,"KHM","Cambodia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90021,116,"KHM","Cambodia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90022,116,"KHM","Cambodia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90023,116,"KHM","Cambodia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90024,116,"KHM","Cambodia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90025,116,"KHM","Cambodia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KHM/khm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90026,120,"CMR","Cameroon","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90027,120,"CMR","Cameroon","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90028,120,"CMR","Cameroon","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90029,120,"CMR","Cameroon","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90030,120,"CMR","Cameroon","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90031,120,"CMR","Cameroon","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90032,120,"CMR","Cameroon","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90033,120,"CMR","Cameroon","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90034,120,"CMR","Cameroon","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90035,120,"CMR","Cameroon","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90036,120,"CMR","Cameroon","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90037,120,"CMR","Cameroon","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90038,120,"CMR","Cameroon","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90039,120,"CMR","Cameroon","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90040,120,"CMR","Cameroon","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90041,120,"CMR","Cameroon","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90042,120,"CMR","Cameroon","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90043,120,"CMR","Cameroon","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90044,120,"CMR","Cameroon","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90045,120,"CMR","Cameroon","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90046,120,"CMR","Cameroon","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90047,120,"CMR","Cameroon","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90048,120,"CMR","Cameroon","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90049,120,"CMR","Cameroon","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90050,120,"CMR","Cameroon","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90051,120,"CMR","Cameroon","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90052,120,"CMR","Cameroon","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90053,120,"CMR","Cameroon","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90054,120,"CMR","Cameroon","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90055,120,"CMR","Cameroon","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90056,120,"CMR","Cameroon","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90057,120,"CMR","Cameroon","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90058,120,"CMR","Cameroon","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90059,120,"CMR","Cameroon","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90060,120,"CMR","Cameroon","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90061,120,"CMR","Cameroon","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CMR/cmr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90062,132,"CPV","Cape Verde","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90063,132,"CPV","Cape Verde","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90064,132,"CPV","Cape Verde","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90065,132,"CPV","Cape Verde","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90066,132,"CPV","Cape Verde","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90067,132,"CPV","Cape Verde","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90068,132,"CPV","Cape Verde","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90069,132,"CPV","Cape Verde","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90070,132,"CPV","Cape Verde","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90071,132,"CPV","Cape Verde","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90072,132,"CPV","Cape Verde","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90073,132,"CPV","Cape Verde","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90074,132,"CPV","Cape Verde","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90075,132,"CPV","Cape Verde","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90076,132,"CPV","Cape Verde","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90077,132,"CPV","Cape Verde","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90078,132,"CPV","Cape Verde","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90079,132,"CPV","Cape Verde","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90080,132,"CPV","Cape Verde","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90081,132,"CPV","Cape Verde","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90082,132,"CPV","Cape Verde","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90083,132,"CPV","Cape Verde","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90084,132,"CPV","Cape Verde","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90085,132,"CPV","Cape Verde","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90086,132,"CPV","Cape Verde","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90087,132,"CPV","Cape Verde","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90088,132,"CPV","Cape Verde","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90089,132,"CPV","Cape Verde","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90090,132,"CPV","Cape Verde","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90091,132,"CPV","Cape Verde","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90092,132,"CPV","Cape Verde","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90093,132,"CPV","Cape Verde","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90094,132,"CPV","Cape Verde","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90095,132,"CPV","Cape Verde","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90096,132,"CPV","Cape Verde","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90097,132,"CPV","Cape Verde","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CPV/cpv_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90098,136,"CYM","Cayman Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90099,136,"CYM","Cayman Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90100,136,"CYM","Cayman Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90101,136,"CYM","Cayman Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90102,136,"CYM","Cayman Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90103,136,"CYM","Cayman Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90104,136,"CYM","Cayman Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90105,136,"CYM","Cayman Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90106,136,"CYM","Cayman Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90107,136,"CYM","Cayman Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90108,136,"CYM","Cayman Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90109,136,"CYM","Cayman Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90110,136,"CYM","Cayman Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90111,136,"CYM","Cayman Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90112,136,"CYM","Cayman Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90113,136,"CYM","Cayman Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90114,136,"CYM","Cayman Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90115,136,"CYM","Cayman Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90116,136,"CYM","Cayman Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90117,136,"CYM","Cayman Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90118,136,"CYM","Cayman Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90119,136,"CYM","Cayman Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90120,136,"CYM","Cayman Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90121,136,"CYM","Cayman Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90122,136,"CYM","Cayman Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90123,136,"CYM","Cayman Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90124,136,"CYM","Cayman Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90125,136,"CYM","Cayman Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90126,136,"CYM","Cayman Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90127,136,"CYM","Cayman Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90128,136,"CYM","Cayman Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90129,136,"CYM","Cayman Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90130,136,"CYM","Cayman Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90131,136,"CYM","Cayman Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90132,136,"CYM","Cayman Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90133,136,"CYM","Cayman Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYM/cym_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90134,140,"CAF","Central African Republic","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90135,140,"CAF","Central African Republic","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90136,140,"CAF","Central African Republic","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90137,140,"CAF","Central African Republic","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90138,140,"CAF","Central African Republic","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90139,140,"CAF","Central African Republic","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90140,140,"CAF","Central African Republic","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90141,140,"CAF","Central African Republic","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90142,140,"CAF","Central African Republic","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90143,140,"CAF","Central African Republic","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90144,140,"CAF","Central African Republic","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90145,140,"CAF","Central African Republic","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90146,140,"CAF","Central African Republic","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90147,140,"CAF","Central African Republic","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90148,140,"CAF","Central African Republic","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90149,140,"CAF","Central African Republic","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90150,140,"CAF","Central African Republic","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90151,140,"CAF","Central African Republic","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90152,140,"CAF","Central African Republic","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90153,140,"CAF","Central African Republic","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90154,140,"CAF","Central African Republic","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90155,140,"CAF","Central African Republic","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90156,140,"CAF","Central African Republic","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90157,140,"CAF","Central African Republic","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90158,140,"CAF","Central African Republic","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90159,140,"CAF","Central African Republic","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90160,140,"CAF","Central African Republic","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90161,140,"CAF","Central African Republic","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90162,140,"CAF","Central African Republic","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90163,140,"CAF","Central African Republic","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90164,140,"CAF","Central African Republic","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90165,140,"CAF","Central African Republic","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90166,140,"CAF","Central African Republic","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90167,140,"CAF","Central African Republic","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90168,140,"CAF","Central African Republic","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90169,140,"CAF","Central African Republic","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CAF/caf_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90170,144,"LKA","Sri Lanka","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90171,144,"LKA","Sri Lanka","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90172,144,"LKA","Sri Lanka","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90173,144,"LKA","Sri Lanka","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90174,144,"LKA","Sri Lanka","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90175,144,"LKA","Sri Lanka","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90176,144,"LKA","Sri Lanka","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90177,144,"LKA","Sri Lanka","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90178,144,"LKA","Sri Lanka","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90179,144,"LKA","Sri Lanka","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90180,144,"LKA","Sri Lanka","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90181,144,"LKA","Sri Lanka","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90182,144,"LKA","Sri Lanka","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90183,144,"LKA","Sri Lanka","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90184,144,"LKA","Sri Lanka","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90185,144,"LKA","Sri Lanka","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90186,144,"LKA","Sri Lanka","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90187,144,"LKA","Sri Lanka","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90188,144,"LKA","Sri Lanka","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90189,144,"LKA","Sri Lanka","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90190,144,"LKA","Sri Lanka","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90191,144,"LKA","Sri Lanka","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90192,144,"LKA","Sri Lanka","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90193,144,"LKA","Sri Lanka","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90194,144,"LKA","Sri Lanka","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90195,144,"LKA","Sri Lanka","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90196,144,"LKA","Sri Lanka","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90197,144,"LKA","Sri Lanka","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90198,144,"LKA","Sri Lanka","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90199,144,"LKA","Sri Lanka","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90200,144,"LKA","Sri Lanka","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90201,144,"LKA","Sri Lanka","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90202,144,"LKA","Sri Lanka","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90203,144,"LKA","Sri Lanka","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90204,144,"LKA","Sri Lanka","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90205,144,"LKA","Sri Lanka","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LKA/lka_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90206,148,"TCD","Chad","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90207,148,"TCD","Chad","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90208,148,"TCD","Chad","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90209,148,"TCD","Chad","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90210,148,"TCD","Chad","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90211,148,"TCD","Chad","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90212,148,"TCD","Chad","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90213,148,"TCD","Chad","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90214,148,"TCD","Chad","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90215,148,"TCD","Chad","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90216,148,"TCD","Chad","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90217,148,"TCD","Chad","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90218,148,"TCD","Chad","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90219,148,"TCD","Chad","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90220,148,"TCD","Chad","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90221,148,"TCD","Chad","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90222,148,"TCD","Chad","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90223,148,"TCD","Chad","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90224,148,"TCD","Chad","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90225,148,"TCD","Chad","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90226,148,"TCD","Chad","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90227,148,"TCD","Chad","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90228,148,"TCD","Chad","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90229,148,"TCD","Chad","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90230,148,"TCD","Chad","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90231,148,"TCD","Chad","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90232,148,"TCD","Chad","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90233,148,"TCD","Chad","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90234,148,"TCD","Chad","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90235,148,"TCD","Chad","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90236,148,"TCD","Chad","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90237,148,"TCD","Chad","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90238,148,"TCD","Chad","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90239,148,"TCD","Chad","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90240,148,"TCD","Chad","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90241,148,"TCD","Chad","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCD/tcd_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90242,158,"TWN","Taiwan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90243,158,"TWN","Taiwan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90244,158,"TWN","Taiwan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90245,158,"TWN","Taiwan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90246,158,"TWN","Taiwan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90247,158,"TWN","Taiwan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90248,158,"TWN","Taiwan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90249,158,"TWN","Taiwan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90250,158,"TWN","Taiwan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90251,158,"TWN","Taiwan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90252,158,"TWN","Taiwan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90253,158,"TWN","Taiwan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90254,158,"TWN","Taiwan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90255,158,"TWN","Taiwan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90256,158,"TWN","Taiwan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90257,158,"TWN","Taiwan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90258,158,"TWN","Taiwan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90259,158,"TWN","Taiwan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90260,158,"TWN","Taiwan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90261,158,"TWN","Taiwan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90262,158,"TWN","Taiwan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90263,158,"TWN","Taiwan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90264,158,"TWN","Taiwan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90265,158,"TWN","Taiwan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90266,158,"TWN","Taiwan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90267,158,"TWN","Taiwan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90268,158,"TWN","Taiwan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90269,158,"TWN","Taiwan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90270,158,"TWN","Taiwan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90271,158,"TWN","Taiwan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90272,158,"TWN","Taiwan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90273,158,"TWN","Taiwan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90274,158,"TWN","Taiwan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90275,158,"TWN","Taiwan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90276,158,"TWN","Taiwan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90277,158,"TWN","Taiwan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TWN/twn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90278,170,"COL","Colombia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90279,170,"COL","Colombia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90280,170,"COL","Colombia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90281,170,"COL","Colombia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90282,170,"COL","Colombia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90283,170,"COL","Colombia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90284,170,"COL","Colombia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90285,170,"COL","Colombia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90286,170,"COL","Colombia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90287,170,"COL","Colombia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90288,170,"COL","Colombia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90289,170,"COL","Colombia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90290,170,"COL","Colombia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90291,170,"COL","Colombia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90292,170,"COL","Colombia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90293,170,"COL","Colombia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90294,170,"COL","Colombia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90295,170,"COL","Colombia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90296,170,"COL","Colombia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90297,170,"COL","Colombia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90298,170,"COL","Colombia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90299,170,"COL","Colombia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90300,170,"COL","Colombia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90301,170,"COL","Colombia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90302,170,"COL","Colombia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90303,170,"COL","Colombia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90304,170,"COL","Colombia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90305,170,"COL","Colombia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90306,170,"COL","Colombia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90307,170,"COL","Colombia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90308,170,"COL","Colombia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90309,170,"COL","Colombia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90310,170,"COL","Colombia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90311,170,"COL","Colombia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90312,170,"COL","Colombia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90313,170,"COL","Colombia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COL/col_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90314,174,"COM","Comoros","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90315,174,"COM","Comoros","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90316,174,"COM","Comoros","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90317,174,"COM","Comoros","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90318,174,"COM","Comoros","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90319,174,"COM","Comoros","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90320,174,"COM","Comoros","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90321,174,"COM","Comoros","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90322,174,"COM","Comoros","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90323,174,"COM","Comoros","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90324,174,"COM","Comoros","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90325,174,"COM","Comoros","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90326,174,"COM","Comoros","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90327,174,"COM","Comoros","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90328,174,"COM","Comoros","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90329,174,"COM","Comoros","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90330,174,"COM","Comoros","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90331,174,"COM","Comoros","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90332,174,"COM","Comoros","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90333,174,"COM","Comoros","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90334,174,"COM","Comoros","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90335,174,"COM","Comoros","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90336,174,"COM","Comoros","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90337,174,"COM","Comoros","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90338,174,"COM","Comoros","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90339,174,"COM","Comoros","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90340,174,"COM","Comoros","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90341,174,"COM","Comoros","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90342,174,"COM","Comoros","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90343,174,"COM","Comoros","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90344,174,"COM","Comoros","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90345,174,"COM","Comoros","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90346,174,"COM","Comoros","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90347,174,"COM","Comoros","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90348,174,"COM","Comoros","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90349,174,"COM","Comoros","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COM/com_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90350,175,"MYT","Mayotte","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90351,175,"MYT","Mayotte","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90352,175,"MYT","Mayotte","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90353,175,"MYT","Mayotte","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90354,175,"MYT","Mayotte","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90355,175,"MYT","Mayotte","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90356,175,"MYT","Mayotte","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90357,175,"MYT","Mayotte","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90358,175,"MYT","Mayotte","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90359,175,"MYT","Mayotte","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90360,175,"MYT","Mayotte","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90361,175,"MYT","Mayotte","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90362,175,"MYT","Mayotte","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90363,175,"MYT","Mayotte","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90364,175,"MYT","Mayotte","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90365,175,"MYT","Mayotte","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90366,175,"MYT","Mayotte","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90367,175,"MYT","Mayotte","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90368,175,"MYT","Mayotte","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90369,175,"MYT","Mayotte","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90370,175,"MYT","Mayotte","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90371,175,"MYT","Mayotte","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90372,175,"MYT","Mayotte","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90373,175,"MYT","Mayotte","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90374,175,"MYT","Mayotte","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90375,175,"MYT","Mayotte","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90376,175,"MYT","Mayotte","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90377,175,"MYT","Mayotte","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90378,175,"MYT","Mayotte","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90379,175,"MYT","Mayotte","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90380,175,"MYT","Mayotte","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90381,175,"MYT","Mayotte","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90382,175,"MYT","Mayotte","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90383,175,"MYT","Mayotte","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90384,175,"MYT","Mayotte","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90385,175,"MYT","Mayotte","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYT/myt_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90386,178,"COG","Republic of Congo","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90387,178,"COG","Republic of Congo","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90388,178,"COG","Republic of Congo","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90389,178,"COG","Republic of Congo","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90390,178,"COG","Republic of Congo","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90391,178,"COG","Republic of Congo","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90392,178,"COG","Republic of Congo","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90393,178,"COG","Republic of Congo","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90394,178,"COG","Republic of Congo","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90395,178,"COG","Republic of Congo","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90396,178,"COG","Republic of Congo","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90397,178,"COG","Republic of Congo","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90398,178,"COG","Republic of Congo","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90399,178,"COG","Republic of Congo","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90400,178,"COG","Republic of Congo","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90401,178,"COG","Republic of Congo","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90402,178,"COG","Republic of Congo","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90403,178,"COG","Republic of Congo","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90404,178,"COG","Republic of Congo","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90405,178,"COG","Republic of Congo","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90406,178,"COG","Republic of Congo","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90407,178,"COG","Republic of Congo","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90408,178,"COG","Republic of Congo","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90409,178,"COG","Republic of Congo","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90410,178,"COG","Republic of Congo","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90411,178,"COG","Republic of Congo","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90412,178,"COG","Republic of Congo","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90413,178,"COG","Republic of Congo","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90414,178,"COG","Republic of Congo","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90415,178,"COG","Republic of Congo","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90416,178,"COG","Republic of Congo","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90417,178,"COG","Republic of Congo","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90418,178,"COG","Republic of Congo","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90419,178,"COG","Republic of Congo","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90420,178,"COG","Republic of Congo","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90421,178,"COG","Republic of Congo","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COG/cog_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90422,180,"COD","Democratic Republic of the Congo","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90423,180,"COD","Democratic Republic of the Congo","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90424,180,"COD","Democratic Republic of the Congo","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90425,180,"COD","Democratic Republic of the Congo","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90426,180,"COD","Democratic Republic of the Congo","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90427,180,"COD","Democratic Republic of the Congo","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90428,180,"COD","Democratic Republic of the Congo","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90429,180,"COD","Democratic Republic of the Congo","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90430,180,"COD","Democratic Republic of the Congo","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90431,180,"COD","Democratic Republic of the Congo","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90432,180,"COD","Democratic Republic of the Congo","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90433,180,"COD","Democratic Republic of the Congo","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90434,180,"COD","Democratic Republic of the Congo","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90435,180,"COD","Democratic Republic of the Congo","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90436,180,"COD","Democratic Republic of the Congo","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90437,180,"COD","Democratic Republic of the Congo","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90438,180,"COD","Democratic Republic of the Congo","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90439,180,"COD","Democratic Republic of the Congo","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90440,180,"COD","Democratic Republic of the Congo","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90441,180,"COD","Democratic Republic of the Congo","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90442,180,"COD","Democratic Republic of the Congo","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90443,180,"COD","Democratic Republic of the Congo","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90444,180,"COD","Democratic Republic of the Congo","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90445,180,"COD","Democratic Republic of the Congo","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90446,180,"COD","Democratic Republic of the Congo","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90447,180,"COD","Democratic Republic of the Congo","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90448,180,"COD","Democratic Republic of the Congo","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90449,180,"COD","Democratic Republic of the Congo","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90450,180,"COD","Democratic Republic of the Congo","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90451,180,"COD","Democratic Republic of the Congo","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90452,180,"COD","Democratic Republic of the Congo","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90453,180,"COD","Democratic Republic of the Congo","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90454,180,"COD","Democratic Republic of the Congo","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90455,180,"COD","Democratic Republic of the Congo","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90456,180,"COD","Democratic Republic of the Congo","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90457,180,"COD","Democratic Republic of the Congo","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COD/cod_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90458,184,"COK","Cook Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90459,184,"COK","Cook Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90460,184,"COK","Cook Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90461,184,"COK","Cook Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90462,184,"COK","Cook Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90463,184,"COK","Cook Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90464,184,"COK","Cook Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90465,184,"COK","Cook Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90466,184,"COK","Cook Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90467,184,"COK","Cook Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90468,184,"COK","Cook Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90469,184,"COK","Cook Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90470,184,"COK","Cook Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90471,184,"COK","Cook Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90472,184,"COK","Cook Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90473,184,"COK","Cook Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90474,184,"COK","Cook Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90475,184,"COK","Cook Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90476,184,"COK","Cook Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90477,184,"COK","Cook Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90478,184,"COK","Cook Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90479,184,"COK","Cook Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90480,184,"COK","Cook Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90481,184,"COK","Cook Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90482,184,"COK","Cook Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90483,184,"COK","Cook Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90484,184,"COK","Cook Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90485,184,"COK","Cook Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90486,184,"COK","Cook Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90487,184,"COK","Cook Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90488,184,"COK","Cook Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90489,184,"COK","Cook Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90490,184,"COK","Cook Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90491,184,"COK","Cook Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90492,184,"COK","Cook Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90493,184,"COK","Cook Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/COK/cok_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90494,188,"CRI","Costa Rica","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90495,188,"CRI","Costa Rica","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90496,188,"CRI","Costa Rica","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90497,188,"CRI","Costa Rica","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90498,188,"CRI","Costa Rica","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90499,188,"CRI","Costa Rica","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90500,188,"CRI","Costa Rica","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90501,188,"CRI","Costa Rica","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90502,188,"CRI","Costa Rica","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90503,188,"CRI","Costa Rica","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90504,188,"CRI","Costa Rica","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90505,188,"CRI","Costa Rica","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90506,188,"CRI","Costa Rica","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90507,188,"CRI","Costa Rica","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90508,188,"CRI","Costa Rica","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90509,188,"CRI","Costa Rica","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90510,188,"CRI","Costa Rica","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90511,188,"CRI","Costa Rica","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90512,188,"CRI","Costa Rica","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90513,188,"CRI","Costa Rica","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90514,188,"CRI","Costa Rica","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90515,188,"CRI","Costa Rica","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90516,188,"CRI","Costa Rica","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90517,188,"CRI","Costa Rica","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90518,188,"CRI","Costa Rica","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90519,188,"CRI","Costa Rica","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90520,188,"CRI","Costa Rica","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90521,188,"CRI","Costa Rica","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90522,188,"CRI","Costa Rica","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90523,188,"CRI","Costa Rica","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90524,188,"CRI","Costa Rica","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90525,188,"CRI","Costa Rica","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90526,188,"CRI","Costa Rica","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90527,188,"CRI","Costa Rica","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90528,188,"CRI","Costa Rica","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90529,188,"CRI","Costa Rica","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CRI/cri_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90530,191,"HRV","Croatia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90531,191,"HRV","Croatia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90532,191,"HRV","Croatia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90533,191,"HRV","Croatia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90534,191,"HRV","Croatia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90535,191,"HRV","Croatia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90536,191,"HRV","Croatia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90537,191,"HRV","Croatia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90538,191,"HRV","Croatia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90539,191,"HRV","Croatia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90540,191,"HRV","Croatia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90541,191,"HRV","Croatia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90542,191,"HRV","Croatia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90543,191,"HRV","Croatia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90544,191,"HRV","Croatia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90545,191,"HRV","Croatia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90546,191,"HRV","Croatia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90547,191,"HRV","Croatia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90548,191,"HRV","Croatia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90549,191,"HRV","Croatia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90550,191,"HRV","Croatia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90551,191,"HRV","Croatia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90552,191,"HRV","Croatia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90553,191,"HRV","Croatia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90554,191,"HRV","Croatia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90555,191,"HRV","Croatia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90556,191,"HRV","Croatia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90557,191,"HRV","Croatia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90558,191,"HRV","Croatia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90559,191,"HRV","Croatia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90560,191,"HRV","Croatia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90561,191,"HRV","Croatia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90562,191,"HRV","Croatia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90563,191,"HRV","Croatia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90564,191,"HRV","Croatia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90565,191,"HRV","Croatia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HRV/hrv_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90566,192,"CUB","Cuba","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90567,192,"CUB","Cuba","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90568,192,"CUB","Cuba","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90569,192,"CUB","Cuba","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90570,192,"CUB","Cuba","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90571,192,"CUB","Cuba","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90572,192,"CUB","Cuba","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90573,192,"CUB","Cuba","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90574,192,"CUB","Cuba","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90575,192,"CUB","Cuba","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90576,192,"CUB","Cuba","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90577,192,"CUB","Cuba","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90578,192,"CUB","Cuba","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90579,192,"CUB","Cuba","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90580,192,"CUB","Cuba","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90581,192,"CUB","Cuba","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90582,192,"CUB","Cuba","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90583,192,"CUB","Cuba","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90584,192,"CUB","Cuba","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90585,192,"CUB","Cuba","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90586,192,"CUB","Cuba","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90587,192,"CUB","Cuba","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90588,192,"CUB","Cuba","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90589,192,"CUB","Cuba","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90590,192,"CUB","Cuba","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90591,192,"CUB","Cuba","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90592,192,"CUB","Cuba","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90593,192,"CUB","Cuba","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90594,192,"CUB","Cuba","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90595,192,"CUB","Cuba","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90596,192,"CUB","Cuba","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90597,192,"CUB","Cuba","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90598,192,"CUB","Cuba","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90599,192,"CUB","Cuba","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90600,192,"CUB","Cuba","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90601,192,"CUB","Cuba","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUB/cub_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90602,196,"CYP","Cyprus","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90603,196,"CYP","Cyprus","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90604,196,"CYP","Cyprus","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90605,196,"CYP","Cyprus","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90606,196,"CYP","Cyprus","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90607,196,"CYP","Cyprus","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90608,196,"CYP","Cyprus","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90609,196,"CYP","Cyprus","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90610,196,"CYP","Cyprus","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90611,196,"CYP","Cyprus","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90612,196,"CYP","Cyprus","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90613,196,"CYP","Cyprus","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90614,196,"CYP","Cyprus","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90615,196,"CYP","Cyprus","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90616,196,"CYP","Cyprus","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90617,196,"CYP","Cyprus","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90618,196,"CYP","Cyprus","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90619,196,"CYP","Cyprus","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90620,196,"CYP","Cyprus","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90621,196,"CYP","Cyprus","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90622,196,"CYP","Cyprus","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90623,196,"CYP","Cyprus","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90624,196,"CYP","Cyprus","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90625,196,"CYP","Cyprus","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90626,196,"CYP","Cyprus","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90627,196,"CYP","Cyprus","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90628,196,"CYP","Cyprus","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90629,196,"CYP","Cyprus","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90630,196,"CYP","Cyprus","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90631,196,"CYP","Cyprus","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90632,196,"CYP","Cyprus","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90633,196,"CYP","Cyprus","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90634,196,"CYP","Cyprus","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90635,196,"CYP","Cyprus","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90636,196,"CYP","Cyprus","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90637,196,"CYP","Cyprus","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CYP/cyp_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90638,203,"CZE","Czech Republic","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90639,203,"CZE","Czech Republic","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90640,203,"CZE","Czech Republic","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90641,203,"CZE","Czech Republic","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90642,203,"CZE","Czech Republic","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90643,203,"CZE","Czech Republic","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90644,203,"CZE","Czech Republic","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90645,203,"CZE","Czech Republic","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90646,203,"CZE","Czech Republic","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90647,203,"CZE","Czech Republic","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90648,203,"CZE","Czech Republic","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90649,203,"CZE","Czech Republic","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90650,203,"CZE","Czech Republic","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90651,203,"CZE","Czech Republic","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90652,203,"CZE","Czech Republic","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90653,203,"CZE","Czech Republic","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90654,203,"CZE","Czech Republic","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90655,203,"CZE","Czech Republic","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90656,203,"CZE","Czech Republic","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90657,203,"CZE","Czech Republic","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90658,203,"CZE","Czech Republic","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90659,203,"CZE","Czech Republic","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90660,203,"CZE","Czech Republic","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90661,203,"CZE","Czech Republic","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90662,203,"CZE","Czech Republic","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90663,203,"CZE","Czech Republic","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90664,203,"CZE","Czech Republic","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90665,203,"CZE","Czech Republic","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90666,203,"CZE","Czech Republic","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90667,203,"CZE","Czech Republic","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90668,203,"CZE","Czech Republic","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90669,203,"CZE","Czech Republic","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90670,203,"CZE","Czech Republic","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90671,203,"CZE","Czech Republic","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90672,203,"CZE","Czech Republic","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90673,203,"CZE","Czech Republic","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CZE/cze_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90674,204,"BEN","Benin","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90675,204,"BEN","Benin","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90676,204,"BEN","Benin","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90677,204,"BEN","Benin","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90678,204,"BEN","Benin","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90679,204,"BEN","Benin","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90680,204,"BEN","Benin","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90681,204,"BEN","Benin","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90682,204,"BEN","Benin","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90683,204,"BEN","Benin","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90684,204,"BEN","Benin","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90685,204,"BEN","Benin","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90686,204,"BEN","Benin","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90687,204,"BEN","Benin","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90688,204,"BEN","Benin","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90689,204,"BEN","Benin","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90690,204,"BEN","Benin","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90691,204,"BEN","Benin","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90692,204,"BEN","Benin","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90693,204,"BEN","Benin","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90694,204,"BEN","Benin","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90695,204,"BEN","Benin","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90696,204,"BEN","Benin","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90697,204,"BEN","Benin","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90698,204,"BEN","Benin","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90699,204,"BEN","Benin","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90700,204,"BEN","Benin","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90701,204,"BEN","Benin","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90702,204,"BEN","Benin","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90703,204,"BEN","Benin","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90704,204,"BEN","Benin","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90705,204,"BEN","Benin","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90706,204,"BEN","Benin","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90707,204,"BEN","Benin","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90708,204,"BEN","Benin","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90709,204,"BEN","Benin","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BEN/ben_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90710,208,"DNK","Denmark","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90711,208,"DNK","Denmark","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90712,208,"DNK","Denmark","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90713,208,"DNK","Denmark","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90714,208,"DNK","Denmark","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90715,208,"DNK","Denmark","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90716,208,"DNK","Denmark","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90717,208,"DNK","Denmark","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90718,208,"DNK","Denmark","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90719,208,"DNK","Denmark","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90720,208,"DNK","Denmark","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90721,208,"DNK","Denmark","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90722,208,"DNK","Denmark","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90723,208,"DNK","Denmark","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90724,208,"DNK","Denmark","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90725,208,"DNK","Denmark","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90726,208,"DNK","Denmark","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90727,208,"DNK","Denmark","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90728,208,"DNK","Denmark","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90729,208,"DNK","Denmark","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90730,208,"DNK","Denmark","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90731,208,"DNK","Denmark","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90732,208,"DNK","Denmark","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90733,208,"DNK","Denmark","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90734,208,"DNK","Denmark","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90735,208,"DNK","Denmark","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90736,208,"DNK","Denmark","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90737,208,"DNK","Denmark","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90738,208,"DNK","Denmark","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90739,208,"DNK","Denmark","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90740,208,"DNK","Denmark","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90741,208,"DNK","Denmark","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90742,208,"DNK","Denmark","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90743,208,"DNK","Denmark","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90744,208,"DNK","Denmark","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90745,208,"DNK","Denmark","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DNK/dnk_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90746,212,"DMA","Dominica","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90747,212,"DMA","Dominica","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90748,212,"DMA","Dominica","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90749,212,"DMA","Dominica","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90750,212,"DMA","Dominica","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90751,212,"DMA","Dominica","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90752,212,"DMA","Dominica","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90753,212,"DMA","Dominica","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90754,212,"DMA","Dominica","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90755,212,"DMA","Dominica","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90756,212,"DMA","Dominica","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90757,212,"DMA","Dominica","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90758,212,"DMA","Dominica","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90759,212,"DMA","Dominica","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90760,212,"DMA","Dominica","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90761,212,"DMA","Dominica","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90762,212,"DMA","Dominica","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90763,212,"DMA","Dominica","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90764,212,"DMA","Dominica","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90765,212,"DMA","Dominica","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90766,212,"DMA","Dominica","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90767,212,"DMA","Dominica","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90768,212,"DMA","Dominica","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90769,212,"DMA","Dominica","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90770,212,"DMA","Dominica","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90771,212,"DMA","Dominica","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90772,212,"DMA","Dominica","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90773,212,"DMA","Dominica","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90774,212,"DMA","Dominica","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90775,212,"DMA","Dominica","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90776,212,"DMA","Dominica","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90777,212,"DMA","Dominica","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90778,212,"DMA","Dominica","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90779,212,"DMA","Dominica","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90780,212,"DMA","Dominica","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90781,212,"DMA","Dominica","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DMA/dma_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90782,214,"DOM","Dominican Republic","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90783,214,"DOM","Dominican Republic","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90784,214,"DOM","Dominican Republic","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90785,214,"DOM","Dominican Republic","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90786,214,"DOM","Dominican Republic","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90787,214,"DOM","Dominican Republic","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90788,214,"DOM","Dominican Republic","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90789,214,"DOM","Dominican Republic","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90790,214,"DOM","Dominican Republic","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90791,214,"DOM","Dominican Republic","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90792,214,"DOM","Dominican Republic","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90793,214,"DOM","Dominican Republic","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90794,214,"DOM","Dominican Republic","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90795,214,"DOM","Dominican Republic","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90796,214,"DOM","Dominican Republic","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90797,214,"DOM","Dominican Republic","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90798,214,"DOM","Dominican Republic","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90799,214,"DOM","Dominican Republic","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90800,214,"DOM","Dominican Republic","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90801,214,"DOM","Dominican Republic","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90802,214,"DOM","Dominican Republic","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90803,214,"DOM","Dominican Republic","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90804,214,"DOM","Dominican Republic","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90805,214,"DOM","Dominican Republic","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90806,214,"DOM","Dominican Republic","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90807,214,"DOM","Dominican Republic","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90808,214,"DOM","Dominican Republic","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90809,214,"DOM","Dominican Republic","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90810,214,"DOM","Dominican Republic","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90811,214,"DOM","Dominican Republic","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90812,214,"DOM","Dominican Republic","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90813,214,"DOM","Dominican Republic","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90814,214,"DOM","Dominican Republic","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90815,214,"DOM","Dominican Republic","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90816,214,"DOM","Dominican Republic","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90817,214,"DOM","Dominican Republic","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DOM/dom_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90818,218,"ECU","Ecuador","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90819,218,"ECU","Ecuador","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90820,218,"ECU","Ecuador","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90821,218,"ECU","Ecuador","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90822,218,"ECU","Ecuador","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90823,218,"ECU","Ecuador","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90824,218,"ECU","Ecuador","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90825,218,"ECU","Ecuador","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90826,218,"ECU","Ecuador","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90827,218,"ECU","Ecuador","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90828,218,"ECU","Ecuador","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90829,218,"ECU","Ecuador","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90830,218,"ECU","Ecuador","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90831,218,"ECU","Ecuador","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90832,218,"ECU","Ecuador","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90833,218,"ECU","Ecuador","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90834,218,"ECU","Ecuador","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90835,218,"ECU","Ecuador","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90836,218,"ECU","Ecuador","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90837,218,"ECU","Ecuador","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90838,218,"ECU","Ecuador","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90839,218,"ECU","Ecuador","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90840,218,"ECU","Ecuador","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90841,218,"ECU","Ecuador","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90842,218,"ECU","Ecuador","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90843,218,"ECU","Ecuador","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90844,218,"ECU","Ecuador","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90845,218,"ECU","Ecuador","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90846,218,"ECU","Ecuador","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90847,218,"ECU","Ecuador","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90848,218,"ECU","Ecuador","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90849,218,"ECU","Ecuador","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90850,218,"ECU","Ecuador","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90851,218,"ECU","Ecuador","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90852,218,"ECU","Ecuador","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90853,218,"ECU","Ecuador","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ECU/ecu_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90854,222,"SLV","El Salvador","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90855,222,"SLV","El Salvador","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90856,222,"SLV","El Salvador","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90857,222,"SLV","El Salvador","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90858,222,"SLV","El Salvador","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90859,222,"SLV","El Salvador","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90860,222,"SLV","El Salvador","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90861,222,"SLV","El Salvador","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90862,222,"SLV","El Salvador","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90863,222,"SLV","El Salvador","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90864,222,"SLV","El Salvador","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90865,222,"SLV","El Salvador","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90866,222,"SLV","El Salvador","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90867,222,"SLV","El Salvador","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90868,222,"SLV","El Salvador","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90869,222,"SLV","El Salvador","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90870,222,"SLV","El Salvador","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90871,222,"SLV","El Salvador","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90872,222,"SLV","El Salvador","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90873,222,"SLV","El Salvador","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90874,222,"SLV","El Salvador","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90875,222,"SLV","El Salvador","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90876,222,"SLV","El Salvador","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90877,222,"SLV","El Salvador","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90878,222,"SLV","El Salvador","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90879,222,"SLV","El Salvador","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90880,222,"SLV","El Salvador","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90881,222,"SLV","El Salvador","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90882,222,"SLV","El Salvador","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90883,222,"SLV","El Salvador","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90884,222,"SLV","El Salvador","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90885,222,"SLV","El Salvador","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90886,222,"SLV","El Salvador","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90887,222,"SLV","El Salvador","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90888,222,"SLV","El Salvador","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90889,222,"SLV","El Salvador","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLV/slv_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90890,226,"GNQ","Equatorial Guinea","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90891,226,"GNQ","Equatorial Guinea","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90892,226,"GNQ","Equatorial Guinea","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90893,226,"GNQ","Equatorial Guinea","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90894,226,"GNQ","Equatorial Guinea","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90895,226,"GNQ","Equatorial Guinea","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90896,226,"GNQ","Equatorial Guinea","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90897,226,"GNQ","Equatorial Guinea","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90898,226,"GNQ","Equatorial Guinea","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90899,226,"GNQ","Equatorial Guinea","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90900,226,"GNQ","Equatorial Guinea","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90901,226,"GNQ","Equatorial Guinea","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90902,226,"GNQ","Equatorial Guinea","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90903,226,"GNQ","Equatorial Guinea","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90904,226,"GNQ","Equatorial Guinea","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90905,226,"GNQ","Equatorial Guinea","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90906,226,"GNQ","Equatorial Guinea","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90907,226,"GNQ","Equatorial Guinea","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90908,226,"GNQ","Equatorial Guinea","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90909,226,"GNQ","Equatorial Guinea","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90910,226,"GNQ","Equatorial Guinea","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90911,226,"GNQ","Equatorial Guinea","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90912,226,"GNQ","Equatorial Guinea","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90913,226,"GNQ","Equatorial Guinea","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90914,226,"GNQ","Equatorial Guinea","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90915,226,"GNQ","Equatorial Guinea","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90916,226,"GNQ","Equatorial Guinea","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90917,226,"GNQ","Equatorial Guinea","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90918,226,"GNQ","Equatorial Guinea","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90919,226,"GNQ","Equatorial Guinea","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90920,226,"GNQ","Equatorial Guinea","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90921,226,"GNQ","Equatorial Guinea","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90922,226,"GNQ","Equatorial Guinea","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90923,226,"GNQ","Equatorial Guinea","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90924,226,"GNQ","Equatorial Guinea","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90925,226,"GNQ","Equatorial Guinea","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNQ/gnq_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90926,231,"ETH","Ethiopia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90927,231,"ETH","Ethiopia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90928,231,"ETH","Ethiopia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90929,231,"ETH","Ethiopia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90930,231,"ETH","Ethiopia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90931,231,"ETH","Ethiopia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90932,231,"ETH","Ethiopia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90933,231,"ETH","Ethiopia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90934,231,"ETH","Ethiopia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90935,231,"ETH","Ethiopia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90936,231,"ETH","Ethiopia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90937,231,"ETH","Ethiopia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90938,231,"ETH","Ethiopia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90939,231,"ETH","Ethiopia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90940,231,"ETH","Ethiopia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90941,231,"ETH","Ethiopia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90942,231,"ETH","Ethiopia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90943,231,"ETH","Ethiopia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90944,231,"ETH","Ethiopia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90945,231,"ETH","Ethiopia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90946,231,"ETH","Ethiopia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90947,231,"ETH","Ethiopia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90948,231,"ETH","Ethiopia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90949,231,"ETH","Ethiopia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90950,231,"ETH","Ethiopia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90951,231,"ETH","Ethiopia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90952,231,"ETH","Ethiopia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90953,231,"ETH","Ethiopia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90954,231,"ETH","Ethiopia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90955,231,"ETH","Ethiopia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90956,231,"ETH","Ethiopia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90957,231,"ETH","Ethiopia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90958,231,"ETH","Ethiopia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90959,231,"ETH","Ethiopia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90960,231,"ETH","Ethiopia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90961,231,"ETH","Ethiopia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ETH/eth_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90962,232,"ERI","Eritrea","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90963,232,"ERI","Eritrea","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90964,232,"ERI","Eritrea","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90965,232,"ERI","Eritrea","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90966,232,"ERI","Eritrea","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90967,232,"ERI","Eritrea","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90968,232,"ERI","Eritrea","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90969,232,"ERI","Eritrea","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90970,232,"ERI","Eritrea","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90971,232,"ERI","Eritrea","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90972,232,"ERI","Eritrea","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90973,232,"ERI","Eritrea","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90974,232,"ERI","Eritrea","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90975,232,"ERI","Eritrea","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90976,232,"ERI","Eritrea","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90977,232,"ERI","Eritrea","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90978,232,"ERI","Eritrea","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90979,232,"ERI","Eritrea","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90980,232,"ERI","Eritrea","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90981,232,"ERI","Eritrea","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90982,232,"ERI","Eritrea","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90983,232,"ERI","Eritrea","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90984,232,"ERI","Eritrea","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90985,232,"ERI","Eritrea","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90986,232,"ERI","Eritrea","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90987,232,"ERI","Eritrea","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90988,232,"ERI","Eritrea","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90989,232,"ERI","Eritrea","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90990,232,"ERI","Eritrea","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90991,232,"ERI","Eritrea","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90992,232,"ERI","Eritrea","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90993,232,"ERI","Eritrea","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90994,232,"ERI","Eritrea","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90995,232,"ERI","Eritrea","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90996,232,"ERI","Eritrea","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90997,232,"ERI","Eritrea","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ERI/eri_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
90998,233,"EST","Estonia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
90999,233,"EST","Estonia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91000,233,"EST","Estonia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91001,233,"EST","Estonia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91002,233,"EST","Estonia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91003,233,"EST","Estonia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91004,233,"EST","Estonia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91005,233,"EST","Estonia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91006,233,"EST","Estonia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91007,233,"EST","Estonia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91008,233,"EST","Estonia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91009,233,"EST","Estonia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91010,233,"EST","Estonia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91011,233,"EST","Estonia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91012,233,"EST","Estonia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91013,233,"EST","Estonia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91014,233,"EST","Estonia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91015,233,"EST","Estonia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91016,233,"EST","Estonia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91017,233,"EST","Estonia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91018,233,"EST","Estonia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91019,233,"EST","Estonia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91020,233,"EST","Estonia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91021,233,"EST","Estonia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91022,233,"EST","Estonia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91023,233,"EST","Estonia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91024,233,"EST","Estonia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91025,233,"EST","Estonia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91026,233,"EST","Estonia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91027,233,"EST","Estonia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91028,233,"EST","Estonia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91029,233,"EST","Estonia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91030,233,"EST","Estonia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91031,233,"EST","Estonia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91032,233,"EST","Estonia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91033,233,"EST","Estonia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EST/est_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91034,234,"FRO","Faroe Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91035,234,"FRO","Faroe Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91036,234,"FRO","Faroe Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91037,234,"FRO","Faroe Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91038,234,"FRO","Faroe Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91039,234,"FRO","Faroe Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91040,234,"FRO","Faroe Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91041,234,"FRO","Faroe Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91042,234,"FRO","Faroe Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91043,234,"FRO","Faroe Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91044,234,"FRO","Faroe Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91045,234,"FRO","Faroe Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91046,234,"FRO","Faroe Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91047,234,"FRO","Faroe Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91048,234,"FRO","Faroe Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91049,234,"FRO","Faroe Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91050,234,"FRO","Faroe Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91051,234,"FRO","Faroe Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91052,234,"FRO","Faroe Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91053,234,"FRO","Faroe Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91054,234,"FRO","Faroe Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91055,234,"FRO","Faroe Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91056,234,"FRO","Faroe Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91057,234,"FRO","Faroe Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91058,234,"FRO","Faroe Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91059,234,"FRO","Faroe Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91060,234,"FRO","Faroe Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91061,234,"FRO","Faroe Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91062,234,"FRO","Faroe Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91063,234,"FRO","Faroe Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91064,234,"FRO","Faroe Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91065,234,"FRO","Faroe Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91066,234,"FRO","Faroe Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91067,234,"FRO","Faroe Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91068,234,"FRO","Faroe Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91069,234,"FRO","Faroe Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRO/fro_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91070,238,"FLK","Falkland Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91071,238,"FLK","Falkland Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91072,238,"FLK","Falkland Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91073,238,"FLK","Falkland Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91074,238,"FLK","Falkland Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91075,238,"FLK","Falkland Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91076,238,"FLK","Falkland Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91077,238,"FLK","Falkland Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91078,238,"FLK","Falkland Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91079,238,"FLK","Falkland Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91080,238,"FLK","Falkland Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91081,238,"FLK","Falkland Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91082,238,"FLK","Falkland Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91083,238,"FLK","Falkland Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91084,238,"FLK","Falkland Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91085,238,"FLK","Falkland Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91086,238,"FLK","Falkland Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91087,238,"FLK","Falkland Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91088,238,"FLK","Falkland Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91089,238,"FLK","Falkland Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91090,238,"FLK","Falkland Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91091,238,"FLK","Falkland Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91092,238,"FLK","Falkland Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91093,238,"FLK","Falkland Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91094,238,"FLK","Falkland Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91095,238,"FLK","Falkland Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91096,238,"FLK","Falkland Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91097,238,"FLK","Falkland Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91098,238,"FLK","Falkland Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91099,238,"FLK","Falkland Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91100,238,"FLK","Falkland Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91101,238,"FLK","Falkland Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91102,238,"FLK","Falkland Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91103,238,"FLK","Falkland Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91104,238,"FLK","Falkland Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91105,238,"FLK","Falkland Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FLK/flk_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91106,242,"FJI","Fiji","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91107,242,"FJI","Fiji","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91108,242,"FJI","Fiji","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91109,242,"FJI","Fiji","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91110,242,"FJI","Fiji","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91111,242,"FJI","Fiji","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91112,242,"FJI","Fiji","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91113,242,"FJI","Fiji","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91114,242,"FJI","Fiji","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91115,242,"FJI","Fiji","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91116,242,"FJI","Fiji","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91117,242,"FJI","Fiji","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91118,242,"FJI","Fiji","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91119,242,"FJI","Fiji","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91120,242,"FJI","Fiji","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91121,242,"FJI","Fiji","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91122,242,"FJI","Fiji","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91123,242,"FJI","Fiji","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91124,242,"FJI","Fiji","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91125,242,"FJI","Fiji","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91126,242,"FJI","Fiji","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91127,242,"FJI","Fiji","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91128,242,"FJI","Fiji","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91129,242,"FJI","Fiji","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91130,242,"FJI","Fiji","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91131,242,"FJI","Fiji","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91132,242,"FJI","Fiji","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91133,242,"FJI","Fiji","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91134,242,"FJI","Fiji","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91135,242,"FJI","Fiji","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91136,242,"FJI","Fiji","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91137,242,"FJI","Fiji","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91138,242,"FJI","Fiji","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91139,242,"FJI","Fiji","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91140,242,"FJI","Fiji","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91141,242,"FJI","Fiji","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FJI/fji_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91142,246,"FIN","Finland","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91143,246,"FIN","Finland","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91144,246,"FIN","Finland","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91145,246,"FIN","Finland","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91146,246,"FIN","Finland","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91147,246,"FIN","Finland","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91148,246,"FIN","Finland","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91149,246,"FIN","Finland","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91150,246,"FIN","Finland","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91151,246,"FIN","Finland","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91152,246,"FIN","Finland","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91153,246,"FIN","Finland","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91154,246,"FIN","Finland","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91155,246,"FIN","Finland","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91156,246,"FIN","Finland","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91157,246,"FIN","Finland","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91158,246,"FIN","Finland","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91159,246,"FIN","Finland","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91160,246,"FIN","Finland","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91161,246,"FIN","Finland","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91162,246,"FIN","Finland","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91163,246,"FIN","Finland","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91164,246,"FIN","Finland","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91165,246,"FIN","Finland","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91166,246,"FIN","Finland","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91167,246,"FIN","Finland","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91168,246,"FIN","Finland","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91169,246,"FIN","Finland","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91170,246,"FIN","Finland","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91171,246,"FIN","Finland","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91172,246,"FIN","Finland","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91173,246,"FIN","Finland","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91174,246,"FIN","Finland","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91175,246,"FIN","Finland","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91176,246,"FIN","Finland","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91177,246,"FIN","Finland","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FIN/fin_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91178,248,"ALA","Aland Islands ","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91179,248,"ALA","Aland Islands ","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91180,248,"ALA","Aland Islands ","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91181,248,"ALA","Aland Islands ","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91182,248,"ALA","Aland Islands ","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91183,248,"ALA","Aland Islands ","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91184,248,"ALA","Aland Islands ","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91185,248,"ALA","Aland Islands ","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91186,248,"ALA","Aland Islands ","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91187,248,"ALA","Aland Islands ","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91188,248,"ALA","Aland Islands ","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91189,248,"ALA","Aland Islands ","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91190,248,"ALA","Aland Islands ","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91191,248,"ALA","Aland Islands ","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91192,248,"ALA","Aland Islands ","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91193,248,"ALA","Aland Islands ","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91194,248,"ALA","Aland Islands ","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91195,248,"ALA","Aland Islands ","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91196,248,"ALA","Aland Islands ","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91197,248,"ALA","Aland Islands ","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91198,248,"ALA","Aland Islands ","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91199,248,"ALA","Aland Islands ","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91200,248,"ALA","Aland Islands ","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91201,248,"ALA","Aland Islands ","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91202,248,"ALA","Aland Islands ","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91203,248,"ALA","Aland Islands ","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91204,248,"ALA","Aland Islands ","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91205,248,"ALA","Aland Islands ","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91206,248,"ALA","Aland Islands ","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91207,248,"ALA","Aland Islands ","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91208,248,"ALA","Aland Islands ","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91209,248,"ALA","Aland Islands ","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91210,248,"ALA","Aland Islands ","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91211,248,"ALA","Aland Islands ","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91212,248,"ALA","Aland Islands ","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91213,248,"ALA","Aland Islands ","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ALA/ala_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91214,250,"FRA","France","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91215,250,"FRA","France","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91216,250,"FRA","France","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91217,250,"FRA","France","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91218,250,"FRA","France","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91219,250,"FRA","France","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91220,250,"FRA","France","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91221,250,"FRA","France","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91222,250,"FRA","France","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91223,250,"FRA","France","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91224,250,"FRA","France","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91225,250,"FRA","France","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91226,250,"FRA","France","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91227,250,"FRA","France","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91228,250,"FRA","France","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91229,250,"FRA","France","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91230,250,"FRA","France","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91231,250,"FRA","France","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91232,250,"FRA","France","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91233,250,"FRA","France","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91234,250,"FRA","France","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91235,250,"FRA","France","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91236,250,"FRA","France","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91237,250,"FRA","France","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91238,250,"FRA","France","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91239,250,"FRA","France","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91240,250,"FRA","France","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91241,250,"FRA","France","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91242,250,"FRA","France","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91243,250,"FRA","France","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91244,250,"FRA","France","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91245,250,"FRA","France","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91246,250,"FRA","France","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91247,250,"FRA","France","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91248,250,"FRA","France","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91249,250,"FRA","France","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FRA/fra_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91250,254,"GUF","French Guiana","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91251,254,"GUF","French Guiana","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91252,254,"GUF","French Guiana","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91253,254,"GUF","French Guiana","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91254,254,"GUF","French Guiana","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91255,254,"GUF","French Guiana","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91256,254,"GUF","French Guiana","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91257,254,"GUF","French Guiana","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91258,254,"GUF","French Guiana","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91259,254,"GUF","French Guiana","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91260,254,"GUF","French Guiana","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91261,254,"GUF","French Guiana","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91262,254,"GUF","French Guiana","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91263,254,"GUF","French Guiana","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91264,254,"GUF","French Guiana","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91265,254,"GUF","French Guiana","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91266,254,"GUF","French Guiana","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91267,254,"GUF","French Guiana","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91268,254,"GUF","French Guiana","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91269,254,"GUF","French Guiana","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91270,254,"GUF","French Guiana","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91271,254,"GUF","French Guiana","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91272,254,"GUF","French Guiana","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91273,254,"GUF","French Guiana","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91274,254,"GUF","French Guiana","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91275,254,"GUF","French Guiana","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91276,254,"GUF","French Guiana","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91277,254,"GUF","French Guiana","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91278,254,"GUF","French Guiana","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91279,254,"GUF","French Guiana","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91280,254,"GUF","French Guiana","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91281,254,"GUF","French Guiana","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91282,254,"GUF","French Guiana","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91283,254,"GUF","French Guiana","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91284,254,"GUF","French Guiana","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91285,254,"GUF","French Guiana","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUF/guf_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91286,258,"PYF","French Polynesia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91287,258,"PYF","French Polynesia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91288,258,"PYF","French Polynesia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91289,258,"PYF","French Polynesia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91290,258,"PYF","French Polynesia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91291,258,"PYF","French Polynesia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91292,258,"PYF","French Polynesia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91293,258,"PYF","French Polynesia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91294,258,"PYF","French Polynesia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91295,258,"PYF","French Polynesia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91296,258,"PYF","French Polynesia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91297,258,"PYF","French Polynesia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91298,258,"PYF","French Polynesia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91299,258,"PYF","French Polynesia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91300,258,"PYF","French Polynesia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91301,258,"PYF","French Polynesia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91302,258,"PYF","French Polynesia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91303,258,"PYF","French Polynesia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91304,258,"PYF","French Polynesia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91305,258,"PYF","French Polynesia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91306,258,"PYF","French Polynesia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91307,258,"PYF","French Polynesia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91308,258,"PYF","French Polynesia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91309,258,"PYF","French Polynesia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91310,258,"PYF","French Polynesia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91311,258,"PYF","French Polynesia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91312,258,"PYF","French Polynesia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91313,258,"PYF","French Polynesia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91314,258,"PYF","French Polynesia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91315,258,"PYF","French Polynesia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91316,258,"PYF","French Polynesia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91317,258,"PYF","French Polynesia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91318,258,"PYF","French Polynesia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91319,258,"PYF","French Polynesia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91320,258,"PYF","French Polynesia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91321,258,"PYF","French Polynesia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PYF/pyf_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91322,262,"DJI","Djibouti","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91323,262,"DJI","Djibouti","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91324,262,"DJI","Djibouti","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91325,262,"DJI","Djibouti","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91326,262,"DJI","Djibouti","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91327,262,"DJI","Djibouti","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91328,262,"DJI","Djibouti","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91329,262,"DJI","Djibouti","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91330,262,"DJI","Djibouti","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91331,262,"DJI","Djibouti","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91332,262,"DJI","Djibouti","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91333,262,"DJI","Djibouti","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91334,262,"DJI","Djibouti","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91335,262,"DJI","Djibouti","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91336,262,"DJI","Djibouti","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91337,262,"DJI","Djibouti","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91338,262,"DJI","Djibouti","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91339,262,"DJI","Djibouti","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91340,262,"DJI","Djibouti","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91341,262,"DJI","Djibouti","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91342,262,"DJI","Djibouti","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91343,262,"DJI","Djibouti","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91344,262,"DJI","Djibouti","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91345,262,"DJI","Djibouti","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91346,262,"DJI","Djibouti","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91347,262,"DJI","Djibouti","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91348,262,"DJI","Djibouti","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91349,262,"DJI","Djibouti","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91350,262,"DJI","Djibouti","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91351,262,"DJI","Djibouti","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91352,262,"DJI","Djibouti","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91353,262,"DJI","Djibouti","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91354,262,"DJI","Djibouti","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91355,262,"DJI","Djibouti","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91356,262,"DJI","Djibouti","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91357,262,"DJI","Djibouti","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DJI/dji_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91358,266,"GAB","Gabon","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91359,266,"GAB","Gabon","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91360,266,"GAB","Gabon","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91361,266,"GAB","Gabon","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91362,266,"GAB","Gabon","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91363,266,"GAB","Gabon","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91364,266,"GAB","Gabon","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91365,266,"GAB","Gabon","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91366,266,"GAB","Gabon","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91367,266,"GAB","Gabon","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91368,266,"GAB","Gabon","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91369,266,"GAB","Gabon","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91370,266,"GAB","Gabon","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91371,266,"GAB","Gabon","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91372,266,"GAB","Gabon","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91373,266,"GAB","Gabon","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91374,266,"GAB","Gabon","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91375,266,"GAB","Gabon","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91376,266,"GAB","Gabon","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91377,266,"GAB","Gabon","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91378,266,"GAB","Gabon","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91379,266,"GAB","Gabon","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91380,266,"GAB","Gabon","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91381,266,"GAB","Gabon","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91382,266,"GAB","Gabon","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91383,266,"GAB","Gabon","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91384,266,"GAB","Gabon","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91385,266,"GAB","Gabon","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91386,266,"GAB","Gabon","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91387,266,"GAB","Gabon","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91388,266,"GAB","Gabon","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91389,266,"GAB","Gabon","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91390,266,"GAB","Gabon","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91391,266,"GAB","Gabon","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91392,266,"GAB","Gabon","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91393,266,"GAB","Gabon","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GAB/gab_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91394,268,"GEO","Georgia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91395,268,"GEO","Georgia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91396,268,"GEO","Georgia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91397,268,"GEO","Georgia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91398,268,"GEO","Georgia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91399,268,"GEO","Georgia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91400,268,"GEO","Georgia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91401,268,"GEO","Georgia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91402,268,"GEO","Georgia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91403,268,"GEO","Georgia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91404,268,"GEO","Georgia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91405,268,"GEO","Georgia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91406,268,"GEO","Georgia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91407,268,"GEO","Georgia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91408,268,"GEO","Georgia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91409,268,"GEO","Georgia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91410,268,"GEO","Georgia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91411,268,"GEO","Georgia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91412,268,"GEO","Georgia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91413,268,"GEO","Georgia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91414,268,"GEO","Georgia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91415,268,"GEO","Georgia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91416,268,"GEO","Georgia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91417,268,"GEO","Georgia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91418,268,"GEO","Georgia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91419,268,"GEO","Georgia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91420,268,"GEO","Georgia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91421,268,"GEO","Georgia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91422,268,"GEO","Georgia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91423,268,"GEO","Georgia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91424,268,"GEO","Georgia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91425,268,"GEO","Georgia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91426,268,"GEO","Georgia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91427,268,"GEO","Georgia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91428,268,"GEO","Georgia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91429,268,"GEO","Georgia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GEO/geo_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91430,270,"GMB","Gambia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91431,270,"GMB","Gambia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91432,270,"GMB","Gambia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91433,270,"GMB","Gambia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91434,270,"GMB","Gambia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91435,270,"GMB","Gambia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91436,270,"GMB","Gambia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91437,270,"GMB","Gambia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91438,270,"GMB","Gambia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91439,270,"GMB","Gambia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91440,270,"GMB","Gambia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91441,270,"GMB","Gambia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91442,270,"GMB","Gambia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91443,270,"GMB","Gambia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91444,270,"GMB","Gambia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91445,270,"GMB","Gambia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91446,270,"GMB","Gambia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91447,270,"GMB","Gambia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91448,270,"GMB","Gambia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91449,270,"GMB","Gambia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91450,270,"GMB","Gambia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91451,270,"GMB","Gambia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91452,270,"GMB","Gambia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91453,270,"GMB","Gambia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91454,270,"GMB","Gambia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91455,270,"GMB","Gambia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91456,270,"GMB","Gambia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91457,270,"GMB","Gambia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91458,270,"GMB","Gambia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91459,270,"GMB","Gambia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91460,270,"GMB","Gambia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91461,270,"GMB","Gambia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91462,270,"GMB","Gambia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91463,270,"GMB","Gambia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91464,270,"GMB","Gambia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91465,270,"GMB","Gambia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GMB/gmb_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91466,275,"PSE","Palestina","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91467,275,"PSE","Palestina","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91468,275,"PSE","Palestina","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91469,275,"PSE","Palestina","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91470,275,"PSE","Palestina","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91471,275,"PSE","Palestina","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91472,275,"PSE","Palestina","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91473,275,"PSE","Palestina","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91474,275,"PSE","Palestina","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91475,275,"PSE","Palestina","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91476,275,"PSE","Palestina","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91477,275,"PSE","Palestina","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91478,275,"PSE","Palestina","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91479,275,"PSE","Palestina","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91480,275,"PSE","Palestina","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91481,275,"PSE","Palestina","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91482,275,"PSE","Palestina","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91483,275,"PSE","Palestina","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91484,275,"PSE","Palestina","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91485,275,"PSE","Palestina","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91486,275,"PSE","Palestina","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91487,275,"PSE","Palestina","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91488,275,"PSE","Palestina","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91489,275,"PSE","Palestina","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91490,275,"PSE","Palestina","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91491,275,"PSE","Palestina","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91492,275,"PSE","Palestina","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91493,275,"PSE","Palestina","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91494,275,"PSE","Palestina","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91495,275,"PSE","Palestina","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91496,275,"PSE","Palestina","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91497,275,"PSE","Palestina","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91498,275,"PSE","Palestina","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91499,275,"PSE","Palestina","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91500,275,"PSE","Palestina","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91501,275,"PSE","Palestina","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PSE/pse_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91502,276,"DEU","Germany","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91503,276,"DEU","Germany","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91504,276,"DEU","Germany","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91505,276,"DEU","Germany","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91506,276,"DEU","Germany","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91507,276,"DEU","Germany","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91508,276,"DEU","Germany","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91509,276,"DEU","Germany","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91510,276,"DEU","Germany","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91511,276,"DEU","Germany","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91512,276,"DEU","Germany","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91513,276,"DEU","Germany","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91514,276,"DEU","Germany","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91515,276,"DEU","Germany","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91516,276,"DEU","Germany","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91517,276,"DEU","Germany","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91518,276,"DEU","Germany","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91519,276,"DEU","Germany","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91520,276,"DEU","Germany","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91521,276,"DEU","Germany","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91522,276,"DEU","Germany","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91523,276,"DEU","Germany","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91524,276,"DEU","Germany","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91525,276,"DEU","Germany","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91526,276,"DEU","Germany","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91527,276,"DEU","Germany","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91528,276,"DEU","Germany","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91529,276,"DEU","Germany","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91530,276,"DEU","Germany","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91531,276,"DEU","Germany","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91532,276,"DEU","Germany","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91533,276,"DEU","Germany","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91534,276,"DEU","Germany","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91535,276,"DEU","Germany","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91536,276,"DEU","Germany","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91537,276,"DEU","Germany","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/DEU/deu_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91538,288,"GHA","Ghana","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91539,288,"GHA","Ghana","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91540,288,"GHA","Ghana","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91541,288,"GHA","Ghana","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91542,288,"GHA","Ghana","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91543,288,"GHA","Ghana","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91544,288,"GHA","Ghana","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91545,288,"GHA","Ghana","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91546,288,"GHA","Ghana","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91547,288,"GHA","Ghana","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91548,288,"GHA","Ghana","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91549,288,"GHA","Ghana","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91550,288,"GHA","Ghana","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91551,288,"GHA","Ghana","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91552,288,"GHA","Ghana","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91553,288,"GHA","Ghana","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91554,288,"GHA","Ghana","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91555,288,"GHA","Ghana","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91556,288,"GHA","Ghana","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91557,288,"GHA","Ghana","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91558,288,"GHA","Ghana","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91559,288,"GHA","Ghana","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91560,288,"GHA","Ghana","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91561,288,"GHA","Ghana","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91562,288,"GHA","Ghana","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91563,288,"GHA","Ghana","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91564,288,"GHA","Ghana","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91565,288,"GHA","Ghana","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91566,288,"GHA","Ghana","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91567,288,"GHA","Ghana","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91568,288,"GHA","Ghana","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91569,288,"GHA","Ghana","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91570,288,"GHA","Ghana","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91571,288,"GHA","Ghana","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91572,288,"GHA","Ghana","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91573,288,"GHA","Ghana","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GHA/gha_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91574,292,"GIB","Gibraltar","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91575,292,"GIB","Gibraltar","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91576,292,"GIB","Gibraltar","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91577,292,"GIB","Gibraltar","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91578,292,"GIB","Gibraltar","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91579,292,"GIB","Gibraltar","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91580,292,"GIB","Gibraltar","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91581,292,"GIB","Gibraltar","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91582,292,"GIB","Gibraltar","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91583,292,"GIB","Gibraltar","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91584,292,"GIB","Gibraltar","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91585,292,"GIB","Gibraltar","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91586,292,"GIB","Gibraltar","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91587,292,"GIB","Gibraltar","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91588,292,"GIB","Gibraltar","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91589,292,"GIB","Gibraltar","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91590,292,"GIB","Gibraltar","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91591,292,"GIB","Gibraltar","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91592,292,"GIB","Gibraltar","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91593,292,"GIB","Gibraltar","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91594,292,"GIB","Gibraltar","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91595,292,"GIB","Gibraltar","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91596,292,"GIB","Gibraltar","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91597,292,"GIB","Gibraltar","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91598,292,"GIB","Gibraltar","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91599,292,"GIB","Gibraltar","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91600,292,"GIB","Gibraltar","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91601,292,"GIB","Gibraltar","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91602,292,"GIB","Gibraltar","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91603,292,"GIB","Gibraltar","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91604,292,"GIB","Gibraltar","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91605,292,"GIB","Gibraltar","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91606,292,"GIB","Gibraltar","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91607,292,"GIB","Gibraltar","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91608,292,"GIB","Gibraltar","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91609,292,"GIB","Gibraltar","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIB/gib_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91610,296,"KIR","Kiribati","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91611,296,"KIR","Kiribati","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91612,296,"KIR","Kiribati","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91613,296,"KIR","Kiribati","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91614,296,"KIR","Kiribati","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91615,296,"KIR","Kiribati","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91616,296,"KIR","Kiribati","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91617,296,"KIR","Kiribati","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91618,296,"KIR","Kiribati","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91619,296,"KIR","Kiribati","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91620,296,"KIR","Kiribati","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91621,296,"KIR","Kiribati","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91622,296,"KIR","Kiribati","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91623,296,"KIR","Kiribati","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91624,296,"KIR","Kiribati","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91625,296,"KIR","Kiribati","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91626,296,"KIR","Kiribati","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91627,296,"KIR","Kiribati","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91628,296,"KIR","Kiribati","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91629,296,"KIR","Kiribati","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91630,296,"KIR","Kiribati","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91631,296,"KIR","Kiribati","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91632,296,"KIR","Kiribati","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91633,296,"KIR","Kiribati","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91634,296,"KIR","Kiribati","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91635,296,"KIR","Kiribati","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91636,296,"KIR","Kiribati","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91637,296,"KIR","Kiribati","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91638,296,"KIR","Kiribati","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91639,296,"KIR","Kiribati","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91640,296,"KIR","Kiribati","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91641,296,"KIR","Kiribati","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91642,296,"KIR","Kiribati","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91643,296,"KIR","Kiribati","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91644,296,"KIR","Kiribati","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91645,296,"KIR","Kiribati","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KIR/kir_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91646,300,"GRC","Greece","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91647,300,"GRC","Greece","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91648,300,"GRC","Greece","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91649,300,"GRC","Greece","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91650,300,"GRC","Greece","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91651,300,"GRC","Greece","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91652,300,"GRC","Greece","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91653,300,"GRC","Greece","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91654,300,"GRC","Greece","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91655,300,"GRC","Greece","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91656,300,"GRC","Greece","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91657,300,"GRC","Greece","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91658,300,"GRC","Greece","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91659,300,"GRC","Greece","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91660,300,"GRC","Greece","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91661,300,"GRC","Greece","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91662,300,"GRC","Greece","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91663,300,"GRC","Greece","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91664,300,"GRC","Greece","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91665,300,"GRC","Greece","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91666,300,"GRC","Greece","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91667,300,"GRC","Greece","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91668,300,"GRC","Greece","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91669,300,"GRC","Greece","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91670,300,"GRC","Greece","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91671,300,"GRC","Greece","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91672,300,"GRC","Greece","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91673,300,"GRC","Greece","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91674,300,"GRC","Greece","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91675,300,"GRC","Greece","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91676,300,"GRC","Greece","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91677,300,"GRC","Greece","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91678,300,"GRC","Greece","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91679,300,"GRC","Greece","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91680,300,"GRC","Greece","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91681,300,"GRC","Greece","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRC/grc_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91682,308,"GRD","Grenada","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91683,308,"GRD","Grenada","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91684,308,"GRD","Grenada","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91685,308,"GRD","Grenada","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91686,308,"GRD","Grenada","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91687,308,"GRD","Grenada","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91688,308,"GRD","Grenada","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91689,308,"GRD","Grenada","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91690,308,"GRD","Grenada","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91691,308,"GRD","Grenada","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91692,308,"GRD","Grenada","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91693,308,"GRD","Grenada","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91694,308,"GRD","Grenada","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91695,308,"GRD","Grenada","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91696,308,"GRD","Grenada","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91697,308,"GRD","Grenada","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91698,308,"GRD","Grenada","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91699,308,"GRD","Grenada","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91700,308,"GRD","Grenada","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91701,308,"GRD","Grenada","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91702,308,"GRD","Grenada","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91703,308,"GRD","Grenada","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91704,308,"GRD","Grenada","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91705,308,"GRD","Grenada","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91706,308,"GRD","Grenada","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91707,308,"GRD","Grenada","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91708,308,"GRD","Grenada","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91709,308,"GRD","Grenada","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91710,308,"GRD","Grenada","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91711,308,"GRD","Grenada","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91712,308,"GRD","Grenada","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91713,308,"GRD","Grenada","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91714,308,"GRD","Grenada","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91715,308,"GRD","Grenada","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91716,308,"GRD","Grenada","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91717,308,"GRD","Grenada","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GRD/grd_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91718,312,"GLP","Guadeloupe","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91719,312,"GLP","Guadeloupe","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91720,312,"GLP","Guadeloupe","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91721,312,"GLP","Guadeloupe","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91722,312,"GLP","Guadeloupe","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91723,312,"GLP","Guadeloupe","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91724,312,"GLP","Guadeloupe","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91725,312,"GLP","Guadeloupe","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91726,312,"GLP","Guadeloupe","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91727,312,"GLP","Guadeloupe","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91728,312,"GLP","Guadeloupe","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91729,312,"GLP","Guadeloupe","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91730,312,"GLP","Guadeloupe","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91731,312,"GLP","Guadeloupe","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91732,312,"GLP","Guadeloupe","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91733,312,"GLP","Guadeloupe","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91734,312,"GLP","Guadeloupe","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91735,312,"GLP","Guadeloupe","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91736,312,"GLP","Guadeloupe","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91737,312,"GLP","Guadeloupe","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91738,312,"GLP","Guadeloupe","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91739,312,"GLP","Guadeloupe","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91740,312,"GLP","Guadeloupe","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91741,312,"GLP","Guadeloupe","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91742,312,"GLP","Guadeloupe","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91743,312,"GLP","Guadeloupe","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91744,312,"GLP","Guadeloupe","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91745,312,"GLP","Guadeloupe","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91746,312,"GLP","Guadeloupe","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91747,312,"GLP","Guadeloupe","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91748,312,"GLP","Guadeloupe","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91749,312,"GLP","Guadeloupe","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91750,312,"GLP","Guadeloupe","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91751,312,"GLP","Guadeloupe","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91752,312,"GLP","Guadeloupe","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91753,312,"GLP","Guadeloupe","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GLP/glp_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91754,316,"GUM","Guam","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91755,316,"GUM","Guam","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91756,316,"GUM","Guam","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91757,316,"GUM","Guam","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91758,316,"GUM","Guam","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91759,316,"GUM","Guam","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91760,316,"GUM","Guam","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91761,316,"GUM","Guam","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91762,316,"GUM","Guam","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91763,316,"GUM","Guam","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91764,316,"GUM","Guam","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91765,316,"GUM","Guam","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91766,316,"GUM","Guam","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91767,316,"GUM","Guam","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91768,316,"GUM","Guam","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91769,316,"GUM","Guam","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91770,316,"GUM","Guam","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91771,316,"GUM","Guam","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91772,316,"GUM","Guam","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91773,316,"GUM","Guam","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91774,316,"GUM","Guam","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91775,316,"GUM","Guam","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91776,316,"GUM","Guam","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91777,316,"GUM","Guam","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91778,316,"GUM","Guam","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91779,316,"GUM","Guam","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91780,316,"GUM","Guam","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91781,316,"GUM","Guam","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91782,316,"GUM","Guam","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91783,316,"GUM","Guam","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91784,316,"GUM","Guam","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91785,316,"GUM","Guam","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91786,316,"GUM","Guam","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91787,316,"GUM","Guam","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91788,316,"GUM","Guam","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91789,316,"GUM","Guam","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUM/gum_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91790,320,"GTM","Guatemala","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91791,320,"GTM","Guatemala","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91792,320,"GTM","Guatemala","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91793,320,"GTM","Guatemala","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91794,320,"GTM","Guatemala","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91795,320,"GTM","Guatemala","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91796,320,"GTM","Guatemala","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91797,320,"GTM","Guatemala","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91798,320,"GTM","Guatemala","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91799,320,"GTM","Guatemala","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91800,320,"GTM","Guatemala","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91801,320,"GTM","Guatemala","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91802,320,"GTM","Guatemala","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91803,320,"GTM","Guatemala","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91804,320,"GTM","Guatemala","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91805,320,"GTM","Guatemala","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91806,320,"GTM","Guatemala","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91807,320,"GTM","Guatemala","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91808,320,"GTM","Guatemala","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91809,320,"GTM","Guatemala","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91810,320,"GTM","Guatemala","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91811,320,"GTM","Guatemala","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91812,320,"GTM","Guatemala","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91813,320,"GTM","Guatemala","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91814,320,"GTM","Guatemala","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91815,320,"GTM","Guatemala","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91816,320,"GTM","Guatemala","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91817,320,"GTM","Guatemala","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91818,320,"GTM","Guatemala","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91819,320,"GTM","Guatemala","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91820,320,"GTM","Guatemala","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91821,320,"GTM","Guatemala","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91822,320,"GTM","Guatemala","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91823,320,"GTM","Guatemala","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91824,320,"GTM","Guatemala","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91825,320,"GTM","Guatemala","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GTM/gtm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91826,324,"GIN","Guinea","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91827,324,"GIN","Guinea","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91828,324,"GIN","Guinea","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91829,324,"GIN","Guinea","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91830,324,"GIN","Guinea","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91831,324,"GIN","Guinea","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91832,324,"GIN","Guinea","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91833,324,"GIN","Guinea","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91834,324,"GIN","Guinea","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91835,324,"GIN","Guinea","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91836,324,"GIN","Guinea","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91837,324,"GIN","Guinea","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91838,324,"GIN","Guinea","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91839,324,"GIN","Guinea","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91840,324,"GIN","Guinea","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91841,324,"GIN","Guinea","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91842,324,"GIN","Guinea","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91843,324,"GIN","Guinea","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91844,324,"GIN","Guinea","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91845,324,"GIN","Guinea","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91846,324,"GIN","Guinea","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91847,324,"GIN","Guinea","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91848,324,"GIN","Guinea","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91849,324,"GIN","Guinea","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91850,324,"GIN","Guinea","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91851,324,"GIN","Guinea","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91852,324,"GIN","Guinea","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91853,324,"GIN","Guinea","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91854,324,"GIN","Guinea","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91855,324,"GIN","Guinea","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91856,324,"GIN","Guinea","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91857,324,"GIN","Guinea","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91858,324,"GIN","Guinea","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91859,324,"GIN","Guinea","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91860,324,"GIN","Guinea","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91861,324,"GIN","Guinea","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GIN/gin_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
91862,328,"GUY","Guyana","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91863,328,"GUY","Guyana","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91864,328,"GUY","Guyana","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91865,328,"GUY","Guyana","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91866,328,"GUY","Guyana","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91867,328,"GUY","Guyana","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91868,328,"GUY","Guyana","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91869,328,"GUY","Guyana","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91870,328,"GUY","Guyana","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91871,328,"GUY","Guyana","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91872,328,"GUY","Guyana","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91873,328,"GUY","Guyana","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91874,328,"GUY","Guyana","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91875,328,"GUY","Guyana","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91876,328,"GUY","Guyana","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91877,328,"GUY","Guyana","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91878,328,"GUY","Guyana","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91879,328,"GUY","Guyana","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91880,328,"GUY","Guyana","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91881,328,"GUY","Guyana","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91882,328,"GUY","Guyana","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91883,328,"GUY","Guyana","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91884,328,"GUY","Guyana","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91885,328,"GUY","Guyana","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91886,328,"GUY","Guyana","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91887,328,"GUY","Guyana","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91888,328,"GUY","Guyana","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91889,328,"GUY","Guyana","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91890,328,"GUY","Guyana","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91891,328,"GUY","Guyana","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91892,328,"GUY","Guyana","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91893,328,"GUY","Guyana","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91894,328,"GUY","Guyana","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91895,328,"GUY","Guyana","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91896,328,"GUY","Guyana","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91897,328,"GUY","Guyana","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GUY/guy_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91898,332,"HTI","Haiti","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91899,332,"HTI","Haiti","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91900,332,"HTI","Haiti","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91901,332,"HTI","Haiti","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91902,332,"HTI","Haiti","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91903,332,"HTI","Haiti","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91904,332,"HTI","Haiti","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91905,332,"HTI","Haiti","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91906,332,"HTI","Haiti","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91907,332,"HTI","Haiti","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91908,332,"HTI","Haiti","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91909,332,"HTI","Haiti","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91910,332,"HTI","Haiti","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91911,332,"HTI","Haiti","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91912,332,"HTI","Haiti","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91913,332,"HTI","Haiti","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91914,332,"HTI","Haiti","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91915,332,"HTI","Haiti","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91916,332,"HTI","Haiti","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91917,332,"HTI","Haiti","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91918,332,"HTI","Haiti","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91919,332,"HTI","Haiti","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91920,332,"HTI","Haiti","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91921,332,"HTI","Haiti","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91922,332,"HTI","Haiti","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91923,332,"HTI","Haiti","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91924,332,"HTI","Haiti","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91925,332,"HTI","Haiti","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91926,332,"HTI","Haiti","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91927,332,"HTI","Haiti","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91928,332,"HTI","Haiti","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91929,332,"HTI","Haiti","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91930,332,"HTI","Haiti","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91931,332,"HTI","Haiti","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91932,332,"HTI","Haiti","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91933,332,"HTI","Haiti","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HTI/hti_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91934,336,"VAT","Vatican City","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91935,336,"VAT","Vatican City","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91936,336,"VAT","Vatican City","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91937,336,"VAT","Vatican City","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91938,336,"VAT","Vatican City","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91939,336,"VAT","Vatican City","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91940,336,"VAT","Vatican City","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91941,336,"VAT","Vatican City","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91942,336,"VAT","Vatican City","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91943,336,"VAT","Vatican City","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91944,336,"VAT","Vatican City","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91945,336,"VAT","Vatican City","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91946,336,"VAT","Vatican City","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91947,336,"VAT","Vatican City","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91948,336,"VAT","Vatican City","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91949,336,"VAT","Vatican City","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91950,336,"VAT","Vatican City","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91951,336,"VAT","Vatican City","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91952,336,"VAT","Vatican City","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91953,336,"VAT","Vatican City","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91954,336,"VAT","Vatican City","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91955,336,"VAT","Vatican City","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91956,336,"VAT","Vatican City","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91957,336,"VAT","Vatican City","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91958,336,"VAT","Vatican City","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91959,336,"VAT","Vatican City","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91960,336,"VAT","Vatican City","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91961,336,"VAT","Vatican City","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91962,336,"VAT","Vatican City","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91963,336,"VAT","Vatican City","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91964,336,"VAT","Vatican City","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91965,336,"VAT","Vatican City","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91966,336,"VAT","Vatican City","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91967,336,"VAT","Vatican City","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91968,336,"VAT","Vatican City","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91969,336,"VAT","Vatican City","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VAT/vat_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91970,340,"HND","Honduras","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91971,340,"HND","Honduras","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91972,340,"HND","Honduras","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91973,340,"HND","Honduras","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91974,340,"HND","Honduras","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91975,340,"HND","Honduras","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91976,340,"HND","Honduras","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91977,340,"HND","Honduras","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91978,340,"HND","Honduras","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91979,340,"HND","Honduras","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91980,340,"HND","Honduras","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91981,340,"HND","Honduras","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91982,340,"HND","Honduras","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91983,340,"HND","Honduras","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91984,340,"HND","Honduras","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91985,340,"HND","Honduras","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91986,340,"HND","Honduras","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91987,340,"HND","Honduras","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91988,340,"HND","Honduras","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91989,340,"HND","Honduras","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91990,340,"HND","Honduras","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91991,340,"HND","Honduras","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91992,340,"HND","Honduras","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91993,340,"HND","Honduras","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91994,340,"HND","Honduras","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91995,340,"HND","Honduras","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91996,340,"HND","Honduras","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91997,340,"HND","Honduras","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91998,340,"HND","Honduras","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
91999,340,"HND","Honduras","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92000,340,"HND","Honduras","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92001,340,"HND","Honduras","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92002,340,"HND","Honduras","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92003,340,"HND","Honduras","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92004,340,"HND","Honduras","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92005,340,"HND","Honduras","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HND/hnd_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92006,344,"HKG","Hong Kong","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92007,344,"HKG","Hong Kong","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92008,344,"HKG","Hong Kong","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92009,344,"HKG","Hong Kong","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92010,344,"HKG","Hong Kong","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92011,344,"HKG","Hong Kong","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92012,344,"HKG","Hong Kong","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92013,344,"HKG","Hong Kong","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92014,344,"HKG","Hong Kong","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92015,344,"HKG","Hong Kong","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92016,344,"HKG","Hong Kong","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92017,344,"HKG","Hong Kong","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92018,344,"HKG","Hong Kong","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92019,344,"HKG","Hong Kong","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92020,344,"HKG","Hong Kong","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92021,344,"HKG","Hong Kong","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92022,344,"HKG","Hong Kong","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92023,344,"HKG","Hong Kong","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92024,344,"HKG","Hong Kong","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92025,344,"HKG","Hong Kong","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92026,344,"HKG","Hong Kong","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92027,344,"HKG","Hong Kong","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92028,344,"HKG","Hong Kong","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92029,344,"HKG","Hong Kong","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92030,344,"HKG","Hong Kong","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92031,344,"HKG","Hong Kong","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92032,344,"HKG","Hong Kong","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92033,344,"HKG","Hong Kong","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92034,344,"HKG","Hong Kong","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92035,344,"HKG","Hong Kong","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92036,344,"HKG","Hong Kong","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92037,344,"HKG","Hong Kong","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92038,344,"HKG","Hong Kong","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92039,344,"HKG","Hong Kong","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92040,344,"HKG","Hong Kong","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92041,344,"HKG","Hong Kong","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HKG/hkg_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92042,348,"HUN","Hungary","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92043,348,"HUN","Hungary","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92044,348,"HUN","Hungary","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92045,348,"HUN","Hungary","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92046,348,"HUN","Hungary","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92047,348,"HUN","Hungary","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92048,348,"HUN","Hungary","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92049,348,"HUN","Hungary","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92050,348,"HUN","Hungary","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92051,348,"HUN","Hungary","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92052,348,"HUN","Hungary","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92053,348,"HUN","Hungary","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92054,348,"HUN","Hungary","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92055,348,"HUN","Hungary","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92056,348,"HUN","Hungary","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92057,348,"HUN","Hungary","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92058,348,"HUN","Hungary","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92059,348,"HUN","Hungary","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92060,348,"HUN","Hungary","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92061,348,"HUN","Hungary","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92062,348,"HUN","Hungary","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92063,348,"HUN","Hungary","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92064,348,"HUN","Hungary","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92065,348,"HUN","Hungary","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92066,348,"HUN","Hungary","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92067,348,"HUN","Hungary","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92068,348,"HUN","Hungary","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92069,348,"HUN","Hungary","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92070,348,"HUN","Hungary","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92071,348,"HUN","Hungary","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92072,348,"HUN","Hungary","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92073,348,"HUN","Hungary","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92074,348,"HUN","Hungary","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92075,348,"HUN","Hungary","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92076,348,"HUN","Hungary","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92077,348,"HUN","Hungary","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/HUN/hun_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92078,352,"ISL","Iceland","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92079,352,"ISL","Iceland","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92080,352,"ISL","Iceland","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92081,352,"ISL","Iceland","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92082,352,"ISL","Iceland","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92083,352,"ISL","Iceland","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92084,352,"ISL","Iceland","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92085,352,"ISL","Iceland","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92086,352,"ISL","Iceland","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92087,352,"ISL","Iceland","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92088,352,"ISL","Iceland","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92089,352,"ISL","Iceland","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92090,352,"ISL","Iceland","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92091,352,"ISL","Iceland","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92092,352,"ISL","Iceland","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92093,352,"ISL","Iceland","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92094,352,"ISL","Iceland","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92095,352,"ISL","Iceland","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92096,352,"ISL","Iceland","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92097,352,"ISL","Iceland","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92098,352,"ISL","Iceland","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92099,352,"ISL","Iceland","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92100,352,"ISL","Iceland","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92101,352,"ISL","Iceland","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92102,352,"ISL","Iceland","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92103,352,"ISL","Iceland","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92104,352,"ISL","Iceland","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92105,352,"ISL","Iceland","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92106,352,"ISL","Iceland","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92107,352,"ISL","Iceland","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92108,352,"ISL","Iceland","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92109,352,"ISL","Iceland","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92110,352,"ISL","Iceland","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92111,352,"ISL","Iceland","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92112,352,"ISL","Iceland","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92113,352,"ISL","Iceland","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISL/isl_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92114,356,"IND","India","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92115,356,"IND","India","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92116,356,"IND","India","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92117,356,"IND","India","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92118,356,"IND","India","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92119,356,"IND","India","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92120,356,"IND","India","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92121,356,"IND","India","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92122,356,"IND","India","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92123,356,"IND","India","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92124,356,"IND","India","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92125,356,"IND","India","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92126,356,"IND","India","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92127,356,"IND","India","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92128,356,"IND","India","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92129,356,"IND","India","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92130,356,"IND","India","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92131,356,"IND","India","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92132,356,"IND","India","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92133,356,"IND","India","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92134,356,"IND","India","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92135,356,"IND","India","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92136,356,"IND","India","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92137,356,"IND","India","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92138,356,"IND","India","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92139,356,"IND","India","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92140,356,"IND","India","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92141,356,"IND","India","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92142,356,"IND","India","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92143,356,"IND","India","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92144,356,"IND","India","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92145,356,"IND","India","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92146,356,"IND","India","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92147,356,"IND","India","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92148,356,"IND","India","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92149,356,"IND","India","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IND/ind_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92150,364,"IRN","Iran","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92151,364,"IRN","Iran","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92152,364,"IRN","Iran","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92153,364,"IRN","Iran","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92154,364,"IRN","Iran","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92155,364,"IRN","Iran","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92156,364,"IRN","Iran","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92157,364,"IRN","Iran","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92158,364,"IRN","Iran","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92159,364,"IRN","Iran","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92160,364,"IRN","Iran","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92161,364,"IRN","Iran","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92162,364,"IRN","Iran","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92163,364,"IRN","Iran","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92164,364,"IRN","Iran","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92165,364,"IRN","Iran","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92166,364,"IRN","Iran","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92167,364,"IRN","Iran","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92168,364,"IRN","Iran","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92169,364,"IRN","Iran","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92170,364,"IRN","Iran","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92171,364,"IRN","Iran","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92172,364,"IRN","Iran","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92173,364,"IRN","Iran","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92174,364,"IRN","Iran","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92175,364,"IRN","Iran","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92176,364,"IRN","Iran","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92177,364,"IRN","Iran","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92178,364,"IRN","Iran","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92179,364,"IRN","Iran","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92180,364,"IRN","Iran","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92181,364,"IRN","Iran","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92182,364,"IRN","Iran","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92183,364,"IRN","Iran","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92184,364,"IRN","Iran","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92185,364,"IRN","Iran","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRN/irn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92186,368,"IRQ","Iraq","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92187,368,"IRQ","Iraq","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92188,368,"IRQ","Iraq","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92189,368,"IRQ","Iraq","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92190,368,"IRQ","Iraq","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92191,368,"IRQ","Iraq","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92192,368,"IRQ","Iraq","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92193,368,"IRQ","Iraq","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92194,368,"IRQ","Iraq","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92195,368,"IRQ","Iraq","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92196,368,"IRQ","Iraq","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92197,368,"IRQ","Iraq","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92198,368,"IRQ","Iraq","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92199,368,"IRQ","Iraq","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92200,368,"IRQ","Iraq","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92201,368,"IRQ","Iraq","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92202,368,"IRQ","Iraq","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92203,368,"IRQ","Iraq","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92204,368,"IRQ","Iraq","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92205,368,"IRQ","Iraq","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92206,368,"IRQ","Iraq","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92207,368,"IRQ","Iraq","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92208,368,"IRQ","Iraq","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92209,368,"IRQ","Iraq","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92210,368,"IRQ","Iraq","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92211,368,"IRQ","Iraq","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92212,368,"IRQ","Iraq","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92213,368,"IRQ","Iraq","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92214,368,"IRQ","Iraq","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92215,368,"IRQ","Iraq","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92216,368,"IRQ","Iraq","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92217,368,"IRQ","Iraq","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92218,368,"IRQ","Iraq","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92219,368,"IRQ","Iraq","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92220,368,"IRQ","Iraq","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92221,368,"IRQ","Iraq","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRQ/irq_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92222,372,"IRL","Ireland","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92223,372,"IRL","Ireland","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92224,372,"IRL","Ireland","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92225,372,"IRL","Ireland","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92226,372,"IRL","Ireland","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92227,372,"IRL","Ireland","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92228,372,"IRL","Ireland","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92229,372,"IRL","Ireland","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92230,372,"IRL","Ireland","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92231,372,"IRL","Ireland","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92232,372,"IRL","Ireland","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92233,372,"IRL","Ireland","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92234,372,"IRL","Ireland","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92235,372,"IRL","Ireland","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92236,372,"IRL","Ireland","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92237,372,"IRL","Ireland","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92238,372,"IRL","Ireland","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92239,372,"IRL","Ireland","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92240,372,"IRL","Ireland","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92241,372,"IRL","Ireland","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92242,372,"IRL","Ireland","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92243,372,"IRL","Ireland","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92244,372,"IRL","Ireland","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92245,372,"IRL","Ireland","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92246,372,"IRL","Ireland","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92247,372,"IRL","Ireland","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92248,372,"IRL","Ireland","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92249,372,"IRL","Ireland","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92250,372,"IRL","Ireland","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92251,372,"IRL","Ireland","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92252,372,"IRL","Ireland","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92253,372,"IRL","Ireland","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92254,372,"IRL","Ireland","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92255,372,"IRL","Ireland","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92256,372,"IRL","Ireland","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92257,372,"IRL","Ireland","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IRL/irl_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92258,376,"ISR","Israel","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92259,376,"ISR","Israel","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92260,376,"ISR","Israel","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92261,376,"ISR","Israel","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92262,376,"ISR","Israel","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92263,376,"ISR","Israel","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92264,376,"ISR","Israel","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92265,376,"ISR","Israel","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92266,376,"ISR","Israel","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92267,376,"ISR","Israel","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92268,376,"ISR","Israel","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92269,376,"ISR","Israel","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92270,376,"ISR","Israel","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92271,376,"ISR","Israel","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92272,376,"ISR","Israel","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92273,376,"ISR","Israel","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92274,376,"ISR","Israel","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92275,376,"ISR","Israel","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92276,376,"ISR","Israel","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92277,376,"ISR","Israel","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92278,376,"ISR","Israel","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92279,376,"ISR","Israel","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92280,376,"ISR","Israel","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92281,376,"ISR","Israel","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92282,376,"ISR","Israel","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92283,376,"ISR","Israel","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92284,376,"ISR","Israel","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92285,376,"ISR","Israel","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92286,376,"ISR","Israel","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92287,376,"ISR","Israel","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92288,376,"ISR","Israel","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92289,376,"ISR","Israel","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92290,376,"ISR","Israel","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92291,376,"ISR","Israel","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92292,376,"ISR","Israel","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92293,376,"ISR","Israel","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ISR/isr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92294,380,"ITA","Italy","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92295,380,"ITA","Italy","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92296,380,"ITA","Italy","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92297,380,"ITA","Italy","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92298,380,"ITA","Italy","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92299,380,"ITA","Italy","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92300,380,"ITA","Italy","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92301,380,"ITA","Italy","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92302,380,"ITA","Italy","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92303,380,"ITA","Italy","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92304,380,"ITA","Italy","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92305,380,"ITA","Italy","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92306,380,"ITA","Italy","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92307,380,"ITA","Italy","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92308,380,"ITA","Italy","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92309,380,"ITA","Italy","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92310,380,"ITA","Italy","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92311,380,"ITA","Italy","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92312,380,"ITA","Italy","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92313,380,"ITA","Italy","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92314,380,"ITA","Italy","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92315,380,"ITA","Italy","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92316,380,"ITA","Italy","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92317,380,"ITA","Italy","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92318,380,"ITA","Italy","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92319,380,"ITA","Italy","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92320,380,"ITA","Italy","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92321,380,"ITA","Italy","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92322,380,"ITA","Italy","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92323,380,"ITA","Italy","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92324,380,"ITA","Italy","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92325,380,"ITA","Italy","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92326,380,"ITA","Italy","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92327,380,"ITA","Italy","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92328,380,"ITA","Italy","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92329,380,"ITA","Italy","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ITA/ita_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92330,384,"CIV","CIte dIvoire","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92331,384,"CIV","CIte dIvoire","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92332,384,"CIV","CIte dIvoire","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92333,384,"CIV","CIte dIvoire","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92334,384,"CIV","CIte dIvoire","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92335,384,"CIV","CIte dIvoire","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92336,384,"CIV","CIte dIvoire","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92337,384,"CIV","CIte dIvoire","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92338,384,"CIV","CIte dIvoire","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92339,384,"CIV","CIte dIvoire","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92340,384,"CIV","CIte dIvoire","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92341,384,"CIV","CIte dIvoire","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92342,384,"CIV","CIte dIvoire","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92343,384,"CIV","CIte dIvoire","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92344,384,"CIV","CIte dIvoire","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92345,384,"CIV","CIte dIvoire","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92346,384,"CIV","CIte dIvoire","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92347,384,"CIV","CIte dIvoire","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92348,384,"CIV","CIte dIvoire","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92349,384,"CIV","CIte dIvoire","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92350,384,"CIV","CIte dIvoire","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92351,384,"CIV","CIte dIvoire","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92352,384,"CIV","CIte dIvoire","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92353,384,"CIV","CIte dIvoire","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92354,384,"CIV","CIte dIvoire","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92355,384,"CIV","CIte dIvoire","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92356,384,"CIV","CIte dIvoire","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92357,384,"CIV","CIte dIvoire","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92358,384,"CIV","CIte dIvoire","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92359,384,"CIV","CIte dIvoire","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92360,384,"CIV","CIte dIvoire","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92361,384,"CIV","CIte dIvoire","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92362,384,"CIV","CIte dIvoire","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92363,384,"CIV","CIte dIvoire","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92364,384,"CIV","CIte dIvoire","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92365,384,"CIV","CIte dIvoire","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CIV/civ_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92366,388,"JAM","Jamaica","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92367,388,"JAM","Jamaica","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92368,388,"JAM","Jamaica","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92369,388,"JAM","Jamaica","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92370,388,"JAM","Jamaica","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92371,388,"JAM","Jamaica","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92372,388,"JAM","Jamaica","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92373,388,"JAM","Jamaica","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92374,388,"JAM","Jamaica","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92375,388,"JAM","Jamaica","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92376,388,"JAM","Jamaica","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92377,388,"JAM","Jamaica","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92378,388,"JAM","Jamaica","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92379,388,"JAM","Jamaica","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92380,388,"JAM","Jamaica","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92381,388,"JAM","Jamaica","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92382,388,"JAM","Jamaica","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92383,388,"JAM","Jamaica","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92384,388,"JAM","Jamaica","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92385,388,"JAM","Jamaica","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92386,388,"JAM","Jamaica","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92387,388,"JAM","Jamaica","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92388,388,"JAM","Jamaica","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92389,388,"JAM","Jamaica","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92390,388,"JAM","Jamaica","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92391,388,"JAM","Jamaica","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92392,388,"JAM","Jamaica","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92393,388,"JAM","Jamaica","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92394,388,"JAM","Jamaica","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92395,388,"JAM","Jamaica","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92396,388,"JAM","Jamaica","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92397,388,"JAM","Jamaica","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92398,388,"JAM","Jamaica","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92399,388,"JAM","Jamaica","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92400,388,"JAM","Jamaica","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92401,388,"JAM","Jamaica","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JAM/jam_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92402,392,"JPN","Japan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92403,392,"JPN","Japan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92404,392,"JPN","Japan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92405,392,"JPN","Japan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92406,392,"JPN","Japan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92407,392,"JPN","Japan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92408,392,"JPN","Japan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92409,392,"JPN","Japan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92410,392,"JPN","Japan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92411,392,"JPN","Japan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92412,392,"JPN","Japan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92413,392,"JPN","Japan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92414,392,"JPN","Japan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92415,392,"JPN","Japan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92416,392,"JPN","Japan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92417,392,"JPN","Japan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92418,392,"JPN","Japan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92419,392,"JPN","Japan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92420,392,"JPN","Japan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92421,392,"JPN","Japan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92422,392,"JPN","Japan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92423,392,"JPN","Japan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92424,392,"JPN","Japan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92425,392,"JPN","Japan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92426,392,"JPN","Japan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92427,392,"JPN","Japan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92428,392,"JPN","Japan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92429,392,"JPN","Japan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92430,392,"JPN","Japan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92431,392,"JPN","Japan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92432,392,"JPN","Japan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92433,392,"JPN","Japan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92434,392,"JPN","Japan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92435,392,"JPN","Japan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92436,392,"JPN","Japan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92437,392,"JPN","Japan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JPN/jpn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92438,398,"KAZ","Kazakhstan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92439,398,"KAZ","Kazakhstan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92440,398,"KAZ","Kazakhstan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92441,398,"KAZ","Kazakhstan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92442,398,"KAZ","Kazakhstan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92443,398,"KAZ","Kazakhstan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92444,398,"KAZ","Kazakhstan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92445,398,"KAZ","Kazakhstan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92446,398,"KAZ","Kazakhstan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92447,398,"KAZ","Kazakhstan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92448,398,"KAZ","Kazakhstan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92449,398,"KAZ","Kazakhstan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92450,398,"KAZ","Kazakhstan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92451,398,"KAZ","Kazakhstan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92452,398,"KAZ","Kazakhstan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92453,398,"KAZ","Kazakhstan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92454,398,"KAZ","Kazakhstan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92455,398,"KAZ","Kazakhstan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92456,398,"KAZ","Kazakhstan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92457,398,"KAZ","Kazakhstan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92458,398,"KAZ","Kazakhstan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92459,398,"KAZ","Kazakhstan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92460,398,"KAZ","Kazakhstan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92461,398,"KAZ","Kazakhstan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92462,398,"KAZ","Kazakhstan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92463,398,"KAZ","Kazakhstan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92464,398,"KAZ","Kazakhstan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92465,398,"KAZ","Kazakhstan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92466,398,"KAZ","Kazakhstan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92467,398,"KAZ","Kazakhstan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92468,398,"KAZ","Kazakhstan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92469,398,"KAZ","Kazakhstan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92470,398,"KAZ","Kazakhstan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92471,398,"KAZ","Kazakhstan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92472,398,"KAZ","Kazakhstan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92473,398,"KAZ","Kazakhstan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KAZ/kaz_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92474,400,"JOR","Jordan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92475,400,"JOR","Jordan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92476,400,"JOR","Jordan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92477,400,"JOR","Jordan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92478,400,"JOR","Jordan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92479,400,"JOR","Jordan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92480,400,"JOR","Jordan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92481,400,"JOR","Jordan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92482,400,"JOR","Jordan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92483,400,"JOR","Jordan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92484,400,"JOR","Jordan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92485,400,"JOR","Jordan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92486,400,"JOR","Jordan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92487,400,"JOR","Jordan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92488,400,"JOR","Jordan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92489,400,"JOR","Jordan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92490,400,"JOR","Jordan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92491,400,"JOR","Jordan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92492,400,"JOR","Jordan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92493,400,"JOR","Jordan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92494,400,"JOR","Jordan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92495,400,"JOR","Jordan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92496,400,"JOR","Jordan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92497,400,"JOR","Jordan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92498,400,"JOR","Jordan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92499,400,"JOR","Jordan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92500,400,"JOR","Jordan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92501,400,"JOR","Jordan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92502,400,"JOR","Jordan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92503,400,"JOR","Jordan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92504,400,"JOR","Jordan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92505,400,"JOR","Jordan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92506,400,"JOR","Jordan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92507,400,"JOR","Jordan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92508,400,"JOR","Jordan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92509,400,"JOR","Jordan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JOR/jor_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92510,404,"KEN","Kenya","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92511,404,"KEN","Kenya","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92512,404,"KEN","Kenya","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92513,404,"KEN","Kenya","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92514,404,"KEN","Kenya","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92515,404,"KEN","Kenya","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92516,404,"KEN","Kenya","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92517,404,"KEN","Kenya","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92518,404,"KEN","Kenya","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92519,404,"KEN","Kenya","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92520,404,"KEN","Kenya","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92521,404,"KEN","Kenya","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92522,404,"KEN","Kenya","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92523,404,"KEN","Kenya","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92524,404,"KEN","Kenya","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92525,404,"KEN","Kenya","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92526,404,"KEN","Kenya","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92527,404,"KEN","Kenya","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92528,404,"KEN","Kenya","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92529,404,"KEN","Kenya","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92530,404,"KEN","Kenya","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92531,404,"KEN","Kenya","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92532,404,"KEN","Kenya","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92533,404,"KEN","Kenya","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92534,404,"KEN","Kenya","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92535,404,"KEN","Kenya","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92536,404,"KEN","Kenya","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92537,404,"KEN","Kenya","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92538,404,"KEN","Kenya","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92539,404,"KEN","Kenya","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92540,404,"KEN","Kenya","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92541,404,"KEN","Kenya","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92542,404,"KEN","Kenya","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92543,404,"KEN","Kenya","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92544,404,"KEN","Kenya","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92545,404,"KEN","Kenya","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KEN/ken_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92546,408,"PRK","North Korea","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92547,408,"PRK","North Korea","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92548,408,"PRK","North Korea","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92549,408,"PRK","North Korea","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92550,408,"PRK","North Korea","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92551,408,"PRK","North Korea","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92552,408,"PRK","North Korea","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92553,408,"PRK","North Korea","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92554,408,"PRK","North Korea","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92555,408,"PRK","North Korea","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92556,408,"PRK","North Korea","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92557,408,"PRK","North Korea","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92558,408,"PRK","North Korea","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92559,408,"PRK","North Korea","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92560,408,"PRK","North Korea","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92561,408,"PRK","North Korea","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92562,408,"PRK","North Korea","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92563,408,"PRK","North Korea","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92564,408,"PRK","North Korea","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92565,408,"PRK","North Korea","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92566,408,"PRK","North Korea","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92567,408,"PRK","North Korea","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92568,408,"PRK","North Korea","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92569,408,"PRK","North Korea","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92570,408,"PRK","North Korea","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92571,408,"PRK","North Korea","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92572,408,"PRK","North Korea","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92573,408,"PRK","North Korea","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92574,408,"PRK","North Korea","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92575,408,"PRK","North Korea","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92576,408,"PRK","North Korea","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92577,408,"PRK","North Korea","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92578,408,"PRK","North Korea","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92579,408,"PRK","North Korea","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92580,408,"PRK","North Korea","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92581,408,"PRK","North Korea","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRK/prk_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92582,410,"KOR","South Korea","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92583,410,"KOR","South Korea","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92584,410,"KOR","South Korea","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92585,410,"KOR","South Korea","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92586,410,"KOR","South Korea","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92587,410,"KOR","South Korea","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92588,410,"KOR","South Korea","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92589,410,"KOR","South Korea","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92590,410,"KOR","South Korea","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92591,410,"KOR","South Korea","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92592,410,"KOR","South Korea","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92593,410,"KOR","South Korea","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92594,410,"KOR","South Korea","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92595,410,"KOR","South Korea","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92596,410,"KOR","South Korea","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92597,410,"KOR","South Korea","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92598,410,"KOR","South Korea","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92599,410,"KOR","South Korea","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92600,410,"KOR","South Korea","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92601,410,"KOR","South Korea","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92602,410,"KOR","South Korea","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92603,410,"KOR","South Korea","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92604,410,"KOR","South Korea","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92605,410,"KOR","South Korea","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92606,410,"KOR","South Korea","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92607,410,"KOR","South Korea","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92608,410,"KOR","South Korea","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92609,410,"KOR","South Korea","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92610,410,"KOR","South Korea","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92611,410,"KOR","South Korea","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92612,410,"KOR","South Korea","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92613,410,"KOR","South Korea","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92614,410,"KOR","South Korea","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92615,410,"KOR","South Korea","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92616,410,"KOR","South Korea","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92617,410,"KOR","South Korea","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOR/kor_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92618,414,"KWT","Kuwait","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92619,414,"KWT","Kuwait","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92620,414,"KWT","Kuwait","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92621,414,"KWT","Kuwait","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92622,414,"KWT","Kuwait","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92623,414,"KWT","Kuwait","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92624,414,"KWT","Kuwait","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92625,414,"KWT","Kuwait","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92626,414,"KWT","Kuwait","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92627,414,"KWT","Kuwait","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92628,414,"KWT","Kuwait","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92629,414,"KWT","Kuwait","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92630,414,"KWT","Kuwait","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92631,414,"KWT","Kuwait","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92632,414,"KWT","Kuwait","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92633,414,"KWT","Kuwait","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92634,414,"KWT","Kuwait","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92635,414,"KWT","Kuwait","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92636,414,"KWT","Kuwait","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92637,414,"KWT","Kuwait","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92638,414,"KWT","Kuwait","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92639,414,"KWT","Kuwait","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92640,414,"KWT","Kuwait","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92641,414,"KWT","Kuwait","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92642,414,"KWT","Kuwait","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92643,414,"KWT","Kuwait","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92644,414,"KWT","Kuwait","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92645,414,"KWT","Kuwait","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92646,414,"KWT","Kuwait","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92647,414,"KWT","Kuwait","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92648,414,"KWT","Kuwait","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92649,414,"KWT","Kuwait","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92650,414,"KWT","Kuwait","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92651,414,"KWT","Kuwait","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92652,414,"KWT","Kuwait","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92653,414,"KWT","Kuwait","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KWT/kwt_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92654,417,"KGZ","Kyrgyzstan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92655,417,"KGZ","Kyrgyzstan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92656,417,"KGZ","Kyrgyzstan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92657,417,"KGZ","Kyrgyzstan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92658,417,"KGZ","Kyrgyzstan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92659,417,"KGZ","Kyrgyzstan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92660,417,"KGZ","Kyrgyzstan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92661,417,"KGZ","Kyrgyzstan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92662,417,"KGZ","Kyrgyzstan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92663,417,"KGZ","Kyrgyzstan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92664,417,"KGZ","Kyrgyzstan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92665,417,"KGZ","Kyrgyzstan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92666,417,"KGZ","Kyrgyzstan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92667,417,"KGZ","Kyrgyzstan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92668,417,"KGZ","Kyrgyzstan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92669,417,"KGZ","Kyrgyzstan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92670,417,"KGZ","Kyrgyzstan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92671,417,"KGZ","Kyrgyzstan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92672,417,"KGZ","Kyrgyzstan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92673,417,"KGZ","Kyrgyzstan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92674,417,"KGZ","Kyrgyzstan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92675,417,"KGZ","Kyrgyzstan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92676,417,"KGZ","Kyrgyzstan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92677,417,"KGZ","Kyrgyzstan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92678,417,"KGZ","Kyrgyzstan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92679,417,"KGZ","Kyrgyzstan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92680,417,"KGZ","Kyrgyzstan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92681,417,"KGZ","Kyrgyzstan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92682,417,"KGZ","Kyrgyzstan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92683,417,"KGZ","Kyrgyzstan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92684,417,"KGZ","Kyrgyzstan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92685,417,"KGZ","Kyrgyzstan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92686,417,"KGZ","Kyrgyzstan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92687,417,"KGZ","Kyrgyzstan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92688,417,"KGZ","Kyrgyzstan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92689,417,"KGZ","Kyrgyzstan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KGZ/kgz_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92690,418,"LAO","Laos","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92691,418,"LAO","Laos","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92692,418,"LAO","Laos","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92693,418,"LAO","Laos","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92694,418,"LAO","Laos","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92695,418,"LAO","Laos","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92696,418,"LAO","Laos","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92697,418,"LAO","Laos","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92698,418,"LAO","Laos","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92699,418,"LAO","Laos","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92700,418,"LAO","Laos","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92701,418,"LAO","Laos","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92702,418,"LAO","Laos","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92703,418,"LAO","Laos","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92704,418,"LAO","Laos","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92705,418,"LAO","Laos","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92706,418,"LAO","Laos","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92707,418,"LAO","Laos","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92708,418,"LAO","Laos","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92709,418,"LAO","Laos","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92710,418,"LAO","Laos","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92711,418,"LAO","Laos","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92712,418,"LAO","Laos","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92713,418,"LAO","Laos","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92714,418,"LAO","Laos","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92715,418,"LAO","Laos","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92716,418,"LAO","Laos","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92717,418,"LAO","Laos","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92718,418,"LAO","Laos","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92719,418,"LAO","Laos","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92720,418,"LAO","Laos","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92721,418,"LAO","Laos","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92722,418,"LAO","Laos","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92723,418,"LAO","Laos","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92724,418,"LAO","Laos","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92725,418,"LAO","Laos","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LAO/lao_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92726,422,"LBN","Lebanon","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92727,422,"LBN","Lebanon","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92728,422,"LBN","Lebanon","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92729,422,"LBN","Lebanon","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92730,422,"LBN","Lebanon","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92731,422,"LBN","Lebanon","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92732,422,"LBN","Lebanon","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92733,422,"LBN","Lebanon","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92734,422,"LBN","Lebanon","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92735,422,"LBN","Lebanon","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92736,422,"LBN","Lebanon","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92737,422,"LBN","Lebanon","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92738,422,"LBN","Lebanon","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92739,422,"LBN","Lebanon","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92740,422,"LBN","Lebanon","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92741,422,"LBN","Lebanon","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92742,422,"LBN","Lebanon","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92743,422,"LBN","Lebanon","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92744,422,"LBN","Lebanon","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92745,422,"LBN","Lebanon","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92746,422,"LBN","Lebanon","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92747,422,"LBN","Lebanon","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92748,422,"LBN","Lebanon","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92749,422,"LBN","Lebanon","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92750,422,"LBN","Lebanon","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92751,422,"LBN","Lebanon","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92752,422,"LBN","Lebanon","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92753,422,"LBN","Lebanon","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92754,422,"LBN","Lebanon","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92755,422,"LBN","Lebanon","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92756,422,"LBN","Lebanon","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92757,422,"LBN","Lebanon","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92758,422,"LBN","Lebanon","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92759,422,"LBN","Lebanon","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92760,422,"LBN","Lebanon","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92761,422,"LBN","Lebanon","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBN/lbn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92762,426,"LSO","Lesotho","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92763,426,"LSO","Lesotho","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92764,426,"LSO","Lesotho","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92765,426,"LSO","Lesotho","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92766,426,"LSO","Lesotho","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92767,426,"LSO","Lesotho","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92768,426,"LSO","Lesotho","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92769,426,"LSO","Lesotho","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92770,426,"LSO","Lesotho","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92771,426,"LSO","Lesotho","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92772,426,"LSO","Lesotho","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92773,426,"LSO","Lesotho","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92774,426,"LSO","Lesotho","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92775,426,"LSO","Lesotho","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92776,426,"LSO","Lesotho","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92777,426,"LSO","Lesotho","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92778,426,"LSO","Lesotho","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92779,426,"LSO","Lesotho","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92780,426,"LSO","Lesotho","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92781,426,"LSO","Lesotho","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92782,426,"LSO","Lesotho","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92783,426,"LSO","Lesotho","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92784,426,"LSO","Lesotho","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92785,426,"LSO","Lesotho","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92786,426,"LSO","Lesotho","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92787,426,"LSO","Lesotho","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92788,426,"LSO","Lesotho","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92789,426,"LSO","Lesotho","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92790,426,"LSO","Lesotho","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92791,426,"LSO","Lesotho","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92792,426,"LSO","Lesotho","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92793,426,"LSO","Lesotho","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92794,426,"LSO","Lesotho","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92795,426,"LSO","Lesotho","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92796,426,"LSO","Lesotho","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92797,426,"LSO","Lesotho","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LSO/lso_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92798,428,"LVA","Latvia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92799,428,"LVA","Latvia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92800,428,"LVA","Latvia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92801,428,"LVA","Latvia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92802,428,"LVA","Latvia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92803,428,"LVA","Latvia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92804,428,"LVA","Latvia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92805,428,"LVA","Latvia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92806,428,"LVA","Latvia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92807,428,"LVA","Latvia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92808,428,"LVA","Latvia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92809,428,"LVA","Latvia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92810,428,"LVA","Latvia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92811,428,"LVA","Latvia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92812,428,"LVA","Latvia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92813,428,"LVA","Latvia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92814,428,"LVA","Latvia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92815,428,"LVA","Latvia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92816,428,"LVA","Latvia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92817,428,"LVA","Latvia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92818,428,"LVA","Latvia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92819,428,"LVA","Latvia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92820,428,"LVA","Latvia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92821,428,"LVA","Latvia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92822,428,"LVA","Latvia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92823,428,"LVA","Latvia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92824,428,"LVA","Latvia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92825,428,"LVA","Latvia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92826,428,"LVA","Latvia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92827,428,"LVA","Latvia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92828,428,"LVA","Latvia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92829,428,"LVA","Latvia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92830,428,"LVA","Latvia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92831,428,"LVA","Latvia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92832,428,"LVA","Latvia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92833,428,"LVA","Latvia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LVA/lva_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92834,430,"LBR","Liberia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92835,430,"LBR","Liberia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92836,430,"LBR","Liberia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92837,430,"LBR","Liberia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92838,430,"LBR","Liberia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92839,430,"LBR","Liberia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92840,430,"LBR","Liberia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92841,430,"LBR","Liberia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92842,430,"LBR","Liberia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92843,430,"LBR","Liberia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92844,430,"LBR","Liberia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92845,430,"LBR","Liberia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92846,430,"LBR","Liberia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92847,430,"LBR","Liberia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92848,430,"LBR","Liberia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92849,430,"LBR","Liberia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92850,430,"LBR","Liberia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92851,430,"LBR","Liberia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92852,430,"LBR","Liberia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92853,430,"LBR","Liberia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92854,430,"LBR","Liberia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92855,430,"LBR","Liberia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92856,430,"LBR","Liberia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92857,430,"LBR","Liberia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92858,430,"LBR","Liberia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92859,430,"LBR","Liberia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92860,430,"LBR","Liberia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92861,430,"LBR","Liberia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92862,430,"LBR","Liberia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92863,430,"LBR","Liberia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92864,430,"LBR","Liberia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92865,430,"LBR","Liberia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92866,430,"LBR","Liberia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92867,430,"LBR","Liberia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92868,430,"LBR","Liberia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92869,430,"LBR","Liberia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBR/lbr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
92870,434,"LBY","Libya","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92871,434,"LBY","Libya","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92872,434,"LBY","Libya","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92873,434,"LBY","Libya","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92874,434,"LBY","Libya","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92875,434,"LBY","Libya","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92876,434,"LBY","Libya","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92877,434,"LBY","Libya","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92878,434,"LBY","Libya","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92879,434,"LBY","Libya","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92880,434,"LBY","Libya","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92881,434,"LBY","Libya","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92882,434,"LBY","Libya","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92883,434,"LBY","Libya","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92884,434,"LBY","Libya","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92885,434,"LBY","Libya","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92886,434,"LBY","Libya","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92887,434,"LBY","Libya","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92888,434,"LBY","Libya","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92889,434,"LBY","Libya","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92890,434,"LBY","Libya","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92891,434,"LBY","Libya","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92892,434,"LBY","Libya","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92893,434,"LBY","Libya","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92894,434,"LBY","Libya","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92895,434,"LBY","Libya","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92896,434,"LBY","Libya","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92897,434,"LBY","Libya","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92898,434,"LBY","Libya","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92899,434,"LBY","Libya","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92900,434,"LBY","Libya","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92901,434,"LBY","Libya","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92902,434,"LBY","Libya","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92903,434,"LBY","Libya","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92904,434,"LBY","Libya","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92905,434,"LBY","Libya","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LBY/lby_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92906,438,"LIE","Liechtenstein","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92907,438,"LIE","Liechtenstein","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92908,438,"LIE","Liechtenstein","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92909,438,"LIE","Liechtenstein","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92910,438,"LIE","Liechtenstein","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92911,438,"LIE","Liechtenstein","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92912,438,"LIE","Liechtenstein","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92913,438,"LIE","Liechtenstein","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92914,438,"LIE","Liechtenstein","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92915,438,"LIE","Liechtenstein","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92916,438,"LIE","Liechtenstein","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92917,438,"LIE","Liechtenstein","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92918,438,"LIE","Liechtenstein","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92919,438,"LIE","Liechtenstein","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92920,438,"LIE","Liechtenstein","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92921,438,"LIE","Liechtenstein","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92922,438,"LIE","Liechtenstein","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92923,438,"LIE","Liechtenstein","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92924,438,"LIE","Liechtenstein","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92925,438,"LIE","Liechtenstein","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92926,438,"LIE","Liechtenstein","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92927,438,"LIE","Liechtenstein","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92928,438,"LIE","Liechtenstein","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92929,438,"LIE","Liechtenstein","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92930,438,"LIE","Liechtenstein","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92931,438,"LIE","Liechtenstein","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92932,438,"LIE","Liechtenstein","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92933,438,"LIE","Liechtenstein","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92934,438,"LIE","Liechtenstein","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92935,438,"LIE","Liechtenstein","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92936,438,"LIE","Liechtenstein","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92937,438,"LIE","Liechtenstein","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92938,438,"LIE","Liechtenstein","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92939,438,"LIE","Liechtenstein","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92940,438,"LIE","Liechtenstein","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92941,438,"LIE","Liechtenstein","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LIE/lie_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92942,440,"LTU","Lithuania","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92943,440,"LTU","Lithuania","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92944,440,"LTU","Lithuania","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92945,440,"LTU","Lithuania","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92946,440,"LTU","Lithuania","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92947,440,"LTU","Lithuania","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92948,440,"LTU","Lithuania","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92949,440,"LTU","Lithuania","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92950,440,"LTU","Lithuania","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92951,440,"LTU","Lithuania","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92952,440,"LTU","Lithuania","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92953,440,"LTU","Lithuania","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92954,440,"LTU","Lithuania","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92955,440,"LTU","Lithuania","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92956,440,"LTU","Lithuania","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92957,440,"LTU","Lithuania","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92958,440,"LTU","Lithuania","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92959,440,"LTU","Lithuania","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92960,440,"LTU","Lithuania","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92961,440,"LTU","Lithuania","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92962,440,"LTU","Lithuania","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92963,440,"LTU","Lithuania","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92964,440,"LTU","Lithuania","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92965,440,"LTU","Lithuania","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92966,440,"LTU","Lithuania","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92967,440,"LTU","Lithuania","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92968,440,"LTU","Lithuania","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92969,440,"LTU","Lithuania","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92970,440,"LTU","Lithuania","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92971,440,"LTU","Lithuania","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92972,440,"LTU","Lithuania","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92973,440,"LTU","Lithuania","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92974,440,"LTU","Lithuania","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92975,440,"LTU","Lithuania","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92976,440,"LTU","Lithuania","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92977,440,"LTU","Lithuania","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LTU/ltu_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92978,442,"LUX","Luxembourg","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92979,442,"LUX","Luxembourg","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92980,442,"LUX","Luxembourg","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92981,442,"LUX","Luxembourg","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92982,442,"LUX","Luxembourg","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92983,442,"LUX","Luxembourg","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92984,442,"LUX","Luxembourg","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92985,442,"LUX","Luxembourg","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92986,442,"LUX","Luxembourg","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92987,442,"LUX","Luxembourg","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92988,442,"LUX","Luxembourg","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92989,442,"LUX","Luxembourg","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92990,442,"LUX","Luxembourg","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92991,442,"LUX","Luxembourg","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92992,442,"LUX","Luxembourg","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92993,442,"LUX","Luxembourg","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92994,442,"LUX","Luxembourg","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92995,442,"LUX","Luxembourg","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92996,442,"LUX","Luxembourg","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92997,442,"LUX","Luxembourg","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92998,442,"LUX","Luxembourg","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
92999,442,"LUX","Luxembourg","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93000,442,"LUX","Luxembourg","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93001,442,"LUX","Luxembourg","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93002,442,"LUX","Luxembourg","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93003,442,"LUX","Luxembourg","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93004,442,"LUX","Luxembourg","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93005,442,"LUX","Luxembourg","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93006,442,"LUX","Luxembourg","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93007,442,"LUX","Luxembourg","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93008,442,"LUX","Luxembourg","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93009,442,"LUX","Luxembourg","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93010,442,"LUX","Luxembourg","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93011,442,"LUX","Luxembourg","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93012,442,"LUX","Luxembourg","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93013,442,"LUX","Luxembourg","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LUX/lux_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93014,446,"MAC","Macao","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93015,446,"MAC","Macao","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93016,446,"MAC","Macao","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93017,446,"MAC","Macao","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93018,446,"MAC","Macao","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93019,446,"MAC","Macao","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93020,446,"MAC","Macao","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93021,446,"MAC","Macao","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93022,446,"MAC","Macao","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93023,446,"MAC","Macao","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93024,446,"MAC","Macao","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93025,446,"MAC","Macao","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93026,446,"MAC","Macao","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93027,446,"MAC","Macao","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93028,446,"MAC","Macao","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93029,446,"MAC","Macao","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93030,446,"MAC","Macao","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93031,446,"MAC","Macao","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93032,446,"MAC","Macao","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93033,446,"MAC","Macao","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93034,446,"MAC","Macao","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93035,446,"MAC","Macao","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93036,446,"MAC","Macao","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93037,446,"MAC","Macao","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93038,446,"MAC","Macao","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93039,446,"MAC","Macao","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93040,446,"MAC","Macao","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93041,446,"MAC","Macao","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93042,446,"MAC","Macao","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93043,446,"MAC","Macao","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93044,446,"MAC","Macao","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93045,446,"MAC","Macao","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93046,446,"MAC","Macao","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93047,446,"MAC","Macao","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93048,446,"MAC","Macao","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93049,446,"MAC","Macao","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAC/mac_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93050,450,"MDG","Madagascar","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93051,450,"MDG","Madagascar","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93052,450,"MDG","Madagascar","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93053,450,"MDG","Madagascar","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93054,450,"MDG","Madagascar","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93055,450,"MDG","Madagascar","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93056,450,"MDG","Madagascar","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93057,450,"MDG","Madagascar","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93058,450,"MDG","Madagascar","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93059,450,"MDG","Madagascar","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93060,450,"MDG","Madagascar","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93061,450,"MDG","Madagascar","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93062,450,"MDG","Madagascar","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93063,450,"MDG","Madagascar","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93064,450,"MDG","Madagascar","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93065,450,"MDG","Madagascar","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93066,450,"MDG","Madagascar","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93067,450,"MDG","Madagascar","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93068,450,"MDG","Madagascar","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93069,450,"MDG","Madagascar","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93070,450,"MDG","Madagascar","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93071,450,"MDG","Madagascar","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93072,450,"MDG","Madagascar","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93073,450,"MDG","Madagascar","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93074,450,"MDG","Madagascar","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93075,450,"MDG","Madagascar","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93076,450,"MDG","Madagascar","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93077,450,"MDG","Madagascar","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93078,450,"MDG","Madagascar","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93079,450,"MDG","Madagascar","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93080,450,"MDG","Madagascar","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93081,450,"MDG","Madagascar","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93082,450,"MDG","Madagascar","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93083,450,"MDG","Madagascar","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93084,450,"MDG","Madagascar","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93085,450,"MDG","Madagascar","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDG/mdg_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93086,454,"MWI","Malawi","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93087,454,"MWI","Malawi","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93088,454,"MWI","Malawi","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93089,454,"MWI","Malawi","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93090,454,"MWI","Malawi","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93091,454,"MWI","Malawi","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93092,454,"MWI","Malawi","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93093,454,"MWI","Malawi","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93094,454,"MWI","Malawi","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93095,454,"MWI","Malawi","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93096,454,"MWI","Malawi","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93097,454,"MWI","Malawi","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93098,454,"MWI","Malawi","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93099,454,"MWI","Malawi","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93100,454,"MWI","Malawi","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93101,454,"MWI","Malawi","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93102,454,"MWI","Malawi","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93103,454,"MWI","Malawi","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93104,454,"MWI","Malawi","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93105,454,"MWI","Malawi","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93106,454,"MWI","Malawi","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93107,454,"MWI","Malawi","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93108,454,"MWI","Malawi","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93109,454,"MWI","Malawi","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93110,454,"MWI","Malawi","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93111,454,"MWI","Malawi","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93112,454,"MWI","Malawi","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93113,454,"MWI","Malawi","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93114,454,"MWI","Malawi","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93115,454,"MWI","Malawi","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93116,454,"MWI","Malawi","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93117,454,"MWI","Malawi","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93118,454,"MWI","Malawi","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93119,454,"MWI","Malawi","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93120,454,"MWI","Malawi","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93121,454,"MWI","Malawi","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MWI/mwi_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93122,458,"MYS","Malaysia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93123,458,"MYS","Malaysia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93124,458,"MYS","Malaysia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93125,458,"MYS","Malaysia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93126,458,"MYS","Malaysia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93127,458,"MYS","Malaysia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93128,458,"MYS","Malaysia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93129,458,"MYS","Malaysia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93130,458,"MYS","Malaysia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93131,458,"MYS","Malaysia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93132,458,"MYS","Malaysia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93133,458,"MYS","Malaysia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93134,458,"MYS","Malaysia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93135,458,"MYS","Malaysia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93136,458,"MYS","Malaysia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93137,458,"MYS","Malaysia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93138,458,"MYS","Malaysia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93139,458,"MYS","Malaysia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93140,458,"MYS","Malaysia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93141,458,"MYS","Malaysia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93142,458,"MYS","Malaysia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93143,458,"MYS","Malaysia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93144,458,"MYS","Malaysia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93145,458,"MYS","Malaysia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93146,458,"MYS","Malaysia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93147,458,"MYS","Malaysia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93148,458,"MYS","Malaysia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93149,458,"MYS","Malaysia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93150,458,"MYS","Malaysia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93151,458,"MYS","Malaysia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93152,458,"MYS","Malaysia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93153,458,"MYS","Malaysia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93154,458,"MYS","Malaysia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93155,458,"MYS","Malaysia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93156,458,"MYS","Malaysia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93157,458,"MYS","Malaysia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MYS/mys_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93158,462,"MDV","Maldives","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93159,462,"MDV","Maldives","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93160,462,"MDV","Maldives","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93161,462,"MDV","Maldives","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93162,462,"MDV","Maldives","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93163,462,"MDV","Maldives","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93164,462,"MDV","Maldives","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93165,462,"MDV","Maldives","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93166,462,"MDV","Maldives","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93167,462,"MDV","Maldives","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93168,462,"MDV","Maldives","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93169,462,"MDV","Maldives","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93170,462,"MDV","Maldives","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93171,462,"MDV","Maldives","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93172,462,"MDV","Maldives","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93173,462,"MDV","Maldives","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93174,462,"MDV","Maldives","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93175,462,"MDV","Maldives","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93176,462,"MDV","Maldives","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93177,462,"MDV","Maldives","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93178,462,"MDV","Maldives","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93179,462,"MDV","Maldives","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93180,462,"MDV","Maldives","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93181,462,"MDV","Maldives","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93182,462,"MDV","Maldives","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93183,462,"MDV","Maldives","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93184,462,"MDV","Maldives","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93185,462,"MDV","Maldives","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93186,462,"MDV","Maldives","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93187,462,"MDV","Maldives","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93188,462,"MDV","Maldives","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93189,462,"MDV","Maldives","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93190,462,"MDV","Maldives","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93191,462,"MDV","Maldives","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93192,462,"MDV","Maldives","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93193,462,"MDV","Maldives","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDV/mdv_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93194,466,"MLI","Mali","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93195,466,"MLI","Mali","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93196,466,"MLI","Mali","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93197,466,"MLI","Mali","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93198,466,"MLI","Mali","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93199,466,"MLI","Mali","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93200,466,"MLI","Mali","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93201,466,"MLI","Mali","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93202,466,"MLI","Mali","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93203,466,"MLI","Mali","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93204,466,"MLI","Mali","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93205,466,"MLI","Mali","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93206,466,"MLI","Mali","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93207,466,"MLI","Mali","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93208,466,"MLI","Mali","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93209,466,"MLI","Mali","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93210,466,"MLI","Mali","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93211,466,"MLI","Mali","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93212,466,"MLI","Mali","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93213,466,"MLI","Mali","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93214,466,"MLI","Mali","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93215,466,"MLI","Mali","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93216,466,"MLI","Mali","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93217,466,"MLI","Mali","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93218,466,"MLI","Mali","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93219,466,"MLI","Mali","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93220,466,"MLI","Mali","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93221,466,"MLI","Mali","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93222,466,"MLI","Mali","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93223,466,"MLI","Mali","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93224,466,"MLI","Mali","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93225,466,"MLI","Mali","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93226,466,"MLI","Mali","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93227,466,"MLI","Mali","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93228,466,"MLI","Mali","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93229,466,"MLI","Mali","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLI/mli_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93230,470,"MLT","Malta","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93231,470,"MLT","Malta","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93232,470,"MLT","Malta","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93233,470,"MLT","Malta","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93234,470,"MLT","Malta","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93235,470,"MLT","Malta","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93236,470,"MLT","Malta","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93237,470,"MLT","Malta","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93238,470,"MLT","Malta","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93239,470,"MLT","Malta","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93240,470,"MLT","Malta","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93241,470,"MLT","Malta","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93242,470,"MLT","Malta","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93243,470,"MLT","Malta","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93244,470,"MLT","Malta","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93245,470,"MLT","Malta","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93246,470,"MLT","Malta","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93247,470,"MLT","Malta","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93248,470,"MLT","Malta","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93249,470,"MLT","Malta","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93250,470,"MLT","Malta","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93251,470,"MLT","Malta","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93252,470,"MLT","Malta","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93253,470,"MLT","Malta","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93254,470,"MLT","Malta","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93255,470,"MLT","Malta","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93256,470,"MLT","Malta","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93257,470,"MLT","Malta","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93258,470,"MLT","Malta","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93259,470,"MLT","Malta","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93260,470,"MLT","Malta","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93261,470,"MLT","Malta","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93262,470,"MLT","Malta","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93263,470,"MLT","Malta","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93264,470,"MLT","Malta","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93265,470,"MLT","Malta","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MLT/mlt_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93266,474,"MTQ","Martinique","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93267,474,"MTQ","Martinique","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93268,474,"MTQ","Martinique","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93269,474,"MTQ","Martinique","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93270,474,"MTQ","Martinique","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93271,474,"MTQ","Martinique","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93272,474,"MTQ","Martinique","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93273,474,"MTQ","Martinique","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93274,474,"MTQ","Martinique","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93275,474,"MTQ","Martinique","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93276,474,"MTQ","Martinique","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93277,474,"MTQ","Martinique","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93278,474,"MTQ","Martinique","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93279,474,"MTQ","Martinique","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93280,474,"MTQ","Martinique","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93281,474,"MTQ","Martinique","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93282,474,"MTQ","Martinique","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93283,474,"MTQ","Martinique","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93284,474,"MTQ","Martinique","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93285,474,"MTQ","Martinique","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93286,474,"MTQ","Martinique","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93287,474,"MTQ","Martinique","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93288,474,"MTQ","Martinique","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93289,474,"MTQ","Martinique","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93290,474,"MTQ","Martinique","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93291,474,"MTQ","Martinique","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93292,474,"MTQ","Martinique","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93293,474,"MTQ","Martinique","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93294,474,"MTQ","Martinique","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93295,474,"MTQ","Martinique","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93296,474,"MTQ","Martinique","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93297,474,"MTQ","Martinique","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93298,474,"MTQ","Martinique","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93299,474,"MTQ","Martinique","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93300,474,"MTQ","Martinique","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93301,474,"MTQ","Martinique","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MTQ/mtq_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93302,478,"MRT","Mauritania","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93303,478,"MRT","Mauritania","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93304,478,"MRT","Mauritania","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93305,478,"MRT","Mauritania","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93306,478,"MRT","Mauritania","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93307,478,"MRT","Mauritania","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93308,478,"MRT","Mauritania","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93309,478,"MRT","Mauritania","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93310,478,"MRT","Mauritania","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93311,478,"MRT","Mauritania","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93312,478,"MRT","Mauritania","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93313,478,"MRT","Mauritania","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93314,478,"MRT","Mauritania","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93315,478,"MRT","Mauritania","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93316,478,"MRT","Mauritania","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93317,478,"MRT","Mauritania","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93318,478,"MRT","Mauritania","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93319,478,"MRT","Mauritania","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93320,478,"MRT","Mauritania","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93321,478,"MRT","Mauritania","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93322,478,"MRT","Mauritania","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93323,478,"MRT","Mauritania","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93324,478,"MRT","Mauritania","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93325,478,"MRT","Mauritania","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93326,478,"MRT","Mauritania","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93327,478,"MRT","Mauritania","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93328,478,"MRT","Mauritania","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93329,478,"MRT","Mauritania","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93330,478,"MRT","Mauritania","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93331,478,"MRT","Mauritania","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93332,478,"MRT","Mauritania","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93333,478,"MRT","Mauritania","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93334,478,"MRT","Mauritania","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93335,478,"MRT","Mauritania","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93336,478,"MRT","Mauritania","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93337,478,"MRT","Mauritania","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MRT/mrt_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93338,480,"MUS","Mauritius","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93339,480,"MUS","Mauritius","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93340,480,"MUS","Mauritius","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93341,480,"MUS","Mauritius","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93342,480,"MUS","Mauritius","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93343,480,"MUS","Mauritius","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93344,480,"MUS","Mauritius","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93345,480,"MUS","Mauritius","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93346,480,"MUS","Mauritius","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93347,480,"MUS","Mauritius","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93348,480,"MUS","Mauritius","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93349,480,"MUS","Mauritius","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93350,480,"MUS","Mauritius","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93351,480,"MUS","Mauritius","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93352,480,"MUS","Mauritius","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93353,480,"MUS","Mauritius","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93354,480,"MUS","Mauritius","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93355,480,"MUS","Mauritius","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93356,480,"MUS","Mauritius","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93357,480,"MUS","Mauritius","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93358,480,"MUS","Mauritius","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93359,480,"MUS","Mauritius","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93360,480,"MUS","Mauritius","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93361,480,"MUS","Mauritius","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93362,480,"MUS","Mauritius","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93363,480,"MUS","Mauritius","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93364,480,"MUS","Mauritius","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93365,480,"MUS","Mauritius","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93366,480,"MUS","Mauritius","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93367,480,"MUS","Mauritius","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93368,480,"MUS","Mauritius","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93369,480,"MUS","Mauritius","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93370,480,"MUS","Mauritius","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93371,480,"MUS","Mauritius","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93372,480,"MUS","Mauritius","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93373,480,"MUS","Mauritius","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MUS/mus_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93374,484,"MEX","Mexico","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93375,484,"MEX","Mexico","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93376,484,"MEX","Mexico","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93377,484,"MEX","Mexico","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93378,484,"MEX","Mexico","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93379,484,"MEX","Mexico","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93380,484,"MEX","Mexico","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93381,484,"MEX","Mexico","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93382,484,"MEX","Mexico","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93383,484,"MEX","Mexico","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93384,484,"MEX","Mexico","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93385,484,"MEX","Mexico","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93386,484,"MEX","Mexico","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93387,484,"MEX","Mexico","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93388,484,"MEX","Mexico","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93389,484,"MEX","Mexico","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93390,484,"MEX","Mexico","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93391,484,"MEX","Mexico","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93392,484,"MEX","Mexico","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93393,484,"MEX","Mexico","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93394,484,"MEX","Mexico","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93395,484,"MEX","Mexico","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93396,484,"MEX","Mexico","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93397,484,"MEX","Mexico","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93398,484,"MEX","Mexico","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93399,484,"MEX","Mexico","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93400,484,"MEX","Mexico","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93401,484,"MEX","Mexico","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93402,484,"MEX","Mexico","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93403,484,"MEX","Mexico","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93404,484,"MEX","Mexico","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93405,484,"MEX","Mexico","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93406,484,"MEX","Mexico","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93407,484,"MEX","Mexico","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93408,484,"MEX","Mexico","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93409,484,"MEX","Mexico","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MEX/mex_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93410,492,"MCO","Monaco","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93411,492,"MCO","Monaco","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93412,492,"MCO","Monaco","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93413,492,"MCO","Monaco","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93414,492,"MCO","Monaco","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93415,492,"MCO","Monaco","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93416,492,"MCO","Monaco","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93417,492,"MCO","Monaco","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93418,492,"MCO","Monaco","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93419,492,"MCO","Monaco","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93420,492,"MCO","Monaco","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93421,492,"MCO","Monaco","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93422,492,"MCO","Monaco","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93423,492,"MCO","Monaco","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93424,492,"MCO","Monaco","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93425,492,"MCO","Monaco","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93426,492,"MCO","Monaco","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93427,492,"MCO","Monaco","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93428,492,"MCO","Monaco","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93429,492,"MCO","Monaco","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93430,492,"MCO","Monaco","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93431,492,"MCO","Monaco","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93432,492,"MCO","Monaco","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93433,492,"MCO","Monaco","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93434,492,"MCO","Monaco","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93435,492,"MCO","Monaco","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93436,492,"MCO","Monaco","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93437,492,"MCO","Monaco","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93438,492,"MCO","Monaco","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93439,492,"MCO","Monaco","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93440,492,"MCO","Monaco","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93441,492,"MCO","Monaco","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93442,492,"MCO","Monaco","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93443,492,"MCO","Monaco","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93444,492,"MCO","Monaco","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93445,492,"MCO","Monaco","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MCO/mco_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93446,496,"MNG","Mongolia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93447,496,"MNG","Mongolia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93448,496,"MNG","Mongolia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93449,496,"MNG","Mongolia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93450,496,"MNG","Mongolia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93451,496,"MNG","Mongolia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93452,496,"MNG","Mongolia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93453,496,"MNG","Mongolia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93454,496,"MNG","Mongolia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93455,496,"MNG","Mongolia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93456,496,"MNG","Mongolia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93457,496,"MNG","Mongolia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93458,496,"MNG","Mongolia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93459,496,"MNG","Mongolia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93460,496,"MNG","Mongolia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93461,496,"MNG","Mongolia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93462,496,"MNG","Mongolia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93463,496,"MNG","Mongolia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93464,496,"MNG","Mongolia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93465,496,"MNG","Mongolia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93466,496,"MNG","Mongolia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93467,496,"MNG","Mongolia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93468,496,"MNG","Mongolia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93469,496,"MNG","Mongolia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93470,496,"MNG","Mongolia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93471,496,"MNG","Mongolia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93472,496,"MNG","Mongolia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93473,496,"MNG","Mongolia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93474,496,"MNG","Mongolia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93475,496,"MNG","Mongolia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93476,496,"MNG","Mongolia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93477,496,"MNG","Mongolia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93478,496,"MNG","Mongolia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93479,496,"MNG","Mongolia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93480,496,"MNG","Mongolia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93481,496,"MNG","Mongolia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNG/mng_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93482,498,"MDA","Moldova","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93483,498,"MDA","Moldova","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93484,498,"MDA","Moldova","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93485,498,"MDA","Moldova","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93486,498,"MDA","Moldova","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93487,498,"MDA","Moldova","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93488,498,"MDA","Moldova","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93489,498,"MDA","Moldova","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93490,498,"MDA","Moldova","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93491,498,"MDA","Moldova","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93492,498,"MDA","Moldova","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93493,498,"MDA","Moldova","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93494,498,"MDA","Moldova","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93495,498,"MDA","Moldova","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93496,498,"MDA","Moldova","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93497,498,"MDA","Moldova","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93498,498,"MDA","Moldova","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93499,498,"MDA","Moldova","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93500,498,"MDA","Moldova","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93501,498,"MDA","Moldova","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93502,498,"MDA","Moldova","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93503,498,"MDA","Moldova","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93504,498,"MDA","Moldova","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93505,498,"MDA","Moldova","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93506,498,"MDA","Moldova","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93507,498,"MDA","Moldova","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93508,498,"MDA","Moldova","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93509,498,"MDA","Moldova","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93510,498,"MDA","Moldova","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93511,498,"MDA","Moldova","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93512,498,"MDA","Moldova","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93513,498,"MDA","Moldova","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93514,498,"MDA","Moldova","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93515,498,"MDA","Moldova","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93516,498,"MDA","Moldova","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93517,498,"MDA","Moldova","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MDA/mda_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93518,499,"MNE","Montenegro","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93519,499,"MNE","Montenegro","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93520,499,"MNE","Montenegro","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93521,499,"MNE","Montenegro","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93522,499,"MNE","Montenegro","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93523,499,"MNE","Montenegro","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93524,499,"MNE","Montenegro","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93525,499,"MNE","Montenegro","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93526,499,"MNE","Montenegro","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93527,499,"MNE","Montenegro","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93528,499,"MNE","Montenegro","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93529,499,"MNE","Montenegro","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93530,499,"MNE","Montenegro","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93531,499,"MNE","Montenegro","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93532,499,"MNE","Montenegro","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93533,499,"MNE","Montenegro","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93534,499,"MNE","Montenegro","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93535,499,"MNE","Montenegro","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93536,499,"MNE","Montenegro","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93537,499,"MNE","Montenegro","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93538,499,"MNE","Montenegro","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93539,499,"MNE","Montenegro","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93540,499,"MNE","Montenegro","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93541,499,"MNE","Montenegro","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93542,499,"MNE","Montenegro","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93543,499,"MNE","Montenegro","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93544,499,"MNE","Montenegro","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93545,499,"MNE","Montenegro","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93546,499,"MNE","Montenegro","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93547,499,"MNE","Montenegro","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93548,499,"MNE","Montenegro","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93549,499,"MNE","Montenegro","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93550,499,"MNE","Montenegro","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93551,499,"MNE","Montenegro","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93552,499,"MNE","Montenegro","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93553,499,"MNE","Montenegro","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNE/mne_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93554,500,"MSR","Montserrat","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93555,500,"MSR","Montserrat","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93556,500,"MSR","Montserrat","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93557,500,"MSR","Montserrat","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93558,500,"MSR","Montserrat","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93559,500,"MSR","Montserrat","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93560,500,"MSR","Montserrat","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93561,500,"MSR","Montserrat","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93562,500,"MSR","Montserrat","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93563,500,"MSR","Montserrat","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93564,500,"MSR","Montserrat","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93565,500,"MSR","Montserrat","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93566,500,"MSR","Montserrat","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93567,500,"MSR","Montserrat","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93568,500,"MSR","Montserrat","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93569,500,"MSR","Montserrat","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93570,500,"MSR","Montserrat","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93571,500,"MSR","Montserrat","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93572,500,"MSR","Montserrat","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93573,500,"MSR","Montserrat","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93574,500,"MSR","Montserrat","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93575,500,"MSR","Montserrat","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93576,500,"MSR","Montserrat","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93577,500,"MSR","Montserrat","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93578,500,"MSR","Montserrat","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93579,500,"MSR","Montserrat","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93580,500,"MSR","Montserrat","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93581,500,"MSR","Montserrat","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93582,500,"MSR","Montserrat","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93583,500,"MSR","Montserrat","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93584,500,"MSR","Montserrat","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93585,500,"MSR","Montserrat","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93586,500,"MSR","Montserrat","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93587,500,"MSR","Montserrat","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93588,500,"MSR","Montserrat","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93589,500,"MSR","Montserrat","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MSR/msr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93590,504,"MAR","Morocco","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93591,504,"MAR","Morocco","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93592,504,"MAR","Morocco","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93593,504,"MAR","Morocco","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93594,504,"MAR","Morocco","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93595,504,"MAR","Morocco","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93596,504,"MAR","Morocco","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93597,504,"MAR","Morocco","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93598,504,"MAR","Morocco","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93599,504,"MAR","Morocco","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93600,504,"MAR","Morocco","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93601,504,"MAR","Morocco","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93602,504,"MAR","Morocco","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93603,504,"MAR","Morocco","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93604,504,"MAR","Morocco","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93605,504,"MAR","Morocco","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93606,504,"MAR","Morocco","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93607,504,"MAR","Morocco","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93608,504,"MAR","Morocco","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93609,504,"MAR","Morocco","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93610,504,"MAR","Morocco","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93611,504,"MAR","Morocco","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93612,504,"MAR","Morocco","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93613,504,"MAR","Morocco","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93614,504,"MAR","Morocco","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93615,504,"MAR","Morocco","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93616,504,"MAR","Morocco","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93617,504,"MAR","Morocco","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93618,504,"MAR","Morocco","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93619,504,"MAR","Morocco","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93620,504,"MAR","Morocco","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93621,504,"MAR","Morocco","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93622,504,"MAR","Morocco","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93623,504,"MAR","Morocco","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93624,504,"MAR","Morocco","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93625,504,"MAR","Morocco","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAR/mar_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93626,508,"MOZ","Mozambique","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93627,508,"MOZ","Mozambique","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93628,508,"MOZ","Mozambique","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93629,508,"MOZ","Mozambique","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93630,508,"MOZ","Mozambique","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93631,508,"MOZ","Mozambique","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93632,508,"MOZ","Mozambique","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93633,508,"MOZ","Mozambique","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93634,508,"MOZ","Mozambique","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93635,508,"MOZ","Mozambique","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93636,508,"MOZ","Mozambique","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93637,508,"MOZ","Mozambique","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93638,508,"MOZ","Mozambique","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93639,508,"MOZ","Mozambique","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93640,508,"MOZ","Mozambique","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93641,508,"MOZ","Mozambique","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93642,508,"MOZ","Mozambique","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93643,508,"MOZ","Mozambique","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93644,508,"MOZ","Mozambique","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93645,508,"MOZ","Mozambique","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93646,508,"MOZ","Mozambique","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93647,508,"MOZ","Mozambique","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93648,508,"MOZ","Mozambique","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93649,508,"MOZ","Mozambique","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93650,508,"MOZ","Mozambique","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93651,508,"MOZ","Mozambique","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93652,508,"MOZ","Mozambique","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93653,508,"MOZ","Mozambique","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93654,508,"MOZ","Mozambique","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93655,508,"MOZ","Mozambique","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93656,508,"MOZ","Mozambique","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93657,508,"MOZ","Mozambique","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93658,508,"MOZ","Mozambique","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93659,508,"MOZ","Mozambique","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93660,508,"MOZ","Mozambique","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93661,508,"MOZ","Mozambique","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MOZ/moz_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93662,512,"OMN","Oman","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93663,512,"OMN","Oman","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93664,512,"OMN","Oman","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93665,512,"OMN","Oman","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93666,512,"OMN","Oman","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93667,512,"OMN","Oman","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93668,512,"OMN","Oman","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93669,512,"OMN","Oman","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93670,512,"OMN","Oman","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93671,512,"OMN","Oman","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93672,512,"OMN","Oman","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93673,512,"OMN","Oman","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93674,512,"OMN","Oman","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93675,512,"OMN","Oman","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93676,512,"OMN","Oman","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93677,512,"OMN","Oman","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93678,512,"OMN","Oman","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93679,512,"OMN","Oman","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93680,512,"OMN","Oman","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93681,512,"OMN","Oman","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93682,512,"OMN","Oman","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93683,512,"OMN","Oman","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93684,512,"OMN","Oman","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93685,512,"OMN","Oman","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93686,512,"OMN","Oman","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93687,512,"OMN","Oman","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93688,512,"OMN","Oman","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93689,512,"OMN","Oman","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93690,512,"OMN","Oman","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93691,512,"OMN","Oman","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93692,512,"OMN","Oman","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93693,512,"OMN","Oman","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93694,512,"OMN","Oman","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93695,512,"OMN","Oman","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93696,512,"OMN","Oman","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93697,512,"OMN","Oman","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/OMN/omn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93698,516,"NAM","Namibia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93699,516,"NAM","Namibia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93700,516,"NAM","Namibia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93701,516,"NAM","Namibia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93702,516,"NAM","Namibia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93703,516,"NAM","Namibia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93704,516,"NAM","Namibia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93705,516,"NAM","Namibia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93706,516,"NAM","Namibia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93707,516,"NAM","Namibia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93708,516,"NAM","Namibia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93709,516,"NAM","Namibia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93710,516,"NAM","Namibia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93711,516,"NAM","Namibia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93712,516,"NAM","Namibia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93713,516,"NAM","Namibia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93714,516,"NAM","Namibia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93715,516,"NAM","Namibia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93716,516,"NAM","Namibia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93717,516,"NAM","Namibia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93718,516,"NAM","Namibia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93719,516,"NAM","Namibia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93720,516,"NAM","Namibia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93721,516,"NAM","Namibia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93722,516,"NAM","Namibia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93723,516,"NAM","Namibia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93724,516,"NAM","Namibia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93725,516,"NAM","Namibia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93726,516,"NAM","Namibia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93727,516,"NAM","Namibia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93728,516,"NAM","Namibia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93729,516,"NAM","Namibia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93730,516,"NAM","Namibia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93731,516,"NAM","Namibia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93732,516,"NAM","Namibia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93733,516,"NAM","Namibia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NAM/nam_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
93734,520,"NRU","Nauru","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93735,520,"NRU","Nauru","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93736,520,"NRU","Nauru","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93737,520,"NRU","Nauru","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93738,520,"NRU","Nauru","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93739,520,"NRU","Nauru","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93740,520,"NRU","Nauru","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93741,520,"NRU","Nauru","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93742,520,"NRU","Nauru","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93743,520,"NRU","Nauru","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93744,520,"NRU","Nauru","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93745,520,"NRU","Nauru","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93746,520,"NRU","Nauru","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93747,520,"NRU","Nauru","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93748,520,"NRU","Nauru","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93749,520,"NRU","Nauru","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93750,520,"NRU","Nauru","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93751,520,"NRU","Nauru","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93752,520,"NRU","Nauru","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93753,520,"NRU","Nauru","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93754,520,"NRU","Nauru","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93755,520,"NRU","Nauru","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93756,520,"NRU","Nauru","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93757,520,"NRU","Nauru","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93758,520,"NRU","Nauru","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93759,520,"NRU","Nauru","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93760,520,"NRU","Nauru","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93761,520,"NRU","Nauru","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93762,520,"NRU","Nauru","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93763,520,"NRU","Nauru","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93764,520,"NRU","Nauru","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93765,520,"NRU","Nauru","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93766,520,"NRU","Nauru","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93767,520,"NRU","Nauru","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93768,520,"NRU","Nauru","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93769,520,"NRU","Nauru","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NRU/nru_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93770,524,"NPL","Nepal","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93771,524,"NPL","Nepal","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93772,524,"NPL","Nepal","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93773,524,"NPL","Nepal","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93774,524,"NPL","Nepal","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93775,524,"NPL","Nepal","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93776,524,"NPL","Nepal","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93777,524,"NPL","Nepal","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93778,524,"NPL","Nepal","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93779,524,"NPL","Nepal","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93780,524,"NPL","Nepal","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93781,524,"NPL","Nepal","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93782,524,"NPL","Nepal","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93783,524,"NPL","Nepal","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93784,524,"NPL","Nepal","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93785,524,"NPL","Nepal","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93786,524,"NPL","Nepal","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93787,524,"NPL","Nepal","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93788,524,"NPL","Nepal","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93789,524,"NPL","Nepal","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93790,524,"NPL","Nepal","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93791,524,"NPL","Nepal","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93792,524,"NPL","Nepal","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93793,524,"NPL","Nepal","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93794,524,"NPL","Nepal","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93795,524,"NPL","Nepal","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93796,524,"NPL","Nepal","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93797,524,"NPL","Nepal","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93798,524,"NPL","Nepal","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93799,524,"NPL","Nepal","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93800,524,"NPL","Nepal","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93801,524,"NPL","Nepal","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93802,524,"NPL","Nepal","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93803,524,"NPL","Nepal","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93804,524,"NPL","Nepal","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93805,524,"NPL","Nepal","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NPL/npl_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93806,528,"NLD","Netherlands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93807,528,"NLD","Netherlands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93808,528,"NLD","Netherlands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93809,528,"NLD","Netherlands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93810,528,"NLD","Netherlands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93811,528,"NLD","Netherlands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93812,528,"NLD","Netherlands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93813,528,"NLD","Netherlands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93814,528,"NLD","Netherlands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93815,528,"NLD","Netherlands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93816,528,"NLD","Netherlands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93817,528,"NLD","Netherlands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93818,528,"NLD","Netherlands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93819,528,"NLD","Netherlands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93820,528,"NLD","Netherlands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93821,528,"NLD","Netherlands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93822,528,"NLD","Netherlands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93823,528,"NLD","Netherlands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93824,528,"NLD","Netherlands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93825,528,"NLD","Netherlands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93826,528,"NLD","Netherlands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93827,528,"NLD","Netherlands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93828,528,"NLD","Netherlands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93829,528,"NLD","Netherlands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93830,528,"NLD","Netherlands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93831,528,"NLD","Netherlands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93832,528,"NLD","Netherlands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93833,528,"NLD","Netherlands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93834,528,"NLD","Netherlands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93835,528,"NLD","Netherlands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93836,528,"NLD","Netherlands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93837,528,"NLD","Netherlands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93838,528,"NLD","Netherlands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93839,528,"NLD","Netherlands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93840,528,"NLD","Netherlands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93841,528,"NLD","Netherlands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NLD/nld_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93842,531,"CUW","Curacao","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93843,531,"CUW","Curacao","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93844,531,"CUW","Curacao","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93845,531,"CUW","Curacao","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93846,531,"CUW","Curacao","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93847,531,"CUW","Curacao","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93848,531,"CUW","Curacao","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93849,531,"CUW","Curacao","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93850,531,"CUW","Curacao","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93851,531,"CUW","Curacao","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93852,531,"CUW","Curacao","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93853,531,"CUW","Curacao","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93854,531,"CUW","Curacao","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93855,531,"CUW","Curacao","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93856,531,"CUW","Curacao","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93857,531,"CUW","Curacao","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93858,531,"CUW","Curacao","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93859,531,"CUW","Curacao","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93860,531,"CUW","Curacao","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93861,531,"CUW","Curacao","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93862,531,"CUW","Curacao","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93863,531,"CUW","Curacao","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93864,531,"CUW","Curacao","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93865,531,"CUW","Curacao","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93866,531,"CUW","Curacao","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93867,531,"CUW","Curacao","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93868,531,"CUW","Curacao","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93869,531,"CUW","Curacao","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93870,531,"CUW","Curacao","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93871,531,"CUW","Curacao","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93872,531,"CUW","Curacao","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93873,531,"CUW","Curacao","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93874,531,"CUW","Curacao","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93875,531,"CUW","Curacao","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93876,531,"CUW","Curacao","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93877,531,"CUW","Curacao","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CUW/cuw_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93878,533,"ABW","Aruba","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93879,533,"ABW","Aruba","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93880,533,"ABW","Aruba","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93881,533,"ABW","Aruba","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93882,533,"ABW","Aruba","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93883,533,"ABW","Aruba","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93884,533,"ABW","Aruba","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93885,533,"ABW","Aruba","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93886,533,"ABW","Aruba","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93887,533,"ABW","Aruba","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93888,533,"ABW","Aruba","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93889,533,"ABW","Aruba","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93890,533,"ABW","Aruba","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93891,533,"ABW","Aruba","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93892,533,"ABW","Aruba","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93893,533,"ABW","Aruba","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93894,533,"ABW","Aruba","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93895,533,"ABW","Aruba","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93896,533,"ABW","Aruba","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93897,533,"ABW","Aruba","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93898,533,"ABW","Aruba","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93899,533,"ABW","Aruba","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93900,533,"ABW","Aruba","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93901,533,"ABW","Aruba","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93902,533,"ABW","Aruba","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93903,533,"ABW","Aruba","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93904,533,"ABW","Aruba","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93905,533,"ABW","Aruba","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93906,533,"ABW","Aruba","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93907,533,"ABW","Aruba","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93908,533,"ABW","Aruba","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93909,533,"ABW","Aruba","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93910,533,"ABW","Aruba","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93911,533,"ABW","Aruba","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93912,533,"ABW","Aruba","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93913,533,"ABW","Aruba","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ABW/abw_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93914,534,"SXM","Sint Maarten (Dutch part)","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93915,534,"SXM","Sint Maarten (Dutch part)","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93916,534,"SXM","Sint Maarten (Dutch part)","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93917,534,"SXM","Sint Maarten (Dutch part)","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93918,534,"SXM","Sint Maarten (Dutch part)","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93919,534,"SXM","Sint Maarten (Dutch part)","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93920,534,"SXM","Sint Maarten (Dutch part)","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93921,534,"SXM","Sint Maarten (Dutch part)","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93922,534,"SXM","Sint Maarten (Dutch part)","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93923,534,"SXM","Sint Maarten (Dutch part)","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93924,534,"SXM","Sint Maarten (Dutch part)","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93925,534,"SXM","Sint Maarten (Dutch part)","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93926,534,"SXM","Sint Maarten (Dutch part)","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93927,534,"SXM","Sint Maarten (Dutch part)","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93928,534,"SXM","Sint Maarten (Dutch part)","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93929,534,"SXM","Sint Maarten (Dutch part)","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93930,534,"SXM","Sint Maarten (Dutch part)","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93931,534,"SXM","Sint Maarten (Dutch part)","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93932,534,"SXM","Sint Maarten (Dutch part)","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93933,534,"SXM","Sint Maarten (Dutch part)","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93934,534,"SXM","Sint Maarten (Dutch part)","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93935,534,"SXM","Sint Maarten (Dutch part)","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93936,534,"SXM","Sint Maarten (Dutch part)","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93937,534,"SXM","Sint Maarten (Dutch part)","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93938,534,"SXM","Sint Maarten (Dutch part)","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93939,534,"SXM","Sint Maarten (Dutch part)","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93940,534,"SXM","Sint Maarten (Dutch part)","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93941,534,"SXM","Sint Maarten (Dutch part)","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93942,534,"SXM","Sint Maarten (Dutch part)","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93943,534,"SXM","Sint Maarten (Dutch part)","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93944,534,"SXM","Sint Maarten (Dutch part)","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93945,534,"SXM","Sint Maarten (Dutch part)","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93946,534,"SXM","Sint Maarten (Dutch part)","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93947,534,"SXM","Sint Maarten (Dutch part)","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93948,534,"SXM","Sint Maarten (Dutch part)","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93949,534,"SXM","Sint Maarten (Dutch part)","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SXM/sxm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93950,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93951,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93952,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93953,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93954,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93955,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93956,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93957,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93958,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93959,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93960,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93961,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93962,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93963,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93964,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93965,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93966,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93967,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93968,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93969,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93970,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93971,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93972,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93973,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93974,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93975,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93976,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93977,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93978,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93979,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93980,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93981,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93982,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93983,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93984,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93985,535,"BES","Bonaire, Sint Eustatius and Saba","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BES/bes_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93986,540,"NCL","New Caledonia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93987,540,"NCL","New Caledonia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93988,540,"NCL","New Caledonia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93989,540,"NCL","New Caledonia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93990,540,"NCL","New Caledonia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93991,540,"NCL","New Caledonia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93992,540,"NCL","New Caledonia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93993,540,"NCL","New Caledonia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93994,540,"NCL","New Caledonia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93995,540,"NCL","New Caledonia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93996,540,"NCL","New Caledonia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93997,540,"NCL","New Caledonia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93998,540,"NCL","New Caledonia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
93999,540,"NCL","New Caledonia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94000,540,"NCL","New Caledonia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94001,540,"NCL","New Caledonia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94002,540,"NCL","New Caledonia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94003,540,"NCL","New Caledonia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94004,540,"NCL","New Caledonia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94005,540,"NCL","New Caledonia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94006,540,"NCL","New Caledonia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94007,540,"NCL","New Caledonia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94008,540,"NCL","New Caledonia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94009,540,"NCL","New Caledonia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94010,540,"NCL","New Caledonia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94011,540,"NCL","New Caledonia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94012,540,"NCL","New Caledonia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94013,540,"NCL","New Caledonia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94014,540,"NCL","New Caledonia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94015,540,"NCL","New Caledonia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94016,540,"NCL","New Caledonia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94017,540,"NCL","New Caledonia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94018,540,"NCL","New Caledonia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94019,540,"NCL","New Caledonia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94020,540,"NCL","New Caledonia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94021,540,"NCL","New Caledonia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NCL/ncl_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94022,548,"VUT","Vanuatu","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94023,548,"VUT","Vanuatu","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94024,548,"VUT","Vanuatu","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94025,548,"VUT","Vanuatu","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94026,548,"VUT","Vanuatu","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94027,548,"VUT","Vanuatu","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94028,548,"VUT","Vanuatu","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94029,548,"VUT","Vanuatu","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94030,548,"VUT","Vanuatu","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94031,548,"VUT","Vanuatu","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94032,548,"VUT","Vanuatu","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94033,548,"VUT","Vanuatu","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94034,548,"VUT","Vanuatu","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94035,548,"VUT","Vanuatu","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94036,548,"VUT","Vanuatu","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94037,548,"VUT","Vanuatu","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94038,548,"VUT","Vanuatu","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94039,548,"VUT","Vanuatu","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94040,548,"VUT","Vanuatu","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94041,548,"VUT","Vanuatu","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94042,548,"VUT","Vanuatu","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94043,548,"VUT","Vanuatu","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94044,548,"VUT","Vanuatu","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94045,548,"VUT","Vanuatu","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94046,548,"VUT","Vanuatu","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94047,548,"VUT","Vanuatu","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94048,548,"VUT","Vanuatu","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94049,548,"VUT","Vanuatu","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94050,548,"VUT","Vanuatu","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94051,548,"VUT","Vanuatu","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94052,548,"VUT","Vanuatu","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94053,548,"VUT","Vanuatu","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94054,548,"VUT","Vanuatu","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94055,548,"VUT","Vanuatu","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94056,548,"VUT","Vanuatu","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94057,548,"VUT","Vanuatu","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VUT/vut_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94058,554,"NZL","New Zealand","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94059,554,"NZL","New Zealand","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94060,554,"NZL","New Zealand","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94061,554,"NZL","New Zealand","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94062,554,"NZL","New Zealand","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94063,554,"NZL","New Zealand","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94064,554,"NZL","New Zealand","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94065,554,"NZL","New Zealand","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94066,554,"NZL","New Zealand","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94067,554,"NZL","New Zealand","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94068,554,"NZL","New Zealand","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94069,554,"NZL","New Zealand","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94070,554,"NZL","New Zealand","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94071,554,"NZL","New Zealand","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94072,554,"NZL","New Zealand","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94073,554,"NZL","New Zealand","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94074,554,"NZL","New Zealand","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94075,554,"NZL","New Zealand","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94076,554,"NZL","New Zealand","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94077,554,"NZL","New Zealand","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94078,554,"NZL","New Zealand","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94079,554,"NZL","New Zealand","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94080,554,"NZL","New Zealand","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94081,554,"NZL","New Zealand","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94082,554,"NZL","New Zealand","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94083,554,"NZL","New Zealand","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94084,554,"NZL","New Zealand","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94085,554,"NZL","New Zealand","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94086,554,"NZL","New Zealand","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94087,554,"NZL","New Zealand","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94088,554,"NZL","New Zealand","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94089,554,"NZL","New Zealand","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94090,554,"NZL","New Zealand","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94091,554,"NZL","New Zealand","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94092,554,"NZL","New Zealand","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94093,554,"NZL","New Zealand","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NZL/nzl_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94094,558,"NIC","Nicaragua","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94095,558,"NIC","Nicaragua","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94096,558,"NIC","Nicaragua","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94097,558,"NIC","Nicaragua","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94098,558,"NIC","Nicaragua","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94099,558,"NIC","Nicaragua","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94100,558,"NIC","Nicaragua","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94101,558,"NIC","Nicaragua","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94102,558,"NIC","Nicaragua","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94103,558,"NIC","Nicaragua","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94104,558,"NIC","Nicaragua","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94105,558,"NIC","Nicaragua","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94106,558,"NIC","Nicaragua","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94107,558,"NIC","Nicaragua","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94108,558,"NIC","Nicaragua","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94109,558,"NIC","Nicaragua","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94110,558,"NIC","Nicaragua","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94111,558,"NIC","Nicaragua","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94112,558,"NIC","Nicaragua","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94113,558,"NIC","Nicaragua","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94114,558,"NIC","Nicaragua","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94115,558,"NIC","Nicaragua","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94116,558,"NIC","Nicaragua","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94117,558,"NIC","Nicaragua","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94118,558,"NIC","Nicaragua","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94119,558,"NIC","Nicaragua","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94120,558,"NIC","Nicaragua","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94121,558,"NIC","Nicaragua","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94122,558,"NIC","Nicaragua","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94123,558,"NIC","Nicaragua","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94124,558,"NIC","Nicaragua","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94125,558,"NIC","Nicaragua","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94126,558,"NIC","Nicaragua","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94127,558,"NIC","Nicaragua","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94128,558,"NIC","Nicaragua","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94129,558,"NIC","Nicaragua","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIC/nic_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94130,562,"NER","Niger","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94131,562,"NER","Niger","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94132,562,"NER","Niger","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94133,562,"NER","Niger","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94134,562,"NER","Niger","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94135,562,"NER","Niger","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94136,562,"NER","Niger","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94137,562,"NER","Niger","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94138,562,"NER","Niger","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94139,562,"NER","Niger","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94140,562,"NER","Niger","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94141,562,"NER","Niger","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94142,562,"NER","Niger","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94143,562,"NER","Niger","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94144,562,"NER","Niger","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94145,562,"NER","Niger","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94146,562,"NER","Niger","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94147,562,"NER","Niger","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94148,562,"NER","Niger","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94149,562,"NER","Niger","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94150,562,"NER","Niger","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94151,562,"NER","Niger","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94152,562,"NER","Niger","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94153,562,"NER","Niger","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94154,562,"NER","Niger","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94155,562,"NER","Niger","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94156,562,"NER","Niger","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94157,562,"NER","Niger","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94158,562,"NER","Niger","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94159,562,"NER","Niger","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94160,562,"NER","Niger","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94161,562,"NER","Niger","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94162,562,"NER","Niger","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94163,562,"NER","Niger","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94164,562,"NER","Niger","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94165,562,"NER","Niger","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NER/ner_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94166,566,"NGA","Nigeria","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94167,566,"NGA","Nigeria","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94168,566,"NGA","Nigeria","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94169,566,"NGA","Nigeria","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94170,566,"NGA","Nigeria","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94171,566,"NGA","Nigeria","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94172,566,"NGA","Nigeria","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94173,566,"NGA","Nigeria","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94174,566,"NGA","Nigeria","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94175,566,"NGA","Nigeria","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94176,566,"NGA","Nigeria","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94177,566,"NGA","Nigeria","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94178,566,"NGA","Nigeria","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94179,566,"NGA","Nigeria","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94180,566,"NGA","Nigeria","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94181,566,"NGA","Nigeria","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94182,566,"NGA","Nigeria","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94183,566,"NGA","Nigeria","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94184,566,"NGA","Nigeria","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94185,566,"NGA","Nigeria","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94186,566,"NGA","Nigeria","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94187,566,"NGA","Nigeria","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94188,566,"NGA","Nigeria","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94189,566,"NGA","Nigeria","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94190,566,"NGA","Nigeria","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94191,566,"NGA","Nigeria","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94192,566,"NGA","Nigeria","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94193,566,"NGA","Nigeria","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94194,566,"NGA","Nigeria","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94195,566,"NGA","Nigeria","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94196,566,"NGA","Nigeria","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94197,566,"NGA","Nigeria","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94198,566,"NGA","Nigeria","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94199,566,"NGA","Nigeria","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94200,566,"NGA","Nigeria","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94201,566,"NGA","Nigeria","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NGA/nga_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94202,570,"NIU","Niue","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94203,570,"NIU","Niue","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94204,570,"NIU","Niue","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94205,570,"NIU","Niue","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94206,570,"NIU","Niue","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94207,570,"NIU","Niue","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94208,570,"NIU","Niue","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94209,570,"NIU","Niue","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94210,570,"NIU","Niue","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94211,570,"NIU","Niue","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94212,570,"NIU","Niue","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94213,570,"NIU","Niue","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94214,570,"NIU","Niue","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94215,570,"NIU","Niue","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94216,570,"NIU","Niue","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94217,570,"NIU","Niue","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94218,570,"NIU","Niue","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94219,570,"NIU","Niue","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94220,570,"NIU","Niue","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94221,570,"NIU","Niue","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94222,570,"NIU","Niue","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94223,570,"NIU","Niue","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94224,570,"NIU","Niue","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94225,570,"NIU","Niue","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94226,570,"NIU","Niue","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94227,570,"NIU","Niue","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94228,570,"NIU","Niue","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94229,570,"NIU","Niue","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94230,570,"NIU","Niue","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94231,570,"NIU","Niue","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94232,570,"NIU","Niue","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94233,570,"NIU","Niue","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94234,570,"NIU","Niue","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94235,570,"NIU","Niue","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94236,570,"NIU","Niue","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94237,570,"NIU","Niue","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NIU/niu_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94238,574,"NFK","Norfolk Island","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94239,574,"NFK","Norfolk Island","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94240,574,"NFK","Norfolk Island","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94241,574,"NFK","Norfolk Island","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94242,574,"NFK","Norfolk Island","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94243,574,"NFK","Norfolk Island","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94244,574,"NFK","Norfolk Island","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94245,574,"NFK","Norfolk Island","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94246,574,"NFK","Norfolk Island","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94247,574,"NFK","Norfolk Island","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94248,574,"NFK","Norfolk Island","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94249,574,"NFK","Norfolk Island","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94250,574,"NFK","Norfolk Island","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94251,574,"NFK","Norfolk Island","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94252,574,"NFK","Norfolk Island","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94253,574,"NFK","Norfolk Island","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94254,574,"NFK","Norfolk Island","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94255,574,"NFK","Norfolk Island","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94256,574,"NFK","Norfolk Island","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94257,574,"NFK","Norfolk Island","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94258,574,"NFK","Norfolk Island","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94259,574,"NFK","Norfolk Island","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94260,574,"NFK","Norfolk Island","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94261,574,"NFK","Norfolk Island","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94262,574,"NFK","Norfolk Island","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94263,574,"NFK","Norfolk Island","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94264,574,"NFK","Norfolk Island","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94265,574,"NFK","Norfolk Island","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94266,574,"NFK","Norfolk Island","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94267,574,"NFK","Norfolk Island","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94268,574,"NFK","Norfolk Island","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94269,574,"NFK","Norfolk Island","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94270,574,"NFK","Norfolk Island","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94271,574,"NFK","Norfolk Island","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94272,574,"NFK","Norfolk Island","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94273,574,"NFK","Norfolk Island","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NFK/nfk_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94274,578,"NOR","Norway","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94275,578,"NOR","Norway","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94276,578,"NOR","Norway","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94277,578,"NOR","Norway","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94278,578,"NOR","Norway","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94279,578,"NOR","Norway","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94280,578,"NOR","Norway","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94281,578,"NOR","Norway","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94282,578,"NOR","Norway","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94283,578,"NOR","Norway","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94284,578,"NOR","Norway","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94285,578,"NOR","Norway","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94286,578,"NOR","Norway","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94287,578,"NOR","Norway","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94288,578,"NOR","Norway","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94289,578,"NOR","Norway","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94290,578,"NOR","Norway","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94291,578,"NOR","Norway","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94292,578,"NOR","Norway","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94293,578,"NOR","Norway","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94294,578,"NOR","Norway","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94295,578,"NOR","Norway","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94296,578,"NOR","Norway","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94297,578,"NOR","Norway","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94298,578,"NOR","Norway","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94299,578,"NOR","Norway","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94300,578,"NOR","Norway","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94301,578,"NOR","Norway","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94302,578,"NOR","Norway","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94303,578,"NOR","Norway","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94304,578,"NOR","Norway","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94305,578,"NOR","Norway","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94306,578,"NOR","Norway","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94307,578,"NOR","Norway","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94308,578,"NOR","Norway","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94309,578,"NOR","Norway","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/NOR/nor_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94310,580,"MNP","Northern Mariana Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94311,580,"MNP","Northern Mariana Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94312,580,"MNP","Northern Mariana Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94313,580,"MNP","Northern Mariana Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94314,580,"MNP","Northern Mariana Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94315,580,"MNP","Northern Mariana Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94316,580,"MNP","Northern Mariana Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94317,580,"MNP","Northern Mariana Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94318,580,"MNP","Northern Mariana Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94319,580,"MNP","Northern Mariana Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94320,580,"MNP","Northern Mariana Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94321,580,"MNP","Northern Mariana Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94322,580,"MNP","Northern Mariana Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94323,580,"MNP","Northern Mariana Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94324,580,"MNP","Northern Mariana Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94325,580,"MNP","Northern Mariana Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94326,580,"MNP","Northern Mariana Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94327,580,"MNP","Northern Mariana Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94328,580,"MNP","Northern Mariana Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94329,580,"MNP","Northern Mariana Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94330,580,"MNP","Northern Mariana Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94331,580,"MNP","Northern Mariana Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94332,580,"MNP","Northern Mariana Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94333,580,"MNP","Northern Mariana Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94334,580,"MNP","Northern Mariana Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94335,580,"MNP","Northern Mariana Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94336,580,"MNP","Northern Mariana Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94337,580,"MNP","Northern Mariana Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94338,580,"MNP","Northern Mariana Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94339,580,"MNP","Northern Mariana Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94340,580,"MNP","Northern Mariana Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94341,580,"MNP","Northern Mariana Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94342,580,"MNP","Northern Mariana Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94343,580,"MNP","Northern Mariana Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94344,580,"MNP","Northern Mariana Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94345,580,"MNP","Northern Mariana Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MNP/mnp_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94346,583,"FSM","Micronesia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94347,583,"FSM","Micronesia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94348,583,"FSM","Micronesia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94349,583,"FSM","Micronesia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94350,583,"FSM","Micronesia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94351,583,"FSM","Micronesia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94352,583,"FSM","Micronesia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94353,583,"FSM","Micronesia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94354,583,"FSM","Micronesia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94355,583,"FSM","Micronesia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94356,583,"FSM","Micronesia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94357,583,"FSM","Micronesia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94358,583,"FSM","Micronesia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94359,583,"FSM","Micronesia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94360,583,"FSM","Micronesia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94361,583,"FSM","Micronesia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94362,583,"FSM","Micronesia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94363,583,"FSM","Micronesia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94364,583,"FSM","Micronesia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94365,583,"FSM","Micronesia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94366,583,"FSM","Micronesia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94367,583,"FSM","Micronesia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94368,583,"FSM","Micronesia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94369,583,"FSM","Micronesia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94370,583,"FSM","Micronesia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94371,583,"FSM","Micronesia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94372,583,"FSM","Micronesia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94373,583,"FSM","Micronesia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94374,583,"FSM","Micronesia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94375,583,"FSM","Micronesia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94376,583,"FSM","Micronesia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94377,583,"FSM","Micronesia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94378,583,"FSM","Micronesia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94379,583,"FSM","Micronesia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94380,583,"FSM","Micronesia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94381,583,"FSM","Micronesia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/FSM/fsm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94382,584,"MHL","Marshall Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94383,584,"MHL","Marshall Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94384,584,"MHL","Marshall Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94385,584,"MHL","Marshall Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94386,584,"MHL","Marshall Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94387,584,"MHL","Marshall Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94388,584,"MHL","Marshall Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94389,584,"MHL","Marshall Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94390,584,"MHL","Marshall Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94391,584,"MHL","Marshall Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94392,584,"MHL","Marshall Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94393,584,"MHL","Marshall Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94394,584,"MHL","Marshall Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94395,584,"MHL","Marshall Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94396,584,"MHL","Marshall Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94397,584,"MHL","Marshall Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94398,584,"MHL","Marshall Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94399,584,"MHL","Marshall Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94400,584,"MHL","Marshall Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94401,584,"MHL","Marshall Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94402,584,"MHL","Marshall Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94403,584,"MHL","Marshall Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94404,584,"MHL","Marshall Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94405,584,"MHL","Marshall Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94406,584,"MHL","Marshall Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94407,584,"MHL","Marshall Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94408,584,"MHL","Marshall Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94409,584,"MHL","Marshall Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94410,584,"MHL","Marshall Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94411,584,"MHL","Marshall Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94412,584,"MHL","Marshall Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94413,584,"MHL","Marshall Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94414,584,"MHL","Marshall Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94415,584,"MHL","Marshall Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94416,584,"MHL","Marshall Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94417,584,"MHL","Marshall Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MHL/mhl_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94418,585,"PLW","Palau","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94419,585,"PLW","Palau","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94420,585,"PLW","Palau","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94421,585,"PLW","Palau","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94422,585,"PLW","Palau","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94423,585,"PLW","Palau","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94424,585,"PLW","Palau","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94425,585,"PLW","Palau","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94426,585,"PLW","Palau","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94427,585,"PLW","Palau","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94428,585,"PLW","Palau","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94429,585,"PLW","Palau","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94430,585,"PLW","Palau","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94431,585,"PLW","Palau","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94432,585,"PLW","Palau","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94433,585,"PLW","Palau","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94434,585,"PLW","Palau","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94435,585,"PLW","Palau","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94436,585,"PLW","Palau","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94437,585,"PLW","Palau","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94438,585,"PLW","Palau","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94439,585,"PLW","Palau","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94440,585,"PLW","Palau","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94441,585,"PLW","Palau","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94442,585,"PLW","Palau","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94443,585,"PLW","Palau","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94444,585,"PLW","Palau","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94445,585,"PLW","Palau","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94446,585,"PLW","Palau","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94447,585,"PLW","Palau","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94448,585,"PLW","Palau","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94449,585,"PLW","Palau","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94450,585,"PLW","Palau","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94451,585,"PLW","Palau","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94452,585,"PLW","Palau","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94453,585,"PLW","Palau","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PLW/plw_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94454,586,"PAK","Pakistan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94455,586,"PAK","Pakistan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94456,586,"PAK","Pakistan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94457,586,"PAK","Pakistan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94458,586,"PAK","Pakistan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94459,586,"PAK","Pakistan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94460,586,"PAK","Pakistan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94461,586,"PAK","Pakistan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94462,586,"PAK","Pakistan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94463,586,"PAK","Pakistan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94464,586,"PAK","Pakistan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94465,586,"PAK","Pakistan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94466,586,"PAK","Pakistan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94467,586,"PAK","Pakistan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94468,586,"PAK","Pakistan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94469,586,"PAK","Pakistan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94470,586,"PAK","Pakistan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94471,586,"PAK","Pakistan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94472,586,"PAK","Pakistan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94473,586,"PAK","Pakistan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94474,586,"PAK","Pakistan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94475,586,"PAK","Pakistan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94476,586,"PAK","Pakistan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94477,586,"PAK","Pakistan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94478,586,"PAK","Pakistan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94479,586,"PAK","Pakistan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94480,586,"PAK","Pakistan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94481,586,"PAK","Pakistan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94482,586,"PAK","Pakistan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94483,586,"PAK","Pakistan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94484,586,"PAK","Pakistan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94485,586,"PAK","Pakistan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94486,586,"PAK","Pakistan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94487,586,"PAK","Pakistan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94488,586,"PAK","Pakistan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94489,586,"PAK","Pakistan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAK/pak_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94490,591,"PAN","Panama","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94491,591,"PAN","Panama","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94492,591,"PAN","Panama","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94493,591,"PAN","Panama","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94494,591,"PAN","Panama","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94495,591,"PAN","Panama","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94496,591,"PAN","Panama","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94497,591,"PAN","Panama","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94498,591,"PAN","Panama","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94499,591,"PAN","Panama","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94500,591,"PAN","Panama","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94501,591,"PAN","Panama","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94502,591,"PAN","Panama","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94503,591,"PAN","Panama","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94504,591,"PAN","Panama","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94505,591,"PAN","Panama","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94506,591,"PAN","Panama","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94507,591,"PAN","Panama","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94508,591,"PAN","Panama","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94509,591,"PAN","Panama","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94510,591,"PAN","Panama","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94511,591,"PAN","Panama","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94512,591,"PAN","Panama","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94513,591,"PAN","Panama","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94514,591,"PAN","Panama","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94515,591,"PAN","Panama","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94516,591,"PAN","Panama","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94517,591,"PAN","Panama","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94518,591,"PAN","Panama","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94519,591,"PAN","Panama","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94520,591,"PAN","Panama","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94521,591,"PAN","Panama","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94522,591,"PAN","Panama","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94523,591,"PAN","Panama","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94524,591,"PAN","Panama","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94525,591,"PAN","Panama","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PAN/pan_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94526,598,"PNG","Papua New Guinea","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94527,598,"PNG","Papua New Guinea","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94528,598,"PNG","Papua New Guinea","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94529,598,"PNG","Papua New Guinea","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94530,598,"PNG","Papua New Guinea","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94531,598,"PNG","Papua New Guinea","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94532,598,"PNG","Papua New Guinea","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94533,598,"PNG","Papua New Guinea","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94534,598,"PNG","Papua New Guinea","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94535,598,"PNG","Papua New Guinea","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94536,598,"PNG","Papua New Guinea","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94537,598,"PNG","Papua New Guinea","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94538,598,"PNG","Papua New Guinea","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94539,598,"PNG","Papua New Guinea","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94540,598,"PNG","Papua New Guinea","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94541,598,"PNG","Papua New Guinea","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94542,598,"PNG","Papua New Guinea","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94543,598,"PNG","Papua New Guinea","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94544,598,"PNG","Papua New Guinea","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94545,598,"PNG","Papua New Guinea","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94546,598,"PNG","Papua New Guinea","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94547,598,"PNG","Papua New Guinea","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94548,598,"PNG","Papua New Guinea","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94549,598,"PNG","Papua New Guinea","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94550,598,"PNG","Papua New Guinea","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94551,598,"PNG","Papua New Guinea","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94552,598,"PNG","Papua New Guinea","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94553,598,"PNG","Papua New Guinea","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94554,598,"PNG","Papua New Guinea","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94555,598,"PNG","Papua New Guinea","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94556,598,"PNG","Papua New Guinea","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94557,598,"PNG","Papua New Guinea","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94558,598,"PNG","Papua New Guinea","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94559,598,"PNG","Papua New Guinea","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94560,598,"PNG","Papua New Guinea","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94561,598,"PNG","Papua New Guinea","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PNG/png_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94562,600,"PRY","Paraguay","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94563,600,"PRY","Paraguay","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94564,600,"PRY","Paraguay","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94565,600,"PRY","Paraguay","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94566,600,"PRY","Paraguay","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94567,600,"PRY","Paraguay","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94568,600,"PRY","Paraguay","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94569,600,"PRY","Paraguay","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94570,600,"PRY","Paraguay","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94571,600,"PRY","Paraguay","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94572,600,"PRY","Paraguay","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94573,600,"PRY","Paraguay","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94574,600,"PRY","Paraguay","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94575,600,"PRY","Paraguay","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94576,600,"PRY","Paraguay","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94577,600,"PRY","Paraguay","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94578,600,"PRY","Paraguay","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94579,600,"PRY","Paraguay","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94580,600,"PRY","Paraguay","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94581,600,"PRY","Paraguay","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94582,600,"PRY","Paraguay","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94583,600,"PRY","Paraguay","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94584,600,"PRY","Paraguay","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94585,600,"PRY","Paraguay","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94586,600,"PRY","Paraguay","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94587,600,"PRY","Paraguay","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94588,600,"PRY","Paraguay","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94589,600,"PRY","Paraguay","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94590,600,"PRY","Paraguay","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94591,600,"PRY","Paraguay","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94592,600,"PRY","Paraguay","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94593,600,"PRY","Paraguay","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94594,600,"PRY","Paraguay","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94595,600,"PRY","Paraguay","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94596,600,"PRY","Paraguay","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94597,600,"PRY","Paraguay","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRY/pry_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94598,604,"PER","Peru","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94599,604,"PER","Peru","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94600,604,"PER","Peru","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94601,604,"PER","Peru","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94602,604,"PER","Peru","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94603,604,"PER","Peru","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94604,604,"PER","Peru","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94605,604,"PER","Peru","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94606,604,"PER","Peru","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94607,604,"PER","Peru","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94608,604,"PER","Peru","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94609,604,"PER","Peru","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94610,604,"PER","Peru","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94611,604,"PER","Peru","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94612,604,"PER","Peru","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94613,604,"PER","Peru","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94614,604,"PER","Peru","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94615,604,"PER","Peru","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94616,604,"PER","Peru","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94617,604,"PER","Peru","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94618,604,"PER","Peru","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94619,604,"PER","Peru","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94620,604,"PER","Peru","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94621,604,"PER","Peru","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94622,604,"PER","Peru","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94623,604,"PER","Peru","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94624,604,"PER","Peru","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94625,604,"PER","Peru","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94626,604,"PER","Peru","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94627,604,"PER","Peru","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94628,604,"PER","Peru","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94629,604,"PER","Peru","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94630,604,"PER","Peru","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94631,604,"PER","Peru","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94632,604,"PER","Peru","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94633,604,"PER","Peru","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PER/per_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94634,608,"PHL","Philippines","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94635,608,"PHL","Philippines","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94636,608,"PHL","Philippines","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94637,608,"PHL","Philippines","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94638,608,"PHL","Philippines","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94639,608,"PHL","Philippines","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94640,608,"PHL","Philippines","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94641,608,"PHL","Philippines","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94642,608,"PHL","Philippines","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94643,608,"PHL","Philippines","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94644,608,"PHL","Philippines","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94645,608,"PHL","Philippines","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94646,608,"PHL","Philippines","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94647,608,"PHL","Philippines","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94648,608,"PHL","Philippines","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94649,608,"PHL","Philippines","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94650,608,"PHL","Philippines","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94651,608,"PHL","Philippines","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94652,608,"PHL","Philippines","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94653,608,"PHL","Philippines","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94654,608,"PHL","Philippines","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94655,608,"PHL","Philippines","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94656,608,"PHL","Philippines","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94657,608,"PHL","Philippines","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94658,608,"PHL","Philippines","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94659,608,"PHL","Philippines","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94660,608,"PHL","Philippines","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94661,608,"PHL","Philippines","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94662,608,"PHL","Philippines","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94663,608,"PHL","Philippines","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94664,608,"PHL","Philippines","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94665,608,"PHL","Philippines","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94666,608,"PHL","Philippines","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94667,608,"PHL","Philippines","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94668,608,"PHL","Philippines","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94669,608,"PHL","Philippines","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PHL/phl_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94670,612,"PCN","Pitcairn Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94671,612,"PCN","Pitcairn Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94672,612,"PCN","Pitcairn Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94673,612,"PCN","Pitcairn Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94674,612,"PCN","Pitcairn Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94675,612,"PCN","Pitcairn Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94676,612,"PCN","Pitcairn Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94677,612,"PCN","Pitcairn Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94678,612,"PCN","Pitcairn Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94679,612,"PCN","Pitcairn Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94680,612,"PCN","Pitcairn Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94681,612,"PCN","Pitcairn Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94682,612,"PCN","Pitcairn Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94683,612,"PCN","Pitcairn Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94684,612,"PCN","Pitcairn Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94685,612,"PCN","Pitcairn Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94686,612,"PCN","Pitcairn Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94687,612,"PCN","Pitcairn Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94688,612,"PCN","Pitcairn Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94689,612,"PCN","Pitcairn Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94690,612,"PCN","Pitcairn Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94691,612,"PCN","Pitcairn Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94692,612,"PCN","Pitcairn Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94693,612,"PCN","Pitcairn Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94694,612,"PCN","Pitcairn Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94695,612,"PCN","Pitcairn Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94696,612,"PCN","Pitcairn Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94697,612,"PCN","Pitcairn Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94698,612,"PCN","Pitcairn Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94699,612,"PCN","Pitcairn Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94700,612,"PCN","Pitcairn Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94701,612,"PCN","Pitcairn Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94702,612,"PCN","Pitcairn Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94703,612,"PCN","Pitcairn Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94704,612,"PCN","Pitcairn Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94705,612,"PCN","Pitcairn Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PCN/pcn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94706,616,"POL","Poland","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94707,616,"POL","Poland","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94708,616,"POL","Poland","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94709,616,"POL","Poland","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94710,616,"POL","Poland","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94711,616,"POL","Poland","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94712,616,"POL","Poland","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94713,616,"POL","Poland","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94714,616,"POL","Poland","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94715,616,"POL","Poland","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94716,616,"POL","Poland","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94717,616,"POL","Poland","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94718,616,"POL","Poland","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94719,616,"POL","Poland","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94720,616,"POL","Poland","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94721,616,"POL","Poland","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94722,616,"POL","Poland","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94723,616,"POL","Poland","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94724,616,"POL","Poland","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94725,616,"POL","Poland","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94726,616,"POL","Poland","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94727,616,"POL","Poland","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94728,616,"POL","Poland","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94729,616,"POL","Poland","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94730,616,"POL","Poland","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94731,616,"POL","Poland","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94732,616,"POL","Poland","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94733,616,"POL","Poland","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94734,616,"POL","Poland","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94735,616,"POL","Poland","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94736,616,"POL","Poland","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94737,616,"POL","Poland","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94738,616,"POL","Poland","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94739,616,"POL","Poland","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94740,616,"POL","Poland","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94741,616,"POL","Poland","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/POL/pol_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94742,620,"PRT","Portugal","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94743,620,"PRT","Portugal","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94744,620,"PRT","Portugal","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94745,620,"PRT","Portugal","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94746,620,"PRT","Portugal","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94747,620,"PRT","Portugal","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94748,620,"PRT","Portugal","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94749,620,"PRT","Portugal","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94750,620,"PRT","Portugal","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94751,620,"PRT","Portugal","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94752,620,"PRT","Portugal","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94753,620,"PRT","Portugal","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94754,620,"PRT","Portugal","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94755,620,"PRT","Portugal","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94756,620,"PRT","Portugal","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94757,620,"PRT","Portugal","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94758,620,"PRT","Portugal","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94759,620,"PRT","Portugal","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94760,620,"PRT","Portugal","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94761,620,"PRT","Portugal","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94762,620,"PRT","Portugal","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94763,620,"PRT","Portugal","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94764,620,"PRT","Portugal","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94765,620,"PRT","Portugal","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94766,620,"PRT","Portugal","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94767,620,"PRT","Portugal","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94768,620,"PRT","Portugal","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94769,620,"PRT","Portugal","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94770,620,"PRT","Portugal","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94771,620,"PRT","Portugal","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94772,620,"PRT","Portugal","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94773,620,"PRT","Portugal","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94774,620,"PRT","Portugal","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94775,620,"PRT","Portugal","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94776,620,"PRT","Portugal","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94777,620,"PRT","Portugal","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRT/prt_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94778,624,"GNB","Guinea-Bissau","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94779,624,"GNB","Guinea-Bissau","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94780,624,"GNB","Guinea-Bissau","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94781,624,"GNB","Guinea-Bissau","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94782,624,"GNB","Guinea-Bissau","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94783,624,"GNB","Guinea-Bissau","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94784,624,"GNB","Guinea-Bissau","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94785,624,"GNB","Guinea-Bissau","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94786,624,"GNB","Guinea-Bissau","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94787,624,"GNB","Guinea-Bissau","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94788,624,"GNB","Guinea-Bissau","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94789,624,"GNB","Guinea-Bissau","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94790,624,"GNB","Guinea-Bissau","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94791,624,"GNB","Guinea-Bissau","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94792,624,"GNB","Guinea-Bissau","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94793,624,"GNB","Guinea-Bissau","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94794,624,"GNB","Guinea-Bissau","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94795,624,"GNB","Guinea-Bissau","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94796,624,"GNB","Guinea-Bissau","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94797,624,"GNB","Guinea-Bissau","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94798,624,"GNB","Guinea-Bissau","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94799,624,"GNB","Guinea-Bissau","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94800,624,"GNB","Guinea-Bissau","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94801,624,"GNB","Guinea-Bissau","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94802,624,"GNB","Guinea-Bissau","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94803,624,"GNB","Guinea-Bissau","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94804,624,"GNB","Guinea-Bissau","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94805,624,"GNB","Guinea-Bissau","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94806,624,"GNB","Guinea-Bissau","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94807,624,"GNB","Guinea-Bissau","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94808,624,"GNB","Guinea-Bissau","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94809,624,"GNB","Guinea-Bissau","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94810,624,"GNB","Guinea-Bissau","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94811,624,"GNB","Guinea-Bissau","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94812,624,"GNB","Guinea-Bissau","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94813,624,"GNB","Guinea-Bissau","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GNB/gnb_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94814,626,"TLS","East Timor","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94815,626,"TLS","East Timor","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94816,626,"TLS","East Timor","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94817,626,"TLS","East Timor","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94818,626,"TLS","East Timor","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94819,626,"TLS","East Timor","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94820,626,"TLS","East Timor","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94821,626,"TLS","East Timor","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94822,626,"TLS","East Timor","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94823,626,"TLS","East Timor","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94824,626,"TLS","East Timor","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94825,626,"TLS","East Timor","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94826,626,"TLS","East Timor","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94827,626,"TLS","East Timor","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94828,626,"TLS","East Timor","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94829,626,"TLS","East Timor","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94830,626,"TLS","East Timor","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94831,626,"TLS","East Timor","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94832,626,"TLS","East Timor","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94833,626,"TLS","East Timor","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94834,626,"TLS","East Timor","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94835,626,"TLS","East Timor","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94836,626,"TLS","East Timor","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94837,626,"TLS","East Timor","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94838,626,"TLS","East Timor","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94839,626,"TLS","East Timor","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94840,626,"TLS","East Timor","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94841,626,"TLS","East Timor","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94842,626,"TLS","East Timor","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94843,626,"TLS","East Timor","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94844,626,"TLS","East Timor","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94845,626,"TLS","East Timor","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94846,626,"TLS","East Timor","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94847,626,"TLS","East Timor","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94848,626,"TLS","East Timor","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94849,626,"TLS","East Timor","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TLS/tls_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94850,630,"PRI","Puerto Rico","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94851,630,"PRI","Puerto Rico","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94852,630,"PRI","Puerto Rico","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94853,630,"PRI","Puerto Rico","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94854,630,"PRI","Puerto Rico","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94855,630,"PRI","Puerto Rico","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94856,630,"PRI","Puerto Rico","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94857,630,"PRI","Puerto Rico","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94858,630,"PRI","Puerto Rico","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94859,630,"PRI","Puerto Rico","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94860,630,"PRI","Puerto Rico","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94861,630,"PRI","Puerto Rico","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94862,630,"PRI","Puerto Rico","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94863,630,"PRI","Puerto Rico","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94864,630,"PRI","Puerto Rico","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94865,630,"PRI","Puerto Rico","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94866,630,"PRI","Puerto Rico","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94867,630,"PRI","Puerto Rico","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94868,630,"PRI","Puerto Rico","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94869,630,"PRI","Puerto Rico","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94870,630,"PRI","Puerto Rico","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94871,630,"PRI","Puerto Rico","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94872,630,"PRI","Puerto Rico","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94873,630,"PRI","Puerto Rico","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94874,630,"PRI","Puerto Rico","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94875,630,"PRI","Puerto Rico","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94876,630,"PRI","Puerto Rico","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94877,630,"PRI","Puerto Rico","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94878,630,"PRI","Puerto Rico","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94879,630,"PRI","Puerto Rico","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94880,630,"PRI","Puerto Rico","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94881,630,"PRI","Puerto Rico","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94882,630,"PRI","Puerto Rico","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94883,630,"PRI","Puerto Rico","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94884,630,"PRI","Puerto Rico","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94885,630,"PRI","Puerto Rico","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/PRI/pri_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94886,634,"QAT","Qatar","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94887,634,"QAT","Qatar","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94888,634,"QAT","Qatar","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94889,634,"QAT","Qatar","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94890,634,"QAT","Qatar","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94891,634,"QAT","Qatar","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94892,634,"QAT","Qatar","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94893,634,"QAT","Qatar","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94894,634,"QAT","Qatar","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94895,634,"QAT","Qatar","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94896,634,"QAT","Qatar","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94897,634,"QAT","Qatar","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94898,634,"QAT","Qatar","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94899,634,"QAT","Qatar","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94900,634,"QAT","Qatar","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94901,634,"QAT","Qatar","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94902,634,"QAT","Qatar","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94903,634,"QAT","Qatar","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94904,634,"QAT","Qatar","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94905,634,"QAT","Qatar","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94906,634,"QAT","Qatar","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94907,634,"QAT","Qatar","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94908,634,"QAT","Qatar","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94909,634,"QAT","Qatar","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94910,634,"QAT","Qatar","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94911,634,"QAT","Qatar","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94912,634,"QAT","Qatar","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94913,634,"QAT","Qatar","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94914,634,"QAT","Qatar","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94915,634,"QAT","Qatar","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94916,634,"QAT","Qatar","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94917,634,"QAT","Qatar","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94918,634,"QAT","Qatar","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94919,634,"QAT","Qatar","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94920,634,"QAT","Qatar","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94921,634,"QAT","Qatar","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/QAT/qat_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94922,638,"REU","Reunion","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94923,638,"REU","Reunion","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94924,638,"REU","Reunion","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94925,638,"REU","Reunion","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94926,638,"REU","Reunion","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94927,638,"REU","Reunion","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94928,638,"REU","Reunion","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94929,638,"REU","Reunion","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94930,638,"REU","Reunion","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94931,638,"REU","Reunion","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94932,638,"REU","Reunion","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94933,638,"REU","Reunion","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94934,638,"REU","Reunion","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94935,638,"REU","Reunion","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94936,638,"REU","Reunion","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94937,638,"REU","Reunion","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94938,638,"REU","Reunion","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94939,638,"REU","Reunion","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94940,638,"REU","Reunion","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94941,638,"REU","Reunion","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94942,638,"REU","Reunion","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94943,638,"REU","Reunion","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94944,638,"REU","Reunion","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94945,638,"REU","Reunion","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94946,638,"REU","Reunion","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94947,638,"REU","Reunion","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94948,638,"REU","Reunion","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94949,638,"REU","Reunion","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94950,638,"REU","Reunion","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94951,638,"REU","Reunion","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94952,638,"REU","Reunion","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94953,638,"REU","Reunion","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94954,638,"REU","Reunion","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94955,638,"REU","Reunion","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94956,638,"REU","Reunion","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94957,638,"REU","Reunion","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/REU/reu_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94958,642,"ROU","Romania","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94959,642,"ROU","Romania","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94960,642,"ROU","Romania","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94961,642,"ROU","Romania","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94962,642,"ROU","Romania","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94963,642,"ROU","Romania","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94964,642,"ROU","Romania","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94965,642,"ROU","Romania","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94966,642,"ROU","Romania","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94967,642,"ROU","Romania","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94968,642,"ROU","Romania","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94969,642,"ROU","Romania","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94970,642,"ROU","Romania","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94971,642,"ROU","Romania","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94972,642,"ROU","Romania","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94973,642,"ROU","Romania","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94974,642,"ROU","Romania","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94975,642,"ROU","Romania","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94976,642,"ROU","Romania","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94977,642,"ROU","Romania","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94978,642,"ROU","Romania","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94979,642,"ROU","Romania","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94980,642,"ROU","Romania","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94981,642,"ROU","Romania","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94982,642,"ROU","Romania","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94983,642,"ROU","Romania","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94984,642,"ROU","Romania","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94985,642,"ROU","Romania","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94986,642,"ROU","Romania","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94987,642,"ROU","Romania","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94988,642,"ROU","Romania","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94989,642,"ROU","Romania","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94990,642,"ROU","Romania","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94991,642,"ROU","Romania","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94992,642,"ROU","Romania","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94993,642,"ROU","Romania","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ROU/rou_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
94994,646,"RWA","Rwanda","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94995,646,"RWA","Rwanda","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94996,646,"RWA","Rwanda","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94997,646,"RWA","Rwanda","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94998,646,"RWA","Rwanda","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
94999,646,"RWA","Rwanda","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95000,646,"RWA","Rwanda","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95001,646,"RWA","Rwanda","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95002,646,"RWA","Rwanda","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95003,646,"RWA","Rwanda","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95004,646,"RWA","Rwanda","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95005,646,"RWA","Rwanda","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95006,646,"RWA","Rwanda","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95007,646,"RWA","Rwanda","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95008,646,"RWA","Rwanda","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95009,646,"RWA","Rwanda","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95010,646,"RWA","Rwanda","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95011,646,"RWA","Rwanda","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95012,646,"RWA","Rwanda","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95013,646,"RWA","Rwanda","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95014,646,"RWA","Rwanda","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95015,646,"RWA","Rwanda","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95016,646,"RWA","Rwanda","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95017,646,"RWA","Rwanda","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95018,646,"RWA","Rwanda","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95019,646,"RWA","Rwanda","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95020,646,"RWA","Rwanda","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95021,646,"RWA","Rwanda","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95022,646,"RWA","Rwanda","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95023,646,"RWA","Rwanda","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95024,646,"RWA","Rwanda","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95025,646,"RWA","Rwanda","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95026,646,"RWA","Rwanda","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95027,646,"RWA","Rwanda","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95028,646,"RWA","Rwanda","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95029,646,"RWA","Rwanda","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/RWA/rwa_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95030,652,"BLM","Saint Barthelemy","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95031,652,"BLM","Saint Barthelemy","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95032,652,"BLM","Saint Barthelemy","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95033,652,"BLM","Saint Barthelemy","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95034,652,"BLM","Saint Barthelemy","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95035,652,"BLM","Saint Barthelemy","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95036,652,"BLM","Saint Barthelemy","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95037,652,"BLM","Saint Barthelemy","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95038,652,"BLM","Saint Barthelemy","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95039,652,"BLM","Saint Barthelemy","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95040,652,"BLM","Saint Barthelemy","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95041,652,"BLM","Saint Barthelemy","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95042,652,"BLM","Saint Barthelemy","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95043,652,"BLM","Saint Barthelemy","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95044,652,"BLM","Saint Barthelemy","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95045,652,"BLM","Saint Barthelemy","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95046,652,"BLM","Saint Barthelemy","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95047,652,"BLM","Saint Barthelemy","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95048,652,"BLM","Saint Barthelemy","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95049,652,"BLM","Saint Barthelemy","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95050,652,"BLM","Saint Barthelemy","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95051,652,"BLM","Saint Barthelemy","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95052,652,"BLM","Saint Barthelemy","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95053,652,"BLM","Saint Barthelemy","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95054,652,"BLM","Saint Barthelemy","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95055,652,"BLM","Saint Barthelemy","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95056,652,"BLM","Saint Barthelemy","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95057,652,"BLM","Saint Barthelemy","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95058,652,"BLM","Saint Barthelemy","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95059,652,"BLM","Saint Barthelemy","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95060,652,"BLM","Saint Barthelemy","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95061,652,"BLM","Saint Barthelemy","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95062,652,"BLM","Saint Barthelemy","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95063,652,"BLM","Saint Barthelemy","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95064,652,"BLM","Saint Barthelemy","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95065,652,"BLM","Saint Barthelemy","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BLM/blm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95066,654,"SHN","Saint Helena","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95067,654,"SHN","Saint Helena","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95068,654,"SHN","Saint Helena","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95069,654,"SHN","Saint Helena","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95070,654,"SHN","Saint Helena","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95071,654,"SHN","Saint Helena","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95072,654,"SHN","Saint Helena","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95073,654,"SHN","Saint Helena","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95074,654,"SHN","Saint Helena","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95075,654,"SHN","Saint Helena","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95076,654,"SHN","Saint Helena","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95077,654,"SHN","Saint Helena","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95078,654,"SHN","Saint Helena","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95079,654,"SHN","Saint Helena","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95080,654,"SHN","Saint Helena","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95081,654,"SHN","Saint Helena","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95082,654,"SHN","Saint Helena","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95083,654,"SHN","Saint Helena","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95084,654,"SHN","Saint Helena","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95085,654,"SHN","Saint Helena","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95086,654,"SHN","Saint Helena","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95087,654,"SHN","Saint Helena","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95088,654,"SHN","Saint Helena","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95089,654,"SHN","Saint Helena","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95090,654,"SHN","Saint Helena","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95091,654,"SHN","Saint Helena","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95092,654,"SHN","Saint Helena","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95093,654,"SHN","Saint Helena","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95094,654,"SHN","Saint Helena","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95095,654,"SHN","Saint Helena","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95096,654,"SHN","Saint Helena","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95097,654,"SHN","Saint Helena","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95098,654,"SHN","Saint Helena","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95099,654,"SHN","Saint Helena","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95100,654,"SHN","Saint Helena","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95101,654,"SHN","Saint Helena","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SHN/shn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95102,659,"KNA","Saint Kitts and Nevis","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95103,659,"KNA","Saint Kitts and Nevis","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95104,659,"KNA","Saint Kitts and Nevis","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95105,659,"KNA","Saint Kitts and Nevis","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95106,659,"KNA","Saint Kitts and Nevis","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95107,659,"KNA","Saint Kitts and Nevis","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95108,659,"KNA","Saint Kitts and Nevis","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95109,659,"KNA","Saint Kitts and Nevis","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95110,659,"KNA","Saint Kitts and Nevis","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95111,659,"KNA","Saint Kitts and Nevis","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95112,659,"KNA","Saint Kitts and Nevis","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95113,659,"KNA","Saint Kitts and Nevis","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95114,659,"KNA","Saint Kitts and Nevis","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95115,659,"KNA","Saint Kitts and Nevis","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95116,659,"KNA","Saint Kitts and Nevis","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95117,659,"KNA","Saint Kitts and Nevis","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95118,659,"KNA","Saint Kitts and Nevis","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95119,659,"KNA","Saint Kitts and Nevis","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95120,659,"KNA","Saint Kitts and Nevis","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95121,659,"KNA","Saint Kitts and Nevis","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95122,659,"KNA","Saint Kitts and Nevis","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95123,659,"KNA","Saint Kitts and Nevis","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95124,659,"KNA","Saint Kitts and Nevis","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95125,659,"KNA","Saint Kitts and Nevis","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95126,659,"KNA","Saint Kitts and Nevis","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95127,659,"KNA","Saint Kitts and Nevis","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95128,659,"KNA","Saint Kitts and Nevis","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95129,659,"KNA","Saint Kitts and Nevis","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95130,659,"KNA","Saint Kitts and Nevis","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95131,659,"KNA","Saint Kitts and Nevis","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95132,659,"KNA","Saint Kitts and Nevis","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95133,659,"KNA","Saint Kitts and Nevis","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95134,659,"KNA","Saint Kitts and Nevis","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95135,659,"KNA","Saint Kitts and Nevis","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95136,659,"KNA","Saint Kitts and Nevis","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95137,659,"KNA","Saint Kitts and Nevis","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KNA/kna_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95138,660,"AIA","Anguilla","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95139,660,"AIA","Anguilla","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95140,660,"AIA","Anguilla","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95141,660,"AIA","Anguilla","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95142,660,"AIA","Anguilla","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95143,660,"AIA","Anguilla","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95144,660,"AIA","Anguilla","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95145,660,"AIA","Anguilla","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95146,660,"AIA","Anguilla","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95147,660,"AIA","Anguilla","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95148,660,"AIA","Anguilla","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95149,660,"AIA","Anguilla","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95150,660,"AIA","Anguilla","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95151,660,"AIA","Anguilla","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95152,660,"AIA","Anguilla","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95153,660,"AIA","Anguilla","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95154,660,"AIA","Anguilla","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95155,660,"AIA","Anguilla","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95156,660,"AIA","Anguilla","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95157,660,"AIA","Anguilla","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95158,660,"AIA","Anguilla","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95159,660,"AIA","Anguilla","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95160,660,"AIA","Anguilla","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95161,660,"AIA","Anguilla","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95162,660,"AIA","Anguilla","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95163,660,"AIA","Anguilla","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95164,660,"AIA","Anguilla","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95165,660,"AIA","Anguilla","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95166,660,"AIA","Anguilla","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95167,660,"AIA","Anguilla","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95168,660,"AIA","Anguilla","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95169,660,"AIA","Anguilla","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95170,660,"AIA","Anguilla","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95171,660,"AIA","Anguilla","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95172,660,"AIA","Anguilla","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95173,660,"AIA","Anguilla","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/AIA/aia_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95174,662,"LCA","Saint Lucia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95175,662,"LCA","Saint Lucia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95176,662,"LCA","Saint Lucia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95177,662,"LCA","Saint Lucia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95178,662,"LCA","Saint Lucia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95179,662,"LCA","Saint Lucia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95180,662,"LCA","Saint Lucia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95181,662,"LCA","Saint Lucia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95182,662,"LCA","Saint Lucia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95183,662,"LCA","Saint Lucia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95184,662,"LCA","Saint Lucia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95185,662,"LCA","Saint Lucia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95186,662,"LCA","Saint Lucia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95187,662,"LCA","Saint Lucia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95188,662,"LCA","Saint Lucia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95189,662,"LCA","Saint Lucia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95190,662,"LCA","Saint Lucia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95191,662,"LCA","Saint Lucia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95192,662,"LCA","Saint Lucia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95193,662,"LCA","Saint Lucia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95194,662,"LCA","Saint Lucia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95195,662,"LCA","Saint Lucia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95196,662,"LCA","Saint Lucia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95197,662,"LCA","Saint Lucia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95198,662,"LCA","Saint Lucia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95199,662,"LCA","Saint Lucia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95200,662,"LCA","Saint Lucia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95201,662,"LCA","Saint Lucia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95202,662,"LCA","Saint Lucia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95203,662,"LCA","Saint Lucia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95204,662,"LCA","Saint Lucia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95205,662,"LCA","Saint Lucia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95206,662,"LCA","Saint Lucia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95207,662,"LCA","Saint Lucia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95208,662,"LCA","Saint Lucia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95209,662,"LCA","Saint Lucia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/LCA/lca_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95210,663,"MAF","Saint Martin (French part)","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95211,663,"MAF","Saint Martin (French part)","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95212,663,"MAF","Saint Martin (French part)","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95213,663,"MAF","Saint Martin (French part)","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95214,663,"MAF","Saint Martin (French part)","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95215,663,"MAF","Saint Martin (French part)","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95216,663,"MAF","Saint Martin (French part)","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95217,663,"MAF","Saint Martin (French part)","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95218,663,"MAF","Saint Martin (French part)","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95219,663,"MAF","Saint Martin (French part)","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95220,663,"MAF","Saint Martin (French part)","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95221,663,"MAF","Saint Martin (French part)","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95222,663,"MAF","Saint Martin (French part)","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95223,663,"MAF","Saint Martin (French part)","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95224,663,"MAF","Saint Martin (French part)","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95225,663,"MAF","Saint Martin (French part)","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95226,663,"MAF","Saint Martin (French part)","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95227,663,"MAF","Saint Martin (French part)","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95228,663,"MAF","Saint Martin (French part)","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95229,663,"MAF","Saint Martin (French part)","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95230,663,"MAF","Saint Martin (French part)","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95231,663,"MAF","Saint Martin (French part)","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95232,663,"MAF","Saint Martin (French part)","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95233,663,"MAF","Saint Martin (French part)","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95234,663,"MAF","Saint Martin (French part)","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95235,663,"MAF","Saint Martin (French part)","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95236,663,"MAF","Saint Martin (French part)","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95237,663,"MAF","Saint Martin (French part)","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95238,663,"MAF","Saint Martin (French part)","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95239,663,"MAF","Saint Martin (French part)","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95240,663,"MAF","Saint Martin (French part)","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95241,663,"MAF","Saint Martin (French part)","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95242,663,"MAF","Saint Martin (French part)","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95243,663,"MAF","Saint Martin (French part)","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95244,663,"MAF","Saint Martin (French part)","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95245,663,"MAF","Saint Martin (French part)","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MAF/maf_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95246,666,"SPM","Saint Pierre and Miquelon","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95247,666,"SPM","Saint Pierre and Miquelon","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95248,666,"SPM","Saint Pierre and Miquelon","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95249,666,"SPM","Saint Pierre and Miquelon","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95250,666,"SPM","Saint Pierre and Miquelon","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95251,666,"SPM","Saint Pierre and Miquelon","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95252,666,"SPM","Saint Pierre and Miquelon","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95253,666,"SPM","Saint Pierre and Miquelon","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95254,666,"SPM","Saint Pierre and Miquelon","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95255,666,"SPM","Saint Pierre and Miquelon","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95256,666,"SPM","Saint Pierre and Miquelon","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95257,666,"SPM","Saint Pierre and Miquelon","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95258,666,"SPM","Saint Pierre and Miquelon","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95259,666,"SPM","Saint Pierre and Miquelon","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95260,666,"SPM","Saint Pierre and Miquelon","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95261,666,"SPM","Saint Pierre and Miquelon","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95262,666,"SPM","Saint Pierre and Miquelon","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95263,666,"SPM","Saint Pierre and Miquelon","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95264,666,"SPM","Saint Pierre and Miquelon","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95265,666,"SPM","Saint Pierre and Miquelon","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95266,666,"SPM","Saint Pierre and Miquelon","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95267,666,"SPM","Saint Pierre and Miquelon","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95268,666,"SPM","Saint Pierre and Miquelon","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95269,666,"SPM","Saint Pierre and Miquelon","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95270,666,"SPM","Saint Pierre and Miquelon","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95271,666,"SPM","Saint Pierre and Miquelon","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95272,666,"SPM","Saint Pierre and Miquelon","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95273,666,"SPM","Saint Pierre and Miquelon","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95274,666,"SPM","Saint Pierre and Miquelon","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95275,666,"SPM","Saint Pierre and Miquelon","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95276,666,"SPM","Saint Pierre and Miquelon","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95277,666,"SPM","Saint Pierre and Miquelon","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95278,666,"SPM","Saint Pierre and Miquelon","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95279,666,"SPM","Saint Pierre and Miquelon","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95280,666,"SPM","Saint Pierre and Miquelon","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95281,666,"SPM","Saint Pierre and Miquelon","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SPM/spm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95282,670,"VCT","Saint Vincent and the Grenadines","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95283,670,"VCT","Saint Vincent and the Grenadines","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95284,670,"VCT","Saint Vincent and the Grenadines","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95285,670,"VCT","Saint Vincent and the Grenadines","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95286,670,"VCT","Saint Vincent and the Grenadines","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95287,670,"VCT","Saint Vincent and the Grenadines","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95288,670,"VCT","Saint Vincent and the Grenadines","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95289,670,"VCT","Saint Vincent and the Grenadines","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95290,670,"VCT","Saint Vincent and the Grenadines","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95291,670,"VCT","Saint Vincent and the Grenadines","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95292,670,"VCT","Saint Vincent and the Grenadines","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95293,670,"VCT","Saint Vincent and the Grenadines","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95294,670,"VCT","Saint Vincent and the Grenadines","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95295,670,"VCT","Saint Vincent and the Grenadines","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95296,670,"VCT","Saint Vincent and the Grenadines","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95297,670,"VCT","Saint Vincent and the Grenadines","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95298,670,"VCT","Saint Vincent and the Grenadines","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95299,670,"VCT","Saint Vincent and the Grenadines","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95300,670,"VCT","Saint Vincent and the Grenadines","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95301,670,"VCT","Saint Vincent and the Grenadines","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95302,670,"VCT","Saint Vincent and the Grenadines","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95303,670,"VCT","Saint Vincent and the Grenadines","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95304,670,"VCT","Saint Vincent and the Grenadines","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95305,670,"VCT","Saint Vincent and the Grenadines","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95306,670,"VCT","Saint Vincent and the Grenadines","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95307,670,"VCT","Saint Vincent and the Grenadines","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95308,670,"VCT","Saint Vincent and the Grenadines","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95309,670,"VCT","Saint Vincent and the Grenadines","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95310,670,"VCT","Saint Vincent and the Grenadines","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95311,670,"VCT","Saint Vincent and the Grenadines","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95312,670,"VCT","Saint Vincent and the Grenadines","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95313,670,"VCT","Saint Vincent and the Grenadines","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95314,670,"VCT","Saint Vincent and the Grenadines","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95315,670,"VCT","Saint Vincent and the Grenadines","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95316,670,"VCT","Saint Vincent and the Grenadines","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95317,670,"VCT","Saint Vincent and the Grenadines","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VCT/vct_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95318,674,"SMR","San Marino","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95319,674,"SMR","San Marino","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95320,674,"SMR","San Marino","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95321,674,"SMR","San Marino","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95322,674,"SMR","San Marino","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95323,674,"SMR","San Marino","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95324,674,"SMR","San Marino","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95325,674,"SMR","San Marino","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95326,674,"SMR","San Marino","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95327,674,"SMR","San Marino","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95328,674,"SMR","San Marino","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95329,674,"SMR","San Marino","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95330,674,"SMR","San Marino","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95331,674,"SMR","San Marino","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95332,674,"SMR","San Marino","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95333,674,"SMR","San Marino","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95334,674,"SMR","San Marino","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95335,674,"SMR","San Marino","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95336,674,"SMR","San Marino","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95337,674,"SMR","San Marino","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95338,674,"SMR","San Marino","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95339,674,"SMR","San Marino","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95340,674,"SMR","San Marino","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95341,674,"SMR","San Marino","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95342,674,"SMR","San Marino","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95343,674,"SMR","San Marino","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95344,674,"SMR","San Marino","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95345,674,"SMR","San Marino","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95346,674,"SMR","San Marino","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95347,674,"SMR","San Marino","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95348,674,"SMR","San Marino","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95349,674,"SMR","San Marino","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95350,674,"SMR","San Marino","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95351,674,"SMR","San Marino","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95352,674,"SMR","San Marino","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95353,674,"SMR","San Marino","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SMR/smr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95354,678,"STP","Sao Tome and Principe","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95355,678,"STP","Sao Tome and Principe","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95356,678,"STP","Sao Tome and Principe","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95357,678,"STP","Sao Tome and Principe","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95358,678,"STP","Sao Tome and Principe","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95359,678,"STP","Sao Tome and Principe","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95360,678,"STP","Sao Tome and Principe","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95361,678,"STP","Sao Tome and Principe","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95362,678,"STP","Sao Tome and Principe","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95363,678,"STP","Sao Tome and Principe","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95364,678,"STP","Sao Tome and Principe","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95365,678,"STP","Sao Tome and Principe","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95366,678,"STP","Sao Tome and Principe","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95367,678,"STP","Sao Tome and Principe","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95368,678,"STP","Sao Tome and Principe","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95369,678,"STP","Sao Tome and Principe","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95370,678,"STP","Sao Tome and Principe","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95371,678,"STP","Sao Tome and Principe","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95372,678,"STP","Sao Tome and Principe","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95373,678,"STP","Sao Tome and Principe","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95374,678,"STP","Sao Tome and Principe","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95375,678,"STP","Sao Tome and Principe","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95376,678,"STP","Sao Tome and Principe","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95377,678,"STP","Sao Tome and Principe","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95378,678,"STP","Sao Tome and Principe","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95379,678,"STP","Sao Tome and Principe","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95380,678,"STP","Sao Tome and Principe","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95381,678,"STP","Sao Tome and Principe","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95382,678,"STP","Sao Tome and Principe","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95383,678,"STP","Sao Tome and Principe","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95384,678,"STP","Sao Tome and Principe","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95385,678,"STP","Sao Tome and Principe","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95386,678,"STP","Sao Tome and Principe","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95387,678,"STP","Sao Tome and Principe","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95388,678,"STP","Sao Tome and Principe","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95389,678,"STP","Sao Tome and Principe","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/STP/stp_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95390,682,"SAU","Saudi Arabia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95391,682,"SAU","Saudi Arabia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95392,682,"SAU","Saudi Arabia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95393,682,"SAU","Saudi Arabia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95394,682,"SAU","Saudi Arabia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95395,682,"SAU","Saudi Arabia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95396,682,"SAU","Saudi Arabia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95397,682,"SAU","Saudi Arabia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95398,682,"SAU","Saudi Arabia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95399,682,"SAU","Saudi Arabia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95400,682,"SAU","Saudi Arabia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95401,682,"SAU","Saudi Arabia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95402,682,"SAU","Saudi Arabia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95403,682,"SAU","Saudi Arabia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95404,682,"SAU","Saudi Arabia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95405,682,"SAU","Saudi Arabia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95406,682,"SAU","Saudi Arabia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95407,682,"SAU","Saudi Arabia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95408,682,"SAU","Saudi Arabia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95409,682,"SAU","Saudi Arabia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95410,682,"SAU","Saudi Arabia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95411,682,"SAU","Saudi Arabia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95412,682,"SAU","Saudi Arabia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95413,682,"SAU","Saudi Arabia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95414,682,"SAU","Saudi Arabia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95415,682,"SAU","Saudi Arabia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95416,682,"SAU","Saudi Arabia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95417,682,"SAU","Saudi Arabia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95418,682,"SAU","Saudi Arabia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95419,682,"SAU","Saudi Arabia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95420,682,"SAU","Saudi Arabia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95421,682,"SAU","Saudi Arabia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95422,682,"SAU","Saudi Arabia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95423,682,"SAU","Saudi Arabia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95424,682,"SAU","Saudi Arabia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95425,682,"SAU","Saudi Arabia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SAU/sau_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95426,686,"SEN","Senegal","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95427,686,"SEN","Senegal","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95428,686,"SEN","Senegal","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95429,686,"SEN","Senegal","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95430,686,"SEN","Senegal","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95431,686,"SEN","Senegal","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95432,686,"SEN","Senegal","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95433,686,"SEN","Senegal","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95434,686,"SEN","Senegal","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95435,686,"SEN","Senegal","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95436,686,"SEN","Senegal","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95437,686,"SEN","Senegal","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95438,686,"SEN","Senegal","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95439,686,"SEN","Senegal","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95440,686,"SEN","Senegal","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95441,686,"SEN","Senegal","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95442,686,"SEN","Senegal","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95443,686,"SEN","Senegal","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95444,686,"SEN","Senegal","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95445,686,"SEN","Senegal","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95446,686,"SEN","Senegal","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95447,686,"SEN","Senegal","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95448,686,"SEN","Senegal","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95449,686,"SEN","Senegal","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95450,686,"SEN","Senegal","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95451,686,"SEN","Senegal","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95452,686,"SEN","Senegal","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95453,686,"SEN","Senegal","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95454,686,"SEN","Senegal","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95455,686,"SEN","Senegal","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95456,686,"SEN","Senegal","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95457,686,"SEN","Senegal","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95458,686,"SEN","Senegal","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95459,686,"SEN","Senegal","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95460,686,"SEN","Senegal","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95461,686,"SEN","Senegal","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SEN/sen_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95462,688,"SRB","Serbia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95463,688,"SRB","Serbia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95464,688,"SRB","Serbia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95465,688,"SRB","Serbia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95466,688,"SRB","Serbia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95467,688,"SRB","Serbia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95468,688,"SRB","Serbia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95469,688,"SRB","Serbia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95470,688,"SRB","Serbia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95471,688,"SRB","Serbia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95472,688,"SRB","Serbia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95473,688,"SRB","Serbia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95474,688,"SRB","Serbia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95475,688,"SRB","Serbia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95476,688,"SRB","Serbia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95477,688,"SRB","Serbia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95478,688,"SRB","Serbia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95479,688,"SRB","Serbia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95480,688,"SRB","Serbia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95481,688,"SRB","Serbia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95482,688,"SRB","Serbia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95483,688,"SRB","Serbia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95484,688,"SRB","Serbia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95485,688,"SRB","Serbia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95486,688,"SRB","Serbia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95487,688,"SRB","Serbia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95488,688,"SRB","Serbia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95489,688,"SRB","Serbia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95490,688,"SRB","Serbia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95491,688,"SRB","Serbia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95492,688,"SRB","Serbia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95493,688,"SRB","Serbia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95494,688,"SRB","Serbia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95495,688,"SRB","Serbia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95496,688,"SRB","Serbia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95497,688,"SRB","Serbia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SRB/srb_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95498,690,"SYC","Seychelles","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95499,690,"SYC","Seychelles","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95500,690,"SYC","Seychelles","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95501,690,"SYC","Seychelles","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95502,690,"SYC","Seychelles","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95503,690,"SYC","Seychelles","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95504,690,"SYC","Seychelles","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95505,690,"SYC","Seychelles","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95506,690,"SYC","Seychelles","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95507,690,"SYC","Seychelles","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95508,690,"SYC","Seychelles","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95509,690,"SYC","Seychelles","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95510,690,"SYC","Seychelles","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95511,690,"SYC","Seychelles","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95512,690,"SYC","Seychelles","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95513,690,"SYC","Seychelles","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95514,690,"SYC","Seychelles","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95515,690,"SYC","Seychelles","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95516,690,"SYC","Seychelles","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95517,690,"SYC","Seychelles","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95518,690,"SYC","Seychelles","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95519,690,"SYC","Seychelles","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95520,690,"SYC","Seychelles","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95521,690,"SYC","Seychelles","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95522,690,"SYC","Seychelles","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95523,690,"SYC","Seychelles","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95524,690,"SYC","Seychelles","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95525,690,"SYC","Seychelles","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95526,690,"SYC","Seychelles","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95527,690,"SYC","Seychelles","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95528,690,"SYC","Seychelles","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95529,690,"SYC","Seychelles","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95530,690,"SYC","Seychelles","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95531,690,"SYC","Seychelles","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95532,690,"SYC","Seychelles","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95533,690,"SYC","Seychelles","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYC/syc_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95534,694,"SLE","Sierra Leone","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95535,694,"SLE","Sierra Leone","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95536,694,"SLE","Sierra Leone","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95537,694,"SLE","Sierra Leone","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95538,694,"SLE","Sierra Leone","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95539,694,"SLE","Sierra Leone","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95540,694,"SLE","Sierra Leone","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95541,694,"SLE","Sierra Leone","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95542,694,"SLE","Sierra Leone","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95543,694,"SLE","Sierra Leone","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95544,694,"SLE","Sierra Leone","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95545,694,"SLE","Sierra Leone","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95546,694,"SLE","Sierra Leone","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95547,694,"SLE","Sierra Leone","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95548,694,"SLE","Sierra Leone","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95549,694,"SLE","Sierra Leone","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95550,694,"SLE","Sierra Leone","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95551,694,"SLE","Sierra Leone","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95552,694,"SLE","Sierra Leone","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95553,694,"SLE","Sierra Leone","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95554,694,"SLE","Sierra Leone","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95555,694,"SLE","Sierra Leone","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95556,694,"SLE","Sierra Leone","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95557,694,"SLE","Sierra Leone","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95558,694,"SLE","Sierra Leone","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95559,694,"SLE","Sierra Leone","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95560,694,"SLE","Sierra Leone","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95561,694,"SLE","Sierra Leone","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95562,694,"SLE","Sierra Leone","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95563,694,"SLE","Sierra Leone","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95564,694,"SLE","Sierra Leone","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95565,694,"SLE","Sierra Leone","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95566,694,"SLE","Sierra Leone","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95567,694,"SLE","Sierra Leone","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95568,694,"SLE","Sierra Leone","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95569,694,"SLE","Sierra Leone","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SLE/sle_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95570,702,"SGP","Singapore","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95571,702,"SGP","Singapore","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95572,702,"SGP","Singapore","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95573,702,"SGP","Singapore","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95574,702,"SGP","Singapore","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95575,702,"SGP","Singapore","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95576,702,"SGP","Singapore","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95577,702,"SGP","Singapore","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95578,702,"SGP","Singapore","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95579,702,"SGP","Singapore","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95580,702,"SGP","Singapore","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95581,702,"SGP","Singapore","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95582,702,"SGP","Singapore","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95583,702,"SGP","Singapore","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95584,702,"SGP","Singapore","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95585,702,"SGP","Singapore","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95586,702,"SGP","Singapore","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95587,702,"SGP","Singapore","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95588,702,"SGP","Singapore","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95589,702,"SGP","Singapore","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95590,702,"SGP","Singapore","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95591,702,"SGP","Singapore","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95592,702,"SGP","Singapore","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95593,702,"SGP","Singapore","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95594,702,"SGP","Singapore","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95595,702,"SGP","Singapore","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95596,702,"SGP","Singapore","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95597,702,"SGP","Singapore","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95598,702,"SGP","Singapore","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95599,702,"SGP","Singapore","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95600,702,"SGP","Singapore","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95601,702,"SGP","Singapore","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95602,702,"SGP","Singapore","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95603,702,"SGP","Singapore","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95604,702,"SGP","Singapore","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95605,702,"SGP","Singapore","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SGP/sgp_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95606,703,"SVK","Slovakia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95607,703,"SVK","Slovakia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95608,703,"SVK","Slovakia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95609,703,"SVK","Slovakia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95610,703,"SVK","Slovakia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95611,703,"SVK","Slovakia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95612,703,"SVK","Slovakia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95613,703,"SVK","Slovakia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95614,703,"SVK","Slovakia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95615,703,"SVK","Slovakia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95616,703,"SVK","Slovakia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95617,703,"SVK","Slovakia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95618,703,"SVK","Slovakia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95619,703,"SVK","Slovakia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95620,703,"SVK","Slovakia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95621,703,"SVK","Slovakia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95622,703,"SVK","Slovakia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95623,703,"SVK","Slovakia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95624,703,"SVK","Slovakia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95625,703,"SVK","Slovakia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95626,703,"SVK","Slovakia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95627,703,"SVK","Slovakia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95628,703,"SVK","Slovakia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95629,703,"SVK","Slovakia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95630,703,"SVK","Slovakia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95631,703,"SVK","Slovakia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95632,703,"SVK","Slovakia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95633,703,"SVK","Slovakia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95634,703,"SVK","Slovakia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95635,703,"SVK","Slovakia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95636,703,"SVK","Slovakia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95637,703,"SVK","Slovakia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95638,703,"SVK","Slovakia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95639,703,"SVK","Slovakia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95640,703,"SVK","Slovakia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95641,703,"SVK","Slovakia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVK/svk_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95642,704,"VNM","Vietnam","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95643,704,"VNM","Vietnam","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95644,704,"VNM","Vietnam","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95645,704,"VNM","Vietnam","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95646,704,"VNM","Vietnam","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95647,704,"VNM","Vietnam","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95648,704,"VNM","Vietnam","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95649,704,"VNM","Vietnam","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95650,704,"VNM","Vietnam","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95651,704,"VNM","Vietnam","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95652,704,"VNM","Vietnam","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95653,704,"VNM","Vietnam","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95654,704,"VNM","Vietnam","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95655,704,"VNM","Vietnam","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95656,704,"VNM","Vietnam","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95657,704,"VNM","Vietnam","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95658,704,"VNM","Vietnam","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95659,704,"VNM","Vietnam","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95660,704,"VNM","Vietnam","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95661,704,"VNM","Vietnam","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95662,704,"VNM","Vietnam","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95663,704,"VNM","Vietnam","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95664,704,"VNM","Vietnam","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95665,704,"VNM","Vietnam","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95666,704,"VNM","Vietnam","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95667,704,"VNM","Vietnam","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95668,704,"VNM","Vietnam","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95669,704,"VNM","Vietnam","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95670,704,"VNM","Vietnam","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95671,704,"VNM","Vietnam","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95672,704,"VNM","Vietnam","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95673,704,"VNM","Vietnam","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95674,704,"VNM","Vietnam","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95675,704,"VNM","Vietnam","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95676,704,"VNM","Vietnam","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95677,704,"VNM","Vietnam","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VNM/vnm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95678,705,"SVN","Slovenia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95679,705,"SVN","Slovenia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95680,705,"SVN","Slovenia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95681,705,"SVN","Slovenia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95682,705,"SVN","Slovenia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95683,705,"SVN","Slovenia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95684,705,"SVN","Slovenia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95685,705,"SVN","Slovenia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95686,705,"SVN","Slovenia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95687,705,"SVN","Slovenia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95688,705,"SVN","Slovenia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95689,705,"SVN","Slovenia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95690,705,"SVN","Slovenia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95691,705,"SVN","Slovenia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95692,705,"SVN","Slovenia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95693,705,"SVN","Slovenia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95694,705,"SVN","Slovenia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95695,705,"SVN","Slovenia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95696,705,"SVN","Slovenia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95697,705,"SVN","Slovenia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95698,705,"SVN","Slovenia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95699,705,"SVN","Slovenia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95700,705,"SVN","Slovenia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95701,705,"SVN","Slovenia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95702,705,"SVN","Slovenia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95703,705,"SVN","Slovenia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95704,705,"SVN","Slovenia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95705,705,"SVN","Slovenia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95706,705,"SVN","Slovenia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95707,705,"SVN","Slovenia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95708,705,"SVN","Slovenia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95709,705,"SVN","Slovenia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95710,705,"SVN","Slovenia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95711,705,"SVN","Slovenia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95712,705,"SVN","Slovenia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95713,705,"SVN","Slovenia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SVN/svn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95714,706,"SOM","Somalia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95715,706,"SOM","Somalia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95716,706,"SOM","Somalia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95717,706,"SOM","Somalia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95718,706,"SOM","Somalia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95719,706,"SOM","Somalia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95720,706,"SOM","Somalia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95721,706,"SOM","Somalia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95722,706,"SOM","Somalia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95723,706,"SOM","Somalia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95724,706,"SOM","Somalia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95725,706,"SOM","Somalia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95726,706,"SOM","Somalia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95727,706,"SOM","Somalia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95728,706,"SOM","Somalia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95729,706,"SOM","Somalia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95730,706,"SOM","Somalia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95731,706,"SOM","Somalia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95732,706,"SOM","Somalia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95733,706,"SOM","Somalia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95734,706,"SOM","Somalia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95735,706,"SOM","Somalia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95736,706,"SOM","Somalia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95737,706,"SOM","Somalia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95738,706,"SOM","Somalia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95739,706,"SOM","Somalia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95740,706,"SOM","Somalia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95741,706,"SOM","Somalia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95742,706,"SOM","Somalia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95743,706,"SOM","Somalia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95744,706,"SOM","Somalia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95745,706,"SOM","Somalia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95746,706,"SOM","Somalia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95747,706,"SOM","Somalia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95748,706,"SOM","Somalia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95749,706,"SOM","Somalia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SOM/som_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95750,710,"ZAF","South Africa","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95751,710,"ZAF","South Africa","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95752,710,"ZAF","South Africa","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95753,710,"ZAF","South Africa","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95754,710,"ZAF","South Africa","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95755,710,"ZAF","South Africa","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95756,710,"ZAF","South Africa","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95757,710,"ZAF","South Africa","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95758,710,"ZAF","South Africa","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95759,710,"ZAF","South Africa","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95760,710,"ZAF","South Africa","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95761,710,"ZAF","South Africa","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95762,710,"ZAF","South Africa","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95763,710,"ZAF","South Africa","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95764,710,"ZAF","South Africa","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95765,710,"ZAF","South Africa","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95766,710,"ZAF","South Africa","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95767,710,"ZAF","South Africa","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95768,710,"ZAF","South Africa","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95769,710,"ZAF","South Africa","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95770,710,"ZAF","South Africa","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95771,710,"ZAF","South Africa","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95772,710,"ZAF","South Africa","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95773,710,"ZAF","South Africa","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95774,710,"ZAF","South Africa","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95775,710,"ZAF","South Africa","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95776,710,"ZAF","South Africa","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95777,710,"ZAF","South Africa","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95778,710,"ZAF","South Africa","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95779,710,"ZAF","South Africa","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95780,710,"ZAF","South Africa","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95781,710,"ZAF","South Africa","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95782,710,"ZAF","South Africa","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95783,710,"ZAF","South Africa","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95784,710,"ZAF","South Africa","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95785,710,"ZAF","South Africa","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZAF/zaf_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95786,716,"ZWE","Zimbabwe","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95787,716,"ZWE","Zimbabwe","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95788,716,"ZWE","Zimbabwe","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95789,716,"ZWE","Zimbabwe","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95790,716,"ZWE","Zimbabwe","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95791,716,"ZWE","Zimbabwe","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95792,716,"ZWE","Zimbabwe","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95793,716,"ZWE","Zimbabwe","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95794,716,"ZWE","Zimbabwe","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95795,716,"ZWE","Zimbabwe","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95796,716,"ZWE","Zimbabwe","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95797,716,"ZWE","Zimbabwe","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95798,716,"ZWE","Zimbabwe","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95799,716,"ZWE","Zimbabwe","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95800,716,"ZWE","Zimbabwe","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95801,716,"ZWE","Zimbabwe","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95802,716,"ZWE","Zimbabwe","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95803,716,"ZWE","Zimbabwe","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95804,716,"ZWE","Zimbabwe","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95805,716,"ZWE","Zimbabwe","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95806,716,"ZWE","Zimbabwe","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95807,716,"ZWE","Zimbabwe","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95808,716,"ZWE","Zimbabwe","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95809,716,"ZWE","Zimbabwe","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95810,716,"ZWE","Zimbabwe","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95811,716,"ZWE","Zimbabwe","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95812,716,"ZWE","Zimbabwe","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95813,716,"ZWE","Zimbabwe","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95814,716,"ZWE","Zimbabwe","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95815,716,"ZWE","Zimbabwe","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95816,716,"ZWE","Zimbabwe","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95817,716,"ZWE","Zimbabwe","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95818,716,"ZWE","Zimbabwe","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95819,716,"ZWE","Zimbabwe","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95820,716,"ZWE","Zimbabwe","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95821,716,"ZWE","Zimbabwe","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZWE/zwe_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95822,724,"ESP","Spain","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95823,724,"ESP","Spain","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95824,724,"ESP","Spain","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95825,724,"ESP","Spain","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95826,724,"ESP","Spain","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95827,724,"ESP","Spain","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95828,724,"ESP","Spain","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95829,724,"ESP","Spain","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95830,724,"ESP","Spain","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95831,724,"ESP","Spain","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95832,724,"ESP","Spain","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95833,724,"ESP","Spain","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95834,724,"ESP","Spain","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95835,724,"ESP","Spain","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95836,724,"ESP","Spain","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95837,724,"ESP","Spain","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95838,724,"ESP","Spain","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95839,724,"ESP","Spain","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95840,724,"ESP","Spain","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95841,724,"ESP","Spain","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95842,724,"ESP","Spain","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95843,724,"ESP","Spain","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95844,724,"ESP","Spain","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95845,724,"ESP","Spain","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95846,724,"ESP","Spain","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95847,724,"ESP","Spain","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95848,724,"ESP","Spain","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95849,724,"ESP","Spain","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95850,724,"ESP","Spain","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95851,724,"ESP","Spain","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95852,724,"ESP","Spain","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95853,724,"ESP","Spain","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95854,724,"ESP","Spain","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95855,724,"ESP","Spain","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95856,724,"ESP","Spain","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95857,724,"ESP","Spain","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESP/esp_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95858,728,"SSD","South Sudan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95859,728,"SSD","South Sudan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95860,728,"SSD","South Sudan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95861,728,"SSD","South Sudan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95862,728,"SSD","South Sudan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95863,728,"SSD","South Sudan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95864,728,"SSD","South Sudan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95865,728,"SSD","South Sudan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95866,728,"SSD","South Sudan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95867,728,"SSD","South Sudan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95868,728,"SSD","South Sudan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95869,728,"SSD","South Sudan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95870,728,"SSD","South Sudan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95871,728,"SSD","South Sudan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95872,728,"SSD","South Sudan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95873,728,"SSD","South Sudan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95874,728,"SSD","South Sudan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95875,728,"SSD","South Sudan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95876,728,"SSD","South Sudan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95877,728,"SSD","South Sudan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95878,728,"SSD","South Sudan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95879,728,"SSD","South Sudan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95880,728,"SSD","South Sudan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95881,728,"SSD","South Sudan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95882,728,"SSD","South Sudan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95883,728,"SSD","South Sudan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95884,728,"SSD","South Sudan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95885,728,"SSD","South Sudan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95886,728,"SSD","South Sudan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95887,728,"SSD","South Sudan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95888,728,"SSD","South Sudan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95889,728,"SSD","South Sudan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95890,728,"SSD","South Sudan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95891,728,"SSD","South Sudan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95892,728,"SSD","South Sudan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95893,728,"SSD","South Sudan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SSD/ssd_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95894,729,"SDN","Sudan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95895,729,"SDN","Sudan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95896,729,"SDN","Sudan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95897,729,"SDN","Sudan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95898,729,"SDN","Sudan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95899,729,"SDN","Sudan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95900,729,"SDN","Sudan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95901,729,"SDN","Sudan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95902,729,"SDN","Sudan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95903,729,"SDN","Sudan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95904,729,"SDN","Sudan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95905,729,"SDN","Sudan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95906,729,"SDN","Sudan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95907,729,"SDN","Sudan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95908,729,"SDN","Sudan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95909,729,"SDN","Sudan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95910,729,"SDN","Sudan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95911,729,"SDN","Sudan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95912,729,"SDN","Sudan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95913,729,"SDN","Sudan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95914,729,"SDN","Sudan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95915,729,"SDN","Sudan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95916,729,"SDN","Sudan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95917,729,"SDN","Sudan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95918,729,"SDN","Sudan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95919,729,"SDN","Sudan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95920,729,"SDN","Sudan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95921,729,"SDN","Sudan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95922,729,"SDN","Sudan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95923,729,"SDN","Sudan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95924,729,"SDN","Sudan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95925,729,"SDN","Sudan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95926,729,"SDN","Sudan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95927,729,"SDN","Sudan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95928,729,"SDN","Sudan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95929,729,"SDN","Sudan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SDN/sdn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95930,732,"ESH","Western Sahara","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95931,732,"ESH","Western Sahara","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95932,732,"ESH","Western Sahara","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95933,732,"ESH","Western Sahara","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95934,732,"ESH","Western Sahara","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95935,732,"ESH","Western Sahara","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95936,732,"ESH","Western Sahara","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95937,732,"ESH","Western Sahara","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95938,732,"ESH","Western Sahara","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95939,732,"ESH","Western Sahara","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95940,732,"ESH","Western Sahara","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95941,732,"ESH","Western Sahara","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95942,732,"ESH","Western Sahara","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95943,732,"ESH","Western Sahara","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95944,732,"ESH","Western Sahara","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95945,732,"ESH","Western Sahara","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95946,732,"ESH","Western Sahara","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95947,732,"ESH","Western Sahara","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95948,732,"ESH","Western Sahara","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95949,732,"ESH","Western Sahara","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95950,732,"ESH","Western Sahara","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95951,732,"ESH","Western Sahara","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95952,732,"ESH","Western Sahara","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95953,732,"ESH","Western Sahara","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95954,732,"ESH","Western Sahara","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95955,732,"ESH","Western Sahara","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95956,732,"ESH","Western Sahara","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95957,732,"ESH","Western Sahara","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95958,732,"ESH","Western Sahara","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95959,732,"ESH","Western Sahara","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95960,732,"ESH","Western Sahara","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95961,732,"ESH","Western Sahara","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95962,732,"ESH","Western Sahara","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95963,732,"ESH","Western Sahara","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95964,732,"ESH","Western Sahara","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95965,732,"ESH","Western Sahara","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ESH/esh_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
95966,740,"SUR","Suriname","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95967,740,"SUR","Suriname","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95968,740,"SUR","Suriname","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95969,740,"SUR","Suriname","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95970,740,"SUR","Suriname","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95971,740,"SUR","Suriname","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95972,740,"SUR","Suriname","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95973,740,"SUR","Suriname","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95974,740,"SUR","Suriname","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95975,740,"SUR","Suriname","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95976,740,"SUR","Suriname","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95977,740,"SUR","Suriname","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95978,740,"SUR","Suriname","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95979,740,"SUR","Suriname","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95980,740,"SUR","Suriname","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95981,740,"SUR","Suriname","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95982,740,"SUR","Suriname","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95983,740,"SUR","Suriname","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95984,740,"SUR","Suriname","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95985,740,"SUR","Suriname","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95986,740,"SUR","Suriname","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95987,740,"SUR","Suriname","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95988,740,"SUR","Suriname","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95989,740,"SUR","Suriname","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95990,740,"SUR","Suriname","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95991,740,"SUR","Suriname","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95992,740,"SUR","Suriname","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95993,740,"SUR","Suriname","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95994,740,"SUR","Suriname","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95995,740,"SUR","Suriname","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95996,740,"SUR","Suriname","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95997,740,"SUR","Suriname","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95998,740,"SUR","Suriname","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
95999,740,"SUR","Suriname","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96000,740,"SUR","Suriname","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96001,740,"SUR","Suriname","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SUR/sur_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96002,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96003,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96004,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96005,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96006,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96007,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96008,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96009,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96010,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96011,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96012,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96013,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96014,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96015,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96016,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96017,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96018,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96019,744,"SJM","Svalbard and Jan Mayen Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96020,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96021,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96022,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96023,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96024,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96025,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96026,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96027,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96028,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96029,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96030,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96031,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96032,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96033,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96034,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96035,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96036,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96037,744,"SJM","Svalbard and Jan Mayen Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SJM/sjm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96038,748,"SWZ","Swaziland","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96039,748,"SWZ","Swaziland","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96040,748,"SWZ","Swaziland","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96041,748,"SWZ","Swaziland","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96042,748,"SWZ","Swaziland","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96043,748,"SWZ","Swaziland","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96044,748,"SWZ","Swaziland","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96045,748,"SWZ","Swaziland","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96046,748,"SWZ","Swaziland","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96047,748,"SWZ","Swaziland","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96048,748,"SWZ","Swaziland","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96049,748,"SWZ","Swaziland","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96050,748,"SWZ","Swaziland","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96051,748,"SWZ","Swaziland","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96052,748,"SWZ","Swaziland","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96053,748,"SWZ","Swaziland","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96054,748,"SWZ","Swaziland","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96055,748,"SWZ","Swaziland","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96056,748,"SWZ","Swaziland","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96057,748,"SWZ","Swaziland","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96058,748,"SWZ","Swaziland","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96059,748,"SWZ","Swaziland","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96060,748,"SWZ","Swaziland","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96061,748,"SWZ","Swaziland","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96062,748,"SWZ","Swaziland","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96063,748,"SWZ","Swaziland","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96064,748,"SWZ","Swaziland","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96065,748,"SWZ","Swaziland","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96066,748,"SWZ","Swaziland","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96067,748,"SWZ","Swaziland","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96068,748,"SWZ","Swaziland","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96069,748,"SWZ","Swaziland","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96070,748,"SWZ","Swaziland","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96071,748,"SWZ","Swaziland","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96072,748,"SWZ","Swaziland","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96073,748,"SWZ","Swaziland","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWZ/swz_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96074,752,"SWE","Sweden","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96075,752,"SWE","Sweden","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96076,752,"SWE","Sweden","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96077,752,"SWE","Sweden","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96078,752,"SWE","Sweden","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96079,752,"SWE","Sweden","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96080,752,"SWE","Sweden","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96081,752,"SWE","Sweden","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96082,752,"SWE","Sweden","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96083,752,"SWE","Sweden","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96084,752,"SWE","Sweden","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96085,752,"SWE","Sweden","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96086,752,"SWE","Sweden","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96087,752,"SWE","Sweden","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96088,752,"SWE","Sweden","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96089,752,"SWE","Sweden","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96090,752,"SWE","Sweden","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96091,752,"SWE","Sweden","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96092,752,"SWE","Sweden","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96093,752,"SWE","Sweden","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96094,752,"SWE","Sweden","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96095,752,"SWE","Sweden","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96096,752,"SWE","Sweden","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96097,752,"SWE","Sweden","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96098,752,"SWE","Sweden","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96099,752,"SWE","Sweden","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96100,752,"SWE","Sweden","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96101,752,"SWE","Sweden","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96102,752,"SWE","Sweden","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96103,752,"SWE","Sweden","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96104,752,"SWE","Sweden","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96105,752,"SWE","Sweden","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96106,752,"SWE","Sweden","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96107,752,"SWE","Sweden","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96108,752,"SWE","Sweden","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96109,752,"SWE","Sweden","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SWE/swe_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96110,756,"CHE","Switzerland","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96111,756,"CHE","Switzerland","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96112,756,"CHE","Switzerland","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96113,756,"CHE","Switzerland","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96114,756,"CHE","Switzerland","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96115,756,"CHE","Switzerland","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96116,756,"CHE","Switzerland","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96117,756,"CHE","Switzerland","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96118,756,"CHE","Switzerland","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96119,756,"CHE","Switzerland","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96120,756,"CHE","Switzerland","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96121,756,"CHE","Switzerland","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96122,756,"CHE","Switzerland","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96123,756,"CHE","Switzerland","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96124,756,"CHE","Switzerland","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96125,756,"CHE","Switzerland","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96126,756,"CHE","Switzerland","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96127,756,"CHE","Switzerland","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96128,756,"CHE","Switzerland","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96129,756,"CHE","Switzerland","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96130,756,"CHE","Switzerland","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96131,756,"CHE","Switzerland","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96132,756,"CHE","Switzerland","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96133,756,"CHE","Switzerland","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96134,756,"CHE","Switzerland","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96135,756,"CHE","Switzerland","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96136,756,"CHE","Switzerland","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96137,756,"CHE","Switzerland","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96138,756,"CHE","Switzerland","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96139,756,"CHE","Switzerland","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96140,756,"CHE","Switzerland","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96141,756,"CHE","Switzerland","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96142,756,"CHE","Switzerland","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96143,756,"CHE","Switzerland","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96144,756,"CHE","Switzerland","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96145,756,"CHE","Switzerland","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/CHE/che_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96146,760,"SYR","Syria","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96147,760,"SYR","Syria","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96148,760,"SYR","Syria","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96149,760,"SYR","Syria","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96150,760,"SYR","Syria","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96151,760,"SYR","Syria","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96152,760,"SYR","Syria","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96153,760,"SYR","Syria","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96154,760,"SYR","Syria","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96155,760,"SYR","Syria","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96156,760,"SYR","Syria","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96157,760,"SYR","Syria","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96158,760,"SYR","Syria","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96159,760,"SYR","Syria","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96160,760,"SYR","Syria","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96161,760,"SYR","Syria","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96162,760,"SYR","Syria","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96163,760,"SYR","Syria","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96164,760,"SYR","Syria","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96165,760,"SYR","Syria","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96166,760,"SYR","Syria","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96167,760,"SYR","Syria","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96168,760,"SYR","Syria","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96169,760,"SYR","Syria","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96170,760,"SYR","Syria","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96171,760,"SYR","Syria","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96172,760,"SYR","Syria","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96173,760,"SYR","Syria","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96174,760,"SYR","Syria","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96175,760,"SYR","Syria","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96176,760,"SYR","Syria","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96177,760,"SYR","Syria","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96178,760,"SYR","Syria","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96179,760,"SYR","Syria","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96180,760,"SYR","Syria","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96181,760,"SYR","Syria","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/SYR/syr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96182,762,"TJK","Tajikistan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96183,762,"TJK","Tajikistan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96184,762,"TJK","Tajikistan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96185,762,"TJK","Tajikistan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96186,762,"TJK","Tajikistan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96187,762,"TJK","Tajikistan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96188,762,"TJK","Tajikistan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96189,762,"TJK","Tajikistan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96190,762,"TJK","Tajikistan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96191,762,"TJK","Tajikistan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96192,762,"TJK","Tajikistan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96193,762,"TJK","Tajikistan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96194,762,"TJK","Tajikistan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96195,762,"TJK","Tajikistan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96196,762,"TJK","Tajikistan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96197,762,"TJK","Tajikistan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96198,762,"TJK","Tajikistan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96199,762,"TJK","Tajikistan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96200,762,"TJK","Tajikistan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96201,762,"TJK","Tajikistan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96202,762,"TJK","Tajikistan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96203,762,"TJK","Tajikistan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96204,762,"TJK","Tajikistan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96205,762,"TJK","Tajikistan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96206,762,"TJK","Tajikistan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96207,762,"TJK","Tajikistan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96208,762,"TJK","Tajikistan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96209,762,"TJK","Tajikistan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96210,762,"TJK","Tajikistan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96211,762,"TJK","Tajikistan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96212,762,"TJK","Tajikistan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96213,762,"TJK","Tajikistan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96214,762,"TJK","Tajikistan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96215,762,"TJK","Tajikistan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96216,762,"TJK","Tajikistan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96217,762,"TJK","Tajikistan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TJK/tjk_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96218,764,"THA","Thailand","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96219,764,"THA","Thailand","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96220,764,"THA","Thailand","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96221,764,"THA","Thailand","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96222,764,"THA","Thailand","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96223,764,"THA","Thailand","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96224,764,"THA","Thailand","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96225,764,"THA","Thailand","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96226,764,"THA","Thailand","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96227,764,"THA","Thailand","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96228,764,"THA","Thailand","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96229,764,"THA","Thailand","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96230,764,"THA","Thailand","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96231,764,"THA","Thailand","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96232,764,"THA","Thailand","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96233,764,"THA","Thailand","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96234,764,"THA","Thailand","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96235,764,"THA","Thailand","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96236,764,"THA","Thailand","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96237,764,"THA","Thailand","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96238,764,"THA","Thailand","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96239,764,"THA","Thailand","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96240,764,"THA","Thailand","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96241,764,"THA","Thailand","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96242,764,"THA","Thailand","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96243,764,"THA","Thailand","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96244,764,"THA","Thailand","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96245,764,"THA","Thailand","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96246,764,"THA","Thailand","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96247,764,"THA","Thailand","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96248,764,"THA","Thailand","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96249,764,"THA","Thailand","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96250,764,"THA","Thailand","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96251,764,"THA","Thailand","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96252,764,"THA","Thailand","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96253,764,"THA","Thailand","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/THA/tha_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96254,768,"TGO","Togo","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96255,768,"TGO","Togo","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96256,768,"TGO","Togo","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96257,768,"TGO","Togo","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96258,768,"TGO","Togo","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96259,768,"TGO","Togo","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96260,768,"TGO","Togo","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96261,768,"TGO","Togo","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96262,768,"TGO","Togo","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96263,768,"TGO","Togo","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96264,768,"TGO","Togo","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96265,768,"TGO","Togo","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96266,768,"TGO","Togo","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96267,768,"TGO","Togo","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96268,768,"TGO","Togo","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96269,768,"TGO","Togo","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96270,768,"TGO","Togo","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96271,768,"TGO","Togo","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96272,768,"TGO","Togo","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96273,768,"TGO","Togo","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96274,768,"TGO","Togo","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96275,768,"TGO","Togo","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96276,768,"TGO","Togo","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96277,768,"TGO","Togo","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96278,768,"TGO","Togo","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96279,768,"TGO","Togo","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96280,768,"TGO","Togo","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96281,768,"TGO","Togo","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96282,768,"TGO","Togo","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96283,768,"TGO","Togo","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96284,768,"TGO","Togo","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96285,768,"TGO","Togo","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96286,768,"TGO","Togo","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96287,768,"TGO","Togo","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96288,768,"TGO","Togo","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96289,768,"TGO","Togo","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TGO/tgo_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96290,772,"TKL","Tokelau","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96291,772,"TKL","Tokelau","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96292,772,"TKL","Tokelau","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96293,772,"TKL","Tokelau","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96294,772,"TKL","Tokelau","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96295,772,"TKL","Tokelau","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96296,772,"TKL","Tokelau","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96297,772,"TKL","Tokelau","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96298,772,"TKL","Tokelau","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96299,772,"TKL","Tokelau","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96300,772,"TKL","Tokelau","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96301,772,"TKL","Tokelau","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96302,772,"TKL","Tokelau","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96303,772,"TKL","Tokelau","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96304,772,"TKL","Tokelau","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96305,772,"TKL","Tokelau","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96306,772,"TKL","Tokelau","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96307,772,"TKL","Tokelau","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96308,772,"TKL","Tokelau","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96309,772,"TKL","Tokelau","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96310,772,"TKL","Tokelau","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96311,772,"TKL","Tokelau","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96312,772,"TKL","Tokelau","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96313,772,"TKL","Tokelau","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96314,772,"TKL","Tokelau","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96315,772,"TKL","Tokelau","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96316,772,"TKL","Tokelau","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96317,772,"TKL","Tokelau","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96318,772,"TKL","Tokelau","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96319,772,"TKL","Tokelau","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96320,772,"TKL","Tokelau","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96321,772,"TKL","Tokelau","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96322,772,"TKL","Tokelau","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96323,772,"TKL","Tokelau","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96324,772,"TKL","Tokelau","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96325,772,"TKL","Tokelau","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKL/tkl_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96326,776,"TON","Tonga","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96327,776,"TON","Tonga","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96328,776,"TON","Tonga","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96329,776,"TON","Tonga","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96330,776,"TON","Tonga","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96331,776,"TON","Tonga","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96332,776,"TON","Tonga","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96333,776,"TON","Tonga","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96334,776,"TON","Tonga","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96335,776,"TON","Tonga","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96336,776,"TON","Tonga","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96337,776,"TON","Tonga","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96338,776,"TON","Tonga","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96339,776,"TON","Tonga","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96340,776,"TON","Tonga","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96341,776,"TON","Tonga","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96342,776,"TON","Tonga","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96343,776,"TON","Tonga","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96344,776,"TON","Tonga","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96345,776,"TON","Tonga","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96346,776,"TON","Tonga","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96347,776,"TON","Tonga","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96348,776,"TON","Tonga","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96349,776,"TON","Tonga","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96350,776,"TON","Tonga","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96351,776,"TON","Tonga","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96352,776,"TON","Tonga","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96353,776,"TON","Tonga","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96354,776,"TON","Tonga","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96355,776,"TON","Tonga","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96356,776,"TON","Tonga","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96357,776,"TON","Tonga","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96358,776,"TON","Tonga","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96359,776,"TON","Tonga","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96360,776,"TON","Tonga","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96361,776,"TON","Tonga","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TON/ton_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96362,780,"TTO","Trinidad and Tobago","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96363,780,"TTO","Trinidad and Tobago","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96364,780,"TTO","Trinidad and Tobago","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96365,780,"TTO","Trinidad and Tobago","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96366,780,"TTO","Trinidad and Tobago","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96367,780,"TTO","Trinidad and Tobago","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96368,780,"TTO","Trinidad and Tobago","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96369,780,"TTO","Trinidad and Tobago","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96370,780,"TTO","Trinidad and Tobago","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96371,780,"TTO","Trinidad and Tobago","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96372,780,"TTO","Trinidad and Tobago","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96373,780,"TTO","Trinidad and Tobago","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96374,780,"TTO","Trinidad and Tobago","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96375,780,"TTO","Trinidad and Tobago","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96376,780,"TTO","Trinidad and Tobago","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96377,780,"TTO","Trinidad and Tobago","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96378,780,"TTO","Trinidad and Tobago","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96379,780,"TTO","Trinidad and Tobago","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96380,780,"TTO","Trinidad and Tobago","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96381,780,"TTO","Trinidad and Tobago","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96382,780,"TTO","Trinidad and Tobago","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96383,780,"TTO","Trinidad and Tobago","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96384,780,"TTO","Trinidad and Tobago","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96385,780,"TTO","Trinidad and Tobago","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96386,780,"TTO","Trinidad and Tobago","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96387,780,"TTO","Trinidad and Tobago","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96388,780,"TTO","Trinidad and Tobago","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96389,780,"TTO","Trinidad and Tobago","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96390,780,"TTO","Trinidad and Tobago","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96391,780,"TTO","Trinidad and Tobago","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96392,780,"TTO","Trinidad and Tobago","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96393,780,"TTO","Trinidad and Tobago","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96394,780,"TTO","Trinidad and Tobago","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96395,780,"TTO","Trinidad and Tobago","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96396,780,"TTO","Trinidad and Tobago","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96397,780,"TTO","Trinidad and Tobago","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TTO/tto_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96398,784,"ARE","United Arab Emirates","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96399,784,"ARE","United Arab Emirates","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96400,784,"ARE","United Arab Emirates","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96401,784,"ARE","United Arab Emirates","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96402,784,"ARE","United Arab Emirates","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96403,784,"ARE","United Arab Emirates","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96404,784,"ARE","United Arab Emirates","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96405,784,"ARE","United Arab Emirates","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96406,784,"ARE","United Arab Emirates","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96407,784,"ARE","United Arab Emirates","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96408,784,"ARE","United Arab Emirates","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96409,784,"ARE","United Arab Emirates","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96410,784,"ARE","United Arab Emirates","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96411,784,"ARE","United Arab Emirates","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96412,784,"ARE","United Arab Emirates","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96413,784,"ARE","United Arab Emirates","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96414,784,"ARE","United Arab Emirates","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96415,784,"ARE","United Arab Emirates","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96416,784,"ARE","United Arab Emirates","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96417,784,"ARE","United Arab Emirates","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96418,784,"ARE","United Arab Emirates","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96419,784,"ARE","United Arab Emirates","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96420,784,"ARE","United Arab Emirates","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96421,784,"ARE","United Arab Emirates","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96422,784,"ARE","United Arab Emirates","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96423,784,"ARE","United Arab Emirates","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96424,784,"ARE","United Arab Emirates","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96425,784,"ARE","United Arab Emirates","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96426,784,"ARE","United Arab Emirates","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96427,784,"ARE","United Arab Emirates","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96428,784,"ARE","United Arab Emirates","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96429,784,"ARE","United Arab Emirates","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96430,784,"ARE","United Arab Emirates","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96431,784,"ARE","United Arab Emirates","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96432,784,"ARE","United Arab Emirates","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96433,784,"ARE","United Arab Emirates","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ARE/are_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96434,788,"TUN","Tunisia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96435,788,"TUN","Tunisia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96436,788,"TUN","Tunisia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96437,788,"TUN","Tunisia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96438,788,"TUN","Tunisia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96439,788,"TUN","Tunisia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96440,788,"TUN","Tunisia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96441,788,"TUN","Tunisia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96442,788,"TUN","Tunisia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96443,788,"TUN","Tunisia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96444,788,"TUN","Tunisia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96445,788,"TUN","Tunisia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96446,788,"TUN","Tunisia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96447,788,"TUN","Tunisia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96448,788,"TUN","Tunisia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96449,788,"TUN","Tunisia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96450,788,"TUN","Tunisia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96451,788,"TUN","Tunisia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96452,788,"TUN","Tunisia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96453,788,"TUN","Tunisia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96454,788,"TUN","Tunisia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96455,788,"TUN","Tunisia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96456,788,"TUN","Tunisia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96457,788,"TUN","Tunisia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96458,788,"TUN","Tunisia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96459,788,"TUN","Tunisia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96460,788,"TUN","Tunisia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96461,788,"TUN","Tunisia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96462,788,"TUN","Tunisia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96463,788,"TUN","Tunisia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96464,788,"TUN","Tunisia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96465,788,"TUN","Tunisia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96466,788,"TUN","Tunisia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96467,788,"TUN","Tunisia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96468,788,"TUN","Tunisia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96469,788,"TUN","Tunisia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUN/tun_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96470,792,"TUR","Turkey","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96471,792,"TUR","Turkey","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96472,792,"TUR","Turkey","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96473,792,"TUR","Turkey","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96474,792,"TUR","Turkey","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96475,792,"TUR","Turkey","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96476,792,"TUR","Turkey","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96477,792,"TUR","Turkey","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96478,792,"TUR","Turkey","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96479,792,"TUR","Turkey","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96480,792,"TUR","Turkey","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96481,792,"TUR","Turkey","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96482,792,"TUR","Turkey","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96483,792,"TUR","Turkey","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96484,792,"TUR","Turkey","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96485,792,"TUR","Turkey","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96486,792,"TUR","Turkey","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96487,792,"TUR","Turkey","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96488,792,"TUR","Turkey","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96489,792,"TUR","Turkey","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96490,792,"TUR","Turkey","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96491,792,"TUR","Turkey","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96492,792,"TUR","Turkey","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96493,792,"TUR","Turkey","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96494,792,"TUR","Turkey","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96495,792,"TUR","Turkey","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96496,792,"TUR","Turkey","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96497,792,"TUR","Turkey","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96498,792,"TUR","Turkey","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96499,792,"TUR","Turkey","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96500,792,"TUR","Turkey","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96501,792,"TUR","Turkey","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96502,792,"TUR","Turkey","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96503,792,"TUR","Turkey","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96504,792,"TUR","Turkey","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96505,792,"TUR","Turkey","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUR/tur_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96506,795,"TKM","Turkmenistan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96507,795,"TKM","Turkmenistan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96508,795,"TKM","Turkmenistan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96509,795,"TKM","Turkmenistan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96510,795,"TKM","Turkmenistan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96511,795,"TKM","Turkmenistan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96512,795,"TKM","Turkmenistan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96513,795,"TKM","Turkmenistan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96514,795,"TKM","Turkmenistan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96515,795,"TKM","Turkmenistan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96516,795,"TKM","Turkmenistan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96517,795,"TKM","Turkmenistan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96518,795,"TKM","Turkmenistan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96519,795,"TKM","Turkmenistan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96520,795,"TKM","Turkmenistan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96521,795,"TKM","Turkmenistan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96522,795,"TKM","Turkmenistan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96523,795,"TKM","Turkmenistan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96524,795,"TKM","Turkmenistan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96525,795,"TKM","Turkmenistan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96526,795,"TKM","Turkmenistan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96527,795,"TKM","Turkmenistan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96528,795,"TKM","Turkmenistan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96529,795,"TKM","Turkmenistan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96530,795,"TKM","Turkmenistan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96531,795,"TKM","Turkmenistan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96532,795,"TKM","Turkmenistan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96533,795,"TKM","Turkmenistan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96534,795,"TKM","Turkmenistan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96535,795,"TKM","Turkmenistan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96536,795,"TKM","Turkmenistan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96537,795,"TKM","Turkmenistan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96538,795,"TKM","Turkmenistan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96539,795,"TKM","Turkmenistan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96540,795,"TKM","Turkmenistan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96541,795,"TKM","Turkmenistan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TKM/tkm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96542,796,"TCA","Turks and Caicos Islands","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96543,796,"TCA","Turks and Caicos Islands","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96544,796,"TCA","Turks and Caicos Islands","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96545,796,"TCA","Turks and Caicos Islands","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96546,796,"TCA","Turks and Caicos Islands","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96547,796,"TCA","Turks and Caicos Islands","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96548,796,"TCA","Turks and Caicos Islands","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96549,796,"TCA","Turks and Caicos Islands","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96550,796,"TCA","Turks and Caicos Islands","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96551,796,"TCA","Turks and Caicos Islands","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96552,796,"TCA","Turks and Caicos Islands","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96553,796,"TCA","Turks and Caicos Islands","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96554,796,"TCA","Turks and Caicos Islands","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96555,796,"TCA","Turks and Caicos Islands","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96556,796,"TCA","Turks and Caicos Islands","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96557,796,"TCA","Turks and Caicos Islands","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96558,796,"TCA","Turks and Caicos Islands","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96559,796,"TCA","Turks and Caicos Islands","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96560,796,"TCA","Turks and Caicos Islands","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96561,796,"TCA","Turks and Caicos Islands","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96562,796,"TCA","Turks and Caicos Islands","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96563,796,"TCA","Turks and Caicos Islands","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96564,796,"TCA","Turks and Caicos Islands","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96565,796,"TCA","Turks and Caicos Islands","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96566,796,"TCA","Turks and Caicos Islands","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96567,796,"TCA","Turks and Caicos Islands","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96568,796,"TCA","Turks and Caicos Islands","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96569,796,"TCA","Turks and Caicos Islands","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96570,796,"TCA","Turks and Caicos Islands","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96571,796,"TCA","Turks and Caicos Islands","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96572,796,"TCA","Turks and Caicos Islands","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96573,796,"TCA","Turks and Caicos Islands","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96574,796,"TCA","Turks and Caicos Islands","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96575,796,"TCA","Turks and Caicos Islands","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96576,796,"TCA","Turks and Caicos Islands","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96577,796,"TCA","Turks and Caicos Islands","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TCA/tca_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96578,798,"TUV","Tuvalu","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96579,798,"TUV","Tuvalu","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96580,798,"TUV","Tuvalu","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96581,798,"TUV","Tuvalu","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96582,798,"TUV","Tuvalu","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96583,798,"TUV","Tuvalu","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96584,798,"TUV","Tuvalu","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96585,798,"TUV","Tuvalu","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96586,798,"TUV","Tuvalu","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96587,798,"TUV","Tuvalu","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96588,798,"TUV","Tuvalu","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96589,798,"TUV","Tuvalu","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96590,798,"TUV","Tuvalu","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96591,798,"TUV","Tuvalu","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96592,798,"TUV","Tuvalu","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96593,798,"TUV","Tuvalu","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96594,798,"TUV","Tuvalu","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96595,798,"TUV","Tuvalu","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96596,798,"TUV","Tuvalu","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96597,798,"TUV","Tuvalu","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96598,798,"TUV","Tuvalu","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96599,798,"TUV","Tuvalu","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96600,798,"TUV","Tuvalu","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96601,798,"TUV","Tuvalu","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96602,798,"TUV","Tuvalu","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96603,798,"TUV","Tuvalu","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96604,798,"TUV","Tuvalu","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96605,798,"TUV","Tuvalu","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96606,798,"TUV","Tuvalu","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96607,798,"TUV","Tuvalu","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96608,798,"TUV","Tuvalu","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96609,798,"TUV","Tuvalu","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96610,798,"TUV","Tuvalu","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96611,798,"TUV","Tuvalu","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96612,798,"TUV","Tuvalu","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96613,798,"TUV","Tuvalu","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TUV/tuv_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96614,800,"UGA","Uganda","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96615,800,"UGA","Uganda","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96616,800,"UGA","Uganda","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96617,800,"UGA","Uganda","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96618,800,"UGA","Uganda","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96619,800,"UGA","Uganda","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96620,800,"UGA","Uganda","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96621,800,"UGA","Uganda","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96622,800,"UGA","Uganda","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96623,800,"UGA","Uganda","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96624,800,"UGA","Uganda","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96625,800,"UGA","Uganda","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96626,800,"UGA","Uganda","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96627,800,"UGA","Uganda","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96628,800,"UGA","Uganda","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96629,800,"UGA","Uganda","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96630,800,"UGA","Uganda","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96631,800,"UGA","Uganda","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96632,800,"UGA","Uganda","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96633,800,"UGA","Uganda","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96634,800,"UGA","Uganda","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96635,800,"UGA","Uganda","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96636,800,"UGA","Uganda","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96637,800,"UGA","Uganda","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96638,800,"UGA","Uganda","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96639,800,"UGA","Uganda","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96640,800,"UGA","Uganda","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96641,800,"UGA","Uganda","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96642,800,"UGA","Uganda","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96643,800,"UGA","Uganda","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96644,800,"UGA","Uganda","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96645,800,"UGA","Uganda","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96646,800,"UGA","Uganda","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96647,800,"UGA","Uganda","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96648,800,"UGA","Uganda","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96649,800,"UGA","Uganda","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UGA/uga_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96650,804,"UKR","Ukraine","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96651,804,"UKR","Ukraine","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96652,804,"UKR","Ukraine","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96653,804,"UKR","Ukraine","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96654,804,"UKR","Ukraine","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96655,804,"UKR","Ukraine","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96656,804,"UKR","Ukraine","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96657,804,"UKR","Ukraine","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96658,804,"UKR","Ukraine","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96659,804,"UKR","Ukraine","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96660,804,"UKR","Ukraine","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96661,804,"UKR","Ukraine","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96662,804,"UKR","Ukraine","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96663,804,"UKR","Ukraine","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96664,804,"UKR","Ukraine","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96665,804,"UKR","Ukraine","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96666,804,"UKR","Ukraine","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96667,804,"UKR","Ukraine","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96668,804,"UKR","Ukraine","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96669,804,"UKR","Ukraine","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96670,804,"UKR","Ukraine","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96671,804,"UKR","Ukraine","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96672,804,"UKR","Ukraine","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96673,804,"UKR","Ukraine","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96674,804,"UKR","Ukraine","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96675,804,"UKR","Ukraine","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96676,804,"UKR","Ukraine","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96677,804,"UKR","Ukraine","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96678,804,"UKR","Ukraine","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96679,804,"UKR","Ukraine","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96680,804,"UKR","Ukraine","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96681,804,"UKR","Ukraine","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96682,804,"UKR","Ukraine","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96683,804,"UKR","Ukraine","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96684,804,"UKR","Ukraine","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96685,804,"UKR","Ukraine","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UKR/ukr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96686,807,"MKD","Macedonia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96687,807,"MKD","Macedonia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96688,807,"MKD","Macedonia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96689,807,"MKD","Macedonia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96690,807,"MKD","Macedonia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96691,807,"MKD","Macedonia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96692,807,"MKD","Macedonia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96693,807,"MKD","Macedonia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96694,807,"MKD","Macedonia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96695,807,"MKD","Macedonia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96696,807,"MKD","Macedonia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96697,807,"MKD","Macedonia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96698,807,"MKD","Macedonia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96699,807,"MKD","Macedonia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96700,807,"MKD","Macedonia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96701,807,"MKD","Macedonia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96702,807,"MKD","Macedonia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96703,807,"MKD","Macedonia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96704,807,"MKD","Macedonia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96705,807,"MKD","Macedonia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96706,807,"MKD","Macedonia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96707,807,"MKD","Macedonia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96708,807,"MKD","Macedonia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96709,807,"MKD","Macedonia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96710,807,"MKD","Macedonia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96711,807,"MKD","Macedonia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96712,807,"MKD","Macedonia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96713,807,"MKD","Macedonia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96714,807,"MKD","Macedonia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96715,807,"MKD","Macedonia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96716,807,"MKD","Macedonia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96717,807,"MKD","Macedonia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96718,807,"MKD","Macedonia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96719,807,"MKD","Macedonia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96720,807,"MKD","Macedonia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96721,807,"MKD","Macedonia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/MKD/mkd_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96722,818,"EGY","Egypt","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96723,818,"EGY","Egypt","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96724,818,"EGY","Egypt","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96725,818,"EGY","Egypt","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96726,818,"EGY","Egypt","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96727,818,"EGY","Egypt","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96728,818,"EGY","Egypt","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96729,818,"EGY","Egypt","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96730,818,"EGY","Egypt","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96731,818,"EGY","Egypt","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96732,818,"EGY","Egypt","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96733,818,"EGY","Egypt","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96734,818,"EGY","Egypt","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96735,818,"EGY","Egypt","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96736,818,"EGY","Egypt","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96737,818,"EGY","Egypt","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96738,818,"EGY","Egypt","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96739,818,"EGY","Egypt","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96740,818,"EGY","Egypt","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96741,818,"EGY","Egypt","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96742,818,"EGY","Egypt","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96743,818,"EGY","Egypt","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96744,818,"EGY","Egypt","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96745,818,"EGY","Egypt","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96746,818,"EGY","Egypt","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96747,818,"EGY","Egypt","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96748,818,"EGY","Egypt","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96749,818,"EGY","Egypt","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96750,818,"EGY","Egypt","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96751,818,"EGY","Egypt","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96752,818,"EGY","Egypt","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96753,818,"EGY","Egypt","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96754,818,"EGY","Egypt","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96755,818,"EGY","Egypt","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96756,818,"EGY","Egypt","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96757,818,"EGY","Egypt","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/EGY/egy_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96758,826,"GBR","United Kingdom","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96759,826,"GBR","United Kingdom","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96760,826,"GBR","United Kingdom","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96761,826,"GBR","United Kingdom","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96762,826,"GBR","United Kingdom","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96763,826,"GBR","United Kingdom","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96764,826,"GBR","United Kingdom","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96765,826,"GBR","United Kingdom","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96766,826,"GBR","United Kingdom","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96767,826,"GBR","United Kingdom","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96768,826,"GBR","United Kingdom","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96769,826,"GBR","United Kingdom","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96770,826,"GBR","United Kingdom","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96771,826,"GBR","United Kingdom","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96772,826,"GBR","United Kingdom","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96773,826,"GBR","United Kingdom","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96774,826,"GBR","United Kingdom","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96775,826,"GBR","United Kingdom","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96776,826,"GBR","United Kingdom","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96777,826,"GBR","United Kingdom","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96778,826,"GBR","United Kingdom","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96779,826,"GBR","United Kingdom","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96780,826,"GBR","United Kingdom","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96781,826,"GBR","United Kingdom","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96782,826,"GBR","United Kingdom","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96783,826,"GBR","United Kingdom","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96784,826,"GBR","United Kingdom","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96785,826,"GBR","United Kingdom","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96786,826,"GBR","United Kingdom","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96787,826,"GBR","United Kingdom","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96788,826,"GBR","United Kingdom","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96789,826,"GBR","United Kingdom","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96790,826,"GBR","United Kingdom","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96791,826,"GBR","United Kingdom","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96792,826,"GBR","United Kingdom","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96793,826,"GBR","United Kingdom","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GBR/gbr_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96794,831,"GGY","Guernsey","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96795,831,"GGY","Guernsey","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96796,831,"GGY","Guernsey","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96797,831,"GGY","Guernsey","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96798,831,"GGY","Guernsey","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96799,831,"GGY","Guernsey","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96800,831,"GGY","Guernsey","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96801,831,"GGY","Guernsey","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96802,831,"GGY","Guernsey","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96803,831,"GGY","Guernsey","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96804,831,"GGY","Guernsey","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96805,831,"GGY","Guernsey","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96806,831,"GGY","Guernsey","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96807,831,"GGY","Guernsey","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96808,831,"GGY","Guernsey","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96809,831,"GGY","Guernsey","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96810,831,"GGY","Guernsey","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96811,831,"GGY","Guernsey","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96812,831,"GGY","Guernsey","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96813,831,"GGY","Guernsey","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96814,831,"GGY","Guernsey","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96815,831,"GGY","Guernsey","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96816,831,"GGY","Guernsey","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96817,831,"GGY","Guernsey","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96818,831,"GGY","Guernsey","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96819,831,"GGY","Guernsey","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96820,831,"GGY","Guernsey","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96821,831,"GGY","Guernsey","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96822,831,"GGY","Guernsey","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96823,831,"GGY","Guernsey","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96824,831,"GGY","Guernsey","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96825,831,"GGY","Guernsey","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96826,831,"GGY","Guernsey","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96827,831,"GGY","Guernsey","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96828,831,"GGY","Guernsey","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96829,831,"GGY","Guernsey","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/GGY/ggy_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96830,832,"JEY","Jersey","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96831,832,"JEY","Jersey","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96832,832,"JEY","Jersey","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96833,832,"JEY","Jersey","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96834,832,"JEY","Jersey","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96835,832,"JEY","Jersey","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96836,832,"JEY","Jersey","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96837,832,"JEY","Jersey","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96838,832,"JEY","Jersey","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96839,832,"JEY","Jersey","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96840,832,"JEY","Jersey","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96841,832,"JEY","Jersey","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96842,832,"JEY","Jersey","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96843,832,"JEY","Jersey","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96844,832,"JEY","Jersey","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96845,832,"JEY","Jersey","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96846,832,"JEY","Jersey","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96847,832,"JEY","Jersey","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96848,832,"JEY","Jersey","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96849,832,"JEY","Jersey","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96850,832,"JEY","Jersey","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96851,832,"JEY","Jersey","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96852,832,"JEY","Jersey","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96853,832,"JEY","Jersey","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96854,832,"JEY","Jersey","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96855,832,"JEY","Jersey","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96856,832,"JEY","Jersey","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96857,832,"JEY","Jersey","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96858,832,"JEY","Jersey","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96859,832,"JEY","Jersey","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96860,832,"JEY","Jersey","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96861,832,"JEY","Jersey","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96862,832,"JEY","Jersey","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96863,832,"JEY","Jersey","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96864,832,"JEY","Jersey","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96865,832,"JEY","Jersey","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/JEY/jey_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96866,833,"IMN","Isle of Man","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96867,833,"IMN","Isle of Man","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96868,833,"IMN","Isle of Man","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96869,833,"IMN","Isle of Man","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96870,833,"IMN","Isle of Man","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96871,833,"IMN","Isle of Man","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96872,833,"IMN","Isle of Man","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96873,833,"IMN","Isle of Man","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96874,833,"IMN","Isle of Man","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96875,833,"IMN","Isle of Man","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96876,833,"IMN","Isle of Man","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96877,833,"IMN","Isle of Man","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96878,833,"IMN","Isle of Man","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96879,833,"IMN","Isle of Man","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96880,833,"IMN","Isle of Man","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96881,833,"IMN","Isle of Man","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96882,833,"IMN","Isle of Man","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96883,833,"IMN","Isle of Man","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96884,833,"IMN","Isle of Man","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96885,833,"IMN","Isle of Man","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96886,833,"IMN","Isle of Man","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96887,833,"IMN","Isle of Man","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96888,833,"IMN","Isle of Man","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96889,833,"IMN","Isle of Man","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96890,833,"IMN","Isle of Man","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96891,833,"IMN","Isle of Man","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96892,833,"IMN","Isle of Man","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96893,833,"IMN","Isle of Man","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96894,833,"IMN","Isle of Man","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96895,833,"IMN","Isle of Man","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96896,833,"IMN","Isle of Man","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96897,833,"IMN","Isle of Man","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96898,833,"IMN","Isle of Man","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96899,833,"IMN","Isle of Man","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96900,833,"IMN","Isle of Man","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96901,833,"IMN","Isle of Man","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/IMN/imn_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96902,834,"TZA","Tanzania","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96903,834,"TZA","Tanzania","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96904,834,"TZA","Tanzania","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96905,834,"TZA","Tanzania","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96906,834,"TZA","Tanzania","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96907,834,"TZA","Tanzania","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96908,834,"TZA","Tanzania","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96909,834,"TZA","Tanzania","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96910,834,"TZA","Tanzania","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96911,834,"TZA","Tanzania","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96912,834,"TZA","Tanzania","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96913,834,"TZA","Tanzania","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96914,834,"TZA","Tanzania","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96915,834,"TZA","Tanzania","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96916,834,"TZA","Tanzania","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96917,834,"TZA","Tanzania","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96918,834,"TZA","Tanzania","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96919,834,"TZA","Tanzania","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96920,834,"TZA","Tanzania","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96921,834,"TZA","Tanzania","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96922,834,"TZA","Tanzania","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96923,834,"TZA","Tanzania","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96924,834,"TZA","Tanzania","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96925,834,"TZA","Tanzania","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96926,834,"TZA","Tanzania","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96927,834,"TZA","Tanzania","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96928,834,"TZA","Tanzania","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96929,834,"TZA","Tanzania","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96930,834,"TZA","Tanzania","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96931,834,"TZA","Tanzania","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96932,834,"TZA","Tanzania","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96933,834,"TZA","Tanzania","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96934,834,"TZA","Tanzania","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96935,834,"TZA","Tanzania","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96936,834,"TZA","Tanzania","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96937,834,"TZA","Tanzania","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/TZA/tza_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96938,854,"BFA","Burkina Faso","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96939,854,"BFA","Burkina Faso","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96940,854,"BFA","Burkina Faso","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96941,854,"BFA","Burkina Faso","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96942,854,"BFA","Burkina Faso","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96943,854,"BFA","Burkina Faso","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96944,854,"BFA","Burkina Faso","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96945,854,"BFA","Burkina Faso","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96946,854,"BFA","Burkina Faso","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96947,854,"BFA","Burkina Faso","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96948,854,"BFA","Burkina Faso","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96949,854,"BFA","Burkina Faso","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96950,854,"BFA","Burkina Faso","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96951,854,"BFA","Burkina Faso","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96952,854,"BFA","Burkina Faso","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96953,854,"BFA","Burkina Faso","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96954,854,"BFA","Burkina Faso","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96955,854,"BFA","Burkina Faso","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96956,854,"BFA","Burkina Faso","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96957,854,"BFA","Burkina Faso","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96958,854,"BFA","Burkina Faso","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96959,854,"BFA","Burkina Faso","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96960,854,"BFA","Burkina Faso","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96961,854,"BFA","Burkina Faso","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96962,854,"BFA","Burkina Faso","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96963,854,"BFA","Burkina Faso","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96964,854,"BFA","Burkina Faso","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96965,854,"BFA","Burkina Faso","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96966,854,"BFA","Burkina Faso","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96967,854,"BFA","Burkina Faso","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96968,854,"BFA","Burkina Faso","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96969,854,"BFA","Burkina Faso","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96970,854,"BFA","Burkina Faso","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96971,854,"BFA","Burkina Faso","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96972,854,"BFA","Burkina Faso","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96973,854,"BFA","Burkina Faso","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/BFA/bfa_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
96974,858,"URY","Uruguay","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96975,858,"URY","Uruguay","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96976,858,"URY","Uruguay","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96977,858,"URY","Uruguay","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96978,858,"URY","Uruguay","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96979,858,"URY","Uruguay","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96980,858,"URY","Uruguay","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96981,858,"URY","Uruguay","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96982,858,"URY","Uruguay","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96983,858,"URY","Uruguay","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96984,858,"URY","Uruguay","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96985,858,"URY","Uruguay","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96986,858,"URY","Uruguay","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96987,858,"URY","Uruguay","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96988,858,"URY","Uruguay","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96989,858,"URY","Uruguay","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96990,858,"URY","Uruguay","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96991,858,"URY","Uruguay","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96992,858,"URY","Uruguay","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96993,858,"URY","Uruguay","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96994,858,"URY","Uruguay","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96995,858,"URY","Uruguay","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96996,858,"URY","Uruguay","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96997,858,"URY","Uruguay","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96998,858,"URY","Uruguay","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
96999,858,"URY","Uruguay","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97000,858,"URY","Uruguay","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97001,858,"URY","Uruguay","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97002,858,"URY","Uruguay","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97003,858,"URY","Uruguay","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97004,858,"URY","Uruguay","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97005,858,"URY","Uruguay","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97006,858,"URY","Uruguay","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97007,858,"URY","Uruguay","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97008,858,"URY","Uruguay","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97009,858,"URY","Uruguay","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/URY/ury_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97010,860,"UZB","Uzbekistan","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97011,860,"UZB","Uzbekistan","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97012,860,"UZB","Uzbekistan","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97013,860,"UZB","Uzbekistan","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97014,860,"UZB","Uzbekistan","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97015,860,"UZB","Uzbekistan","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97016,860,"UZB","Uzbekistan","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97017,860,"UZB","Uzbekistan","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97018,860,"UZB","Uzbekistan","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97019,860,"UZB","Uzbekistan","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97020,860,"UZB","Uzbekistan","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97021,860,"UZB","Uzbekistan","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97022,860,"UZB","Uzbekistan","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97023,860,"UZB","Uzbekistan","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97024,860,"UZB","Uzbekistan","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97025,860,"UZB","Uzbekistan","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97026,860,"UZB","Uzbekistan","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97027,860,"UZB","Uzbekistan","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97028,860,"UZB","Uzbekistan","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97029,860,"UZB","Uzbekistan","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97030,860,"UZB","Uzbekistan","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97031,860,"UZB","Uzbekistan","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97032,860,"UZB","Uzbekistan","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97033,860,"UZB","Uzbekistan","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97034,860,"UZB","Uzbekistan","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97035,860,"UZB","Uzbekistan","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97036,860,"UZB","Uzbekistan","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97037,860,"UZB","Uzbekistan","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97038,860,"UZB","Uzbekistan","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97039,860,"UZB","Uzbekistan","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97040,860,"UZB","Uzbekistan","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97041,860,"UZB","Uzbekistan","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97042,860,"UZB","Uzbekistan","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97043,860,"UZB","Uzbekistan","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97044,860,"UZB","Uzbekistan","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97045,860,"UZB","Uzbekistan","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/UZB/uzb_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97046,862,"VEN","Venezuela","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97047,862,"VEN","Venezuela","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97048,862,"VEN","Venezuela","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97049,862,"VEN","Venezuela","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97050,862,"VEN","Venezuela","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97051,862,"VEN","Venezuela","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97052,862,"VEN","Venezuela","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97053,862,"VEN","Venezuela","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97054,862,"VEN","Venezuela","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97055,862,"VEN","Venezuela","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97056,862,"VEN","Venezuela","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97057,862,"VEN","Venezuela","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97058,862,"VEN","Venezuela","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97059,862,"VEN","Venezuela","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97060,862,"VEN","Venezuela","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97061,862,"VEN","Venezuela","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97062,862,"VEN","Venezuela","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97063,862,"VEN","Venezuela","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97064,862,"VEN","Venezuela","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97065,862,"VEN","Venezuela","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97066,862,"VEN","Venezuela","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97067,862,"VEN","Venezuela","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97068,862,"VEN","Venezuela","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97069,862,"VEN","Venezuela","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97070,862,"VEN","Venezuela","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97071,862,"VEN","Venezuela","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97072,862,"VEN","Venezuela","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97073,862,"VEN","Venezuela","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97074,862,"VEN","Venezuela","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97075,862,"VEN","Venezuela","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97076,862,"VEN","Venezuela","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97077,862,"VEN","Venezuela","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97078,862,"VEN","Venezuela","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97079,862,"VEN","Venezuela","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97080,862,"VEN","Venezuela","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97081,862,"VEN","Venezuela","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/VEN/ven_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97082,876,"WLF","Wallis and Futuna","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97083,876,"WLF","Wallis and Futuna","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97084,876,"WLF","Wallis and Futuna","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97085,876,"WLF","Wallis and Futuna","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97086,876,"WLF","Wallis and Futuna","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97087,876,"WLF","Wallis and Futuna","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97088,876,"WLF","Wallis and Futuna","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97089,876,"WLF","Wallis and Futuna","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97090,876,"WLF","Wallis and Futuna","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97091,876,"WLF","Wallis and Futuna","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97092,876,"WLF","Wallis and Futuna","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97093,876,"WLF","Wallis and Futuna","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97094,876,"WLF","Wallis and Futuna","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97095,876,"WLF","Wallis and Futuna","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97096,876,"WLF","Wallis and Futuna","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97097,876,"WLF","Wallis and Futuna","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97098,876,"WLF","Wallis and Futuna","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97099,876,"WLF","Wallis and Futuna","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97100,876,"WLF","Wallis and Futuna","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97101,876,"WLF","Wallis and Futuna","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97102,876,"WLF","Wallis and Futuna","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97103,876,"WLF","Wallis and Futuna","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97104,876,"WLF","Wallis and Futuna","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97105,876,"WLF","Wallis and Futuna","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97106,876,"WLF","Wallis and Futuna","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97107,876,"WLF","Wallis and Futuna","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97108,876,"WLF","Wallis and Futuna","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97109,876,"WLF","Wallis and Futuna","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97110,876,"WLF","Wallis and Futuna","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97111,876,"WLF","Wallis and Futuna","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97112,876,"WLF","Wallis and Futuna","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97113,876,"WLF","Wallis and Futuna","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97114,876,"WLF","Wallis and Futuna","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97115,876,"WLF","Wallis and Futuna","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97116,876,"WLF","Wallis and Futuna","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97117,876,"WLF","Wallis and Futuna","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WLF/wlf_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97118,882,"WSM","Samoa","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97119,882,"WSM","Samoa","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97120,882,"WSM","Samoa","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97121,882,"WSM","Samoa","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97122,882,"WSM","Samoa","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97123,882,"WSM","Samoa","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97124,882,"WSM","Samoa","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97125,882,"WSM","Samoa","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97126,882,"WSM","Samoa","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97127,882,"WSM","Samoa","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97128,882,"WSM","Samoa","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97129,882,"WSM","Samoa","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97130,882,"WSM","Samoa","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97131,882,"WSM","Samoa","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97132,882,"WSM","Samoa","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97133,882,"WSM","Samoa","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97134,882,"WSM","Samoa","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97135,882,"WSM","Samoa","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97136,882,"WSM","Samoa","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97137,882,"WSM","Samoa","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97138,882,"WSM","Samoa","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97139,882,"WSM","Samoa","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97140,882,"WSM","Samoa","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97141,882,"WSM","Samoa","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97142,882,"WSM","Samoa","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97143,882,"WSM","Samoa","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97144,882,"WSM","Samoa","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97145,882,"WSM","Samoa","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97146,882,"WSM","Samoa","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97147,882,"WSM","Samoa","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97148,882,"WSM","Samoa","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97149,882,"WSM","Samoa","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97150,882,"WSM","Samoa","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97151,882,"WSM","Samoa","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97152,882,"WSM","Samoa","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97153,882,"WSM","Samoa","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/WSM/wsm_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97154,887,"YEM","Yemen","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97155,887,"YEM","Yemen","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97156,887,"YEM","Yemen","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97157,887,"YEM","Yemen","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97158,887,"YEM","Yemen","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97159,887,"YEM","Yemen","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97160,887,"YEM","Yemen","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97161,887,"YEM","Yemen","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97162,887,"YEM","Yemen","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97163,887,"YEM","Yemen","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97164,887,"YEM","Yemen","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97165,887,"YEM","Yemen","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97166,887,"YEM","Yemen","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97167,887,"YEM","Yemen","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97168,887,"YEM","Yemen","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97169,887,"YEM","Yemen","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97170,887,"YEM","Yemen","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97171,887,"YEM","Yemen","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97172,887,"YEM","Yemen","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97173,887,"YEM","Yemen","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97174,887,"YEM","Yemen","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97175,887,"YEM","Yemen","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97176,887,"YEM","Yemen","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97177,887,"YEM","Yemen","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97178,887,"YEM","Yemen","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97179,887,"YEM","Yemen","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97180,887,"YEM","Yemen","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97181,887,"YEM","Yemen","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97182,887,"YEM","Yemen","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97183,887,"YEM","Yemen","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97184,887,"YEM","Yemen","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97185,887,"YEM","Yemen","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97186,887,"YEM","Yemen","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97187,887,"YEM","Yemen","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97188,887,"YEM","Yemen","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97189,887,"YEM","Yemen","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/YEM/yem_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97190,894,"ZMB","Zambia","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97191,894,"ZMB","Zambia","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97192,894,"ZMB","Zambia","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97193,894,"ZMB","Zambia","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97194,894,"ZMB","Zambia","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97195,894,"ZMB","Zambia","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97196,894,"ZMB","Zambia","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97197,894,"ZMB","Zambia","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97198,894,"ZMB","Zambia","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97199,894,"ZMB","Zambia","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97200,894,"ZMB","Zambia","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97201,894,"ZMB","Zambia","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97202,894,"ZMB","Zambia","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97203,894,"ZMB","Zambia","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97204,894,"ZMB","Zambia","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97205,894,"ZMB","Zambia","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97206,894,"ZMB","Zambia","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97207,894,"ZMB","Zambia","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97208,894,"ZMB","Zambia","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97209,894,"ZMB","Zambia","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97210,894,"ZMB","Zambia","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97211,894,"ZMB","Zambia","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97212,894,"ZMB","Zambia","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97213,894,"ZMB","Zambia","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97214,894,"ZMB","Zambia","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97215,894,"ZMB","Zambia","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97216,894,"ZMB","Zambia","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97217,894,"ZMB","Zambia","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97218,894,"ZMB","Zambia","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97219,894,"ZMB","Zambia","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97220,894,"ZMB","Zambia","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97221,894,"ZMB","Zambia","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97222,894,"ZMB","Zambia","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97223,894,"ZMB","Zambia","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97224,894,"ZMB","Zambia","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97225,894,"ZMB","Zambia","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/ZMB/zmb_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on building footprints provided by the Digitize Africa project of Ecopia.AI and Maxar Technologies (2020)"
97226,900,"KOS","Kosovo","agesex_f_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_0_2020_constrained_UNadj.tif","Estimated 0-12 month old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97227,900,"KOS","Kosovo","agesex_f_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_1_2020_constrained_UNadj.tif","Estimated 1-4 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97228,900,"KOS","Kosovo","agesex_f_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_5_2020_constrained_UNadj.tif","Estimated 5-8 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97229,900,"KOS","Kosovo","agesex_f_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_10_2020_constrained_UNadj.tif","Estimated 10-14 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97230,900,"KOS","Kosovo","agesex_f_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_15_2020_constrained_UNadj.tif","Estimated 15-19 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97231,900,"KOS","Kosovo","agesex_f_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_20_2020_constrained_UNadj.tif","Estimated 20-24 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97232,900,"KOS","Kosovo","agesex_f_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_25_2020_constrained_UNadj.tif","Estimated 25-29 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97233,900,"KOS","Kosovo","agesex_f_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_30_2020_constrained_UNadj.tif","Estimated 30-34 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97234,900,"KOS","Kosovo","agesex_f_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_35_2020_constrained_UNadj.tif","Estimated 35-39 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97235,900,"KOS","Kosovo","agesex_f_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_40_2020_constrained_UNadj.tif","Estimated 40-44 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97236,900,"KOS","Kosovo","agesex_f_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_45_2020_constrained_UNadj.tif","Estimated 45-49 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97237,900,"KOS","Kosovo","agesex_f_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_50_2020_constrained_UNadj.tif","Estimated 50-54 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97238,900,"KOS","Kosovo","agesex_f_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_55_2020_constrained_UNadj.tif","Estimated 55-59 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97239,900,"KOS","Kosovo","agesex_f_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_60_2020_constrained_UNadj.tif","Estimated 60-64 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97240,900,"KOS","Kosovo","agesex_f_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_65_2020_constrained_UNadj.tif","Estimated 65-69 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97241,900,"KOS","Kosovo","agesex_f_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_70_2020_constrained_UNadj.tif","Estimated 70-74 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97242,900,"KOS","Kosovo","agesex_f_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_75_2020_constrained_UNadj.tif","Estimated 75-79 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97243,900,"KOS","Kosovo","agesex_f_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_f_80_2020_constrained_UNadj.tif","Estimated 80 year old female per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97244,900,"KOS","Kosovo","agesex_m_0_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_0_2020_constrained_UNadj.tif","Estimated 0-12 month old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97245,900,"KOS","Kosovo","agesex_m_1_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_1_2020_constrained_UNadj.tif","Estimated 1-4 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97246,900,"KOS","Kosovo","agesex_m_5_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_5_2020_constrained_UNadj.tif","Estimated 5-8 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97247,900,"KOS","Kosovo","agesex_m_10_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_10_2020_constrained_UNadj.tif","Estimated 10-14 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97248,900,"KOS","Kosovo","agesex_m_15_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_15_2020_constrained_UNadj.tif","Estimated 15-19 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97249,900,"KOS","Kosovo","agesex_m_20_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_20_2020_constrained_UNadj.tif","Estimated 20-24 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97250,900,"KOS","Kosovo","agesex_m_25_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_25_2020_constrained_UNadj.tif","Estimated 25-29 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97251,900,"KOS","Kosovo","agesex_m_30_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_30_2020_constrained_UNadj.tif","Estimated 30-34 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97252,900,"KOS","Kosovo","agesex_m_35_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_35_2020_constrained_UNadj.tif","Estimated 35-39 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97253,900,"KOS","Kosovo","agesex_m_40_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_40_2020_constrained_UNadj.tif","Estimated 40-44 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97254,900,"KOS","Kosovo","agesex_m_45_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_45_2020_constrained_UNadj.tif","Estimated 45-49 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97255,900,"KOS","Kosovo","agesex_m_50_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_50_2020_constrained_UNadj.tif","Estimated 50-54 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97256,900,"KOS","Kosovo","agesex_m_55_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_55_2020_constrained_UNadj.tif","Estimated 55-59 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97257,900,"KOS","Kosovo","agesex_m_60_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_60_2020_constrained_UNadj.tif","Estimated 60-64 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97258,900,"KOS","Kosovo","agesex_m_65_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_65_2020_constrained_UNadj.tif","Estimated 65-69 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97259,900,"KOS","Kosovo","agesex_m_70_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_70_2020_constrained_UNadj.tif","Estimated 70-74 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97260,900,"KOS","Kosovo","agesex_m_75_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_75_2020_constrained_UNadj.tif","Estimated 75-79 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"
97261,900,"KOS","Kosovo","agesex_m_80_2020_constrained_UNadj","GIS/AgeSex_structures/Global_2000_2020_Constrained_UNadj/2020/KOS/kos_m_80_2020_constrained_UNadj.tif","Estimated 80 year old male per grid-cell  in 2020.  with country total adjusted to match the corresponding UNPD estimate. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). NoData values represent areas that were mapped as unsettled based on the outputs of the Built-Settlement Growth Model (BSGM) developed by Jeremiah J.Nieves et al. 2020"